Measurement Uncertainty

The Physical Computation Laboratory investigates hardware structures for efficiently quantifying uncertainty in sensors as well as hardware architectures for tracking uncertainty throughout computations.

A System for Generating Non-Uniform Random Variates Using Graphene Field-Effect Transistors

N. J. Tye, J. T. Meech, B. A. Bilgin, and P. Stanley-Marbell, 31st IEEE International Conference on Application-specific Systems, Architectures and Processors, July 2020.      
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A System for Generating Non-Uniform Random Variates Using Graphene Field-Effect Transistors
Exploiting Errors for Efficiency: A Survey from Circuits to Algorithms

P. Stanley-Marbell, A. Alaghi, M. Carbin, E. Darulova, L. Dolecek, A. Gerstlauer, G. Gillani, D. Jevdjic, T. Moreau, M. Cacciotti, A. Daglis, N. Enright Jerger, B. Falsafi, A. Misailovic, A. Sampson, and D. Zufferey, ACM Computing Surveys, 2020.      
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Exploiting Errors for Efficiency: A Survey from Circuits to Algorithms
Error-Efficient Computing Systems

Phillip Stanley-Marbell and Martin Rinard, Foundations and Trends in Electronic Design Automation, 2017. ISBN: 9978-1680833584. Paperback: 114 pages. Publisher: NOW Publishers.       
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Error-Efficient Computing Systems
Encoder logic for reducing serial I/O power in sensors and sensor hubs

Phillip Stanley-Marbell, Pier Andrea Francese, and Martin Rinard, IEEE Hot Chips 28 Symposium 2016 Poster.      
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Encoder logic for reducing serial I/O power in sensors and sensor hubs