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Self-Scheduling is a dynamic and adaptive loop scheduling approach to reduce the total execution time for a task running in the cluster or grid environment. This paper focuses on how to use and optimize Self-scheduling technologies to allocate tasks reasonable and achieve better parallel performance. It introduces the prediction algorithms and proposes a novel Chunk-based Task Runtime Prediction (CTRP) algorithm according to the characters of desk grid and multi-core environment. The authors' experimental results show that their approach can predict the execution time more accurate and achieve better load balancing than that of others when most slave nodes' load is changing frequently and rulelessly in the multi-core desk grid.
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