| Project/Area Number |
24300112
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Partial Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Bioinformatics/Life informatics
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| Research Institution | Keio University |
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Principal Investigator |
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| Co-Investigator(Renkei-kenkyūsha) |
HIROI Noriko 慶應義塾大学, 理工学部・生命情報学科, 専任講師 (20548408)
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| Project Period (FY) |
2012-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥17,940,000 (Direct Cost: ¥13,800,000、Indirect Cost: ¥4,140,000)
Fiscal Year 2014: ¥5,200,000 (Direct Cost: ¥4,000,000、Indirect Cost: ¥1,200,000)
Fiscal Year 2013: ¥5,980,000 (Direct Cost: ¥4,600,000、Indirect Cost: ¥1,380,000)
Fiscal Year 2012: ¥6,760,000 (Direct Cost: ¥5,200,000、Indirect Cost: ¥1,560,000)
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| Keywords | 情報工学 / 並列処理 / GPGPU / 空間モデル / 偏微分方程式 / 数値積分 / SBML / ハイパフォーマンス・コンピューティング / システムバイオロジー / 生体生命情報学 / バイオテクノロジー |
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| Outline of Final Research Achievements |
On a spatial model simulation based on PDEs, the simulation space is discretized by grid and simulators will compute on each grid sequentially which will increase the simulation time enormously depending on the number of grids. In order to solve this problem, we have applied parallelization of this sequential numerical integration on GPGPU (General Purpose computing on GPU).
In this research, we parallelized a CPU-based SBML spatial model simulator by GPGPU. We implemented numerical integration of advection, reaction and diffusion equation with NVIDIA CUDA. For the evaluation of the CPU application, we used Intel Xeon X5687 and for the evaluation of GPU case, we used Tesla K40. As a result, we achieved 52x performance improvement in advection equation, 64x in reaction equation, 63x in diffusion equation for 512x512 grids.
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