This paper presents a new benchmark to evaluate performance and energy consumption of different Parallel Programming Interfaces (PPIs). The benchmark is composed of 11 algorithms implemented in PThreads, OpenMP, MPI-1 and MPI-2 (spawn) PPIs. Previous studies have used some of these applications to perform this type of evaluation in different architectures, since there is no benchmark that offers this variety of PPIs and communication models. In this work we measure the energy and performance of each application in a single architecture, varying the number of threads/processes. The goal is to show that this set of applications has enough features to form a parallel benchmark. The results show that there is no single best case that provides both better performance and low energy consumption in the presented scenarios. However, PThreads and OpenMP achieve the best trade-offs between performance and energy in most cases.

A New Parallel Benchmark for Performance Evaluation and Energy Consumption

Adriano Marques Garcia
First
;
2019-01-01

Abstract

This paper presents a new benchmark to evaluate performance and energy consumption of different Parallel Programming Interfaces (PPIs). The benchmark is composed of 11 algorithms implemented in PThreads, OpenMP, MPI-1 and MPI-2 (spawn) PPIs. Previous studies have used some of these applications to perform this type of evaluation in different architectures, since there is no benchmark that offers this variety of PPIs and communication models. In this work we measure the energy and performance of each application in a single architecture, varying the number of threads/processes. The goal is to show that this set of applications has enough features to form a parallel benchmark. The results show that there is no single best case that provides both better performance and low energy consumption in the presented scenarios. However, PThreads and OpenMP achieve the best trade-offs between performance and energy in most cases.
2019
Inglese
contributo
1 - Conferenza
13th International Conference on High Performance Computing in Computational Science, VECPAR 2018
Sao Pedro, Brazil
2018
Internazionale
Lecture Notes in Computer Science
Comitato scientifico
Springer Verlag
Cham
SVIZZERA
11333
188
201
14
978-3-030-15995-5
978-3-030-15996-2
Benchmark; Energy consumption; Performance
BRASILE
2 – prodotto con deroga d’ufficio (SOLO se editore non consente/non ha risposto)
4
info:eu-repo/semantics/conferenceObject
04-CONTRIBUTO IN ATTI DI CONVEGNO::04A-Conference paper in volume
Adriano Marques Garcia, Claudio Schepke, Alessandro Gonçalves Girardi & Sherlon Almeida da Silva
273
partially_open
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1949994
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