High Performance Computing and Big Data are widely used tools in Science and Engineering. They are used to study problems in bioinformatics, physics, chemistry, biology, statistics, computer science, engineering and many other disciplines. Specific applications include may areas of study including:
- Galaxy formation
- Climate modeling
- Genetic sequence analysis
- Artificial intelligence
- Structural analysis
- Computational fluid dynamics and many others.
Professors can often enhance the educational experience in their courses by providing students with access to resources similar to those used by professionals in academic or industrial research and development or decision support organizations. For example more realistic simulations, machine learning or analytics problems can be performed in course work. Other examples of classroom assignments may include implementation of massively parallel algorithms in courses on numerical methods, or development of algorithms which can efficiently use GPUs as accelerators.
Additional Information
- The University Research Computing educational clusters are configured to use many of the same applications and techniques used in production environments.
- Professors can register for an entire class to use the resources or can sponsor an individual student working on a class or independent study project. See this FAQ for more information.