Agile Simulation of Stochastic Computing Image Processing with Contingency Tables

The rapid computerized simulation of stochastic computing (SC) systems is a challenging problem. A method for agile simulation of SC image processing is proposed in this work. The input operands are processed with the aid of a correlation-controlled contingency table (CT) construct without using act...

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Vydáno v:	IEEE transactions on computer-aided design of integrated circuits and systems Ročník 42; číslo 10; s. 1
Hlavní autoři:	Aygun, Sercan, Najafi, M. Hassan, Imani, Mohsen, Gunes, Ece Olcay
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.10.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Bit-stream processing Computational modeling Computed tomography Computer memory computer-aided simulation Contingency contingency table Contingency tables Correlation Error analysis Image processing Integrated circuit modeling Interpolation Logic gates Pseudorandom Simulation stochastic computing Stochastic processes
ISSN:	0278-0070, 1937-4151
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Abstract	The rapid computerized simulation of stochastic computing (SC) systems is a challenging problem. A method for agile simulation of SC image processing is proposed in this work. The input operands are processed with the aid of a correlation-controlled contingency table (CT) construct without using actual stochastic bit-streams. The proposed approach underlines the validity of CT simulation with (i) image compositing, (ii) pattern detection, and (iii) bilinear interpolation case studies. Using the corresponding error models, we emulate the state-of-the-art pseudo-random and quasi-random bit-streams. Experimental results show that the proposed approach achieves similar computation accuracy to the traditional SC simulation while performing runtime-and memory-efficient computations. The execution time reduces more than 200× for the image compositing task when emulating random bit-streams with CT. Pattern detection and bilinear interpolation further showed 76× and 22× lower memory usage, respectively, when employing CT.
AbstractList	The rapid computerized simulation of stochastic computing (SC) systems is a challenging problem. A method for agile simulation of SC image processing is proposed in this work. The input operands are processed with the aid of a correlation-controlled contingency table (CT) construct without using actual stochastic bit-streams. The proposed approach underlines the validity of CT simulation with 1) image compositing; 2) pattern detection; and 3) bilinear interpolation case studies. Using the corresponding error models, we emulate the state-of-the-art pseudo-random and quasi-random bit-streams. Experimental results show that the proposed approach achieves similar computation accuracy to the traditional SC simulation while performing runtime- and memory-efficient computations. The execution time reduces more than [Formula Omitted] for the image compositing task when emulating random bit-streams with CT. Pattern detection and bilinear interpolation further showed [Formula Omitted] and [Formula Omitted] lower memory usage, respectively, when employing CT. The rapid computerized simulation of stochastic computing (SC) systems is a challenging problem. A method for agile simulation of SC image processing is proposed in this work. The input operands are processed with the aid of a correlation-controlled contingency table (CT) construct without using actual stochastic bit-streams. The proposed approach underlines the validity of CT simulation with (i) image compositing, (ii) pattern detection, and (iii) bilinear interpolation case studies. Using the corresponding error models, we emulate the state-of-the-art pseudo-random and quasi-random bit-streams. Experimental results show that the proposed approach achieves similar computation accuracy to the traditional SC simulation while performing runtime-and memory-efficient computations. The execution time reduces more than 200× for the image compositing task when emulating random bit-streams with CT. Pattern detection and bilinear interpolation further showed 76× and 22× lower memory usage, respectively, when employing CT.
Author	Najafi, M. Hassan Gunes, Ece Olcay Aygun, Sercan Imani, Mohsen
Author_xml	– sequence: 1 givenname: Sercan orcidid: 0000-0002-4615-7914 surname: Aygun fullname: Aygun, Sercan organization: ECE Dept, Istanbul Technical Univ, Istanbul, Turkey – sequence: 2 givenname: M. Hassan orcidid: 0000-0002-4655-6229 surname: Najafi fullname: Najafi, M. Hassan organization: Sch. Comp. and Info, University of Louisiana at Lafayette, Lafayette, LA, USA – sequence: 3 givenname: Mohsen orcidid: 0000-0002-5761-0622 surname: Imani fullname: Imani, Mohsen organization: Department of Computer Science, University of California Irvine, Irvine, CA, USA – sequence: 4 givenname: Ece Olcay orcidid: 0000-0001-9186-7424 surname: Gunes fullname: Gunes, Ece Olcay organization: ECE Dept, Istanbul Technical Univ, Istanbul, Turkey
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SubjectTerms	Bit-stream processing Computational modeling Computed tomography Computer memory computer-aided simulation Contingency contingency table Contingency tables Correlation Error analysis Image processing Integrated circuit modeling Interpolation Logic gates Pseudorandom Simulation stochastic computing Stochastic processes
Title	Agile Simulation of Stochastic Computing Image Processing with Contingency Tables
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