TAM/wrapper Co-optimization And Test Scheduling For SOCs Based On Hybrid Genetic Algorithm
TAM/wrapper Co-optimization And Test Scheduling For SOCs Based On Hybrid Genetic Algorithm
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DOI：
10.4304/jcp.5.7.1086-1093
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发表时间：
2010-01
期刊：
影响因子：
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通讯作者：
Chuan-pei Xu;Xue-yun Lu;Cong Hu
中科院分区：
文献类型：
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作者：
Chuan-pei Xu;Xue-yun Lu;Cong Hu
提出了一种基于混合遗传算法和二维布局问题的/包装机联合优化方法。该方法将核心测试用矩形表示，并采用混合遗传算法对分配和测试调度问题进行求解，为二维布局问题提供了高度优化的解。在调度过程中，可以将分配给核的宽度调整到合适的大小，以最大限度地减少空闲时间。这种基于混合遗传算法的方法用C语言实现，并应用于ITC‘02 SOC测试基准测试。实验结果表明，与其他方法相比，该方法具有更短的测试时间[1，4，5]。
In this paper, a new method is presented for TAM/wrapper co-optimization based on hybrid genetic algorithm and two- dimensional packing problem. In this method, core test is represented by rectangles, and a hybrid genetic algorithm that provides highly optimal solution for two-dimensional packing problem is introduced for TAM allocation and test scheduling. During the scheduling, the TAM width assigned to cores could be adjusted to an appropriate size to minimize the idle time. This HGA based method was implemented in C and applied to ITC’02 SOC Test Benchmark. Experimental results show that lower testing time was obtained by this new method compared to other methods [1,4,5].