Parallel programming and GPU programming in Python
In this training basic concepts of programming in Python and general parallel programming are introduced. You will also work in an interactive way with important theory about graphics processing unit (GPU) computing.
Python for scientific computing use
This training is organized in collaboration with PRACE: partner in advanced computing. The Python programming language has become increasingly popular among researchers because of the simplicity and availability of specific programming libraries, while the correct exploitation of heterogeneous architectures poses challenges for the development of parallel applications. To bring these two subjects together, this course focuses on the use of Python on CPU and GPU platforms for scientific computing in general.
The basic concepts of good programming in Python and general parallel programming are introduced. You will then hear more about essential theoretical concepts of GPU computing in hands-on sessions. For the exercises you make use of supercomputing facilities from SURFsara using Python with different programming libraries:
Bring your own laptop with an SSH client for the hands-on sessions. The most important requirements for following the course are some familiarity with bash assignments and Python programming language.