Non-uniform MPI_Alltoallv communication is critical in many high-performance computing (HPC) applications where data exchange patterns vary significantly between processes. However, existing MPI implementations rely on fixed heuristics that are not well-suited for dynamic, irregular workloads, often leading to suboptimal performance. Furthermore, there are customized non-uniform All-to-all functions having performance advantage compared to official MPI Alltoallv, under certain scenarios. Creating a framework which can accurately select the optimal algorithm will be extremely beneficial, but challenging due to its potential complexity.

Currently, there are research works regarding the data-driven approach for tuning MPI functions, but most of them they focus on MPI functions such as MPI_Scatter, MPI_Reduce, MPI_gather, uniform MPI_Alltoall Non-uniform Alltoall is still an under-developed area. One challenge of developing a tuning framework for non-uniform Alltoall is that the blocksizes between processes are not fixed and it introduces significant additional complexity to the tuning workflow.

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Qi, K., Fan, K., Kumar, S., Performance Characterization and Tuning of Non-uniform All-to-all Data Exchanges (poster), The 12th Greater Chicago Area Systems Research Workshop (GCASR), Chicago, IL, May 8th, 2025. https://gcasr.org/2025/posters