optimizing noise-immune nanoscale circuits using principles of markov random fields
As CMOS devices and operating voltages are scaled down, noise and defective devices will impact the reliability of digital circuits. Probabilistic computing compatible with CMOS offers a possible solution. In this work, we present a new area and power efficient design methodology for the implementation of a probabilistic framework into CMOS technology based on Markov Random Fields (MRF). Using SPICE, we simulate elementary logic components and sample circuits from the MCNC'91 benchmark set and show the area and power benefits compared to older MRF mapping strategies. We also extend our area and power efficient approach to improving the design of a Hamming decoder based on MRF principles.
markov random fields subthreshold operation noise immunity error correcting codes emerging technologies circuit optimization