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Memory System Optimzation for Energy Efficient Big Data Processing

Research Project

Project/Area Number 16H06677
Research Category

Grant-in-Aid for Research Activity Start-up

Allocation TypeSingle-year Grants
Research Field Computer system
Research InstitutionThe University of Tokyo

Principal Investigator

Arima Eishi  東京大学, 情報基盤センター, 特任助教 (50780699)

Research Collaborator Schulz Martin  Lawrence Livermore National Laboratory, Computer Scientist
Project Period (FY) 2016-08-26 – 2018-03-31
Project Status Completed (Fiscal Year 2017)
Budget Amount *help
¥2,990,000 (Direct Cost: ¥2,300,000、Indirect Cost: ¥690,000)
Fiscal Year 2017: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2016: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Keywordsメモリシステム / ビッグデータ / 高電力効率化 / キャッシュ / ストレージクラスメモリ / 計算機システム / 電力制御
Outline of Final Research Achievements

To improve the energy efficiency of big data processing, this work focused on optimizing memory systems, the major performance/power bottlenecks during executing big data applications, by hardware/software-side approaches. In particular, this work is based on two novel approaches: (1) address translation aware cache management and (2) storage class memory aware power management. Consequently, it is quantified that a few tens of percent of energy efficiency improvement can be achieved by applying those methods.

Report

(3 results)
  • 2017 Annual Research Report   Final Research Report ( PDF )
  • 2016 Annual Research Report
  • Research Products

    (4 results)

All 2018 2017 Other

All Int'l Joint Research (1 results) Presentation (3 results) (of which Int'l Joint Research: 1 results)

  • [Int'l Joint Research] Lawrence Livermore National Laboratory(米国)

    • Related Report
      2017 Annual Research Report
  • [Presentation] ハイブリッドメモリを搭載するシステムにおけるデータサイズを考慮した電力制御2018

    • Author(s)
      有間 英志,塙 敏博
    • Organizer
      2018-HPC-164
    • Related Report
      2017 Annual Research Report
  • [Presentation] Near Memory Processing on Hybrid Memories2017

    • Author(s)
      Eishi Arima
    • Organizer
      2017-ARC-224
    • Place of Presentation
      慶応大学(神奈川県・横浜市)
    • Year and Date
      2017-01-23
    • Related Report
      2016 Annual Research Report
  • [Presentation] Page Table Walk Aware Cache Management for Efficient Big Data Processing2017

    • Author(s)
      Eishi Arima, and Hiroshi Nakamura
    • Organizer
      The Eighth Workshop on Big Data Benchmarks, Performance Optimization, and Emerging Hardware (BPOE-8)
    • Place of Presentation
      西安(中華人民共和国)
    • Related Report
      2016 Annual Research Report
    • Int'l Joint Research

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Published: 2016-09-02   Modified: 2022-05-23  

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