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This module will address the rapid increase, in recent years, of computer simulations and data analysis on high performance computers, for research in all fields of scientific computing.

• ability to formulate, implement, and evaluate an appropriate high-performance computer algorithm to tackle a task in scientific research.
• concepts of message passing programming constructs, and their utility in scientific programming applications.
• ability to write a parallel program using message passing constructs, for scientific applications.

1. Introduction to Parallel Programming. Super problems need super-computers. Parallel programming. Array constructs and how they represent physical fields. Optimising scientific calculations for high performance. Parallelisation strategies. Compiler directives.
2. Program development. Writing programs more easily, and with fewer errors. Adopting a structured approach. Using syntax-aware program editors and makefiles. Using interactive development environments. Program testing and debugging.
3. Advanced parallelization. Harnessing the power of many distributed computers. Distributed memory architectures and cluster computing. Message passing using the MPI standard. Point-to-point and collective communication. Large-scale scientific problems tackled by the single-program-multiple-data paradigm. How to measure the performance of a scientific program on a cluster computer.