Introduction to Scientific and High Performance Computing

These lecture notes are a complement to the class and hopefully a good resource for the students.

Google Collab

Complementary presentations

Introduction to scientific computing and programming tools

• 1. Introduction
• 2. Computer Architecture
• 3. Errors in Floating Point Numbers
• 4. Makefiles as automation tools
• 5. Standard library of functions: math functions, containers and random numbers
• 6. Using software in a hpc environment
• 7. Debugging
• 8. Unit Testing : Making sure your bugs don’t come back

High Performance Computing and Parallel Programming

• 9. Optimization
• 10. Profiling
• 11. Numerical libraries in Matrix Problems
• 12. Performance measurement for some matrix ops
• 13. Introduction to High Performance Computing
• 14. Introduction to OpenMp (Shared memory)
• 15. HPC resource manager: Slurm
• 16. Introduction to MPI (distributed memory)
• 17. Ref
• 18. Some extra tools for development