Abstract
This short paper introduces the basic concepts of Stochastic Computing (SC), and presents additions to a remote lab with reconfigurable logic to allow testing SC circuits. Recently, SC has been revisited and evaluated as a possible way of performing approximate probabilistic computations for artificial perception systems. New modules allow the generation of pseudo-random numbers, given a seed key and using linear feedback shift registers, but also having true random number generation using ring oscillators and embedded PLLs. Stochastic computing allows a tradeoff between resource usage and precision, allowing very simple circuits to perform computations, at the expense of a longer integration time to have reasonable results. We provide the basic stochastic computing modules, so that any user can use them to build a stochastic computing circuit and go beyond software simulations, providing a remote hardware device to test real circuits at high clock speeds.
Publisher
International Association of Online Engineering (IAOE)
Cited by
1 articles.
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1. Reservoir Computing for Scalable Hardware with
Block‐Based
Neural Network;IEEJ Transactions on Electrical and Electronic Engineering;2021-08-11