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Results 126–150 of 482

Courtenay T. Vaughan
Staff Page • Scalable Computer Architecture. Biography My current research interests include performance modeling and analysis, code optimization, and characterization of current high performance computing (HPC) platforms. As a member of the Application Performance Modeling and Anaylsis Team, we are using the knowledge of current architectures to predict performance of future machines and...

CRADA Signed with Rigetti Quantum Computing RQC
News Article, July 1, 2017 • Quantum computing researchers at Sandia National Laboratories have established a cooperative research agreement (CRADA) with Rigetti Quantum Computing (RQC), a Berkeley, CA based startup company.  Sandia and RQC will collaborate to test and evaluate RQC's 8-qubit quantum information processor.  This collaboration will produce detailed, high-fidelity information about errors and fault...
Under this CRADA, Sandia's open-source pyGSTi software will be deployed to probe the quantum logic behavior of Rigetti Quantum Computing's new 8-qubit quantum processor, generating new ideas for debugging quantum processors.

Craig M. Vineyard
Staff Page • Computer Scientist. Biography Craig M. Vineyard, PhD has degrees in computer engineering with expertise in machine learning and neuromorphic computing. He has been at Sandia National Laboratories for over 15 years pursuing computing research and development for national security. This includes performing foundational research on how advanced computing technologies can...

Credibility in Scientific Machine Learning: Data Verification and Model Qualification
News Article, June 1, 2021 • The Advanced Simulation and Computing (ASC) initiative on Advanced Machine Learning (AML) aims to maximize near and long-term impact of Artificial Intelligence (AI) and Machine Learning (ML) technologies on Sandia’s Nuclear Deterrence (ND) program. In this ASC-AML funded project, the team is developing new approaches for assessing the quality of...
Workflow illustration of a machine learning classifier, trained on labeled time- or frequency-domain signals in order to classify new measurements, with uncertainty metrics.

CrossSim
Software • CrossSim is a crossbar simulator designed to model resistive memory crossbars for both neuromorphic computing and (in a future release) digital memories.  It provides a clean python API so that different algorithms can be built upon crossbars while modeling realistic device properties and variability.  The crossbar can be modeled using...

Curtis C. Ober
Staff Page • Computational Science. Biography Curt has extensive experience with seismic imaging, full-waveform inversion, verification, time-integration, and discontinuous Galerkin methods. Additionally, he has a diverse background in computational dynamics, including computational fluid dynamics in the areas of Shock physicsSupersonic and hypersonic flowSupersonic wakes Education 1/1991-5/1994 University of Texas at Austin, Austin, Texas,...

Cyber Security
Focus Area • Our cybersecurity research is focused on developing cross-cutting enabling capabilities that can impact a wide range of cybersecurity challenges. This includes research in streaming algorithms to quickly process large cyber data streams, algorithms to find patterns in large graphs and machine learning techniques to detect adversarial behavior (e.g. phishing emails)....

Cynthia Ann Phillips
Staff Page • Computing Research. Biography I have historically worked in combinatorial optimization, algorithm design and analysis, and parallel computation with elements of operations research. My work has spanned theory, general solver development, and applications. I still work in combinatorial optimization. More recently, I have worked in "big data" areas, including streaming, complex...

D2T – Doubly Distributed Transactions
Software • Typical distributed transactions are a single client and multiple servers. For the supercomputing simulations, we have multiple clients to multiple servers when attempting to do atomic actions, hence doubly distributed transactions. This project created a library that can handle scalably offering a two-phase commit style transaction for both storage oriented...

Dakota
Software • Dakota: Optimization and Uncertainty Quantification Algorithms for Design Exploration and Simulation Credibility. The Dakota toolkit provides a flexible, extensible interface between analysis codes and iterative systems analysis methods. Dakota contains algorithms for: optimization with gradient and nongradient-based methods;uncertainty quantification with sampling, reliability, stochastic expansion, and epistemic methods;parameter estimation with nonlinear...

Daniel Thomas Seidl
Staff Page • Scientific Machine Learning. Biography Tom has been at Sandia National Labs since January 2016. He develops computational methods in the areas of PDE-constrained optimization, finite elements, and uncertainty quantification. Education Ph.D. Mechanical Engineering, Boston University, August 2015 M.S. Mechanical Engineering, Boston University, May 2012 B.S. University of Rochester, Biomedical Engineering,...

DARPA/Amazon/IEEE Graph Challenge Champion
News Article, December 1, 2017 • A Sandia team from the Center for Computational Research (Michael Wolf, Mehmet Deveci, Jon Berry, Si Hammond, and Siva Rajamanickam) was awarded champion status in the 2017 DARPA/Amazon/IEEE Graph Challenge (http://graphchallenge.mit.edu/champions) for their fast triangle counting implementation KKTri.  KKTri was developed as part of the KokkosKernels framework, leveraging linear algebra-based...
DARPA/Amazon/IEEE Graph Challenge Champion

Data Analysis and Visualization
Focus Area • The data analysis and visualization groups focus on scalable techniques for providing decision support in national security and national-level challenges. By incorporating advanced algorithms, innovative hardware architectures, and scalable analysis components, we develop solutions that promote insight, regardless of the complexity, size, or uncertainty of the data. With a focus...

Data and Decision Sciences
Research Area • Sandia and the CCR support decision-makers in multiple national security application domains including cyber security, non-proliferation, counterterrorism, and battlefield situational awareness. The decision sciences research is multidisciplinary and blurs the line between computing and humans. This group has extensive experience in a number of computational fields such as discrete math,...

Data collection for the Transportation Security Administration
News Article, February 1, 2016 • Data collection for the Transportation Security Administration Recently, two projects for the Transportation Security Administration (TSA) have succeeded in collecting data from Transportation Security Officers (TSOs) that are, in many ways, unparalleled in the research community. These projects, Performance Decrement and Passenger Threat Detection Resolution (PTDR) were aimed at answering...

David Littlewood
Staff Page • Computational Multiscale. Biography I am the manager of the Computational Multiscale Department (Org. 1444) in the Center for Computing Research at Sandia National Laboratories. My managerial role and technical background are in the development, implementation, and application of multiscale, multiphysics techniques for materials modeling and computational solid mechanics. I am...

Defense Applications
Focus Area • We develop and apply multiphysics analysis tools that address various issues important to the DOE, DoD, DHS, and other U.S. Government agencies, and support production use of our codes by our principal customers. Our ALEGRA multiphysics code employs an Arbitrary Lagrangian-Eulerian (ALE) methodology targeted at the simulation of high strain rate,...

Demonstration by Sandia National Laboratories helps to improves cyber training
News Article, March 1, 2017 • Sandia National Laboratories (Sandia), a partner to Team Orlando, hosted a three-day demonstration of Sandia’s Information Design Assurance Red Team (IDART™) training capability on Jan. 31-Feb. 2. The goal of the demonstration was to determine whether Team Orlando could expand its relationship with Sandia to include IDART training for the...
Dan Torgler (left) welcomes Sandia National Laboratories’ William Atkins (center) and Benjamin Anderson.

Denis Mamaluy
Staff Page • Cognitive & Emerging Computing. Biography The CMOS technology is famously approaching its scaling limit: within the next decade or so, nano-scale FET transistors will reach the sub 5-nm physical gate lengths, at which point any further reduction of their sizes will likely become impractical and even impossible due to the...

Denis Ridzal
Staff Page • Optimization & Uncertainty Quantification. See my expanded staff site.

Density Functional Theory
Focus Area • Our research in electronic structure methods, particularly density functional theory (DFT), spans investigations of improved physical approximations (new functionals, time-dependent DFT), development of high-performance quantum simulation codes (SeqQuest), and applications focused on probing microscopic materials chemistry underlying challenging materials problems.  The research encompasses the pursuit for predictive simulations of materials...

Density Functional Theory (DFT)
Page • This page is intended to provide information useful for people using and/or developing density-functional theory based tools for electronic structure calculations. The main focus will be on usage and development of DFT methods within Sandia. If you do not find what you wanted and think we should know about it...

Departments
Page • Cognitive & Emerging Computing Computational Mathematics Computational Multiphysics Computational Multiscale Computational Science Computational Sciences & Math Discrete Math & Optimization Enhanced Decision Making Extreme-scale Computing Machine Intelligence and Vis Optimization & Uncertainty Quantification Quantum Computer Science Scalable Algorithms Scalable Computer Architecture Scalable System Software Scientific Machine Learning Software Engineering &...
Results 126–150 of 482