The SCore cluster enabled OpenMP environment: Performance prospects for computational science

H'sien J. Wong; Alistair P. Rendell

doi:10.1007/11428831_133

The SCore cluster enabled OpenMP environment: Performance prospects for computational science

H'sien J. Wong, Alistair P. Rendell

Research output: Contribution to journal › Conference article › peer-review

2 Citations (Scopus)

Abstract

The OpenMP shared memory programming paradigm has been widely embraced by the computational science community, as has distributed memory clusters. What are the prospects for running OpenMP applications on clusters? This paper gives an overview of the SCore cluster enabled OpenMP environment, provides performance data for some of the fundamental underlying operations, and reports overall performance for a model computational science application (the finite difference solution of the 2D Laplace equation).

Original language	English
Pages (from-to)	1067-1075
Number of pages	9
Journal	Lecture Notes in Computer Science
Volume	3514
Issue number	I
DOIs	https://doi.org/10.1007/11428831_133
Publication status	Published - 30 Sept 2005
Externally published	Yes
Event	5th International Conference on Computational Science - ICCS 2005 - Atlanta, GA, United States Duration: 22 May 2005 → 25 May 2005

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abstract = "The OpenMP shared memory programming paradigm has been widely embraced by the computational science community, as has distributed memory clusters. What are the prospects for running OpenMP applications on clusters? This paper gives an overview of the SCore cluster enabled OpenMP environment, provides performance data for some of the fundamental underlying operations, and reports overall performance for a model computational science application (the finite difference solution of the 2D Laplace equation).",

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The SCore cluster enabled OpenMP environment: Performance prospects for computational science

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