7 citations · 9 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 2 cited
DLAS: An Exploration and Assessment of the Deep Learning Acceleration Stack
Perry Gibson, José Cano, Elliot J. Crowley +2
Deep Neural Networks (DNNs) are extremely computationally demanding, which presents a large barrier to their deployment on resource-constrained devices. Since such devices are wher…
cs.LG2020
Performance Aware Convolutional Neural Network Channel Pruning for Embedded GPUs
Valentin Radu, Kuba Kaszyk, Yuan Wen +6
Convolutional Neural Networks (CNN) are becoming a common presence in many applications and services, due to their superior recognition accuracy. They are increasingly being used o…
stat.ML2018★ 7 cited
Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks
Jack Turner, José Cano, Valentin Radu +3
Convolutional Neural Networks (CNNs) are extremely computationally demanding, presenting a large barrier to their deployment on resource-constrained devices. Since such systems are…