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首页> 外文会议>18th International Symposium on VLSI Design and Test >Particle Swarm Optimization guided multi-frequency power-aware System-on-Chip test scheduling using window-based peak power model
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Particle Swarm Optimization guided multi-frequency power-aware System-on-Chip test scheduling using window-based peak power model

机译：基于窗口的峰值功率模型的粒子群优化指导多频功率感知片上系统测试调度

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摘要

This paper presents a multi-frequency test scheduling strategy for System-on-chip (SoC) under power constraint. While existing approaches consider either global peak or cycle-accurate power model, the proposed work considers an intermediate approach to reduce the power overestimation of global peak power model as well as the computational complexity of cycle-accurate power model. A Particle Swarm Optimization (PSO) guided test scheduling strategy has been integrated with our new window-based peak power model to reduce Test Application Time (TAT) over global peak power model. Experimental results show that further improvement in TAT can be achieved using multi-frequency test environment over single-frequency test approach.
机译：本文提出了一种功率受限的片上系统（SoC）的多频测试调度策略。尽管现有方法考虑了全局峰值功率模型或周期精确功率模型，但本文提出的工作是考虑一种中间方法来减少全局峰值功率模型的功率高估以及周期精确功率模型的计算复杂性。粒子群优化（PSO）指导的测试计划策略已与我们新的基于窗口的峰值功率模型相集成，从而比全球峰值功率模型减少了测试应用时间（TAT）。实验结果表明，与单频测试方法相比，多频测试环境可以进一步提高TAT。

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