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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao IEEE Transactions on...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
IEEE Transactions on Parallel and Distributed Systems
Article . 2012 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
DBLP
Article . 2012
Data sources: DBLP
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Program Regularization in Memory Consistency Verification

Authors: Yunji Chen; Lei Li; Tianshi Chen 0002; Ling Li 0001; Lei Wang; Xiaoxue Feng; Weiwu Hu;

Program Regularization in Memory Consistency Verification

Abstract

A widely adopted methodology for verifying the memory subsystem of a Chip Multiprocessor (CMP) is to verify executions of parallel test programs on the CMP against the given memory consistency model, which has been long known to be time consuming in both theory and practice. To accelerate memory consistency verification, previous approaches have to bear the cost of availability (e.g., relying on dedicated hardware supports that have not been offered by many commodity CMPs) or completeness (e.g., missing some bugs). In the meantime, the impact of parallel programs on memory consistency verification has more or less been overlooked. One piece of evidence is that few investigations have been dedicated to finding appropriate test programs enabling more efficient verification From a novel perspective of test program, we devise a practical technique called “program regularization,” which can effectively reduce the computation time of memory consistency verification. The key intuition behind program regularization is that any parallel program, if being reformed appropriately, can enable efficient memory consistency verification. More specifically, for an original program, program regularization introduces some auxiliary memory addresses, and periodically inserts load/store operations accessing these addresses to the original program. With the regularized program, memory consistency verification can be accomplished in linear time (with respect to the number of memory operations) when the number of processors is fixed. Experimental results show that program regularization can significantly accelerate memory consistency verification. Last but not least, our technique, which does not rely on concrete verification algorithm or dedicated hardware support, can be smoothly integrated into existing presilicon/postsilicon verification platforms of industrial CMPs to speed up memory consistency verification.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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