Efficient electro-thermal co-analysis on CPU+GPU heterogeneous architecture

Huang Kun, Yang Xu, Guoxing Zhao, Zuying Luo
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引用次数: 1

Abstract

Since supply voltage and temperature (V&T) directly influence IC performance and reliability, electro-thermal (ET) analysis including power/ground (P/G) analysis and thermal analysis is very important in IC design. On the observation that temperature's influence on leakage current (ET coupling effect) and supply voltage's influence on power consumption, this work proposes a novel iteration-based ET co-analysis method that simultaneously solves V&T and then with them to refresh power consumption for the next round of V&T solving. Different from present methods that regard the P/G analysis and thermal analysis as independent processes without interaction, the ET co-analysis method takes their interaction into the consideration, which leads to more practical results. Since both P/G analysis and thermal analysis are very time-consuming, this work further employs multi-thread and GPU parallel computing techniques to speed up the ET co-analysis based on a parallel computing system of CPU+GPU heterogeneous architecture (PCS_CGHA). Experimental results show that compared with our method, present ET analysis methods will give too pessimistic or optimistic results W/O considering ET coupling effect. And our efficient method on PCS_CGHA provides 44 times speedup over the naive analysis method with no acceleration.
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CPU+GPU异构架构的高效电热协同分析
由于电源电压和温度(V&T)直接影响集成电路的性能和可靠性,因此包括电源/地(P/G)分析和热分析在内的电热(ET)分析在集成电路设计中非常重要。在观察温度对漏电流的影响(ET耦合效应)和电源电压对功耗的影响的基础上,提出了一种基于迭代的ET协同分析方法,该方法同时求解V&T,然后与V&T一起刷新功耗,以进行下一轮V&T求解。与现有方法将P/G分析和热分析视为独立的过程而不相互作用不同,蒸散发联合分析方法考虑了它们之间的相互作用,结果更加实际。由于P/G分析和热分析都非常耗时,本工作进一步采用多线程和GPU并行计算技术,基于CPU+GPU异构架构并行计算系统(PCS_CGHA)加速ET协同分析。实验结果表明,与我们的方法相比,考虑到ET耦合效应,现有的ET分析方法会给出过于悲观或过于乐观的结果。在PCS_CGHA上,该方法比无加速的朴素分析方法提高了44倍。
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