SHPC5001 Advanced Scientific Computation

Credit
6 points
Offering
AvailabilityLocationMode
Not available in 2019UWA (Perth)Face to face
Content
Efficient algorithms for numerical analysis and optimisation are the basis for high performance computing (HPC) in many scientific fields. This unit provides the mathematics and algorithms needed to implement such efficient algorithms for HPC applications in Physics, Chemistry and the Geosciences, illustrated by examples from these fields. The laboratory component emphasises the implementation of these algorithms from scratch, as well as the use of pre-written programs and packages commonly used in HPC.

Specific topics are selected from (1) linear algebra, eigensystems, singular value decomposition, and sparse methods for dealing with them; (2) single and multidimensional quadrature; (3) function approximation; (4) pseudorandom numbers and monte carlo; (5) Newton-Raphson, conjugate gradient, least squares; (6) fourier transforms, wavelets and filters; (7) modelling data—least squares, maximum likelihood, inverse problems and regularisation, and compressive sensing; and (8) multimensional partial differential equations. Except for laboratory sessions, the unit involves significant self-study with lectures partly used as tutorials or as assessment periods.
Outcomes
Students are able to (1) be familiar with numerical analysis techniques as described above, their implementation, cost and accuracy and (2) demonstrate mastery of programming of numerical techniques in Fortran or C taking advantage of the above techniques.
Assessment
Indicative assessments in this unit are as follows: (1) quizzes; (2) laboratories; and (3) examination. Further information is available in the unit outline.

Supplementary assessment is not available in this unit.
Unit Coordinator(s)
Professor Jingbo Wang
Unit rules
Prerequisites:
SHPC4001 Principles of Scientific Computation
or equivalent as approved by the Faculty
Contact hours
lectures: 26 hours per semester (2 hours per week from week 1); practical classes/labs: 36 hours per semester (3 hours per week from week 2)
Recommended
reading

Numerical recipes

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