An Automated Synthesis Tool for Generating Noise-Immune Sub-Threshold Circuits

My project for the summer is to build an automatic synthesis tool for noise-immune sub-threshold circuit design based on selective use of Schmitt-trigger logic. Dr. Bahar's group has been developing a technique for designing noise-immune circuits, and my goal is to automate this technique to dynamically synthesize a circuit that maximizes noise suppression with minimal area overhead by including Schmitt-trigger logic at the most failure-prone nodes in a circuit.

Research Summary: Prior work has demonstrated invariant relationships, or implications, to be an effective means of detecting errors in sub-threshold circuits. We propose strategically replacing gates in a circuit with their modified Schmitt-trigger equivalent so as to reinforce invariant relationships throughout the circuit. Our goal is to effectively place these modified gates so as to supress noise at a circuit's outputs and reduce errors. We weigh different heuristics and strategies for placing implications, including chain-building based on high-activation probability and node distances, reinforcing high-fault nodes, and determining low-fault nodes for use as steady implicants.

Final Deliverables

I presented a poster at the Brown Summer Research Symposium on August 2, 2013. A PDF version of the slides can be found here.

I also wrote a paper for DREU on my summer work. You can read it here.

About Dr. Bahar

My mentor for the summer is Dr. Iris Bahar, a professor in the computer engineering department at Brown. Her research is in the areas of computer architecture, electronic design automation, and digital circuit design.

You can find more about her at her research site.

About Marco

On a day-to-day basis I am being advised by Marco Donato, a Ph. D student at Brown who is actively working on this research.

About the DREU Program

DREU (Distributed Research Experiences for Undergraduates) is a research internship program that promotes research opportunities in computer science for women and students from underrepresented groups. Its goal is to increase the number of students in these categories that go into graduate studies.