Скачать или смотреть Efficient Computing for AI and Robotics

In this talk, we will describe how the joint algorithm and hardware design can be used to reduce energy consumption while delivering real-time and robust performance for applications including deep learning, computer vision, autonomous navigation/exploration, and video/image processing.

This talk has a greater emphasis on our AI work compared to "Efficient Computing for Robotics and AI" which focuses more on our robotics work.    • Efficient Computing for Robotics and AI  

Slides: http://www.rle.mit.edu/eems/wp-conten...

Works highlighted in this talk include
A. Suleiman, Z. Zhang, L. Carlone, S. Karaman, V. Sze, “Navion: A 2mW Fully Integrated Real-Time Visual-Inertial Odometry Accelerator for Autonomous Navigation of Nano Drones,” IEEE Journal of Solid-State Circuits (JSSC), VLSI Symposia Special Issue, Vol. 54, No. 4, pp. 1106-1119, April 2019. [Project website http://navion.mit.edu]

Y.-H. Chen, T. Krishna, J. Emer, V. Sze, “Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks,” IEEE Journal of Solid-State Circuits (JSSC), ISSCC Special Issue, Vol. 52, No. 1, pp. 127-138, January 2017. [Project website http://eyeriss.mit.edu]

A. Suleiman*, Y.-H. Chen*, J. Emer, V. Sze, “Towards Closing the Energy Gap Between HOG and CNN Features for Embedded Vision,” IEEE International Symposium of Circuits and Systems (ISCAS), Invited Paper, May 2017. http://www.rle.mit.edu/eems/wp-conten...

T.-J. Yang, Y.-H. Chen, V. Sze, “Designing Energy-Efficient Convolutional Neural Networks using Energy-Aware Pruning,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017. http://eyeriss.mit.edu/energy.html

T.-J. Yang, A. Howard, B. Chen, X. Zhang, A. Go, M. Sandler, V. Sze, H. Adam, “NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications,” European Conference on Computer Vision (ECCV), September 2018. https://arxiv.org/abs/1804.03230

*D. Wofk*, F. Ma*, T.-J. Yang, S. Karaman, V. Sze, “FastDepth: Fast Monocular Depth Estimation on Embedded Systems,” IEEE International Conference on Robotics and Automation (ICRA), May 2019. http://fastdepth.mit.edu/

*Y.-H. Chen, T.-J Yang, J. Emer, V. Sze, “Eyeriss v2: A Flexible Accelerator for Emerging Deep Neural Networks on Mobile Devices,” to appear in IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS), June 2019. https://arxiv.org/abs/1807.07928

P. Z. X. Li*, Z. Zhang*, S. Karaman, V. Sze, “High-throughput Computation of Shannon Mutual Information on Chip,” Robotics: Science and Systems (RSS), June 2019. http://www.rle.mit.edu/eems/wp-conten...