Python is increasingly used in high-performance computing projects. It can be used as a high-level interface to existing HPC applications and libraries, as an embedded interpreter, or as main language for writing new software.
In this course we will show how Python can be used in parallel architectures and how to optimize critical parts of code using various tools. The course combines lectures and hands-on sessions.
The main topics that the course will cover are:
- Running Numpy-like code on CPUs and GPUs
- Compiled Python
- Scaling Python workloads to multiple nodes
The agenda will be shared shortly before the start of the course.
This course addresses scientists with a working knowledge of NumPy who wish to explore the productivity gains made possible by Python for HPC.
The lessons on the first day will start at 9:30. In general the course will be held from 9:00 to 12:00 and from 13:00 to 17:00. Both, morning and afternoon sessions, will have a 15-minutes break.
Dr. Rafael Sarmiento (Computational Scientist, CSCS)
Dr. Theofilos Manitaras (Computational Scientist, CSCS)
Participation Fee and Registration
All participants must register for the course. The registration fee includes lunch and coffee breaks.
Course Fee: 240 CHF
Deadline for registration: Monday, June 12, 2023.
Kindly note that the course can take place only if there are sufficient confirmed registrations received by the deadline. The minimum number of participants is eight. Registration for the course will automatically close when we reach the maximum number of participants (30).
Inquiries may be addressed to email@example.com.