Realizing Exascale Performance for Uncertainty Quantification
Abstract not provided.
Publications
Search results
Jump to search filtersExploring Emerging Manycore Architectures for Uncertainty Quantification Through Embedded Stochastic Galerkin Methods
Abstract not provided.
Realizing Exascale Performance for Uncertainty Quantification
Abstract not provided.
Efficient uncertainty propagation for network multiphysics systems
Proposed for publication in International Journal for Numerical Methods in Engineering.
Abstract not provided.
Exploring Emerging Manycore Architectures for Uncertainty Quantification Through Embedded Stochastic Galerkin Methods
Proposed for publication in International Journal of Computer Mathematics.
Abstract not provided.
The Algorithm Research Experience in Albany
Abstract not provided.
Numerical Bifurcation Methods and their Application to Fluid Dynamics: Analysis beyond Simulation
Proposed for publication in Communications in Computational Physics.
Abstract not provided.
Efficient expression templates for operator overloading-based automatic differentiation
Lecture Notes in Computational Science and Engineering
Expression templates are a well-known set of techniques for improving the efficiency of operator overloading-based forward mode automatic differentiation schemes in the C++ programming language by translating the differentiation from individual operators to whole expressions. However standard expression template approaches result in a large amount of duplicate computation, particularly for large expression trees, degrading their performance. In this paper we describe several techniques for improving the efficiency of expression templates and their implementation in the automatic differentiation package Sacado (Phipps et al., Advances in automatic differentiation, Lecture notes in computational science and engineering, Springer, Berlin, 2008; Phipps and Gay, Sacado automatic differentiation package. http://trilinos.sandia.gov/packages/sacado/, 2011). We demonstrate their improved efficiency through test functions as well as their application to differentiation of a large-scale fluid dynamics simulation code. © 2012 Springer-Verlag.
Supporting Embedded Algorithms through Template-based Generic Programming
Abstract not provided.
Efficient Expression Templates for Operator Overloading-based Automatic Differentiation
Abstract not provided.
Exploring Embedded UQ Approaches for Improved Scalability and Efficiency
Abstract not provided.
Hierarchical Schur complement preconditioner for the stochastic Galerkin finite element methods
Proposed for publication in Numerical Linear Algebra with Applications.
Abstract not provided.
Reduced chaos expansions with random coefficients in reduced-dimensional stochastic modeling of coupled problems
Proposed for publication in International Journal for Numerical Methods in Engineering.
Abstract not provided.
A posteriori error analysis and adaptive construction of surrogate models for probabilities
Abstract not provided.
Enabling Embedded Algorithms R&D Through Template-based Generic Programming
Abstract not provided.
Preliminary Investigations of Multi-Core Accelerated Embedded Uncertainty Quantification
Abstract not provided.
Scalable Collocation Methods using a Combination of Krylov Basis Recycling and Adjoint Enhancement
Abstract not provided.
Automating embedded analysis capabilities and managing software complexity in multiphysics simulation, Part I: Template-based generic programming
Scientific Programming
An approach for incorporating embedded simulation and analysis capabilities in complex simulation codes through template-based generic programming is presented. This approach relies on templating and operator overloading within the C++ language to transform a given calculation into one that can compute a variety of additional quantities that are necessary for many state-of-the-art simulation and analysis algorithms. An approach for incorporating these ideas into complex simulation codes through general graph-based assembly is also presented. These ideas have been implemented within a set of packages in the Trilinos framework and are demonstrated on a simple problem from chemical engineering. © 2012 - IOS Press and the authors. All rights reserved.
Uncertainty segregation and tensor-product-type approximation in reduced-dimensional stochastic analysis of coupled systems
International Journal for Numerical Methods in Engineering
Abstract not provided.
Embedded Algorithms through Template-based Generic Programming
Abstract not provided.
A Posteriori Error Analysis of Stochastic Differential Equations Using Polynomial Chaos Approximations
Abstract not provided.
Embedded Stochastic Galerkin Projection and Solver Methods via Template-based Generic Programming
Abstract not provided.
Building Hierarchical Toolchains for Nonlinear Analysis
Abstract not provided.
Applying template-based generic programming to the simulation and analysis of partial differential equations
Scientific Programming
Abstract not provided.
SciDAC Institute QUEST (Quantification of Uncertainty in Extreme Scale Computations)
Abstract not provided.
Results 101–125 of 161