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

机译:公交车内串扰的快速词级统计估算器

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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 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.
机译:给定词级统计,即均值,标准偏差和输入数据的一个时间相关性,我们使用非枚举统计方法估计系统总线上的比特级串扰概率。我们介绍了一种采样技术,可在估计过程中快速评估积分。我们先前提出了两种技术 - (a)基于流的估计,可以在公共汽车上计算串扰事件; (b)统计枚举技术,其枚举在总线上产生串扰的值并计算其发生概率。这两种技术都遭受了相对于总线宽度的指数时间复杂性。在这项工作中,我们提出了一种统计非枚举技术,其具有相对于总线宽度的线性时间复杂性。我们通过诉诸:(1)操纵数据流以使得串扰制作值连续和(2)采样分布函数并将其存储为查找表来实现线性复杂性。呈现来自不同数据环境的数据流的实验结果,与基于流的方法进行比较。对于从8B至32B的总线宽度获得的平均误差为小于12%。

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