Multi-Layer In-Memory Processing

Daichi Fujiki, Alireza Khadem, Scott Mahlke, Reetuparna Das

研究成果: Conference contribution

抄録

In-memory computing provides revolutionary changes to computer architecture by fusing memory and computation, allowing data-intensive computations to reduce data communications. Despite promising results of in-memory computing in each layer of the memory hierarchy, an integrated approach to a system with multiple computable memories has not been examined. This paper presents a holistic and application-driven approach to building Multi-Layer In-Memory Processing (MLIMP) systems, enabling applications with variable computation demands to reap the benefits of heterogeneous compute resources in an integrated MLIMP system. By introducing concurrent task scheduling to MLIMP, we achieve improved performance and energy efficiency for graph neural networks and multiprogramming of data parallel applications.

本文言語English
ホスト出版物のタイトルProceedings - 2022 55th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2022
出版社IEEE Computer Society
ページ920-936
ページ数17
ISBN(電子版)9781665462723
DOI
出版ステータスPublished - 2022
イベント55th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2022 - Chicago, United States
継続期間: 2022 10月 12022 10月 5

出版物シリーズ

名前Proceedings of the Annual International Symposium on Microarchitecture, MICRO
2022-October
ISSN(印刷版)1072-4451

Conference

Conference55th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2022
国/地域United States
CityChicago
Period22/10/122/10/5

ASJC Scopus subject areas

  • ハードウェアとアーキテクチャ

フィンガープリント

「Multi-Layer In-Memory Processing」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル