Units:

12

Description:

This course will focus on software development skills and tools that cross most disciplines, and how they are applied towards larger software development goals. The course will be taught in the context of several dominant algorithmic patterns found in scientific computing: dense and sparse linear algebra, structured and unstructured grid methods, particle methods, and fast Fourier transforms (FFTs). The course will be taught using C++, although no prior experience with the language will be assumed. Specific topics will include: working in a typical Unix environment, Makefiles, compilers, revision control systems, debuggers, profilers. Fundamentals of C++: Functions, pointers, references; scoping; classes, encapsulation, inheritance; templates; memory management. Fundamentals of data structures and algorithms as they arise in scientific computing. Asymptotic analysis of algorithmic complexity. Correctness debugging and performance debugging. Engineering larger systems: factoring, reuse, dependencies, composition, use of external libraries.

Last Modified: 2024-08-09 2:02PM

Semesters offered:

• Fall 2024
• Fall 2011
• Fall 2010
• Spring 2010
• Spring 2009