Practical acceleration methods to achieve high performance for large-scale applications
Takashi Shimokawabe(Information Technology Center, The University of Tokyo)

This project aims to establish practical methodologies for porting CPU applications to accelerator-equipped supercomputers, focusing on the NVIDIA GH200-based “Miyabi-G” system. Through collaboration between domain and HPC experts, it addresses the trade-offs between performance, portability, and maintainability. The research includes five themes: optimizing unified memory for OpenSWPC, developing a lambda-based custom wrapper for N-body codes, improving Kokkos performance for fluid dynamics, introducing a Kokkos-Python interface via MLIR, and enhancing the Kokkos ecosystem. These efforts utilize the GH200’s tightly coupled architecture to advance scientific applications.

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