Reduction and IR-drop Compensations Techniques for Reliable Neuromorphic Computing Systems Conference Paper uri icon


  • 2014 IEEE. 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.

name of conference

  • 2014 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)

published proceedings


author list (cited authors)

  • Liu, B., Li, H., Chen, Y., Li, X., Huang, T., Wu, Q., & Barnell, M.

citation count

  • 90

complete list of authors

  • Liu, Beiye||Li, Hai||Chen, Yiran||Li, Xin||Huang, Tingwen||Wu, Qing||Barnell, Mark

publication date

  • November 2014