Fast thermal simulation of 2D/3D integrated circuits exploiting neural networks and GPUs

A. Vincenzi, A. Sridhar, M. Ruggiero, David Atienza Alonso
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引用次数: 26

Abstract

Heat removal is one of the major challenges faced in developing the new generation of high density integrated circuits. Future design technologies strongly depend on the availability of efficient means for thermal modeling and analysis. These thermal models must be also accurate and provide the most efficient level of abstraction enabling fast execution. We propose an innovative thermal simulation method based on Neural Networks that is able to solve the scalability problem of transient heat flow simulation in large 2D/3D multi-processor ICs by exploiting the computational power of massively parallel graphics processing units (GPUs).
基于神经网络和gpu的2D/3D集成电路快速热模拟
散热是开发新一代高密度集成电路所面临的主要挑战之一。未来的设计技术在很大程度上取决于热建模和分析的有效手段。这些热模型还必须是准确的,并提供最有效的抽象级别,以实现快速执行。本文提出了一种基于神经网络的热模拟方法,利用大规模并行图形处理器(gpu)的计算能力,解决了大型2D/3D多处理器集成电路中瞬态热流模拟的可扩展性问题。
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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