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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Scaling the Ion Trap Quantum Processor

Trapped atomic ions are standards for quantum information processing, serving as quantum memories, hosts of quantum gates in quantum computers and simulators, and nodes of quantum communication networks. Quantum bits based on trapped ions enjoy a rare combination of attributes: They have exquisite coherence properties, they can be prepared and measured with nearly 100% efficiency, and they are readily entangled with each other through the Coulomb interaction or remote photonic interconnects. The outstanding challenge is the scaling of trapped ions to hundreds or thousands of qubits and beyond, at which scale quantum processors can outperform their classical counterparts in certain applications. We review the latest progress and prospects in that effort, with the promise of advanced architectures and new technologies, such as microfabricated ion traps and integrated photonics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Umpire: Application-Focused Management and Coordination of Complex Hierarchical Memory

Advanced architectures like Sierra provide a wide range of memory resources that must often be carefully controlled by the user. These resources have varying capacities, access timing rules, and visibility to different compute resources. Applications must intelligently allocate data in these spaces, and depending on the total amount of memory required, applications may also be forced to move data between different parts of the memory hierarchy. Finally, applications using multiple packages must coordinate effectively to ensure that each package can use the memory resources it needs. To address these challenges, we present Umpire, an application-oriented library for managing memory resources. Specifically, Umpire provides support for querying memory resources, provisioning and allocating memory, and memory introspection. It allows computer scientists and computational physicists to efficiently program the memory hierarchies of current and future high-performance computing architectures, without tying their application to specific hardware or software. In this paper, we describe the design and implementation of Umpire and present case studies from the integration of Umpire into applications that are currently running on Sierra.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Portage, Version 2.0

Portage is a software library system for physics remapping (mapping physics variables from one computational mesh to another) either within a single simulation code or between two disparate simulation codes. Portage is designed to utilize advanced-architecture compute platforms and to be easily extensible by third parties.

Herring, Angela↗
DOE OSTI2017

Pececillo

Pececillo is a proxy-app for the open source Truchas metal processing code (LA-CC-15-097). It implements many of the physics models used in Truchas: free-surface, incompressible Navier-Stokes fluid dynamics (e.g., water waves); heat transport, material phase change, view factor thermal radiation; species advection-diffusion; quasi-static, elastic/plastic solid mechanics with contact; electomagnetics (Maxwell's equations). The models are simplified versions that retain the fundamental computational complexity of the Truchas models while omitting many non-essential features and modeling capabilities. The purpose is to expose Truchas algorithms in a greatly simplified context where computer science problems related to parallel performance on advanced architectures can be more easily investigated. While Pececillo is capable of performing simulations representative of typical Truchas metal casting, welding, and additive manufacturing simulations, it lacks many of the modeling capabilites needed for real applications.

Jibben, Zechariah↗
DOE OSTI2012

Overview of the CoCoMANS Project, with a focus on Algorithms and a Paradigm Shift [Slides]

Project Goals are: 1. Demonstrate a paradigm shift in the simulation approach to each application on an advanced architecture. 2. Deliver a documented computational co-design knowledge-base, built upon an evolving software infrastructure 3. Foster broad, long-term research collaborations with appropriate hardware partners 4. Deepen understanding of, and our experience-base with, consistent, two-way, scale-bridging algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Computing NLTE Opacities -- Node Level Parallel Calculation

Presentation. The goal: to produce a robust library capable of computing reasonably accurate opacities inline with the assumption of LTE relaxed (non-LTE). Near term: demonstrate acceleration of non-LTE opacity computation. Far term (if funded): connect to application codes with in-line capability and compute opacities. Study science problems. Use efficient algorithms that expose many levels of parallelism and utilize good memory access patterns for use on advanced architectures. Portability to multiple types of hardware including multicore processors, manycore processors such as KNL, GPUs, etc. Easily coupled to radiation hydrodynamics and thermal radiative transfer codes.

Astronomy & Astrophysics(79)↗
DOE OSTI2015

ASC Tri-lab Co-design Level 2 Milestone Report 2015

In 2015, the three Department of Energy (DOE) National Laboratories that make up the Advanced Sci- enti c Computing (ASC) Program (Sandia, Lawrence Livermore, and Los Alamos) collaboratively explored performance portability programming environments in the context of several ASC co-design proxy applica- tions as part of a tri-lab L2 milestone executed by the co-design teams at each laboratory. The programming environments that were studied included Kokkos (developed at Sandia), RAJA (LLNL), and Legion (Stan- ford University). The proxy apps studied included: miniAero, LULESH, CoMD, Kripke, and SNAP. These programming models and proxy-apps are described herein. Each lab focused on a particular combination of abstractions and proxy apps, with the goal of assessing performance portability using those. Performance portability was determined by: a) the ability to run a single application source code on multiple advanced architectures, b) comparing runtime performance between \native" and \portable" implementations, and c) the degree to which these abstractions can improve programmer productivity by allowing non-portable implementation details to be hidden from the application developer. This report captures the work that was completed for this milestone, and outlines future co-design work to be performed by application developers, programming environment developers, compiler writers, and hardware vendors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

An Early Quantum Computing Proposal

The D-Wave 2X is the third generation of quantum processing created by D-Wave. NASA (with Google and USRA) and Lockheed Martin (with USC), both own D-Wave systems. Los Alamos National Laboratory (LANL) purchased a D-Wave 2X in November 2015. The D-Wave 2X processor contains (nominally) 1152 quantum bits (or qubits) and is designed to specifically perform quantum annealing, which is a well-known method for finding a global minimum of an optimization problem. This methodology is based on direct execution of a quantum evolution in experimental quantum hardware. While this can be a powerful method for solving particular kinds of problems, it also means that the D-Wave 2X processor is not a general computing processor and cannot be programmed to perform a wide variety of tasks. It is a highly specialized processor, well beyond what NNSA currently thinks of as an “advanced architecture.”A D-Wave is best described as a quantum optimizer. That is, it uses quantum superposition to find the lowest energy state of a system by repeated doses of power and settling stages. The D-Wave produces multiple solutions to any suitably formulated problem, one of which is the lowest energy state solution (global minimum). Mapping problems onto the D-Wave requires defining an objective function to be minimized and then encoding that function in the Hamiltonian of the D-Wave system. The quantum annealing method is then used to find the lowest energy configuration of the Hamiltonian using the current D-Wave Two, two-level, quantum processor. This is not always an easy thing to do, and the D-Wave Two has significant limitations that restrict problem sizes that can be run and algorithmic choices that can be made. Furthermore, as more people are exploring this technology, it has become clear that it is very difficult to come up with general approaches to optimization that can both utilize the D-Wave and that can do better than highly developed algorithms on conventional computers for specific applications. These are all fundamental challenges that must be overcome for the D-Wave, or similar, quantum computing technology to be broadly applicable.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Update on Small Modular Reactors Dynamic System Modeling Tool: Web Application

Previous reports focused on the development of component and system models as well as end-to-end system models using Modelica and Dymola for two advanced reactor architectures: (1) Advanced Liquid Metal Reactor and (2) fluoride high-temperature reactor (FHR). The focus of this report is the release of the first beta version of the web-based application for model use and collaboration, as well as an update on the FHR model. The web-based application allows novice users to configure end-to-end system models from preconfigured choices to investigate the instrumentation and controls implications of these designs and allows for the collaborative development of individual component models that can be benchmarked against test systems for potential inclusion in the model library. A description of this application is provided along with examples of its use and a listing and discussion of all the models that currently exist in the library.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

FY17Q4 Ristra project: Release Version 1.0 of a production toolkit

The Next Generation Code project will release Version 1.0 of a production toolkit for multi-physics application development on advanced architectures. Features of this toolkit will include remap and link utilities, control and state manager, setup, visualization and I/O, as well as support for a variety of mesh and particle data representations. Numerical physics packages that operate atop this foundational toolkit will be employed in a multi-physics demonstration problem and released to the community along with results from the demonstration.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Milestone Completion Report STCO04-1 AAPS: engagements with code teams, vendors, collaborators, developers

The Advanced Architecture and Portability Specialists team (AAPS) worked with a select set of LLNL application teams to develop and/or implement a portability strategy for next-generation architectures. The team also investigated new and updated programming models and helped develop programming abstractions targeting maintainability and performance portability. Significant progress was made on both fronts in FY17, resulting in multiple applications being significantly more prepared for the nextgeneration machines than before.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Computer Science Research Institute (CSRI) Summer Proceedings 2013

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia National Laboratories for focused collaborative research on computer science, computational science, and mathematics problems that are critical to the mission of the laboratories, the Department of Energy, and the United States. The CSRI provides a mechanism by which university researchers learn about and impact national— and global—scale problems while simultaneously bringing new ideas from the academic research community to bear on these important problems. A key component of CSRI programs over the last decade has been an active and productive summer program where students from around the country conduct internships at CSRI. Each student is paired with a Sandia staff member who serves as technical advisor and mentor. The goals of the summer program are to expose the students to research in mathematical and computer sciences at Sandia and to conduct a meaningful and impactful summer research project with their Sandia mentor. Every effort is made to align summer projects with the student's research objectives and all work is coordinated with the ongoing research activities of the Sandia mentor in alignment with Sandia technical thrusts. For the 2013 CSRI Proceedings, research articles have been organized into the following broad technical focus areas — Computational Mathematics and Algorithms, Combinatorial Algorithms and Visualization, Advanced Architectures and Systems Software, Computational Applications — which are well aligned with Sandia's strategic thrusts in computer and information sciences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Building 725 Expansion

In October 2017, Sandia broke ground for a new computing center dedicated to High Performance Computing. The east expansion of Building 725 was entirely conceived of, designed, and built in less than 18 months and is a certified LEED Gold design building, the first of its kind for a data center in the State of New Mexico. This 15,000 square-foot building, with novel energy and water-saving technologies, will house Astra, the first in a new generation of Advanced Architecture Prototype Systems to be deployed by the NNSA and the first of many HPC systems in Building 725 East.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

(U) New xRage Capabilities Enabled by Infrastructure Cleanup

For the past several years, the Eulerian Applications Project at LANL has been working to modernize the xRage code base. Initial efforts, done in FY15-16 and presented in previous work, focused primarily on splitting the code into meaningful packages and levelizing the dependency structure. Ongoing efforts include further refactoring across packages, code cleanup within packages, and writing of unit tests (Fig. 1). When we started the modernization process, one of our major goals was to simplify the code base and enable future code changes, in support of advanced architectures and also of new physics methods. As a result, several recent xRage improvements have been enabled by this infrastructure cleanup. This paper describes some of these improvements, and the infrastructure cleanup tasks that enabled them.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

SNL ATDM Visualization (ECP ST Capability Assessment Report)

The SNL ATDM Data and Visualization work consolidates existing ATDM activities in scalable data management and visualization. Part of the responsibilities of the SNL ATDM Data and Visualization Project is the maintenance and development of visualization resources for ATDM applications on Exascale platforms. The ATDM Scalable Visualization project provides visualization and analysis required to satisfy the needs of the ASC/ATDM applications on next-generation, many-core platforms. This involves many activities including the re-engineering of visualization algorithms, services, and tools that enable ASC customers to carry out data analysis on ASC systems and ACES platforms. Current tools include scalable data analysis software released open source through ParaView, VTK, and Catalyst. We are also both leveraging and contributing to VTK-m, a many-core visualization library, to satisfy our visualization needs on advanced architectures. The scope of the Scalable Visualization under ATDM at SNL is R&D for the programming model and implementation of visualization code for ASC/ATDM projects and ASC/ATDM application support.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Development of MGMC: A proxy Multi-Group Monte Carlo Particle Transport Application

This document details the development and current state of MGMC: a proxy Multi-Group Monte Carlo transport application. The goal of this work was to develop a light-weight Monte Carlo transport solver that could be easily reconfigured to test parallelization strategies targeting advanced architectures and heterogeneous computing environments. Additionally, MGMC is able to act as a proxy-app for testing the development of algorithms and the integration of other libraries and into Monte Carlo transport codes. MGMC is currently able to run in parallel using OpenMP for CPU threads or CUDA for NVIDIA GPUs. MGMC was also used to investigate the using SYCL for portable parallelization targeting either CPU threads, vender-agnostic GPUs, and ARM chips, detailed in Section II. In the process of developing MGMC, several other C++ libraries have been created with the intent for re-use in future research projects and potential inclusion in production-level codes, detailed in Section III. The physics capabilities in MGMC are detailed in Section IV, code verification is detailed in Section V, and performance results are detailed in Section VI.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Summer Proceedings 2019

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researchers to learn about problems in computer and computational science at DOE laboratories. Participants conduct leading-edge research, interact with scientists and engineers at the laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, adaptivity and mesh refinement, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers and heterogeneous computers, data-intensive computing, environments for scalable computing, parallel input/output, advanced architectures, and theoretical computer science. The CSRI Summer Program includes the organization of a weekly seminar series and the publication of this summer proceedings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

CSRI Summer Proceedings 2020

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researchers to learn about problems in computer and computational science at DOE laboratories. Participants conduct leading-edge research, interact with scientists and engineers at the laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, adaptivity and mesh refinement, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, data-intensive computing, environments for scalable computing, parallel input/output, advanced architectures, and theoretical computer science. The CSRI Summer Program is organized by CSRI and typically includes the organization of a weekly seminar series and the publication of a summer proceedings. In 2020, the CSRI summer program was executed completely virtually; all student interns worked from home, due to the COVID-19 pandemic.

97 MATHEMATICS AND COMPUTING↗