Knowledge-Based Adaptive Self-Scheduling - Network and Parallel Computing Access content directly
Conference Papers Year : 2012

Knowledge-Based Adaptive Self-Scheduling

Yizhuo Wang
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  • PersonId : 994391
Weixing Ji
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  • PersonId : 1006897
Feng Shi
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  • PersonId : 1011279
Qi Zuo
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  • PersonId : 1011280
Ning Deng
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  • PersonId : 1011281

Abstract

Loop scheduling scheme plays a critical role in the efficient execution of programs, especially loop dominated applications. This paper presents KASS, a knowledge-based adaptive loop scheduling scheme. KASS consists of two phases: static partitioning and dynamic scheduling. To balance the workload, the knowledge of loop features and the capabilities of processors are both taken into account using a heuristic approach in static partitioning phase. In dynamic scheduling phase, an adaptive self-scheduling algorithm is applied, in which two tuning parameters are set to control chunk sizes, aiming at load balancing and minimizing synchronization overhead. In addition, we extend KASS to apply on loop nests and adjust the chunk sizes at runtime. The experimental results show that KASS performs 4.8% to 16.9% better than the existing self- scheduling schemes, and up to 21% better than the affinity scheduling scheme.
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hal-01551352 , version 1 (30-06-2017)

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Yizhuo Wang, Weixing Ji, Feng Shi, Qi Zuo, Ning Deng. Knowledge-Based Adaptive Self-Scheduling. 9th International Conference on Network and Parallel Computing (NPC), Sep 2012, Gwangju, South Korea. pp.22-32, ⟨10.1007/978-3-642-35606-3_3⟩. ⟨hal-01551352⟩
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