October 18th 2019, IBM T. J. Watson Research Center, NY
In conjunction with the 2019 IBM IEEE CAS/EDS – AI Compute Symposium
The 4th Workshop on the Future of Computing Architectures (FOCA 2019) will be held on Friday October
18th, 2019 at the IBM Thomas J. Watson Research Center in Yorktown Heights, New York. This event is a full-day workshop
that provides a forum for invited students in a broad range of fields covering all aspects of architectures for the
future of computing. Invited students are expected to showcase their work and interact with their peers and members of
the IBM Research community.
The topics covered by FOCA 2019 include but are not limited to:
FOCA 2019 will be held in conjunction with the 2019 IBM IEEE CAS/EDS – AI Compute Symposium. Refer to the main venue to continue with the registration process.
IBM T. J. Watson Research Center
1101 Kitchawan Rd
Yorktown Heights, NY 10598
The AI and Robotics Timeline from 1939 to date.
The IBM Q Experience to try a quantum computer online.
IBM Watson in action in this on-line demo using deep learning.
The AI Portal with the latest IBM research activities.
Virginia Tech
Harvard University
University of Michigan
Georgia Tech
Princeton University
University of Illinois,
Urbana-Champaign
University of California,
Berkeley
Yale University
Friday October 18th, 2019 | |
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8:30 - 8:50am | Breakfast |
8:50 - 9:00am | Introduction and Welcoming Remarks |
9:00 - 10:00am | Keynote: "Distributed AI for Intelligence at Edge" Dinesh Verma (IBM Fellow, Distributed AI) |
10:00 - 10:30am | "Experiences in Scaling TensorFlow/Horovod to the Full Scale of Summit" Sarunya Pumma (Virginia Tech) |
10:30 - 11:00am | "MaxNVM: Maximizing DNN Storage Density and Inference Efficiency with Sparse Encoding and Error Mitigation" Lillian Pentecost (Harvard University) |
11:00 - 11:15am | Coffee Break |
11:15 - 11:45am | "Rethinking Computer Architecture to Enable Low-Cost Security" Gururaj Saileshwar (Georgia Tech) |
11:45am - 1:00pm | Lunch |
1:00 - 2:00pm | Quantum Lab Tour & Break |
2:00 - 2:30pm | "Hitting an Accelerator Wall: When Specialized Chips Meet the End of Moore's Law" Adi Fuchs (Princeton University) |
2:30 - 3:00pm | "Democratizing Error-Efficient Computing via Principled Application Error Analysis" Radha Venkatagiri (University of Illinois, Urbana-Champaign) |
3:00 - 3:30pm | Coffee Break |
3:30 - 4:00pm | "Keystone: A Framework for Architecting TEEs" Dayeol Lee (University of California, Berkeley) |
4:00 - 4:30pm | "Post-Quantum Secure Digital Signatures on Embedded Systems" Wen Wang (Yale University) |
4:30 - 5:30pm | Panel: "The «Golden» Age for Computer Architecture: Challenges and Pitfalls" Moderator: Dr. Pradip Bose (IBM Distinguished Research Staff Member and Manager) Panelists: • Dr. Guerney Hunt • Dr. Hubertus Franke • Dr. Jaime Moreno • Dr. Kaoutar El Maghraoui • Dr. Valentina Salapura |
5:30pm | Concluding Remarks |
Augusto Vega is a Research Staff Member at IBM T. J. Watson Research Center involved in research and development work in the areas of highly-reliable power-efficient embedded designs, cognitive systems and mobile computing. He holds M.S. and Ph.D. degrees from Polytechnic University of Catalonia (UPC), Spain.
Michael Healy is a Research Staff Member at IBM T. J. Watson Research Center. His research interests cover a wide range of topics from low-level processor design to high-level system architecture. Michael's current work focuses on the memory subsystem. He also explores the use of 3D stacked memories such as High Bandwidth Memory (HBM) and the Hybrid Memory Cube (HMC). He graduated from the Georgia Institute of Technology with B.S., M.S., and Ph.D. degrees in Computer Engineering.
Karthik Swaminathan is a Research Staff Member at IBM T. J. Watson Research Center. His research interests include power-aware architectures, domain-specific accelerators and emerging device technologies in processor design. He is also interested in architectures for approximate and cognitive computing, particularly in aspects related to their reliability and energy efficiency. He holds a Ph.D. degree from Penn State University.
Xinyu Que is a Research Staff Member in the Data Centric Systems Co-Design department at the T. J. Watson Research Center. He received his M.S. degree in Computer Science and Engineering from University of Connecticut and Ph.D. degrees in Computational Science and Software Engineering from Auburn University. Xinyu has broad interests in high performance computing and large-scale graph analytics.