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High Performance Scientific Computing


Provider
coursera

Price
Free

School
University of Washington

Type
University

Instructor
Randall LeVeque

Categories
Mathematics, Technology

Duration
10 weeks

Format
Video

Language
English

Description
Computation and simulation are increasingly important in all aspects of science and engineering. At the same time writing efficient computer programs to take full advantage of current computers is becoming increasingly difficult. Even laptops now have 4 or more processors, but using them all to solve a single problem faster often requires rethinking the algorithm to introduce parallelism, and then programming in a language that can express this parallelism.  Writing efficient programs also requires some knowledge of machine arithmetic, computer architecture, and memory hierarchies. Although parallel computing will be covered, this is not a class on the most advanced techniques for using supercomputers, which these days have tens of thousands of processors and cost millions of dollars. Instead, the goal is to teach tools that you can use immediately on your own laptop, desktop, or a small cluster. Cloud computing will also be discussed, and students who don't have a multiprocessor computer of their own will still be able to do projects using Amazon Web Services at very low cost. Along the way there will also be discussion of software engineering tools such as debuggers, unit testing, Makefiles, and the use of version control systems. After all, your time is more valuable than computer time, and a program that runs fast is totally useless if it produces the wrong results. High performance programming is also an important aspect of high performance scientific computing, and so another main theme of the course is the use of basic tools and techniques to improve your efficiency as a computational scientist.