A very wide range of activities are carried out in the Center for CS&IT at Sandia, California. Below, we feature fact sheet downloads (PDF format) for a few selected projects:
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FClib: A Library for Building Data Analysis and Data Discovery Tools |
| FCLib, a data analysis toolkit, was constructed to meet the needs of data discovery in large-scale, spatio-temporal data. FCLib is a C library toolkit of building blocks that can be used to assemble analyses for data discovery. (more...) | |
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Weapon Data Analysis & Visualization |
| Making sense of a collection of data is a familiar challenge for scientists and engineers. While tools are available to collect terabytes of data per event, understanding this vast quantity of information is another story. (more...) | |
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MPQC: Massively Parallel Quantum Chemistry Program |
| The Massively Parallel Quantum Chemistry (MPQC) Program computes properties of atoms and molecules from first principles using the time independent Schrödinger equation. It runs on a wide range of architectures ranging from indivdual workstations to symmetric multiprocessors to massively parallel computers. (more...) | |
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Programmable Hardware Shaders |
| Programmable hardware shaders can replace the fixed-functionality vertex and pixel shaders traditionally found on Graphics Processing Units (graphics cards or GPUs). This allows greater control of how data are rendered to images and makes possible the use of sophisticated rendering techniques at interactive frame rates. (more...) | |
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Distributed, Intelligent RAS System for Large Computational Clusters |
| Cluster computing as the backbone of Sandia's capacity computing has become crucial to many of Sandia's missions. Viewing a cluster as a large collection of statistically similar devices allows us to detect aberrant node behavior due to various effects long before catastrophic failure occurs. (more...) | |
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SHOE: Higher-Order Finite-Element Visualization |
| SHOE (Sandia Higher-Order Elements) is a research program to investigate the visualization of higher-order finite-element simulation results. Finite-element simulations typically use low-order (linear or occasionally quadratic) polynomials to approximate solutions of differential equations describing interesting situations. (more...) |