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Reduction and IR-drop compensations techniques for reliable neuromorphic computing systems

Publication ,  Conference
Liu, B; Li, H; Chen, Y; Li, X; Huang, T; Wu, Q; Barnell, M
Published in: IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
January 5, 2015

Neuromorphic computing system (NCS) is a promising architecture to combat the well-known memory bottleneck in Von Neumann architecture. The recent breakthrough on memristor devices made an important step toward realizing a low-power, small-footprint NCS on-A-chip. However, the currently low manufacturing reliability of nano-devices and the voltage IR-drop along metal wires and memristors arrays severely limits the scale of me-mristor crossbar based NCS and hinders the design scalability. In this work, we propose a novel system reduction scheme that significantly lowers the required dimension of the memristor crossbars in NCS while maintaining high computing accuracy. An IR-drop compensation technique is also proposed to overcome the adverse impacts of the wire resistance and the sneak-path problem in large memristor crossbar designs. Our simulation results show that the proposed techniques can improve computing accuracy by 27.0% and 38.7% less circuit area compared to the original NCS design.

Duke Scholars

Published In

IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD

DOI

ISSN

1092-3152

ISBN

9781479962785

Publication Date

January 5, 2015

Volume

2015-January

Issue

January

Start / End Page

63 / 70
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Liu, B., Li, H., Chen, Y., Li, X., Huang, T., Wu, Q., & Barnell, M. (2015). Reduction and IR-drop compensations techniques for reliable neuromorphic computing systems. In IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD (Vol. 2015-January, pp. 63–70). https://doi.org/10.1109/ICCAD.2014.7001330
Liu, B., H. Li, Y. Chen, X. Li, T. Huang, Q. Wu, and M. Barnell. “Reduction and IR-drop compensations techniques for reliable neuromorphic computing systems.” In IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD, 2015-January:63–70, 2015. https://doi.org/10.1109/ICCAD.2014.7001330.
Liu B, Li H, Chen Y, Li X, Huang T, Wu Q, et al. Reduction and IR-drop compensations techniques for reliable neuromorphic computing systems. In: IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD. 2015. p. 63–70.
Liu, B., et al. “Reduction and IR-drop compensations techniques for reliable neuromorphic computing systems.” IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD, vol. 2015-January, no. January, 2015, pp. 63–70. Scopus, doi:10.1109/ICCAD.2014.7001330.
Liu B, Li H, Chen Y, Li X, Huang T, Wu Q, Barnell M. Reduction and IR-drop compensations techniques for reliable neuromorphic computing systems. IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD. 2015. p. 63–70.

Published In

IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD

DOI

ISSN

1092-3152

ISBN

9781479962785

Publication Date

January 5, 2015

Volume

2015-January

Issue

January

Start / End Page

63 / 70