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Modified Adaptive Differential Evolution Algorithm for Test Scheduling of Multi-Core SOC Based on DVS and MVI

机译:基于DVS和MVI的改进型自适应差分进化算法在多核SOC测试调度中的应用

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As a popular kind of system chip, multi-core SOC based on DVS and MVI has the advantages of low power consumption and high performance. However, the test technology is still in the exploration stage, being the first problem restricting the development of multi-core SOC. In this paper, a new modified differential evolution algorithm (JADE-MaS) is applied to system-level test optimization. JADE-MaS proposes a multiangle searching strategy and obtains good effect on enhancing population diversity. The mathematical model of TAM resource division and test scheduling include four decision variables: the test bus width, the location of IP cores, the start and end times of the test. We encode the first two variables as population individuals and use JADE-MaS to seek the optimal individual, then use a priority scheduling mechanism based on heuristic algorithm to distribute the test tasks to evaluate the individual fitness. The remaining variables can also be solved in this process. After being decoded, the individual with the shortest test time is the solution of system-level test scheduling problem. Series of experiments on ITC'02 SOC benchmarks show that JADE-MaS has searched the better scheme comparing with the GA and the PSO algorithm and effectively shortens the system-level test time.
机译:基于DVS和MVI的多核SOC作为一种流行的系统芯片,具有功耗低,性能高的优点。但是,测试技术仍处于探索阶段,成为制约多核SOC发展的第一个问题。本文将一种新的改进的差分进化算法(JADE-MaS)应用于系统级测试优化。 JADE-MaS提出了一种多角度搜索策略,并在增强人口多样性方面取得了良好的效果。 TAM资源分配和测试计划的数学模型包括四个决策变量:测试总线宽度,IP内核的位置,测试的开始和结束时间。我们将前两个变量编码为人口个体,并使用JADE-MaS寻求最优个体,然后使用基于启发式算法的优先级调度机制来分配测试任务以评估个体适应性。其余变量也可以在此过程中求解。解码后,测试时间最短的个人是系统级测试计划问题的解决方案。在ITC'02 SOC基准测试中进行的一系列实验表明,JADE-MaS寻求了与GA和PSO算法相比更好的方案,并有效地缩短了系统级测试时间。

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