Measuring High Performance Computing Productivity
نویسندگان
چکیده
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.
منابع مشابه
Measuring Productivity on High Performance Computers
In the high performance computing domain, the speed of execution of a program has typically been the primary performance metric. But productivity is also of concern to high performance computing developers. In this paper we will discuss the problems of defining and measuring productivity for these machines and we develop a model of productivity that includes both a performance component and a c...
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We propose a framework for measuring the productivity of High Performance Computing (HPC) platforms and outline a research program that will lead to the definition of valid productivity metrics for HPC.
متن کاملMeasuring HPC Productivity
One key to improving high-performance computing (HPC) productivity is finding 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. ...
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One key to improving high-performance computing (HPC) productivity is finding 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. ...
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ورودعنوان ژورنال:
- IJHPCA
دوره 18 شماره
صفحات -
تاریخ انتشار 2004