Techniques for scientific computing
4 points * Second semester * Clayton * Prerequisites: MAT2010, MAA2011 and MAA2032 * Prohibitions: ASP3132
Objectives On completion of this subject students will have a basic understanding of a variety of techniques commonly used in large scale scientific computations; be able to design programs which are fast and accurate while using a minimum of computer storage.
Synopsis Topics to be covered include numerical error estimation for ordinary differential equations, adaptive grid and time stepping, multigrid and particle methods, efficient function evaluation, efficient data storage including linked lists and tree codes, stiff differential equations, multistep integration schemes, Monte Carlo methods and Fast Fourier transforms. Skeleton computer programs will be provided.
Assessment Examinations (1.5 hours): 85% * Tests and/or assignments: 15%
Recommended texts
Press W H, Flannery B P, Teukolsky S A and Vetterling W T Numerical recipes, Fortran edn, CUP, 1992
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