The October 2016 issue of Computer magazine on Energy Efficient Computing contains three feature articles co-authored by Sandians, including two articles from staff in the Center for Computing Research. The article “Standardizing Power Monitoring and Control at Exascale” co-authored by Ryan Grant (1423), Michael Levenhagen (1423), Stephen Olivier (1423), Kevin Pedretti (1423), and Jim Laros (1422) describes the Power API project, while “Using Performance-Power Modeling to Improve Energy Efficiency of HPC Applications,” co-written by Jeanine Cook (1422), describes a framework for modeling power that considers application-specific data to predict power consumption. Computer magazine is the flagship publication of the IEEE Computer Society.

October 2016 issue of Computer Magazine

Contact: Brightwell, Ronald B. (Ron)
November 2016
SAND2016-11379E

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A new multigrid linear solver has been developed and deployed for ARIA, a finite element analysis code for the solution of coupled multiphysics problems.  The new linear solver specifically addresses challenges associated with PDE simulations where the number of degrees-of-freedom at each mesh node varies. This scenario frequently arises within ARIA when representing fields with discontinuities at interfaces.  The new iterative solver is able to main these interfaces throughout the internal multigrid hierarchy, which is critical to realizing the solver's rapid convergence rates.  On some problems, the new solver runs 10x faster than anything previously available to the ARIA team.  One problem required 20 minutes to solve with the new solver, whereas the old solver did not converge in 10 hours.  The ARIA team is currently utilizing and accessing the new solver for a broad range of applications such as Navy railgun applications, and NW applications including laser welding, thermal battery modeling, and environmental sensing devices.

X direction velocities for a rising bubble calculation employing the new solver

Contact: Tuminaro, Raymond S.
October 2016
2016-10945 O

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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, and better quantify the uncertainties of model results. The U.S. Dept. of Energy has chartered the laboratories to develop an advanced Earth system modeling capability (ACME) to address these needs and has targeted DOE's upcoming pre-exascale and future exascale computing systems.

Simulating the Earth system at the necessary spatial scales on these new architectures is driving much of the work in center 1400. The DOE LEAP project is focusing on the ACME model's transport algorithms. Transport is a key subcomponent of the ACME atmosphere, ocean, and ice components, and represents the single most expensive computational kernel in the ACME system. The LEAP project is developing a new transport algorithm designed to run well on next generation architectures. The new algorithm combines a multi-moment approach to minimize interprocess communication with a characteristic trajectory algorithm to allow for significantly larger time-steps than with the current method. The implementation uses Kokkos to enable performance portability across traditional CPU systems and upcoming GPU and many-core systems.

Important components of this transport algorithm are spherical polygon intersection and numerical quadrature over the resulting overlap polygons. A spherical polygon is a polygon projected onto a sphere such that the edges are great arcs. We have developed the library SIQK (Spherical Intersection and Quadrature with Kokkos) to provide these capabilities across architectures, including conventional CPU, Intel Xeon Phi, and Nvidia GPU. SIQK intersects an arbitrary (convex or nonconvex and possibly self-intersecting) spherical polygon against a convex polygon. This supports clipping an advected mesh cell against an Eulerian mesh cell. The resulting polygon can be partitioned into triangles, and then SIQK performs numerical quadrature over each triangle.

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.

Contact: Bradley, Andrew Michael
October 2016
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Technology Development Award: Sandia’s GazeAppraise team received a Notable Technology Development award from the Federal Laboratory Consortium (FLC) on Technology Transfer, Mid-Continent Region. The award for GazeAppraise Eye Movement Analysis Software was presented at the annual FLC regional meeting in Albuquerque, September 13-15, 2016. The Mid-Continent region includes 15 states. This year’s meeting was attended by representatives from DOE, DoD and other federal laboratories. The GazeAppraise team is: Mike Haass (1461); Laura McNamara (5346); Danny Rintoul (1462), Andy Wilson (1461) and Laura Matzen (1463).

New Eye Movement Analysis Technology: GazeAppraise software offers a new way to understand human performance as it relates to analysis of dynamic soft-copy images on computer screens. The visual cognition research community lacks software that models how our eyes dynamically recalibrate their trajectory when tracking a moving target across a scene and GazeAppraise is strong at characterizing those “smooth pursuit” eye movements. It has opened up entirely new ways of evaluating search strategies in a wide range of problem areas.

Insights discovered through the use of GazeAppraise will be incorporated into next-generation analysis hardware and software systems. These systems will be used to improve human performance in dynamic image analysis applied to medical diagnostics, airport security, nuclear nonproliferation, and any area where people are working with soft-copy images.

Partnerships Formed: The partnerships the Sandia team has developed create interaction between behavioral scientists, computer scientists, and specialists in other fields, enriching eye tracking research and applications.

Partnerships with two academic partners, Georgia Tech (GT) and the University of Illinois at Urbana-Champaign (UIUC), help Sandia to fine tune the quality of the technology and algorithms in GazeAppraise. The work Sandia and the university partners are doing will be an important part of eye movement research. GT is helping with the value framework that can be used to evaluate information displays. UIUC, with an interdisciplinary team, is helping with image-driven visual saliency and goal-directed visual processing.

A cooperative research and development agreement (CRADA) with EyeTracking, Inc., a company specializing in this field, gives the Sandia team access to a wide array of eye tracking systems and a pathway to commercial applications for this planned technology transfer.

Sandia Researcher Mike Haass demonstrates how an eye tracker under a computer monitor is calibrated to capture his eye movements on the screen.

A summary of how GazeAppraise works collecting samples from many subjects and then using algorithms to categorize the scanpaths.

Contact: Haass, Michael Joseph (Haass)
September 2016
2016-11584 O

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