C-Mine: Data Mining of Logic Common Cases for Low Power Synthesis of Better-Than-Worst-Case Designs

DAC(2014)

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摘要
The Better-Than-Worst-Case (BTW) design methodology is well-known for its potential to improve circuit energy efficiency, performance, and reliability. However, most existing methods do not provide sufficiently scalable solutions. Thus, we propose a new technique, C-Mine, which combines two scalable techniques, data mining and SAT solving, to provide scale-up solutions. Data mining can efficiently extract patterns from an enormous data set, and SAT solving is famous for its scalable verification. The experimental results show that, compared to a recent publication, C-Mine can achieve compatible performance with an additional 5% energy savings, and 50x speedup for bigger benchmarks on average.
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关键词
circuit reliability,logic circuits,common case,resynthesis,scalability,design aids,low power synthesis,better-than-worst-case designs,timing error resilience,reliability,c-mine,data mining,scalable techniques,logic common cases,energy efficiency,sat solving
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