Data movement aware computation partitioning

Xulong Tang, Orhan Kislal, Mahmut Kandemir, Mustafa Karakoy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

39 Scopus citations


Data access costs dominate the execution times of most parallel applications and they are expected to be even more important in the future. To address this, recent research has focused on Near Data Processing (NDP) as a new paradigm that tries to bring computation to data, instead of bringing data to computation (which is the norm in conventional computing). This paper explores the potential of compiler support in exploiting NDP in the context of emerging manycore systems. To that end, we propose a novel compiler algorithm that partitions the computations in a given loop nest into subcomputations and schedules the resulting subcomputations on different cores with the goal of reducing the distance-to-data on the on-chip network. An important characteristic of our approach is that it exploits NDP while taking advantage of data locality. Our experiments with 12 multithreaded applications running on a stateof-the-art commercial manycore system indicate that the proposed compiler-based approach significantly reduces data movements on the on-chip network by taking advantage of NDP, and these benefits lead to an average execution time improvement of 18.4%.

Original languageEnglish (US)
Title of host publicationMICRO 2017 - 50th Annual IEEE/ACM International Symposium on Microarchitecture Proceedings
PublisherIEEE Computer Society
Number of pages15
ISBN (Electronic)9781450349529
StatePublished - Oct 14 2017
Event50th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2017 - Cambridge, United States
Duration: Oct 14 2017Oct 18 2017

Publication series

NameProceedings of the Annual International Symposium on Microarchitecture, MICRO
VolumePart F131207
ISSN (Print)1072-4451


Other50th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2017
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture


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