改进并行随机计算延迟的范围分割

Rai Saraiva, Julio C. Ruzicki, A. Souza, R. Soares
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引用次数: 1

摘要

随机计算(SC)是一种容错设计范式,其中数值数据被转换为随机数字比特流上的概率。这种表示允许在低复杂度的硬件上进行计算。SC允许显着减少面积并增加对瞬态误差的容忍度,但要实现中等精度,则需要高延迟。最近的论文使用并行和随机多比特数表示来解决这个问题。本文提出了一种新的基于距离分割的随机表示方法——多级随机编码(MSC),利用FPGA设计流程开发了其运算符,并与其他方法进行了比较。在面积和延迟方面的比较应用于实现给定信噪比(SNR)的方法之间。结果表明,MSC表现出显著的延迟减少和较小的面积惩罚。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Range segmentation to improve latency in parallel stochastic computing
Stochastic Computing (SC) is a fault tolerant design paradigm where numeric data are converted to probabilities on streams of random digital bits. This representation allows computing on low complexity hardware. SC allows a significant area reduction and an increased tolerance to transient errors, but presents high latency to achieve a moderate accuracy. Recent papers address this issue using parallelism and stochastic multibit number representations. In this paper, Multilevel Stochastic Coding (MSC), a new stochastic representation based on range segmentation is presented and its operators are developed using FPGA design flow and compared to alternative approaches. A comparison in terms of area and latency is applied between approaches to achieve a given signal to noise ratio (SNR). Results show that MSC presents a significant latency reduction with a smaller area penalty.
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