Publications

van Bloemen Waanders, Bart G.; Long, Kevin R.; Hill, Judith C.

Abstract not provided.

Debusschere, Bert D.; Adalsteinsson, Helgi A.; Long, Kevin R.; Najm, H.N.; Hickner, Michael A.; Simmons, Blake S.; Davalos, Rafael V.; Ponce, Pierre P.

Abstract not provided.

Bartlett, Roscoe B.; Long, Kevin R.

Abstract not provided.

Long, Kevin R.

Sundance is a system of software components that allows construction of an entire parallel simulator and its derivatives using a high-level symbolic language. With this high-level problem description, it is possible to specify a weak formulation of a PDE and its discretization method in a small amount of user-level code; furthermore, because derivatives are easily available, a simulation in Sundance is immediately suitable for accelerated PDE-constrained optimization algorithms. This paper is a tutorial for setting up and solving linear and nonlinear PDEs in Sundance. With several simple examples, we show how to set up mesh objects, geometric regions for BC application, the weak form of the PDE, and boundary conditions. Each example then illustrates use of an appropriate solver and solution visualization.

Heroux, Michael A.; Kolda, Tamara G.; Long, Kevin R.; Hoekstra, Robert J.; Pawlowski, Roger P.; Phipps, Eric T.; Salinger, Andrew G.; Williams, Alan B.; Heroux, Michael A.; Hu, Jonathan J.; Lehoucq, Richard B.; Thornquist, Heidi K.; Tuminaro, Raymond S.; Willenbring, James M.; Bartlett, Roscoe B.; Howle, Victoria E.

The Trilinos Project is an effort to facilitate the design, development, integration and ongoing support of mathematical software libraries. In particular, our goal is 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. Our emphasis is on developing robust, scalable algorithms in a software framework, using abstract interfaces for flexible interoperability of components while providing a full-featured set of concrete classes that implement all abstract interfaces. Trilinos uses a two-level software structure designed around collections of packages. A Trilinos package is an integral unit usually developed by a small team of experts in a particular algorithms area such as algebraic preconditioners, nonlinear solvers, etc. Packages exist underneath the Trilinos top level, which provides a common look-and-feel, including configuration, documentation, licensing, and bug-tracking. Trilinos packages are primarily written in C++, but provide some C and Fortran user interface support. We provide an open architecture that allows easy integration with other solver packages and we deliver our software to the outside community via the Gnu Lesser General Public License (LGPL). This report provides an overview of Trilinos, discussing the objectives, history, current development and future plans of the project.

van Bloemen Waanders, Bart G.; Bartlett, Roscoe B.; Long, Kevin R.; Boggs, Paul T.; Salinger, Andrew G.

Three years of large-scale PDE-constrained optimization research and development are summarized in this report. We have developed an optimization framework for 3 levels of SAND optimization and developed a powerful PDE prototyping tool. The optimization algorithms have been interfaced and tested on CVD problems using a chemically reacting fluid flow simulator resulting in an order of magnitude reduction in compute time over a black box method. Sandia's simulation environment is reviewed by characterizing each discipline and identifying a possible target level of optimization. Because SAND algorithms are difficult to test on actual production codes, a symbolic simulator (Sundance) was developed and interfaced with a reduced-space sequential quadratic programming framework (rSQP++) to provide a PDE prototyping environment. The power of Sundance/rSQP++ is demonstrated by applying optimization to a series of different PDE-based problems. In addition, we show the merits of SAND methods by comparing seven levels of optimization for a source-inversion problem using Sundance and rSQP++. Algorithmic results are discussed for hierarchical control methods. The design of an interior point quadratic programming solver is presented.