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Adaptive pre-task assignment scheduling strategy for heterogenous distributed raytracing system
DOI:10.1016/j.compeleceng.2006.05.001.png)
Abstract
En 中文
One of the main obstacles in obtaining high performance from heterogeneous distributed computing (HDC) system is the inevitable communication overhead. This occurs when tasks executing on different computing nodes exchange data or the assigned sub-task size is very small. In this paper, we present adaptive pre-task assignment (APA) strategy for heterogeneous distributed raytracing system. In this strategy, the master assigns pre-task to the each node. The size of sub-task for each node is proportional to the node's performance. One of the main features of this strategy is that it reduces the inter-processes communication, the cost overhead of the node's idle time and load imbalance, which normally occurs in traditional runtime task scheduling (RTS) strategies. Performances of the RTS and APA strategies are evaluated on manager/master and workers model of HDC system. The experimental results of our proposed (APA) strategy have shown a significant improvement in the performance over RTS strategy. (c) 2006 Elsevier Ltd. All rights reserved.
Keywords:
task partitioning and scheduling
load balancing
heterogeneous distributed computing
runtime task scheduling strategy
adaptive pre-task assignment strategy
distributed image/raytracing computing
performance evaluation
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