An Efficient and Accurate Stochastic Number Generator Using Even-Distribution Coding

Zhakatayev, Aidyn; Kim, Kyounghoon; Choi, Ki‐Young; Lee, Jong-Eun

doi:10.1109/tcad.2018.2789732

Cited by 10 publications

(2 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on the concept of statistically independent sequences as the SNG, a modulator-based system that generates binary sequences has been developed [7]. Considering that the SNG needs more area and power than SC computing cores, and also due to the importance of error measurement at the output, an error-cancelling conversion unit [8] and even-distribution coding method have been implemented [9]. The computational cost of the SNG in an SC system has been reduced by using a methodology of decomposition in the design and re-use of its functional unit [10].…”

Section: Related Work On Stochastic Computing Elementsmentioning

confidence: 99%

Accuracy Analysis on Design of Stochastic Computing in Arithmetic Components and Combinational Circuit

Ashok,

Bala Tripura Sundari

2023

Computation

View full text Add to dashboard Cite

Stochastic circuits are used in applications that require low area and power consumption. The computing performed using these circuits is referred to as Stochastic computing (SC). The arithmetic operations in this computing can be realized using minimum logic circuits. The SC system allows a tradeoff of computational accuracy and area; thereby, the challenge in SC is improving the accuracy. The accuracy depends on the SC system’s stochastic number generator (SNG) part. SNGs provide the appropriate stochastic input required for stochastic computation. Hence we explore the accuracy in SC for various arithmetic operations performed using stochastic computing with the help of logic circuits. The contributions in this paper are; first, we have performed stochastic computing for arithmetic components using two different SNGs. The SNGs considered are Linear Feed-back Shift Register (LFSR) -based traditional stochastic number generators and S-box-based stochastic number generators. Second, the arithmetic components are implemented in a combinational circuit for algebraic expression in the stochastic domain using two different SNGs. Third, computational analysis for stochastic arithmetic components and the stochastic algebraic equation has been conducted. Finally, accuracy analysis and measurement are performed between LFSR-based computation and S-box-based computation. The novel aspect of this work is the use of S-box-based SNG in the development of stochastic computing in arithmetic components. Also, the implementation of stochastic computing in the combinational circuit using the developed basic arithmetic components, and exploration of accuracy with respect to stochastic number generators used is presented.

show abstract

Section: Related Work On Stochastic Computing Elementsmentioning

confidence: 99%

Accuracy Analysis on Design of Stochastic Computing in Arithmetic Components and Combinational Circuit

Ashok,

Bala Tripura Sundari

2023

Computation

View full text Add to dashboard Cite

show abstract

“…Non Availability of Reactive Power: DG's like traditional wind farms using asynchronous generators do not supply reactive power to the grid. But DG [23] units along with power electronic interfaces are capable of delivering reactive power. DG's can supply and consume reactive power as and when desired System Frequency: The penetration of DG in the system affects the system frequency and control becomes more complicated.…”

Section: Dg Issues and Limitationsmentioning

confidence: 99%

A Comparative Investigation on Optimization Techniques for Optimal Penetration of Distribution Generators in Power System Application

Bondriya,

Kumar,

Wadhwani

2018

AJES

View full text Add to dashboard Cite

In deregulation of power system, different regulatory units, environmental concerns and economic concerns have lead to the penetration of Distributed Generation (DG) in power system. When DGs are penetrated, various parameters like DG technology, optimal size, optimal location, and its impact on various operating characteristics such electrical losses, voltage profile, stability and reliability of power system are to be monitored. The performance of DG penetration depends largely upon the selection of the optimal parameter values. Special optimizing techniques used to evaluate optimal value of parameter in context of heuristic nature of variable. A literature review has been carried out on different optimal technique used to optimize parameter values. The authors have reviewed various definitions related to DG and conventional and non conventional technologies on which DG are based. Various issues regarding DG integration have been discussed. Exhaustive reviews of many optimization techniques have been done for optimal location and size of DG.

show abstract

Accelerating Deep Convolutional Neural Network base on stochastic computing

Sadi

Mahani

2021

Integration

View full text Add to dashboard Cite

An Efficient and Accurate Stochastic Number Generator Using Even-Distribution Coding

Cited by 10 publications

References 17 publications

Accuracy Analysis on Design of Stochastic Computing in Arithmetic Components and Combinational Circuit

Accuracy Analysis on Design of Stochastic Computing in Arithmetic Components and Combinational Circuit

A Comparative Investigation on Optimization Techniques for Optimal Penetration of Distribution Generators in Power System Application

Accelerating Deep Convolutional Neural Network base on stochastic computing

Contact Info

Product

Resources

About