Analyzing Dynamic Task-Based Applications on Hybrid Platforms: An Agile Scripting ApproachReport as inadecuate




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1 UGA - Université Grenoble Alpes 2 UFRGS - Universidade Federal do Rio Grande do Sul Porto Alegre 3 STORM - STatic Optimizations, Runtime Methods LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest 4 HiePACS - High-End Parallel Algorithms for Challenging Numerical Simulations LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest 5 Inria Bordeaux - Sud-Ouest 6 POLARIS - Performance analysis and optimization of LARge Infrastructures and Systems Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d-Informatique de Grenoble

Abstract : In this paper, we present visual analysis techniques to evaluate the performance of HPC task-based applications on hybrid architectures. Our approach is based on composing modern data analysis tools pjdump, R, ggplot2, plotly, enabling an agile and flexible scripting framework with minor development cost. We validate our proposal by analyzing traces from the full-fledged implementation of the Cholesky decomposition available in the MORSE library running on a hybrid CPU-GPU platform. The analysis compares two different workloads and three different task schedulers from the StarPU runtime system. Our analysis based on composite views allows to identify allocation mistakes, priority problems in scheduling decisions, GPU tasks anomalies causing bad performance, and critical path issues.





Author: Vinicius Garcia Pinto - Luka Stanisic - Arnaud Legrand - Lucas Mello Schnorr - Samuel Thibault - Vincent Danjean -

Source: https://hal.archives-ouvertes.fr/



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