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Measuring high performance computing productivity

delete2004-11-01
delete24
PRE
AI
S
Stuart Faulk *
J
John L. Gustafson
P
Philip M. Johnson
A
Adam Porter
W
Walter F. Tichy
L
Lawrence G. Votta
E
Edu, FU
DOI：10.1177/1094342004048539delete
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Abstract

Abstract

En 中文
One key to improving high performance computing (HPC) productivity is to find better ways to measure it. We define productivity in terms of mission goals, i.e. greater productivity means that more science is accomplished with less cost and effort. Traditional software productivity metrics and computing benchmarks have proven inadequate for assessing or predicting such end-to-end productivity. In this paper we introduce a new approach to measuring productivity in HPC applications that addresses both development time and execution time. Our goal is to develop a public repository of effective productivity benchmarks that anyone in the HPC community can apply to assess or predict productivity.
Keywords:
HPCS
productivity
productivity metric
productivity benchmark
performance benchmark
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Journal

International Journal of High Performance Computing Applications cover
International Journal of High Performance Computing Applications
IF:
2.5
Papers:
1.1K
Citations:
1.3K

Organization

No organization information available