CS 521 - Computational Sciences

Bulletin Description

Study of computer science techniques and tools that support computational sciences and engineering. Emphasis on visualization, performance evaluation, parallel computing, and distributed computing.

Prerequisites

CS 115, CS/EE 380, and engineering standing.

Expected Preparation

Students need to be familiar with computer architectures, a programming language like C or Fortran, and mathematics like numerical linear algebra and differential equations.

Student Learning Outcomes

Students will develop a knowledge of a variety of computational science basics, applications, and why computational science a multidisciplinary field.

Specifically, students will learn:

  1. Computer science aspects common to typical scientific applications.
  2. Basic algorithms used in computational science applications.
  3. Simple modeling techniques.
  4. Simple to quite complex implementation techniques.
  5. How to research and present computational science application methods.

Measures

Direct Measures:

Students are evaluated on their work and their class participation. Students receive back all of their work. Any papers are marked to indicate problems and they point out correct or better solutions. All work is discussed in detail in class.

NOTE: 100% lecture unless a project is requested by the class (which occurs most years).

Indirect Measures:

These five specific outcomes will be evaluated on the basis of student work (homeworks, presentations, projects, and possibly exams) that will contain assignments specifically addressing these outcomes. They will be evaluated at the end of the semester.

Syllabus Information

 

Possible Textbooks:

No formal textbook is required at this time. Possible study materials include:

University of Colorado High Performance Scientific Computing Course Materials
EPCC training and education course materials available on line through the internet.