WARDen: Specializing Cache Coherence for High-Level Parallel Languages

Michael Wilkins, Sam Westrick, Vijay Kandiah, Alex Bernat, Brian Suchy*, Enrico Armenio Deiana, Simone Campanoni, Umut A. Acar, Peter Dinda, Nikos Hardavellas

*Corresponding author for this work

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

2 Scopus citations

Abstract

High-level parallel languages (HLPLs) make it easier to write correct parallel programs. Disciplined memory usage in these languages enables new optimizations for hardware bottlenecks, such as cache coherence. In this work, we show how to reduce the costs of cache coherence by integrating the hardware coherence protocol directly with the programming language; no programmer effort or static analysis is required. We identify a new low-level memory property, WARD (WAW Apathy and RAW Dependence-freedom), by construction in HLPL programs. We design a new coherence protocol, WARDen, to selectively disable coherence using WARD. We evaluate WARDen with a widely-used HLPL benchmark suite on both current and future x64 machine structures. WARDen both accelerates the benchmarks (by an average of 1.46x) and reduces energy (by 23%) by eliminating unnecessary data movement and coherency messages.

Original languageEnglish (US)
Title of host publicationCGO 2023 - Proceedings of the 21st ACM/IEEE International Symposium on Code Generation and Optimization
EditorsChristophe Dubach, Derek Bruening, Ben Hardekopf
PublisherAssociation for Computing Machinery, Inc
Pages122-135
Number of pages14
ISBN (Electronic)9798400701016
DOIs
StatePublished - Feb 17 2023
Event21st ACM/IEEE International Symposium on Code Generation and Optimization, CGO 2023 - Montreal, Canada
Duration: Feb 25 2023Mar 1 2023

Publication series

NameCGO 2023 - Proceedings of the 21st ACM/IEEE International Symposium on Code Generation and Optimization

Conference

Conference21st ACM/IEEE International Symposium on Code Generation and Optimization, CGO 2023
Country/TerritoryCanada
CityMontreal
Period2/25/233/1/23

Keywords

  • cache coherence
  • disentanglement

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Hardware and Architecture
  • Software
  • Applied Mathematics
  • Control and Optimization

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