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The influence of random delays on parallel execution times
Stochastic models are widely used for the performance evaluation of parallel programs and systems. The stochastic assumptions in such models exe intended to represent non-deterministic processing requirements as well as random delays due to inter-process communication end resource contention. In thi...
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Main Authors: | , |
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Format: | Conference Proceeding |
Language: | English |
Subjects: |
Computer systems organization
> Architectures
> Parallel architectures
> Multiple instruction, multiple data
Mathematics of computing
> Probability and statistics
> Probabilistic reasoning algorithms
> Markov-chain Monte Carlo methods
Mathematics of computing
> Probability and statistics
> Probabilistic reasoning algorithms
> Sequential Monte Carlo methods
Social and professional topics
> Professional topics
> Management of computing and information systems
> Software management
> Software selection and adaptation
Software and its engineering
> Software notations and tools
> General programming languages
> Language types
> Parallel programming languages
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Online Access: | Get full text |
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Summary: | Stochastic models are widely used for the performance evaluation of parallel programs and systems. The stochastic assumptions in such models exe intended to represent non-deterministic processing requirements as well as random delays due to inter-process communication end resource contention. In this paper, we provide compelling analytical and experimental evidence that in current and foreseeable shared-memory programs, communication delays introduce negligible variance into the execution time between synchronization points. Furthermore, we show using direct measurements of variance that other sources of randomness, particularly non-deterministic computational requirements, also do not introduce significant variance in many programs. We then use two examples to demonstrate the implications of these results for parallel program performance prediction models, as well as for general stochastic models of parallel systems. |
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ISSN: | 0163-5999 |
DOI: | 10.1145/166955.166982 |