Browsing School of Computer Science and Statistics by Author "Garland, James Philip"
Now showing items 1-2 of 2
-
Arbitrary Precision and Low Complexity Micro-Architectural Arithmetic Optimisations of Machine Learning Algorithms for Compute Bound and High-Performance Systems
Garland, James Philip (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Computer Science, 2021)Artificial intelligence is becoming ubiquitous and pervasive in our daily lives. Machine learning (ML), a subset of Artificial intelligence (AI), supplies more accurate internet searches, voice recognition in home appliances, ... -
Low Complexity Multiply-Accumulate Units for Convolutional Neural Networks with Weight-Sharing
Garland, James Philip; Gregg, David (2018)Convolutional neural networks (CNNs) are one of the most successful machine-learning techniques for image, voice, and video processing. CNNs require large amounts of processing capacity and memory bandwidth. Hardware ...