Power-Efficient Breadth-First Search with DRAM Row Buffer Locality-Aware Address Mapping

Satoshi Imamura, Yuichiro Yasui, Koji Inoue, Takatsugu Ono, Hiroshi Sasaki, Katsuki Fujisawa

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

2 被引用数 (Scopus)

抄録

Graph analysis applications have been widely used in real services such as road-traffic analysis and social network services. Breadth-first search (BFS) is one of the most representative algorithms for such applications; therefore, many researchers have tuned it to maximize performance. On the other hand, owing to the strict power constraints of modern HPC systems, it is necessary to improve power efficiency (i.e., performance per watt) when executing BFS. In this work, we focus on the power efficiency of DRAM and investigate the memory access pattern of a state-of-the-art BFS implementation using a cycle-accurate processor simulator. The results reveal that the conventional address mapping schemes of modern memory controllers do not efficiently exploit row buffers in DRAM. Thus, we propose a new scheme called per-row channel interleaving and improve the DRAM power efficiency by 30.3% compared to a conventional scheme for a certain simulator setting. Moreover, we demonstrate that this proposed scheme is effective for various configurations of memory controllers.

本文言語英語
ホスト出版物のタイトルProceedings of HPGDMP 2016
ホスト出版物のサブタイトルHigh Performance Graph Data Management and Processing - Held in conjunction with SC 2016: The International Conference for High Performance Computing, Networking, Storage and Analysis
出版社Institute of Electrical and Electronics Engineers Inc.
ページ17-24
ページ数8
ISBN(電子版)9781509038800
DOI
出版ステータス出版済み - 1 23 2017
イベント2016 High Performance Graph Data Management and Processing, HPGDMP 2016 - Salt Lake City, 米国
継続期間: 11 13 2016 → …

出版物シリーズ

名前Proceedings of HPGDMP 2016: High Performance Graph Data Management and Processing - Held in conjunction with SC 2016: The International Conference for High Performance Computing, Networking, Storage and Analysis

その他

その他2016 High Performance Graph Data Management and Processing, HPGDMP 2016
国/地域米国
CitySalt Lake City
Period11/13/16 → …

All Science Journal Classification (ASJC) codes

  • ハードウェアとアーキテクチャ

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