Particle Swarm Optimization guided multi-frequency power-aware System-on-Chip test scheduling using window-based peak power model

R. Karmakar, Aditya Agarwal, S. Chattopadhyay
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引用次数: 2

Abstract

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.
基于窗口峰值功率模型的粒子群算法指导多频功耗感知的片上系统测试调度
提出了一种功耗约束下的单片系统多频测试调度策略。现有的方法考虑全局峰值功率模型或周期精确功率模型,而本文考虑一种中间方法来降低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度。将粒子群优化(PSO)指导的测试调度策略与基于窗口的峰值功率模型相结合,比全局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改善TAT。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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