Machine learning using PyTorch on DelftBlue and DAIC
Planned courses
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This course teaches you how to scale up your machine learning workflows to large amounts of data on a supercomputer.
At the end of the day, you should be able to
- Understand the basic setup of a supercomputer and the possible bottlenecks in Machine Learning applications;
- Run PyTorch examples on CPUs and GPUs on DelftBlue and/or DAIC;
- Assess performance on different hardware and make realistic estimates of resource requirements (RAM, CPU/GPU time, data movement);
- Optimize your workflows to make good use of computational resources;
- Reproduce the steps needed for distributed training on a cluster.
One day course
30 max. participants
Teachers:
A. Ahmed
S. Wacker
Costs:
€100,-
€25,- for BSc and MSc students.
including lunch and course materials, free for DCSE members.
Location:
Penguinlab, EWI B36.HB.2.130
Prerequisites:
Command line and DelftBlue basics
Python
Basic knowledge of ML algorithms
Note:
This course is organized in the computer lab of the Mathematics department. You will log in to a prepared environment that contains all files needed for the in-class exercises.