2021 Fiscal Year Final Research Report
A research and development of an advanced CFD algorithm for next generation multi FPGA system.
| Project/Area Number |
19K20282
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 60090:High performance computing-related
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| Research Institution | Meiji University (2021)
Institute of Physical and Chemical Research (2019-2020) |
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Principal Investigator |
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| Project Period (FY) |
2019-04-01 – 2022-03-31
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| Keywords | コンフィギュラブル・コンピューティング / 数値流体力学 / 高性能計算 / MPS法 |
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| Outline of Final Research Achievements |
A proposal to make a search for neighbour particles in MPS method into a form of data flow was published at an international conference. The proposal was also implemented on FPGA and evaluated. It is shown that the processing time on Arria10 FPGA slightly out-perform it on multi-core CPU. We found that there is room for improvement in a proposed model to estimate circuit area. Regarding multiple FPGA, a bridged data transfer with CPU was proposed and evaluated. An evaluation shows that although the bridged data transfer is more flexible than FPGA dedicated data transfer, bandwidth is lower than FPGA-dedicated one. We are now considering using the latter one to achieve higher performance.
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| Free Research Field |
高性能計算
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| Academic Significance and Societal Importance of the Research Achievements |
非圧縮性流体の解析に用いられる粒子法の一種である、MPS法について、初めてデータフロー型のアルゴリズムの提案を行った。提案手法は広帯域のメモリを必要としない方法で、GPUなどの広帯域メモリを性能向上の要因とするデバイスの性能向上が頭打ちになった場合にも利用可能な手法である。他の粒子法に応用可能かどうかの要因解析も終わっており、Incompressive SPH法などへの応用も期待できる。
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