Realizing Fast and Scalable Brain Information Processing based on Skeletal Parallel Programming
| Project/Area Number |
25330088
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Software
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| Research Institution | Kochi University of Technology |
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Principal Investigator |
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| Project Period (FY) |
2013-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2015: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2014: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2013: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Keywords | 並列プログラミング / 脳情報処理 / 計算パターン / 超解像処理 / MapReduce / ソフトウェア / fMRI / 超解像 / 並列化 / 脳科学 |
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| Outline of Final Research Achievements |
This research is to apply systematic parallel programming methodology to applications in the brain science area. It consists of the following two tasks: task 1) application of parallel programming to brain image processing applications; task 2) study on large-scale parallel/distributed framework for brain-image database. We applied three program-optimization methods to super-resolution processing of fMRI images and obtained speedups by a factor of about three by each of methods. We also proposed an algorithm to process data with tree dependency on the MapReduce framework and formalized the functional model of Hadoop MapReduce.
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Report
(4 results)
Research Products
(11 results)
