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Erschienen in:
2007 | OriginalPaper | Buchkapitel
A New Memory Slowdown Model for the Characterization of Computing Systems
verfasst von : Rodrigo Fernandes de Mello, Luciano José Senger, Kuan-Ching Li, Laurence Tianruo Yang
Erschienen in: Parallel Computing Technologies
Verlag: Springer Berlin Heidelberg
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Performance measurements were extensively conducted to characterize parallel computer systems by using modelling and experiments. By analyzing them, we corroborate current models did not provide precise memory characterization. After detailed result observation, we conclude that the performance slowdown is linear when using the main memory, and exponential when using the virtual memory.
In this paper, we propose a characterization model composed of two regressions which represent the slowdown caused by memory usage. Experimental results confirm the memory slowdown model improves the quality of computing system characterization, allowing to carry out simulations and the use of such results as a way to design real systems, minimizing project design costs.