On the Functions Realized by Stochastic Computing Circuits

Alaghi, Armin; Hayes, John P.

doi:10.1145/2742060.2743758

Cited by 20 publications

(9 citation statements)

References 27 publications

(52 reference statements)

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“…Some related research challenges posed by SC are also discussed. Yin Liu et al [7] this paper addresses computing complicated functions using unipolar stochastic logic. Stochastic computing requires simple logic gates and is inherently fault-tolerant.…”

Section: Stochastic Logic Approachmentioning

confidence: 99%

Estimation of Mathematical Function by Stochastic Logic

Wadhekar¹

2020

IJRASET

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Recent application demand high speed and robustness with small area and low power consumptions. Much pupation in nanometer scale technology in VLSI dimension of transistors goes on reducing. On the other hand increasing number of transistors leads to leakage current so Circuit becomes unreliable. Additionally, if transistors are replacing by other devices it does not yield satisfied result. Owning to these complications an alternative method for computing technique called stochastic logic. This paper described a stochastic implementation for various mathematical functions which analyses the area, power consumption, delay, efficiency. Logic implementations overcome the disadvantages of conventional methods.

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Section: Stochastic Logic Approachmentioning

confidence: 99%

Estimation of Mathematical Function by Stochastic Logic

Wadhekar¹

2020

IJRASET

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“…This approach decreases the random fluctuations and enables the designer to use part of the SNs to obtain acceptable results that improve the latency. Secondly, accuracy is improved by using circuits with correlated inputs (CSC) [6,19], which reduce the area cost. Thirdly, accuracy can be enhanced by performing SC operations using deterministic bit-streams [20,21].…”

Section: Related Workmentioning

confidence: 99%

“…The accuracy in SC is affected by multiple sources. The sources of these inaccuracies are the low precision, random number fluctuations, conversion error, and correlation-induced inaccuracies [19]. In this work, we concentrate on the correlation-induced inaccuracies.…”

Section: Related Workmentioning

confidence: 99%

Accurate and compact stochastic computations by exploiting correlation

Abdellatef¹,

Khalil-Hani²,

Shaikh-Husin³

2019

Turk J Elec Eng & Comp Sci

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Recent studies have shown, contrary to what was previously believed, that by exploiting correlation in stochastic computing (SC) designs, more accurate SC circuits with low area cost can be realized. However, if these basic SC circuits or blocks are cascaded in series to form a large complex system, correlation between stochastic numbers (SNs) from one block to the next would be lost; thus, inaccuracies are introduced. In this study, we propose correlating circuits to be used in building complex correlated SC systems. One of the circuits is the correlator that restores lost correlations between two SNs due to previous processing. In addition, a correlated SN generator is introduced to generate SN correlated to a specific SN. Experimental results show that our methods have improved the accuracy of stochastic computation and preserved the stochastic computing correlation without the need for conversion from SC to the conventional binary-encoded computing, and vice versa. Consequently, lower latency and lower area cost are achieved.

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“…In SC, a set of SNs X = {X1, X2, …, Xn} with probability values {X1, X2,…, Xn} is typically applied to a combinational logic circuit C realizing some Boolean function f (x1, x2,…, xn). Viewed as a stochastic circuit, C computes an arithmetic function F(X1,X2,…, Xn) determined by f and the joint probability distribution of X [3]. For example, the AND gate of Fig.…”

Section: Introductionmentioning

confidence: 99%

On the Role of Sequential Circuits in Stochastic Computing

Ting

Hayes

2017

Proceedings of the Great Lakes Symposium on VLSI 2017

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Interest in stochastic computing (SC) has been growing due to the need for low-cost circuitry in areas like image processing and machine learning. While combinational stochastic circuits are relatively easy to design, their limitations such as having few implementable functions and inaccuracies due to correlation, call for sequential components and design methods. The theory underlying sequential stochastic circuits is not fully understood, however. Almost all existing sequential SC circuits fall into the up/down-counter-based (UCB) class. In this paper, we identify and investigate a new SC circuit class: shift-register-based (SRB). We focus on the properties of SRB circuits and demonstrate their central role in stochastic computing. This leads to an algorithm MOUSE for sequential design optimization. By exploiting sequential stochastic equivalence, MOUSE can reduce SRB circuit cost without compromising performance or accuracy.

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On the Functions Realized by Stochastic Computing Circuits

Cited by 20 publications

References 27 publications

Estimation of Mathematical Function by Stochastic Logic

Estimation of Mathematical Function by Stochastic Logic

Accurate and compact stochastic computations by exploiting correlation

On the Role of Sequential Circuits in Stochastic Computing

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