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

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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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Notes

  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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Acknowledgements

This work was supported by the European Regional Development Fund ’A way to achieve Europe’ (ERDF) and the Extremadura Local Government (Ref. IB16118). This work also was partially supported by Advanced Computing and Technologies Foundation of Extremadura (CenitS/COMPUTAEX).

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Authors and Affiliations

  1. Department of Computer Systems Engineering and Telematics, School of Technology, University of Extremadura, Avd. Universidad s/n, 10003, Cáceres, Spain

    Juan A. Rico-Gallego & Sergio Moreno-Álvarez

  2. Department of Computer and Communication Technology, University of Extremadura, Cáceres, Spain

    Juan C. Díaz-Martín

  3. School of Computer Science, University College Dublin, Dublin, Ireland

    Alexey L. Lastovetsky

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  1. Juan A. Rico-Gallego
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  2. Sergio Moreno-Álvarez
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  3. Juan C. Díaz-Martín
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  4. Alexey L. Lastovetsky
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Correspondence to Juan A. Rico-Gallego.

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Rico-Gallego, J.A., Moreno-Álvarez, S., Díaz-Martín, J.C. et al. A tool to assess the communication cost of parallel kernels on heterogeneous platforms. J Supercomput 76, 4629–4644 (2020). https://doi.org/10.1007/s11227-019-02919-1

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  • DOI: https://doi.org/10.1007/s11227-019-02919-1

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