research-article

Open access

A Simplified Phase Model for Simulation of Oscillator-Based Computing Systems

Authors: Yan Fang, Victor V. Yashin, Brandon B. Jennings, Donald M. Chiarulli, Steven P. LevitanAuthors Info & Claims

ACM Journal on Emerging Technologies in Computing Systems (JETC), Volume 13, Issue 2

Article No.: 14, Pages 1 - 20

https://doi.org/10.1145/2976743

Published: 01 December 2016 Publication History

Abstract

Building oscillator-based computing systems with emerging nano-device technologies has become a promising solution for unconventional computing tasks like computer vision and pattern recognition. However, simulation and analysis of these computing systems is both time and compute intensive due to the nonlinearity of new devices and the complex behavior of coupled oscillators. In order to speed up the simulation of coupled oscillator systems, we propose a simplified phase model to perform phase and frequency synchronization prediction based on a synthesis of earlier models. Our model can predict the frequency-locking behavior with several orders of magnitude speedup compared to direct evaluation, enabling the effective and efficient simulation of the large numbers of oscillators required for practical computing systems. We demonstrate the oscillator-based computing paradigm with three applications, pattern matching, convolution, and image segmentation. The simulation with these models are respectively sped up by factors of 780, 300, and 1120 in our tests.

References

[1]

G. I. Bourianoff, J. E. Brewer, R. Cavin, J. A. Hutchby, and V. Zhirnov. 2008. Boolean logic and alternative information-processing devices. Computer 41 5, 38--46.

Digital Library

[2]

D. M. Chiarulli, B. B. Jennings, Y. Fang, A. Seel, and S. P. Levitan. 2015. A computational primitive for convolution based on coupled oscillator arrays. In Proceedings of the 2015 IEEE Computer Society Annual Symposium on VLSI (ISVLSI).

[3]

M. J. Cotter, Y. Fang, S. P. Levitan, D. M. Chiarulli, and V. Narayanan. 2014. Computational architectures based on coupled oscillators. In Proceedings of the 2014 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 130--135.

Digital Library

[4]

G. Csaba and W. Porod. 2013. Computational study of spin-torque oscillator interactions for non-Boolean computing applications. IEEE Transactions on Magnetics 49, 7, 4447--4451.

[5]

A. Demir, A. Mehrotra, and J. Roychowdhury. 2000. Phase noise in oscillators: a unifying theory and numerical methods for characterization. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 47, 5, 655--674.

[6]

D. Fan, S. Maji, K. Yogendra, M. Sharad, and K. Roy. 2015. Injection-locked spin hall-induced coupled-oscillators for energy efficient associative computing. IEEE Transactions on Nanotechnology 14, 6, 1083--1093.

[7]

Y. Fang, M. J. Cotter, D. M. Chiarulli, and S. P. Levitan. 2014. Image segmentation using frequency locking of coupled oscillators. In Proceedings of the 2014 14th International Workshop on Cellular Nanoscale Networks and Their Applications (CNNA), IEEE, 1--2.

[8]

Y. Fang, S. P. Levitan, D. M. Chiarulli, and D. H. Dash. 2015. Alternative architectures for non-Boolean information processing systems. In Emerging Nanoelectronic Devices. John Wiley and Sons Ltd., 467--497.

[9]

C. C. Foster, 1976. Content addressable parallel processors, John Wiley and Sons, Inc., New York.

Digital Library

[10]

F. C. Hoppensteadt and E. M. Izhikevich. 1997. Weakly Connected Neural Networks. Springer-Verlag, New York.

Digital Library

[11]

F. C. Hoppensteadt and E. M. Izhikevich. 2000. Pattern recognition via synchronization in phase-locked loop neural networks. IEEE Transactions on Neural Networks, 3, 734--738.

Digital Library

[12]

J. A. Hutchby, R. Cavin, V. Zhirnov, J. E. Brewer, and G. I. Bourianoff. 2008. Emerging nanoscale memory and logic devices: A critical assessment. Computer 41, 5, 28--32.

Digital Library

[13]

B. B. Jennings, R. Barnett, C. Gnegy, J. Carpenter, Y. Fang, D. M. Chiarulli, and S. P. Levitan. 2014. HMAX image processing pipeline with coupled oscillator acceleration. In Proceedings of the 2014 IEEE Workshop on Signal Processing Systems (SiPS) 1--6.

[14]

M. Kabir and M. Stan. 2014. Computing with hybrid CMOS/STO circuits. In Proceedings of the 51st Annual Design Automation Conference on Design Automation Conference, ACM, 1--6.

Digital Library

[15]

A. Krizhevsky, I. Sutskever, and G. E. Hinton. 2012. Imagenet classification with deep convolutional neural networks. In Advances in Neural Information Processing Systems. 1097--1105.

Digital Library

[16]

Y. Kuramoto 1984. Chemical Oscillations, Waves, and Turbulence. Springer.

[17]

X. Lai and J. Roychowdhury. 2005. Analytical equations for predicting injection locking in LC and ring oscillators. In Proceedings of the IEEE Custom Integrated Circuits Conference, 2005, 461--464.

[18]

Y. LeCun and C. Cortes. 1998. MNIST handwritten digit database. AT8T Labs [Online]. Available: http://yann.lecun.com/exdb/mnist/.

[19]

S. P. Levitan, Y. Fang, D. H. Dash, T. Shibata, D. E. Nikonov, and G. I. Bourianoff. 2012. Non-Boolean associative architectures based on nano-oscillators. In Proceedings of the 13th IEEE International Workshop on Cellular Nanoscale Networks and Their Applications (CNNA), (1--6).

[20]

N. Locatelli, V. Cros, and J. Grollier. 2014. Spin-torque building blocks. Nature Materials 13, 1, 11--20.

[21]

Neovision2 dataset - iLab - University of Southern California. Retrieved November 12, 2013, from http://ilab.usc.edu/neo2/dataset/, 2013.

[22]

Paolo. Maffezzoni. 2010. Synchronization analysis of two weakly coupled oscillators through a PPV macromodel. IEEE Transactions on Circuits and Systems I: Regular Papers 57.3, 654--663.

Digital Library

[23]

M. R. Pufall, W. H. Rippard, S. Kaka, T. J. Silva, and S. E. Russek. 2005. Frequency modulation of spin-transfer oscillators, Applied Physics Letters 86, 8, 082506--082506.

[24]

T. Serre and M. Riesenhuber. 2004. Realistic modeling of simple and complex cell tuning in the HMAX model, and implications for invariant object recognition in cortex, CBCL Paper 239/AI Memo 2004--017, Massachusetts Institute of Technology, Cambridge, 2004.

[25]

T. Shibata, R. Zhang, S. P. Levitan, D. E. Nikonov, and G. I. Bourianoff, 2012. CMOS supporting circuitries for nano-oscillator-based associative memories. In Proceedings of the 13th IEEE International Workshop on Cellular Nanoscale Networks and Their Applications (CNNA), 1--5.

[26]

N. Shukla, A. Parihar, E. Freeman, H. Paik, G. Stone, V. Narayanan, H. Wen, Z. Cai, V. Gopalan, R. Engel-Herbert, D. G. Schlom, A. Raychowdhury, and S. Datta. 2014. Synchronized charge oscillations in correlated electron systems. Scientific Reports 4.

[27]

E. M. Izhikevich. 2007. Synchronization, Chapter 10 In Dynamical Systems in Neuroscience. MIT press.

[28]

D. Wang and D. Termani. 1995. Locally excitatory globally inhibitory oscillator networks. IEEE Transactions on Neural, 1, 283--286.

Digital Library

[29]

D. Weinstein and S. A. Bhave. 2010. The resonant body transistor. Nano Letters, 4, 1234--1237.

[30]

A. T. Winfree. 1967. Biological rhythms and the behavior of populations of coupled oscillators. J. Theoret., 16, 1, 15--42.

Cited By

Zahedinejad MAwad AMuralidhar SKhymyn RFulara HMazraati HDvornik MÅkerman J(2019)Two-dimensional mutually synchronized spin Hall nano-oscillator arrays for neuromorphic computingNature Nanotechnology10.1038/s41565-019-0593-9Online publication date: 23-Dec-2019
https://doi.org/10.1038/s41565-019-0593-9
ESKALEN HÖZĞAN Ş(2018)Examining phase response curve of nerve cell by using three different methodsInternational Journal of Chemistry and Technology10.32571/ijct.3384032:1(1-9)Online publication date: 28-Feb-2018
https://doi.org/10.32571/ijct.338403

Index Terms

A Simplified Phase Model for Simulation of Oscillator-Based Computing Systems
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
2. Hardware
  1. Emerging technologies

Recommendations

A fully monolithic 5.8 GHz low phase noise coupled VCO network for phased-array systems

A fully monolithic coupled differential Voltage-Controlled-Oscillators (VCOs) network for phased-array applications is presented in this paper. The proposed integrated VCO array is implemented on a 0.25 µm BiCMOS SiGe process and is made of four LC-NMOS ...
A quadrature RC-oscillator with capacitive coupling

In this paper the capacitive coupling in quadrature RC-oscillators is investigated. The capacitive coupling has the advantages of being noiseless with a small area penalty and without increasing the power dissipation. The results show that a phase error ...
A low-phase-noise 900-MHz CMOS ring oscillator with quadrature output

A 900-MHz two-stage CMOS voltage controlled ring oscillator (VCRO) with quadrature output is presented. The circuit is designed in a 0.18-um CMOS technology and operated on a 1.8-V supply voltage. The VCRO have a tuning range of 730 MHz to 1.43 GHz and ...

Comments

Information & Contributors

Information

Published In

cover image ACM Journal on Emerging Technologies in Computing Systems

ACM Journal on Emerging Technologies in Computing Systems Volume 13, Issue 2

Special Issue on Nanoelectronic Circuit and System Design Methods for the Mobile Computing Era and Regular Papers

April 2017

377 pages

ISSN:1550-4832

EISSN:1550-4840

DOI:10.1145/3014160

Editor:
Yuan Xie
University of California, Santa Barbara, USA

Issue’s Table of Contents

Copyright © 2016 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Journal Family

ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 01 December 2016

Accepted: 01 July 2016

Revised: 01 February 2016

Received: 01 September 2015

Published in JETC Volume 13, Issue 2

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Funding Sources

National Science Foundation

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
814
Total Downloads

Downloads (Last 12 months)74
Downloads (Last 6 weeks)16

Reflects downloads up to 17 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

Zahedinejad MAwad AMuralidhar SKhymyn RFulara HMazraati HDvornik MÅkerman J(2019)Two-dimensional mutually synchronized spin Hall nano-oscillator arrays for neuromorphic computingNature Nanotechnology10.1038/s41565-019-0593-9Online publication date: 23-Dec-2019
https://doi.org/10.1038/s41565-019-0593-9
ESKALEN HÖZĞAN Ş(2018)Examining phase response curve of nerve cell by using three different methodsInternational Journal of Chemistry and Technology10.32571/ijct.3384032:1(1-9)Online publication date: 28-Feb-2018
https://doi.org/10.32571/ijct.338403

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

Media

Figures

Other

Tables

View Issue’s Table of Contents