Sandia National Laboratories, California

Coordinator: Michael Veilleux

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Sandia is a multiprogram science and engineering laboratory operated for the Department of Energy with major facilities at Albuquerque, New Mexico, and Livermore, California, and a test range near Tonopah, Nevada. Since its formation over 40 years ago, Sandia has established itself as a major research and development center with responsibilities for nuclear weapons, arms control, energy, the environment, economic competitiveness, and other areas of national importance. Sandia employs about 7000 staff with about 60% in scientific and technical positions.

Research in computational science at Sandia ranges from exploring issues in theoretical and applied computer science to the development of new numerical algorithms for novel architecture computers. Sandia is currently developing applications software to perform scientific and engineering calculations on massively parallel computers. The primary goal of this effort is to develop a unique capability for performing large-scale simulations and to investigate important scientific and engineering questions that would otherwise be impossible using conventional supercomputers. Research in the computational sciences is spread across many centers, several of which are described below.

The Computational Sciences, Computer Sciences, and Mathematics Center at Sandia has a number of research projects in which fellowship students could participate. These projects cover a broad range of scientific and engineering disciplines and represent exceptional challenges for applied research on advanced computers. For more details on Sandia’s computational science activities, see and

The Combustion Research Facility (CRF) is DOE’s premier site for broad-based research in combustion science and technology. Since 1981, the CRF has been a DOE “user facility” where scientists and engineers from industry and academia collaborate with CRF researchers on problems of mutual interest. Working closely with experimentalists, researchers at the Combustion Research Facility use theory, modeling, and simulation tools to better understand problems ranging from fundamental chemical dynamics to the full characterization of the operation of combustion devices. The ultimate goal is to discover how to reliably predict factors that can guide design, operation and fuel selection. For more details on Sandia’s activities in the modeling and simulation of combustion, see

The Distributed Information Systems Center at Sandia has research projects in distributed computing, optimization, component architectures and frameworks for scientific computing, computational chemistry, intelligent agents, and cluster visualization. For more details, see

Computational Molecular Science

Our work in this area is focused on developing and applying state-of-the-art computational molecular methods ranging from electronic structure to molecular theory for massively parallel supercomputers. Examples of current research topics include radiation effects in electronic materials, mesoscale modeling of fracture and failure in alloys, lubrication in microelectromechanical (MEMs) systems, transport in polymers and biomembranes, protein folding, and cell modeling.

Computational Biology

Our research organization develops and applies state-of-the-art parallel algorithms for bioinformatics applications such as large-scale search and discovery for genomic and proteomic data. Example problems include gene finding, genome-genome comparisons, motif discovery in amino acids towards resolving the function, structure and evolution of proteins, and database searches that involve mass spectrometry spectrum identification and peptide mapping to protein databases.

Extreme Cluster Computing

The Computational Plant project at Sandia National Laboratories is developing a large-scale,massively parallel computing resource from a cluster of commodity computing and networking components. We are combining the knowledge and research of previous and ongoing commodity cluster projects with our expertise in designing, developing, using, and maintaining large-scale MPP machines. Our goal is to provide a commodity-based, large-scale computing resource that meets the level of compute performance needed by Sandia’s critical applications.

Structural Mechanics/Finite Element Analysis

Sandia has developed a broad capability for performing finite element analysis of complex engineering systems to verify that they meet structural design requirements. Massively parallel computers are being used to perform large-scale finite element analyses to reduce production costs and to increase efficiency of the design process. Parallel algorithm development, as well as graphical analysis of the results, are topics of on-going research that are important to the development of a massively parallel production environment at Sandia.

3-D Seismic Imaging of Complex Geologies

A key to reducing the risks and costs associated with domestic oil and gas exploration is the ability to image complex geologies, such as thrusts in mountainous areas and sub-salt structures in the Gulf of Mexico. Commonly used poststack depth migration and prestack time migration techniques are not able to accurately resolve these geologies. Prestack depth migration has the potential to image these geologies, but further algorithmic developments and an improved computational infrastructure are needed. Together with our industrial partners, we have launched a new effort to develop massively parallel finite-difference techniques to enable large-scale prestack depth migration.

Shock Physics Research

Sandia is a nationally recognized expert in modeling shock waves, the associated nonlinear material response, and the associated large deformations. We develop massively parallel, three-dimensional shock physics computer codes and apply them to government, industry, and scientific problems. The codes must model the nonlinear behavior of metals, geological materials, and explosives under high pressure and large strains. We have used the codes to model a broad variety of problems including the impact of meteors on satellites, fragmentation of oil shale for sit retorting, the lethality of a United States missile colliding with a foreign missile, the effectiveness of modern ‘bulletproof’ vests, and even the fireball arising from the impact of the Shoemaker-Levy 9 comet with Jupiter. We are extending our models to use adaptive finite-element techniques, arbitrary-connectivity meshes, and explicit and implicit solution techniques.