E
Eric T. Phipps
Researcher at Sandia National Laboratories
Publications - 71
Citations - 2592
Eric T. Phipps is an academic researcher from Sandia National Laboratories. The author has contributed to research in topics: Uncertainty quantification & Finite element method. The author has an hindex of 19, co-authored 68 publications receiving 2396 citations. Previous affiliations of Eric T. Phipps include National Nuclear Security Administration & University of Colorado Boulder.
Papers
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Journal ArticleDOI
An overview of the Trilinos project
Michael A. Heroux,Roscoe A. Bartlett,Vicki E. Howle,Robert J. Hoekstra,Jonathan Joseph Hu,Tamara G. Kolda,Richard B. Lehoucq,Kevin Long,Roger P. Pawlowski,Eric T. Phipps,Andrew G. Salinger,Heidi K. Thornquist,Raymond S. Tuminaro,James M. Willenbring,Alan B. Williams,Kendall S. Stanley +15 more
TL;DR: The overall Trilinos design is presented, describing the use of abstract interfaces and default concrete implementations and how packages can be combined to rapidly develop new algorithms.
ReportDOI
An overview of Trilinos.
Kevin Long,Raymond S. Tuminaro,Roscoe A. Bartlett,Robert J. Hoekstra,Eric T. Phipps,Tamara G. Kolda,Richard B. Lehoucq,Heidi K. Thornquist,Jonathan Joseph Hu,Alan B. Williams,Andrew G. Salinger,Victoria E. Howle,Roger P. Pawlowski,James M. Willenbring,Michael A. Heroux +14 more
TL;DR: The Trilinos Project is an effort to develop parallel solver algorithms and libraries within an object-oriented software framework for the solution of large-scale, complex multi-physics engineering and scientific applications.
Journal ArticleDOI
Sparse Pseudospectral Approximation Method
TL;DR: A sparse pseudospectral approximation method that accurately reproduces the coefficients for basis functions that naturally correspond to the sparse grid integration rule by reexamining Smolyak's algorithm and exploiting the connections between interpolation and projection in tensor product spaces.
Journal ArticleDOI
Assessment of collocation and galerkin approaches to linear diffusion equations with random data
TL;DR: This work implements both methods for solving partial differential equations with random data using the Trilinos software package, and develops a cost model for both methods which allows for a realistic assessment of the computational complexity of the methods.
Book ChapterDOI
Efficient Expression Templates for Operator Overloading-based Automatic Differentiation.
TL;DR: Several techniques for improving the efficiency of expression templates and their implementation in the automatic differentiation package Sacado are described and their application to differentiation of a large-scale fluid dynamics simulation code is demonstrated.