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A Fast Word-Level Statistical Estimator of Intra-Bus Crosstalk

机译:总线内串扰的快速字级统计估计器

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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 linearcomplexity 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. Experimentalresults 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.
机译:给定字级统计信息,即平均值,标准偏差和输入数据的滞后一时间相关性,我们使用非枚举统计方法估算系统总线上的位级串扰概率。我们介绍了一种在估算过程中用于快速评估积分的采样技术。我们以前曾提出过两种技术-(a)基于流的估计器,用于计算总线上的串扰事件; (b)一种统计枚举技术,该技术枚举总线上产生串扰的值并计算其发生概率。相对于总线宽度,这两种技术都遭受指数时间复杂度的困扰。在这项工作中,我们提出了一种统计非枚举技术,该技术相对于总线宽度具有线性时间复杂度。我们通过以下方式实现线性复杂度:(1)处理数据流以使产生串扰的值连续,以及(2)对分布函数进行采样并将其存储为查找表。与基于流的方法相比,提供了来自不同数据环境的数据流的实验结果。对于8b至32b的总线宽度,获得的平均误差小于12%。

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