Scientific Computing (SCI)

The researchers produced some of the most heavily used scientific software (and hardware standards!) in the world. Their strength is a result of their commitment to building industrial-strength software and algorithms and supporting full-scale scientific applications in large interdisciplinary collaborations among scientists, engineers, mathematicians, and computer scientists. Their research encompasses symbolic, numerical, and geometric computation, often on parallel or distributed systems.

Topics

• Parallel computing

  Languages and numerical algorithms for parallel computers

• Automatic Performance Tuning

  Automatic generation of optimized implementations of computational and communication kernels, tuned for particular architectures and work loads.

• Mesh generation

  Automatic generation of triangulated meshes to represent physical and computational domains.

• Matrix computations

  Numerical algorithms and software for fast and accurate numerical linear algebra.

• Floating point

  Extended precision arithmetic. Reliable floating point standards. Architectural and run time implications of floating point standards. Programming language implications of floating point standards.

• Animation

• Computer Algebra

  Methods for symbolic mathematical computation.