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1460 researchers awarded contract to provide test and evaluation for IARPA MICrONS Program
News Article, September 1, 2016 • 1460 researchers recently won a contract to provide test and evaluation support for a new IARPA program: Machine Intelligence from Cortical Networks (MICrONS).  The MICrONS program aims to advance a new generation of neural-inspired machine learning algorithms by reverse engineering the algorithms and computations of the brain.  The Sandia team’s...

2013 Dakota releases provide users an array of new features
News Article, May 1, 2013 • Dakota version 5.3, released 1/31/2013, and its partner version 5.3.1, released 5/15/2013, feature new adaptive, sparse, and surrogate-based UQ methods, new Bayesian calibration methods, and improvements to discrete optimization. The new versions also include enhancements to the testing infrastructure, core framework, and portability (including to native Windows). The Dakota user...

2017 Defense Programs Award of Excellence
Award, October 1, 2017 • Other external recognition, National Nuclear Security Administration. Trinity High Performance Computing Team for significant contributions to the Stockpile Stewardship Program

2020 Rising Stars Workshop Supports Women in Computational & Data Sciences
News Article, January 1, 2021 • Rising Stars in Computational & Data Sciences is an intensive academic and research career workshop series for women graduate students and postdocs. Co-organized by Sandia and UT-Austin’s Oden Institute for Computational Engineering & Sciences, Rising Stars brings together top women PhD students and postdocs for technical talks, panels, and networking...
Rising 2020 Stars

5th Annual NICE Workshop
News Article, June 1, 2017 • Neural computing researchers at Sandia National Laboratories helped organize and facilitate the 5th Neuro-Inspired Computational Elements (NICE) Workshop at IBM Almaden in San Jose, CA. The meeting was attended by neural computing researchers from numerous universities, computing software and hardware companies, and national laboratories (including LLNL, LANL, and Oak Ridge)....

A Lightweight Trilinos Solver Interface for Fortran-Based Multiphysics Applications
News Article, April 1, 2016 • Sandia researchers have previously developed a lightweight interface software layer that makes linear solvers from the Sandia Trilinos project accessible to the Fortran-based multiphase flow solver suite named MFIX (https://mfix.netl.doe.gov), originally developed by the National Energy Technology Laboratory (NETL).  Under a current Office of Fossil Energy project named "MFIX-DEM Phi",...
Source: Visualizations prepared by Aytekin Gel & OLCF Visualization Support for Commercial Scale Gasifier Simulations with MFIX as part of INCITE award to NETL (2010) https://mfix.netl.doe.gov/results.php#commercialscalegasifier

A new optimization-based mesh correction method with volume and convexity constraints.
News Article, April 1, 2016 • Mesh motion is at the core of many numerical methods for time dependent flow and structure problems.  Examples include Lagrangian hydrodynamics methods, in which the mesh evolves with time in order to track deformations of the problem domain, and the related Arbitrary Lagrangian-Eulerian methods, which incorporate a mesh rezoning step...
For a divergence free velocity field, superimposition of the mesh obtained with “exact” movement (cells are shaded with different shades of grey) and the mesh obtained without volume correction (Figure 1) and the one with volume correction (Figure 2); the latter is in much closer agreement with the exact mesh than the uncorrected mesh.

A new, optimization-based coupling strategy for nonlocal and local diffusion models
News Article, April 1, 2016 • The use of nonlocal models in science and engineering applications has been steadily increasing over the past decade. The ability of nonlocal theories to accurately capture effects that are difficult or impossible to represent by local partial differential equation (PDE) models motivates and drives the interest in a wide range...
Simulation of a bar containing a discontinuity. The discontinuity extends vertically from the top of the bar halfway through the height of the bar. Dirichlet boundary conditions are applied to the ends of the bar (local domain), circumventing the need to prescribe volume constraints in the nonlocal domain.

A new, optimization-based coupling strategy for nonlocal and local diffusion models
News Article, December 1, 2015 • The use of nonlocal models in science and engineering applications has been steadily increasing over the past decade. The ability of nonlocal theories to accurately capture effects that are difficult or impossible to represent by local partial differential equation (PDE) models motivates and drives the interest in a wide range...
Simulation of a bar containing a discontinuity. The discontinuity extends vertically from the top of the bar halfway through the height of the bar. Dirichlet boundary conditions are applied to the ends of the bar (local domain), circumventing the need to prescribe volume constraints in the nonlocal domain.

A spherical polygon intersection library for climate tracer transport algorithms
News Article, October 1, 2016 • Substantial and ongoing improvements to coupled models of the Earth system have steadily increased our ability to assess future global climate change. Providing quantified predictions of the impacts of global climate change on regional scales and human systems requires advanced global models that resolve multiple spatial scales, capture missing processes,...
An example of a nonconvex, self-intersecting polygon (red) clipped against a convex polygon (dashed blue) to form the green polygon. This kind of calculation is done at every cell of a mesh, at every time step of a simulation.

ACES and NERSC form partnership for next-generation supercomputers, an unprecedented collaboration between NNSA and the Office of Science
News Article, March 1, 2013 • The Alliance for Computing at Extreme Scale (ACES, a collaboration of the NNSA’s Los Alamos National Laboratory and Sandia National Laboratories) and the Office of Science’s National Energy Research Scientific Computing Center (NERSC) have fully integrated as a team as they work towards their respective next-generation supercomputer deployments. The goal...

Advanced Device Technologies
Focus Area • Despite the vast computational power available in today's extreme-scale computing systems, there are still certain types of problems for which that power is inadequate and silicon-based computing devices will likely never be able to solve. Sandia is exploring technologies necessary to enable a new paradigm of computing that goes beyond...

Advanced Release of Draft Technical Specifications for Crossroads
News Article, February 1, 2016 • The first version of the draft technical specifications for Crossroads were released on November 1st 2015 to the vendor community for comment. Crossroads, one of two platforms targeted for delivery in 2020, will be the NNSA’s third Advanced Technology System. Crossroads will be the second platform procured as part of...
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Advanced Tri-lab Software Environment (ATSE)
Project • The Advanced Tri-lab Software Environment (ATSE) is an effort led by Sandia in partnership The Advanced Tri-lab Software Environment (ATSE) is an effort led by Sandia in partnership with Lawrence Livermore National Laboratory and Los Alamos National Laboratory to build an open, modular, extensible, community-engaged, vendor-adaptable software ecosystem that enables...

Aeras Project Develops Next-Generation Atmosphere Model
News Article, April 1, 2016 • The goal of the Aeras LDRD project is to develop a next-generation atmosphere model suitable for a global climate model, with advanced capabilities such as performance portability and embedded uncertainty quantification (UQ). Performance portability will allow us to run our code very efficiently on a diverse set of current and...
Timings for Aeras finite element assembly of the shallow water equations on serial, threaded (using OpenMP), and GPU (using CUDA) architectures. Note that these three implementations were achieved with a single piece of code enabled by the Kokkos package and programming model. Figure (a) represents total finite element assembly time, while (b) isolates the computational time by removing copy times to and from the device.
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