2022 Fiscal Year Final Research Report
Write latency reduction on PCM for approximate computing
| Project/Area Number |
20K11728
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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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| Review Section |
Basic Section 60040:Computer system-related
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| Research Institution | Chiba University |
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Principal Investigator |
Kazuteru NAMBA 千葉大学, 大学院工学研究院, 准教授 (60359594)
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| Co-Investigator(Kenkyū-buntansha) |
イン ユウ 群馬大学, 大学院理工学府, 教授 (10520124)
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| Project Period (FY) |
2020-04-01 – 2023-03-31
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| Keywords | メモリシステム / 誤差許容計算 |
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| Outline of Final Research Achievements |
This work has not achieved a write time reduction, which was the main objective. However, we have presented several related techniques, such as power consumption reduction on memory systems for an approximate computing system.
For example, we have presented a power consumption reduction for a neural network system, a typical example of an approximate computing system. The proposed system uses two different power supply voltages. The proposed method achieves a power consumption reduction of 35%, avoiding a significant reduction in the recognition rate.
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| Free Research Field |
情報学
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| Academic Significance and Societal Importance of the Research Achievements |
本研究においては主目的であった書き込み時間削減については結果を出せていない。しかし，副産物と言える消費電力削減手法などはいずれも実用性の高いものであり，本研究成果の工業的産業的重要性は十分に高いものであったと言える。また，目的であったメモリシステム書き込み時間についてもいくつかの知見が得られており，研究当初に考えていた問いにもいくらかは答えられた，学術的にも意義がある研究であったと考えている。
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