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Automatic Benchmark Profiling through Advanced Trace Analysis

Abstract : Benchmarking has proven to be crucial for the investigation of the behavior and performances of a system. However, the choice of relevant benchmarks still remains a challenge. To help the process of comparing and choosing among benchmarks, we propose a solution for automatic benchmark profiling. It computes unified benchmark profiles reflecting benchmarks' duration, function repartition, stability, CPU efficiency, parallelization and memory usage. It identifies the needed system information for profile computation, collects it from execution traces and produces profiles through efficient and reproducible trace analysis treatments. The paper presents the design, implementation and the evaluation of the approach.
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Contributor : Alexis Martin <>
Submitted on : Thursday, March 24, 2016 - 4:04:40 PM
Last modification on : Tuesday, October 6, 2020 - 4:20:09 PM
Long-term archiving on: : Monday, November 14, 2016 - 2:50:16 AM


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  • HAL Id : hal-01292618, version 1


Alexis Martin, Vania Marangozova-Martin. Automatic Benchmark Profiling through Advanced Trace Analysis. [Research Report] RR-8889, Inria - Research Centre Grenoble – Rhône-Alpes; Université Grenoble Alpes; CNRS. 2016. ⟨hal-01292618⟩



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