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Process Affinity, Metrics and Impact on Performance: an Empirical Study

Cyril Bordage 1 Emmanuel Jeannot 1
1 TADAAM - Topology-Aware System-Scale Data Management for High-Performance Computing
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest
Abstract : Process placement, also called topology mapping, is a well-known strategy to improve parallel program execution by reducing the communication cost between processes. It requires two inputs: the topology of the target machine and a measure of the affinity between processes. In the literature, the dominant affinity measure is the communication matrix that describes the amount of communication between processes. The goal of this paper is to study the accuracy of the communication matrix as a measure of affinity. We have done an extensive set of tests with two fat-tree machines and a 3d-torus machine to evaluate several hypotheses that are often made in the literature and to discuss their validity. First, we check the correlation between algorithmic metrics and the performance of the application. Then, we check whether a good generic process placement algorithm never degrades performance. And finally, we see whether the structure of the communication matrix can be used to predict gain.
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Submitted on : Tuesday, December 19, 2017 - 11:51:02 AM
Last modification on : Thursday, May 16, 2019 - 6:46:02 PM


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  • HAL Id : hal-01667273, version 1



Cyril Bordage, Emmanuel Jeannot. Process Affinity, Metrics and Impact on Performance: an Empirical Study. [Research Report] RR-9132, Inria Bordeaux Sud-Ouest. 2017. ⟨hal-01667273⟩



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