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.

Highlights

  • This demo showcases the basic principles of Stochastic Computing and allows the design and test of circuits using the remote FPGA

  • This enables to go beyond simple simulations, and having real circuits working at high clock speeds and embedded real random number generators

  • The other input of the comparator is connected to the input of the value that is to be converted to stochastic computing

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Summary

INTRODUCTION

Stochastic Computing (SC), has been proposed [1, 2] as an alternative number representation scheme which provides higher tolerance to errors and more compact operators than conventional representation schemes, e.g. fixedpoint and floating point binary representations. A stochastic stream, according to [3], is defined as a sequence of stochastic signals over time, where its value is defined as the number of ones over the total number of bits It has gained the attention of the scientific community for its low implementation cost, fast computations and robustness of approximated streams [4]. This demo showcases the basic principles of Stochastic Computing and allows the design and test of circuits using the remote FPGA. In [6] the system is described in more detail, and presented in the context of a digital design course

STOCHASTIC COMPUTING
Stochastic to Binary Conversion
Multiplication
Addition
REMOTE LAB FOR STOCHASTIC COMPUTING
Building and Testing a Circuit
CONCLUSIONS
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