Thu, Mar 30, 2023

3:30 PM – 5 PM EDT (GMT-4)

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PyTorch's top priorities have always been flexibility and hackability, while continuing to deliver good performance. PyTorch 2.0 introduces new compiler technologies that improves PyTorch's performance, while maintaining the eager-mode development and user experience you know and love. In this workshop I’ll introduce new PyTorch 2.0 provide an overview of the technology stack that powers the new torch.compile() API: TorchDynamo, AITAutograd, PrimTorch and TorchInductor. The new compiler stack reduces training times across a wide range of workloads while being fully backwards compatible. Bring your laptops, or connect to remote GPU powered systems to run the examples.

Workshop format: presentation and hands-on

Target audience: This talk is intended for a those looking to start using PyTorch and experienced PyTorch users.

Knowledge prerequisites: Some experience with Python would be beneficial

Hardware/software prerequisites: TBD

Learning objectives: Attendees will leave with an understanding of how to take full advantage of PyTorch 2.0.


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Shashank Prasanna


Shashank Prasanna is an PyTorch Developer Advocate at Meta. His technical expertise includes machine learning algorithms, specialized AI hardware for machine learning and cloud technologies for ML infrastructure. Prior to joining Meta, he worked at AWS, NVIDIA, and MathWorks (makers of MATLAB) in product and software development roles.

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Co-hosted with: GradFUTURES, The Graduate School

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