2 citations · 3 across the 7 of their papers we have counts for
10 papers
Theoretical Analysis of Thermodynamic Matrix Inversion: First-order Equivalence to Preconditioned Gradient Descent and Implications for Analog Computing
Gerhard Kirsten, Michael Selby, Janith Petangoda +3
Recent research has demonstrated the possibility of exploiting the thermodynamics of coupled electrical oscillators to implement computational tasks such as matrix inversion. While…
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…
Machine Learning for Sensor Transducer Conversion Routines
Thomas Newton, James T. Meech, Phillip Stanley-Marbell
Sensors with digital outputs require software conversion routines to transform the unitless analogue-to-digital converter samples to physical quantities with correct units. These c…
An Algorithm for Sensor Data Uncertainty Quantification
James T. Meech, Phillip Stanley-Marbell
This article presents an algorithm for reducing measurement uncertainty of one physical quantity when given oversampled measurements of two physical quantities with correlated nois…
A System for Generating Non-Uniform Random Variates using Graphene Field-Effect Transistors
Nathaniel Joseph Tye, James Timothy Meech, Bilgesu Arif Bilgin +1
We introduce a new method for hardware non-uniform random number generation based on the transfer characteristics of graphene field-effect transistors (GFETs) which requires as few…
Efficient Programmable Random Variate Generation Accelerator from Sensor Noise
James Timothy Meech, Phillip Stanley-Marbell
We introduce a method for non-uniform random number generation based on sampling a physical process in a controlled environment. We demonstrate one proof-of-concept implementation…