activity
20132022
most citedThread Parallelism for Highly Irregular Computation in Anisotropic Mesh Adaptation

7 citations · 26 across the 10 of their papers we have counts for

collaborators

16 papers

cs.RO20221 cited

Systematic Comparison of Path Planning Algorithms using PathBench

Hao-Ya Hsueh, Alexandru-Iosif Toma, Hussein Ali Jaafar +4

Path planning is an essential component of mobile robotics. Classical path planning algorithms, such as wavefront and rapidly-exploring random tree (RRT) are used heavily in autono…

cs.AR20213 cited

Extending the RISC-V ISA for exploring advanced reconfigurable SIMD instructions

Philippos Papaphilippou, Paul H. J. Kelly, Wayne Luk

This paper presents a novel, non-standard set of vector instruction types for exploring custom SIMD instructions in a softcore. The new types allow simultaneous access to a relativ…

cs.RO2021

PathBench: A Benchmarking Platform for Classical and Learned Path Planning Algorithms

Alexandru-Iosif Toma, Hao-Ya Hsueh, Hussein Ali Jaafar +3

Path planning is a key component in mobile robotics. A wide range of path planning algorithms exist, but few attempts have been made to benchmark the algorithms holistically or uni…

cs.AR2021

Cain: Automatic Code Generation for Simultaneous Convolutional Kernels on Focal-plane Sensor-processors

Edward Stow, Riku Murai, Sajad Saeedi +1

Focal-plane Sensor-processors (FPSPs) are a camera technology that enable low power, high frame rate computation, making them suitable for edge computation. Unfortunately, these de…

cs.DC2020

Temporal blocking of finite-difference stencil operators with sparse "off-the-grid" sources

George Bisbas, Fabio Luporini, Mathias Louboutin +3

Stencil kernels dominate a range of scientific applications, including seismic and medical imaging, image processing, and neural networks. Temporal blocking is a performance optimi…

eess.SP20203 cited

AnalogNet: Convolutional Neural Network Inference on Analog Focal Plane Sensor Processors

Matthew Z. Wong, Benoit Guillard, Riku Murai +2

We present a high-speed, energy-efficient Convolutional Neural Network (CNN) architecture utilising the capabilities of a unique class of devices known as analog Focal Plane Sensor…