Efficient architectures and implementation of arithmetic functions approximation based stochastic computing

dc.contributor.authorLuong, Tieu-Khanh
dc.contributor.authorNguyen, Van-Tinh
dc.contributor.authorNguyen, Anh-Thai
dc.contributor.authorPopovici, Emanuel M.
dc.date.accessioned2019-10-21T14:13:58Z
dc.date.available2019-10-21T14:13:58Z
dc.date.issued2019-07
dc.date.updated2019-10-21T14:07:55Z
dc.description.abstractStochastic computing (SC) has emerged as a potential alternative to binary computing for a number of low-power embedded systems, DSP, neural networks and communications applications. In this paper, a new method, associated architectures and implementations of complex arithmetic functions, such as exponential, sigmoid and hyperbolic tangent functions are presented. Our approach is based on a combination of piecewise linear (PWL) approximation as well as a polynomial interpolation based (Lagrange interpolation) methods. The proposed method aims at reducing the number of binary to stochastic converters. This is the most power sensitive module in an SC system. The hardware implementation for each complex arithmetic function is then derived using the 65nm CMOS technology node. In terms of accuracy, the proposed approach outperforms other well-known methods by 2 times on average. The power consumption of the implementations based on our method is decreased on average by 40 % comparing to other previous solutions. Additionally, the hardware complexity of our proposed method is also improved (40 % on average) while the critical path of the proposed method is slightly increased by 2.5% on average when comparing to other methods.en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationLuong, T., Nguyen, V., Nguyen, A. and Popovici, E. (2019) 'Efficient Architectures and Implementation of Arithmetic Functions Approximation Based Stochastic Computing'. 2019 IEEE 30th International Conference on Application-specific Systems, Architectures and Processors (ASAP), New York, USA, 15-17 July, pp. 281-287. doi: 10.1109/ASAP.2019.00018en
dc.identifier.doi10.1109/ASAP.2019.00018en
dc.identifier.endpage287en
dc.identifier.issn2160-052X
dc.identifier.startpage281en
dc.identifier.urihttps://hdl.handle.net/10468/8805
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urihttps://ieeexplore.ieee.org/abstract/document/8825149
dc.rights© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en
dc.subjectComputer architectureen
dc.subjectDigital arithmeticen
dc.subjectEmbedded systemsen
dc.subjectFunction approximationen
dc.subjectInterpolationen
dc.subjectPolynomialsen
dc.subjectStochastic processesen
dc.subjectCommunications applicationsen
dc.subjectAssociated architecturesen
dc.subjectComplex arithmetic functionen
dc.subjectExponential functionsen
dc.subjectSigmoid functionsen
dc.subjectHyperbolic tangent functionsen
dc.subjectPiecewise linear approximationen
dc.subjectPolynomial interpolationen
dc.subjectStochastic convertersen
dc.subjectPower sensitive moduleen
dc.subjectSC systemen
dc.subjectHardware implementationen
dc.subjectPower consumptionen
dc.subjectHardware complexityen
dc.subjectArithmetic functions approximationen
dc.subjectStochastic computingen
dc.subjectBinary computingen
dc.subjectLow-power embedded systemsen
dc.subjectNeural networksen
dc.subjectCMOS technology nodeen
dc.subjectHardwareen
dc.subjectLogic gatesen
dc.subjectComplexity theoryen
dc.subjectPower demanden
dc.subjectStochastic computingen
dc.subjectVLSIen
dc.subjectArithmeticen
dc.subjectLow poweren
dc.subjectEfficient architecturesen
dc.subjectSigmoid functionen
dc.subjectPiecewise linear approximationen
dc.subjectLagrange interpolationsen
dc.titleEfficient architectures and implementation of arithmetic functions approximation based stochastic computingen
dc.typeConference itemen
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