Moderator: XUEMENG ZHANG, NVIDIA, Australia
Xuemeng (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.

Lecturer(s): XUEMENG ZHANG, NVIDIA, Australia
Xuemeng (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.

Description: We will 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. We will also examine features and tips and tricks to optimize your workloads right from data loading, processing using Data Loading Library (DALI), to automatic mixed precision training.