Machine learning using PyTorch on DelftBlue and DAIC
Planned courses
Geen resultaten gevonden.
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.