CASA: Correlation-aware speculative adders
CASA: Correlation-aware speculative adders
复制标题
CASA：相关感知推测加法器
DOI：
--
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Zhiru Zhang
中科院分区：
文献类型：
--
作者：
Gai Liu;Ye Tao;Mingxing Tan;Zhiru Zhang
投机性加法器将加法划分为子组并并行执行，以提高执行速度和能源效率，但会冒着生成错误结果的风险。在本文中，我们提出了一种轻量级相关感知推测加法(CASA)方法，该方法利用输入数据与实际基准测试中观察到的进位值之间的相关性来提高推测加法器的精度。实验结果表明，应用CASA方法后，误码率显著降低，而在时序、面积和功耗方面的开销都很小。
Speculative adders divide addition into subgroups and execute them in parallel for higher execution speed and energy efficiency, but at the risk of generating incorrect results. In this paper, we propose a lightweight correlation-aware speculative addition (CASA) method, which exploits the correlation between input data and carry-in values observed in real-life benchmarks to improve the accuracy of speculative adders. Experimental results show that applying the CASA method leads to a significant reduction in error rate with only marginal overhead in timing, area, and power consumption.