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A smoothed two-and three-dimensional interface reconstruction method

Computing and Visualization in Science

Mosso, Stewart; Garasi, Christopher J.; Drake, Richard R.

The Patterned Interface Reconstruction algorithm reduces the discontinuity between material interfaces in neighboring computational elements. This smoothing improves the accuracy of the reconstruction for smooth bodies. The method can be used in two- and three-dimensional Cartesian and unstructured meshes. Planar interfaces will be returned for planar volume fraction distributions. The algorithm is second-order accurate for smooth volume fraction distributions. © 2008 Springer-Verlag.

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Pamgen, a library for parallel generation of simple finite element meshes

Hensinger, David M.; Drake, Richard R.; Foucar, James G.

Generating finite-element meshes is a serious bottleneck for large parallel simulations. When mesh generation is limited to serial machines and element counts approach a billion, this bottleneck becomes a roadblock. Pamgen is a parallel mesh generation library that allows on-the-fly scalable generation of hexahedral and quadrilateral finite element meshes for several simple geometries. It has been used to generate more that 1.1 billion elements on 17,576 processors. Pamgen generates an unstructured finite element mesh on each processor at the start of a simulation. The mesh is specified by commands passed to the library as a 'C'-programming language string. The resulting mesh geometry, topology, and communication information can then be queried through an API. pamgen allows specification of boundary condition application regions using sidesets (element faces) and nodesets (collections of nodes). It supports several simple geometry types. It has multiple alternatives for mesh grading. It has several alternatives for the initial domain decomposition. Pamgen makes it easy to change details of the finite element mesh and is very useful for performance studies and scoping calculations.

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Sandia National Laboratories Advanced Simulation and Computing (ASC) software quality plan part 2 mappings for the ASC software quality engineering practices, version 2.0

Boucheron, Edward A.; Sturtevant, Judy E.; Drake, Richard R.; Edwards, Harold C.; Forsythe, Christi A.; Heaphy, Robert T.; Hodges, Ann L.; Minana, Molly A.; Pavlakos, Constantine P.; Schofield, Joseph R.

The purpose of the Sandia National Laboratories Advanced Simulation and Computing (ASC) Software Quality Plan is to clearly identify the practices that are the basis for continually improving the quality of ASC software products. The plan defines the ASC program software quality practices and provides mappings of these practices to Sandia Corporate Requirements CPR001.3.2 and CPR001.3.6 and to a Department of Energy document, ''ASCI Software Quality Engineering: Goals, Principles, and Guidelines''. This document also identifies ASC management and software project teams' responsibilities in implementing the software quality practices and in assessing progress towards achieving their software quality goals.

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Sandia National Laboratories Advanced Simulation and Computing (ASC) software quality plan. Part 1: ASC software quality engineering practices, Version 2.0

Drake, Richard R.; Sturtevant, Judy E.; Boucheron, Edward A.; Edwards, Harold C.; Minana, Molly A.; Forsythe, Christi A.; Heaphy, Robert T.; Hodges, Ann L.; Pavlakos, Constantine P.; Schofield, Joseph R.

The purpose of the Sandia National Laboratories Advanced Simulation and Computing (ASC) Software Quality Plan is to clearly identify the practices that are the basis for continually improving the quality of ASC software products. The plan defines the ASC program software quality practices and provides mappings of these practices to Sandia Corporate Requirements CPR 1.3.2 and 1.3.6 and to a Department of Energy document, ASCI Software Quality Engineering: Goals, Principles, and Guidelines. This document also identifies ASC management and software project teams responsibilities in implementing the software quality practices and in assessing progress towards achieving their software quality goals.

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ALEGRA : version 4.6

Wong, Michael K.; Brunner, Thomas A.; Garasi, Christopher J.; Haill, Thomas A.; Mehlhorn, Thomas A.; Drake, Richard R.; Hensinger, David M.; Robbins, Joshua R.; Robinson, Allen C.; Summers, Randall M.; Voth, Thomas E.

ALEGRA is an arbitrary Lagrangian-Eulerian multi-material finite element code used for modeling solid dynamics problems involving large distortion and shock propagation. This document describes the basic user input language and instructions for using the software.

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Sandia National Laboratories Advanced Simulation and Computing (ASC) Software Quality Plan. Part 2, Mappings for the ASC software quality engineering practices. Version 1.0

Boucheron, Edward A.; Schofield, Joseph R.; Drake, Richard R.; Minana, Molly A.; Forsythe, Christi A.; Heaphy, Robert T.; Hodges, Ann L.; Pavlakos, Constantine P.; Sturtevant, Judy E.

The purpose of the Sandia National Laboratories Advanced Simulation and Computing (ASC) Software Quality Plan is to clearly identify the practices that are the basis for continually improving the quality of ASC software products. The plan defines the ASC program software quality practices and provides mappings of these practices to Sandia Corporate Requirements CPR 1.3.2 and 1.3.6 and to a Department of Energy document, 'ASCI Software Quality Engineering: Goals, Principles, and Guidelines'. This document also identifies ASC management and software project teams responsibilities in implementing the software quality practices and in assessing progress towards achieving their software quality goals.

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Sandia National Laboratories Advanced Simulation and Computing (ASC) software quality plan. Part 1 : ASC software quality engineering practices version 1.0

Boucheron, Edward A.; Schofield, Joseph R.; Drake, Richard R.; Edwards, Harold C.; Minana, Molly A.; Forsythe, Christi A.; Heaphy, Robert T.; Hodges, Ann L.; Pavlakos, Constantine P.; Sturtevant, Judy E.

The purpose of the Sandia National Laboratories (SNL) Advanced Simulation and Computing (ASC) Software Quality Plan is to clearly identify the practices that are the basis for continually improving the quality of ASC software products. Quality is defined in DOE/AL Quality Criteria (QC-1) as conformance to customer requirements and expectations. This quality plan defines the ASC program software quality practices and provides mappings of these practices to the SNL Corporate Process Requirements (CPR 1.3.2 and CPR 1.3.6) and the Department of Energy (DOE) document, ASCI Software Quality Engineering: Goals, Principles, and Guidelines (GP&G). This quality plan identifies ASC management and software project teams' responsibilities for cost-effective software engineering quality practices. The SNL ASC Software Quality Plan establishes the signatories commitment to improving software products by applying cost-effective software engineering quality practices. This document explains the project teams opportunities for tailoring and implementing the practices; enumerates the practices that compose the development of SNL ASC's software products; and includes a sample assessment checklist that was developed based upon the practices in this document.

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An Exploration in Implementing Fault Tolerance in Scientific Simulation Application Software

Drake, Richard R.; Drake, Richard R.; Summers, Randall M.

The ability for scientific simulation software to detect and recover from errors and failures of supporting hardware and software layers is becoming more important due to the pressure to shift from large, specialized multi-million dollar ASCI computing platforms to smaller, less expensive interconnected machines consisting of off-the-shelf hardware. As evidenced by the CPlant{trademark} experiences, fault tolerance can be necessary even on such a homogeneous system and may also prove useful in the next generation of ASCI platforms. This report describes a research effort intended to study, implement, and test the feasibility of various fault tolerance mechanisms controlled at the simulation code level. Errors and failures would be detected by underlying software layers, communicated to the application through a convenient interface, and then handled by the simulation code itself. Targeted faults included corrupt communication messages, processor node dropouts, and unacceptable slowdown of service from processing nodes. Recovery techniques such as re-sending communication messages and dynamic reallocation of failing processor nodes were considered. However, most fault tolerance mechanisms rely on underlying software layers which were discovered to be lacking to such a degree that mechanisms at the application level could not be implemented. This research effort has been postponed and shifted to these supporting layers.

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ALEGRA: User Input and Physics Descriptions Version 4.2

Boucheron, Edward A.; Haill, Thomas A.; Peery, James S.; Petney, Sharon P.; Robbins, Joshua R.; Robinson, Allen C.; Summers, Randall M.; Voth, Thomas E.; Wong, Michael K.; Brown, Kevin H.; Budge, Kent G.; Burns, Shawn P.; Carroll, Daniel E.; Carroll, Susan K.; Christon, Mark A.; Drake, Richard R.; Garasi, Christopher J.

ALEGRA is an arbitrary Lagrangian-Eulerian finite element code that emphasizes large distortion and shock propagation. This document describes the user input language for the code.

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Results 26–45 of 45
Results 26–45 of 45