The approach relies on effective theories, which contain the relevant degrees of freedom for the particluar problem, and a few basic algorithms, such as Monte Carlo, molecular dynamics and finite differences. This course builds on the concepts presented in computer simulation section of Introduction to High Performance Computing . It explores the basic techniques used in computational science, and provides a thorough introduction to the use of HPC in areas of scientific research. The talks concepts are illustrated by way of examples of current Grand Challenge Projects. Who should attend These courses are aimed at users who are competent programmers in either C or Fortran, and who have a problem which may benefit from the application of high performance computing.
Course dates To be announced.
Back to top Genetic Algorithms Natural evolution has produced many optimal forms. Photo-synthesis, the wing of the albatross, and the structural characteristics of bone are just some of its remarkable accomplishments. What is more, evolution is able to reproduce these accomplishments, as shown by the similar forms of the shark, the ichthyosaur, and the dolphin. Evolution is all the more remarkable because of its randomness, and by the absence of a directing intelligence. In this course, we will examine how the principles used by evolutionary systems can be employed to optimise man-made problems.