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Published in: The Journal of Supercomputing 6/2020

05-06-2019

A tool to assess the communication cost of parallel kernels on heterogeneous platforms

Authors: Juan A. Rico-Gallego, Sergio Moreno-Álvarez, Juan C. Díaz-Martín, Alexey L. Lastovetsky

Published in: The Journal of Supercomputing | Issue 6/2020

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Abstract

Ensuring applications to achieve an efficient usage of resources and fast execution time in the complex current heterogeneous high-performance computing platforms is a paramount problem. Essential efforts to reach the goal are the optimal partitioning of the data space between the processes composing a typical task/data-parallel application, and their right mapping and deployment on the platform. The computational and communication performance modeling describing the platform and the application behaviors is an increasingly recognized approach. This paper discusses the utility of the \(\uptau\)–Lop analytic communication performance model in facing these issues and contributes with a practical symbolic computation tool that represents, manipulates and accurately evaluates the formal communication cost expression derived from a hybrid kernel. We identify a set of scenarios where the tool could be applied, provide with both basic and advanced use examples and evaluate the tool on real-life kernels.

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Footnotes
1
Ring algorithm executes in \(P-1\) steps. In each step process with rank p sends a message of size m to process with rank \(p+1\) and receives a message of the same size from rank \(p-1\). The Recursive Doubling algorithm executes in \(\log _2 P\) steps by doubling the message size interchanged in each step. Process p communicates with process \(p \oplus 2^s\) in the step s.
 
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Metadata
Title
A tool to assess the communication cost of parallel kernels on heterogeneous platforms
Authors
Juan A. Rico-Gallego
Sergio Moreno-Álvarez
Juan C. Díaz-Martín
Alexey L. Lastovetsky
Publication date
05-06-2019
Publisher
Springer US
Published in
The Journal of Supercomputing / Issue 6/2020
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-019-02919-1

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