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

机译:C-矿:低功耗合成逻辑常见案例的数据挖掘,更良好的案例设计

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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.
机译:众所周知,更良好的案例(BTW)设计方法,以提高电路能效,性能和可靠性。但是,大多数现有方法不提供足够可扩展的解决方案。因此,我们提出了一种新的技术,C-MINE,它结合了两个可扩展技术,数据挖掘和SAT解决,提供了扩展解决方案。数据挖掘可以有效地从巨大的数据集中提取模式,并且SAT Solving以其可扩展验证而闻名。实验结果表明,与最近的出版物相比,C-Mine可以通过额外的5%节能,平均更大的基准,50倍加速,C-Mine可以实现兼容性。

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