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Conference Papers Year : 2023

Using Mixed-Radix Decomposition to Enumerate Computational Resources of Deeply Hierarchical Architectures

Abstract

Current HPC architectures are deeply hierarchical (racks, nodes, sockets, NUMA domains, caches, ...), and the mapping of MPI processes to cores can significantly influence application performance. To study hierarchy effects on MPI application performance, we propose a procedure for expressing mappings by enumerating cores in the hierarchy in different orders. We explore two use cases: MPI rank reordering for applications using subcommunicators, and core selection for applications not using all cores on a node. Results of micro-benchmarks executing collective operations in subcommunicators show a performance difference up to a factor 4 between the best and the worst rank orderings. By changing the rank orders, we observe a performance impact for the Splatt application. The evaluation of the strong scalability of a conjugate gradient benchmark shows that considering all hierarchy levels in the core selection policy can give better performance than using only options available with common MPI application launchers.
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hal-04283479 , version 1 (13-11-2023)

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Philippe Swartvagher, Sascha Hunold, Jesper Larsson Träff, Ioannis Vardas. Using Mixed-Radix Decomposition to Enumerate Computational Resources of Deeply Hierarchical Architectures. SC 2023 - Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, Nov 2023, Denver, CO, United States. pp.404-415, ⟨10.1145/3624062.3624109⟩. ⟨hal-04283479⟩
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