Abstract
Accelerated computing in HPC such as with GPU, plays a central role in HPC nowadays. However, in some complicated applications with partially different performance behavior is hard to solve with a single type of accelerator where GPU is not the perfect solution in these cases. We are developing a framework and transpiler allowing the users to program the codes with a single notation of OpenACC to be compiled for multi-hybrid accelerators, named MHOAT (Multi-Hybrid OpenACC Translator) for HPC applications. MHOAT parses the original code with directives to identify the target accelerating devices, currently supporting NVIDIA GPU and Intel FPGA, dispatching these specific partial codes to background compilers such as NVIDIA HPC SDK for GPU and OpenARC research compiler for FPGA, then assembles binaries for the final object with FPGA bitstream file. In this paper, we present the concept, design, implementation, and performance evaluation of a practical astrophysics simulation code where we successfully enhanced the performance up to 10 times faster than the GPU-only solution.
Original language | English |
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Title of host publication | High Performance Computing - ISC High Performance 2023 International Workshops, Revised Selected Papers |
Editors | Amanda Bienz, Michèle Weiland, Marc Baboulin, Carola Kruse |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 662-674 |
Number of pages | 13 |
ISBN (Print) | 9783031408427 |
DOIs | |
State | Published - 2023 |
Event | 38th International Conference on High Performance Computing, ISC High Performance 2023 - Hamburg, Germany Duration: May 21 2023 → May 25 2023 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 13999 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 38th International Conference on High Performance Computing, ISC High Performance 2023 |
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Country/Territory | Germany |
City | Hamburg |
Period | 05/21/23 → 05/25/23 |
Funding
Acknowledgements. This work is supported by JSPS KAKENHI (Grant Number 21H04869). The Cygnus utilization is supported by the MCRP 2022 Program by the Center for Computational Sciences, University of Tsukuba.
Keywords
- FPGA
- GPU
- MHOAT
- OpenACC
- Programming framework