Effective parallelization of loops in the presence of I/O operations

Min Feng, Rajiv Gupta, Iulian Neamtiu

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

4 Scopus citations

Abstract

Software-based thread-level parallelization has been widely studied for exploiting data parallelism in purely computational loops to improve program performance on multiprocessors. However, none of the previous efforts deal with efficient parallelization of hybrid loops, i.e., loops that contain a mix of computation and I/O operations. In this paper, we propose a set of techniques for efficiently parallelizing hybrid loops. Our techniques apply DOALL parallelism to hybrid loops by breaking the cross-iteration dependences caused by I/O operations. We also support speculative execution of I/O operations to enable speculative parallelization of hybrid loops. Helper threading is used to reduce the I/O bus contention caused by the improved parallelism. We provide an easy-to-use programming model for exploiting parallelism in loops with I/O operations. Parallelizing hybrid loops using our model requires few modifications to the code. We have developed a prototype implementation of our programming model. We have evaluated our implementation on a 24-core machine using eight applications, including a widely-used genomic sequence assembler and a multi-player game server, and others from PARSEC and SPEC CPU2000 benchmark suites. The hybrid loops in these applications take 23%-99% of the total execution time on our 24-core machine. The parallelized applications achieve speedups of 3.0x-12.8x with hybrid loop parallelization over the sequential versions of the same applications. Compared to the versions of applications where only computation loops are parallelized, hybrid loop parallelization improves the application performance by 68% on average.

Original languageEnglish (US)
Title of host publicationPLDI'12 - Proceedings of the 2012 ACM SIGPLAN Conference on Programming Language Design and Implementation
Pages487-497
Number of pages11
DOIs
StatePublished - Jul 9 2012
Externally publishedYes
Event33rd ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI'12 - Beijing, China
Duration: Jun 11 2012Jun 16 2012

Publication series

NameProceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI)

Other

Other33rd ACM SIGPLAN Conference on Programming Language Design and Implementation, PLDI'12
CountryChina
CityBeijing
Period6/11/126/16/12

All Science Journal Classification (ASJC) codes

  • Software

Keywords

  • DOALL parallelization
  • Helper threading
  • I/O contention
  • Speculative parallelization

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