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A methodology approach to compare performance of parallel programming models for shared-memory architectures

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10.1007/978-3-030-39081-5_28
 
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hdl:2117/336816

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Utrera Iglesias, Gladys MiriamMés informacióMés informació
Gil, MarisaMés informacióMés informacióMés informació
Martorell Bofill, XavierMés informacióMés informacióMés informació
Document typePart of book or chapter of book
Defense date2020
PublisherSpringer
Rights accessOpen Access
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder
ProjectCOMPUTACION DE ALTAS PRESTACIONES VII (MINECO-TIN2015-65316-P)
Abstract
The majority of current HPC applications are composed of complex and irregular data structures that involve techniques such as linear algebra, graph algorithms, and resource management, for which new platforms with varying computation-unit capacity and features are required. Platforms using several cores with different performance characteristics make a challenge the selection of the best programming model, based on the corresponding executing algorithm. To make this study, there are approaches in the literature, that go from comparing in isolation the corresponding programming models’ primitives to the evaluation of a complete set of benchmarks. Our study shows that none of them may provide enough information for a HPC application to make a programming model selection. In addition, modern platforms are modifying the memory hierarchy, evolving to larger shared and private caches or NUMA regions making the memory wall an issue to consider depending on the memory access patterns of applications. In this work, we propose a methodology based on Parallel Programming Patterns to consider intra and inter socket communication. In this sense, we analyze MPI, OpenMP and the hybrid solution MPI/OpenMP in shared-memory environments. We demonstrate that the proposed comparison methodology may give more accurate predictions in performance for given HPC applications and consequently a useful tool to select the appropriate parallel programming model.
CitationUtrera, G.; Gil, M.; Martorell, X. A methodology approach to compare performance of parallel programming models for shared-memory architectures. A: "Numerical Computations: Theory and Algorithms: Third International Conference, NUMTA 2019, Crotone, Italy, June 15–21, 2019: revised selected papers, part I". Berlín: Springer, 2020, p. 318-325. 
URIhttp://hdl.handle.net/2117/336816
DOI10.1007/978-3-030-39081-5_28
ISBN978-3-030-39080-8
Publisher versionhttps://link.springer.com/book/10.1007/978-3-030-39081-5
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  • CAP - Grup de Computació d'Altes Prestacions - Capítols de llibre [29]
  • Departament d'Arquitectura de Computadors - Capítols de llibre [73]
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