矩阵-向量乘法的电荷模式并行架构

Roman Genov, Gert Cauwenberghs
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引用次数: 28

摘要

提出了一种内部模拟,外部数字的矩阵向量乘法体系结构。完全并行处理允许高数据吞吐量和最小延迟。模拟体系结构包含一组带动态存储和行并行闪存模数转换器(ADC)的电荷模式模拟计算单元。每个单元包括一个动态存储单元和一个电荷注入装置,用于计算两个参数的二进制内积。矩阵元素以位并行方式存储在计算单元数组中,输入向量以位串行方式表示。然后对ADC输出进行数字后处理,以构建精度高于每次转换的结果乘积。模拟架构专为高密度和低功耗VLSI实现而量身定制,在标准CMOS 0.5 /spl mu/m技术的3mm /spl times/ 3mm芯片上,矩阵尺寸为128/spl times/512, ADC分辨率为6位,总分辨率超过8位。
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Charge-mode parallel architecture for matrix-vector multiplication
An internally analog, externally digital architecture for matrix-vector multiplication is presented. Fully parallel processing allows for high data throughput and minimal latency. The analog architecture incorporates an array of charge-mode analog computational cells with dynamic storage and row-parallel flash analog-to-digital converters (ADC). Each of the cells includes a dynamic storage element and a charge injection device computing binary inner product of two arguments. The matrix elements are stored in the array of computational cells in bit-parallel fashion, and the input vector is presented bit-serially. Digital post-processing is then performed on the ADC outputs to construct the resulting product with precision higher than that of each conversion. The analog architecture is tailored for high-density and low power VLSI implementation, and matrix dimensions of 128/spl times/512 and ADC resolution of 6 bits for an overall resolution in excess of 8 bits are feasible on a 3 mm/spl times/3 mm chip in standard CMOS 0.5 /spl mu/m technology.
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