no code implementations • 6 Dec 2022 • Kavya Sreedhar, Jason Clemons, Rangharajan Venkatesan, Stephen W. Keckler, Mark Horowitz
We can use dynamic models to adapt the model execution to meet real-time application resource constraints.
no code implementations • 1 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.
3 code implementations • 18 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.
4 code implementations • 25 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.