by RLE at MIT | Jul 18, 2017 | RLE Recent Papers
Tien-Ju Yang, Yu-Hsin Chen, Vivienne Sze DOI: arXiv:1611.05128v4 Abstract: Deep convolutional neural networks (CNNs) are indispensable to state-of-the-art computer vision algorithms. However, they are still rarely deployed on battery-powered...
by RLE at MIT | Jul 6, 2017 | RLE Recent Papers
Max M. Shulaker, Gage Hills , Rebecca S. Park , Roger T. Howe , Krishna Saraswat , H.-S. Philip Wong & Subhasish Mitra doi:10.1038/nature22994 Abstract: The computing demands of future data-intensive applications will greatly exceed the capabilities of...
by RLE at MIT | Jun 22, 2017 | RLE Recent Papers
Nicholas C. Harris, Gregory R. Steinbrecher, Mihika Prabhu, Yoav Lahini, Jacob Mower, Darius Bunandar, Changchen Chen, Franco N. C. Wong, Tom Baehr-Jones, Michael Hochberg, Seth Lloyd and Dirk Englund doi:10.1038/nphoton.2017.95 Abstract: Environmental noise and...
by RLE at MIT | Jun 20, 2017 | RLE Recent Papers
Hyeongrak Choi, Mikkel Heuck, and Dirk Englund DOI: 10.1103/PhysRevLett.118.223605 Abstract: We propose a photonic crystal nanocavity design with self-similar electromagnetic boundary conditions, achieving ultrasmall mode volume (Veff). The electric energy...
by RLE at MIT | Jun 20, 2017 | RLE Recent Papers
Yichen Shen, Nicholas C. Harris, Scott Skirlo, Mihika Prabhu , Tom Baehr-Jones, Michael Hochberg, Xin Sun, Shijie Zhao, Hugo Larochelle, Dirk Englund and Marin Soljačić DOI: 10.1038/NPHOTON.2017.93 Abstract: Artificial neural networks are computational network...
by RLE at MIT | Jun 15, 2017 | RLE Recent Papers
Yu-Hsin Chen, Joel Emer, Vivienne Sze DOI: 10.1109/MM.2017.54 Abstract: The authors demonstrate the key role dataflows play in the optimization of energy efficiency for deep neural network (DNN) accelerators. By introducing a systematic approach to...