Measuring Productivity on High Performance Computers

Authors:
Marvin Zelkowitz;Victor Basili;Sima Asgari;Lorin Hochstein;Jeff Hollingsworth;Taiga Nakamura
Affiliations:
University of Maryland at College Park and Fraunhofer Center Maryland;University of Maryland at College Park and Fraunhofer Center Maryland;University of Maryland at College Park;University of Maryland at College Park;University of Maryland at College Park;University of Maryland at College Park
Venue:
METRICS '05 Proceedings of the 11th IEEE International Software Metrics Symposium
Year:
2005

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Combining self-reported and automatic data to improve programming effort measurement

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An effective speedup metric for measuring productivity in large-scale parallel computer systems

The Journal of Supercomputing

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Abstract

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 component that measures the development time of the program. We ran several experiments using students in high performance courses at several universities, and we report on those results with respect to our model of productivity.