Results for “Programming models” — Page 46

DOE OSTI2011

DFT Study Revises Interstitial Configurations in HCP Zr

Analysis of experimental result on microstructure evolution in irradiated Zr and alloys has demonstrated that available knowledge on self-interstitial defects in Zr is in contradiction. We therefore have initiated an extensive theoretical and modeling program to clarify this issue. In this report we present first ab initio calculations results of single SIA configurations in Zr. We demonstrate importance of simulations cell size, applied exchange-correlation functional and simulated c/a ratio. The results obtained demonstrate clearly that the most stable configurations are in basal plane and provide some evidences for enhanced interstitial transport along basal planes. The results obtained will be used in generation a new interatomic potential for Zr to be used in large-scale atomistic modeling of mechanisms relevant for radiation-induced microstructure evolution.

36 MATERIALS SCIENCE↗

NASA NTRS1999

NASA Nebraska Space Grant Consortium 1995-1999 Self Evaluation

The NASA Nebraska Space Grant Consortium receives funds from NASA to allow Nebraska colleges and universities to implement balanced programs of research, education and public service related to aeronautics, space science and technology. Nebraska is a capability enhancement state which directs efforts and resources toward developing research infrastructure and enhancing the quality of aerospace research and education for all Nebraskans. Furthermore, the Nebraska Space Grant strives to provide national leadership in applied aspects of aeronautics. Nebraska has met, meets and will continue to meet all requirements set forth by NASA. Nebraska is a top-tier consortium and will continue to be a model program.

Schaaf, Michaela M.↗

DOE OSTI2025

The Viskores User's Guide, Release 1.1

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created Viskores: the visualization toolkit for multi/many-core architectures. Viskores supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. Viskores also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although Viskores provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

The Viskores User's Guide (V.1.0)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created Viskores: the visualization toolkit for multi-/many-core architectures. Viskores supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. Viskores also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although Viskores provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Advances in Multi-Physics Modeling for Parallel Finite Element Code Suite ACE3P

SLAC developed ACE3P code suite is a comprehensive set of parallel finite-element codes for multi-physics modeling of particle accelerators. Running on massively parallel computer platforms for high fidelity and high accuracy simulation, ACE3P enables rapid virtual prototyping of accelerator and RF component design, optimization and analysis. Furthermore, recent advances of ACE3P have been focused on the implementation of advanced numerical algorithms, enhancement of multi-physics capabilities, and improvement of code performance on state-of-the-art high performance computing (HPC) platforms for large-scale RF modeling in accelerator applications and beyond. In this paper, we will present a nonlinear electromagnetic (EM) eigensolver for damping calculation of resonant modes for cavities coupled with waveguides, the thermal solver for accurate evaluation of heat loads in superconducting RF (SRF) cavity power coupler, the elastic solver for investigation of SRF cavity cryomodule (CM) bowing due to thermal effect, the frequency domain mechanical solver for studying SRF cavity mechanical oscillation modes, the particle tracking code for dark current simulation in SRF CM using a hybrid MPI+OpenMP parallel programing model, the time domain solver for high fidelity modeling of EM wave propagation for medical device in human body.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1981

Modelling the high-latitude ionosphere

Results of an ionospheric model program are presented which demonstrate the extreme variability of the steady state, daytime, ionospheric F region electron density and ion composition due to both neutral atmospheric changes with solar cycle, season and magnetic activity, and to the effects of ionospheric drifts caused by perpendicular electric fields. Consideration is given to the time history of the ionospheric plasma as it undergoes convective motion due to the combined effects of corotation forces and electromagnetic forces which results from the mapping of the magnetospheric cross tail electric field to the rotating ionosphere. A simple model of the convection pattern is described. The model calculates the net effect of the tendency for the plasma to corotate about the geographic pole and the E sub Bar times B sub Bar velocity induced by a perpendicular electric field mapped to a circle centered about a point 5 deg antisunward of the geomagnetic pole and oriented such that the equipotentials are parallel to the noon midnight meridian. This convection pattern shows the generally accepted features of high latitude convection, but because of the offset between the geographic and geomagnetic poles a marked universal time dependence in these features is predicted.

Raitt, W. J.↗

NASA NTRS2003

Automated Modeling and Simulation Using the Bond Graph Method for the Aerospace Industry

Bond graph modeling was originally developed in the late 1950s by the late Prof. Henry M. Paynter of M.I.T. Prof. Paynter acted well before his time as the main advantage of his creation, other than the modeling insight that it provides and the ability of effectively dealing with Mechatronics, came into fruition only with the recent advent of modern computer technology and the tools derived as a result of it, including symbolic manipulation, MATLAB, and SIMULINK and the Computer Aided Modeling Program (CAMPG). Thus, only recently have these tools been available allowing one to fully utilize the advantages that the bond graph method has to offer. The purpose of this paper is to help fill the knowledge void concerning its use of bond graphs in the aerospace industry. The paper first presents simple examples to serve as a tutorial on bond graphs for those not familiar with the technique. The reader is given the basic understanding needed to appreciate the applications that follow. After that, several aerospace applications are developed such as modeling of an arresting system for aircraft carrier landings, suspension models used for landing gears and multibody dynamics. The paper presents also an update on NASA's progress in modeling the International Space Station (ISS) using bond graph techniques, and an advanced actuation system utilizing shape memory alloys. The later covers the Mechatronics advantages of the bond graph method, applications that simultaneously involves mechanical, hydraulic, thermal, and electrical subsystem modeling.

Granda, Jose J.↗

DOE OSTI2021

VTK-m User's' Guide (V.1.7)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures. VTK-m supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. VTK-m also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although VTK-m provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction. VTK-m simplifies the development of parallel scientific visualization algorithms by providing a framework of supporting functionality that allows developers to focus on visualization operations. Consider the listings in Figure 1.1 that compares the size of the implementation for the Marching Cubes algorithm in VTK-m with the equivalent reference implementation in the CUDA software development kit. Because VTK-m internally manages the parallel distribution of work and data, the VTK-m implementation is shorter and easier to maintain. Additionally, VTK-m provides data abstractions not provided by other libraries that make code written in VTK-m more versatile.This book includes contributions from the VTK-m community including the VTK-m development team and the user community.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

VTK-m User's Guide (V.1.8)

Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures. VTK-m supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. VTK-m also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although VTK-m provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction. VTK-m simplifies the development of parallel scientific visualization algorithms by providing a framework of supporting functionality that allows developers to focus on visualization operations. Additionally, VTK-m provides data abstractions not provided by other libraries that make code written in VTK-m more versatile.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

The VTK-m Users' Guide (V.1.9)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures. VTK-m supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. VTK-m also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although VTK-m provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction. VTK-m simplifies the development of parallel scientific visualization algorithms by providing a framework of supporting functionality that allows developers to focus on visualization operations. Consider the listings in Figure 1.1 that compares the size of the implementation for the Marching Cubes algorithm in VTK-m with the equivalent reference implementation in the CUDA software development kit. Because VTK-m internally manages the parallel distribution of work and data, the VTK-m implementation is shorter and easier to maintain. Additionally, VTK-m provides data abstractions not provided by other libraries that make code written in VTK-m more versatile.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

The VTK-m Users' Guide (V.2.0)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures. VTK-m supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. VTK-m also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although VTK-m provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction. VTK-m simplifies the development of parallel scientific visualization algorithms by providing a framework of supporting functionality that allows developers to focus on visualization operations. Consider the listings in Figure 1.1 that compares the size of the implementation for the Marching Cubes algorithm in VTK-m with the equivalent reference implementation in the CUDA software development kit. Because VTK-m internally manages the parallel distribution of work and data, the VTK-m implementation is shorter and easier to maintain. Additionally, VTK-m provides data abstractions not provided by other libraries that make code written in VTK-m more versatile.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

The VTK-m User's Guide (V. 2.2)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures. VTK-m supports a number of algorithms and the ability to design further algorithms through a top-down design with an emphasis on extreme parallelism. VTK-m also provides support for finding and building links across topologies, making it possible to perform operations that determine manifold surfaces, interpolate generated values, and find adjacencies. Although VTK-m provides a simplified high-level interface for programming, its template-based code removes the overhead of abstraction.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Model for Collaboration among Carriers to Reduce Empty Container Truck Trips

In recent years, intermodal transport has become an increasingly attractive alternative to freight shippers. However, the current intermodal freight transport is not as efficient as it could be. Oftentimes an empty container needs to be transported from the empty container depot to the shipper, and conversely, an empty container needs to be transported from the receiver to the empty container depot. These empty container movements decrease the freight carrier’s profit, as well as increase traffic congestion, decrease roadway safety, and add unnecessary emissions to the environment. To this end, our study evaluates a potential collaboration strategy to be used by carriers for domestic intermodal freight transport based on an optimization approach to reduce the number of empty container trips. A binary integer-linear programming model is developed to determine each freight carrier’s optimal schedule while minimizing its operating cost. The model ensures that the cost for each carrier with collaboration is less than or equal to its cost without collaboration. It also ensures that average savings from the collaboration are shared equally among all participating carriers. Additionally, two stochastic models are provided to account for uncertainty in truck travel times. The proposed collaboration strategy is tested using empirical data and is demonstrated to be effective in meeting all of the shipment constraints.

42 ENGINEERING↗

DOE OSTI2018

Battery and backup generator sizing for a resilient microgrid under stochastic extreme events

Owing to the recent power outages caused by extreme events, installing battery energy storage and backup generators is important to improve resiliency for a grid-tied microgrid. In the design stage, the event occurrence time and duration, which are highly uncertain and cannot be effectively predicted, may affect the needed battery and backup generator capacity but are usually assumed to be pre-determined in utility planning tools. This study investigates the optimal battery and backup generator sizing problem considering the stochastic event occurrence time and duration for the grid-tied microgrid under islanded operation. The reliability requirement is quantified by the mean value of the critical customer interruption time in each stochastic islanding time window (ITW), whose length is the duration and the centre is the occurrence time. The stochastic ITW constraint is then transformed to a probability-weighted expression to derive an equivalent Mixed Integer Linear Programming model. Numerical simulations on a realistic grid-tied PV-based microgrid demonstrate that the total cost is reduced by 11.5% considering the stochastic ITW, compared with the deterministic ITW under the same reliability requirement.

24 POWER TRANSMISSION AND DISTRIBUTION↗

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 OSTI2018

Nonparametric Prediction Intervals of Wind Power via Linear Programming

This letter proposes a machine learning-based linear programming model that quickly establishes the nonparametric prediction intervals of wind power by integrating extreme learning machine and quantile regression. The proportions of quantiles can be adaptively determined via sensitivity analysis. The proposed method has been proven to be significantly efficient and reliable, with a high application potential in power systems.

extreme learning machine↗

DOE OSTI2016

A Distributed OpenCL Framework using Redundant Computation and Data Replication

Applications written solely in OpenCL or CUDA cannot execute on a cluster as a whole. Most previous approaches that extend these programming models to clusters are based on a common idea: designating a centralized host node and coordinating the other nodes with the host for computation. However, the centralized host node is a serious performance bottleneck when the number of nodes is large. In this paper, we propose a scalable and distributed OpenCL framework called SnuCL-D for large-scale clusters. SnuCL-D's remote device virtualization provides an OpenCL application with an illusion that all compute devices in a cluster are confined in a single node. To reduce the amount of control-message and data communication between nodes, SnuCL-D replicates the OpenCL host program execution and data in each node. We also propose a new OpenCL host API function and a queueing optimization technique that significantly reduce the overhead incurred by the previous centralized approaches. To show the effectiveness of SnuCL-D, we evaluate SnuCL-D with a microbenchmark and eleven benchmark applications on a large-scale CPU cluster and a medium-scale GPU cluster.

Kim, Junghyun↗

DOE OSTI2018

Stochastic Programming Approach for Resource Selection under Demand Uncertainty

Cost-efficient selection and scheduling of a subset of geographically distributed resources to meet the demands of a scientific workflow is a challenging problem. The problem is exacerbated by uncertainties in demand and availability of resources. In this paper, we present a stochastic optimization based framework for robust decision making in the selection of distributed resources over a planning horizon under demand uncertainty. We present a novel two-stage stochastic programming model for resource selection, and implement an L-shaped decomposition algorithm to solve this model. A Sample Average Approximation algorithm is integrated to enable stochastic optimization to solve problems with a large number of scenarios. Using the metric of stochastic solution, we demonstrate up to 30% cost reduction relative to solutions without explicit consideration of demand uncertainty for a 24-month problem. We also demonstrate up to 54% cost reduction relative to a previously developed solution for a 36-month problem. We further argue that the composition of resources selected is superior to solutions computed without explicit consideration of uncertainties. Given the importance of resource selection and scheduling of complex scientific workflows, especially in the context of commercial cloud computing, we believe that our novel stochastic programming framework will benefit many researchers as well as users of distributed computing resources.

scientific workflows, task scheduling, optimizatio↗