University of Minnesota M.S.E.E. thesis. December 2017. Major: Electrical/Computer Engineering. Advisor: kia Bazargan. 1 computer file (PDF); vi, 35 pages.Stochastic Computing is a digital computation approach that operates on random bit streams to perform complex tasks with much smaller hardware footprints compared to conventional binary radix approaches. SC works based on the assumption that input bit streams are independent random sequences of 1’s and 0’s. In this dissertation, both serial and parallel configuration of SC are presented in a class of complex dynamic system
A design based on parallel processing is laid out for solving (multistage) stochastic programs. Beca...
Stochastic programming provides an effective framework for addressing decision prob-lems under uncer...
The Nagel-Schreckenberg model is a stochastic one-dimensional traffic model. In this assignment, we ...
Stochastic computing (SC) is an unconventional technique that has recently re-emerged as an attracti...
This thesis is comprised of two papers, where the first paper presents a novel approach for parallel...
this report we shall present the fundamentals of random number generation on parallel processors. We...
Thesis (Ph.D.)--University of Washington, 2019The end of Dennard scaling and demands for energy effi...
University of Minnesota Ph.D. dissertation.July 2018. Major: Electrical/Computer Engineering. Advis...
Stochastic iterative decoding is a novel method to decode the bits received at the end of a communic...
The reproducibility of numerical experiments on high performance computing systems is sometimes over...
International audienceThere is an increasing interest in the distribution of parallel random number ...
This short paper introduces the basic concepts of Stochastic Computing (SC), and presents additions...
International audienceIn recent years, shrinking size in integrated circuits has imposed a big chall...
Stochastic computing (SC) was proposed in the 1960s as a low-cost alternative to conventional binary...
International audienceIn this paper, we present some investigations on the parallelization of stocha...
A design based on parallel processing is laid out for solving (multistage) stochastic programs. Beca...
Stochastic programming provides an effective framework for addressing decision prob-lems under uncer...
The Nagel-Schreckenberg model is a stochastic one-dimensional traffic model. In this assignment, we ...
Stochastic computing (SC) is an unconventional technique that has recently re-emerged as an attracti...
This thesis is comprised of two papers, where the first paper presents a novel approach for parallel...
this report we shall present the fundamentals of random number generation on parallel processors. We...
Thesis (Ph.D.)--University of Washington, 2019The end of Dennard scaling and demands for energy effi...
University of Minnesota Ph.D. dissertation.July 2018. Major: Electrical/Computer Engineering. Advis...
Stochastic iterative decoding is a novel method to decode the bits received at the end of a communic...
The reproducibility of numerical experiments on high performance computing systems is sometimes over...
International audienceThere is an increasing interest in the distribution of parallel random number ...
This short paper introduces the basic concepts of Stochastic Computing (SC), and presents additions...
International audienceIn recent years, shrinking size in integrated circuits has imposed a big chall...
Stochastic computing (SC) was proposed in the 1960s as a low-cost alternative to conventional binary...
International audienceIn this paper, we present some investigations on the parallelization of stocha...
A design based on parallel processing is laid out for solving (multistage) stochastic programs. Beca...
Stochastic programming provides an effective framework for addressing decision prob-lems under uncer...
The Nagel-Schreckenberg model is a stochastic one-dimensional traffic model. In this assignment, we ...