"Efficient Dot Products (Or, Scaling ML Workloads)" by Erich Plondke (Qualcomm)

Talk given on Nov 11, 2020 for the internal Harvard offering of the Intro to TinyML course.

Erich Plondke has been designing signal processor architectures for almost 20 years. For the last 16 years he has been working at Qualcomm on the Hexagon signal processor architecture. Over 10 billion Hexagon cores have shipped into phones and other devices. For the last several years he has been working on accelerating and improving the efficiency of machine learning workloads. He has a Bachelor’s and a Master’s in Electrical and Computer Engineering from Georgia Tech.

See more: https://sites.google.com/g.harvard.edu/tinyml/home

Видео "Efficient Dot Products (Or, Scaling ML Workloads)" by Erich Plondke (Qualcomm) канала Harvard CS249R: Intro to TinyML