基于改进差分进化算法的SOC测试调度优化

Deng Li-bao, Wei Debao, Qiao Liyan, Bian Xiaolong, Zhang Baoquan
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引用次数: 0

摘要

基于可复用IP核的片上系统(SOC)在集成电路设计和制造中得到了广泛的应用。然而,SOC的高效测试仍然是瓶颈问题。测试调度可以增强并行测试,最大限度地减少SOC系统级的测试应用时间。提出了一种改进的差分进化(MDE)方法来解决片上系统测试调度和测试访问机制(TAM)划分问题。为了更好地处理测试调度,本文引入了一种基于概率估计算子的混合突变机制,其中第一变异系数保持不变,而第二变异系数随迭代次数而变化。采用不同的进化策略,尽可能在不损失种群多样性的情况下有效地加速收敛。将不同的变异算子和进化策略相结合以获得最优结果。与改进的量子启发进化(IQI)、遗传算法(GA)、整数线性规划公式(ILP)和启发式方法相比,ITC'02 SOC基准的实验结果令人鼓舞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of core-based SOC test scheduling based on modified differential evolution algorithm
System on a chip (SOC) based on reusable IP core has been widely used in integrated circuit (IC) design and manufacturing. However SOC efficient test is still the bottle-neck issue. Test scheduling can enhance parallel test to minimize test application time at SOC system level. We present a modified differential evolution (MDE) approach to solve the problems of test scheduling and test access mechanism (TAM) partition for system on chips. A new hybrid mutation mechanism based on the probability estimation operator is introduced in the paper for better handling test scheduling, where the first variation coefficient stays the same but the second variation coefficient changes with iterative times. The different evolutionary strategies are adopted to accelerate effectively convergence without loss in population diversity as far as possible. Different mutation operators and evolutionary strategies are combined to get optimal results. The experimental results on ITC'02 SOC benchmarks are encouraging compared with the improved quantum-inspired evolutionary (IQI), genetic algorithm (GA), the integer linear programming formulation (ILP) and heuristic approaches.
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