Supercomputing and Computation



The Computational Mathematics activities include the developing and deploying computational and applied mathematical capabilities for modeling, simulating, and predicting complex phenomena of importantance to the Department of Energy (DOE). A particular focus is on developing novel scalable algorithms for exploiting novel high performance computing resources for scientific discovery as well as decision-sciences.

Related Projects

1-3 of 3 Results

Multiresolution and Adaptive Numerical Environment for Scientific Simulations (MADNESS)
— Numerical modeling softwares and solvers are key components of successful and accurate simulations for effective predictions and analysis. The results help us to improve our scientific theories as well as product and engineering designs. A representative of the most successful of the traditional software and solver environment is MATLAB with a core that is based on matrix and vector operations.

— ORNL's research focuses on the development of several transformational methodologies related to the efficient, accurate and robust computation of statistical quantities of interest.

Scalable stencil-based solver algorithms
— This research concentrates on developing highly scalable algorithms and modular software in support of numerical methods for solving partial differential equations with stencil-based discretization approaches. Stencil codes require only nearest neighbor information in order to perform a numerical update and are thereby amenable to efficient and hybrid parallelization.


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