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
13th International Conference on High Performance Computing in Computational Science, VECPAR 2018
Sao Pedro, Brazil
2018
Lecture Notes in Computer Science
Springer Verlag
11333
188
201
978-3-030-15995-5
978-3-030-15996-2
Benchmark; Energy consumption; Performance
Adriano Marques Garcia, Claudio Schepke, Alessandro Gonçalves Girardi & Sherlon Almeida da Silva
File in questo prodotto:
File Dimensione Formato  
VECPAR_2018_paper.pdf

Accesso riservato

Tipo di file: PDF EDITORIALE
Dimensione 375.83 kB
Formato Adobe PDF
375.83 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
VECPAR_2018_paper_preprint.pdf

Accesso aperto

Tipo di file: PREPRINT (PRIMA BOZZA)
Dimensione 402.3 kB
Formato Adobe PDF
402.3 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1949994
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact