- Departmental Computing Resources
- 24 Hour Lab
- Graphics Hardware
- Cluster and Parallel Computing Resources
- Software Tools
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 e-mail servers that are available for students. The Department of Mathematics also contains a computer laboratory that students may use.
Upon completion of CSC 204, majors in Computational Science may be granted access to the departments 24 hour computer lab. This priveledge is shared with upper division students in Computer Science and IST.
Many of the lab systems feature graphics cards and processors with outstanding performance. All of 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 utilizes OpenGL, but that also use the high-end performance options available on these cards.
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 features 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.
Several software tools for symbolic mathematics, linear algebra, the solution of differential equations, and modelling, are available. In addition to these resources, computational science students have access to state of the art programs for scientific visualization, simulation, and graphics.