In this course, you will learn about parallel programming with Python, a language that is becoming increasingly popular among researchers because of its simplicity and the availability of dedicated programming libraries. In large computing systems, it is essential to properly exploit heterogeneous architectures, and here you will understand the different challenges and how to overcome them with different Python functions for CPU and GPU platforms that are directly applicable to scientific computing.
In this course, you will
Anyone interested in learning how to achieve high performance with Python codes.
You must have:
Day 2 (GPU):
10:00 to 10:15: Welcome and introduction to the course
10:15 to 10:30: Coffee break
10:45 to 12:00: Introduction to PyCUDA
12:00 to 13:00: Lunch
13:00 to 15:00: Hands-on: PyCUDA examples