PyTorch is one of the most popular deep learning frameworks in use today. In this course, we will learn how to get the most out of our PyTorch code when using HPC resources. Topics covered include profiling and debugging PyTorch code, different types of parallelism in PyTorch, and hyper-parameter tuning using HPC resources.
Live online classes will take place on Tues. Feb. 4, Fri. Feb. 7, and Tues. Feb. 11 from 1 P.M. to 2 P.M. Eastern Time. Recordings of live classes will be available afterwards in this course for self-paced learning and review.
- Teacher: Collin Wilson
Access is restricted to Digital Research Alliance of Canada (formerly Compute Canada) authenticated users only: Yes