2 citations · 3 across the 7 of their papers we have counts for
5 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…
Leveraging High-Level Synthesis and Large Language Models to Generate, Simulate, and Deploy a Uniform Random Number Generator Hardware Design
James T. Meech
We present a new high-level synthesis methodology for using large language model tools to generate hardware designs. The methodology uses exclusively open-source tools excluding th…
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…
Is This Computing Accelerator Evaluation Full of Hot Air?
James T. Meech
Computing accelerators must significantly improve at least one metric such as: cost, speed, or efficiency for customers to find them useful. They must do this for at least one appl…