On-the-fly detection of data races for programs with nested fork-join parallelism

Detecting data races in shared-memory parallel programs is an important debugging problem. This paper presents a new protocol for run-time detection of data races in executions of shared-memory programs with nested fork-join parallelism and no other inter-thread synchronization. This protocol has si...

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Bibliographic Details
Published in:Proceedings of the 1991 ACM/IEEE Conference on Supercomputing pp. 24 - 33
Main Author: Mellor-Crummey, John
Format: Conference Proceeding
Language:English
Published: New York, NY, USA ACM 01.08.1991
IEEE
Series:ACM Conferences
Subjects:
Computer systems organization > Architectures > Distributed architectures > Grid computing
Computer systems organization > Architectures > Parallel architectures
Computer systems organization > Architectures > Parallel architectures > Multicore architectures
Computer systems organization > Architectures > Serial architectures > Superscalar architectures
Computing methodologies > Modeling and simulation > Simulation types and techniques > Massively parallel and high-performance simulations
Computing methodologies > Parallel computing methodologies > Parallel programming languages
Debugging
Monitoring
Protocols
Runtime
Software and its engineering > Software creation and management > Software verification and validation > Software defect analysis > Software testing and debugging
Software and its engineering > Software notations and tools > General programming languages > Language features > Concurrent programming structures
Software and its engineering > Software notations and tools > General programming languages > Language types > Parallel programming languages
Software and its engineering > Software organization and properties > Software system structures > Distributed systems organizing principles > Grid computing
ISBN:9780897914598, 0897914597
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Summary:Detecting data races in shared-memory parallel programs is an important debugging problem. This paper presents a new protocol for run-time detection of data races in executions of shared-memory programs with nested fork-join parallelism and no other inter-thread synchronization. This protocol has significantly smaller worst-case run-time overhead than previous techniques. The worst-case space required by our protocol when monitoring an execution of a program P is O(VN), where V is the number of shared variables in P, and N is the maximum dynamic nesting of parallel constructs in P's execution. The worst-case time required to perform any monitoring operation is O(N). We formally prove that our new protocol always reports a nonempty subset of the data races in a monitored program execution and describe how this property leads to an effective debugging strategy.
Bibliography:SourceType-Conference Papers & Proceedings-1
ObjectType-Conference Paper-1
content type line 25
ISBN:9780897914598
0897914597
DOI:10.1145/125826.125861