Development of data-driven custom pipeline processing system for accelerating big data processing
| Project/Area Number |
26540019
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Computer system
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| Research Institution | Tokyo Institute of Technology (2015-2017)
Japan Advanced Institute of Science and Technology (2014) |
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Principal Investigator |
Sato Yukinori 東京工業大学, 学術国際情報センター, 特任講師 (30452113)
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| Research Collaborator |
LUK Wayne Imperial College London, Department of Computing, Professor
MENCER Oskar Maxeler Technologies Ltd, CEO/CTO
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| Project Period (FY) |
2014-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2016: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2015: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2014: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | FPGAアクセラレータ / カスタムコンピューティング / ビッグデータ / ハード・ソフト協調設計 / データ局所性 / アクセラレーション / ハード・ソフト強調設計 |
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| Outline of Final Research Achievements |
In this research, we developed a data-driven custom pipeline processing system for accelerating big data processing, which attempts to make full use of FPGA accelerators that can customize their memory hierarchy and datapath with high-level synthesis tool chains. We focused on the following core technologies that enhance data locality within time and space dimensions; (1) data locality optimization by loop tiling, (2) a new dataflow profiling technique based on semantics of data manipulation, (3) a novel framework for large-scale data stream processing. As a result of implementation and evaluation of these technologies, we showed that our proposal is beneficial to improving productivity of customization.
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Report
(5 results)
Research Products
(5 results)
