Student Resources

Departmental computing resources

The Computer Science Department contains many servers and systems that are available for Computational Science students. These include numerous dual boot Windows/Linux systems as well as a large four-processor server for program development. The department also houses several web and email servers that are available for students. The Department of Mathematics and Statistics also has a computer laboratory that students may use.

24-hour lab

Upon completion of CSC 204, majors in Computational Science may be granted access to the department’s 24-hour computer lab. This privilege is shared with upper division students in Computer Science and Information Science and Technology.

Graphics hardware

Many of the lab systems feature graphics cards and processors with outstanding performance. All the graphics cards are OpenGL certified with many of the newest industrial graphics and hardware features available. In graphics programming classes, students will develop codes that not only utilize OpenGL but also use the high-end performance options available on these cards.

Cluster and parallel computing resources

In 2003, a computing cluster was developed in the Computer Science building. The novel approach to unifying available resources resulted in a publication in a peer-reviewed journal and conference presentation. The “Olympus” cluster contains several high-end servers for not only multi-node parallel program development and testing but also shared memory and threaded parallel program development. At night up to four additional labs (85 multi-core processors) come online to facilitate state-of-the-art research in Computational Science. Two of these labs feature systems with NVIDIA CUDA processors for even greater parallel performance. These computational resources have been used by faculty and students to do collaborative work with researchers at the University of Miami, The University of British Columbia, The University of California San Diego, and the Massachusetts Institute of Technology.

Software tools

Several software tools for symbolic mathematics, linear algebra, the solution of differential equations, and modeling are available. In addition to these resources, Computational Science students have access to state-of-the-art programs for scientific visualization, simulation, and graphics.