Search Results for author: Jason Clemons

Found 4 papers, 2 papers with code

Structurally Sparsified Backward Propagation for Faster Long Short-Term Memory Training

no code implementations1 Jun 2018 Maohua Zhu, Jason Clemons, Jeff Pool, Minsoo Rhu, Stephen W. Keckler, Yuan Xie

Further, we can enforce structured sparsity in the gate gradients to make the LSTM backward pass up to 45% faster than the state-of-the-art dense approach and 168% faster than the state-of-the-art sparsifying method on modern GPUs.

Reinforcement Learning through Asynchronous Advantage Actor-Critic on a GPU

3 code implementations18 Nov 2016 Mohammad Babaeizadeh, Iuri Frosio, Stephen Tyree, Jason Clemons, Jan Kautz

We introduce a hybrid CPU/GPU version of the Asynchronous Advantage Actor-Critic (A3C) algorithm, currently the state-of-the-art method in reinforcement learning for various gaming tasks.

reinforcement-learning Reinforcement Learning (RL) +1

vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design

4 code implementations25 Feb 2016 Minsoo Rhu, Natalia Gimelshein, Jason Clemons, Arslan Zulfiqar, Stephen W. Keckler

The most widely used machine learning frameworks require users to carefully tune their memory usage so that the deep neural network (DNN) fits into the DRAM capacity of a GPU.

BIG-bench Machine Learning Efficient Neural Network

Cannot find the paper you are looking for? You can Submit a new open access paper.