Variable Precision Computing
Researchers develop innovative data representations and algorithms to provide faster, more efficient ways to preserve information encoded in data.
Mesh Management
We’re developing fast and scalable algorithms for solving partial differential equations that dynamically adjust the computation mesh in order to improve accuracy and make the best use of computational resources. We research new methods for block-structured adaptive mesh refinement and high-order unstructured curvilinear mesh optimization, targeting applications with moving and deforming meshes. Our algorithms can be used to accurately represent the moving and deforming geometry as well as to resolve internally moving features such as material interfaces, shocks, and reaction fronts. View content related to Mesh Management.
Leading a Revolution in Design
ETHOS: Enabling Technologies for High-Order Simulations
The Enabling Technologies for High-Order Simulations (ETHOS) project performs research of fundamental mathematical technologies for next-generation high-order simulations algorithms.
Center for Applied Scientific Computing Marks 20th Anniversary
For 20 years, scientists from LLNL’s Center for Applied Scientific Computing (CASC) have contributed scientific research and development in mathematics, computer science, and data science that have directly impacted national security and advanced basic science.
SAMRAI: Structured Adaptive Mesh Refinement Application Infrastructure
The Center for Applied Scientific Computing (CASC) at Lawrence Livermore National Laboratory is developing algorithms and software technology to enable the application of structured adaptive mesh refinement (SAMR) to large-scale multi-physics problems relevant to U.S. Department of Energy programs. The SAMRAI (Structured Adaptive Mesh Refinement Application Infrastructure) library is the code base in CASC for exploring application, numerical, parallel computing, and software issues associated with SAMR.
Brian Gunney Values Real-World Results, in Work and Play
Brian Gunney became fascinated with the field of computational fluid dynamics because he thought it could be critical in solving many problems he considered unsolvable.
