A fast word-level statistical estimator of intra-bus crosstalk

Suvodeep Gupta, S. Katkoori
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引用次数: 2

Abstract

Given word-level statistics, namely mean, standard deviation, and lag-one temporal correlation of input data, we estimate the bit-level crosstalk probability on a system bus using a non-enumerative statistical approach. We introduce a sampling technique for fast evaluation of integrals during the estimation process. We had proposed two techniques previously - (a) a stream-based estimator that counts crosstalk events on a bus; and (b) a statistical enumeration technique that enumerates crosstalk-producing values on a bus and computes their occurrence probability. Both these techniques suffer from exponential time complexity with respect to the bus-width. In this work, we propose a statistical non-enumerative technique that has linear time complexity with respect to the bus-width. We achieve the linear complexity by resorting to: (1) manipulating the data stream to make the crosstalk-producing values contiguous and (2) sampling the distribution function and storing it as a lookup table. Experimental results for data streams from different data environments are presented, compared against the stream-based approach. Average errors of less than 12% are obtained for bus-widths ranging from 8b to 32b.
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总线内串扰的快速字级统计估计
给定字级统计,即输入数据的平均值、标准差和滞后时间相关性,我们使用非枚举统计方法估计系统总线上的位级串扰概率。在估计过程中,我们引入了一种快速求积分的采样技术。我们之前提出了两种技术:(a)基于流的估计器,用于统计总线上的串扰事件;(b)统计枚举技术,枚举总线上产生串音的值并计算它们的发生概率。这两种技术都有相对于总线宽度的指数时间复杂度。在这项工作中,我们提出了一种统计非枚举技术,它具有相对于总线宽度的线性时间复杂度。我们通过以下方式实现线性复杂性:(1)操纵数据流使产生串扰的值相邻;(2)对分布函数进行采样并将其存储为查找表。给出了不同数据环境下的数据流的实验结果,并与基于流的方法进行了比较。母线宽度在8b ~ 32b范围内,平均误差小于12%。
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