Designing analog integrated circuits is more of an art than a science. Their continuous nature makes them difficult to both verify to be correct before fabrication as well as difficult to test to be free of faults after fabrication. This fact leads to design errors forcing costly re-spins (repetitions of the design and fabrication process) and even worse faulty parts being shipped to customers. In an attempt to address this problem, engineers are exploring the use of digitally-intensive analog circuits. In these circuits, designers use the simpler 0-1 binary digital assumption for the majority of the implementation, and they only use analog components when absolutely essentially. While this has some advantages, it creates new challenges as traditional verification and test methodologies for digital and analog design are extremely different. The project is attempting to address these challenges. In particular, the project is exploring the integration of both design-time verification as well as new built-in self-test and tuning techniques. This integration will allow not only joint enhancement of design correctness and robustness, hence a holistic guarantee of design quality, but also verification of self healing analog systems with built-in digitally-assisted test and tuning.

The broader impact of this work is that it will enable the design of nanoscale robust computing systems vital to a wide range of applications. Also, interdisciplinary explorations will provide new opportunities for solving research problems of practical significance and offer educational opportunities to make students well grounded in both theory and application. The PIs will promote the research participation from undergraduate students and students from underrepresented groups. The research outcomes of this work will be integrated into undergraduate and graduate curriculum and widely disseminated in the research community. The developed software computer-aided design tools will be released in the public domain.

Project Start
Project End
Budget Start
2011-08-01
Budget End
2015-07-31
Support Year
Fiscal Year
2011
Total Cost
$225,000
Indirect Cost
Name
Texas A&M Engineering Experiment Station
Department
Type
DUNS #
City
College Station
State
TX
Country
United States
Zip Code
77845