Parallelizing Sequential Programs with Statistical Accuracy Tests
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Author(s)
Misailovic, Sasa
Kim, Deokhwan
Rinard, Martin C.
Date Issued
May 2013
Journal
ACM Transactions on Embedded Computing Systems
Publisher
Association for Computing Machinery (ACM)
Citation
Sasa Misailovic, Deokhwan Kim, and Martin Rinard. 2013. Parallelizing Sequential Programs with Statistical Accuracy Tests. ACM Trans. Embed. Comput. Syst. 12, 2s, Article 88 (May 2013), 26 pages.
Version
Author's final manuscript
Abstract
We present QuickStep, a novel system for parallelizing sequential programs. Unlike standard parallelizing compilers (which are designed to preserve the semantics of the original sequential computation), QuickStep is instead designed to generate (potentially nondeterministic) parallel programs that produce acceptably accurate results acceptably often. The freedom to generate parallel programs whose output may differ (within statistical accuracy bounds) from the output of the sequential program enables a dramatic simplification of the compiler, a dramatic increase in the range of applications that it can parallelize, and a significant expansion in the range of parallel programs that it can legally generate.
Results from our benchmark set of applications show that QuickStep can automatically generate acceptably accurate and efficient parallel programs---the automatically generated parallel versions of five of our six benchmark applications run between 5.0 and 7.8 times faster on eight cores than the original sequential versions. These applications and parallelizations contain features (such as the use of modern object-oriented programming constructs or desirable parallelizations with infrequent but acceptable data races) that place them inherently beyond the reach of standard approaches.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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DOI of Published Version
https://doi.org/10.1145/2465787.2465790
