research-article

A technique for the effective and automatic reuse of classical compiler optimizations on multithreaded code

Authors:

Pramod G. Joisha,

Robert S. Schreiber,

Prithviraj Banerjee,

Dhruva R. ChakrabartiAuthors Info & Claims

POPL '11: Proceedings of the 38th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages

Pages 623 - 636

https://doi.org/10.1145/1926385.1926457

Published: 26 January 2011 Publication History

Abstract

A large body of data-flow analyses exists for analyzing and optimizing sequential code. Unfortunately, much of it cannot be directly applied on parallel code, for reasons of correctness. This paper presents a technique to automatically, aggressively, yet safely apply sequentially-sound data-flow transformations, without change, on shared-memory programs. The technique is founded on the notion of program references being "siloed" on certain control-flow paths. Intuitively, siloed references are free of interference from other threads within the confines of such paths. Data-flow transformations can, in general, be unblocked on siloed references.

The solution has been implemented in a widely used compiler. Results on benchmarks from SPLASH-2 show that performance improvements of up to 41% are possible, with an average improvement of 6% across all the tested programs over all thread counts.

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Index Terms

A technique for the effective and automatic reuse of classical compiler optimizations on multithreaded code
1. Software and its engineering
  1. Software notations and tools
    1. Compilers

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cover image ACM Conferences

POPL '11: Proceedings of the 38th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages

January 2011

652 pages

ISBN:9781450304900

DOI:10.1145/1926385

General Chair:
Thomas Ball
Microsoft Research, USA
,
Program Chair:
Mooly Sagiv
Tel Aviv University, Israel

ACM SIGPLAN Notices Volume 46, Issue 1
POPL '11
January 2011
624 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/1925844
Issue’s Table of Contents

Copyright © 2011 ACM.

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Published: 26 January 2011

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https://doi.org/10.1109/TPDS.2017.2771509
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https://dl.acm.org/doi/10.5555/3049832.3049835
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