Workshop on Energy Efficient Machine Learning and Cognitive Computing
announcement Important Announcements
Call for Proposal announced for EMC2 6th Edition: To make the EMC2 Workshop more accessible to the community, we are transitioning to a virtual format this year. 6th Edition will be an independent virtual online event on December 5, 2020. For further details and logistics, please look out our Call for Proposal and keep checking our website
EMC2 Model Compression Challenge: We are pleased to announce the first EMC2 Model Compression Challenge (EMCC) which aims to identify the best ideas and approaches for deep learning model compression. Check this page for more details.
memory Upcoming Workshops
- 6th Edition on December 05, 2020 in Online (from San Jose, California) EMC2 Online Workshop 2020 Accepting Submissions!
schedule Program for EMC2 at EMC2 Online Workshop 2020
description Workshop Objective
As artificial intelligence and other forms of cognitive computing continue to proliferate into new domains, many forums for dialogue and knowledge sharing have emerged. In the proposed workshop, the primary focus is on the exploration of energy efficient techniques and architectures for cognitive computing and machine learning, particularly for applications and systems running at the edge. For such resource constrained environments, performance alone is never sufficient, requiring system designers to carefully balance performance with power, energy, and area (overall PPA metric).
The goal of this workshop is to provide a forum for researchers who are exploring novel ideas in the field of energy efficient machine learning and artificial intelligence for a variety of applications. We also hope to provide a solid platform for forging relationships and exchange of ideas between the industry and the academic world through discussions and active collaborations.
format_list_bulleted Topics for the Workshop
- Architectures for the edge: IoT, automotive, and mobile
- Approximation, quantization reduced precision computing
- Hardware/software techniques for sparsity
- Neural network architectures for resource constrained devices
- Neural network pruning, tuning and and automatic architecture search
- Novel memory architectures for machine learing
- Communication/computation scheduling for better performance and energy
- Load balancing and efficient task distribution techniques
- Exploring the interplay between precision, performance, power and energy
- Exploration of new and efficient applications for machine learning
- Characterization of machine learning benchmarks and workloads
- Performance profiling and synthesis of workloads
- Simulation and emulation techniques, frameworks and platforms for machine learning
- Power, performance and area (PPA) based comparison of neural networks
- Verification, validation and determinism in neural networks
- Efficient on-device learning techniques
- Security, safety and privacy challenges and building secure AI systems
Recent Editions
- 5th Edition co-located with NeurIPS 2019 in Vancouver BC, Canada December 13, 2019
- 4th Edition co-located with ISCA 2019 in Phoenix, AZ June 23, 2019
- 3rd Edition co-located with CVPR 2019 in Long Beach, CA June 16, 2019
- 2nd Edition co-located with HPCA 2019 in Washington D.C. February 17, 2019
- 1st Edition co-located with ASPLOS 2018 in Williamsburg, VA March 25, 2018