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Using Polyhedral Techniques to Tighten WCET Estimates of Optimized Code: A Case Study with Array Contraction
Abstract : The ARGO H2020 European project aims at developing a Worst-Case Execution Time (WCET)-aware parallelizing compilation toolchain. This toolchain operates on Scilab and XCoS inputs, and targets ScratchPad memory (SPM)-based multi-cores. Data-layout and loop transformations play a key role in this flow as they improve SPM efficiency and reduce the number of accesses to shared main memory. In this paper, we study how these transformations impact WCET estimates of sequential codes. We demonstrate that they can bring significant improvements of WCET estimates (up to 2.7×) provided that the WCET analysis process is guided with automatically generated flow annotations obtained using polyhedral counting techniques.
Cited literature [14 references]
https://hal.inria.fr/hal-01815499
Contributor : Isabelle Puaut <>
Submitted on : Thursday, June 14, 2018 - 11:12:40 AM
Last modification on : Wednesday, June 24, 2020 - 4:19:46 PM
Document(s) archivé(s) le : Monday, September 17, 2018 - 10:33:04 AM
Contributor : Isabelle Puaut <>
Submitted on : Thursday, June 14, 2018 - 11:12:40 AM
Last modification on : Wednesday, June 24, 2020 - 4:19:46 PM
Document(s) archivé(s) le : Monday, September 17, 2018 - 10:33:04 AM
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