Computing polynomials with positive coefficients using stochastic logic by double-NAND expansion

Sayed Ahmad Salehi; Yin Liu; Marc D. Riedel; Keshab K. Parhi

doi:10.1145/3060403.3060410

Computing polynomials with positive coefficients using stochastic logic by double-NAND expansion

Sayed Ahmad Salehi, Yin Liu, Marc D. Riedel, Keshab K. Parhi

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

19 Scopus citations

Abstract

This paper proposes a novel method, referred to as double-NAND expansion, to implement polynomials with all positive coefficients using unipolar stochastic logic. The proposed double-NAND expansion leads to implementations of polynomials using no more than 2n NAND gates where n represents the degree of the polynomial. The proposed implementations are compared with those based on multiplexers, Bernstein polynomial method, finite state machine method and factorization. The paper also considers implementations of several functions expressed as polynomials using truncated Mclaurin series based on the proposed approach. The experimental results show that the proposed method outperforms the prior methods in terms of accuracy, hardware complexity, and critical path.

Original language	English (US)
Title of host publication	GLSVLSI 2017 - Proceedings of the Great Lakes Symposium on VLSI 2017
Publisher	Association for Computing Machinery
Pages	471-474
Number of pages	4
ISBN (Electronic)	9781450349727
DOIs	https://doi.org/10.1145/3060403.3060410
State	Published - May 10 2017
Event	27th Great Lakes Symposium on VLSI, GLSVLSI 2017 - Banff, Canada Duration: May 10 2017 → May 12 2017

Publication series

Name	Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI
Volume	Part F127756

Other

Other	27th Great Lakes Symposium on VLSI, GLSVLSI 2017
Country/Territory	Canada
City	Banff
Period	5/10/17 → 5/12/17

Bibliographical note

Publisher Copyright:
© 2017 ACM.

Keywords

Double-NAND expansion
Stochastic logic

Publisher link

10.1145/3060403.3060410

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Salehi, S. A., Liu, Y., Riedel, M. D., & Parhi, K. K. (2017). Computing polynomials with positive coefficients using stochastic logic by double-NAND expansion. In GLSVLSI 2017 - Proceedings of the Great Lakes Symposium on VLSI 2017 (pp. 471-474). (Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI; Vol. Part F127756). Association for Computing Machinery. https://doi.org/10.1145/3060403.3060410

Computing polynomials with positive coefficients using stochastic logic by double-NAND expansion. / Salehi, Sayed Ahmad; Liu, Yin; Riedel, Marc D. et al.
GLSVLSI 2017 - Proceedings of the Great Lakes Symposium on VLSI 2017. Association for Computing Machinery, 2017. p. 471-474 (Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI; Vol. Part F127756).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Salehi, SA, Liu, Y, Riedel, MD & Parhi, KK 2017, Computing polynomials with positive coefficients using stochastic logic by double-NAND expansion. in GLSVLSI 2017 - Proceedings of the Great Lakes Symposium on VLSI 2017. Proceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI, vol. Part F127756, Association for Computing Machinery, pp. 471-474, 27th Great Lakes Symposium on VLSI, GLSVLSI 2017, Banff, Canada, 5/10/17. https://doi.org/10.1145/3060403.3060410

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abstract = "This paper proposes a novel method, referred to as double-NAND expansion, to implement polynomials with all positive coefficients using unipolar stochastic logic. The proposed double-NAND expansion leads to implementations of polynomials using no more than 2n NAND gates where n represents the degree of the polynomial. The proposed implementations are compared with those based on multiplexers, Bernstein polynomial method, finite state machine method and factorization. The paper also considers implementations of several functions expressed as polynomials using truncated Mclaurin series based on the proposed approach. The experimental results show that the proposed method outperforms the prior methods in terms of accuracy, hardware complexity, and critical path.",

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Computing polynomials with positive coefficients using stochastic logic by double-NAND expansion

Abstract

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