Compiler support for near data computing

Mahmut Taylan Kandemir, Jihyun Ryoo, Xulong Tang, Mustafa Karakoy

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

Abstract

Recent works from both hardware and software domains offer various optimizations that try to take advantage of near data computing (NDC) opportunities. While the results from these works indicate performance improvements of various magnitudes, the existing literature lacks a detailed quantification of the potential of NDC and analysis of compiler optimizations on tapping into that potential. This paper first presents an analysis of the NDC potential when executing multithreaded applications on manycore platforms. It then presents two compiler schemes designed to take advantage of NDC. The first of these schemes try to increase the amount of computation that can be performed in a hardware component, whereas the second compiler strategy strikes a balance between optimizing NDC and exploiting data reuse, by being more selective on when to perform NDC (even if the opportunity presents itself) and how. The collected experimental results on a 5×5 manycore system reveal that our first and second compiler schemes improve the overall performance of our multithreaded applications by, respectively, 22.5% and 25.2%, on average. Furthermore, these two compiler schemes are only 6.8% and 4.1% worse than an oracle scheme that makes the best near data computing decisions for each and every computation.

Original languageEnglish (US)
Title of host publicationPPoPP 2021 - Proceedings of the 2021 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
PublisherAssociation for Computing Machinery
Pages90-104
Number of pages15
ISBN (Electronic)9781450382946
DOIs
StatePublished - Feb 17 2021
Event26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2021 - Virtual, Online, Korea, Republic of
Duration: Feb 27 2021Mar 3 2021

Publication series

NameProceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPOPP

Conference

Conference26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2021
CountryKorea, Republic of
CityVirtual, Online
Period2/27/213/3/21

All Science Journal Classification (ASJC) codes

  • Software

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