October 28–31, 2019
Maggie Zhang

Maggie Zhang
Deep learning software engineer, NVIDIA

Website

Maggie Zhang is a deep learning software engineer at NVIDIA, where she works on deep learning frameworks. She earned her PhD in computer science and engineering from the University of New South Wales in Australia. Her research background includes GPU and CPU heterogeneous computing, compiler optimization, computer architecture, and deep learning.

Sessions

1:30pm5:00pm Tuesday, October 29, 2019
Location: Grand Ballroom E
Maggie Zhang (NVIDIA), Nathan Luehr (NVIDIA), Josh Romero (NVIDIA), Pooya Davoodi (NVIDIA), Davide Onofrio (NVIDIA)
Average rating: ****.
(4.00, 1 rating)
Maggie Zhang, Nathan Luehr, Josh Romero, Pooya Davoodi, and Davide Onofrio give you a sneak peek at software components from NVIDIA’s software stack so you can get the best out of your end-to-end AI applications on modern NVIDIA GPUs. They also examine features and tips and tricks to optimize your workloads right from data loading, processing, training, inference, and deployment. Read more.

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