Performance Projection for Design-Space Exploration on future HPC Architectures
Clément Gavoille, Hugo Taboada, Jens Domke, Brice Goglin, Emmanuel Jeannot · 2025
To address the growing need for performance from future HPC machines, their processor designs are constantly evolving. Assessing the impact of changes in hardware, software stack, and applications on performance is crucial in every step of a codesign process. Here, we propose a performance projection workflow to facilitate the exploration of design space for multicore nodes and multi-threaded applications. For this purpose, we analyze the architectural efficiency of an accessible source machine and determine the maximum sustainable flop/s performance of a hypothetical target machine based on its software stack on a per-thread basis. Finally, we use these characterizations to project the performance evolution from the source machine to the target machine. In this work, we assess the strengths and weaknesses of our approach by integrating it into the Fugaku-Next Feasibility Study. We compare the accuracy and overhead of our approach with the gem5 cycle-level simulations and a fast exploration methodology based on Machine Code Analyzer (MCA), using NAS Parallel benchmarks and CCS-QCD, a quantum chromodynamics miniapp. The study demonstrates that, compared to gem5, our approach has a prediction deviation of 5% for most cases and up to 30% for extreme cases. Additionally, it exhibits an execution overhead an order of magnitude bigger than MCA but orders of magnitude smaller than gem5. Finally, we demonstrate our approach's capability to study larger scale and more representative applications than gem5, such as QWS and Genesis, two applications of RIKEN optimized for Fugaku.