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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 ยท 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.

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