Programming basics for HPC

In order to prepare yourself for the use of HPC enabled tools, you have to be familiar with basic programming skills. Therefore a bundle of the most needed programming skills is here to help you.

Description:

Parallel programming describes the breaking down of a larger problem into smaller steps. Instructions are delivered to multiple processors, which will execute necessary calculations in parallel – hence the name.

Skills to be gained:

• Knowing how to set up and run data analysis in parallel on an HPC cluster with R and Python
• Write parallel programs using MPI, OpenMP and CUDA
• Parallelize serial programs by means of MPI, OpenMP and CUDA
• Combine MPI with OpenMP or MPI with CUDA
• Understand the discretization of a problem in order to transfer from real-life case to a numerical one
• Parallelization of Machine and Deep Learning tasks to use multiple compute nodes and/or multiple accelerators (GPUs)

Public available material:

• Python crash course with numpy and scipy;
• Concurrency in Python;
• MPI basics;
• MPI intermediate;
• HPC parallelization methods with emphasis on MPI;
• OpenMP;
• Introduction to R;
• Parallelization in R;
• GPU Programming – CUDA;