An effective speedup metric for measuring productivity in large-scale parallel computer systems |
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Authors: | Xuejun Yang Jing Du Zhiyuan Wang |
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Affiliation: | (1) Department of Information Technologies and System, University of Castilla-La Mancha, Toledo, 45071, Spain;(2) Computing Systems Department, University of Castilla-La Mancha, Albacete, Spain |
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Abstract: | With the parallel computer systems scaling-up, the measure index for performance of the systems demands a shift from traditional
“high performance” to “high productivity.” This brings a new challenge to defining a synthetic, yet meaningful, measure index
of multiple productivity variables; namely computing performance, reliability, energy consumption, parallel software development,
etc. Traditional measures for large-scale parallel computer systems merely focus on computing performance, and are incapable
of measuring the multiple productivity variables simultaneously in an effective manner. A recently proposed market-related
money model, which pursues high utility/cost ratio, relies on money as a measure to consider the multiple productivity variables.
Differing from the previous models, this paper proposes a novel system productivity speedup metric for large-scale parallel
computer systems. The metric uses speedup instead of money to comprehensively unify the measures of multiple productivity
variables. Finally, we propose a trade-off productivity measurement to weigh different productivity variables, to address
different design targets. The measurement can facilitate the system evaluation, expose future technique tendencies, and guide
future system design. |
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