An Efficient Approximate Node Merging with an Error Rate Guarantee

Kit Seng Tam, Chia-Chun Lin, Yung-Chih Chen, Chun-Yao Wang
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引用次数: 3

Abstract

MachineryApproximate computing is an emerging design paradigm for error-tolerant applications. e.g., signal processing and machine learning. In approximate computing, the area, delay, or power consumption of an approximate circuit can be improved by trading off its accuracy. In this paper, we propose an approximate logic synthesis approach based on a node-merging technique with an error rate guarantee. The ideas of our approach are to replace internal nodes by constant values and to merge two similar nodes in the circuit in terms of functionality. We conduct experiments on a set of IWLS 2005 and MCNC benchmarks. The experimental results show that our approach can reduce area by up to 80%, and 31% on average. As compared with the state-of-the-art method, our approach has a speedup of 51 under the same 5% error rate constraint.
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具有错误率保证的高效近似节点合并
MachineryApproximate computing是容错应用的一种新兴设计范式。例如,信号处理和机器学习。在近似计算中,近似电路的面积、延迟或功耗可以通过牺牲其精度来改进。本文提出了一种基于错误率保证的节点合并技术的近似逻辑综合方法。我们的方法是用常量替换内部节点,并在功能方面合并电路中两个相似的节点。我们在IWLS 2005和MCNC基准上进行了实验。实验结果表明,我们的方法可以减少80%的面积,平均减少31%。与最先进的方法相比,在相同的5%错误率约束下,我们的方法的加速提高了51。
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