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Mar 4

Software-Hardware Codesign for Machine Learning Workloads, a Workshop at MLSyS 2020

SEI Speaking Workshop
Software-Hardware Codesign for Machine Learning Workloads, a Workshop at MLSyS 2020
Mar 4, 2020 · Austin, TX

Summary

Bridging the Gap Between Software and Hardware

More Information

https://resources.sei.cmu.edu/news-events/events/MLSyS-2020-workshop/index.cfm

Agenda

Machine learning development workflows today involve the siloed design and optimization of task-specific software for a limited number of fixed hardware options. As a result, hardware and software are seen as individual components where the impact of either SW or HW on each other cannot be optimized or assessed jointly. This abstraction leads to computationally inefficient machine learning workloads.

Presenters

Dr. Christopher Aberger - Director, Software Engineering - SambaNova Systems

Dr. Dennis Abts - Chief Architect - Groq

Professor Luca Carloni - Columbia University

Mayank Daga - Director, Deep Learning Software - AMD

Matt Fyles - VP Software - Graphcore

Professor Tze Meng Low - Carnegie Mellon University

James Moawad - Technical Solution Specialist - Intel

Nick Ni - Director of Product Marketing, AI and Software - Xilinx

Dr. Thomas Rondeau - Program Manager - DARPA

Dr. Kshitij Sudan - Principle Solutions Architect - Arm

Professor Michael Taylor - University of Washington

Dr. Natalia Vassilieva - Technical Product Manager - Cerebras Systems

Dr. Jeffrey Vetter - Future Technologies Group Leader - Oak Ridge National Laboratory

 

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