Applied Mathematics 483/583

High Performance Scientific Computing

Spring Quarter, 2013

Class Info:


Introduction to hardware, software, and programming for large-scale scientific computing. Overview of multicore, cluster, and supercomputer architectures; procedure and object oriented languages; parallel computing paradigms and languages; graphics and visualization of large data sets; validation and verification; and scientific software development.

[More about the class and syllabus]

Recommended Background

Experience writing and debugging computer programs is required --- preferably experience with scientific, mathematical, or statistical computing, for example in Matlab or R. (Previous knowledge of Fortran, Python, or parallel computing languages is not assumed.)

Students should also be comfortable with undergraduate mathematics, particularly calculus and linear algebra, which is pervasive in scientific computing applications. Many of the examples used in lectures and assignments will require this background. Past exposure to numerical analysis is a plus.

Slides from lectures

Class Notes

These notes will be updated frequently during the quarter.

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