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Task partitioning algorithm based on parallelism maximization with multi-objective optimization
YUAN Kaijian, ZHANG Xingming, GAO Yanzhao
Journal of Computer Applications    2017, 37 (7): 1916-1920.   DOI: 10.11772/j.issn.1001-9081.2017.07.1916
Abstract573)      PDF (751KB)(395)       Save
Concerning the parallelism maximization of hardware task partitioning in reconfigurable system, a task partitioning algorithm based on parallelism maximization for multi-objective optimization was proposed. Firstly, the operating nodes to be partitioned were discovered according to the breadth first search under the constraints of hardware area resource and reasonable dependency relation. Then, considering the effect of execution delay on system completion time, the parallelism of intra-block operations was maximized. Finally, the new nodes were accepted under the principle of reducing the fragment area without increasing the number of connections between blocks. Otherwise, a block partitioning was ended. The experimental results show that the proposed algorithm achieves the maximum intra-block parallelism and reduces the number of blocks and connecting edges compared with the existing Level Based Partitioning (LBP) and Cluster Based Partitioning (CBP) algorithms.
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