2014Unpublished venueRequires access

Adaptive Simulated Annealing Algorithm for Task Assignment on Homogeneous Multi/Many-core Processors

Yan Qia

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Abstract

With rapid increasing of the number of cores in multi/many-core processors,the task assignment solution space increases sharply so that reducing the relative deviation of the approximate solution becomes more and more difficult.An adaptive simulated annealing algorithm was put forward by establishing the relationship of the algorithm parameters and the number of optimized environment tasks and cores.The increasing of core number can not only effectively reduce the relative deviation of the approximate solution,but also shows high adaptability for the environment. Experiments reveal that on the 16cores platform,the adaptive simulated annealing algorithm iterations are increased by 41%,but the relative deviation is decreased by 86% versus the recent research results.

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What this paper is about

With rapid increasing of the number of cores in multi/many-core processors,the task assignment solution space increases sharply so that reducing the relative deviation of the approximate solution becomes more and more difficult.An adaptive simulated annealing algorithm was put forward by establishing the relationship of the algorithm parameters and the number of optimized environment tasks and cores.The increasing of core number can not only effectively reduce the relative deviation of the approximate solution,but also shows high adaptability for the environment. Experiments reveal that on the 16cores platform,the adaptive simulated annealing algorithm iterations are increased by 41%,but the relative deviation is decreased by 86% versus the recent research results.

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Available abstract

With rapid increasing of the number of cores in multi/many-core processors,the task assignment solution space increases sharply so that reducing the relative deviation of the approximate solution becomes more and more difficult.An adaptive simulated annealing algorithm was put forward by establishing the relationship of the algorithm parameters and the number of optimized environment tasks and cores.The increasing of core number can not only effectively reduce the relative deviation of the approximate solution,but also shows high adaptability for the environment. Experiments reveal that on the 16cores platform,the adaptive simulated annealing algorithm iterations are increased by 41%,but the relative deviation is decreased by 86% versus the recent research results.

Key concepts: Simulated annealing, Computer science, Adaptability, Relative standard deviation, Adaptive simulated annealing, Algorithm, Homogeneous, Absolute deviation

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