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Special Issue on Clusters, Clouds, and Data for Scientific Computing; Guest Editors: J. Dongarra & B. TourancheauNo Access

ASSESSING THE PERFORMANCE OF ENERGY-AWARE MAPPINGS

    https://doi.org/10.1142/S0129626413400033Cited by:3 (Source: Crossref)

    We aim at mapping streaming applications that can be modeled by a series-parallel graph onto a 2-dimensional tiled chip multiprocessor (CMP) architecture. The objective of the mapping is to minimize the energy consumption, using dynamic voltage and frequency scaling (DVFS) techniques, while maintaining a given level of performance, reflected by the rate of processing the data streams. This mapping problem turns out to be NP-hard, and several heuristics are proposed. We assess their performance through comprehensive simulations using the StreamIt workflow suite and randomly generated series-parallel graphs, and various CMP grid sizes.