publications | Michael E. Papka

2024

Andrew E. Johnson, Luc Renambot, G. Elisabeta Marai, Daria Tsoupikova, Michael E. Papka, Lance Long, Dana Plepys, Jonas Talandis, Maxine D. Brown, Jason Leigh, Daniel J. Sandin, and Thomas A. DeFanti, Electronic Visualization Laboratory’s 50th Anniversary Retrospective: Look to the Future, Build on the Past, PRESENCE: Virtual and Augmented Reality,Apr, 2024
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September 2023 marks the 50th anniversary of the Electronic Visualization Laboratory (EVL) at University of Illinois Chicago (UIC). EVL’s introduction of the CAVE Automatic Virtual Environment in 1992, the first widely replicated, projection-based, walk-in, virtual reality (VR) system in the world, put EVL at the forefront of collaborative, immersive data exploration and analytics. However, the journey did not begin then. Since its founding in 1973, EVL has been developing tools and techniques for real-time, interactive visualizations—pillars of VR. But EVL’s culture is also relevant to its successes, as it has always been an interdisciplinary lab that fosters teamwork, where each person’s expertise contributes to the development of the necessary tools, hardware, system software, applications, and human interface models to solve problems. Over the years, as multidisciplinary collaborations evolved and advanced scientific instruments and data resources were distributed globally, the need to access and share data and visualizations while working with colleagues, local and remote, synchronous and asynchronous, also became important fields of study. This paper is a retrospective of EVL’s past 50 years that surveys the many networked, immersive, collaborative visualization and VR systems and applications it developed and deployed, as well as lessons learned and future plans.

2023

Maxim Zvyagin, Alexander Brace, Kyle Hippe, Yuntian Deng, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael Irvin, Defne G. Ozgulbas, Natalia Vassilieva, James Gregory Pauloski, Logan Ward, Valerie Hayot-Sasson, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian Foster, James J. Davis, Michael E. Papka, Thomas Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, and Arvind Ramanathan, GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics, The International Journal of High Performance Computing Applications, 2023
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We seek to transform how new and emergent variants of pandemic-causing viruses, specifically SARS-CoV-2, are identified and classified. By adapting large language models (LLMs) for genomic data, we build genome-scale language models (GenSLMs) which can learn the evolutionary landscape of SARS-CoV-2 genomes. By pre-training on over 110 million prokaryotic gene sequences and fine-tuning a SARS-CoV-2-specific model on 1.5 million genomes, we show that GenSLMs can accurately and rapidly identify variants of concern. Thus, to our knowledge, GenSLMs represents one of the first whole-genome scale foundation models which can generalize to other prediction tasks. We demonstrate scaling of GenSLMs on GPU-based supercomputers and AI-hardware accelerators utilizing 1.63 Zettaflops in training runs with a sustained performance of 121 PFLOPS in mixed precision and peak of 850 PFLOPS. We present initial scientific insights from examining GenSLMs in tracking evolutionary dynamics of SARS-CoV-2, paving the path to realizing this on large biological data.
@article{ZvBrHi23, author = {Zvyagin, Maxim and Brace, Alexander and Hippe, Kyle and Deng, Yuntian and Zhang, Bin and Bohorquez, Cindy Orozco and Clyde, Austin and Kale, Bharat and Perez-Rivera, Danilo and Ma, Heng and Mann, Carla M. and Irvin, Michael and Ozgulbas, Defne G. and Vassilieva, Natalia and Pauloski, James Gregory and Ward, Logan and Hayot-Sasson, Valerie and Emani, Murali and Foreman, Sam and Xie, Zhen and Lin, Diangen and Shukla, Maulik and Nie, Weili and Romero, Josh and Dallago, Christian and Vahdat, Arash and Xiao, Chaowei and Gibbs, Thomas and Foster, Ian and Davis, James J. and Papka, Michael E. and Brettin, Thomas and Stevens, Rick and Anandkumar, Anima and Vishwanath, Venkatram and Ramanathan, Arvind}, title = {GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics}, journal = {The International Journal of High Performance Computing Applications}, volume = {37}, number = {6}, pages = {683-705}, year = {2023}, doi = {10.1177/10943420231201154}, url = {https://doi.org/10.1177/10943420231201154}, eprint = {https://doi.org/10.1177/10943420231201154}, }

Boyang Li, Zhiling Lan, and Michael E. Papka, Interpretable Modeling of Deep Reinforcement Learning Driven Scheduling, In 2023 31st International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), 2023

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@inproceedings{LiLaPa23,
  author = {Li, Boyang and Lan, Zhiling and Papka, Michael E.},
  booktitle = {2023 31st International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)},
  title = {Interpretable Modeling of Deep Reinforcement Learning Driven Scheduling},
  year = {2023},
  pages = {1-8},
  keywords = {Deep learning;Processor scheduling;Computational modeling;Closed box;Optimization methods;Reinforcement learning;Artificial neural networks;cluster scheduling;deep reinforcement learning;high-performance computing;interpretation;decision tree},
  doi = {10.1109/MASCOTS59514.2023.10387651}
}

Victor A. Mateevitsi, Mathis Bode, Nicola Ferrier, Paul Fischer, Jens Henrik Göbbert, Joseph A. Insley, Yu-Hsiang Lan, Misun Min, Michael E. Papka, Saumil Patel, Silvio Rizzi, and Jonathan Windgassen, Scaling Computational Fluid Dynamics: In Situ Visualization of NekRS Using SENSEI, In Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, 2023
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In the realm of Computational Fluid Dynamics (CFD), the demand for memory and computation resources is extreme, necessitating the use of leadership-scale computing platforms for practical domain sizes. This intensive requirement renders traditional checkpointing methods ineffective due to the significant slowdown in simulations while saving state data to disk. As we progress towards exascale and GPU-driven High-Performance Computing (HPC) and confront larger problem sizes, the choice becomes increasingly stark: to compromise data fidelity or to reduce resolution. To navigate this challenge, this study advocates for the use of in situ analysis and visualization techniques. These allow more frequent data "snapshots" to be taken directly from memory, thus avoiding the need for disruptive checkpointing. We detail our approach of instrumenting NekRS, a GPU-focused thermal-fluid simulation code employing the spectral element method (SEM), and describe varied in situ and in transit strategies for data rendering. Additionally, we provide concrete scientific use-cases and report on runs performed on Polaris, Argonne Leadership Computing Facility’s (ALCF) 44 Petaflop supercomputer and Jülich Wizard for European Leadership Science (JUWELS) Booster, Jülich Supercomputing Centre’s (JSC) 71 Petaflop High Performance Computing (HPC) system, offering practical insight into the implications of our methodology.
@inproceedings{MaBoFe23, author = {Mateevitsi, Victor A. and Bode, Mathis and Ferrier, Nicola and Fischer, Paul and G\"{o}bbert, Jens Henrik and Insley, Joseph A. and Lan, Yu-Hsiang and Min, Misun and Papka, Michael E. and Patel, Saumil and Rizzi, Silvio and Windgassen, Jonathan}, title = {Scaling Computational Fluid Dynamics: In Situ Visualization of NekRS Using SENSEI}, year = {2023}, isbn = {9798400707858}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3624062.3624159}, doi = {10.1145/3624062.3624159}, booktitle = {Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis}, pages = {862–867}, numpages = {6}, location = {Denver, CO, USA}, series = {SC-W '23}, dimensions = {true} }
Qi Wu, Joseph A. Insley, Victor A. Mateevitsi, Silvio Rizzi, Michael E. Papka, and Kwan-Liu Ma, Distributed Neural Representation for Reactive in situ Visualization, 2023
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In situ visualization and steering of computational modeling can be effectively achieved using reactive programming, which leverages temporal abstraction and data caching mechanisms to create dynamic workflows. However, implementing a temporal cache for large-scale simulations can be challenging. Implicit neural networks have proven effective in compressing large volume data. However, their application to distributed data has yet to be fully explored. In this work, we develop an implicit neural representation for distributed volume data and incorporate it into the DIVA reactive programming system. This implementation enables us to build an in situ temporal caching system with a capacity 100 times larger than previously achieved. We integrate our implementation into the Ascent infrastructure and evaluate its performance using real-world simulations.
@misc{WuInMa23, title = {Distributed Neural Representation for Reactive in situ Visualization}, author = {Wu, Qi and Insley, Joseph A. and Mateevitsi, Victor A. and Rizzi, Silvio and Papka, Michael E. and Ma, Kwan-Liu}, year = {2023}, eprint = {2304.10516}, archiveprefix = {arXiv}, primaryclass = {cs.DC} }
Murali Emani, Sam Foreman, Varuni Sastry, Zhen Xie, Siddhisanket Raskar, William Arnold, Rajeev Thakur, Venkatram Vishwanath, and Michael E. Papka, A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators, 2023
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Artificial intelligence (AI) methods have become critical in scientific applications to help accelerate scientific discovery. Large language models (LLMs) are being considered as a promising approach to address some of the challenging problems because of their superior generalization capabilities across domains. The effectiveness of the models and the accuracy of the applications is contingent upon their efficient execution on the underlying hardware infrastructure. Specialized AI accelerator hardware systems have recently become available for accelerating AI applications. However, the comparative performance of these AI accelerators on large language models has not been previously studied. In this paper, we systematically study LLMs on multiple AI accelerators and GPUs and evaluate their performance characteristics for these models. We evaluate these systems with (i) a micro-benchmark using a core transformer block, (ii) a GPT- 2 model, and (iii) an LLM-driven science use case, GenSLM. We present our findings and analyses of the models’ performance to better understand the intrinsic capabilities of AI accelerators. Furthermore, our analysis takes into account key factors such as sequence lengths, scaling behavior, sparsity, and sensitivity to gradient accumulation steps.
@misc{EmFoSa23, title = {A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators}, author = {Emani, Murali and Foreman, Sam and Sastry, Varuni and Xie, Zhen and Raskar, Siddhisanket and Arnold, William and Thakur, Rajeev and Vishwanath, Venkatram and Papka, Michael E.}, year = {2023}, eprint = {2310.04607}, archiveprefix = {arXiv}, primaryclass = {cs.PF} }
Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael Irvin, J. Gregory Pauloski, Logan Ward, Valerie Hayot, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian Foster, James J. Davis, Michael E. Papka, Thomas Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi Hanson, Thomas E Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin Aji, Angela Dalton, Michael Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, and Rick Stevens, DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies, 2023
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In the upcoming decade, deep learning may revolutionize the natural sciences, enhancing our capacity to model and predict natural occurrences. This could herald a new era of scientific exploration, bringing significant advancements across sectors from drug development to renewable energy. To answer this call, we present DeepSpeed4Science initiative which aims to build unique capabilities through AI system technology innovations to help domain experts to unlock today’s biggest science mysteries. By leveraging DeepSpeed’s current technology pillars (training, inference and compression) as base technology enablers, DeepSpeed4Science will create a new set of AI system technologies tailored for accelerating scientific discoveries by addressing their unique complexity beyond the common technical approaches used for accelerating generic large language models (LLMs). In this paper, we showcase the early progress we made with DeepSpeed4Science in addressing two of the critical system challenges in structural biology research.
@misc{SoKrZh23, title = {DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies}, author = {Song, Shuaiwen Leon and Kruft, Bonnie and Zhang, Minjia and Li, Conglong and Chen, Shiyang and Zhang, Chengming and Tanaka, Masahiro and Wu, Xiaoxia and Rasley, Jeff and Awan, Ammar Ahmad and Holmes, Connor and Cai, Martin and Ghanem, Adam and Zhou, Zhongzhu and He, Yuxiong and Luferenko, Pete and Kumar, Divya and Weyn, Jonathan and Zhang, Ruixiong and Klocek, Sylwester and Vragov, Volodymyr and AlQuraishi, Mohammed and Ahdritz, Gustaf and Floristean, Christina and Negri, Cristina and Kotamarthi, Rao and Vishwanath, Venkatram and Ramanathan, Arvind and Foreman, Sam and Hippe, Kyle and Arcomano, Troy and Maulik, Romit and Zvyagin, Maxim and Brace, Alexander and Zhang, Bin and Bohorquez, Cindy Orozco and Clyde, Austin and Kale, Bharat and Perez-Rivera, Danilo and Ma, Heng and Mann, Carla M. and Irvin, Michael and Pauloski, J. Gregory and Ward, Logan and Hayot, Valerie and Emani, Murali and Xie, Zhen and Lin, Diangen and Shukla, Maulik and Foster, Ian and Davis, James J. and Papka, Michael E. and Brettin, Thomas and Balaprakash, Prasanna and Tourassi, Gina and Gounley, John and Hanson, Heidi and Potok, Thomas E and Pasini, Massimiliano Lupo and Evans, Kate and Lu, Dan and Lunga, Dalton and Yin, Junqi and Dash, Sajal and Wang, Feiyi and Shankar, Mallikarjun and Lyngaas, Isaac and Wang, Xiao and Cong, Guojing and Zhang, Pei and Fan, Ming and Liu, Siyan and Hoisie, Adolfy and Yoo, Shinjae and Ren, Yihui and Tang, William and Felker, Kyle and Svyatkovskiy, Alexey and Liu, Hang and Aji, Ashwin and Dalton, Angela and Schulte, Michael and Schulz, Karl and Deng, Yuntian and Nie, Weili and Romero, Josh and Dallago, Christian and Vahdat, Arash and Xiao, Chaowei and Gibbs, Thomas and Anandkumar, Anima and Stevens, Rick}, year = {2023}, eprint = {2310.04610}, archiveprefix = {arXiv}, primaryclass = {cs.AI} }
Shilpika, Bethany Lusch, Murali Emani, Filippo Simini, Venkatram Vishwanath, Michael E. Papka, and Kwan-Liu Ma, A Multi-Level, Multi-Scale Visual Analytics Approach to Assessment of Multifidelity HPC Systems, 2023
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The ability to monitor and interpret of hardware system events and behaviors are crucial to improving the robustness and reliability of these systems, especially in a supercomputing facility. The growing complexity and scale of these systems demand an increase in monitoring data collected at multiple fidelity levels and varying temporal resolutions. In this work, we aim to build a holistic analytical system that helps make sense of such massive data, mainly the hardware logs, job logs, and environment logs collected from disparate subsystems and components of a supercomputer system. This end-to-end log analysis system, coupled with visual analytics support, allows users to glean and promptly extract supercomputer usage and error patterns at varying temporal and spatial resolutions. We use multiresolution dynamic mode decomposition (mrDMD), a technique that depicts high-dimensional data as correlated spatial-temporal variations patterns or modes, to extract variation patterns isolated at specified frequencies. Our improvements to the mrDMD algorithm help promptly reveal useful information in the massive environment log dataset, which is then associated with the processed hardware and job log datasets using our visual analytics system. Furthermore, our system can identify the usage and error patterns filtered at user, project, and subcomponent levels. We exemplify the effectiveness of our approach with two use scenarios with the Cray XC40 supercomputer.
@misc{ShLuEm23, archiveprefix = {arXiv}, author = {Shilpika and Lusch, Bethany and Emani, Murali and Simini, Filippo and Vishwanath, Venkatram and Papka, Michael E. and Ma, Kwan-Liu}, eprint = {2306.09457}, primaryclass = {cs.HC}, title = {A Multi-Level, Multi-Scale Visual Analytics Approach to Assessment of Multifidelity HPC Systems}, year = {2023} }
Nickolaus Saint, Ryan Chard, Rafael Vescovi, Jim Pruyne, Ben Blaiszik, Rachana Ananthakrishnan, Michael E. Papka, Rick Wagner, Kyle Chard, and Ian Foster, Active Research Data Management with the Django Globus Portal Framework, In Practice and Experience in Advanced Research Computing, 2023
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Publishing and sharing data is critical to fostering collaboration and advancing scientific research. Data portals are commonly used to organize, publish, and securely disseminate data—a critical step toward making data findable, accessible, interoperable, and reusable (FAIR). However, the diversity of scientific data types, sizes, and their location present significant challenges, e.g., it is difficult for portals to accommodate heterogenous research products when using strict metadata schemas and rigid interfaces. Thus, there is a need for a user-customizable data portal solution that enables rapid creation of new portals that may be tailored to a researchers needs while accommodating distributed data sources and engaging advanced computing resources. In this paper, we present the Django Globus Portal Framework (DGPF), a tool designed to help users rapidly create secure, customizable, and extensible data portals. DGPF is a powerful and flexible framework that builds upon the Globus platform for authentication, data sharing, creation of automation flows, and search capabilities, allowing for seamless integration with existing research workflows. We present the design and implementation of the DGPF and describe our experiences operating the Argonne Community Data Co-op (ACDC)—a collection of DGPF portals with over 1 M records and over 100 TB of published data that has been accessed by more than 300 users.
@inproceedings{SaChVe23, address = {New York, NY, USA}, author = {Saint, Nickolaus and Chard, Ryan and Vescovi, Rafael and Pruyne, Jim and Blaiszik, Ben and Ananthakrishnan, Rachana and Papka, Michael E. and Wagner, Rick and Chard, Kyle and Foster, Ian}, booktitle = {Practice and Experience in Advanced Research Computing}, doi = {10.1145/3569951.3593597}, isbn = {9781450399852}, keywords = {FAIR Data, Modern Research Data Portal, Globus}, location = {Portland, OR, USA}, numpages = {9}, pages = {43–51}, publisher = {Association for Computing Machinery}, series = {PEARC '23}, title = {Active Research Data Management with the Django Globus Portal Framework}, url = {https://doi.org/10.1145/3569951.3593597}, year = {2023} }
Zhengchun Liu, Rajkumar Kettimuthu, Michael E. Papka, and Ian Foster, FreeTrain: A Framework to Utilize Unused Supercomputer Nodes for Training Neural Networks, In 2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid), 2023
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Supercomputer scheduling policies commonly result in many transient idle nodes, a phenomenon that is only partially alleviated by backfill scheduling methods that promote small jobs to run before large jobs. Here we describe how to realize a novel use for these otherwise wasted resources, namely, deep neural network (DNN) training. This important workload is easily organized as many small fragments that can be configured dynamically to fit essentially any node × time hole in a supercomputer’s schedule. We describe how the task of rescaling suitable DNN training tasks to fit dynamically changing holes can be formulated as a deterministic mixed integer linear programming (MILP)-based resource allocation algorithm, and show that this MILP problem can be solved efficiently at run time. We show further how this MILP problem can be adapted to optimize for administrator- or user-defined metrics. We validate our method with supercomputer scheduler logs and different DNN training scenarios, and demonstrate efficiencies of up to 93% compared with running the same training tasks on dedicated nodes. Our method thus enables substantial supercomputer resources to be allocated to DNN training with no impact on other applications.
@inproceedings{LiKePa23, author = {Liu, Zhengchun and Kettimuthu, Rajkumar and Papka, Michael E. and Foster, Ian}, booktitle = {2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid)}, doi = {doi.org/10.1109/CCGrid57682.2023.00036}, pages = {299-310}, title = {FreeTrain: A Framework to Utilize Unused Supercomputer Nodes for Training Neural Networks}, year = {2023} }
Boyang Li, Yuping Fan, Michael E. Papka, and Zhiling Lan, Encoding for Reinforcement Learning Driven Scheduling, In Job Scheduling Strategies for Parallel Processing, 2023
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Reinforcement learning (RL) is exploited for cluster scheduling in the field of high-performance computing (HPC). One of the key challenges for RL driven scheduling is state representation for RL agent (i.e., capturing essential features of dynamic scheduling environment for decision making). Existing state encoding approaches either lack critical scheduling information or suffer from poor scalability. In this study, we present SEM (Scalable and Efficient encoding Model) for general RL driven scheduling in HPC. It captures system resource and waiting job state, both being critical information for scheduling. It encodes these pieces of information into a fixed-sized vector as an input to the agent. A typical agent is built on deep neural network, and its training/inference cost grows exponentially with the size of its input. Production HPC systems contain a large number of computer nodes. As such, a direct encoding of each of the system resources would lead to poor scalability of the RL agent. SEM uses two techniques to transform the system resource state into a small-sized vector, hence being capable of representing a large number of system resources in a vector of 100–200. Our trace-based simulations demonstrate that compared to the existing state encoding methods, SEM can achieve 9X training speedup and 6X inference speedup while maintaining comparable scheduling performance.
@inproceedings{LiFaPa23, address = {Cham}, author = {Li, Boyang and Fan, Yuping and Papka, Michael E. and Lan, Zhiling}, booktitle = {Job Scheduling Strategies for Parallel Processing}, editor = {Klus{\'a}{\v{c}}ek, Dalibor and Julita, Corbal{\'a}n and Rodrigo, Gonzalo P.}, isbn = {978-3-031-22698-4}, pages = {68--87}, publisher = {Springer Nature Switzerland}, title = {Encoding for Reinforcement Learning Driven Scheduling}, year = {2023} }
Bharat Kale, Maoyuan Sun, and Michael E. Papka, The State of the Art in Visualizing Dynamic Multivariate Networks, Computer Graphics Forum, 2023
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Most real-world networks are both dynamic and multivariate in nature, meaning that the network is associated with various attributes and both the network structure and attributes evolve over time. Visualizing dynamic multivariate networks is of great significance to the visualization community because of their wide applications across multiple domains. However, it remains challenging because the techniques should focus on representing the network structure, attributes and their evolution concurrently. Many real-world network analysis tasks require the concurrent usage of the three aspects of the dynamic multivariate networks. In this paper, we analyze current techniques and present a taxonomy to classify the existing visualization techniques based on three aspects: temporal encoding, topology encoding, and attribute encoding. Finally, we survey application areas and evaluation methods; and discuss challenges for future research.
@article{KaSuPa23, author = {Kale, Bharat and Sun, Maoyuan and Papka, Michael E.}, doi = {https://doi.org/10.1111/cgf.14856}, journal = {Computer Graphics Forum}, keywords = {CCS Concepts, • Human-centered computing —> Graph drawings}, number = {3}, pages = {471-490}, title = {The State of the Art in Visualizing Dynamic Multivariate Networks}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.14856}, volume = {42}, year = {2023} }
Bharat Kale, Austin Clyde, Maoyuan Sun, Arvind Ramanathan, Rick Stevens, and Michael E. Papka, ChemoGraph: Interactive Visual Exploration of the Chemical Space, Computer Graphics Forum, 2023
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Exploratory analysis of the chemical space is an important task in the field of cheminformatics. For example, in drug discovery research, chemists investigate sets of thousands of chemical compounds in order to identify novel yet structurally similar synthetic compounds to replace natural products. Manually exploring the chemical space inhabited by all possible molecules and chemical compounds is impractical, and therefore presents a challenge. To fill this gap, we present ChemoGraph, a novel visual analytics technique for interactively exploring related chemicals. In ChemoGraph, we formalize a chemical space as a hypergraph and apply novel machine learning models to compute related chemical compounds. It uses a database to find related compounds from a known space and a machine learning model to generate new ones, which helps enlarge the known space. Moreover, ChemoGraph highlights interactive features that support users in viewing, comparing, and organizing computationally identified related chemicals. With a drug discovery usage scenario and initial expert feedback from a case study, we demonstrate the usefulness of ChemoGraph.
@article{KaClSu23, author = {Kale, Bharat and Clyde, Austin and Sun, Maoyuan and Ramanathan, Arvind and Stevens, Rick and Papka, Michael E.}, doi = {https://doi.org/10.1111/cgf.14807}, journal = {Computer Graphics Forum}, keywords = {chemical space exploration, cheminformatics, multipartite graphs, data visualization, CCS Concepts, • Applied computing → Chemistry}, number = {3}, pages = {13-24}, title = {ChemoGraph: Interactive Visual Exploration of the Chemical Space}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.14807}, volume = {42}, year = {2023} }
Jarrad Hampton-Marcell, Tasia Bryson, Jeffrey Larson, J. Taylor Childers, Spencer Pasero, Cortez Watkins, Thomas Reed, Dorletta Flucas-Payton, and Michael E. Papka, Leveraging national laboratories to increase Black representation in STEM: recommendations within the Department of Energy, International Journal of STEM Education, 2023
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Increasing diversity in STEM disciplines has been a goal at scientific institutions for many decades. Black representation in STEM, however, has remained critically low at all levels (high school, undergraduate, graduate, and professional) for over 40 years, highlighting the need for innovative strategies that promote and retain Black students and professionals in STEM. We refocus efforts on increasing Black representation in STEM by promoting early exposure and continued engagement while leveraging national laboratories—an underutilized resource with immense potential to centralize diversity and inclusion efforts nationally.
@article{HaBrLa23, author = {Hampton-Marcell, Jarrad and Bryson, Tasia and Larson, Jeffrey and Childers, J. Taylor and Pasero, Spencer and Watkins, Cortez and Reed, Thomas and Flucas-Payton, Dorletta and Papka, Michael E.}, bdsk-url-1 = {https://doi.org/10.1186/s40594-022-00394-4}, date = {2023/01/18}, date-added = {2023-03-19 08:49:30 -0500}, date-modified = {2023-03-19 08:49:30 -0500}, doi = {10.1186/s40594-022-00394-4}, id = {Hampton-Marcell2023}, isbn = {2196-7822}, journal = {International Journal of STEM Education}, number = {1}, pages = {4}, title = {Leveraging national laboratories to increase Black representation in STEM: recommendations within the Department of Energy}, url = {https://doi.org/10.1186/s40594-022-00394-4}, volume = {10}, year = {2023} }

2022

Charlie Catlett, Pete Beckman, Nicola Ferrier, Michael E. Papka, Rajesh Sankaran, Jeff Solin, Valerie Taylor, Douglas Pancoast, and Daniel Reed, Hands-On Computer Science: The Array of Things Experimental Urban Instrument, Computing in Science & Engineering, 2022
Maxim Zvyagin, Alexander Brace, Kyle Hippe, Yuntian Deng, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael Irvin, Gregory J. Pauloski, Logan Ward, Valerie Hayot-Sasson, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian Foster, James J. Davis, Michael E. Papka, Thomas Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, and Arvind Ramanathan, GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics, bioRxiv, 2022
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We seek to transform how new and emergent variants of pandemiccausing viruses, specifically SARS-CoV-2, are identified and classified. By adapting large language models (LLMs) for genomic data, we build genome-scale language models (GenSLMs) which can learn the evolutionary landscape of SARS-CoV-2 genomes. By pretraining on over 110 million prokaryotic gene sequences and finetuning a SARS-CoV-2-specific model on 1.5 million genomes, we show that GenSLMs can accurately and rapidly identify variants of concern. Thus, to our knowledge, GenSLMs represents one of the first whole genome scale foundation models which can generalize to other prediction tasks. We demonstrate scaling of GenSLMs on GPU-based supercomputers and AI-hardware accelerators utilizing 1.63 Zettaflops in training runs with a sustained performance of 121 PFLOPS in mixed precision and peak of 850 PFLOPS. We present initial scientific insights from examining GenSLMs in tracking evolutionary dynamics of SARS-CoV-2, paving the path to realizing this on large biological data.Competing Interest StatementThe authors have declared no competing interest.
@article{ZvBrHi22, author = {Zvyagin, Maxim and Brace, Alexander and Hippe, Kyle and Deng, Yuntian and Zhang, Bin and Bohorquez, Cindy Orozco and Clyde, Austin and Kale, Bharat and Perez-Rivera, Danilo and Ma, Heng and Mann, Carla M. and Irvin, Michael and Pauloski, Gregory J. and Ward, Logan and Hayot-Sasson, Valerie and Emani, Murali and Foreman, Sam and Xie, Zhen and Lin, Diangen and Shukla, Maulik and Nie, Weili and Romero, Josh and Dallago, Christian and Vahdat, Arash and Xiao, Chaowei and Gibbs, Thomas and Foster, Ian and Davis, James J. and Papka, Michael E. and Brettin, Thomas and Stevens, Rick and Anandkumar, Anima and Vishwanath, Venkatram and Ramanathan, Arvind}, doi = {10.1101/2022.10.10.511571}, elocation-id = {2022.10.10.511571}, journal = {bioRxiv}, publisher = {Cold Spring Harbor Laboratory}, title = {GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics}, url = {https://www.biorxiv.org/content/early/2022/11/23/2022.10.10.511571}, year = {2022} }
Rafael Vescovi, Ryan Chard, Nickolaus D. Saint, Ben Blaiszik, Jim Pruyne, Tekin Bicer, Alex Lavens, Zhengchun Liu, Michael E. Papka, Suresh Narayanan, Nicholas Schwarz, Kyle Chard, and Ian T. Foster, Linking scientific instruments and computation: Patterns, technologies, and experiences, Patterns, 2022
Abs Bib

Powerful detectors at modern experimental facilities routinely collect data at multiple GB/s. Online analysis methods are needed to enable the collection of only interesting subsets of such massive data streams, such as by explicitly discarding some data elements or by directing instruments to relevant areas of experimental space. Thus, methods are required for configuring and running distributed computing pipelines—what we call flows—that link instruments, computers (e.g., for analysis, simulation, artificial intelligence [AI] model training), edge computing (e.g., for analysis), data stores, metadata catalogs, and high-speed networks. We review common patterns associated with such flows and describe methods for instantiating these patterns. We present experiences with the application of these methods to the processing of data from five different scientific instruments, each of which engages powerful computers for data inversion,model training, or other purposes. We also discuss implications of such methods for operators and users of scientific facilities.
@article{VeChSa22, author = {Vescovi, Rafael and Chard, Ryan and Saint, Nickolaus D. and Blaiszik, Ben and Pruyne, Jim and Bicer, Tekin and Lavens, Alex and Liu, Zhengchun and Papka, Michael E. and Narayanan, Suresh and Schwarz, Nicholas and Chard, Kyle and Foster, Ian T.}, doi = {https://doi.org/10.1016/j.patter.2022.100606}, issn = {2666-3899}, journal = {Patterns}, keywords = {Experiment automation, workflow, Globus, synchrotron light source, big data, machine learning, data fabric, computing fabric, trust fabric, scientific facility}, number = {10}, pages = {100606}, title = {Linking scientific instruments and computation: Patterns, technologies, and experiences}, url = {https://www.sciencedirect.com/science/article/pii/S2666389922002318}, volume = {3}, year = {2022} }
Nazariy Tishchenko, Nicola Ferrier, Joseph A. Insley, Victor A. Mateevitsi, Michael E. Papka, Silvio Rizzi, and Jifu Tan, Toward Bi-directional In Situ Visualization and Analysis of Blood Flow Simulations With Dynamic Deforming Walls [POSTER], In 2022 IEEE 12th Symposium on Large Data Analysis and Visualization (LDAV),Oct, 2022
Abs Bib

We present some preliminary work toward bi-directional in situ visualization and analysis of blood flow considering blood cell suspensions and dynamic moving walls to mimic the clot growth process. The work is implemented through integrating multiple open source packages including fluid flow solver, blood cells, and in situ visualization and analysis. It shows that in situ visualization enables us to examine and process the simulation results without writing data to files. In addition, preliminary results on bidirectional steering (still in progress) can accelerate engineers to explore the complicated stress environment experienced by clots of different sizes.
@inproceedings{TiFeIn22, author = {Tishchenko, Nazariy and Ferrier, Nicola and Insley, Joseph A. and Mateevitsi, Victor A. and Papka, Michael E. and Rizzi, Silvio and Tan, Jifu}, booktitle = {2022 IEEE 12th Symposium on Large Data Analysis and Visualization (LDAV)}, doi = {10.1109/LDAV57265.2022.9966389}, issn = {2832-6512}, month = oct, pages = {1-2}, title = {Toward Bi-directional In Situ Visualization and Analysis of Blood Flow Simulations With Dynamic Deforming Walls [POSTER]}, year = {2022} }
Jason A. Ortiz, Joseph A. Insley, Janet Knowles, Victor A. Mateevitsi, Michael E. Papka, and Silvio Rizzi, Massive Data Visualization Techniques for use in Virtual Reality Devices [POSTER], In 2022 IEEE 12th Symposium on Large Data Analysis and Visualization (LDAV),Oct, 2022
Abs Bib

Scientific simulations executed on supercomputers produce massive amounts of data. Visualizing this data is essential to discovery and dissemination, but methods for transforming and displaying such large data visualizations for use in Extended Reality (XR) devices are not commonly supported. We investigated the viability of existing XR applications (i.e., ParaView VR, SummitVR, and Omniverse XR) to display large data visualizations. Our investigations led us to create a proof-of-concept Virtual Reality (VR) application with Unity using Universal Scene Description (USD) files exported from Houdini to display and interact with large time-varying scientific data visualizations. We present our investigations as a basis for future work to display and interact with scientific data visualizations in XR.
@inproceedings{OrInKn22, author = {Ortiz, Jason A. and Insley, Joseph A. and Knowles, Janet and Mateevitsi, Victor A. and Papka, Michael E. and Rizzi, Silvio}, booktitle = {2022 IEEE 12th Symposium on Large Data Analysis and Visualization (LDAV)}, doi = {10.1109/LDAV57265.2022.9966400}, issn = {2832-6512}, month = oct, pages = {1-2}, title = {Massive Data Visualization Techniques for use in Virtual Reality Devices [POSTER]}, year = {2022} }
Isaac Nealey, Nicola Ferrier, Joseph Insley, Victor A. Mateevitsi, Michael E. Papka, and Silvio Rizzi, Cinema Transfer: A Containerized Visualization Workflow, In High Performance Computing. ISC High Performance 2022 International Workshops, 2022
Abs Bib

We present a containerized workflow demonstrating in situ analysis of simulation data rendered by a ParaView/Catalyst adapter for the generic SENSEI in situ interface, then streamed to a remote site for visualization. We use Cinema, a database approach for navigating the metadata produced in situ. We developed a web socket tool, cinema\_transfer, for transferring the generated cinema databases to a remote machine while the simulation is running. We evaluate the performance of this containerized workflow and identify bottlenecks for large scale runs, in addition to testing identical containers at different sites with differing hardware and Message Passing Interface (MPI) implementations.
@inproceedings{NeFeIn22, address = {Cham}, author = {Nealey, Isaac and Ferrier, Nicola and Insley, Joseph and Mateevitsi, Victor A. and Papka, Michael E. and Rizzi, Silvio}, booktitle = {High Performance Computing. ISC High Performance 2022 International Workshops}, editor = {Anzt, Hartwig and Bienz, Amanda and Luszczek, Piotr and Baboulin, Marc}, isbn = {978-3-031-23220-6}, pages = {324--343}, publisher = {Springer International Publishing}, title = {Cinema Transfer: A Containerized Visualization Workflow}, year = {2022} }
Thomas Marrinan, Jifu Tan, Joseph A. Insley, Alina Kanayinkal, and Michael E. Papka, Interactive Virtual Reality Exploration of Large-Scale Datasets Using Omnidirectional Stereo Images, In Advances in Visual Computing, 2022
Abs Bib

Virtual reality offers unique affordances that can benefit the scientific discovery process. However, virtual reality applications must maintain very high frame rates to provide immersion and prevent adverse events such as visual fatigue and motion sickness. Maintaining high frame rates can be challenging when visualizing scientific data that is large in scale. One successful technique for enabling interactive exploration of large-scale datasets is to create a large image collection from a structured sampling of camera positions, time steps, and visualization operators. This paper highlights our work to adapt this technique for virtual reality, and uses two authentic scientific datasets – a) a large-scale simulation of cancer cell transport and capture in a microfluidic device and b) a large-scale molecular dynamics simulation of graphene for creating extremely low friction interactions. We create a collection of omnidirectional stereoscopic images (three-dimensional surround-view panoramas), each of which captures all possible view angles from a given location. Therefore, virtual reality devices can always render local movements at full frame rates without loading a new image from the collection.
@inproceedings{MaTaIn22, address = {Cham}, author = {Marrinan, Thomas and Tan, Jifu and Insley, Joseph A. and Kanayinkal, Alina and Papka, Michael E.}, booktitle = {Advances in Visual Computing}, editor = {Bebis, George and Li, Bo and Yao, Angela and Liu, Yang and Duan, Ye and Lau, Manfred and Khadka, Rajiv and Crisan, Ana and Chang, Remco}, isbn = {978-3-031-20713-6}, pages = {115--128}, publisher = {Springer International Publishing}, title = {Interactive Virtual Reality Exploration of Large-Scale Datasets Using Omnidirectional Stereo Images}, year = {2022} }
Murali Emani, Zhen Xie, Siddhisanket Raskar, Varuni Sastry, William Arnold, Bruce Wilson, Rajeev Thakur, Venkatram Vishwanath, Zhengchun Liu, Michael E. Papka, Cindy Orozco Bohorquez, Rick Weisner, Karen Li, Yongning Sheng, Yun Du, Jian Zhang, Alexander Tsyplikhin, Gurdaman Khaira, Jeremy Fowers, Ramakrishnan Sivakumar, Victoria Godsoe, Adrian Macias, Chetan Tekur, and Matthew Boyd, A Comprehensive Evaluation of Novel AI Accelerators for Deep Learning Workloads, In 2022 IEEE/ACM International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), 2022
Abs Bib

Scientific applications are increasingly adopting Artificial Intelligence (AI) techniques to advance science. High-performance computing centers are evaluating emerging novel hardware accelerators to efficiently run AI-driven science applications. With a wide diversity in the hardware architectures and software stacks of these systems, it is challenging to understand how these accelerators perform. The state-of-the-art in the evaluation of deep learning workloads primarily focuses on CPUs and GPUs. In this paper, we present an overview of dataflow-based novel AI accelerators from SambaNova, Cerebras, Graphcore, and Groq. We present a first-of-a-kind evaluation of these accelerators with diverse workloads, such as Deep Learning (DL) primitives, benchmark models, and scientific machine learning applications. We also evaluate the performance of collective communication, which is key for distributed DL implementation, along with a study of scaling efficiency. We then discuss key insights, challenges, and opportunities in integrating these novel AI accelerators in supercomputing systems.
@inproceedings{EmXiRa22, author = {Emani, Murali and Xie, Zhen and Raskar, Siddhisanket and Sastry, Varuni and Arnold, William and Wilson, Bruce and Thakur, Rajeev and Vishwanath, Venkatram and Liu, Zhengchun and Papka, Michael E. and Bohorquez, Cindy Orozco and Weisner, Rick and Li, Karen and Sheng, Yongning and Du, Yun and Zhang, Jian and Tsyplikhin, Alexander and Khaira, Gurdaman and Fowers, Jeremy and Sivakumar, Ramakrishnan and Godsoe, Victoria and Macias, Adrian and Tekur, Chetan and Boyd, Matthew}, booktitle = {2022 IEEE/ACM International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS)}, doi = {10.1109/PMBS56514.2022.00007}, pages = {13-25}, title = {A Comprehensive Evaluation of Novel AI Accelerators for Deep Learning Workloads}, year = {2022} }

Pratool Bharti, Priyanjani Chandra, Michael E. Papka, and David Koop, An Edge Map based Ensemble Solution to Detect Water Level in Stream, arXiv preprint arXiv:2201.06098, 2022

Bib

@article{BhChPa22,
  author = {Bharti, Pratool and Chandra, Priyanjani and Papka, Michael E. and Koop, David},
  date-modified = {2022-02-05 06:58:25 -0600},
  journal = {arXiv preprint arXiv:2201.06098},
  title = {An Edge Map based Ensemble Solution to Detect Water Level in Stream},
  year = {2022}
}

2021

Michael Salim, Thomas Uram, J. Taylor Childers, Venkat Vishwanath, and Michael E. Papka, Toward real-time analysis of experimental science workloads on geographically distributed supercomputers, arXiv preprint arXiv:2105.06571, 2021

Bib

@article{SaUrCh21,
  author = {Salim, Michael and Uram, Thomas and Childers, J. Taylor and Vishwanath, Venkat and Papka, Michael E.},
  journal = {arXiv preprint arXiv:2105.06571},
  title = {Toward real-time analysis of experimental science workloads on geographically distributed supercomputers},
  year = {2021}
}

Pambayun Savira, Thomas Marrinan, and Michael E. Papka, Poster: Writing, Running, and Analyzing Large-scale Scientific Simulations with Jupyter Notebooks, In 2021 IEEE 11th Symposium on Large Data Analysis and Visualization (LDAV), 2021

Bib

@inproceedings{SaMaPa21,
  author = {Savira, Pambayun and Marrinan, Thomas and Papka, Michael E.},
  booktitle = {2021 IEEE 11th Symposium on Large Data Analysis and Visualization (LDAV)},
  organization = {IEEE},
  pages = {90--91},
  title = {Poster: Writing, Running, and Analyzing Large-scale Scientific Simulations with Jupyter Notebooks},
  year = {2021}
}

Khairi Reda, Amey A. Salvi, Jack Gray, and Michael E. Papka, Color Nameability Predicts Inference Accuracy in Spatial Visualizations, Computer Graphics Forum, 2021
Abs Bib

Color encoding is foundational to visualizing quantitative data. Guidelines for colormap design have traditionally emphasized perceptual principles, such as order and uniformity. However, colors also evoke cognitive and linguistic associations whose role in data interpretation remains underexplored. We study how two linguistic factors, name salience and name variation, affect people’s ability to draw inferences from spatial visualizations. In two experiments, we found that participants are better at interpreting visualizations when viewing colors with more salient names (e.g., prototypical ‘blue’, ‘yellow’, and ‘red’ over ‘teal’, ‘beige’, and ‘maroon’). The effect was robust across four visualization types, but was more pronounced in continuous (e.g., smooth geographical maps) than in similar discrete representations (e.g., choropleths). Participants’ accuracy also improved as the number of nameable colors increased, although the latter had a less robust effect. Our findings suggest that color nameability is an important design consideration for quantitative colormaps, and may even outweigh traditional perceptual metrics. In particular, we found that the linguistic associations of color are a better predictor of performance than the perceptual properties of those colors. We discuss the implications and outline research opportunities. The data and materials for this study are available at https://osf.io/asb7n
@article{ReSaGr21, author = {Reda, Khairi and Salvi, Amey A. and Gray, Jack and Papka, Michael E.}, doi = {https://doi.org/10.1111/cgf.14288}, journal = {Computer Graphics Forum}, keywords = {CCS Concepts, • Human-centered computing → Empirical studies in visualization}, number = {3}, pages = {49-60}, title = {Color Nameability Predicts Inference Accuracy in Spatial Visualizations}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/cgf.14288}, volume = {40}, year = {2021} }
Thomas Marrinan, and Michael E. Papka, Real-Time Omnidirectional Stereo Rendering: Generating 360° Surround-View Panoramic Images for Comfortable Immersive Viewing, IEEE Transactions on Visualization and Computer Graphics, 2021
Abs Bib

Surround-view panoramic images and videos have become a popular form of media for interactive viewing on mobile devices and virtual reality headsets. Viewing such media provides a sense of immersion by allowing users to control their view direction and experience an entire environment. When using a virtual reality headset, the level of immersion can be improved by leveraging stereoscopic capabilities. Stereoscopic images are generated in pairs, one for the left eye and one for the right eye, and result in providing an important depth cue for the human visual system. For computer generated imagery, rendering proper stereo pairs is well known for a fixed view. However, it is much more difficult to create omnidirectional stereo pairs for a surround-view projection that work well when looking in any direction. One major drawback of traditional omnidirectional stereo images is that they suffer from binocular misalignment in the peripheral vision as a user’s view direction approaches the zenith / nadir (north / south pole) of the projection sphere. This paper presents a real-time geometry-based approach for omnidirectional stereo rendering that fits into the standard rendering pipeline. Our approach includes tunable parameters that enable pole merging - a reduction in the stereo effect near the poles that can minimize binocular misalignment. Results from a user study indicate that pole merging reduces visual fatigue and discomfort associated with binocular misalignment without inhibiting depth perception.
@article{MaPa21, author = {Marrinan, Thomas and Papka, Michael E.}, doi = {10.1109/TVCG.2021.3067780}, journal = {IEEE Transactions on Visualization and Computer Graphics}, number = {5}, pages = {2587-2596}, title = {Real-Time Omnidirectional Stereo Rendering: Generating 360° Surround-View Panoramic Images for Comfortable Immersive Viewing}, volume = {27}, year = {2021} }

Travis Mackoy, Bharat Kale, Michael E. Papka, and Ralph A. Wheeler, viewSq, a Visual Molecular Dynamics (VMD) module for calculating, analyzing, and visualizing X-ray and neutron structure factors from atomistic simulations, Computer Physics Communications, 2021

Bib

@article{MaKaPa21,
  author = {Mackoy, Travis and Kale, Bharat and Papka, Michael E. and Wheeler, Ralph A.},
  journal = {Computer Physics Communications},
  pages = {107881},
  publisher = {North-Holland},
  title = {viewSq, a Visual Molecular Dynamics (VMD) module for calculating, analyzing, and visualizing X-ray and neutron structure factors from atomistic simulations},
  volume = {264},
  year = {2021}
}

Riley Lipinksi, Kenneth Moreland, Michael E. Papka, and Thomas Marrinan, Poster: GPU-based Image Compression for Efficient Compositing in Distributed Rendering Applications, In 2021 IEEE 11th Symposium on Large Data Analysis and Visualization (LDAV), 2021

Bib

@inproceedings{LiMoPa21,
  author = {Lipinksi, Riley and Moreland, Kenneth and Papka, Michael E. and Marrinan, Thomas},
  booktitle = {2021 IEEE 11th Symposium on Large Data Analysis and Visualization (LDAV)},
  organization = {IEEE},
  pages = {43--52},
  title = {Poster: GPU-based Image Compression for Efficient Compositing in Distributed Rendering Applications},
  year = {2021}
}

Zhengchun Liu, Rajkumar Kettimuthu, Michael E. Papka, and Ian Foster, BFTrainer: Low-Cost Training of Neural Networks on Unfillable Supercomputer Nodes, arXiv preprint arXiv:2106.12091, 2021

Bib

@article{LiKePa21,
  author = {Liu, Zhengchun and Kettimuthu, Rajkumar and Papka, Michael E. and Foster, Ian},
  journal = {arXiv preprint arXiv:2106.12091},
  title = {BFTrainer: Low-Cost Training of Neural Networks on Unfillable Supercomputer Nodes},
  year = {2021}
}

Bharat Kale, Maoyuan Sun, and Michael E. Papka, Direct Ordering: A Direct Manipulation Based Ordering Technique, In 26th International Conference on Intelligent User Interfaces - Companion, Fourth Workshop on Exploratory Search and Interactive Data Analytics (ESIDA), 2021
Abs Bib

The ordering of data can reveal patterns in various data visualizations. It significantly affects the expressiveness of visualizations by making them clear or cluttered. Clutter makes it hard for users to perceive patterns, even for a small dataset. Almost all visualization tools available today support ordering through indirect manipulation techniques where users rely on a widget (e.g., a button or a checkbox) to perform ordering in some predefined way. For example, using widgets for sorting a selected subset of data involves creating widgets to filter the data, highlight the filtered data, and then apply the ordering. This work presents a new interaction technique based on direct manipulation, which supports flexible visual ordering. This direct manipulation-based interaction helps to visually filter the data and then order them. We demonstrate how the proposed interaction technique works with bar charts and matrices, two heavily used visualization techniques that involve ordering.
@incollection{KaSuPa21, address = {New York, NY, USA}, author = {Kale, Bharat and Sun, Maoyuan and Papka, Michael E.}, booktitle = {26th International Conference on Intelligent User Interfaces - Companion, Fourth Workshop on Exploratory Search and Interactive Data Analytics (ESIDA)}, doi = {10.1145/3397482.3450711}, editor = {Glowacka, Dorota and Milios, Evangelos and Soto, Axel J. and Mokryn, Osnat and Paulovich, Fernando V. and Parra, Denis}, isbn = {9781450380188}, keywords = {personalisation, data analytics, exploratory search, interactive search}, location = {College Station, TX, USA}, numpages = {3}, pages = {18–20}, publisher = {Association for Computing Machinery}, series = {IUI '21 Companion}, title = {Direct Ordering: A Direct Manipulation Based Ordering Technique}, url = {https://doi.org/10.1145/3397482.3450711}, year = {2021} }

Yuping Fan, Paul Rich, William Allcock, Michael Papka, and Zhiling Lan, Hybrid Workload Scheduling on HPC Systems, arXiv preprint arXiv:2109.05412, 2021

Bib

@article{FaRiAl21,
  author = {Fan, Yuping and Rich, Paul and Allcock, William and Papka, Michael and Lan, Zhiling},
  journal = {arXiv preprint arXiv:2109.05412},
  title = {Hybrid Workload Scheduling on HPC Systems},
  year = {2021}
}

Yuping Fan, Zhiling Lan, J. Taylor Childers, Paul Rich, William Allcock, and Michael E. Papka, Deep reinforcement agent for scheduling in HPC, In 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2021

Bib

@inproceedings{FaLaCh21,
  author = {Fan, Yuping and Lan, Zhiling and Childers, J. Taylor and Rich, Paul and Allcock, William and Papka, Michael E.},
  booktitle = {2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS)},
  organization = {IEEE},
  pages = {807--816},
  title = {Deep reinforcement agent for scheduling in HPC},
  year = {2021}
}

Murali Emani, Venkatram Vishwanath, Corey Adams, Michael E. Papka, Rick Stevens, Laura Florescu, Sumti Jairath, William Liu, Tejas Nama, and Arvind Sujeeth, Accelerating Scientific Applications With SambaNova Reconfigurable Dataflow Architecture, Computing in Science & Engineering, 2021

Bib

@article{EmViAd21,
  author = {Emani, Murali and Vishwanath, Venkatram and Adams, Corey and Papka, Michael E. and Stevens, Rick and Florescu, Laura and Jairath, Sumti and Liu, William and Nama, Tejas and Sujeeth, Arvind},
  doi = {10.1109/MCSE.2021.3057203},
  journal = {Computing in Science & Engineering},
  number = {2},
  pages = {114-119},
  title = {{Accelerating Scientific Applications With SambaNova Reconfigurable Dataflow Architecture}},
  volume = {23},
  year = {2021}
}

Anthony Bucaro, Connor Murphy, Nicola Ferrier, Joseph Insley, Victor Mateevitsi, Michael E. Papka, Silvio Rizzi, and Jifu Tan, Instrumenting Multiphysics Blood Flow Simulation Codes for In Situ Visualization and Analysis, In 2021 IEEE 11th Symposium on Large Data Analysis and Visualization (LDAV), 2021

Bib

@inproceedings{BuMuFe21,
  author = {Bucaro, Anthony and Murphy, Connor and Ferrier, Nicola and Insley, Joseph and Mateevitsi, Victor and Papka, Michael E. and Rizzi, Silvio and Tan, Jifu},
  booktitle = {2021 IEEE 11th Symposium on Large Data Analysis and Visualization (LDAV)},
  organization = {IEEE},
  pages = {88--89},
  title = {Instrumenting Multiphysics Blood Flow Simulation Codes for In Situ Visualization and Analysis},
  year = {2021}
}

2020

Sreeranjani Ramprakash, Haritha Siddabathuni Som, Mark Fahey, Emily Shemon, David Martin, Katherine Riley, Kalyan Kumaran, Laura Wolf, Doug Waldron, and Eric Pershey, 2020 Operational Assessment Report-Argonne Leadership Computing Facility, 2020

Bib

@techreport{RaSoFa20,
  author = {Ramprakash, Sreeranjani and Som, Haritha Siddabathuni and Fahey, Mark and Shemon, Emily and Martin, David and Riley, Katherine and Kumaran, Kalyan and Wolf, Laura and Waldron, Doug and Pershey, Eric},
  institution = {Argonne National Lab.(ANL), Argonne, IL (United States)},
  title = {2020 Operational Assessment Report-Argonne Leadership Computing Facility},
  year = {2020}
}

Zhengchun Liu, Ryan Lewis, Rajkumar Kettimuthu, Kevin Harms, Philip Carns, Nageswara Rao, Ian Foster, and Michael E. Papka, Characterization and identification of HPC applications at leadership computing facility, In Proceedings of the 34th ACM International Conference on Supercomputing, 2020

Bib

@inproceedings{LiLeKe20,
  author = {Liu, Zhengchun and Lewis, Ryan and Kettimuthu, Rajkumar and Harms, Kevin and Carns, Philip and Rao, Nageswara and Foster, Ian and Papka, Michael E.},
  booktitle = {Proceedings of the 34th ACM International Conference on Supercomputing},
  pages = {1--12},
  title = {Characterization and identification of HPC applications at leadership computing facility},
  year = {2020}
}

Ryan D. Lewis, Zhengchun Liu, Rajkumar Kettimuthu, and Michael E. Papka, Log-based identification, classification, and behavor prediction of hpc applications, In In HPCSYSPROS20: HPC System Professionals Workshop, Atlanta, GA, 2020

Bib

@inproceedings{LeLiKe20,
  author = {Lewis, Ryan D. and Liu, Zhengchun and Kettimuthu, Rajkumar and Papka, Michael E.},
  booktitle = {In HPCSYSPROS20: HPC System Professionals Workshop, Atlanta, GA},
  title = {Log-based identification, classification, and behavor prediction of hpc applications},
  year = {2020}
}

James J. Hack, and Michael E. Papka, The US high-performance computing consortium in the fight against COVID-19, Computing in Science & Engineering, 2020

Bib

@article{HaPa20,
  author = {Hack, James J. and Papka, Michael E.},
  journal = {Computing in Science & Engineering},
  number = {6},
  pages = {75--80},
  publisher = {IEEE},
  title = {The US high-performance computing consortium in the fight against COVID-19},
  volume = {22},
  year = {2020}
}

Scott Collis, Pete Beckman, Eugene Kelly, Charles Catlett, Rajesh Sankaran, Ikay Altintas, Jim Olds, Nicola Ferrier, Seongha Park, Yongho Kim, and Michael E. Papka, Introducing Sage: Cyberinfrastructure for Sensing at the Edge., In EGU General Assembly, 2020

Bib

@inproceedings{CoBeKe20,
  author = {Collis, Scott and Beckman, Pete and Kelly, Eugene and Catlett, Charles and Sankaran, Rajesh and Altintas, Ikay and Olds, Jim and Ferrier, Nicola and Park, Seongha and Kim, Yongho and Papka, Michael E.},
  booktitle = {EGU General Assembly},
  doi = {doi.org/10.5194/egusphere-egu2020-12320},
  pages = {12320},
  title = {Introducing Sage: Cyberinfrastructure for Sensing at the Edge.},
  year = {2020}
}

Priyanjani Chandra, Pratool Bharti, and Michael Papka, Poster: A Computer Vision and AI Based Solution to Determine the Change in Water Level in Stream, 2020

Bib

@misc{ChBhPa20,
  author = {Chandra, Priyanjani and Bharti, Pratool and Papka, Michael},
  title = {Poster: A Computer Vision and AI Based Solution to Determine the Change in Water Level in Stream},
  year = {2020}
}

Charlie Catlett, Pete Beckman, Nicola Ferrier, Howard Nusbaum, Michael E. Papka, Marc G. Berman, and Rajesh Sankaran, Measuring Cities with Software-Defined Sensors, Journal of Social Computing, 2020

Bib

@article{CaBeFe20,
  author = {Catlett, Charlie and Beckman, Pete and Ferrier, Nicola and Nusbaum, Howard and Papka, Michael E. and Berman, Marc G. and Sankaran, Rajesh},
  journal = {Journal of Social Computing},
  number = {1},
  pages = {14--27},
  publisher = {TUP},
  title = {Measuring Cities with Software-Defined Sensors},
  volume = {1},
  year = {2020}
}

2019

Rick Stevens, Jini Ramprakash, Paul Messina, Michael Papka, and Katherine Riley, Aurora: Argonne’s next-generation exascale supercomputer, 2019

Bib

@techreport{StRaMe19,
  author = {Stevens, Rick and Ramprakash, Jini and Messina, Paul and Papka, Michael and Riley, Katherine},
  institution = {Argonne National Lab.(ANL), Argonne, IL (United States)},
  title = {Aurora: Argonne's next-generation exascale supercomputer},
  year = {2019}
}

FNU Shilpika, Bethany Lusch, Murali Emani, Venkatram Vishwanath, Michael E. Papka, and Kwan-Liu Ma, Mela: A visual analytics tool for studying multifidelity hpc system logs, In 2019 IEEE/ACM Industry/University Joint International Workshop on Data-center Automation, Analytics, and Control (DAAC), 2019

Bib

@inproceedings{ShLuEm19,
  author = {Shilpika, FNU and Lusch, Bethany and Emani, Murali and Vishwanath, Venkatram and Papka, Michael E. and Ma, Kwan-Liu},
  booktitle = {2019 IEEE/ACM Industry/University Joint International Workshop on Data-center Automation, Analytics, and Control (DAAC)},
  organization = {IEEE},
  pages = {13--18},
  title = {Mela: A visual analytics tool for studying multifidelity hpc system logs},
  year = {2019}
}

Sergei Shudler, Nicola Ferrier, Joseph Insley, Michael E. Papka, Saumil Patel, and Silvio Rizzi, Fast Mesh Validation in Combustion Simulations through In-Situ Visualization, In Eurographics Symposium on Parallel Graphics and Visualization, 2019

Bib

@inproceedings{ShFeIn19b,
  author = {Shudler, Sergei and Ferrier, Nicola and Insley, Joseph and Papka, Michael E. and Patel, Saumil and Rizzi, Silvio},
  booktitle = {Eurographics Symposium on Parallel Graphics and Visualization},
  doi = {10.2312/pgv.20191105},
  editor = {Childs, Hank and Frey, Steffen},
  isbn = {978-3-03868-079-6},
  issn = {1727-348X},
  publisher = {The Eurographics Association},
  title = {{Fast Mesh Validation in Combustion Simulations through In-Situ Visualization}},
  year = {2019}
}

Sergei Shudler, Nicola Ferrier, Joseph Insley, Michael E. Papka, and Silvio Rizzi, Spack meets singularity: creating movable in-situ analysis stacks with ease, In Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, 2019

Bib

@inproceedings{ShFeIn19a,
  author = {Shudler, Sergei and Ferrier, Nicola and Insley, Joseph and Papka, Michael E. and Rizzi, Silvio},
  booktitle = {Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization},
  pages = {34--38},
  title = {Spack meets singularity: creating movable in-situ analysis stacks with ease},
  year = {2019}
}

Michael A. Salim, Thomas D. Uram, J. Taylor Childers, Prasanna Balaprakash, Venkatram Vishwanath, and Michael E. Papka, Balsam: Automated scheduling and execution of dynamic, data-intensive hpc workflows, arXiv preprint arXiv:1909.08704, 2019

Bib

@article{SaUrCh19b,
  author = {Salim, Michael A. and Uram, Thomas D. and Childers, J. Taylor and Balaprakash, Prasanna and Vishwanath, Venkatram and Papka, Michael E.},
  journal = {arXiv preprint arXiv:1909.08704},
  title = {Balsam: Automated scheduling and execution of dynamic, data-intensive hpc workflows},
  year = {2019}
}

Michael Salim, Thomas Uram, J. Taylor Childers, Venkatram Vishwanath, and Michael Papka, Balsam: Near real-time experimental data analysis on supercomputers, In 2019 IEEE/ACM 1st Annual Workshop on Large-scale Experiment-in-the-Loop Computing (XLOOP), 2019

Bib

@inproceedings{SaUrCh19a,
  author = {Salim, Michael and Uram, Thomas and Childers, J. Taylor and Vishwanath, Venkatram and Papka, Michael},
  booktitle = {2019 IEEE/ACM 1st Annual Workshop on Large-scale Experiment-in-the-Loop Computing (XLOOP)},
  organization = {IEEE},
  pages = {26--31},
  title = {Balsam: Near real-time experimental data analysis on supercomputers},
  year = {2019}
}

Allen Sanderson, John Schmidt, Alan Humphrey, Michael Papka, and Robert Sisneros, In Situ Visualization of Performance Metrics in Multiple Domains, In 2019 IEEE/ACM International Workshop on Programming and Performance Visualization Tools (ProTools), 2019

Bib

@inproceedings{SaScHu19,
  author = {Sanderson, Allen and Schmidt, John and Humphrey, Alan and Papka, Michael and Sisneros, Robert},
  booktitle = {2019 IEEE/ACM International Workshop on Programming and Performance Visualization Tools (ProTools)},
  organization = {IEEE},
  pages = {62--69},
  title = {In Situ Visualization of Performance Metrics in Multiple Domains},
  year = {2019}
}

Katherine Riley, Michael E. Papka, Jim Collins, Nils Heinonen, and Beth Cerny, 2019 ALCF Science Report, 2019

Bib

@techreport{RiPaCo19,
  author = {Riley, Katherine and Papka, Michael E. and Collins, Jim and Heinonen, Nils and Cerny, Beth},
  institution = {Argonne National Laboratory (ANL), Argonne, IL (United States)},
  title = {2019 ALCF Science Report},
  year = {2019}
}

Khairi Reda, and Michael E. Papka, Evaluating Gradient Perception in Color-Coded Scalar Fields, In 2019 IEEE Visualization Conference (VIS), 2019
Abs Bib

Color mapping is a commonly used technique for visualizing scalar fields. While there exists advice for choosing effective colormaps, it is unclear if current guidelines apply equally across task types. We study the perception of gradients and evaluate the effectiveness of three colormaps at depicting gradient magnitudes. In a crowd-sourced experiment, we determine the just-noticeable differences (JNDs) at which participants can reliably compare and judge variations in gradient between two scalar fields. We find that participants exhibited lower JNDs with a diverging (cool-warm) or a spectral (rainbow) scheme, as compared with a monotonic-luminance colormap (viridis). The results support a hypothesis that apparent discontinuities in the color ramp may help viewers discern subtle structural differences in gradient. We discuss these findings and highlight future research directions for colormap evaluation.
@inproceedings{RePa19, author = {Reda, Khairi and Papka, Michael E.}, booktitle = {2019 IEEE Visualization Conference (VIS)}, doi = {10.1109/VISUAL.2019.8933760}, pages = {271-275}, title = {Evaluating Gradient Perception in Color-Coded Scalar Fields}, year = {2019} }

Thomas Marrinan, Silvio Rizzi, Joseph A. Insley, Lance Long, Luc Renambot, and Michael E. Papka, Pxstream: Remote visualization for distributed rendering frameworks, In 2019 IEEE 9th Symposium on Large Data Analysis and Visualization (LDAV), 2019

Bib

@inproceedings{MaRiIn19,
  author = {Marrinan, Thomas and Rizzi, Silvio and Insley, Joseph A. and Long, Lance and Renambot, Luc and Papka, Michael E.},
  booktitle = {2019 IEEE 9th Symposium on Large Data Analysis and Visualization (LDAV)},
  organization = {IEEE},
  pages = {37--41},
  title = {Pxstream: Remote visualization for distributed rendering frameworks},
  year = {2019}
}

Travis Mackoy, Bharat Kale, Michael Papka, and Ralph Wheeler, viewSq: VMD module for visualizing and quantifying periodic atomic ordering underlying static structure factors from molecular dynamics simulations, In Abstracts of papers of the American Chemical Society, 2019

Bib

@inproceedings{MaKaPa19,
  author = {Mackoy, Travis and Kale, Bharat and Papka, Michael and Wheeler, Ralph},
  booktitle = {Abstracts of papers of the American Chemical Society},
  organization = {AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA},
  title = {viewSq: VMD module for visualizing and quantifying periodic atomic ordering underlying static structure factors from molecular dynamics simulations},
  volume = {258},
  year = {2019}
}

Thomas Marrinan, Greg Eisenhauer, Matthew Wolf, Joseph A. Insley, Silvio Rizzi, and Michael E. Papka, Parallel streaming between heterogeneous HPC resources for real-time analysis, Journal of Computational Science, 2019

Bib

@article{MaEiWo19,
  author = {Marrinan, Thomas and Eisenhauer, Greg and Wolf, Matthew and Insley, Joseph A. and Rizzi, Silvio and Papka, Michael E.},
  journal = {Journal of Computational Science},
  pages = {163--171},
  publisher = {Elsevier},
  title = {Parallel streaming between heterogeneous HPC resources for real-time analysis},
  volume = {31},
  year = {2019}
}

Yuping Fan, Zhiling Lan, Paul Rich, William E. Allcock, Michael E. Papka, Brian Austin, and David Paul, Scheduling beyond CPUs for HPC, In Proceedings of the 28th International Symposium on High-Performance Parallel and Distributed Computing, 2019

Bib

@inproceedings{FaLaRi19,
  author = {Fan, Yuping and Lan, Zhiling and Rich, Paul and Allcock, William E. and Papka, Michael E. and Austin, Brian and Paul, David},
  booktitle = {Proceedings of the 28th International Symposium on High-Performance Parallel and Distributed Computing},
  pages = {97--108},
  title = {Scheduling beyond CPUs for HPC},
  year = {2019}
}

Mark R. Fahey, Yuri Alexeev, William Allcock, Benjamin S. Allen, Ramesh Balakrishnan, Anouar Benali, Liza Booker, Ashley Boyle, Laural Briggs, Edouard Brooks, Phil Carns, Beth Cerny, Andrew Cherry, Lisa Childers, Sudheer Chunduri, Richard Coffey, James Collins, Paul Coffman, Susan Coghlan, Kathy DiBennardi, Ginny Doyle, Hal Finkel, Graham Fletcher, Marta Garcia, Ira Goldberg, Cheetah Goletz, Susan Gregurich, Kevin Harms, Carissa Holohan, Joseph A. Insley, Tommie Jackson, Janet Jaseckas, Elise Jennings, Derek Jensen, Wei Jiang, Margaret Kaczmarski, Chris Knight, Janet Knowles, Kalyan Kumaran, Ti Leggett, Ben Lenard, Anping Liu, Ray Loy, Preeti Malakar, Avanthi Mantrala, David E. Martin, Guillermo Mayorga, Gordon McPheeters, Paul Messina, Ryan Milner, Vitali Morozov, Zachary Nault, Denise Nelson, Jack O’Connell, James Osborn, Michael E. Papka, Scott Parker, Pragnesh Patel, Saumil Patel, Eric Pershey, Renee Plzak, Adrian Pope, Jared Punzel, Sreeranjani Ramprakash, John ‘Skip’ Reddy, Paul Rich, Katherine Riley, Silvio Rizzi, George Rojas, Nichols A. Romero, Robert Scott, Adam Scovel, William Scullin, Emily Shemon, Haritha Siddabathuni Som, Joan Stover, Mirek Suliba, Brian Toonen, Tom Uram, Alvaro Vazquez-Mayagoitia, Venkatram Vishwanath, R. Douglas Waldron, Gabe West, Timothy J. Williams, Darin Wills, Laura Wolf, Wanda Woods, and Michael Zhang, Theta and Mira at Argonne National Laboratory, In Contemporary High Performance Computing, 2019

Bib

@incollection{FaAlAl19,
  author = {Fahey, Mark R. and Alexeev, Yuri and Allcock, William and Allen, Benjamin S. and Balakrishnan, Ramesh and Benali, Anouar and Booker, Liza and Boyle, Ashley and Briggs, Laural and Brooks, Edouard and Carns, Phil and Cerny, Beth and Cherry, Andrew and Childers, Lisa and Chunduri, Sudheer and Coffey, Richard and Collins, James and Coffman, Paul and Coghlan, Susan and DiBennardi, Kathy and Doyle, Ginny and Finkel, Hal and Fletcher, Graham and Garcia, Marta and Goldberg, Ira and Goletz, Cheetah and Gregurich, Susan and Harms, Kevin and Holohan, Carissa and Insley, Joseph A. and Jackson, Tommie and Jaseckas, Janet and Jennings, Elise and Jensen, Derek and Jiang, Wei and Kaczmarski, Margaret and Knight, Chris and Knowles, Janet and Kumaran, Kalyan and Leggett, Ti and Lenard, Ben and Liu, Anping and Loy, Ray and Malakar, Preeti and Mantrala, Avanthi and Martin, David E. and Mayorga, Guillermo and McPheeters, Gordon and Messina, Paul and Milner, Ryan and Morozov, Vitali and Nault, Zachary and Nelson, Denise and O’Connell, Jack and Osborn, James and Papka, Michael E. and Parker, Scott and Patel, Pragnesh and Patel, Saumil and Pershey, Eric and Plzak, Renee and Pope, Adrian and Punzel, Jared and Ramprakash, Sreeranjani and Reddy, John ‘Skip’ and Rich, Paul and Riley, Katherine and Rizzi, Silvio and Rojas, George and Romero, Nichols A. and Scott, Robert and Scovel, Adam and Scullin, William and Shemon, Emily and Som, Haritha Siddabathuni and Stover, Joan and Suliba, Mirek and Toonen, Brian and Uram, Tom and Vazquez-Mayagoitia, Alvaro and Vishwanath, Venkatram and Waldron, R. Douglas and West, Gabe and Williams, Timothy J. and Wills, Darin and Wolf, Laura and Woods, Wanda and Zhang, Michael},
  booktitle = {Contemporary High Performance Computing},
  pages = {31--61},
  publisher = {CRC Press},
  title = {{Theta and Mira at Argonne National Laboratory}},
  year = {2019}
}

William E. Allcock, Benjamin S. Allen, Rachana Ananthakrishnan, Ben Blaiszik, Kyle Chard, Ryan Chard, Ian Foster, Lukasz Lacinski, Michael E. Papka, and Rick Wagner, Petrel: A Programmatically Accessible Research Data Service, In Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (Learning), 2019
Abs Bib

We report on our experiences deploying and operating Petrel, a data service designed to support science projects that must organize and distribute large quantities of data. Building on a high-performance 3.2 PB parallel file system and embedded in Argonne National Laboratory’s 100+ Gbps network fabric, Petrel leverages Science DMZ concepts and Globus APIs to provide application scientists with a high-speed, highly connected, and programmatically controllable data store. We describe Petrel’s design, implementation, and usage and give representative examples to illustrate the many different ways in which scientists have employed the system.
@incollection{AlAlAn19, address = {New York, NY, USA}, articleno = {49}, author = {Allcock, William E. and Allen, Benjamin S. and Ananthakrishnan, Rachana and Blaiszik, Ben and Chard, Kyle and Chard, Ryan and Foster, Ian and Lacinski, Lukasz and Papka, Michael E. and Wagner, Rick}, booktitle = {Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (Learning)}, doi = {10.1145/3332186.3332241}, isbn = {9781450372275}, location = {Chicago, IL, USA}, numpages = {7}, publisher = {Association for Computing Machinery}, series = {PEARC '19}, title = {Petrel: A Programmatically Accessible Research Data Service}, url = {https://doi.org/10.1145/3332186.3332241}, year = {2019} }

2018

Li Yu, Zhou Zhou, Yuping Fan, Michael E. Papka, and Zhiling Lan, System-wide trade-off modeling of performance, power, and resilience on petascale systems, The Journal of Supercomputing, 2018

Bib

@article{YuZhFa18,
  author = {Yu, Li and Zhou, Zhou and Fan, Yuping and Papka, Michael E. and Lan, Zhiling},
  journal = {The Journal of Supercomputing},
  number = {7},
  pages = {3168--3192},
  publisher = {Springer US},
  title = {System-wide trade-off modeling of performance, power, and resilience on petascale systems},
  volume = {74},
  year = {2018}
}

Will Usher, Silvio Rizzi, Ingo Wald, Jefferson Amstutz, Joseph Insley, Venkatram Vishwanath, Nicola Ferrier, Michael E. Papka, and Valerio Pascucci, libIS: a lightweight library for flexible in transit visualization, In Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, 2018

Bib

@inproceedings{UsRiWa18,
  author = {Usher, Will and Rizzi, Silvio and Wald, Ingo and Amstutz, Jefferson and Insley, Joseph and Vishwanath, Venkatram and Ferrier, Nicola and Papka, Michael E. and Pascucci, Valerio},
  booktitle = {Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization},
  pages = {33--38},
  title = {libIS: a lightweight library for flexible in transit visualization},
  year = {2018}
}

Michael E. Papka, Jim Collins, Beth Cerny, and Nils Heinonen, 2018 Annual Report-Argonne Leadership Computing Facility, 2018

Bib

@techreport{PaCoCe18,
  author = {Papka, Michael E. and Collins, Jim and Cerny, Beth and Heinonen, Nils},
  institution = {Argonne National Lab.(ANL), Argonne, IL (United States)},
  title = {2018 Annual Report-Argonne Leadership Computing Facility},
  year = {2018}
}

Thomas Marrinan, Silvio Rizzi, Joseph Insley, Brian Toonen, William Allcock, and Michael E. Papka, Transferring data from high-performance simulations to extreme scale analysis applications in real-time, In 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2018

Bib

@inproceedings{MaRiIn18,
  author = {Marrinan, Thomas and Rizzi, Silvio and Insley, Joseph and Toonen, Brian and Allcock, William and Papka, Michael E.},
  booktitle = {2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)},
  organization = {IEEE},
  pages = {1214--1220},
  title = {Transferring data from high-performance simulations to extreme scale analysis applications in real-time},
  year = {2018}
}

Preeti Malakar, Todd Munson, Christopher Knight, Venkatram Vishwanath, and Michael E. Papka, Topology-aware space-shared co-analysis of large-scale molecular dynamics simulations, In SC18: International Conference for High Performance Computing, Networking, Storage and Analysis, 2018

Bib

@inproceedings{MaMuKn18,
  author = {Malakar, Preeti and Munson, Todd and Knight, Christopher and Vishwanath, Venkatram and Papka, Michael E.},
  booktitle = {SC18: International Conference for High Performance Computing, Networking, Storage and Analysis},
  organization = {IEEE},
  pages = {305--319},
  title = {Topology-aware space-shared co-analysis of large-scale molecular dynamics simulations},
  year = {2018}
}

Mark Kostuk, Thomas D. Uram, Todd Evans, Dmitri M. Orlov, Michael E. Papka, and David Schissel, Automatic between-pulse analysis of DIII-D experimental data performed remotely on a supercomputer at Argonne Leadership Computing Facility, Fusion Science and Technology, 2018

Bib

@article{KoUrEv18,
  author = {Kostuk, Mark and Uram, Thomas D. and Evans, Todd and Orlov, Dmitri M. and Papka, Michael E. and Schissel, David},
  journal = {Fusion Science and Technology},
  number = {1-2},
  pages = {135--143},
  publisher = {Taylor & Francis},
  title = {Automatic between-pulse analysis of DIII-D experimental data performed remotely on a supercomputer at Argonne Leadership Computing Facility},
  volume = {74},
  year = {2018}
}

Ryan Chard, Ravi Madduri, Nicholas T. Karonis, Kyle Chard, Kirk L. Duffin, Caesar E. Ordoñez, Thomas D. Uram, Justin Fleischauer, Ian T. Foster, Michael E. Papka, and John Winans, Scalable pCT Image Reconstruction Delivered as a Cloud Service, IEEE Transactions on Cloud Computing,Jan, 2018
Abs Bib

We describe a cloud-based medical image reconstruction service designed to meet a real-time and daily demand to reconstruct thousands of images from proton cancer treatment facilities worldwide. Rapid reconstruction of a three-dimensional Proton Computed Tomography (pCT) image can require the transfer of 100 GB of data and use of approximately 120 GPU-enabled compute nodes. The nature of proton therapy means that demand for such a service is sporadic and comes from potentially hundreds of clients worldwide. We thus explore the use of a commercial cloud as a scalable and cost-efficient platform for pCT reconstruction. To address the high performance requirements of this application we leverage Amazon Web Services’ GPU-enabled cluster resources that are provisioned with high performance networks between nodes. To support episodic demand, we develop an on-demand multi-user provisioning service that can dynamically provision and resize clusters based on image reconstruction requirements, priorities, and wait times. We compare the performance of our pCT reconstruction service running on commercial cloud resources with that of the same application on dedicated local high performance computing resources. We show that we can achieve scalable and on-demand reconstruction of large scale pCT images for simultaneous multi-client requests, processing images in less than 10 minutes for less than $10 per image.
@article{ChMaKa18, address = {Los Alamitos, CA, USA}, author = {Chard, Ryan and Madduri, Ravi and Karonis, Nicholas T. and Chard, Kyle and Duffin, Kirk L. and Ordo{\~n}ez, Caesar E. and Uram, Thomas D. and Fleischauer, Justin and Foster, Ian T. and Papka, Michael E. and Winans, John}, bdsk-url-1 = {https://doi.org/10.1109/TCC.2015.2457423}, doi = {10.1109/TCC.2015.2457423}, issn = {2168-7161}, journal = {IEEE Transactions on Cloud Computing}, keywords = {image reconstruction;protons;history;cloud computing;medical treatment;biomedical imaging}, month = jan, number = {01}, pages = {182-195}, publisher = {IEEE Computer Society}, title = {Scalable pCT Image Reconstruction Delivered as a Cloud Service}, volume = {6}, year = {2018} }

Bennett Bernardoni, Nicola Ferrier, Joseph Insley, Michael E. Papka, Saumil Patel, and Silvio Rizzi, In situ visualization and analysis to design large scale experiments in computational fluid dynamics, In 2018 IEEE 8th Symposium on Large Data Analysis and Visualization (LDAV), 2018

Bib

@inproceedings{BeFeIn18,
  author = {Bernardoni, Bennett and Ferrier, Nicola and Insley, Joseph and Papka, Michael E. and Patel, Saumil and Rizzi, Silvio},
  booktitle = {2018 IEEE 8th Symposium on Large Data Analysis and Visualization (LDAV)},
  organization = {IEEE},
  pages = {94--95},
  title = {In situ visualization and analysis to design large scale experiments in computational fluid dynamics},
  year = {2018}
}

William Allcock, Bennett Bernardoni, Colleen Bertoni, Neil Getty, Joseph Insley, Michael E. Papka, Silvio Rizzi, and Brian Toonen, Ram as a network managed resource, In 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2018

Bib

@inproceedings{AlBeBe18,
  author = {Allcock, William and Bernardoni, Bennett and Bertoni, Colleen and Getty, Neil and Insley, Joseph and Papka, Michael E. and Rizzi, Silvio and Toonen, Brian},
  booktitle = {2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)},
  organization = {IEEE},
  pages = {99--106},
  title = {Ram as a network managed resource},
  year = {2018}
}

Joseph Adamo, J. D. Emberson, Edouard Brooks, Silvio Rizzi, Joseph Insley, and Michael E. Papka, Exploring visualization techniques with hacc simulation data, In 2018 IEEE 8th Symposium on Large Data Analysis and Visualization (LDAV), 2018

Bib

@inproceedings{AdEmBr18,
  author = {Adamo, Joseph and Emberson, J. D. and Brooks, Edouard and Rizzi, Silvio and Insley, Joseph and Papka, Michael E.},
  booktitle = {2018 IEEE 8th Symposium on Large Data Analysis and Visualization (LDAV)},
  organization = {IEEE},
  pages = {92--93},
  title = {Exploring visualization techniques with hacc simulation data},
  year = {2018}
}

2017

Sarah Read, and Michael E. Papka, Operational metrics reporting processes at scientific user facilities: Comparing a high-energy x-ray synchrotron facility to a supercomputing facility, In 2017 IEEE International Professional Communication Conference (ProComm), 2017

Bib

@inproceedings{RePa17,
  author = {Read, Sarah and Papka, Michael E.},
  booktitle = {2017 IEEE International Professional Communication Conference (ProComm)},
  organization = {IEEE},
  pages = {1--6},
  title = {Operational metrics reporting processes at scientific user facilities: Comparing a high-energy x-ray synchrotron facility to a supercomputing facility},
  year = {2017}
}

Preeti Malakar, Venkatram Vishwanath, Christopher Knight, Todd Munson, and Michael Papka, Scalable in situ analysis for large-scale molecular dynamics simulations on supercomputers, In ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2017

Bib

@inproceedings{MaViKn17,
  author = {Malakar, Preeti and Vishwanath, Venkatram and Knight, Christopher and Munson, Todd and Papka, Michael},
  booktitle = {ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY},
  organization = {AMER CHEMICAL SOC 1155 16TH ST, NW, WASHINGTON, DC 20036 USA},
  title = {Scalable in situ analysis for large-scale molecular dynamics simulations on supercomputers},
  volume = {254},
  year = {2017}
}

Preeti Malakar, Christopher Knight, Todd Munson, Venkatram Vishwanath, and Michael E. Papka, Scalable In Situ Analysis of Molecular Dynamics Simulations, In Proceedings of the In Situ Infrastructures on Enabling Extreme-Scale Analysis and Visualization, 2017
Abs Bib

Analysis of scientific simulation data enables scientists to glean insight from simulations. In situ analysis, which can be simultaneously executed with the simulation, mitigates I/O bottlenecks and can accelerate discovery of new phenomena. However, in typical modes of operation, this requires either stalling simulation during analysis phase or transferring data for analysis. We study the scalability challenges of time- and space-shared modes of analyzing large-scale molecular dynamics simulations. We also propose topology-aware mapping for simulation and analysis. We demonstrate the benefits of our approach using LAMMPS code on two supercomputers.
@incollection{MaKnMu17, address = {New York, NY, USA}, author = {Malakar, Preeti and Knight, Christopher and Munson, Todd and Vishwanath, Venkatram and Papka, Michael E.}, booktitle = {Proceedings of the In Situ Infrastructures on Enabling Extreme-Scale Analysis and Visualization}, doi = {10.1145/3144769.3144772}, isbn = {9781450351393}, location = {Denver, CO, USA}, numpages = {6}, pages = {1–6}, publisher = {Association for Computing Machinery}, series = {ISAV'17}, title = {Scalable In Situ Analysis of Molecular Dynamics Simulations}, url = {https://doi.org/10.1145/3144769.3144772}, year = {2017} }

Thomas Marrinan, Joseph A. Insley, Silvio Rizzi, François Tessier, and Michael E. Papka, Automated dynamic data redistribution, In 2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2017

Bib

@inproceedings{MaInRi17,
  author = {Marrinan, Thomas and Insley, Joseph A. and Rizzi, Silvio and Tessier, Fran{\c{c}}ois and Papka, Michael E.},
  booktitle = {2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)},
  organization = {IEEE},
  pages = {1208--1215},
  title = {Automated dynamic data redistribution},
  year = {2017}
}

Michael J. Lewis, George K. Thiruvathukal, Venkatram Vishwanath, Michael E. Papka, and Andrew Johnson, A distributed graph approach for pre-processing linked RDF data using supercomputers, In Proceedings of The International Workshop on Semantic Big Data, 2017

Bib

@inproceedings{LeThVi17,
  author = {Lewis, Michael J. and Thiruvathukal, George K. and Vishwanath, Venkatram and Papka, Michael E. and Johnson, Andrew},
  booktitle = {Proceedings of The International Workshop on Semantic Big Data},
  pages = {1--6},
  title = {A distributed graph approach for pre-processing linked RDF data using supercomputers},
  year = {2017}
}

Bharat Kale, Harish Varma Siravuri, Hamed Alhoori, and Michael E. Papka, Predicting research that will be cited in policy documents, In Proceedings of the 2017 ACM on Web Science Conference, 2017

Bib

@inproceedings{KaSiAl17,
  author = {Kale, Bharat and Siravuri, Harish Varma and Alhoori, Hamed and Papka, Michael E.},
  booktitle = {Proceedings of the 2017 ACM on Web Science Conference},
  pages = {389--390},
  title = {Predicting research that will be cited in policy documents},
  year = {2017}
}

Takanori Fujiwara, Preeti Malakar, Khairi Reda, Venkatram Vishwanath, Michael E. Papka, and Kwan-Liu Ma, A visual analytics system for optimizing communications in massively parallel applications, In 2017 IEEE Conference on Visual Analytics Science and Technology (VAST), 2017

Bib

@inproceedings{FuMaRe17,
  author = {Fujiwara, Takanori and Malakar, Preeti and Reda, Khairi and Vishwanath, Venkatram and Papka, Michael E. and Ma, Kwan-Liu},
  booktitle = {2017 IEEE Conference on Visual Analytics Science and Technology (VAST)},
  organization = {IEEE},
  pages = {59--70},
  title = {A visual analytics system for optimizing communications in massively parallel applications},
  year = {2017}
}

Tommy Franczak, Asare Nkansah, Thomas Marrinan, and Michael E. Papka, A path from serial execution to hybrid parallelization for learning hpc, In EduHPC-17: Workshop on Education for High-Performance Computing, 2017

Bib

@inproceedings{FrNkMa17,
  author = {Franczak, Tommy and Nkansah, Asare and Marrinan, Thomas and Papka, Michael E.},
  booktitle = {EduHPC-17: Workshop on Education for High-Performance Computing},
  title = {A path from serial execution to hybrid parallelization for learning hpc},
  volume = {17},
  year = {2017}
}

Yuping Fan, Paul Rich, William E. Allcock, Michael E. Papka, and Zhiling Lan, Trade-off between prediction accuracy and underestimation rate in job runtime estimates, In 2017 IEEE International Conference on Cluster Computing (CLUSTER), 2017

Bib

@inproceedings{FaRiAl17,
  author = {Fan, Yuping and Rich, Paul and Allcock, William E. and Papka, Michael E. and Lan, Zhiling},
  booktitle = {2017 IEEE International Conference on Cluster Computing (CLUSTER)},
  organization = {IEEE},
  pages = {530--540},
  title = {Trade-off between prediction accuracy and underestimation rate in job runtime estimates},
  year = {2017}
}

John T. Childers, Thomas D. Uram, Thomas J. LeCompte, Michael E. Papka, and Douglas P. Benjamin, Adapting the serial Alpgen parton-interaction generator to simulate LHC collisions on millions of parallel threads, Computer Physics Communications, 2017
Abs Bib

As the LHC moves to higher energies and luminosity, the demand for computing resources increases accordingly and will soon outpace the growth of the Worldwide LHC Computing Grid. To meet this greater demand, event generation Monte Carlo was targeted for adaptation to run on Mira, the supercomputer at the Argonne Leadership Computing Facility. Alpgen is a Monte Carlo event generation application that is used by LHC experiments in the simulation of collisions that take place in the Large Hadron Collider. This paper details the process by which Alpgen was adapted from a single-processor serial-application to a large-scale parallel-application and the performance that was achieved.
@article{ChUrLe17, author = {Childers, John T. and Uram, Thomas D. and LeCompte, Thomas J. and Papka, Michael E. and Benjamin, Douglas P.}, doi = {https://doi.org/10.1016/j.cpc.2016.09.013}, issn = {0010-4655}, journal = {Computer Physics Communications}, keywords = {Supercomputer, HEP, Simulation, Parallel}, pages = {54--59}, publisher = {North-Holland}, title = {{Adapting the serial Alpgen parton-interaction generator to simulate LHC collisions on millions of parallel threads}}, url = {https://www.sciencedirect.com/science/article/pii/S0010465516302843}, volume = {210}, year = {2017} }

J Taylor Childers, Thomas D. Uram, Doug Benjamin, Thomas J. LeCompte, and Michael E. Papka, An edge service for managing HPC workflows, In Proceedings of the Fourth International Workshop on HPC User Support Tools, 2017

Bib

@inproceedings{ChUrBe17,
  author = {Childers, J Taylor and Uram, Thomas D. and Benjamin, Doug and LeCompte, Thomas J. and Papka, Michael E.},
  booktitle = {Proceedings of the Fourth International Workshop on HPC User Support Tools},
  pages = {1--8},
  title = {An edge service for managing HPC workflows},
  year = {2017}
}

Edouard B. Brooks, Joseph Insley, Michael E. Papka, and Silvio Rizzi, Virtual reality tools for the correction of automated volume segmentation errors using dense surface reconstructions, In 2017 IEEE 7th Symposium on Large Data Analysis and Visualization (LDAV), 2017

Bib

@inproceedings{BrInPa17,
  author = {Brooks, Edouard B. and Insley, Joseph and Papka, Michael E. and Rizzi, Silvio},
  booktitle = {2017 IEEE 7th Symposium on Large Data Analysis and Visualization (LDAV)},
  organization = {IEEE},
  pages = {92--93},
  title = {Virtual reality tools for the correction of automated volume segmentation errors using dense surface reconstructions},
  year = {2017}
}

Christian Bailey, Bharat Kale, Jamieson Walker, Harish Varma Siravuri, Hamed Alhoori, and Michael E. Papka, Exploring features for predicting policy citations, In 2017 ACM/IEEE Joint Conference on Digital Libraries (JCDL), 2017

Bib

@inproceedings{BaKaWa17,
  author = {Bailey, Christian and Kale, Bharat and Walker, Jamieson and Siravuri, Harish Varma and Alhoori, Hamed and Papka, Michael E.},
  booktitle = {2017 ACM/IEEE Joint Conference on Digital Libraries (JCDL)},
  organization = {IEEE},
  pages = {1--2},
  title = {Exploring features for predicting policy citations},
  year = {2017}
}

2016

Dawid Zawislak, Brian Toonen, William Allcock, Silvio Rizzi, Joseph Insley, Venkatram Vishwanath, and Michael E. Papka, Early Investigations into using a Remote RAM Pool with the vl3 Visualization Framework, In 2016 Second Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization (ISAV), 2016

Bib

@inproceedings{ZaToAl16,
  author = {Zawislak, Dawid and Toonen, Brian and Allcock, William and Rizzi, Silvio and Insley, Joseph and Vishwanath, Venkatram and Papka, Michael E.},
  booktitle = {2016 Second Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization (ISAV)},
  organization = {IEEE},
  pages = {23--28},
  title = {{Early Investigations into using a Remote RAM Pool with the vl3 Visualization Framework}},
  year = {2016}
}

Sean Wallace, Zhou Zhou, Venkatram Vishwanath, Susan Coghlan, John Tramm, Zhiling Lan, and Michael E. Papka, Application power profiling on IBM Blue Gene/Q, Parallel Computing, 2016

Bib

@article{WaZhVi16,
  author = {Wallace, Sean and Zhou, Zhou and Vishwanath, Venkatram and Coghlan, Susan and Tramm, John and Lan, Zhiling and Papka, Michael E.},
  journal = {Parallel Computing},
  pages = {73--86},
  publisher = {North-Holland},
  title = {Application power profiling on IBM Blue Gene/Q},
  volume = {57},
  year = {2016}
}

Sean Wallace, Xu Yang, Venkatram Vishwanath, William E. Allcock, Susan Coghlan, Michael E. Papka, and Zhiling Lan, A data driven scheduling approach for power management on hpc systems, In SC’16: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, 2016

Bib

@inproceedings{WaYaVi16,
  author = {Wallace, Sean and Yang, Xu and Vishwanath, Venkatram and Allcock, William E. and Coghlan, Susan and Papka, Michael E. and Lan, Zhiling},
  booktitle = {SC'16: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis},
  organization = {IEEE},
  pages = {656--666},
  title = {A data driven scheduling approach for power management on hpc systems},
  year = {2016}
}

Will Usher, Ingo Wald, Aaron Knoll, Michael E. Papka, and Valerio Pascucci, In Situ Exploration of Particle Simulations with CPU Ray Tracing, Supercomputing Frontiers and Innovations,Oct, 2016
Abs Bib

We present a system for interactive in situ visualization of large particle simulations, suitable for general CPU-based HPC architectures. As simulations grow in scale, in situ methods are needed to alleviate IO bottlenecks and visualize data at full spatio-temporal resolution. We use a lightweight loosely-coupled layer serving distributed data from the simulation to a data-parallel renderer running in separate processes. Leveraging the OSPRay ray tracing framework for visualization and balanced P-k-d trees, we can render simulation data in real-time, as they arrive, with negligible memory overhead. This flexible solution allows users to perform exploratory in situ visualization on the same computational resources as the simulation code, on dedicated visualization clusters or remote workstations, via a standalone rendering client that can be connected or disconnected as needed. We evaluate this system on simulations with up to 227M particles in the LAMMPS and Uintah computational frameworks, and show that our approach provides many of the advantages of tightly-coupled systems, with the flexibility to render on a wide variety of remote and coprocessing resources.<br /><br />
@article{UsWaKn16, author = {Usher, Will and Wald, Ingo and Knoll, Aaron and Papka, Michael E. and Pascucci, Valerio}, bdsk-url-1 = {https://superfri.org/index.php/superfri/article/view/112}, bdsk-url-2 = {https://doi.org/10.14529/jsfi160401}, doi = {10.14529/jsfi160401}, journal = {Supercomputing Frontiers and Innovations}, month = oct, number = {4}, pages = {4--18}, title = {In Situ Exploration of Particle Simulations with CPU Ray Tracing}, url = {https://superfri.org/index.php/superfri/article/view/112}, volume = {3}, year = {2016} }

Thomas D. Uram, and Michael E. Papka, Expanding the Scope of High-Performance Computing Facilities, Computing in Science & Engineering, 2016

Bib

@article{UrPa16,
  author = {Uram, Thomas D. and Papka, Michael E.},
  journal = {Computing in Science & Engineering},
  number = {3},
  pages = {84--87},
  publisher = {IEEE},
  title = {Expanding the Scope of High-Performance Computing Facilities},
  volume = {18},
  year = {2016}
}

Min Shih, Silvio Rizzi, Joseph Insley, Thomas Uram, Venkatram Vishwanath, Mark Hereld, Michael E. Papka, and Kwan-Liu Ma, Parallel distributed, gpu-accelerated, advanced lighting calculations for large-scale volume visualization, In 2016 IEEE 6th Symposium on Large Data Analysis and Visualization (LDAV), 2016

Bib

@inproceedings{ShRiIn16,
  author = {Shih, Min and Rizzi, Silvio and Insley, Joseph and Uram, Thomas and Vishwanath, Venkatram and Hereld, Mark and Papka, Michael E. and Ma, Kwan-Liu},
  booktitle = {2016 IEEE 6th Symposium on Large Data Analysis and Visualization (LDAV)},
  organization = {IEEE},
  pages = {47--55},
  title = {Parallel distributed, gpu-accelerated, advanced lighting calculations for large-scale volume visualization},
  year = {2016}
}

Silvio Rizzi, Mark Hereld, Joseph Insley, Preeti Malakar, Michael E. Papka, Thomas Uram, and Venkatram Vishwanath, Coupling lammps and the vl3 framework for co-visualization of atomistic simulations, In 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2016

Bib

@inproceedings{RiHeIn16,
  author = {Rizzi, Silvio and Hereld, Mark and Insley, Joseph and Malakar, Preeti and Papka, Michael E. and Uram, Thomas and Vishwanath, Venkatram},
  booktitle = {2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)},
  organization = {IEEE},
  pages = {1038--1042},
  title = {Coupling lammps and the vl3 framework for co-visualization of atomistic simulations},
  year = {2016}
}

Sarah Read, and Michael E. Papka, Improving models of document cycling: Accounting for the less visible writing activities of an annual reporting process at a supercomputing facility, In 2016 IEEE International Professional Communication Conference (IPCC), 2016

Bib

@inproceedings{RePa16,
  author = {Read, Sarah and Papka, Michael E.},
  booktitle = {2016 IEEE International Professional Communication Conference (IPCC)},
  organization = {IEEE},
  pages = {1--10},
  title = {Improving models of document cycling: Accounting for the less visible writing activities of an annual reporting process at a supercomputing facility},
  year = {2016}
}

Khairi Reda, Andrew E. Johnson, Michael E. Papka, and Jason Leigh, Modeling and evaluating user behavior in exploratory visual analysis, Information Visualization, 2016

Bib

@article{ReJoPa16,
  author = {Reda, Khairi and Johnson, Andrew E. and Papka, Michael E. and Leigh, Jason},
  journal = {Information Visualization},
  number = {4},
  pages = {325--339},
  publisher = {SAGE Publications Sage UK: London, England},
  title = {Modeling and evaluating user behavior in exploratory visual analysis},
  volume = {15},
  year = {2016}
}

Paris Perdikaris, Joseph A. Insley, Leopold Grinberg, Yue Yu, Michael E. Papka, and George Em Karniadakis, Visualizing multiphysics, fluid-structure interaction phenomena in intracranial aneurysms, Parallel Computing, 2016

Bib

@article{PeInGr16,
  author = {Perdikaris, Paris and Insley, Joseph A. and Grinberg, Leopold and Yu, Yue and Papka, Michael E. and Karniadakis, George Em},
  journal = {Parallel Computing},
  pages = {9--16},
  publisher = {North-Holland},
  title = {Visualizing multiphysics, fluid-structure interaction phenomena in intracranial aneurysms},
  volume = {55},
  year = {2016}
}

Michael Papka, LSPP 2016 Keynote, In 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2016

Bib

@inproceedings{Pa16,
  author = {Papka, Michael},
  booktitle = {2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)},
  organization = {IEEE},
  pages = {1340--1340},
  title = {LSPP 2016 Keynote},
  year = {2016}
}

Preeti Malakar, Venkatram Vishwanath, Christopher Knight, Todd Munson, and Michael E. Papka, Optimal execution of co-analysis for large-scale molecular dynamics simulations, In SC’16: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, 2016

Bib

@inproceedings{MaViKn16,
  author = {Malakar, Preeti and Vishwanath, Venkatram and Knight, Christopher and Munson, Todd and Papka, Michael E.},
  booktitle = {SC'16: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis},
  organization = {IEEE},
  pages = {702--715},
  title = {Optimal execution of co-analysis for large-scale molecular dynamics simulations},
  year = {2016}
}

Thomas Marrinan, Arthur Nishimoto, Joseph A. Insley, Silvio Rizzi, Andrew Johnson, and Michael E. Papka, Interactive multi-modal display spaces for visual analysis, In Proceedings of the 2016 ACM International Conference on Interactive Surfaces and Spaces, 2016

Bib

@inproceedings{MaNiIn16,
  author = {Marrinan, Thomas and Nishimoto, Arthur and Insley, Joseph A. and Rizzi, Silvio and Johnson, Andrew and Papka, Michael E.},
  booktitle = {Proceedings of the 2016 ACM International Conference on Interactive Surfaces and Spaces},
  pages = {421--426},
  title = {Interactive multi-modal display spaces for visual analysis},
  year = {2016}
}

Si Liu, Eun-Sung Jung, Rajkumar Kettimuthu, Xian-He Sun, and Michael Papka, Towards optimizing large-scale data transfers with end-to-end integrity verification, In 2016 IEEE International Conference on Big Data (Big Data), 2016

Bib

@inproceedings{LiJuKe16,
  author = {Liu, Si and Jung, Eun-Sung and Kettimuthu, Rajkumar and Sun, Xian-He and Papka, Michael},
  booktitle = {2016 IEEE International Conference on Big Data (Big Data)},
  organization = {IEEE},
  pages = {3002--3007},
  title = {Towards optimizing large-scale data transfers with end-to-end integrity verification},
  year = {2016}
}

Jim Collins, Michael E. Papka, Beth A. Cerny, and Richard M. Coffey, 2016 Annual Report-Argonne Leadership Computing Facility, 2016

Bib

@techreport{CoPaCe16,
  author = {Collins, Jim and Papka, Michael E. and Cerny, Beth A. and Coffey, Richard M.},
  institution = {Argonne National Lab.(ANL), Argonne, IL (United States)},
  title = {2016 Annual Report-Argonne Leadership Computing Facility},
  year = {2016}
}

James R. Collins, Beth A. Cerny, Laura Wolf, Richard M. Coffey, and Michael E. Papka, 2016 ALCF Science Highlights, 2016

Bib

@techreport{CoCeWo16,
  author = {Collins, James R. and Cerny, Beth A. and Wolf, Laura and Coffey, Richard M. and Papka, Michael E.},
  institution = {Argonne National Lab.(ANL), Argonne, IL (United States)},
  title = {2016 ALCF Science Highlights},
  year = {2016}
}

Huy Bui, Eun-Sung Jung, Venkatram Vishwanath, Andrew Johnson, Jason Leigh, and Michael E. Papka, Improving sparse data movement performance using multiple paths on the Blue Gene/Q supercomputer, Parallel Computing, 2016

Bib

@article{BuJuVi16,
  author = {Bui, Huy and Jung, Eun-Sung and Vishwanath, Venkatram and Johnson, Andrew and Leigh, Jason and Papka, Michael E.},
  journal = {Parallel Computing},
  pages = {3--16},
  publisher = {North-Holland},
  title = {Improving sparse data movement performance using multiple paths on the Blue Gene/Q supercomputer},
  volume = {51},
  year = {2016}
}

Pete Beckman, Rajesh Sankaran, Charlie Catlett, Nicola Ferrier, Robert Jacob, and Michael E. Papka, Waggle: An Open Sensor Platform for Edge Computing, In 2016 IEEE SENSORS, 2016

Bib

@inproceedings{BeSaCa16,
  author = {Beckman, Pete and Sankaran, Rajesh and Catlett, Charlie and Ferrier, Nicola and Jacob, Robert and Papka, Michael E.},
  booktitle = {2016 IEEE SENSORS},
  organization = {IEEE},
  pages = {1--3},
  title = {Waggle: An Open Sensor Platform for Edge Computing},
  year = {2016}
}

2015

Li Yu, Zhou Zhou, Sean Wallace, Michael E. Papka, and Zhiling Lan, Quantitative modeling of power performance tradeoffs on extreme scale systems, Journal of Parallel and Distributed Computing, 2015

Bib

@article{YuZhWa15,
  author = {Yu, Li and Zhou, Zhou and Wallace, Sean and Papka, Michael E. and Lan, Zhiling},
  journal = {Journal of Parallel and Distributed Computing},
  pages = {1--14},
  publisher = {Academic Press},
  title = {Quantitative modeling of power performance tradeoffs on extreme scale systems},
  volume = {84},
  year = {2015}
}

Sean Wallace, Venkatram Vishwanath, Susan Coghlan, Zhiling Lan, and Michael E. Papka, Comparison of vendor supplied environmental data collection mechanisms, In 2015 IEEE International Conference on Cluster Computing, 2015

Bib

@inproceedings{WaViCo15,
  author = {Wallace, Sean and Vishwanath, Venkatram and Coghlan, Susan and Lan, Zhiling and Papka, Michael E.},
  booktitle = {2015 IEEE International Conference on Cluster Computing},
  organization = {IEEE},
  pages = {690--697},
  year = {2015}
}

Ingo Wald, Aaron Knoll, Gregory P. Johnson, Will Usher, Valerio Pascucci, and Michael E. Papka, CPU ray tracing large particle data with balanced Pkd trees, In 2015 IEEE Scientific Visualization Conference (SciVis), 2015

Bib

@inproceedings{WaKnJo15,
  author = {Wald, Ingo and Knoll, Aaron and Johnson, Gregory P. and Usher, Will and Pascucci, Valerio and Papka, Michael E.},
  booktitle = {2015 IEEE Scientific Visualization Conference (SciVis)},
  organization = {IEEE},
  pages = {57--64},
  title = {CPU ray tracing large particle data with balanced Pkd trees},
  year = {2015}
}

Thomas D. Uram, J. Taylor Childers, Thomas J. LeCompte, Michael E. Papka, and Doug Benjamin, Achieving production-level use of HEP software at the Argonne Leadership Computing Facility, In Journal of Physics: Conference Series, 2015

Bib

@inproceedings{UrChLe15,
  author = {Uram, Thomas D. and Childers, J. Taylor and LeCompte, Thomas J. and Papka, Michael E. and Benjamin, Doug},
  booktitle = {Journal of Physics: Conference Series},
  number = {6},
  organization = {IOP Publishing},
  pages = {062063},
  title = {Achieving production-level use of HEP software at the Argonne Leadership Computing Facility},
  volume = {664},
  year = {2015}
}

Silvio Rizzi, Mark Hereld, Joseph Insley, Michael E. Papka, Thomas Uram, and Venkatram Vishwanath, Large-scale parallel visualization of particle-based simulations using point sprites and level-of-detail, In Proceedings of the 15th Eurographics Symposium on Parallel Graphics and Visualization, 2015

Bib

@inproceedings{RiHeIn15b,
  author = {Rizzi, Silvio and Hereld, Mark and Insley, Joseph and Papka, Michael E. and Uram, Thomas and Vishwanath, Venkatram},
  booktitle = {Proceedings of the 15th Eurographics Symposium on Parallel Graphics and Visualization},
  pages = {1--10},
  title = {Large-scale parallel visualization of particle-based simulations using point sprites and level-of-detail},
  year = {2015}
}

Silvio Rizzi, Mark Hereld, Joseph Insley, Michael E. Papka, Thomas Uram, and Venkatram Vishwanath, Large-scale co-visualization for LAMMPS using vl3, In 2015 IEEE 5th Symposium on Large Data Analysis and Visualization (LDAV), 2015

Bib

@inproceedings{RiHeIn15a,
  author = {Rizzi, Silvio and Hereld, Mark and Insley, Joseph and Papka, Michael E. and Uram, Thomas and Vishwanath, Venkatram},
  booktitle = {2015 IEEE 5th Symposium on Large Data Analysis and Visualization (LDAV)},
  organization = {IEEE},
  pages = {141--142},
  title = {Large-scale co-visualization for LAMMPS using vl3},
  year = {2015}
}

Khairi Reda, Andrew E. Johnson, Michael E. Papka, and Jason Leigh, Effects of display size and resolution on user behavior and insight acquisition in visual exploration, In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, 2015

Bib

@inproceedings{ReJoPa15,
  author = {Reda, Khairi and Johnson, Andrew E. and Papka, Michael E. and Leigh, Jason},
  booktitle = {Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems},
  pages = {2759--2768},
  title = {Effects of display size and resolution on user behavior and insight acquisition in visual exploration},
  year = {2015}
}

Khairi Reda, Alberto González, Jason Leigh, and Michael E. Papka, Tell me what do you see: Detecting perceptually-separable visual patterns via clustering of image-space features in visualizations, In 2015 IEEE Conference on Visual Analytics Science and Technology (VAST), 2015

Bib

@inproceedings{ReGoLe15,
  author = {Reda, Khairi and Gonz{\'a}lez, Alberto and Leigh, Jason and Papka, Michael E.},
  booktitle = {2015 IEEE Conference on Visual Analytics Science and Technology (VAST)},
  organization = {IEEE},
  pages = {211--212},
  title = {Tell me what do you see: Detecting perceptually-separable visual patterns via clustering of image-space features in visualizations},
  year = {2015}
}

Preeti Malakar, Venkatram Vishwanath, Todd Munson, Christopher Knight, Mark Hereld, Sven Leyffer, and Michael E. Papka, Optimal scheduling of in-situ analysis for large-scale scientific simulations, In SC’15: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, 2015

Bib

@inproceedings{MaViMu15,
  author = {Malakar, Preeti and Vishwanath, Venkatram and Munson, Todd and Knight, Christopher and Hereld, Mark and Leyffer, Sven and Papka, Michael E.},
  booktitle = {SC'15: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis},
  organization = {IEEE},
  pages = {1--11},
  title = {Optimal scheduling of in-situ analysis for large-scale scientific simulations},
  year = {2015}
}

Jie Jiang, Mark Hereld, Joseph Insley, Michael E. Papka, Silvio Rizzi, Thomas Uram, and Venkatram Vishwanath, Streaming ultra high resolution images to large tiled display at nearly interactive frame rate with vl3, In 2015 IEEE 5th Symposium on Large Data Analysis and Visualization (LDAV), 2015

Bib

@inproceedings{JiHeIn15,
  author = {Jiang, Jie and Hereld, Mark and Insley, Joseph and Papka, Michael E. and Rizzi, Silvio and Uram, Thomas and Vishwanath, Venkatram},
  booktitle = {2015 IEEE 5th Symposium on Large Data Analysis and Visualization (LDAV)},
  organization = {IEEE},
  pages = {133--134},
  title = {Streaming ultra high resolution images to large tiled display at nearly interactive frame rate with vl3},
  year = {2015}
}

James J. Hack, and Michael E. Papka, Big data: Next-generation machines for big science, Computing in Science & Engineering, 2015

Bib

@article{HaPa15,
  author = {Hack, James J. and Papka, Michael E.},
  journal = {Computing in Science & Engineering},
  number = {4},
  pages = {63--65},
  publisher = {IEEE},
  title = {Big data: Next-generation machines for big science},
  volume = {17},
  year = {2015}
}

Attila Gyulassy, Aaron Knoll, Kah Chun Lau, Bei Wang, Peer-Timo Bremer, Michael E. Papka, Larry A. Curtiss, and Valerio Pascucci, Interstitial and interlayer ion diffusion geometry extraction in graphitic nanosphere battery materials, IEEE transactions on visualization and computer graphics, 2015

Bib

@article{GyKnLa15b,
  author = {Gyulassy, Attila and Knoll, Aaron and Lau, Kah Chun and Wang, Bei and Bremer, Peer-Timo and Papka, Michael E. and Curtiss, Larry A. and Pascucci, Valerio},
  journal = {IEEE transactions on visualization and computer graphics},
  number = {1},
  pages = {916--925},
  publisher = {IEEE},
  title = {Interstitial and interlayer ion diffusion geometry extraction in graphitic nanosphere battery materials},
  volume = {22},
  year = {2015}
}

Attila Gyulassy, Aaron Knoll, Kah Chun Lau, Bei Wang, Peer-Timo Bremer, Michael E. Papka, Larry A. Curtiss, and Valerio Pascucci, Morse-smale analysis of ion diffusion in ab initio battery materials simulations, In Topological Methods in Data Analysis and Visualization, 2015

Bib

@inproceedings{GyKnLa15a,
  author = {Gyulassy, Attila and Knoll, Aaron and Lau, Kah Chun and Wang, Bei and Bremer, Peer-Timo and Papka, Michael E. and Curtiss, Larry A. and Pascucci, Valerio},
  booktitle = {Topological Methods in Data Analysis and Visualization},
  organization = {Springer, Cham},
  pages = {135--149},
  title = {Morse-smale analysis of ion diffusion in ab initio battery materials simulations},
  year = {2015}
}

J. Taylor Childers, Thomas D. Uram, Thomas J. LeCompte, Michael E. Papka, and Douglas P. Benjamin, Simulation of LHC events on a millions threads, In Journal of Physics: Conference Series, 2015

Bib

@inproceedings{ChUrLe15,
  author = {Childers, J. Taylor and Uram, Thomas D. and LeCompte, Thomas J. and Papka, Michael E. and Benjamin, Douglas P.},
  booktitle = {Journal of Physics: Conference Series},
  number = {9},
  organization = {IOP Publishing},
  pages = {092006},
  title = {Simulation of LHC events on a millions threads},
  volume = {664},
  year = {2015}
}

Huy Bui, Preeti Malakar, Venkatram Vishwanath, Todd S. Munson, Eun-Sung Jung, Andrew Johnson, Michael E. Papka, and Jason Leigh, Improving communication throughput by multipath load balancing on Blue Gene/Q, In 2015 IEEE 22nd International Conference on High Performance Computing (HiPC), 2015

Bib

@inproceedings{BuMaVi15,
  author = {Bui, Huy and Malakar, Preeti and Vishwanath, Venkatram and Munson, Todd S. and Jung, Eun-Sung and Johnson, Andrew and Papka, Michael E. and Leigh, Jason},
  booktitle = {2015 IEEE 22nd International Conference on High Performance Computing (HiPC)},
  organization = {IEEE},
  pages = {115--124},
  title = {Improving communication throughput by multipath load balancing on Blue Gene/Q},
  year = {2015}
}

Huy Bui, Robert Jacob, Preeti Malakar, Venkatram Viswanath, Andrew Johnson, Micheal E. Papka, and Jason Leigh, Multipath Load Balancing for M\times N Communication Patterns on the Blue Gene/Q Supercomputer Interconnection Network, In 2015 IEEE International Conference on Cluster Computing, 2015

Bib

@inproceedings{BuJaMa15,
  author = {Bui, Huy and Jacob, Robert and Malakar, Preeti and Viswanath, Venkatram and Johnson, Andrew and Papka, Micheal E. and Leigh, Jason},
  booktitle = {2015 IEEE International Conference on Cluster Computing},
  organization = {IEEE},
  pages = {833--840},
  title = {Multipath Load Balancing for M$\times$ N Communication Patterns on the Blue Gene/Q Supercomputer Interconnection Network},
  year = {2015}
}

2014

Venkatram Vishwanath, Huy Bui, Mark Hereld, and Michael E. Papka, Glean, In High Performance Parallel I/O, 2014

Bib

@incollection{ViBuHe14,
  author = {Vishwanath, Venkatram and Bui, Huy and Hereld, Mark and Papka, Michael E.},
  booktitle = {High Performance Parallel I/O},
  pages = {257--266},
  publisher = {Chapman and Hall/CRC},
  title = {Glean},
  year = {2014}
}

Silvio Rizzi, Mark Hereld, Joseph Insley, Michael E. Papka, Thomas Uram, and Venkatram Vishwanath, Performance modeling of vl3 volume rendering on GPU-based clusters, In Proceedings of the 14th Eurographics Symposium on Parallel Graphics and Visualization, 2014

Bib

@inproceedings{RiHeIn14,
  author = {Rizzi, Silvio and Hereld, Mark and Insley, Joseph and Papka, Michael E. and Uram, Thomas and Vishwanath, Venkatram},
  booktitle = {Proceedings of the 14th Eurographics Symposium on Parallel Graphics and Visualization},
  pages = {65--72},
  title = {Performance modeling of vl3 volume rendering on GPU-based clusters},
  year = {2014}
}

Sarah Read, and Michael E. Papka, Genre cycling: The infrastructural function of an operational assessment review and reporting process at a federal scientific supercomputing user facility, In Proceedings of the 32nd ACM International Conference on The Design of Communication CD-ROM, 2014

Bib

@inproceedings{RePa14,
  author = {Read, Sarah and Papka, Michael E.},
  booktitle = {Proceedings of the 32nd ACM International Conference on The Design of Communication CD-ROM},
  pages = {1--8},
  title = {Genre cycling: The infrastructural function of an operational assessment review and reporting process at a federal scientific supercomputing user facility},
  year = {2014}
}

Khairi Reda, Andrew E. Johnson, Jason Leigh, and Michael E. Papka, Evaluating user behavior and strategy during visual exploration, In Proceedings of the Fifth Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization, 2014

Bib

@inproceedings{ReJoLe14,
  author = {Reda, Khairi and Johnson, Andrew E. and Leigh, Jason and Papka, Michael E.},
  booktitle = {Proceedings of the Fifth Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization},
  pages = {41--45},
  title = {Evaluating user behavior and strategy during visual exploration},
  year = {2014}
}

Phil Lindner, Adolfo Rodriguez, Thomas D. Uram, Michael E. Papka, and Michael Papka, Augmenting views on large format displays with tablets, In Proceedings of the 2nd ACM symposium on Spatial user interaction, 2014

Bib

@inproceedings{LiRoUr14,
  author = {Lindner, Phil and Rodriguez, Adolfo and Uram, Thomas D. and Papka, Michael E. and Papka, Michael},
  booktitle = {Proceedings of the 2nd ACM symposium on Spatial user interaction},
  pages = {161--161},
  title = {Augmenting views on large format displays with tablets},
  year = {2014}
}

Sriram Lakshminarasimhan, Xiaocheng Zou, David A. Boyuka, Saurabh V. Pendse, John Jenkins, Venkatram Vishwanath, Michael E. Papka, Scott Klasky, and Nagiza F. Samatova, DIRAQ: scalable in situ data-and resource-aware indexing for optimized query performance, Cluster computing, 2014

Bib

@article{LaZoBo14,
  author = {Lakshminarasimhan, Sriram and Zou, Xiaocheng and Boyuka, David A. and Pendse, Saurabh V. and Jenkins, John and Vishwanath, Venkatram and Papka, Michael E. and Klasky, Scott and Samatova, Nagiza F.},
  journal = {Cluster computing},
  number = {4},
  pages = {1101--1119},
  publisher = {Springer US},
  title = {DIRAQ: scalable in situ data-and resource-aware indexing for optimized query performance},
  volume = {17},
  year = {2014}
}

Aaron Knoll, Ingo Wald, Paul Navratil, Anne Bowen, Khairi Reda, Michael E. Papka, and Kelly Gaither, RBF volume ray casting on multicore and manycore CPUs, In Computer Graphics Forum, 2014

Bib

@inproceedings{KnWaNa14,
  author = {Knoll, Aaron and Wald, Ingo and Navratil, Paul and Bowen, Anne and Reda, Khairi and Papka, Michael E. and Gaither, Kelly},
  booktitle = {Computer Graphics Forum},
  number = {3},
  pages = {71--80},
  title = {RBF volume ray casting on multicore and manycore CPUs},
  volume = {33},
  year = {2014}
}

James J. Hack, and Michael E. Papka, New Frontiers in Leadership Computing Part II[Guest Editorial], Computing in Science & Engineering, 2014

Bib

@article{HaPa14b,
  author = {Hack, James J. and Papka, Michael E.},
  journal = {Computing in Science & Engineering},
  number = {06},
  pages = {10--12},
  publisher = {IEEE},
  title = {New Frontiers in Leadership Computing Part II[Guest Editorial]},
  volume = {16},
  year = {2014}
}

James J. Hack, and Michael E. Papka, New Frontiers in Leadership Computing Part II[Guest Editorial], Computing in Science & Engineering, 2014

Bib

@article{HaPa14a,
  author = {Hack, James J. and Papka, Michael E.},
  journal = {Computing in Science & Engineering},
  number = {05},
  pages = {10--12},
  publisher = {IEEE},
  title = {New Frontiers in Leadership Computing Part II[Guest Editorial]},
  volume = {16},
  year = {2014}
}

Huy Bui, Jason Leigh, Eun-Sung Jungy, Venkatram Vishwanathy, and Michael E. Papka, Improving data movement performance for sparse data patterns on the blue gene/q supercomputer, In 2014 43rd International Conference on Parallel Processing Workshops, 2014

Bib

@inproceedings{BuLeJu14,
  author = {Bui, Huy and Leigh, Jason and Jungy, Eun-Sung and Vishwanathy, Venkatram and Papka, Michael E.},
  booktitle = {2014 43rd International Conference on Parallel Processing Workshops},
  organization = {IEEE},
  pages = {302--311},
  title = {Improving data movement performance for sparse data patterns on the blue gene/q supercomputer},
  year = {2014}
}

Huy Bui, Hal Finkel, Venkatram Vishwanath, Salma Habib, Katrin Heitmann, Jason Leigh, Michael Papka, and Kevin Harms, Scalable parallel I/O on a Blue Gene/Q supercomputer using compression, topology-aware data aggregation, and subfiling, In 2014 22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, 2014

Bib

@inproceedings{BuFiVi14,
  author = {Bui, Huy and Finkel, Hal and Vishwanath, Venkatram and Habib, Salma and Heitmann, Katrin and Leigh, Jason and Papka, Michael and Harms, Kevin},
  booktitle = {2014 22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing},
  organization = {IEEE},
  pages = {107--111},
  title = {Scalable parallel I/O on a Blue Gene/Q supercomputer using compression, topology-aware data aggregation, and subfiling},
  year = {2014}
}

Eduardo Berrocal, Li Yu, Sean Wallace, Michael E. Papka, and Zhiling Lan, Exploring void search for fault detection on extreme scale systems, In 2014 IEEE International Conference on Cluster Computing (CLUSTER), 2014

Bib

@inproceedings{BeYuWa14,
  author = {Berrocal, Eduardo and Yu, Li and Wallace, Sean and Papka, Michael E. and Lan, Zhiling},
  booktitle = {2014 IEEE International Conference on Cluster Computing (CLUSTER)},
  organization = {IEEE},
  pages = {1--9},
  title = {Exploring void search for fault detection on extreme scale systems},
  year = {2014}
}

2013

Xu Yang, Zhou Zhou, Sean Wallace, Zhiling Lan, Wei Tang, Susan Coghlan, and Michael E. Papka, Integrating dynamic pricing of electricity into energy aware scheduling for HPC systems, In SC’13: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, 2013

Bib

@inproceedings{YaZhWa13,
  author = {Yang, Xu and Zhou, Zhou and Wallace, Sean and Lan, Zhiling and Tang, Wei and Coghlan, Susan and Papka, Michael E.},
  booktitle = {SC'13: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis},
  organization = {IEEE},
  pages = {1--11},
  title = {Integrating dynamic pricing of electricity into energy aware scheduling for HPC systems},
  year = {2013}
}

Sean Wallace, Venkatram Vishwanath, Susan Coghlan, Zhiling Lan, and Michael E. Papka, Measuring power consumption on IBM Blue Gene/Q, In 2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum, 2013

Bib

@inproceedings{WaViCo13,
  author = {Wallace, Sean and Vishwanath, Venkatram and Coghlan, Susan and Lan, Zhiling and Papka, Michael E.},
  booktitle = {2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum},
  organization = {IEEE},
  pages = {853--859},
  title = {Measuring power consumption on IBM Blue Gene/Q},
  year = {2013}
}

Eric R. Schendel, Steve Harenberg, Houjun Tang, Venkatram Vishwanath, Michael E. Papka, and Nagiza F. Samatova, A generic high-performance method for deinterleaving scientific data, In European Conference on Parallel Processing, 2013

Bib

@inproceedings{ScHaTa13,
  author = {Schendel, Eric R. and Harenberg, Steve and Tang, Houjun and Vishwanath, Venkatram and Papka, Michael E. and Samatova, Nagiza F.},
  booktitle = {European Conference on Parallel Processing},
  organization = {Springer, Berlin, Heidelberg},
  pages = {571--582},
  title = {A generic high-performance method for deinterleaving scientific data},
  year = {2013}
}

Khairi Reda, Aaron Knoll, Ken-ichi Nomura, Michael E. Papka, Andrew E. Johnson, and Jason Leigh, Visualizing large-scale atomistic simulations in ultra-resolution immersive environments., In LDAV, 2013

Bib

@inproceedings{ReKnNo13,
  author = {Reda, Khairi and Knoll, Aaron and Nomura, Ken-ichi and Papka, Michael E. and Johnson, Andrew E. and Leigh, Jason},
  booktitle = {LDAV},
  pages = {59--65},
  title = {Visualizing large-scale atomistic simulations in ultra-resolution immersive environments.},
  year = {2013}
}

Khairi Reda, Alessandro Febretti, Aaron Knoll, Jillian Aurisano, Jason Leigh, Andrew Johnson, Michael E. Papka, and Mark Hereld, Visualizing large, heterogeneous data in hybrid-reality environments, IEEE Computer Graphics and Applications, 2013

Bib

@article{ReFeKn13,
  author = {Reda, Khairi and Febretti, Alessandro and Knoll, Aaron and Aurisano, Jillian and Leigh, Jason and Johnson, Andrew and Papka, Michael E. and Hereld, Mark},
  journal = {IEEE Computer Graphics and Applications},
  number = {4},
  pages = {38--48},
  publisher = {IEEE},
  title = {Visualizing large, heterogeneous data in hybrid-reality environments},
  volume = {33},
  year = {2013}
}

Michael Papka, Susan Coghlan, Eric Isaacs, Mark Peters, and Paul Messina, Mira: Argonne’s 10-petaflops supercomputer, 2013

Bib

@techreport{PaCoIs13,
  author = {Papka, Michael and Coghlan, Susan and Isaacs, Eric and Peters, Mark and Messina, Paul},
  institution = {Argonne National Lab.(ANL), Argonne, IL (United States)},
  title = {Mira: Argonne's 10-petaflops supercomputer},
  year = {2013}
}

Vitali Morozov, Jiayuan Meng, Venkatram Vishwanath, Kalyan Kumaran, and Michael E. Papka, Characterization and Understanding Machine-Specific Interconnects, In International Conference on Parallel Computing Technologies, 2013

Bib

@inproceedings{MoMeVi13,
  author = {Morozov, Vitali and Meng, Jiayuan and Vishwanath, Venkatram and Kumaran, Kalyan and Papka, Michael E.},
  booktitle = {International Conference on Parallel Computing Technologies},
  organization = {Springer, Berlin, Heidelberg},
  pages = {90--104},
  title = {Characterization and Understanding Machine-Specific Interconnects},
  year = {2013}
}

Vitali Morozov, Kalyan Kumaran, Venkatram Vishwanath, Jiayuan Meng, and Michael E. Papka, Early experience on the Blue Gene/Q supercomputing system, In 2013 IEEE 27th International Symposium on Parallel and Distributed Processing, 2013

Bib

@inproceedings{MoKuVi13,
  author = {Morozov, Vitali and Kumaran, Kalyan and Vishwanath, Venkatram and Meng, Jiayuan and Papka, Michael E.},
  booktitle = {2013 IEEE 27th International Symposium on Parallel and Distributed Processing},
  organization = {IEEE},
  pages = {1229--1240},
  title = {Early experience on the Blue Gene/Q supercomputing system},
  year = {2013}
}

Nick Leaf, Venkatram Vishwanath, Joseph Insley, Mark Hereld, Michael E. Papka, and Kwan-Liu Ma, Efficient parallel volume rendering of large-scale adaptive mesh refinement data, In 2013 IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV), 2013

Bib

@inproceedings{LeViIn13,
  author = {Leaf, Nick and Vishwanath, Venkatram and Insley, Joseph and Hereld, Mark and Papka, Michael E. and Ma, Kwan-Liu},
  booktitle = {2013 IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV)},
  organization = {IEEE},
  pages = {35--42},
  title = {Efficient parallel volume rendering of large-scale adaptive mesh refinement data},
  year = {2013}
}

Sriram Lakshminarasimhan, David A. Boyuka, Saurabh V. Pendse, Xiaocheng Zou, John Jenkins, Venkatram Vishwanath, Michael E. Papka, and Nagiza F. Samatova, Scalable in situ scientific data encoding for analytical query processing, In Proceedings of the 22nd international symposium on High-performance parallel and distributed computing, 2013

Bib

@inproceedings{LaBoPe13,
  author = {Lakshminarasimhan, Sriram and Boyuka, David A. and Pendse, Saurabh V. and Zou, Xiaocheng and Jenkins, John and Vishwanath, Venkatram and Papka, Michael E. and Samatova, Nagiza F.},
  booktitle = {Proceedings of the 22nd international symposium on High-performance parallel and distributed computing},
  pages = {1--12},
  title = {Scalable in situ scientific data encoding for analytical query processing},
  year = {2013}
}

Sidharth Kumar, Avishek Saha, Venkatram Vishwanath, Philip Carns, John A. Schmidt, Giorgio Scorzelli, Hemanth Kolla, Ray Grout, Robert Latham, Robert Ross, Michael E. Papka, Jacqueline Chen, and Valerio Pascucci, Characterization and modeling of PIDX parallel I/O for performance optimization, In SC ’13: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, 2013

Bib

@inproceedings{KuSaVi13,
  author = {Kumar, Sidharth and Saha, Avishek and Vishwanath, Venkatram and Carns, Philip and Schmidt, John A. and Scorzelli, Giorgio and Kolla, Hemanth and Grout, Ray and Latham, Robert and Ross, Robert and Papka, Michael E. and Chen, Jacqueline and Pascucci, Valerio},
  booktitle = {SC '13: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis},
  doi = {10.1145/2503210.2503252},
  pages = {1-12},
  title = {Characterization and modeling of PIDX parallel I/O for performance optimization},
  year = {2013}
}

Aaron Knoll, Ingo Wald, Paul A. Navrátil, Michael E. Papka, and Kelly P. Gaither, Ray tracing and volume rendering large molecular data on multi-core and many-core architectures, In Proceedings of the 8th International Workshop on Ultrascale Visualization, 2013

Bib

@inproceedings{KnWaNa13,
  author = {Knoll, Aaron and Wald, Ingo and Navr{\'a}til, Paul A. and Papka, Michael E. and Gaither, Kelly P.},
  booktitle = {Proceedings of the 8th International Workshop on Ultrascale Visualization},
  pages = {1--8},
  title = {Ray tracing and volume rendering large molecular data on multi-core and many-core architectures},
  year = {2013}
}

Aaron Knoll, Maria KY Chan, Kah Chun Lau, Bin Liu, Jeffrey Greeley, Larry Curtiss, Mark Hereld, and Michael E. Papka, Uncertainty Classification And Visualization Of Molecular Interfaces, International Journal for Uncertainty Quantification, 2013

Bib

@article{KnChLa13,
  author = {Knoll, Aaron and Chan, Maria KY and Lau, Kah Chun and Liu, Bin and Greeley, Jeffrey and Curtiss, Larry and Hereld, Mark and Papka, Michael E.},
  journal = {International Journal for Uncertainty Quantification},
  number = {2},
  title = {Uncertainty Classification And Visualization Of Molecular Interfaces},
  volume = {3},
  year = {2013}
}

Nicholas T. Karonis, Kirk L. Duffin, Caesar E. Ordoñez, Bela Erdelyi, Thomas D. Uram, Eric C. Olson, George Coutrakon, and Michael E. Papka, Distributed and hardware accelerated computing for clinical medical imaging using proton computed tomography (pCT), Journal of Parallel and Distributed Computing, 2013

Bib

@article{KaDuOr13,
  author = {Karonis, Nicholas T. and Duffin, Kirk L. and Ordo{\~n}ez, Caesar E. and Erdelyi, Bela and Uram, Thomas D. and Olson, Eric C. and Coutrakon, George and Papka, Michael E.},
  journal = {Journal of Parallel and Distributed Computing},
  number = {12},
  pages = {1605--1612},
  publisher = {Academic Press},
  title = {Distributed and hardware accelerated computing for clinical medical imaging using proton computed tomography (pCT)},
  volume = {73},
  year = {2013}
}

Leopold Grinberg, Vitali Morozov, Dmitry A. Fedosov, Joseph Insley, Michael Papka, Kalyan Kumaran, and George Karniadakis, Multiscale simulation of blood flow in brain arteries with an aneurysm, 2013

Bib

@techreport{GrMoFe13,
  author = {Grinberg, Leopold and Morozov, Vitali and Fedosov, Dmitry A. and Insley, Joseph and Papka, Michael and Kumaran, Kalyan and Karniadakis, George},
  institution = {Argonne National Lab.(ANL), Argonne, IL (United States)},
  title = {Multiscale simulation of blood flow in brain arteries with an aneurysm},
  year = {2013}
}

Richard M. Coffey, Beth A. Cerny, James R. Collins, Ahn Chel Heinzel, John J. Spizzirri, Laura K. Wolf, Paul C. Messina, Michael E. Papka, and Katherine M. Riley, Argonne Leadership Computing Facility 2013 Science Highlights, 2013

Bib

@techreport{CoCeCo13,
  author = {Coffey, Richard M. and Cerny, Beth A. and Collins, James R. and Heinzel, Ahn Chel and Spizzirri, John J. and Wolf, Laura K. and Messina, Paul C. and Papka, Michael E. and Riley, Katherine M.},
  institution = {Argonne National Laboratory (ANL), Argonne, IL (United States)},
  title = {Argonne Leadership Computing Facility 2013 Science Highlights},
  year = {2013}
}

Anna Maria Bailey, Adam Bertsch, Barna Bihari, Brian Carnes, Kimberly Cupps, Erik W. Draeger, Larry Fried, Mark Gary, James N. Glosli, John C. Gyllenhaal, Steven Langer, Rose McCallen, Arthur A. Mirin, Fady Najjar, Albert Nichols, Terri Quinn, David Richards, Tom Spelce, Becky Springmeyer, Fred Streitz, Bronis Supinski, Pavlos Vranas, Dong Chen, George L.T. Chiu, Paul W. Coteus, Thomas W. Fox, Thomas Gooding, John A. Gunnels, Ruud A. Haring, Philip Heidelberger, Todd Inglett, Kyu-hyoun Kim, Amith R. Mamidala, Sam Miller, Mike Nelson, Martin Ohmacht, Fabrizio Petrini, Kyung Dong Ryu, Andrew A. Schram, Robert Shearer, Robert E. Walkup, Amy Wang, Robert W. Wisniewski, William E. Allcock, Charles Bacon, Raymond Bair, Ramesh Balakrishnan, Richard Coffey, Susan Coghlan, Jeff Hammond, Mark Hereld, Kalyan Kumaran, Paul Messina, Vitali Morozov, Michael E. Papka, Katherine M. Riley, Nichols A. Romero, and Timothy J. Williams, Blue Gene/Q: Sequoia and Mira, In Contemporary High Performance Computing, 2013

Bib

@incollection{BaBeBi13,
  author = {Bailey, Anna Maria and Bertsch, Adam and Bihari, Barna and Carnes, Brian and Cupps, Kimberly and Draeger, Erik W. and Fried, Larry and Gary, Mark and Glosli, James N. and Gyllenhaal, John C. and Langer, Steven and McCallen, Rose and Mirin, Arthur A. and Najjar, Fady and Nichols, Albert and Quinn, Terri and Richards, David and Spelce, Tom and Springmeyer, Becky and Streitz, Fred and de Supinski, Bronis and Vranas, Pavlos and Chen, Dong and Chiu, George L.T. and Coteus, Paul W. and Fox, Thomas W. and Gooding, Thomas and Gunnels, John A. and Haring, Ruud A. and Heidelberger, Philip and Inglett, Todd and Kim, Kyu-hyoun and Mamidala, Amith R. and Miller, Sam and Nelson, Mike and Ohmacht, Martin and Petrini, Fabrizio and Ryu, Kyung Dong and Schram, Andrew A. and Shearer, Robert and Walkup, Robert E. and Wang, Amy and Wisniewski, Robert W. and Allcock, William E. and Bacon, Charles and Bair, Raymond and Balakrishnan, Ramesh and Coffey, Richard and Coghlan, Susan and Hammond, Jeff and Hereld, Mark and Kumaran, Kalyan and Messina, Paul and Morozov, Vitali and Papka, Michael E. and Riley, Katherine M. and Romero, Nichols A. and Williams, Timothy J.},
  booktitle = {Contemporary High Performance Computing},
  pages = {225--281},
  publisher = {Chapman and Hall/CRC},
  title = {Blue Gene/Q: Sequoia and Mira},
  year = {2013}
}

2012

David P. Schissel, Geni Abla, Justin R. Burruss, Elliot Feibush, Thomas W. Fredian, Monte M. Goode, Martin J. Greenwald, Katarzyna Keahey, Torrance Leggett, Kai Li, Doug C. McCune, Michael E. Papka, Lew Randerson, Allen Sanderson, Joshua Stillerman, Mary R. Thompson, Thomas Uram, and Grant Wallace, A National Collaboratory to Advance the Science of High Temperature Plasma Physics for Magnetic Fusion, 2012

Bib

@techreport{ScAbBu12,
  author = {Schissel, David P. and Abla, Geni and Burruss, Justin R. and Feibush, Elliot and Fredian, Thomas W. and Goode, Monte M. and Greenwald, Martin J. and Keahey, Katarzyna and Leggett, Torrance and Li, Kai and McCune, Doug C. and Papka, Michael E. and Randerson, Lew and Sanderson, Allen and Stillerman, Joshua and Thompson, Mary R. and Uram, Thomas and Wallace, Grant},
  institution = {General Atomics, CA (United States)},
  number = {GA–A25540 Rev. 1},
  title = {A National Collaboratory to Advance the Science of High Temperature Plasma Physics for Magnetic Fusion},
  year = {2012}
}

M. E. Papka, P Messina, R Coffey, and C Drugan, Argonne Leadership Computing Facility 2011 annual report: Shaping future supercomputing., 2012

Bib

@techreport{PaMeCo12,
  author = {Papka, M. E. and Messina, P and Coffey, R and Drugan, C},
  institution = {Argonne National Laboratory (ANL)},
  title = {Argonne Leadership Computing Facility 2011 annual report: Shaping future supercomputing.},
  year = {2012}
}

Vitali Morozov, Jiayuan Meng, Venkatram Vishwanath, Jeff R. Hammond, Kalyan Kumaran, and Michael E. Papka, ALCF MPI benchmarks: Understanding machine-specific communication behavior, In 2012 41st International Conference on Parallel Processing Workshops, 2012

Bib

@inproceedings{MoMeVi12,
  author = {Morozov, Vitali and Meng, Jiayuan and Vishwanath, Venkatram and Hammond, Jeff R. and Kumaran, Kalyan and Papka, Michael E.},
  booktitle = {2012 41st International Conference on Parallel Processing Workshops},
  organization = {IEEE},
  pages = {19--28},
  title = {ALCF MPI benchmarks: Understanding machine-specific communication behavior},
  year = {2012}
}

Shusen Liu, Venkatram Vishwanath, Joseph Insley, Mark Hereld, Michael E. Papka, and Valerio Pascucci, A Static Load Balancing Scheme for Parallel Volume Rendering on Multi-GPU Clusters, In Large-Scale Data Analysis and Visualization (LDAV), 2012 IEEE Symposium on, 2012

Bib

@inproceedings{LiViIn12,
  author = {Liu, Shusen and Vishwanath, Venkatram and Insley, Joseph and Hereld, Mark and Papka, Michael E. and Pascucci, Valerio},
  booktitle = {Large-Scale Data Analysis and Visualization (LDAV), 2012 IEEE Symposium on},
  title = {A Static Load Balancing Scheme for Parallel Volume Rendering on Multi-GPU Clusters},
  year = {2012}
}

Sidharth Kumar, Venkatram Vishwanath, Philip Carns, Joshua A. Levine, Robert Latham, Giorgio Scorzelli, Hemanth Kolla, Ray Grout, Robert Ross, Michael E. Papka, Jacqueline Chen, and Valerio Pascucci, Efficient data restructuring and aggregation for I/O acceleration in PIDX, In SC ’12: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, 2012

Bib

@inproceedings{KuViCa12,
  author = {Kumar, Sidharth and Vishwanath, Venkatram and Carns, Philip and Levine, Joshua A. and Latham, Robert and Scorzelli, Giorgio and Kolla, Hemanth and Grout, Ray and Ross, Robert and Papka, Michael E. and Chen, Jacqueline and Pascucci, Valerio},
  booktitle = {SC '12: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis},
  doi = {10.1109/SC.2012.54},
  pages = {1-11},
  title = {Efficient data restructuring and aggregation for I/O acceleration in PIDX},
  year = {2012}
}

Natallia Kotava, Aaron Knoll, Mathias Schott, Christoph Garth, Xavier Tricoche, Christoph Kessler, Elaine Cohen, Charles D. Hansen, Michael E. Papka, and Hans Hagen, Volume rendering with multidimensional peak finding, In 2012 IEEE Pacific Visualization Symposium, 2012

Bib

@inproceedings{KoKnSc12,
  author = {Kotava, Natallia and Knoll, Aaron and Schott, Mathias and Garth, Christoph and Tricoche, Xavier and Kessler, Christoph and Cohen, Elaine and Hansen, Charles D. and Papka, Michael E. and Hagen, Hans},
  booktitle = {2012 IEEE Pacific Visualization Symposium},
  organization = {IEEE},
  pages = {161--168},
  title = {Volume rendering with multidimensional peak finding},
  year = {2012}
}

Aaron Knoll, Joe Insley, Michael E. Papka, Ken-ichi Nomura, Rajiv K. Kalia, Aiichiro Nakano, and Priya Vashishta, Molecular Dynamics Simulation of Amorphous SiO2 Fracture, In 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, 2012

Bib

@inproceedings{KnInPa12,
  author = {Knoll, Aaron and Insley, Joe and Papka, Michael E. and Nomura, Ken-ichi and Kalia, Rajiv K. and Nakano, Aiichiro and Vashishta, Priya},
  booktitle = {2012 SC Companion: High Performance Computing, Networking Storage and Analysis},
  organization = {IEEE},
  pages = {1569--1571},
  title = {Molecular Dynamics Simulation of Amorphous SiO2 Fracture},
  year = {2012}
}

Joseph A. Insley, Mark Hereld, Michael E. Papka, Rick Wagner, Robert Harkness, Michael L. Norman, and Daniel R. Reynolds, Direct Numerical Simulations of Cosmological Reionization: Field Comparison: Ionization Fraction, In 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, 2012

Bib

@inproceedings{InHePa12,
  author = {Insley, Joseph A. and Hereld, Mark and Papka, Michael E. and Wagner, Rick and Harkness, Robert and Norman, Michael L. and Reynolds, Daniel R.},
  booktitle = {2012 SC Companion: High Performance Computing, Networking Storage and Analysis},
  organization = {IEEE},
  pages = {1574--1575},
  title = {Direct Numerical Simulations of Cosmological Reionization: Field Comparison: Ionization Fraction},
  year = {2012}
}

Leopold Grinberg, Joseph A. Insley, Dmitry A. Fedosov, Vitali A. Morozov, Michael E. Papka, and George Em Karniadakis, Tightly Coupled Atomistic-Continuum Simulations of Brain Blood Flow on Petaflop Supercomputers, IEEE Computing in Science & Engineering, 2012

Bib

@article{GrInFe12,
  author = {Grinberg, Leopold and Insley, Joseph A. and Fedosov, Dmitry A. and Morozov, Vitali A. and Papka, Michael E. and Karniadakis, George Em},
  journal = {IEEE Computing in Science & Engineering},
  number = {6},
  pages = {58--67},
  title = {Tightly Coupled Atomistic-Continuum Simulations of Brain Blood Flow on Petaflop Supercomputers},
  volume = {14},
  year = {2012}
}

Kirk L. Duffin, Nicholas T. Karonis, Caesar E. Ordoñez, Michael E. Papka, George Coutrakon, Bela Erdelyi, Eric C. Olson, and Thomas D. Uram, An analysis of a distributed gpu implementation of proton computed tomographic (pct) reconstruction, In 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, 2012

Bib

@inproceedings{DuKaOr12,
  author = {Duffin, Kirk L. and Karonis, Nicholas T. and Ordo{\~n}ez, Caesar E. and Papka, Michael E. and Coutrakon, George and Erdelyi, Bela and Olson, Eric C. and Uram, Thomas D.},
  booktitle = {2012 SC Companion: High Performance Computing, Networking Storage and Analysis},
  organization = {IEEE},
  pages = {166--175},
  title = {An analysis of a distributed gpu implementation of proton computed tomographic (pct) reconstruction},
  year = {2012}
}

George Coutrakon, Kirk Duffin, Bela Erdelyi, Nicholas Karonis, Eric Olson, Caesar Ordoñez, Michael E. Papka, and Thomas Uram, High-Performance Multiple-CPU/GPU Proton Computed Tomography, Transactions, 2012

Bib

@article{CoDuEr12,
  author = {Coutrakon, George and Duffin, Kirk and Erdelyi, Bela and Karonis, Nicholas and Olson, Eric and Ordo{\~n}ez, Caesar and Papka, Michael E. and Uram, Thomas},
  journal = {Transactions},
  number = {1},
  pages = {70--72},
  publisher = {American Nuclear Society},
  title = {High-Performance Multiple-CPU/GPU Proton Computed Tomography},
  volume = {106},
  year = {2012}
}

Dennis Chau, Bradley McGinnis, Jonas Talandis, Jason Leigh, Tom Peterka, Aaron Knoll, Aslihan Sumer, Michael Papka, and Julius Jellinek, A simultaneous 2D/3D autostereo workstation, In Stereoscopic Displays and Applications XXIII, 2012

Bib

@inproceedings{ChMcTa12,
  author = {Chau, Dennis and McGinnis, Bradley and Talandis, Jonas and Leigh, Jason and Peterka, Tom and Knoll, Aaron and Sumer, Aslihan and Papka, Michael and Jellinek, Julius},
  booktitle = {Stereoscopic Displays and Applications XXIII},
  organization = {SPIE},
  pages = {923--932},
  title = {A simultaneous 2D/3D autostereo workstation},
  volume = {8288},
  year = {2012}
}

Huy Bui, Venkatram Vishwanath, Jason Leigh, and Michael E. Papka, Evaluating Communication Performance in BlueGene/Q and Cray XE6 Supercomputers., In SC Companion, 2012

Bib

@inproceedings{BuViLe12b,
  author = {Bui, Huy and Vishwanath, Venkatram and Leigh, Jason and Papka, Michael E.},
  booktitle = {SC Companion},
  pages = {1514},
  title = {Evaluating Communication Performance in BlueGene/Q and Cray XE6 Supercomputers.},
  year = {2012}
}

Huy Bui, Venkatram Vishwanath, Jason Leigh, and Michael E. Papka, Poster: Evaluating Communication Performance in BlueGene/Q and Cray XE6 Supercomputers, In 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, 2012

Bib

@inproceedings{BuViLe12a,
  author = {Bui, Huy and Vishwanath, Venkatram and Leigh, Jason and Papka, Michael E.},
  booktitle = {2012 SC Companion: High Performance Computing, Networking Storage and Analysis},
  organization = {IEEE},
  pages = {1515--1515},
  title = {Poster: Evaluating Communication Performance in BlueGene/Q and Cray XE6 Supercomputers},
  year = {2012}
}

2011

Venkatram Vishwanath, Mark Hereld, Michael E. Papka, Randy Hudson, G Cal Jordan IV, and Christopher Daley, In situ data analysis and I/O acceleration of FLASH astrophysics simulation on leadership-class system using GLEAN, In SciDAC 2011 Conference, 2011

Bib

@inproceedings{ViHePa11b,
  author = {Vishwanath, Venkatram and Hereld, Mark and Papka, Michael E. and Hudson, Randy and Jordan IV, G Cal and Daley, Christopher},
  booktitle = {SciDAC 2011 Conference},
  title = {In situ data analysis and I/O acceleration of FLASH astrophysics simulation on leadership-class system using GLEAN},
  year = {2011}
}

Venkatram Vishwanath, Mark Hereld, and Michael E. Papka, Toward simulation-time data analysis and i/o acceleration on leadership-class systems, In 2011 IEEE Symposium on Large Data Analysis and Visualization, 2011

Bib

@inproceedings{ViHePa11a,
  author = {Vishwanath, Venkatram and Hereld, Mark and Papka, Michael E.},
  booktitle = {2011 IEEE Symposium on Large Data Analysis and Visualization},
  organization = {IEEE},
  pages = {9--14},
  title = {Toward simulation-time data analysis and i/o acceleration on leadership-class systems},
  year = {2011}
}

Venkatram Vishwanath, Mark Hereld, Vitali Morozov, and Michael E. Papka, Topology-aware data movement and staging for I/O acceleration on Blue Gene/P supercomputing systems, In Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis, 2011

Bib

@inproceedings{ViHeMo11,
  author = {Vishwanath, Venkatram and Hereld, Mark and Morozov, Vitali and Papka, Michael E.},
  booktitle = {Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis},
  organization = {IEEE},
  pages = {1--11},
  title = {Topology-aware data movement and staging for I/O acceleration on Blue Gene/P supercomputing systems},
  year = {2011}
}

Thomas D. Uram, Michael E. Papka, Mark Hereld, and Michael Wilde, A solution looking for lots of problems: Generic portals for science infrastructure, In Proceedings of the 2011 TeraGrid Conference: Extreme Digital Discovery, 2011

Bib

@inproceedings{UrPaHe11,
  author = {Uram, Thomas D. and Papka, Michael E. and Hereld, Mark and Wilde, Michael},
  booktitle = {Proceedings of the 2011 TeraGrid Conference: Extreme Digital Discovery},
  pages = {1--7},
  title = {A solution looking for lots of problems: Generic portals for science infrastructure},
  year = {2011}
}

Michel Rasquin, Patrick Marion, Venkatram Vishwanath, Benjamin Matthews, Mark Hereld, Kenneth Jansen, Raymond Loy, Andrew Bauer, Min Zhou, Onkar Sahni, Jing Fu, Ning Liu, Christopher Carothers, Mark Shephard, Michael E. Papka, Kalyan Kumaran, and Berk Geveci, Electronic Poster: Co-Visualization of Full Data and in Situ Data Extracts from Unstructured Grid CFD at 160K Cores, In Proceedings of the 2011 Companion on High Performance Computing Networking, Storage and Analysis Companion, 2011
Abs Bib

Scalability and time-to-solution studies have historically been focused on the size of the problem and run time. We consider a more strict definition of "solution" whereby a live data analysis (co-visualization of either the full data or in situ data extracts) provides continuous and reconfigurable insight into massively parallel simulations. Specifically, we used the Argonne Leadership Class Facility’s (ALCF) BlueGene/P machine with 163,840 cores tightly linked through a high-speed network to 100 visualization nodes that share 800 cores and 200 GPUs. Three meshes with respectively 52M, 416M and 3.3B elements discretize the flow over a full swept wing with an unsteady synthetic jet to evaluate time-to-solution plus insight. On the full machine, the 416M element mesh takes about 2 seconds per flow solve step including the extraction and rendering of a slice or a contour, slowing currently the simulation by only 10 and 15% respectively. The 3.3B element case proved scalable at about 15 seconds per time step, whereas PHASTA’s strong scaling could compress the time-to-solution for the 52M element case enough to allow the rendering of one frame (slice or contour) every 0.7 second, paving the way for interactive simulation and simulation steering on massively parallel systems1.
@inproceedings{RaMaVi11, address = {New York, NY, USA}, author = {Rasquin, Michel and Marion, Patrick and Vishwanath, Venkatram and Matthews, Benjamin and Hereld, Mark and Jansen, Kenneth and Loy, Raymond and Bauer, Andrew and Zhou, Min and Sahni, Onkar and Fu, Jing and Liu, Ning and Carothers, Christopher and Shephard, Mark and Papka, Michael E. and Kumaran, Kalyan and Geveci, Berk}, booktitle = {Proceedings of the 2011 Companion on High Performance Computing Networking, Storage and Analysis Companion}, doi = {10.1145/2148600.2148653}, isbn = {9781450310307}, keywords = {live data visualization, in situ and full data extract, paraview coprocessing library, phasta cfd solver, glean i/o forwarding tool, data reduction}, location = {Seattle, Washington, USA}, numpages = {2}, pages = {103–104}, publisher = {Association for Computing Machinery}, series = {SC '11 Companion}, title = {{Electronic Poster: Co-Visualization of Full Data and in Situ Data Extracts from Unstructured Grid CFD at 160K Cores}}, url = {https://doi.org/10.1145/2148600.2148653}, year = {2011} }
Kenneth Moreland, Ron Oldfield, Pat Marion, Sebastien Jourdain, Norbert Podhorszki, Venkatram Vishwanath, Nathan Fabian, Ciprian Docan, Manish Parashar, Mark Hereld, Michael E. Papka, and Scott Klasky, Examples of in Transit Visualization, In Proceedings of the 2nd International Workshop on Petascal Data Analytics: Challenges and Opportunities, 2011
Abs Bib

One of the most pressing issues with petascale analysis is the transport of simulation results data to a meaningful analysis. Traditional workflow prescribes storing the simulation results to disk and later retrieving them for analysis and visualization. However, at petascale this storage of the full results is prohibitive. A solution to this problem is to run the analysis and visualization concurrently with the simulation and bypass the storage of the full results. One mechanism for doing so is in transit visualization in which analysis and visualization is run on I/O nodes that receive the full simulation results but write information from analysis or provide run-time visualization. This paper describes the work in progress for three in transit visualization solutions, each using a different transport mechanism.
@inproceedings{MoOlMa11, address = {New York, NY, USA}, author = {Moreland, Kenneth and Oldfield, Ron and Marion, Pat and Jourdain, Sebastien and Podhorszki, Norbert and Vishwanath, Venkatram and Fabian, Nathan and Docan, Ciprian and Parashar, Manish and Hereld, Mark and Papka, Michael E. and Klasky, Scott}, booktitle = {Proceedings of the 2nd International Workshop on Petascal Data Analytics: Challenges and Opportunities}, doi = {10.1145/2110205.2110207}, isbn = {9781450311304}, keywords = {staging, in transit, in situ, parallel scientific visualization}, location = {Seattle, Washington, USA}, numpages = {6}, pages = {1–6}, publisher = {Association for Computing Machinery}, series = {PDAC '11}, title = {Examples of in Transit Visualization}, url = {https://doi.org/10.1145/2110205.2110207}, year = {2011} }

Aaron Knoll, Sebastian Thelen, Ingo Wald, Charles D. Hansen, Hans Hagen, and Michael E. Papka, Full-resolution interactive CPU volume rendering with coherent BVH traversal, In 2011 IEEE Pacific Visualization Symposium, 2011

Bib

@inproceedings{KnThWa11,
  author = {Knoll, Aaron and Thelen, Sebastian and Wald, Ingo and Hansen, Charles D. and Hagen, Hans and Papka, Michael E.},
  booktitle = {2011 IEEE Pacific Visualization Symposium},
  organization = {IEEE},
  pages = {3--10},
  title = {Full-resolution interactive CPU volume rendering with coherent BVH traversal},
  year = {2011}
}

Aaron Knoll, Tom Peterka, Mark Hereld, Michael E. Papka, Bin Liu, Maria Chan, and Jeffrey Greeley, Vis and Analysis for Computational Energy Materials Research, In SciDAC 2011 Conference, 2011

Bib

@inproceedings{KnPeHe11,
  author = {Knoll, Aaron and Peterka, Tom and Hereld, Mark and Papka, Michael E. and Liu, Bin and Chan, Maria and Greeley, Jeffrey},
  booktitle = {SciDAC 2011 Conference},
  title = {Vis and Analysis for Computational Energy Materials Research},
  year = {2011}
}

Joseph A. Insley, Rick Wagner, Robert Harkness, Daniel R. Reynolds, Michael L. Norman, Mark Hereld, Eric C. Olson, Michael E. Papka, and Venkatram Vishwanath, Electronic Poster: Modeling Early Galaxies Using Radiation Hydrodynamics, In Proceedings of the 2011 Companion on High Performance Computing Networking, Storage and Analysis Companion, 2011
Abs Bib

This simulation uses a flux-limited diffusion solver to explore the radiation hydrodynamics of early galaxies, in particular, the ionizing radiation created by Population III stars. At the time of this rendering, the simulation has evolved to a redshift of 3.5. The simulation volume is 11.2 comoving megaparsecs, and has a uniform grid of 10243 cells, with over 1 billion dark matter and star particles.This animation shows a combined view of the baryon density, dark matter density, radiation energy and emissivity from this simulation. The multi-variate rendering is particularly useful because is shows both the baryonic matter ("normal") and dark matter, and the pressure and temperature variables are properties of only the baryonic matter. Visible in the gas density are "bubbles", or shells, created by the radiation feedback from young stars. Seeing the bubbles from feedback provides confirmation of the physics model implemented. Features such as these are difficult to identify algorithmically, but easily found when viewing the visualization
@inproceedings{InWaHa11, address = {New York, NY, USA}, author = {Insley, Joseph A. and Wagner, Rick and Harkness, Robert and Reynolds, Daniel R. and Norman, Michael L. and Hereld, Mark and Olson, Eric C. and Papka, Michael E. and Vishwanath, Venkatram}, booktitle = {Proceedings of the 2011 Companion on High Performance Computing Networking, Storage and Analysis Companion}, doi = {10.1145/2148600.2148674}, isbn = {9781450310307}, keywords = {visualization, modeling, astrophysics}, location = {Seattle, Washington, USA}, numpages = {2}, pages = {141–142}, publisher = {Association for Computing Machinery}, series = {SC '11 Companion}, title = {{Electronic Poster: Modeling Early Galaxies Using Radiation Hydrodynamics}}, url = {https://doi.org/10.1145/2148600.2148674}, year = {2011} }

Joseph A. Insley, Leopold Grinberg, Michael E. Papka, and George Karniadakis, Electronic Poster: Visualizing Multiscale Simulation Data, In Proceedings of the 2011 Companion on High Performance Computing Networking, Storage and Analysis Companion, 2011

Abs Bib

Accurately modeling many physical and biological systems requires simulating at multiple scales. This results in large and heterogeneous data sets on vastly differing scales, both physical and temporal. Here we look specifically at blood flow in a patient-specific cerebrovasculature with a brain aneurysm, and analyze the interaction of platelets with the arterial walls that lead to thrombus formation.

@inproceedings{InGrPa11c,
  address = {New York, NY, USA},
  author = {Insley, Joseph A. and Grinberg, Leopold and Papka, Michael E. and Karniadakis, George},
  booktitle = {Proceedings of the 2011 Companion on High Performance Computing Networking, Storage and Analysis Companion},
  doi = {10.1145/2148600.2148652},
  isbn = {9781450310307},
  keywords = {visualization, modeling, multi-scale},
  location = {Seattle, Washington, USA},
  numpages = {2},
  pages = {101–102},
  publisher = {Association for Computing Machinery},
  series = {SC '11 Companion},
  title = {{Electronic Poster: Visualizing Multiscale Simulation Data}},
  url = {https://doi.org/10.1145/2148600.2148652},
  year = {2011}
}

Joseph A. Insley, Leopold Grinberg, and Michael E. Papka, Visualization of multiscale simulation data: brain blood flow, In Proceedings of the 2011 TeraGrid Conference: Extreme Digital Discovery, 2011

Bib

@inproceedings{InGrPa11b,
  author = {Insley, Joseph A. and Grinberg, Leopold and Papka, Michael E.},
  booktitle = {Proceedings of the 2011 TeraGrid Conference: Extreme Digital Discovery},
  pages = {1--2},
  title = {Visualization of multiscale simulation data: brain blood flow},
  year = {2011}
}

Joseph A. Insley, Leopold Grinberg, and Michael E. Papka, Visualizing multiscale, multiphysics simulation data: Brain blood flow, In 2011 IEEE Symposium on Large Data Analysis and Visualization, 2011

Bib

@inproceedings{InGrPa11a,
  author = {Insley, Joseph A. and Grinberg, Leopold and Papka, Michael E.},
  booktitle = {2011 IEEE Symposium on Large Data Analysis and Visualization},
  organization = {IEEE},
  pages = {3--7},
  title = {Visualizing multiscale, multiphysics simulation data: Brain blood flow},
  year = {2011}
}

Joseph A. Insley, Leopold Grinberg, Dmitry A. Fedosov, Vitali Morozov, Bruce Caswell, Michael E. Papka, and Geroge Em Karniadakis, Blood Flow: Multi-Scale Modeling and Visualization, In Proceedings of the 2011 Companion on High Performance Computing Networking, Storage and Analysis Companion, 2011
Abs Bib

Multi-scale modeling of arterial blood flow can shed light on the interaction between events happening at micro- and meso-scales (i.e., adhesion of red blood cells to the arterial wall, clot formation) and at macro-scales (i.e., change in flow patterns due to the clot). Coupled numerical simulations of such multi-scale flow require state-of-the-art computers and algorithms, along with techniques for multi-scale visualizations.This animation presents results of two studies used in the development of a multi-scale visualization methodology. The first illustrates a flow of healthy (red) and diseased (blue) blood cells with a Dissipative Particle Dynamics (DPD) method. Each blood cell is represented by a mesh made of 500 DPD-particles, and small spheres show a sub-set of the DPD particles representing the blood plasma, while instantaneous streamlines and slices represent the ensemble average velocity. In the second we investigate the process of thrombus (blood clot) formation, which may be responsible for the rupture of aneurysms, by concentrating on the platelet blood cells, observing as they aggregate on the wall of an aneurysm. The ability to use a single integrated tool for the visualization of this multi-scale simulation data is important to understanding the effects of the large-scale flow patterns on the detailed particle behavior.
@inproceedings{InGrFe11, address = {New York, NY, USA}, author = {Insley, Joseph A. and Grinberg, Leopold and Fedosov, Dmitry A. and Morozov, Vitali and Caswell, Bruce and Papka, Michael E. and Karniadakis, Geroge Em}, booktitle = {Proceedings of the 2011 Companion on High Performance Computing Networking, Storage and Analysis Companion}, doi = {10.1145/2148600.2148673}, isbn = {9781450310307}, keywords = {multi-scale, visualization, modeling}, location = {Seattle, Washington, USA}, numpages = {2}, pages = {139–140}, publisher = {Association for Computing Machinery}, series = {SC '11 Companion}, title = {Blood Flow: Multi-Scale Modeling and Visualization}, url = {https://doi.org/10.1145/2148600.2148673}, year = {2011} }

Randy Hudson, John Norris, Lynn B. Reid, G Cal Jordan IV, Klaus Weide, and Michael E. Papka, Data-intensive management and analysis for scientific simulations, In Proceedings of the Ninth Australasian Symposium on Parallel and Distributed Computing-Volume 118, 2011

Bib

@inproceedings{HuNoRe11b,
  author = {Hudson, Randy and Norris, John and Reid, Lynn B. and Jordan IV, G Cal and Weide, Klaus and Papka, Michael E.},
  booktitle = {Proceedings of the Ninth Australasian Symposium on Parallel and Distributed Computing-Volume 118},
  pages = {13--14},
  title = {Data-intensive management and analysis for scientific simulations},
  year = {2011}
}

Randy Hudson, John Norris, Lynn B. Reid, Klaus Weide, G Cal Jordan IV, and Michael E. Papka, Experiences using smaash to manage data-intensive simulations, In Proceedings of the 20th international symposium on High performance distributed computing, 2011

Bib

@inproceedings{HuNoRe11a,
  author = {Hudson, Randy and Norris, John and Reid, Lynn B. and Weide, Klaus and Jordan IV, G Cal and Papka, Michael E.},
  booktitle = {Proceedings of the 20th international symposium on High performance distributed computing},
  pages = {205--216},
  title = {Experiences using smaash to manage data-intensive simulations},
  year = {2011}
}

Mark Hereld, Michael E. Papka, Joseph A. Insley, Michael L. Norman, Eric C. Olson, and Rick Wagner, Interactive large data exploration over the wide area, In Proceedings of the 2011 TeraGrid Conference: Extreme Digital Discovery, 2011

Bib

@inproceedings{HePaIn11,
  author = {Hereld, Mark and Papka, Michael E. and Insley, Joseph A. and Norman, Michael L. and Olson, Eric C. and Wagner, Rick},
  booktitle = {Proceedings of the 2011 TeraGrid Conference: Extreme Digital Discovery},
  pages = {1--2},
  title = {Interactive large data exploration over the wide area},
  year = {2011}
}

Mark Hereld, Joseph A. Insley, Eric C. Olson, Michael E. Papka, Venkatram Vishwanath, Michael L. Norman, and Rick Wagner, Exploring large data over wide area networks, In 2011 IEEE Symposium on Large Data Analysis and Visualization, 2011

Bib

@inproceedings{HeInOl11,
  author = {Hereld, Mark and Insley, Joseph A. and Olson, Eric C. and Papka, Michael E. and Vishwanath, Venkatram and Norman, Michael L. and Wagner, Rick},
  booktitle = {2011 IEEE Symposium on Large Data Analysis and Visualization},
  organization = {IEEE},
  pages = {133--134},
  title = {Exploring large data over wide area networks},
  year = {2011}
}

Leopold Grinberg, Joseph A. Insley, Vitali Morozov, Michael E. Papka, George Em Karniadakis, Dmitry Fedosov, and Kalyan Kumaran, A new computational paradigm in multiscale simulations: Application to brain blood flow, In Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis, 2011

Bib

@inproceedings{GrInMo11,
  author = {Grinberg, Leopold and Insley, Joseph A. and Morozov, Vitali and Papka, Michael E. and Karniadakis, George Em and Fedosov, Dmitry and Kumaran, Kalyan},
  booktitle = {Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis},
  pages = {1--5},
  title = {A new computational paradigm in multiscale simulations: Application to brain blood flow},
  year = {2011}
}

Jack Dongarra, Pete Beckman, Terry Moore, Patrick Aerts, Giovanni Aloisio, Jean-Claude Andre, David Barkai, Jean-Yves Berthou, Taisuke Boku, Bertrand Braunschweig, Franck Cappello, Barbara Chapman, Xuebin Chi, Alok Choudhary, Sudip Dosanjh, Thom Dunning, Sandro Fiore, Al Geist, Bill Gropp, Robert Harrison, Mark Hereld, Michael Heroux, Adolfy Hoisie, Koh Hotta, Zhong Jin, Yutaka Ishikawa, Fred Johnson, Sanjay Kale, Richard Kenway, David Keyes, Bill Kramer, Jesus Labarta, Alain Lichnewsky, Thomas Lippert, Bob Lucas, Barney Maccabe, Satoshi Matsuoka, Paul Messina, Peter Michielse, Bernd Mohr, Matthias S. Mueller, Wolfgang E. Nagel, Hiroshi Nakashima, Michael E. Papka, Dan Reed, Mitsuhisa Sato, Ed Seidel, John Shalf, David Skinner, Marc Snir, Thomas Sterling, Rick Stevens, Fred Streitz, Bob Sugar, Shinji Sumimoto, William Tang, John Taylor, Rajeev Thakur, Anne Trefethen, Mateo Valero, Aad Steen, Jeffrey Vetter, Peg Williams, Robert Wisniewski, and Kathy Yelick, The International Exascale Software Project roadmap, The International Journal of High Performance Computing Applications, 2011
Abs Bib

Over the last 20 years, the open-source community has provided more and more software on which the world’s high-performance computing systems depend for performance and productivity. The community has invested millions of dollars and years of effort to build key components. However, although the investments in these separate software elements have been tremendously valuable, a great deal of productivity has also been lost because of the lack of planning, coordination, and key integration of technologies necessary to make them work together smoothly and efficiently, both within individual petascale systems and between different systems. It seems clear that this completely uncoordinated development model will not provide the software needed to support the unprecedented parallelism required for peta/ exascale computation on millions of cores, or the flexibility required to exploit new hardware models and features, such as transactional memory, speculative execution, and graphics processing units. This report describes the work of the community to prepare for the challenges of exascale computing, ultimately combing their efforts in a coordinated International Exascale Software Project.
@article{DoBeMo11, author = {Dongarra, Jack and Beckman, Pete and Moore, Terry and Aerts, Patrick and Aloisio, Giovanni and Andre, Jean-Claude and Barkai, David and Berthou, Jean-Yves and Boku, Taisuke and Braunschweig, Bertrand and Cappello, Franck and Chapman, Barbara and Chi, Xuebin and Choudhary, Alok and Dosanjh, Sudip and Dunning, Thom and Fiore, Sandro and Geist, Al and Gropp, Bill and Harrison, Robert and Hereld, Mark and Heroux, Michael and Hoisie, Adolfy and Hotta, Koh and Jin, Zhong and Ishikawa, Yutaka and Johnson, Fred and Kale, Sanjay and Kenway, Richard and Keyes, David and Kramer, Bill and Labarta, Jesus and Lichnewsky, Alain and Lippert, Thomas and Lucas, Bob and Maccabe, Barney and Matsuoka, Satoshi and Messina, Paul and Michielse, Peter and Mohr, Bernd and Mueller, Matthias S. and Nagel, Wolfgang E. and Nakashima, Hiroshi and Papka, Michael E. and Reed, Dan and Sato, Mitsuhisa and Seidel, Ed and Shalf, John and Skinner, David and Snir, Marc and Sterling, Thomas and Stevens, Rick and Streitz, Fred and Sugar, Bob and Sumimoto, Shinji and Tang, William and Taylor, John and Thakur, Rajeev and Trefethen, Anne and Valero, Mateo and van der Steen, Aad and Vetter, Jeffrey and Williams, Peg and Wisniewski, Robert and Yelick, Kathy}, doi = {10.1177/1094342010391989}, eprint = {https://doi.org/10.1177/1094342010391989}, journal = {The International Journal of High Performance Computing Applications}, number = {1}, pages = {3-60}, title = {The International Exascale Software Project roadmap}, url = {https://doi.org/10.1177/1094342010391989}, volume = {25}, year = {2011} }

Sean Ahern, Arie Shoshani, Kwan-Liu Ma, Alok Choudhary, Terence Critchlow, Scott Klasky, Valerio Pascucci, Jim Ahrens, E Wes Bethel, Hank Childs, Jian Huang, Ken Joy, Quincey Koziol, Gerald Lofstead, Jeremy Meredith, Kenneth Moreland, George Ostrouchov, Michael E. Papka, Venkatram Vishwanath, Matthew Wolf, Nicholas Wright, and Kesheng Wu, Scientific Discovery at the Exascale: Report from the DOE ASCR 2011 Workshop on Exascale Data Management, Department of Energy Office of Advanced Scientific Computing Research, 2011

Bib

@article{AhShMa11,
  address = {Houston, TX},
  author = {Ahern, Sean and Shoshani, Arie and Ma, Kwan-Liu and Choudhary, Alok and Critchlow, Terence and Klasky, Scott and Pascucci, Valerio and Ahrens, Jim and Bethel, E Wes and Childs, Hank and Huang, Jian and Joy, Ken and Koziol, Quincey and Lofstead, Gerald and Meredith, Jeremy and Moreland, Kenneth and Ostrouchov, George and Papka, Michael E. and Vishwanath, Venkatram and Wolf, Matthew and Wright, Nicholas and Wu, Kesheng},
  journal = {Department of Energy Office of Advanced Scientific Computing Research},
  title = {{Scientific Discovery at the Exascale: Report from the DOE ASCR 2011 Workshop on Exascale Data Management}},
  volume = {1},
  year = {2011}
}

2010

Wenjun Wu, Thomas Uram, Michael Wilde, Mark Hereld, and Michael E. Papka, Accelerating science gateway development with Web 2.0 and Swift, In Proceedings of the 2010 TeraGrid Conference, 2010

Bib

@inproceedings{WuUrWi10b,
  author = {Wu, Wenjun and Uram, Thomas and Wilde, Michael and Hereld, Mark and Papka, Michael E.},
  booktitle = {Proceedings of the 2010 TeraGrid Conference},
  pages = {1--7},
  title = {Accelerating science gateway development with Web 2.0 and Swift},
  year = {2010}
}

Wenjun Wu, Thomas D. Uram, Michael Wilde, Mark Hereld, and Michael E. Papka, A Web 2.0-Based Scientific Application Framework, In 2010 IEEE International Conference on Web Services, 2010

Bib

@inproceedings{WuUrWi10a,
  author = {Wu, Wenjun and Uram, Thomas D. and Wilde, Michael and Hereld, Mark and Papka, Michael E.},
  booktitle = {2010 IEEE International Conference on Web Services},
  organization = {IEEE},
  pages = {642--643},
  title = {A Web 2.0-Based Scientific Application Framework},
  year = {2010}
}

Venkatram Vishwanath, Mark Hereld, Kamil Iskra, Dries Kimpe, Vitali Morozov, Michael E. Papka, Robert Ross, and Kazutomo Yoshii, Accelerating i/o forwarding in ibm blue gene/p systems, In SC’10: Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, 2010

Bib

@inproceedings{ViHeIs10,
  author = {Vishwanath, Venkatram and Hereld, Mark and Iskra, Kamil and Kimpe, Dries and Morozov, Vitali and Papka, Michael E. and Ross, Robert and Yoshii, Kazutomo},
  booktitle = {SC'10: Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis},
  organization = {IEEE},
  pages = {1--10},
  title = {Accelerating i/o forwarding in ibm blue gene/p systems},
  year = {2010}
}

Sidharth Kumar, Valerio Pascucci, Venkatram Vishwanath, Philip Carns, Mark Hereld, Robert Latham, Tom Peterka, Michael E. Papka, and Robert Ross, Towards parallel access of multi-dimensional, multi-resolution scientific data, In 2010 5th Petascale Data Storage Workshop (PDSW’10), 2010

Bib

@inproceedings{KuPaVi10,
  author = {Kumar, Sidharth and Pascucci, Valerio and Vishwanath, Venkatram and Carns, Philip and Hereld, Mark and Latham, Robert and Peterka, Tom and Papka, Michael E. and Ross, Robert},
  booktitle = {2010 5th Petascale Data Storage Workshop (PDSW'10)},
  organization = {IEEE},
  pages = {1--5},
  title = {Towards parallel access of multi-dimensional, multi-resolution scientific data},
  year = {2010}
}

2009

Wenjun Wu, Thomas Uram, and Michael E. Papka, Web 2.0-based social informatics data grid, In Proceedings of the 5th Grid Computing Environments Workshop, 2009

Bib

@inproceedings{WuUrPa09,
  author = {Wu, Wenjun and Uram, Thomas and Papka, Michael E.},
  booktitle = {Proceedings of the 5th Grid Computing Environments Workshop},
  pages = {1--7},
  title = {Web 2.0-based social informatics data grid},
  year = {2009}
}

Michael E.ugene Papka, Visualization and collaboration technologies to support high-performance computing research, 2009

Bib

Kwan-Liu Ma, and Michael E. Papka, Proceedings of the 2009 Workshop on Ultrascale Visualization, UltraVis’ 09: Preface, In Proceedings of the 2009 Workshop on Ultrascale Visualization, UltraVis’ 09, 2009

Bib

@inproceedings{MaPa09,
  author = {Ma, Kwan-Liu and Papka, Michael E.},
  booktitle = {Proceedings of the 2009 Workshop on Ultrascale Visualization, UltraVis' 09},
  title = {Proceedings of the 2009 Workshop on Ultrascale Visualization, UltraVis' 09: Preface},
  year = {2009}
}

Joseph A. Insley, Torrance Leggett, and Michael E. Papka, Using dynamic accounts to enable access to advanced resources through science gateways, In Proceedings of the 5th Grid Computing Environments Workshop, 2009

Bib

@inproceedings{InLePa09,
  author = {Insley, Joseph A. and Leggett, Torrance and Papka, Michael E.},
  booktitle = {Proceedings of the 5th Grid Computing Environments Workshop},
  pages = {1--6},
  title = {Using dynamic accounts to enable access to advanced resources through science gateways},
  year = {2009}
}

Mark Hereld, Joseph A. Insley, Eric C. Olson, Michael E. Papka, Thomas D. Uram, and Venkatram Vishwanath, Modeling resource-coupled computations, In Proceedings of the 2009 Workshop on Ultrascale Visualization, 2009

Bib

@inproceedings{HeInOl09,
  author = {Hereld, Mark and Insley, Joseph A. and Olson, Eric C. and Papka, Michael E. and Uram, Thomas D. and Vishwanath, Venkatram},
  booktitle = {Proceedings of the 2009 Workshop on Ultrascale Visualization},
  pages = {27--33},
  title = {Modeling resource-coupled computations},
  year = {2009}
}

Mark Hereld, Randy Hudson, John Norris, Michael E. Papka, and Thomas Uram, Enabling scientific teamwork, In Journal of Physics: Conference Series, 2009

Bib

@inproceedings{HeHuNo09,
  author = {Hereld, Mark and Hudson, Randy and Norris, John and Papka, Michael E. and Uram, Thomas},
  booktitle = {Journal of Physics: Conference Series},
  number = {1},
  organization = {IOP Publishing},
  pages = {012085},
  title = {Enabling scientific teamwork},
  volume = {180},
  year = {2009}
}

2008

Wenjun Wu, Michael E. Papka, and Rick Stevens, Toward an opensocial life science gateway, In 2008 Grid Computing Environments Workshop, 2008

Bib

@inproceedings{WuPaSt08,
  author = {Wu, Wenjun and Papka, Michael E. and Stevens, Rick},
  booktitle = {2008 Grid Computing Environments Workshop},
  organization = {IEEE},
  pages = {1--6},
  title = {Toward an opensocial life science gateway},
  year = {2008}
}

Wenjun Wu, Rob Edwards, Ivan R. Judson, Michael E. Papka, Mary Thomas, and Rick Stevens, TeraGrid Open Life Science Gateway, In TeraGrid 2008 Conference, 2008

Bib

@inproceedings{WuEdJu08,
  author = {Wu, Wenjun and Edwards, Rob and Judson, Ivan R. and Papka, Michael E. and Thomas, Mary and Stevens, Rick},
  booktitle = {TeraGrid 2008 Conference},
  pages = {9--13},
  title = {TeraGrid Open Life Science Gateway},
  year = {2008}
}

Mark Hereld, Michael E. Papka, and Thomas D. Uram, Collaboration as a second thought, In 2008 International Symposium on Collaborative Technologies and Systems, 2008

Bib

@inproceedings{HePaUr08,
  author = {Hereld, Mark and Papka, Michael E. and Uram, Thomas D.},
  booktitle = {2008 International Symposium on Collaborative Technologies and Systems},
  organization = {IEEE},
  pages = {196--202},
  title = {Collaboration as a second thought},
  year = {2008}
}

Mark Hereld, and Michael E. Papka, The data analysis computing hierarchy, In 2008 Workshop on Ultrascale Visualization, 2008

Bib

@inproceedings{HePa08,
  author = {Hereld, Mark and Papka, Michael E.},
  booktitle = {2008 Workshop on Ultrascale Visualization},
  organization = {IEEE},
  pages = {9--12},
  title = {The data analysis computing hierarchy},
  year = {2008}
}

M Hereld, E Olson, ME Papka, and TD Uram, Streaming visualization for collaborative environments, In Journal of Physics: Conference Series, 2008

Bib

@inproceedings{HeOlPa08,
  author = {Hereld, M and Olson, E and Papka, ME and Uram, TD},
  booktitle = {Journal of Physics: Conference Series},
  number = {1},
  organization = {IOP Publishing},
  pages = {012097},
  title = {Streaming visualization for collaborative environments},
  volume = {125},
  year = {2008}
}

Robert T. Fisher, Leo P. Kadanoff, Donald Q. Lamb, Anshu Dubey, Tomasz Plewa, Alan Calder, Fausto Cattaneo, Peter Constantin, Ian Foster, Michael E. Papka, Snezhana I. Abarzhi, S. M. Asida, Paul M. Rich, Chad C. Glendenin, Katie Antypas, Daniel J. Sheeler, Lynn B. Reid, Brad Gallagher, and Shawn G. Needham, Terascale turbulence computation using the FLASH3 application framework on the IBM Blue Gene/L system, IBM Journal of Research and Development, 2008

Bib

@article{FiKaLa08,
  author = {Fisher, Robert T. and Kadanoff, Leo P. and Lamb, Donald Q. and Dubey, Anshu and Plewa, Tomasz and Calder, Alan and Cattaneo, Fausto and Constantin, Peter and Foster, Ian and Papka, Michael E. and Abarzhi, Snezhana I. and Asida, S. M. and Rich, Paul M. and Glendenin, Chad C. and Antypas, Katie and Sheeler, Daniel J. and Reid, Lynn B. and Gallagher, Brad and Needham, Shawn G.},
  doi = {10.1147/rd.521.0127},
  journal = {IBM Journal of Research and Development},
  number = {1.2},
  pages = {127-136},
  title = {Terascale turbulence computation using the {FLASH3} application framework on the {IBM Blue Gene/L} system},
  volume = {52},
  year = {2008}
}

Charlie Catlett, William E. Allcock, Phil Andrews, Ruth Aydt, Ray Bair, Natasha Balac, Bryan Banister, Trish Barker, Mark Bartelt, Pete Beckman, Francine Berman, Gary Bertoline, Alan Blatecky, Jay Boisseau, Jim Bottum, Sharon Brunett, Julian Bunn, Michelle Butler, David Carver, John Cobb, Tim Cockerill, Peter F. Couvares, Maytal Dahan, Diana Diehl, Thom Dunning, Ian Foster, Kelly Gaither, Dennis Gannon, Sebastien Goasguen, Michael Grobe, Dave Hart, Matt Heinzel, Chris Hempel, Wendy Huntoon, Joseph Insley, Christopher Jordan, Ivan Judson, Anke Kamrath, Nicholas Karonis, Carl Kesselman, Patricia Kovatch, Lex Lane, Scott Lathrop, Michael Levine, David Lifka, Lee Liming, Miron Livny, Rich Loft, Doru Marcusiu, Jim Marsteller, Stuart Martin, Scott McCaulay, John McGee, Laura McGinnis, Michael McRobbie, Paul Messina, Reagan Moore, Richard Moore, J.P. Navarro, Jeff Nichols, Michael E. Papka, Rob Pennington, Greg Pike, Jim Pool, Raghu Reddy, Dan Reed, Tony Rimovsky, Eric Roberts, Ralph Roskies, Sergiu Sanielevici, J. Ray Scott, Anurag Shankar, Mark Sheddon, Mike Showerman, Derek Simmel, Abe Singer, Dane Skow, Shava Smallen, Warren Smith, Carol Song, Rick Stevens, Craig Stewart, Robert B. Stock, Nathan Stone, John Towns, Tomislav Urban, Mike Vildibill, Edward Walker, Von Welch, Nancy Wilkins-Diehr, Roy Williams, Linda Winkler, Lan Zhao, and Ann Zimmerman, High Performance Computing and Grids in Action, 2008

Bib

@inbook{CaAlAn08,
  author = {Catlett, Charlie and Allcock, William E. and Andrews, Phil and Aydt, Ruth and Bair, Ray and Balac, Natasha and Banister, Bryan and Barker, Trish and Bartelt, Mark and Beckman, Pete and Berman, Francine and Bertoline, Gary and Blatecky, Alan and Boisseau, Jay and Bottum, Jim and Brunett, Sharon and Bunn, Julian and Butler, Michelle and Carver, David and Cobb, John and Cockerill, Tim and Couvares, Peter F. and Dahan, Maytal and Diehl, Diana and Dunning, Thom and Foster, Ian and Gaither, Kelly and Gannon, Dennis and Goasguen, Sebastien and Grobe, Michael and Hart, Dave and Heinzel, Matt and Hempel, Chris and Huntoon, Wendy and Insley, Joseph and Jordan, Christopher and Judson, Ivan and Kamrath, Anke and Karonis, Nicholas and Kesselman, Carl and Kovatch, Patricia and Lane, Lex and Lathrop, Scott and Levine, Michael and Lifka, David and Liming, Lee and Livny, Miron and Loft, Rich and Marcusiu, Doru and Marsteller, Jim and Martin, Stuart and McCaulay, Scott and McGee, John and McGinnis, Laura and McRobbie, Michael and Messina, Paul and Moore, Reagan and Moore, Richard and Navarro, J.P. and Nichols, Jeff and Papka, Michael E. and Pennington, Rob and Pike, Greg and Pool, Jim and Reddy, Raghu and Reed, Dan and Rimovsky, Tony and Roberts, Eric and Roskies, Ralph and Sanielevici, Sergiu and Scott, J. Ray and Shankar, Anurag and Sheddon, Mark and Showerman, Mike and Simmel, Derek and Singer, Abe and Skow, Dane and Smallen, Shava and Smith, Warren and Song, Carol and Stevens, Rick and Stewart, Craig and Stock, Robert B. and Stone, Nathan and Towns, John and Urban, Tomislav and Vildibill, Mike and Walker, Edward and Welch, Von and Wilkins-Diehr, Nancy and Williams, Roy and Winkler, Linda and Zhao, Lan and Zimmerman, Ann},
  chapter = {TeraGrid: Analysis of Organization, System Architecture, and Middleware Enabling New Types of Applications},
  editor = {Grandinetti, Lucio},
  pages = {225--249},
  publisher = {IOS Press},
  title = {High Performance Computing and Grids in Action},
  volume = {16},
  year = {2008}
}

2007

Jonathan C. Silverstein, Colin Walsh, Fred Dech, Eric C. Olson, Michael E. Papka, Nigel M. Parsad, and Rick L. Stevens, Immersive virtual anatomy course using a cluster of volume visualization machines and passive stereo., In MMVR, 2007

Bib

@inproceedings{SiWaDe07,
  author = {Silverstein, Jonathan C. and Walsh, Colin and Dech, Fred and Olson, Eric C. and Papka, Michael E. and Parsad, Nigel M. and Stevens, Rick L.},
  booktitle = {MMVR},
  pages = {439--444},
  title = {Immersive virtual anatomy course using a cluster of volume visualization machines and passive stereo.},
  year = {2007}
}

Gina-Anne Levow, Bennett Bertenthal, Mark Hereld, Sarah Kenny, David McNeill, Michael Papka, and Sonjia Waxmonsky, SIDGRID: A Framework for Distributed and Integrated Multimodal Annotation and Archiving and and Analysis, In Proceedings of the 8th SIGdial Workshop on Discourse and Dialogue, 2007

Bib

@inproceedings{LeBeHe07,
  author = {Levow, Gina-Anne and Bertenthal, Bennett and Hereld, Mark and Kenny, Sarah and McNeill, David and Papka, Michael and Waxmonsky, Sonjia},
  booktitle = {Proceedings of the 8th SIGdial Workshop on Discourse and Dialogue},
  pages = {231--234},
  title = {SIDGRID: A Framework for Distributed and Integrated Multimodal Annotation and Archiving and and Analysis},
  year = {2007}
}

Chris Johnson, Robert Ross, S Ahern, J Ahrens, W Bethel, KL Ma, M Papka, JV Rosendale, HW Shen, and J Thomas, Visualization and knowledge discovery: Report from the DOE/ASCR workshop on visual analysis and data exploration at extreme scale, Salt Lake City, 2007

Bib

@article{JoRoAh07,
  author = {Johnson, Chris and Ross, Robert and Ahern, S and Ahrens, J and Bethel, W and Ma, KL and Papka, M and Rosendale, JV and Shen, HW and Thomas, J},
  journal = {Salt Lake City},
  title = {Visualization and knowledge discovery: Report from the DOE/ASCR workshop on visual analysis and data exploration at extreme scale},
  year = {2007}
}

Joseph A. Insley, Michael E. Papka, Suchuan Dong, George Karniadakis, and Nicholas T. Karonis, Runtime visualization of the human arterial tree, IEEE Transactions on Visualization and Computer Graphics, 2007

Bib

@article{InPaDo07,
  author = {Insley, Joseph A. and Papka, Michael E. and Dong, Suchuan and Karniadakis, George and Karonis, Nicholas T.},
  journal = {IEEE Transactions on Visualization and Computer Graphics},
  number = {4},
  pages = {810--821},
  publisher = {IEEE},
  title = {Runtime visualization of the human arterial tree},
  volume = {13},
  year = {2007}
}

Robert L. Grossman, Michal Sabala, Shirley Connelly, Yunhong Gu, Matt Handley, Rajmonda Sulo, Dave Turkington, Anushka Anand, Leland Wilkinson, Ian Foster, Ti Leggett, Michael E. Papka, Mike Wilde, Joe Mambretti, Bob Lucas, and John Tran, Angle: Detecting Anomalies and Emergent Behavior from Distributed Data in Near Real Time [Analytics Challenge Winner], In SC07 International Conference for High Performance Computing, Networking, Storage and Analysis, Reno, NV, 2007

Bib

@inproceedings{GrSaCo07,
  author = {Grossman, Robert L. and Sabala, Michal and Connelly, Shirley and Gu, Yunhong and Handley, Matt and Sulo, Rajmonda and Turkington, Dave and Anand, Anushka and Wilkinson, Leland and Foster, Ian and Leggett, Ti and Papka, Michael E. and Wilde, Mike and Mambretti, Joe and Lucas, Bob and Tran, John},
  booktitle = {SC07 International Conference for High Performance Computing, Networking, Storage and Analysis, Reno, NV},
  title = {Angle: Detecting Anomalies and Emergent Behavior from Distributed Data in Near Real Time [Analytics Challenge Winner]},
  year = {2007}
}

Justin Binns, Jonathan DiCarlo, Joseph A. Insley, Torrance Leggett, Cory Lueninghoener, John-Paul Navarro, and Michael E. Papka, Enabling community access to TeraGrid visualization resources, Concurrency and Computation: Practice and Experience, 2007

Bib

@article{BiDiIn07,
  author = {Binns, Justin and DiCarlo, Jonathan and Insley, Joseph A. and Leggett, Torrance and Lueninghoener, Cory and Navarro, John-Paul and Papka, Michael E.},
  journal = {Concurrency and Computation: Practice and Experience},
  number = {6},
  pages = {783--794},
  publisher = {Wiley Online Library},
  title = {Enabling community access to TeraGrid visualization resources},
  volume = {19},
  year = {2007}
}

Bennett Bertenthal, Robert Grossman, David Hanley, Mark Hereld, Sarah Kenny, Gina Levow, Michael E. Papka, Steve Porges, Kavithaa Rajavenkateshwaran, Rick Stevens, Thomas D. Uram, and Wenjun Wu, Social informatics data grid, In Third International Conference on e-Social Science, 2007

Bib

@inproceedings{BeGrHa07,
  author = {Bertenthal, Bennett and Grossman, Robert and Hanley, David and Hereld, Mark and Kenny, Sarah and Levow, Gina and Papka, Michael E. and Porges, Steve and Rajavenkateshwaran, Kavithaa and Stevens, Rick and Uram, Thomas D. and Wu, Wenjun},
  booktitle = {Third International Conference on e-Social Science},
  pages = {7--9},
  title = {Social informatics data grid},
  year = {2007}
}

Svenja Adolphs, Bennett Bertenthal, Steve Boker, Ronald Carter, Chris Greenhalgh, Mark Hereld, Sarah Kenny, Gina Levow, Michael E. Papka, and Tony Pridmore, Integrating cyberinfrastructure into existing e-Social Science research, In Proceedings of the e-Social Science 2007 Conference, 2007

Bib

@inproceedings{AdBeBo07,
  author = {Adolphs, Svenja and Bertenthal, Bennett and Boker, Steve and Carter, Ronald and Greenhalgh, Chris and Hereld, Mark and Kenny, Sarah and Levow, Gina and Papka, Michael E. and Pridmore, Tony},
  booktitle = {Proceedings of the e-Social Science 2007 Conference},
  title = {Integrating cyberinfrastructure into existing e-Social Science research},
  year = {2007}
}

2006

Mark Hereld, Michael E. Papka, Justin Binns, and Rick L. Stevens, CupHolder: A Multi-Person Interactive High-Resolution Workstation, In IEEE Virtual Reality Conference (VR 2006), 2006

Bib

@inproceedings{HePaBi06,
  author = {Hereld, Mark and Papka, Michael E. and Binns, Justin and Stevens, Rick L.},
  booktitle = {IEEE Virtual Reality Conference (VR 2006)},
  organization = {IEEE},
  pages = {323--323},
  title = {CupHolder: A Multi-Person Interactive High-Resolution Workstation},
  year = {2006}
}

Han Gao, Michael E. Papka, and Rick L. Stevens, Extending Multicast Communications by Hybrid Overlay Network, In 2006 IEEE International Conference on Communications, 2006

Bib

@inproceedings{GaPaSt06,
  author = {Gao, Han and Papka, Michael E. and Stevens, Rick L.},
  booktitle = {2006 IEEE International Conference on Communications},
  organization = {IEEE},
  pages = {820--828},
  title = {Extending Multicast Communications by Hybrid Overlay Network},
  volume = {2},
  year = {2006}
}

Suchuan Dong, Joseph Insley, Nicholas T. Karonis, Michael E. Papka, Justin Binns, and George Karniadakis, Simulating and visualizing the human arterial system on the TeraGrid, Future Generation Computer Systems, 2006

Bib

@article{DoInKa06,
  author = {Dong, Suchuan and Insley, Joseph and Karonis, Nicholas T. and Papka, Michael E. and Binns, Justin and Karniadakis, George},
  journal = {Future Generation Computer Systems},
  number = {8},
  pages = {1011--1017},
  publisher = {North-Holland},
  title = {Simulating and visualizing the human arterial system on the TeraGrid},
  volume = {22},
  year = {2006}
}

Katie B. Antypas, Alan C. Calder, Anshu Dubey, J. Bradley Gallagher, J. Joshi, Donald Q. Lamb, Timur Linde, Ewing L. Lusk, O.E. Bronson Messer, Andrea Mignone, H. Pan, Michael E. Papka, F. Peng, Tomas Plewa, Katherine M. Riley, Paul M. Ricker, Daniel Sheeler, Andrew Siegel, N. Taylor, James W. Truran, Natalia Vladimirova, Greg Weirs, D. Yu, and J. Zhang, FLASH: Applications and Future, In Parallel Computational Fluid Dynamics 2005, 2006
Abs Bib

Flash has been successful in simulating a wide variety of astrophysical problems, both within the flash center and in the external community. The code has steadily gained acceptance since its initial release for the following reasons: (1) it is easily ported to a variety of computer architectures and the distribution includes support for many standard machines; (2) creation of new applications is straightforward and well-documented, and the suite of tools allows users to quickly process and interpret simulation results; (3) and the modularity of the code allows users to readily add functionality. The unusually large scale of flash necessitates the adoption of practices already in wide commercial use but not typically found in an academic scientific project. The principal lesson learned during the development of flash is the importance of good software practices. These include thorough documentation, detailed design specifications for the framework and components, and especially regression testing, which is essential in a project with multiple developers.
@incollection{AnCaDu06, address = {Amsterdam}, author = {Antypas, Katie B. and Calder, Alan C. and Dubey, Anshu and Gallagher, J. Bradley and Joshi, J. and Lamb, Donald Q. and Linde, Timur and Lusk, Ewing L. and Messer, O.E. Bronson and Mignone, Andrea and Pan, H. and Papka, Michael E. and Peng, F. and Plewa, Tomas and Riley, Katherine M. and Ricker, Paul M. and Sheeler, Daniel and Siegel, Andrew and Taylor, N. and Truran, James W. and Vladimirova, Natalia and Weirs, Greg and Yu, D. and Zhang, J.}, booktitle = {Parallel Computational Fluid Dynamics 2005}, doi = {https://doi.org/10.1016/B978-044452206-1/50039-2}, editor = {Deane, Anil and Ecer, Akin and McDonough, James and Satofuka, Nobuyuki and Brenner, Gunther and Emerson, David R. and Periaux, Jacques and Tromeur-Dervout, Damien}, isbn = {978-0-444-52206-1}, pages = {325-331}, publisher = {Elsevier}, title = {FLASH: Applications and Future}, url = {https://www.sciencedirect.com/science/article/pii/B9780444522061500392}, year = {2006} }
James Ahrens, Hank Childs, John Clyne, Wes Bethel, Jian Huang, Scott Klasky, Kwan-Liu Ma, Kenneth Moreland, Michael Papka, Valerio Pascucci, Han-Wei Shen, and Debroah Silver, Workshop on Ultra-Scale Visualization, In Proceedings of the 2006 ACM/IEEE Conference on Supercomputing, 2006
Abs Bib

The output from the massively parallel scientific simulations is so voluminous and complex that advanced visualization technologies are necessary to interpret the calculated results. Even though visualization technology has progressed significantly in recent years, we are barely capable of visualizing and analyzing terascale data to its full extent, and petascale datasets are on the horizon. This workshop aims at addressing this pressing issue by fostering communication between visualization researchers and practitioners. The workshop attendees will be introduced to the latest and greatest research innovations in large data visualization and also help direct further research direction through an open discussion session.
@inproceedings{AhChCl06, address = {New York, NY, USA}, author = {Ahrens, James and Childs, Hank and Clyne, John and Bethel, Wes and Huang, Jian and Klasky, Scott and Ma, Kwan-Liu and Moreland, Kenneth and Papka, Michael and Pascucci, Valerio and Shen, Han-Wei and Silver, Debroah}, booktitle = {Proceedings of the 2006 ACM/IEEE Conference on Supercomputing}, doi = {10.1145/1188455.1188700}, isbn = {0769527000}, location = {Tampa, Florida}, pages = {235–es}, publisher = {Association for Computing Machinery}, series = {SC '06}, title = {Workshop on Ultra-Scale Visualization}, url = {https://doi.org/10.1145/1188455.1188700}, year = {2006} }

2005

Jonathan C. Silverstein, Fred Dech, Justin Binns, David Jones, Michael E. Papka, and Rick Stevens, Distributed collaborative radiological visualization using access grid., Studies in Health Technology and Informatics, 2005

Bib

@article{SiDeBi05,
  author = {Silverstein, Jonathan C. and Dech, Fred and Binns, Justin and Jones, David and Papka, Michael E. and Stevens, Rick},
  journal = {Studies in Health Technology and Informatics},
  pages = {477--481},
  title = {Distributed collaborative radiological visualization using access grid.},
  volume = {111},
  year = {2005}
}

Katarzyna Keahey, Michael E. Papka, Q Peng, David Schissel, Geni Abla, Takuya Araki, Justin Burruss, Elliot Feibush, Peter Lane, Scott Klasky, Torrance Leggett, Doug Mccune, and Lew Randerson, Grid Support for Collaborative Control Room in Fusion Science, Cluster Computing,Oct, 2005
Abs Bib

The National Fusion Collaboratory project seeks to enable fusion scientists to exploit Grid capabilities in support of experimental science. To this end we are exploring the concept of a collaborative control room that harnesses Grid and collaborative technologies to provide an environment in which remote experimental devices, codes, and expertise can interact in real time during an experiment. This concept has the potential to make fusion experiments more efficient by enabling researchers to perform more analysis and by engaging more expertise from a geographically distributed team of scientists and resources. As the realities of software development, talent distribution, and budgets increasingly encourage pooling resources and specialization, we see such environments as a necessary tool for future science.In this paper, we describe an experimental mock-up of a remote interaction with the DIII-D control room. The collaborative control room was demonstrated at SC03 and later reviewed at an international ITER Grid Workshop. We describe how the combined effect of various technologies–collaborative, visualization, and Grid–can be used effectively in experimental science. Specifically, we describe the Access Grid, experimental data presentation tools, and agreement-based resource management and workflow systems enabling time-bounded end-to-end application execution. We also report on FusionGrid services whose use during the fusion experimental cycle became possible for the first time thanks to this technology, and we discuss its potential use in future fusion experiments.
@article{KePaPe05, address = {USA}, author = {Keahey, Katarzyna and Papka, Michael E. and Peng, Q and Schissel, David and Abla, Geni and Araki, Takuya and Burruss, Justin and Feibush, Elliot and Lane, Peter and Klasky, Scott and Leggett, Torrance and Mccune, Doug and Randerson, Lew}, doi = {10.1007/s10586-005-4097-z}, issn = {1386-7857}, issue_date = {October 2005}, journal = {Cluster Computing}, month = oct, number = {4}, numpages = {7}, pages = {305–311}, publisher = {Kluwer Academic Publishers}, title = {Grid Support for Collaborative Control Room in Fusion Science}, url = {https://doi.org/10.1007/s10586-005-4097-z}, volume = {8}, year = {2005} }
Robert Grossman, Michal Sabala, Anushka Aanand, Steve Eick, Leland Wilkinson, Pei Zhang, John Chaves, Steve Vejcik, John Dillenburg, Peter Nelson, Doug Rorem, Javid Alimohideen, Jason Leigh, Michael E. Papka, and Rick Stevens, Real Time Change Detection and Alerts from Highway Traffic Data, In SC ’05: Proceedings of the 2005 ACM/IEEE Conference on Supercomputing,Nov, 2005
Abs Bib

We developed a testbed containing: real time data from over 830 highway traffic sensors in the Chicago region, data about weather, and text data about events that might affect traffic. The goal was to detect in real time interesting changes in traffic conditions. Given the size and complexity of the data, we choose to build a large number of separate baseline models. We built a separate baseline for each hour in the day, for each day in the week, and for every 2 or 3 traffic sensors, resulting in over 42,000 separate baseline models. We also built a baseline engine to build the necessary baselines automatically. We modified an open source scoring engine to process in real time each new sensor reading, update the appropriate feature vectors, score the updated feature vectors using the baseline models, and send out real time alerts when deviations from the baselines were detected.
@inproceedings{GrSaAa05, author = {Grossman, Robert and Sabala, Michal and Aanand, Anushka and Eick, Steve and Wilkinson, Leland and Zhang, Pei and Chaves, John and Vejcik, Steve and Dillenburg, John and Nelson, Peter and Rorem, Doug and Alimohideen, Javid and Leigh, Jason and Papka, Michael E. and Stevens, Rick}, booktitle = {SC '05: Proceedings of the 2005 ACM/IEEE Conference on Supercomputing}, doi = {10.1109/SC.2005.60}, month = nov, pages = {69-69}, title = {Real Time Change Detection and Alerts from Highway Traffic Data}, year = {2005} }

Han Gao, Michael E. Papka, and Rick L. Stevens, Performance metrics of IP multicast sessions, In Seventh IEEE International Symposium on Multimedia (ISM’05), 2005

Bib

@inproceedings{GaPaSt05,
  author = {Gao, Han and Papka, Michael E. and Stevens, Rick L.},
  booktitle = {Seventh IEEE International Symposium on Multimedia (ISM'05)},
  organization = {IEEE},
  pages = {10--pp},
  title = {Performance metrics of IP multicast sessions},
  year = {2005}
}

Han Gao, Ivan R. Judson, Thomas Uram, Susanne Lefvert, Terry L. Disz, Michael E. Papka, and Rick L. Stevens, An Infrastructure of Network Services for Seamless Integration in Advanced Collaborative Computing Environments, In 2005 IEEE International Conference on Cluster Computing, 2005

Bib

@inproceedings{GaJuUr05,
  author = {Gao, Han and Judson, Ivan R. and Uram, Thomas and Lefvert, Susanne and Disz, Terry L. and Papka, Michael E. and Stevens, Rick L.},
  booktitle = {2005 IEEE International Conference on Cluster Computing},
  organization = {IEEE},
  pages = {1--10},
  title = {An Infrastructure of Network Services for Seamless Integration in Advanced Collaborative Computing Environments},
  year = {2005}
}

H Gao, IR Judson, ME Papka, and RL Stevens, Middleware of Performance Analysis for Multimedia Grid, In Proceedings of the 30th IEEE Conference on Local Computer Networks, 2005

Bib

@inproceedings{GaJuPa05,
  author = {Gao, H and Judson, IR and Papka, ME and Stevens, RL},
  booktitle = {Proceedings of the 30th IEEE Conference on Local Computer Networks},
  title = {Middleware of Performance Analysis for Multimedia Grid},
  year = {2005}
}

Justin R. Burruss, Geni Abla, Scott Flanagan, Katarzyna Keahey, Torrance Leggett, Christiane Ludesche, Doug McCune, Michael E. Papka, Qian Peng, Lew Randerson, and David P. Schissel, Developments in Remote Collaboration and Computation, Fusion Science and Technology, 2005

Bib

@article{BuAbFl05,
  author = {Burruss, Justin R. and Abla, Geni and Flanagan, Scott and Keahey, Katarzyna and Leggett, Torrance and Ludesche, Christiane and McCune, Doug and Papka, Michael E. and Peng, Qian and Randerson, Lew and Schissel, David P.},
  journal = {Fusion Science and Technology},
  number = {3},
  pages = {814--818},
  publisher = {Taylor & Francis},
  title = {Developments in Remote Collaboration and Computation},
  volume = {47},
  year = {2005}
}

Justin Binns, Fred Dech, Matthew McCrory, Michael E. Papka, Jonathan C. Silverstein, and Rick Stevens, Developing a distributed collaborative radiological visualization application, Studies in Health Technology and Informatics, 2005

Bib

@article{BiDeMc05,
  author = {Binns, Justin and Dech, Fred and McCrory, Matthew and Papka, Michael E. and Silverstein, Jonathan C. and Stevens, Rick},
  journal = {Studies in Health Technology and Informatics},
  pages = {70--79},
  publisher = {Amsterdam; Washington, DC: IOS Press, 1991-},
  title = {Developing a distributed collaborative radiological visualization application},
  volume = {112},
  year = {2005}
}

2004

David Schissel, Katarzyna Keahey, Doug McCune, Justin Burruss, Lew Randerson, Scott Klasky, Geni Abla, Peter Lane, Elliot Feibush, Michael E. Papka, Torrance Leggett, Takuya Araki, and Qian Peng, Grids for Experimental Science: The Virtual Control Room, In Proceedings of the Second International Workshop on Challenges of Large Applications in Distributed Environments,Jun, 2004
Abs Bib

The National Fusion Collaboratory focuses on enabling fusion scientists to explore Grid capabilities in support of experimental science. Fusion experiments are structured as a series of plasma pulses initiated roughly every 20 minutes. In the between-pulse intervals scientists perform data analysis and discuss results to reach decisions affecting changes to the next plasma pulse. This interaction can be made more efficient by performing more analysis and engaging more expertise from a geographically distributed team of scientists and resources. In this paper, we describe a virtual control room experiment that unites collaborative, visualization, and Grid technologies to provide such environment and shows how their combined effect can advance experimental science. We also report on FusionGrid services whose use during the fusion experimental cycle became possible for the first time thanks to this technology. We also describe the Access Grid, experimental data presentation tools, and agreement-based resource management and workflow systems enabling time-bounded end-to-end application execution. The first virtual control room experiment represented a mock-up of a remote interaction with the DIII-D control room and was presented at SC03 and later reviewed at an international ITER Grid Workshop.
@inproceedings{ScKeMc04, address = {Los Alamitos, CA, USA}, author = {Schissel, David and Keahey, Katarzyna and McCune, Doug and Burruss, Justin and Randerson, Lew and Klasky, Scott and Abla, Geni and Lane, Peter and Feibush, Elliot and Papka, Michael E. and Leggett, Torrance and Araki, Takuya and Peng, Qian}, booktitle = {Proceedings of the Second International Workshop on Challenges of Large Applications in Distributed Environments}, doi = {10.1109/CLADE.2004.1309087}, keywords = {null}, month = jun, pages = {4}, publisher = {IEEE Computer Society}, title = {Grids for Experimental Science: The Virtual Control Room}, url = {https://doi.ieeecomputersociety.org/10.1109/CLADE.2004.1309087}, year = {2004} }

David P. Schissel, Katarzyna Keahey, Takuya Araki, Justin R. Burruss, Elliot Feibush, S M Flanagan, Ian Foster, Thomas W. Fredian, Martin J. Greenwald, Scott A. Klasky, Torrance Leggett, Kai Li, Doug C. McCune, Peter Lane, Michael E. Papka, Q Peng, Lew Randerson, Allen Sanderson, Joshua Stillerman, Mary R. Thompson, and Grant Wallace, The National Fusion Collaboratory Project: Applying Grid Technology for Magnetic Fusion Research, In Workshop on Case Studies on Grid Applications, 2004

Bib

@inproceedings{ScKeAr04,
  author = {Schissel, David P. and Keahey, Katarzyna and Araki, Takuya and Burruss, Justin R. and Feibush, Elliot and Flanagan, S M and Foster, Ian and Fredian, Thomas W. and Greenwald, Martin J. and Klasky, Scott A. and Leggett, Torrance and Li, Kai and McCune, Doug C. and Lane, Peter and Papka, Michael E. and Peng, Q and Randerson, Lew and Sanderson, Allen and Stillerman, Joshua and Thompson, Mary R. and Wallace, Grant},
  booktitle = {Workshop on Case Studies on Grid Applications},
  title = {The National Fusion Collaboratory Project: Applying Grid Technology for Magnetic Fusion Research},
  year = {2004}
}

David P. Schissel, J.R Burruss, Adam Finkelstein, S M Flanagan, Ian T. Foster, Thomas W. Fredian, Martin J. Greenwald, Chris R. Johnson, Katarzyna Keahey, Scott A. Klasky, Kai Li, Doug C. McCune, Michael E. Papka, Q Peng, Lew Randerson, Allen Sanderson, Joshua Stillerman, Rick Stevens, Mary R. Thompson, and Grant Wallace, Building the US National Fusion Grid: results from the National Fusion Collaboratory Project, Fusion Engineering and Design, 2004 4th IAEA Technical Meeting on Control, Data Acquistion, and Remote Participation for Fusion Research
Abs Bib

The US National Fusion Collaboratory Project is developing a persistent infrastructure to enable scientific collaboration for all aspects of magnetic fusion research. The project is creating a robust, user-friendly collaborative software environment and making it available to more than 1000 fusion scientists in 40 institutions who perform magnetic fusion research in the United States. In particular, the project is developing and deploying a national Fusion Energy Sciences Grid (FusionGrid) that is a system for secure sharing of computation, visualization, and data resources over the Internet. The FusionGrid goal is to allow scientists at remote sites to fully participate in experimental and computational activities as if they were working at a common site thereby creating a virtual organization of the US fusion community. The project is funded by the USDOE Office of Science, Scientific Discovery through Advanced Computing (SciDAC) Program and unites fusion and computer science researchers to directly address these challenges.
@article{ScBuFi04, author = {Schissel, David P. and Burruss, J.R and Finkelstein, Adam and Flanagan, S M and Foster, Ian T. and Fredian, Thomas W. and Greenwald, Martin J. and Johnson, Chris R. and Keahey, Katarzyna and Klasky, Scott A. and Li, Kai and McCune, Doug C. and Papka, Michael E. and Peng, Q and Randerson, Lew and Sanderson, Allen and Stillerman, Joshua and Stevens, Rick and Thompson, Mary R. and Wallace, Grant}, doi = {https://doi.org/10.1016/j.fusengdes.2004.04.041}, issn = {0920-3796}, journal = {Fusion Engineering and Design}, keywords = {Fusion, Computer science, US}, note = {4th IAEA Technical Meeting on Control, Data Acquistion, and Remote Participation for Fusion Research}, number = {1}, pages = {245-250}, title = {Building the US National Fusion Grid: results from the National Fusion Collaboratory Project}, url = {https://www.sciencedirect.com/science/article/pii/S0920379604000535}, volume = {71}, year = {2004} }

Nicholas T. Karonis, Michael E. Papka, Justin Binns, John Bresnahan, and Joseph M. Link, Effective use of dedicated wide-area networks for high-performance distributed computing, 2004

Bib

@techreport{KaPaBi04,
  author = {Karonis, Nicholas T. and Papka, Michael E. and Binns, Justin and Bresnahan, John and Link, Joseph M.},
  institution = {Technical Report ANL/MCS-P1151-0404},
  title = {Effective use of dedicated wide-area networks for high-performance distributed computing},
  year = {2004}
}

Han Gao, Ivan R. Judson, Thomas Uram, Terry L. Disz, Michael E. Papka, and Rick L. Stevens, Capability matching of data streams with network services, In IEEE International Symposium on Cluster Computing and the Grid, 2004. CCGrid 2004., 2004

Bib

@inproceedings{GaJuUr04,
  author = {Gao, Han and Judson, Ivan R. and Uram, Thomas and Disz, Terry L. and Papka, Michael E. and Stevens, Rick L.},
  booktitle = {IEEE International Symposium on Cluster Computing and the Grid, 2004. CCGrid 2004.},
  organization = {IEEE},
  pages = {419--425},
  title = {Capability matching of data streams with network services},
  year = {2004}
}

Wim Drongelen, Hyong C. Lee, Mark Hereld, David Jones, Matthew Cohoon, Frank Elsen, Michael E. Papka, and Rick L. Stevens, Simulation of neocortical epileptiform activity using parallel computing, Neurocomputing, 2004

Bib

@article{DrLeHe04,
  author = {van Drongelen, Wim and Lee, Hyong C. and Hereld, Mark and Jones, David and Cohoon, Matthew and Elsen, Frank and Papka, Michael E. and Stevens, Rick L.},
  journal = {Neurocomputing},
  pages = {1203--1209},
  publisher = {Elsevier},
  title = {Simulation of neocortical epileptiform activity using parallel computing},
  volume = {58},
  year = {2004}
}

2003

Rick Stevens, Michael E. Papka, and Terry Disz, The Access Grid: prototyping-workspaces of the future, IEEE Internet Computing, 2003

Bib

@article{StPaDi03,
  author = {Stevens, Rick and Papka, Michael E. and Disz, Terry},
  journal = {IEEE Internet Computing},
  number = {4},
  pages = {51--58},
  title = {The Access Grid: prototyping-workspaces of the future},
  volume = {7},
  year = {2003}
}

Aditi Majumder, David Jones, Matthew McCrory, Michael E. Papka, and Rick Stevens, Using a camera to capture and correct spatial photometric variation in multi-projector displays, In IEEE International Workshop on Projector-Camera Systems, 2003

Bib

@inproceedings{MaJoMc03,
  author = {Majumder, Aditi and Jones, David and McCrory, Matthew and Papka, Michael E. and Stevens, Rick},
  booktitle = {IEEE International Workshop on Projector-Camera Systems},
  title = {Using a camera to capture and correct spatial photometric variation in multi-projector displays},
  year = {2003}
}

Nicholas T. Karonis, Michael E. Papka, Justin Binns, John Bresnahan, Joseph A. Insley, David Jones, and Joseph M. Link, High-resolution remote rendering of large datasets in a collaborative environment, Future Generation Computer Systems, 2003

Bib

@article{KaPaBi03,
  author = {Karonis, Nicholas T. and Papka, Michael E. and Binns, Justin and Bresnahan, John and Insley, Joseph A. and Jones, David and Link, Joseph M.},
  journal = {Future Generation Computer Systems},
  number = {6},
  pages = {909--917},
  publisher = {North-Holland},
  title = {High-resolution remote rendering of large datasets in a collaborative environment},
  volume = {19},
  year = {2003}
}

Han Gao, Rick L. Stevens, and Michael E. Papka, The design of network services for advanced collaborative enviornments, In Proceedings of the 3rd Workshop on Advanced Collaborative Enviornments (WACE),(Seattle, WA), 2003

Bib

@inproceedings{GaStPa03,
  author = {Gao, Han and Stevens, Rick L. and Papka, Michael E.},
  booktitle = {Proceedings of the 3rd Workshop on Advanced Collaborative Enviornments (WACE),(Seattle, WA)},
  title = {The design of network services for advanced collaborative enviornments},
  year = {2003}
}

2002

W Van Drongelen, M Hereld, HC Lee, ME Papka, and RL Stevens, Simulation of neocortical activity, Epilepsia, 2002

Bib

@article{VaHeLe02,
  author = {Van Drongelen, W and Hereld, M and Lee, HC and Papka, ME and Stevens, RL},
  journal = {Epilepsia},
  number = {Suppl 7},
  pages = {149},
  title = {Simulation of neocortical activity},
  volume = {43},
  year = {2002}
}

Justin Binns, Michael E. Papka, Rick Stevens, Qian Peng, and David Schissel, Development of cluster-based image viewer, In High Performance Distrubuted Computing Conference. Edinburgh, Scotland, UK: IEEE CS Press, 2002

Bib

@inproceedings{BiPaSt02,
  author = {Binns, Justin and Papka, Michael E. and Stevens, Rick and Peng, Qian and Schissel, David},
  booktitle = {High Performance Distrubuted Computing Conference. Edinburgh, Scotland, UK: IEEE CS Press},
  pages = {450--454},
  title = {Development of cluster-based image viewer},
  year = {2002}
}

Justin Binns, Gennette Gill, Mark Hereld, David Jones, Ivan Judson, Torrance Leggett, Aditi Majumder, Matthew McCroy, Michael E. Papka, and Rick Stevens, Applying geometry and color correction to tiled display walls, In IEEE Visualization, 2002

Bib

@inproceedings{BiGiHe02b,
  author = {Binns, Justin and Gill, Gennette and Hereld, Mark and Jones, David and Judson, Ivan and Leggett, Torrance and Majumder, Aditi and McCroy, Matthew and Papka, Michael E. and Stevens, Rick},
  booktitle = {IEEE Visualization},
  title = {Applying geometry and color correction to tiled display walls},
  year = {2002}
}

Justin Binns, Gennette Gill, Mark Hereld, David Jones, Ivan Judson, Torrance Leggett, Aditi Majumder, Matthew McCrory, Michael E. Papka, and Rick Stevens, Applying Geometry and Color Correction to Tiled Display Walls, In IEEE Visualization 2002, 2002

Bib

@inproceedings{BiGiHe02a,
  author = {Binns, Justin and Gill, Gennette and Hereld, Mark and Jones, David and Judson, Ivan and Leggett, Torrance and Majumder, Aditi and McCrory, Matthew and Papka, Michael E. and Stevens, Rick},
  booktitle = {IEEE Visualization 2002},
  organization = {IEEE},
  pages = {POSTER},
  title = {Applying Geometry and Color Correction to Tiled Display Walls},
  year = {2002}
}

William Allcock, Joseph Bester, John Bresnahan, Ian Foster, Jarek Gawor, Joseph A. Insley, Joseph M. Link, and Michael E. Papka, GridMapper: a tool for visualizing the behavior of large-scale distributed systems, In Proceedings 11th IEEE International Symposium on High Performance Distributed Computing, 2002

Bib

@inproceedings{AlBeBr02,
  author = {Allcock, William and Bester, Joseph and Bresnahan, John and Foster, Ian and Gawor, Jarek and Insley, Joseph A. and Link, Joseph M. and Papka, Michael E.},
  booktitle = {Proceedings 11th IEEE International Symposium on High Performance Distributed Computing},
  organization = {IEEE},
  pages = {179--187},
  title = {GridMapper: a tool for visualizing the behavior of large-scale distributed systems},
  year = {2002}
}

2001

Rick Stevens, Michael E. Papka, Mark Kilgard, Greg Humphreys, and Thomas Funkhouser, Commodity Graphics Accelerators for Scientific Visualization[Panel], In Proceedings of the conference on Visualization’01, 2001

Bib

@inproceedings{StPaKi01,
  author = {Stevens, Rick and Papka, Michael E. and Kilgard, Mark and Humphreys, Greg and Funkhouser, Thomas},
  booktitle = {Proceedings of the conference on Visualization'01},
  location = {San Diego, California, USA},
  pages = {527--529},
  title = {Commodity Graphics Accelerators for Scientific Visualization[Panel]},
  year = {2001}
}

Rick Stevens, Michael E. Papka, Chris Johnson, Pauline Baker, Jason Leigh, and Samuel Uselton, Challenges for Remote Visualization [Panel], In Proceedings of the Conference on Visualization’01, 2001

Bib

@inproceedings{StPaJo01,
  author = {Stevens, Rick and Papka, Michael E. and Johnson, Chris and Baker, Pauline and Leigh, Jason and Uselton, Samuel},
  booktitle = {Proceedings of the Conference on Visualization'01},
  location = {San Diego, California, USA},
  pages = {519--522},
  title = {{Challenges for Remote Visualization [Panel]}},
  year = {2001}
}

James Ahrens, Kristi Brislawn, Ken Martin, Berk Geveci, C Charles Law, and Michael E. Papka, Large-scale data visualization using parallel data streaming, IEEE Computer graphics and Applications, 2001

Bib

@article{AhBrMa01,
  author = {Ahrens, James and Brislawn, Kristi and Martin, Ken and Geveci, Berk and Law, C Charles and Papka, Michael E.},
  journal = {IEEE Computer graphics and Applications},
  number = {4},
  pages = {34--41},
  publisher = {IEEE},
  title = {Large-scale data visualization using parallel data streaming},
  volume = {21},
  year = {2001}
}

2000

Tushar Udeshi, Randy Hudson, and Michael E. Papka, Seamless multiresolution isosurfaces using wavelets, 2000

Bib

@techreport{UdHuPa00,
  author = {Udeshi, Tushar and Hudson, Randy and Papka, Michael E.},
  institution = {Argonne National Lab., IL (US)},
  title = {Seamless multiresolution isosurfaces using wavelets},
  year = {2000}
}

Robert Olson, and Michael E. Papka, Remote rendering using vtk and vic., 2000

Bib

@techreport{OlPa00,
  author = {Olson, Robert and Papka, Michael E.},
  institution = {Argonne National Lab., IL (US)},
  title = {Remote rendering using vtk and vic.},
  year = {2000}
}

Lisa Childers, Terrance Disz, Robert Olson, Michael E. Papka, Rick Stevens, and Tushar Udeshi, Access grid: Immersive group-to-group collaborative visualization, In 4th International Immersive Projection Technology Workshop,Jul, 2000
Abs Bib

Immersive projection displays have played an important role in enabling large-format virtual reality systems such as the CAVE and CAVE like devices and the various immersive desks and desktop-like displays. However, these devices have played a minor role so far in advancing the sense of immersion for conferencing systems. The Access Grid project led by Argonne is exploring the use of large-scale projection based systems as the basis for building room oriented collaboration and semi-immersive visualization systems. The authors believe these multi-projector systems will become common infrastructure in the future, largely based on their value for enabling group-to-group collaboration in an environment that can also support large-format projector based visualization. Creating a strong sense of immersion is an important goal for future collaboration technologies. Immersion in conferencing applications implies that the users can rely on natural sight and audio cues to facilitate interactions with participants at remote sites. The Access Grid is a low cost environment aimed primarily at supporting conferencing applications, but it also enables semi-immersive visualization and in particular, remote visualization. In this paper, they describe the current state of the Access Grid project and how it relates and compares to other environments. They also discuss augmentations to the Access Grid that will enable it to support more immersive visualizations. These enhancements include stereo, higher performance rendering support, tracking and non-uniform projection surface.
@inproceedings{ChDiOl00, author = {Childers, Lisa and Disz, Terrance and Olson, Robert and Papka, Michael E. and Stevens, Rick and Udeshi, Tushar}, booktitle = {4th International Immersive Projection Technology Workshop}, month = jul, place = {Ames, IA}, title = {Access grid: Immersive group-to-group collaborative visualization}, url = {https://www.osti.gov/biblio/759072}, year = {2000} }
Lisa Childers, Terry Disz, Mark Hereld, Randy Hudson, Robert Olson, Ivan Judson, Michael E. Papka, Joe Paris, and Rick Stevens, ActiveSpaces on the Grid: The Construction of Advanced Visualization and Interaction Environments, In Simulation and Visualization on the Grid, 2000
Abs Bib

The Futures Laboratory group at Argonne National Laboratory and the University of Chicago are designing, building, and evaluating a new type of interactive computing environment that couples in a deep way the concepts of direct manipulation found in virtual reality with the richness and variety of interactive devices found in ubiquitous computing. This environment provides the interactivity and collaboration support of teleimmersive environments with the flexibility and availability of desktop collaboration tools. We call these environments ActiveSpaces. An ActiveSpace is a physical domain that has been augmented with multiscale multi-screen displays, environment-specific and device-specific sensors, body and object trackers, human-input and instrument-input interfaces, streaming audio and video capture devices, and force feedback devices—and has then been connected to other such spaces via the Grid.
@inproceedings{ChDiHe00, address = {Berlin, Heidelberg}, author = {Childers, Lisa and Disz, Terry and Hereld, Mark and Hudson, Randy and Olson, Robert and Judson, Ivan and Papka, Michael E. and Paris, Joe and Stevens, Rick}, booktitle = {Simulation and Visualization on the Grid}, editor = {Engquist, Bj{\"o}rn and Johnsson, Lennart and Hammill, Michael and Short, Faith}, isbn = {978-3-642-57313-2}, pages = {64--80}, publisher = {Springer Berlin Heidelberg}, title = {ActiveSpaces on the Grid: The Construction of Advanced Visualization and Interaction Environments}, year = {2000} }

John Bresnahan, Joseph Insley, and Michael E. Papka, Interacting with scientific visualizations: User-interface tools within spatially immersive displays, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL ANL/MCS-P789-0100, 2000

Bib

@article{BrInPa00,
  author = {Bresnahan, John and Insley, Joseph and Papka, Michael E.},
  journal = {Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL ANL/MCS-P789-0100},
  title = {Interacting with scientific visualizations: User-interface tools within spatially immersive displays},
  year = {2000}
}

James Ahrens, Charles Law, Will Schroeder, Ken Martin, and Michael E. Papka, A parallel approach for efficiently visualizing extremely large, time-varying datasets, Los Alamos National Laboratory, Tech. Rep.\% LAUR-00-1620, 2000

Bib

@article{AhLaSc00,
  author = {Ahrens, James and Law, Charles and Schroeder, Will and Martin, Ken and Papka, Michael E.},
  journal = {Los Alamos National Laboratory, Tech. Rep.\\% LAUR-00-1620},
  title = {A parallel approach for efficiently visualizing extremely large, time-varying datasets},
  year = {2000}
}

1999

Henry M. Tufo, Paul F. Fischer, Michael E. Papka, and Kris Blom, Numerical Simulation and Immersive Visualization of Hairpin Vortices, In Proceedings of the 1999 ACM/IEEE Conference on Supercomputing, 1999

Bib

@inproceedings{TuFiPa99c,
  address = {New York, NY, USA},
  author = {Tufo, Henry M. and Fischer, Paul F. and Papka, Michael E. and Blom, Kris},
  booktitle = {Proceedings of the 1999 ACM/IEEE Conference on Supercomputing},
  doi = {10.1145/331532.331594},
  isbn = {1581130910},
  location = {Portland, Oregon, USA},
  pages = {62–77},
  publisher = {Association for Computing Machinery},
  series = {SC '99},
  title = {Numerical Simulation and Immersive Visualization of Hairpin Vortices},
  url = {https://doi.org/10.1145/331532.331594},
  year = {1999}
}

HM Tufo, PF Fischer, ME Papka, and M Szymanski, Hairpin vortex formation, a case study for unsteady visualization, In 41st CUG Conference, 1999

Bib

@inproceedings{TuFiPa99b,
  author = {Tufo, HM and Fischer, PF and Papka, ME and Szymanski, M},
  booktitle = {41st CUG Conference},
  organization = {Minneapolis MN},
  title = {Hairpin vortex formation, a case study for unsteady visualization},
  year = {1999}
}

Henry M. Tufo, Paul F. Fischer, Michael E. Papka, and K Blom, Numerical simulation and immersive visualization of hairpin vortices, In SC’99: Proceedings of the 1999 ACM/IEEE Conference on Supercomputing, 1999

Bib

@inproceedings{TuFiPa99a,
  author = {Tufo, Henry M. and Fischer, Paul F. and Papka, Michael E. and Blom, K},
  booktitle = {SC'99: Proceedings of the 1999 ACM/IEEE Conference on Supercomputing},
  organization = {IEEE},
  pages = {62--62},
  title = {Numerical simulation and immersive visualization of hairpin vortices},
  year = {1999}
}

Lori Freitag, Terry Disz, Mike Papka, Darin Diachin, Jim Herzog, and Bob Ryan, A 3D Vector/Scalar Visualization and Particle Tracking Package, Aug, 1999
Abs Bib

BOILERMAKER is an interactive visualization system consisting of three components: a visualization component, a particle tracking component, and a communication layer. The software, to date, has been used primarily in the visualization of vector and scalar fields associated with computational fluid dynamics (CFD) models of flue gas flows in industrial boilers and incinerators. Users can interactively request and toggle static vector fields, dynamic streamlines, and flowing vector fields. In addition, the user can interactively place injector nozzles on boiler walls and visualize massed, evaporating sprays emanating from them. Some characteristics of the spray can be adjusted from within the visualization environment including spray shape and particle size. Also included with this release is software that supports 3D menu capabilities, scrollbars, communication and navigation.
@misc{FrDiPa99, author = {Freitag, Lori and Disz, Terry and Papka, Mike and Diachin, Darin and Herzog, Jim and Ryan, Bob}, doi = {10.11578/dc.20180705.4}, month = aug, title = {A 3D Vector/Scalar Visualization and Particle Tracking Package}, url = {https://www.osti.gov/biblio/1230483}, year = {1999} }
Paul F. Fischer, Michael E. Papka, Matthew Szymanski, and Henry M. Tufo, Hairpin vortex formation, a case study for unsteady visualization, Aug, 1999
Abs Bib

To better understand the vortex dynamics of coherent structures in turbulent and transitional boundary layers, we consider direct numerical simulation of the interaction between a flat-plateboundary-layer flow and an isolated hemispherical roughness element. Of principal interest is the evolution of hairpin vortices that form an interlacing pattern in the wake of the hemisphere, lift away from the wall, and are stretched by the shearing action of the boundary layer. Using animations of unsteady three-dimensional representations of this flow, produced by the vtk toolkit and enhanced to operate in a CAVE virtual environment, we identify and study several key features in the evolution of this complex vortex topology not previously observed in other visualization formats.
@techreport{FiPaSz99, author = {Fischer, Paul F. and Papka, Michael E. and Szymanski, Matthew and Tufo, Henry M.}, institution = {Argonne National Laboratory}, month = aug, number = {ANL/MCS/P774}, place = {United States}, title = {Hairpin vortex formation, a case study for unsteady visualization}, url = {https://www.osti.gov/biblio/11928}, year = {1999} }

1998

Michael E. Papka, Rick Stevens, and Matthew Szymanski, Collaborative virtual reality environments for computational science and design, 1998., 1998

Bib

@article{PaStSz98,
  author = {Papka, Michael E. and Stevens, Rick and Szymanski, Matthew},
  journal = {1998.},
  title = {Collaborative virtual reality environments for computational science and design},
  year = {1998}
}

Terrence L. Disz, Robert Olson, Michael E. Papka, Rick Stevens, Matthew Szymanski, and R. James Firby, Two implementations of shared virtual space environments, Jan, 1998

Bib

@techreport{DiOlPa98,
  address = {Lemont, IL},
  author = {Disz, Terrence L. and Olson, Robert and Papka, Michael E. and Stevens, Rick and Szymanski, Matthew and Firby, R. James},
  institution = {Argonne National Laboratory},
  month = jan,
  number = {ANL/MCS-P652-0297},
  title = {Two implementations of shared virtual space environments},
  type = {Technical Report},
  year = {1998}
}

1997

Terry Disz, Michael E. Papka, and Rick Stevens, UbiWorld: an environment integrating virtual reality, supercomputing, and design, In Proceedings Sixth Heterogeneous Computing Workshop (HCW’97), 1997

Bib

@inproceedings{DiPaSt97,
  author = {Disz, Terry and Papka, Michael E. and Stevens, Rick},
  booktitle = {Proceedings Sixth Heterogeneous Computing Workshop (HCW'97)},
  organization = {IEEE},
  pages = {46--57},
  title = {UbiWorld: an environment integrating virtual reality, supercomputing, and design},
  year = {1997}
}

1996

Valerie E. Taylor, Jian Chen, Terrence L. Disz, Michael E. Papka, and Rick Stevens, Immersive Visualization of Supercomputer Applications: A Survey of Lag Models, Computational Science and Engineering, 1996

Bib

@article{TaChDi96b,
  author = {Taylor, Valerie E. and Chen, Jian and Disz, Terrence L. and Papka, Michael E. and Stevens, Rick},
  journal = {Computational Science and Engineering},
  number = {4},
  pages = {46--54},
  title = {Immersive Visualization of Supercomputer Applications: A Survey of Lag Models},
  volume = {3},
  year = {1996}
}

Valerie E. Taylor, Jian Chen, Terrence L. Disz, Michael E. Papka, and Rick Stevens, Interactive virtual reality in simulations: Exploring lag time, IEEE Computational Science and Engineering, 1996

Bib

@article{TaChDi96a,
  author = {Taylor, Valerie E. and Chen, Jian and Disz, Terrence L. and Papka, Michael E. and Stevens, Rick},
  journal = {IEEE Computational Science and Engineering},
  number = {4},
  pages = {46--54},
  publisher = {IEEE},
  title = {Interactive virtual reality in simulations: Exploring lag time},
  volume = {3},
  year = {1996}
}

Michael E. Papka, and Rick Stevens, Ubiworld: An environment integrating virtual reality, supercomputing and design, In Proceedings of 5th IEEE International Symposium on High Performance Distributed Computing, 1996

Bib

@inproceedings{PaSt96,
  author = {Papka, Michael E. and Stevens, Rick},
  booktitle = {Proceedings of 5th IEEE International Symposium on High Performance Distributed Computing},
  organization = {IEEE},
  pages = {306--307},
  title = {Ubiworld: An environment integrating virtual reality, supercomputing and design},
  year = {1996}
}

Ian Foster, Michael E. Papka, and Rick Stevens, Tools for distributed collaborative environments: a research agenda, In Proceedings of 5th IEEE International Symposium on High Performance Distributed Computing, 1996

Bib

@inproceedings{FoPaSt96,
  author = {Foster, Ian and Papka, Michael E. and Stevens, Rick},
  booktitle = {Proceedings of 5th IEEE International Symposium on High Performance Distributed Computing},
  organization = {IEEE},
  pages = {23--28},
  title = {Tools for distributed collaborative environments: a research agenda},
  year = {1996}
}

Terrence L. Disz, Michael E. Papka, Michael Pellegrino, and Matthew Szymanski, CAVEComm users manual, Argonne National Laboratory, Argonne, Technical Memoramum ANL/MCSTM-218, 1996

Bib

@article{DiPaPe96b,
  author = {Disz, Terrence L. and Papka, Michael E. and Pellegrino, Michael and Szymanski, Matthew},
  journal = {Argonne National Laboratory, Argonne, Technical Memoramum ANL/MCSTM-218},
  title = {CAVEComm users manual},
  year = {1996}
}

Terrence L. Disz, Michael E. Papka, Michael Pellegrino, and Rick Stevens, Sharing Visualization Experiences among Remote Virtual Environments, In High Performance Computing for Computer Graphics and Visualisation, 1996
Abs Bib

Virtual reality has become an increasingly familiar part of the science of visualization and communication of information. This, combined with the increase in connectivity of remote sites via high-speed networks, allows for the development of a collaborative distributed virtual environ-ment. Such an environment enables the development of supercomputer simulations with virtual reality visualizations that can be displayed at multiple sites, with each site interacting, viewing, and communicating about the results being discovered.
@inproceedings{DiPaPe96a, address = {London}, author = {Disz, Terrence L. and Papka, Michael E. and Pellegrino, Michael and Stevens, Rick}, booktitle = {High Performance Computing for Computer Graphics and Visualisation}, editor = {Chen, M. and Townsend, P. and Vince, J. A.}, isbn = {978-1-4471-1011-8}, pages = {217--237}, publisher = {Springer London}, title = {Sharing Visualization Experiences among Remote Virtual Environments}, year = {1996} }
Thomas A. DeFanti, Ian Foster, Michael E. Papka, Rick Stevens, and Tim Kuhfuss, Overview of the I-Way: Wide-Area Visual Supercomputing, The International Journal of Supercomputer Applications and High Performance Computing, 1996
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This paper discusses the I-WAY project and provides an overview of the papers in this issue of IJSA. The I-WAY is an experimental environment for building distributed virtual reality applications and for exploring issues of distrib uted wide-area resource management and scheduling. The goal of the I-WAY project is to enable researchers to use multiple internetworked supercomputers and ad vanced visualization systems to conduct very large scale computations. By connecting 12 ATM testbeds, 17 supercomputer centers, 5 virtual reality research sites, and over 60 applications groups, the I-WAY project has created an extremely diverse wide-area environment for exploring advanced applications. This environment has provided a glimpse of the future for advanced scientific and engineering computing.
@article{DeFoPa96, author = {DeFanti, Thomas A. and Foster, Ian and Papka, Michael E. and Stevens, Rick and Kuhfuss, Tim}, doi = {10.1177/109434209601000201}, eprint = {https://doi.org/10.1177/109434209601000201}, journal = {The International Journal of Supercomputer Applications and High Performance Computing}, number = {2-3}, pages = {123-131}, publisher = {Sage Publications Sage CA: Thousand Oaks, CA}, title = {Overview of the I-Way: Wide-Area Visual Supercomputing}, url = {https://doi.org/10.1177/109434209601000201}, volume = {10}, year = {1996} }
Tom Canfield, Terry Disz, Michael E. Papka, Rick Stevens, Milana Huang, Valerie Taylor, and Jian Chen, Toward real-time interactive virtual prototyping of mechanical systems: experiences coupling virtual reality with finite element analysis, In Proceedings of High Performance Computing 1996: Grand Challenges in Computer Simulation, 1996
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Virtual prototyping involves a synthesis of engineering methodology and immersive, three-dimensional visualization technology. Ideally, this is a process in which computational models are used in place of physical models in the development of a new product or design concept. If used successfully, virtual prototyping can lead to more rapid product design and development. Software is currently being developed that will enable virtual prototyping of mechanical systems in the CAVE (CAVE Automatic Virtual Environment) at Argonne National Laboratory. This software has two principal components: (1) fast simulation software, FIFEA (Fast Implicit Finite Element Analysis), for analyzing mechanical systems and (2) virtual reality display software for visualizing results and allowing user interaction. This paper discusses various issues related to the coupling of finite element software to the CAVE display system.
@inproceedings{CaDiPa96, author = {Canfield, Tom and Disz, Terry and Papka, Michael E. and Stevens, Rick and Huang, Milana and Taylor, Valerie and Chen, Jian}, booktitle = {Proceedings of High Performance Computing 1996: Grand Challenges in Computer Simulation}, organization = {Society for Computer Simulation}, title = {Toward real-time interactive virtual prototyping of mechanical systems: experiences coupling virtual reality with finite element analysis}, year = {1996} }

1995

LR Turner, D Levine, M Huang, M Papka, and L Kettunen, Using the CAVE virtual-reality environment as an aid to 3-D electromagnetic field computation, 1995

Bib

@techreport{TuLeHu95,
  author = {Turner, LR and Levine, D and Huang, M and Papka, M and Kettunen, L},
  institution = {Argonne National Laboratory, Argonne, IL (United States)},
  title = {Using the CAVE virtual-reality environment as an aid to 3-D electromagnetic field computation},
  year = {1995}
}

Milana Huang, Michael Papka, Thomas DeFanti, David Levine, Larry Turner, and Lauri Kettunen, Virtual reality visualization of accelerator magnets, 1995

Bib

@techreport{HuPaDe95,
  author = {Huang, Milana and Papka, Michael and DeFanti, Thomas and Levine, David and Turner, Larry and Kettunen, Lauri},
  institution = {Argonne National Laboratory, Argonne, IL (United States)},
  title = {Virtual reality visualization of accelerator magnets},
  year = {1995}
}

Terrence Disz, Michael E. Papka, Rick Stevens, Michael Pellegrino, and Valerie Taylor, Virtual reality visualization of parallel molecular dynamics simulation, 1995

Bib

@techreport{DiPaSt95,
  author = {Disz, Terrence and Papka, Michael E. and Stevens, Rick and Pellegrino, Michael and Taylor, Valerie},
  institution = {Argonne National Laboratory, Argonne, IL (United States)},
  title = {Virtual reality visualization of parallel molecular dynamics simulation},
  year = {1995}
}

Terrence L. Disz, Remy Evard, Mark W. Henderson, William Nickless, Robert Olson, Michael E. Papka, and Rick Stevens, Designing the future of collaborative science: Argonne’s futures laboratory, IEEE Parallel and Distributed Technology: Systems and Applications, 1995

Bib

@article{DiEvHe95,
  author = {Disz, Terrence L. and Evard, Remy and Henderson, Mark W. and Nickless, William and Olson, Robert and Papka, Michael E. and Stevens, Rick},
  journal = {IEEE Parallel and Distributed Technology: Systems and Applications},
  number = {2},
  pages = {14--21},
  publisher = {IEEE},
  title = {Designing the future of collaborative science: Argonne's futures laboratory},
  volume = {3},
  year = {1995}
}

1994

Michael E. Papka, MS Thesis: Extending genetic programming for discrete volume visualization, University of Illinois at Chicago, 1994

Bib

@phdthesis{Pa94,
  author = {Papka, Michael E.},
  school = {University of Illinois at Chicago},
  title = {MS Thesis: Extending genetic programming for discrete volume visualization},
  year = {1994}
}

Sumit Das, Terry Franguiadakis, Michael E. Papka, Thomas A. DeFanti, and Daniel J. Sandin, A genetic programming application in virtual reality, In Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference, 1994

Bib

@inproceedings{DaFrPa94,
  author = {Das, Sumit and Franguiadakis, Terry and Papka, Michael E. and DeFanti, Thomas A. and Sandin, Daniel J.},
  booktitle = {Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference},
  organization = {IEEE},
  pages = {1985--1989},
  title = {A genetic programming application in virtual reality},
  year = {1994}
}

1993

Carolina Cruz-Neira, Jason Leigh, Michael E. Papka, Craig Barnes, Steven M. Cohen, Sumit Das, Roger Engelmann, Randy Hudson, Trina Roy, Lewis Siegel, Christina Vasilakis, Thomas A. DeFanti, and Daniel J. Sandin, Scientists in wonderland: A report on visualization applications in the CAVE virtual reality environment, In Proceedings of 1993 IEEE Research Properties in Virtual Reality Symposium,Oct, 1993
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The authors present the experiences at the Electronic Visualization Laboratory (EVL) in introducing computational scientists to the use of virtual reality as a research tool. They describe the virtual environment, the CAVE. They then describe several applications currently being developed at EVL using the CAVE and conclude with a discussion on possible research paths to follow in making virtual reality an effective tool for visualization.
@inproceedings{CrLePa93, author = {Cruz-Neira, Carolina and Leigh, Jason and Papka, Michael E. and Barnes, Craig and Cohen, Steven M. and Das, Sumit and Engelmann, Roger and Hudson, Randy and Roy, Trina and Siegel, Lewis and Vasilakis, Christina and DeFanti, Thomas A. and Sandin, Daniel J.}, booktitle = {Proceedings of 1993 IEEE Research Properties in Virtual Reality Symposium}, doi = {10.1109/VRAIS.1993.378262}, month = oct, pages = {59-66}, title = {Scientists in wonderland: A report on visualization applications in the CAVE virtual reality environment}, year = {1993} }