SC20 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

Performance Modeling of Streaming Kernels and Sparse Matrix-Vector Multiplication on A64FX


Workshop:PMBS20: The 11th International Workshop on Performance Modeling, Benchmarking and Simulation of High-Performance Computer Systems

Authors: Christie Louis Alappat (Erlangen Regional Computing Center, Friedrich-Alexander University Erlangen-Nuremberg); Jan Laukemann (Friedrich-Alexander University Erlangen-Nuremberg); Thomas Gruber, Georg Hager, and Gerhard Wellein (Erlangen Regional Computing Center, Friedrich-Alexander University Erlangen-Nuremberg); and Nils Meyer and Tilo Wettig (University of Regensburg, Bavaria)


Abstract: The A64FX CPU powers the current #1 supercomputer on the Top500 list. Although it is a traditional cache-based multicore processor, its peak performance and memory bandwidth rival accelerator devices. Generating efficient code for such a new architecture requires a good understanding of its performance features. Using these features, we construct the Execution-Cache-Memory (ECM) performance model for the A64FX processor in the FX700 supercomputer and validate it using streaming loops. We also identify architectural peculiarities and derive optimization hints. Applying the ECM model to sparse matrix-vector multiplication (SpMV), we motivate why the CRS matrix storage format is inappropriate and how the SELL-C-σ format with suitable code optimizations can achieve bandwidth saturation for SpMV.





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