Scalable Critical-Path Based Performance Analysis

Abstract

The critical path, which describes the longest execution sequence without wait states in a parallel program, identifies the activities that determine the overall program runtime. Combining knowledge of the critical path with traditional parallel profiles, we have defined a set of compact performance indicators that help answer a variety of important performance-analysis questions, such as identifying load imbalance, quantifying the impact of imbalance on runtime, and characterizing resource consumption. By replaying event traces in parallel, we can calculate these performance indicators in a highly scalable way, making them a suitable analysis instrument for massively parallel programs with thousands of processes. Case studies with real-world parallel applications confirm that - in comparison to traditional profiles - our indicators provide enhanced insight into program behavior, especially when evaluating partitioning schemes of MPMD programs.

DOI: 10.1109/IPDPS.2012.120

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Cite this paper

@article{Bhme2012ScalableCB, title={Scalable Critical-Path Based Performance Analysis}, author={David B{\"{o}hme and Felix Wolf and Bronis R. de Supinski and Martin Schulz and Markus Geimer}, journal={2012 IEEE 26th International Parallel and Distributed Processing Symposium}, year={2012}, pages={1330-1340} }