Development of GPU/CPU computing framework for realizing large-scale and high-resolution simulations
| Project/Area Number |
15K20995
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
High performance computing
Computational science
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
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| Project Period (FY) |
2015-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2016: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2015: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | 高性能計算 / GPU / ステンシル計算 / 適合細分化格子 / 高生産フレームワーク / スーパーコンピュータ / 適合細分化格子法 |
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| Outline of Final Research Achievements |
Recently grid-based physical simulations with multiple GPUs require effective methods to adapt grid resolution to certain sensitive regions of simulations. In this research, we have developed a framework technology that can execute the translated user code on either multiple multicore CPUs or multiple GPUs with optimization. We have also developed highly productive data structures and auto-tuning mechanism to achieve high performance on GPU. Based on these technologies, we propose a high-productivity framework for an adaptive mesh refinement (AMR) method; the AMR method is one of the effective methods on GPU to compute certain local regions that demand higher accuracy with higher resolution. The compressive fluid calculation based on the proposed AMR framework has demonstrated good results. The proposed AMR framework can contribute to hiding the complicated implementation required by the AMR method and improving the productivity of AMR applications.
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Report
(3 results)
Research Products
(15 results)
