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Entropy Measurement of Concurrent Disorder

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Quantitative Evaluation of Systems (QEST 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12289))

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Abstract

There is an imminent demand to understand the relationship between correctness and performance to deliver highly scalable multiprocessor programs. The motivation for this relationship is that relaxed correctness conditions provide performance benefits by reducing contention on data structure hot spots. Previous approaches propose metrics for characterizing relaxed correctness conditions that measure the number of method calls or state transitions to be shifted to arrive at a legal sequential history. The reason the existing metrics cannot measure the performance effects of a correctness condition is that they ignore delays in method calls since delayed responses from method calls yield correct behavior in even the strictest correctness conditions. We observe that method call delays can be captured by measuring the disorder in method call ordering using a metric from information theory known as entropy. We propose entropy as the first metric for multiprocessor programs that evaluates the trade-offs between correctness and performance. We measure entropy for a variety of concurrent stacks, queues, and sets from the Synchrobench micro-benchmark suite and correlate entropy, correctness, and performance. Our main insight is that lower entropy corresponds to better performance for strict correctness conditions and higher entropy corresponds to better performance for relaxed correctness conditions.

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Notes

  1. 1.

    CAS accepts a memory location, expected value, and new value as parameters. If the dereferenced value of the memory location is equivalent to the expected value, then the memory location value is updated to the new value and true is returned. Otherwise, no change is made and false is returned.

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Authors and Affiliations

  1. University of Central Florida, Orlando, FL, USA

    Victor Cook, Christina Peterson, Zachary Painter & Damian Dechev

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  1. Victor Cook
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  2. Christina Peterson
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  3. Zachary Painter
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  4. Damian Dechev
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Corresponding author

Correspondence to Christina Peterson .

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Editors and Affiliations

  1. Politecnico di Milano, Milan, Italy

    Marco Gribaudo

  2. Chinese Academy of Sciences, Beijing, China

    David N. Jansen

  3. University of Münster, Münster, Germany

    Anne Remke

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Cook, V., Peterson, C., Painter, Z., Dechev, D. (2020). Entropy Measurement of Concurrent Disorder. In: Gribaudo, M., Jansen, D.N., Remke, A. (eds) Quantitative Evaluation of Systems. QEST 2020. Lecture Notes in Computer Science(), vol 12289. Springer, Cham. https://doi.org/10.1007/978-3-030-59854-9_18

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  • DOI: https://doi.org/10.1007/978-3-030-59854-9_18

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