1 citations · 1 across the 2 of their papers we have counts for
3 papers
Training for temporal sparsity in deep neural networks, application in video processing
Amirreza Yousefzadeh, Manolis Sifalakis
Activation sparsity improves compute efficiency and resource utilization in sparsity-aware neural network accelerators. As the predominant operation in DNNs is multiply-accumulate…
Linear-Complexity Relaxed Word Mover's Distance with GPU Acceleration
Kubilay Atasu, Thomas Parnell, Celestine Dünner +6
The amount of unstructured text-based data is growing every day. Querying, clustering, and classifying this big data requires similarity computations across large sets of documents…
Large-Scale Stochastic Learning using GPUs
Thomas Parnell, Celestine Dünner, Kubilay Atasu +2
In this work we propose an accelerated stochastic learning system for very large-scale applications. Acceleration is achieved by mapping the training algorithm onto massively paral…