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DBLP
Article . 2018
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Efficient Race Detection for Reducer Hyperobjects

Authors: I-Ting Angelina Lee; Tao B. Schardl;

Efficient Race Detection for Reducer Hyperobjects

Abstract

A multithreaded Cilk program that is ostensibly deterministic may nevertheless behave nondeterministically due to programming errors in the code. For a Cilk program that uses reducers—a general reduction mechanism supported in various Cilk dialects—such programming errors are especially challenging to debug, because the errors can expose the nondeterminism in how the Cilk runtime system manages reducers. We identify two unique types of races that arise from incorrect use of reducers in a Cilk program, and we present two algorithms to catch these races. The first algorithm, called the Peer-Set algorithm, detects view-read races, which occur when the program attempts to retrieve a value out of a reducer when the read may result in a nondeterministic value, such as before all previously spawned subcomputations that might update the reducer have necessarily returned. The second algorithm, called the SP+ algorithm, detects determinacy races—instances where a write to a memory location occurs logically in parallel with another access to that location—even when the raced-on memory locations relate to reducers. Both algorithms are provably correct, asymptotically efficient, and can be implemented efficiently in practice. We have implemented both algorithms in our prototype race detector, Rader. When running Peer-Set, Rader incurs a geometric-mean multiplicative overhead of 2.56 over running the benchmark without instrumentation. When running SP+, Rader incurs a geometric-mean multiplicative overhead of 16.94.

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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!
0
Average
Average
Average
bronze