230 citations · 487 across the 3 of their papers we have counts for
4 papers
SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks
Angshuman Parashar, Minsoo Rhu, Anurag Mukkara +6
Convolutional Neural Networks (CNNs) have emerged as a fundamental technology for machine learning. High performance and extreme energy efficiency are critical for deployments of C…
Exploring the Regularity of Sparse Structure in Convolutional Neural Networks
Huizi Mao, Song Han, Jeff Pool +4
Sparsity helps reduce the computational complexity of deep neural networks by skipping zeros. Taking advantage of sparsity is listed as a high priority in next generation DNN accel…
Deep Generative Adversarial Networks for Compressed Sensing Automates MRI
Morteza Mardani, Enhao Gong, Joseph Y. Cheng +8
Magnetic resonance image (MRI) reconstruction is a severely ill-posed linear inverse task demanding time and resource intensive computations that can substantially trade off {\it a…
CG-OoO: Energy-Efficient Coarse-Grain Out-of-Order Execution
Milad Mohammadi, Tor M. Aamodt, William J. Dally
We introduce the Coarse-Grain Out-of-Order (CG- OoO) general purpose processor designed to achieve close to In-Order processor energy while maintaining Out-of-Order (OoO) performan…