Departmental computing resources
The Computer Science Department, of which Information Science and Technology is a part, contains many servers and systems that are available for our 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 also contains a computer laboratory that students may use.
Upon completion of CSC 204 (Programming I), majors in Information Science and Technology may be granted access to the department’s 24-hour computer lab. This privilege is shared with upper division students in Computational Science and Computer Science.
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 Computer 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.
Several software tools for symbolic mathematics, linear algebra, the solution of differential equations, and modelling are available. In addition to these resources, Computer Science students have access to state-of-the-art programs for scientific visualization, simulation, and graphics.