2 citations · 5 across the 6 of their papers we have counts for
4 papers · 1 filter
The Monte Carlo Method and New Device and Architectural Techniques for Accelerating It
Janith Petangoda, Chatura Samarakoon, James Meech +5
Computing systems interacting with real-world processes must safely and reliably process uncertain data. The Monte Carlo method is a popular approach for computing with such uncert…
Electron-Tunnelling-Noise Programmable Random Variate Accelerator for Monte Carlo Sampling
James T. Meech, Vasileios Tsoutsouras, Phillip Stanley-Marbell
This article presents an electron tunneling noise programmable random variate accelerator for accelerating the sampling stage of Monte Carlo simulations. We used the LiteX framewor…
The Data Conversion Bottleneck in Analog Computing Accelerators
James T. Meech, Vasileios Tsoutsouras, Phillip Stanley-Marbell
Most modern computing tasks have digital electronic input and output data. Due to these constraints imposed by real-world use cases of computer systems, any analog computing accele…
Synthesizing Compact Hardware for Accelerating Inference from Physical Signals in Sensors
Vasileios Tsoutsouras, Max Vigdorchik, Phillip Stanley-Marbell
We present dimensional circuit synthesis, a new method for generating digital logic circuits that improve the efficiency of training and inference of machine learning models from s…