Search Results for author: Ojas Parekh

Found 3 papers, 0 papers with code

Neuromorphic scaling advantages for energy-efficient random walk computation

no code implementations27 Jul 2021 J. Darby Smith, Aaron J. Hill, Leah E. Reeder, Brian C. Franke, Richard B. Lehoucq, Ojas Parekh, William Severa, James B. Aimone

Computing stands to be radically improved by neuromorphic computing (NMC) approaches inspired by the brain's incredible efficiency and capabilities.

Constant-Depth and Subcubic-Size Threshold Circuits for Matrix Multiplication

no code implementations25 Jun 2020 Ojas Parekh, Cynthia A. Phillips, Conrad D. James, James B. Aimone

Boolean circuits of McCulloch-Pitts threshold gates are a classic model of neural computation studied heavily in the late 20th century as a model of general computation.

Spiking Neural Algorithms for Markov Process Random Walk

no code implementations1 May 2018 William Severa, Rich Lehoucq, Ojas Parekh, James B. Aimone

The random walk is a fundamental stochastic process that underlies many numerical tasks in scientific computing applications.

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