MIT and University of Washington Workshop on AI Implementations and Applications: ML Architecture, Systems and Programming Environments - Day 2
July 30, 2021 - 9am-3:30pm PDT
Organizers (left to right): Prof. Manya Ghobadi (MIT), Prof. Mohammad Alizadeh (MIT), and Prof. Arvind Krishnamurthy (UW).
Agenda: Videos of Presentations
9:00 am PDT: Welcome – Workshop Organizers
Session 1: Distributed Systems (Chair: Manya Ghobadi)
9:05 - 9:50 (45 mins): Ion Stoica, UC Berkeley, "Ray: A Universal Framework for Distributed Computing"
9:50 - 10:35 (45 mins): Luis Ceze, University of Washington and OctoML, "Improving Model Performance, Portability and Productivity with Apache TVM and the Octomizer"
10:35 - 11:00 (25 mins): Ben Klenk, Nvidia, "Accelerated Computing Needs Accelerated Networks"
11:00 - 11:15 Break (Gather Online)
Session 2: Big Data (Chair: Arvind Krishnamurthy)
11:15 - 12:00 (45 mins): Matei Zaharia, Stanford, "What’s Next in Infrastructure for ML?"
12:00 - 12:45 (45 mins): Vinod Kathail, Xilinx, "Innovative HW and SW Solutions for AI Acceleration"
12:45 - 1:30 Lunch break (Gather Online)
Session 3: Hardware (Chair: Mohammad Alizadeh)
1:30 - 2:15 (45 mins): Darius Bunandar, Lightmatter, "Accelerating Artificial Intelligence with Light"
2:15 - 3:00 (45 mins): Amar Phanishayee, Microsoft, "Project Fiddle: Fast and Efficient Infrastructure for Distributed Deep Learning"
3:00 - 3:30 (30 mins): Derek Chickles, Marvell, "Introduction to the Octeon 10 DPU and Integrated Inferencing"
Abstracts and Bios (alphabetically listed by last name) - Please check back later for updates.
Darius Bunandar, Lightmatter, "Accelerating Artificial Intelligence with Light"
Abstract: Lightmatter is leading the evolution of computing to reduce its impact on our planet, while also enabling the next giant leaps in human progress. By unifying the unique properties of light as an ideal carrier of information with the interoperability of electronics, Lightmatter creates photonic processors and interconnect that are faster, more efficient, and cooler than anything else on earth...
Bio: Darius Bunandar is a Founder of Lightmatter...
Prof. Luis Ceze, University of Washington and OctoML, "Improving Model Performance, Portability and Productivity with Apache TVM and the Octomizer"
Abstract: There is an increasing need to bring machine learning to a diverse set of hardware devices...
Bio: Luis Ceze is a Co-founder and CEO at OctoML...
Derek Chickles, Marvell, "Introduction to the Octeon 10 DPU and Integrated Inferencing"
Abstract: With the shift from application-specific compute to data-centric compute...
Bio: Derek Chickles leads the machine learning software group at Marvell...
Vinod Kathail, Xilinx, "Innovative HW and SW Solutions for AI Acceleration"
Abstract: Over the last ten years or so, Machine Learning (ML) or Artificial Intelligence (AI)...
Bio: Vinod Kathail is a Xilinx Fellow...
Ben Klenk, Nvidia, "Accelerated Computing Needs Accelerated Networks"
Abstract: Artificial Intelligence has become ubiquitous and has proven itself to excel at many tasks...
Bio: Benjamin Klenk is a Sr. Research Scientist in NVIDIA’s Networking Research Group...
Amar Phanishayee, Microsoft, "Project Fiddle: Fast and Efficient Infrastructure for Distributed Deep Learning"
Abstract: The goal of Project Fiddle is to build efficient systems infrastructure for fast distributed DNN training...
Bio: Amar Phanishayee is Sr. Principal Researcher at Microsoft Research in Redmond...
Prof. Ion Stoica, UC Berkeley, "Ray: A Universal Framework for Distributed Computing"
Abstract: Distributed computing is becoming the norm...
Bio: Ion Stoica is a Professor in the EECS Department at the University of California at Berkeley...
Prof. Matei Zaharia, Stanford, "What’s Next in Infrastructure for ML?"
Abstract: Building production ML applications is expensive and difficult because of their computational cost...
Bio: Matei Zaharia is an Assistant Professor of Computer Science at Stanford University...