Description:

In this workshop, we discuss how to use Quest GPU resources effectively. First, we show how to use virtual environments and containers to ensure you have all the GPU-enabled software you need for your application. Second, we discuss how to request GPU resources on Quest. This includes how to determine how much GPU memory you need and the type of GPU resource you should request. Finally, we demonstrate running a number of applications including training neural networks with PyTorch and Tensorflow as well as running molecular dynamics simulations.

Prerequisites: Before attending this workshop, researchers new to Quest should:   

• Apply for a Quest allocation. We recommend “Research Allocation I” if you are new to Quest. If your lab has a joint Quest allocation, you can also apply to join that allocation. 

•Watch the Introduction To Quest video series to get an overview of the system, learn how to submit jobs, and become familiar with best practices. To learn more about Quest, see  About Quest. 

• Become familiar with Unix command line: see our Intro Command Line and Bash Scripting workshops and check Online Resource Guide for learning basic command line skills. 

The Topics in Research Computing Series includes a variety of workshops covering introductory topics like how to use the Quest cluster computer and submit array jobs, as well as more advanced computing topics such as profiling code on the cluster and running parallel R and Python code. The specific workshops offered may vary each quarter, so please check back for updates each quarter.