Fast and accurate computation using stochastic circuits
Fast and accurate computation using stochastic circuits
复制标题
使用随机电路进行快速准确的计算
DOI：
10.7873/date2014.089
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
J. Hayes
中科院分区：
文献类型：
--
作者：
Armin Alaghi;J. Hayes
随机计算（SC）是一种低成本的设计技术，在图像处理等应用中具有很大的前景。SC使算术运算能够使用超小和低功耗电路在随机比特流上执行。然而，由于随机数（SN）固有的随机波动，精确的计算往往需要很长的运行时间。我们提出了新的技术SN生成，导致更好的精度/运行时间的权衡。首先，我们分析了一个属性称为渐进精度（PP），它允许计算精度系统地增长与运行时。其次，借用蒙特卡罗方法，我们表明，SC性能可以大大提高，取代通常的伪随机数源的低差异（LD）序列是可预测的进步。最后，我们评估了LD随机数在SC中的使用，并表明它们可以比现有的随机设计产生更快，更准确的结果。
Stochastic computing (SC) is a low-cost design technique that has great promise in applications such as image processing. SC enables arithmetic operations to be performed on stochastic bit-streams using ultra-small and low-power circuitry. However, accurate computations tend to require long run-times due to the random fluctuations inherent in stochastic numbers (SNs). We present novel techniques for SN generation that lead to better accuracy/run-time trade-offs. First, we analyze a property called progressive precision (PP) which allows computational accuracy to grow systematically with run-time. Second, borrowing from Monte Carlo methods, we show that SC performance can be greatly improved by replacing the usual pseudo-random number sources by low-discrepancy (LD) sequences that are predictably progressive. Finally, we evaluate the use of LD stochastic numbers in SC, and show they can produce significantly faster and more accurate results than existing stochastic designs.