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Performance variation considered helpful

Abstract : Understanding the performance of a multi-threaded application is difficult. The threads interfere when they access the same resource, which slows their execution down. Unfortunately, current profiling tools focus on identifying the interference causes, not their effects.The developer can thus not know if optimizing the interference reported by a profiling tool can lead to better performance. In this thesis, we propose to complete the profiling toolbox with an effect-oriented profiling tool able to indicate how much interference impacts performance, regardless of the interference cause. With an evaluation of 27 applications, we show that our tool successfully identifies 12 performance bottlenecks caused by 6 different kinds of interference
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Submitted on : Thursday, May 3, 2018 - 2:53:05 PM
Last modification on : Wednesday, June 24, 2020 - 4:18:25 PM
Long-term archiving on: : Tuesday, September 25, 2018 - 9:26:19 PM


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  • HAL Id : tel-01784480, version 1


Mohamed Said Mosli Bouksiaa. Performance variation considered helpful. Distributed, Parallel, and Cluster Computing [cs.DC]. Université Paris-Saclay, 2018. English. ⟨NNT : 2018SACLL001⟩. ⟨tel-01784480⟩



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