Performance Estimation of Task Graphs Based on Path Profiling |
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Authors: | Email author" target="_blank">Marco?LattuadaEmail author Christian?Pilato Fabrizio?Ferrandi |
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Affiliation: | 1.Dipartimento di Elettronica, Informazione e Bioingegneria,Politecnico di Milano,Milano,Italy;2.Department of Computer Science,Columbia University,New York,USA |
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Abstract: | Correctly estimating the speed-up of a parallel embedded application is crucial to efficiently compare different parallelization techniques, task graph transformations or mapping and scheduling solutions. Unfortunately, especially in case of control-dominated applications, task correlations may heavily affect the execution time of the solutions and usually this is not properly taken into account during performance analysis. We propose a methodology that combines a single profiling of the initial sequential specification with different decisions in terms of partitioning, mapping, and scheduling in order to better estimate the actual speed-up of these solutions. We validated our approach on a multi-processor simulation platform: experimental results show that our methodology, effectively identifying the correlations among tasks, significantly outperforms existing approaches for speed-up estimation. Indeed, we obtained an absolute error less than 5 % in average, even when compiling the code with different optimization levels. |
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