The FASTMath team brings together preeminent scientists in a broad range of applied mathematics areas. The FASTMath team has a proven track record of developing new mathematical technologies and algorithms, tackling difficult algorithmic and implementation issues as computer architectures undergo a fundamental shift, and engaging multiple application domains to enable new scientific discovery.
More than 50 mathematicians from five national laboratories and five universities comprise our team.
Oak Ridge National Laboratory
We are focused on the development of all aspects of exascale data analytic methods. Efforts include the functional representation of data, using sparse polynomial approximation, low dimensional manifolds, and high order regularizers to enable faster storage, retrieval, and analysis of large datasets. Targeted methods are being developed in sparse storage and retrieval of large data, uncertainty estimates for sparse data representation, fast estimation of data statistics, and importance ranking in streaming data.
Rensselaer Polytechnic Institute
We are focused on the development of all aspects of exascale unstructured mesh methods. Efforts include the development of parallel mesh infrastructures, general anisotropic mesh adaptation procedures for general 3D domains including curved high order mesh entities, unstructured mesh adjacency based partitioning tools, interactions with general geometry representations, unstructured mesh particle methods, unstructured mesh adaption in stochastic spaces for UQ, and an unstructured mesh fields infrastructure.
Sandia National Laboratories
Sandia National Laboratories, P.O. Box 5800, MS 1318, Albuquerque, NM 87185-1318
Southern Methodist University
Our FASTMath research and development focuses on time integration methods and nonlinear solvers for multi-rate problems arising from multi-physics and multi-scale simulations. Specifically, we are exploring combination implicit–explicit methods, symplectic methods, and integrators for coupled continuum–particle models.