ART_data_analyzer: Automating parallelized computations to study the evolution of materials
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97 MATHEMATICS AND COMPUTING↗
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Results for “parallel computations”
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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Parallel Computation and Visualization of Three-dimensional, Time-dependent, Thermal Convective Flows
A high-resolution numerical study on parallel systems is reported on three-dimensional, time-dependent, thermal convective flows. A parallel implentation on the finite volume method with a multigrid scheme is discussed, and a parallel visualization systemm is developed on distributed systems for visualizing the flow.
parallelization visualization thermal convectionl ↗
Optimization on a Network-based Parallel Computer System for Supersonic Laminar Wing Design
A set of Computational Fluid Dynamics (CFD) routines and flow transition prediction tools are integrated into a network based parallel numerical optimization routine. Through this optimization routine, the design of a 2-D airfoil and an infinitely swept wing will be studied in order to advance the design cycle capability of supersonic laminar flow wings. The goal of advancing supersonic laminar flow wing design is achieved by wisely choosing the design variables used in the optimization routine. The design variables are represented by the theory of Fourier series and potential theory. These theories, combined with the parallel CFD flow routines and flow transition prediction tools, provide a design space for a global optimal point to be searched. Finally, the parallel optimization routine enables gradient evaluations to be performed in a fast and parallel fashion.
Garcia, Joseph A.↗
Extreme-scale EV charging infrastructure planning for last-mile delivery using high-performance parallel computing
Here, this paper addresses stochastic charger location and allocation problems under queue congestion for last-mile delivery using electric vehicles (EVs). The objective is to decide where to open charging stations and how many chargers of each type to install, subject to budgetary and waiting-time constraints. We formulate the problem as a mixed-integer non-linear program, where each station-charger pair is modeled as a multiserver queue with stochastic arrivals and service times to capture the notion of waiting in fleet operations. The model is extremely large, with billions of variables and constraints for a typical metropolitan area; even loading the model in solver memory is difficult, let alone solving it. To address this challenge, we develop a Lagrangian-based dual decomposition framework that decomposes the problem by station and leverages parallelization on high-performance computing systems, where the subproblems are solved by using a cutting plane method and their solutions are collected at the master level. We also develop a three-step rounding heuristic to transform the fractional subproblem solutions into feasible integral solutions. Computational experiments on data from the Chicago metropolitan area with hundreds of thousands of households and thousands of candidate stations show that our approach produces high-quality solutions in cases where existing exact methods cannot even load the model in memory. We also analyze various policy scenarios, demonstrating that combining existing depots with newly built stations under multiagency collaboration substantially reduces costs and congestion. These findings offer a scalable and efficient framework for developing sustainable large-scale EV charging networks.
Capacity allocation↗
Advances in Modeling the Generation of the Geomagnetic Field by the Use of Massively Parallel Computers and Profound Optimization
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optimization psuedo-spectral parallel MPP Dynamo E↗
CFD Research, Parallel Computation and Aerodynamic Optimization
During the last five years, CFD has matured substantially. Pure CFD research remains to be done, but much of the focus has shifted to integration of CFD into the design process. The work under these cooperative agreements reflects this trend. The recent work, and work which is planned, is designed to enhance the competitiveness of the US aerospace industry. CFD and optimization approaches are being developed and tested, so that the industry can better choose which methods to adopt in their design processes. The range of computer architectures has been dramatically broadened, as the assumption that only huge vector supercomputers could be useful has faded. Today, researchers and industry can trade off time, cost, and availability, choosing vector supercomputers, scalable parallel architectures, networked workstations, or heterogenous combinations of these to complete required computations efficiently.
Ryan, James S.↗
CFD research, parallel computation and aerodynamic optimization
Over five years of research in Computational Fluid Dynamics and its applications are covered in this report. Using CFD as an established tool, aerodynamic optimization on parallel architectures is explored. The objective of this work is to provide better tools to vehicle designers. Submarine design requires accurate force and moment calculations in flow with thick boundary layers and large separated vortices. Low noise production is critical, so flow into the propulsor region must be predicted accurately. The High Speed Civil Transport (HSCT) has been the subject of recent work. This vehicle is to be a passenger vehicle with the capability of cutting overseas flight times by more than half. A successful design must surpass the performance of comparable planes. Fuel economy, other operational costs, environmental impact, and range must all be improved substantially. For all these reasons, improved design tools are required, and these tools must eventually integrate optimization, external aerodynamics, propulsion, structures, heat transfer and other disciplines.
Ryan, James S.↗
Finite Element Modeling on Scalable Parallel Computers
A coupled finite element-integral equation was developed to model fields scattered from inhomogenous, three-dimensional objects of arbitrary shape. This paper outlines how to implement the software on a scalable parallel processor.
modeling three-dimensional coupled finite element ↗
Parallel computation in a three-dimensional elastic-plastic finite-element analysis
CRAY 2 and CRAY Y-MP evaluation runs are undertaken for a three-dimensional, elastoplastic FEM code implementation of the 'autotasking' parallel-processing technique, which is used in all code components except the matrix-equation solver. For a typical example problem in the case of a four-processor CRAY 2, a speedup factor of 2.1 was found achievable in a dedicated environment, and 1.7 in a multiuser environment; for a three-processor CRAY Y-MP, speedup in a multiuser environment was about 2.4. Only minimal effort was required to implement autotasking in this implementation code.
Shivakumar, K. N.↗
Multilevel decomposition of complete vehicle configuration in a parallel computing environment
This research summarizes various approaches to multilevel decomposition to solve large structural problems. A linear decomposition scheme based on the Sobieski algorithm is selected as a vehicle for automated synthesis of a complete vehicle configuration in a parallel processing environment. The research is in a developmental state. Preliminary numerical results are presented for several example problems.
Bhatt, Vinay↗
Asynchronous numerical solution of PDEs on parallel computers
Asynchronous and partially-synchronous finite difference schemes are investigated for the one-dimensional steady-state and nonsteady-state heat equation, respectively. It is shown experimentally that the asynchronous scheme runs twice as fast as the parallel synchronous scheme. For relatively small values of time levels, however, the asynchronous scheme produces the least accurate results, while the partially-asynchronous scheme is almost as accurate as its synchronous counterpart.
Amitai, Dganit↗
Parallel Computing for Module-Based Computational Experiment
Large-scale scientific code plays an important role in scientific researches. In order to facilitate module and element evaluation in scientific applications, we introduce a unit testing framework and describe the demand for module-based experiment customization. We then develop a parallel version of the unit testing framework to handle long-term simulations with a large amount of data. Specifically, we apply message passing based parallelization and I/O behavior optimization to improve the performance of the unit testing framework and use profiling result to guide the parallel process implementation. Finally, we present a case study on litter decomposition experiment using a standalone module from a large-scale Earth System Model. This case study is also a good demonstration on the scalability, portability, and high-efficiency of the framework.
Yao, Zhuo↗
Parallel Computing for Massive Dynamic Contingency Analysis
The first step towards running PSLF in a high-performance computing (HPC) environment was porting PSLF to the Linux operating system from the current shipping target of MS Windows. The target machine was the LLNL Quartz system which is a Linux cluster configured for large parallel jobs. It has 2,688 batch nodes with Dual Socket Intel E5-2695 v4 (Broadwell) CPUs with 18 cores each, with a total of 344,064 GB of memory, each node having 128 GB of memory. Nodes are connected with an Intel Omni-Path 100 GB/s interconnect. Quartz runs the Tri-Laboratory Operating System Software (TOSS) that includes Red Hat Enterprise Linux (RHEL) distribution used on the LLNL HPC machines.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Developing Multiphysics, Integrated, High-Fidelity, Massively Parallel Computational Capabilities for Fusion Applications Using MOOSE
As the need for fusion as a clean, sustainable, and abundant energy source grows internationally, so does the need for multiphysics, computational tools to model, study, and predict the complex interactions between plasma, materials, and engineering processes. These tools have a crucial role to play in solving scientific and engineering challenges and accelerating fusion energy deployment. To address these needs, modeling capabilities should enable massively parallel, multiphysics, fully integrated high-fidelity simulations of fusion systems. Additional attributes, such as being open source and modular while maintaining high software quality assurance standards will maximize impact by ensuring accessibility for all and wide acceptance, rapid expansion and development, as well as reliability, efficiency, and robustness. In this paper, we describe how the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which has a track record of success in the fission space thanks to the attributes listed above, can be leveraged in the fusion energy field. We highlight key successes of the MOOSE application in the fission space and describe how MOOSE has been and is being applied to fusion applications in the United States---e.g., Tritium Migration Analysis Program, version 8 (TMAP8), MOOSE Fusion Module, Fusion ENergy Integrated multiphys-X (FENIX)---and the United Kingdom---e.g., AURORA, Achlys, Apollo. These efforts aim to establish a suite of tools that can be further extended to accelerate fusion energy deployment.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
A Parallel Computing Infrastructure for Building Energy Simulation
In order to study grid-interactive efficient buildings, Pacific Northwest National Laboratories (PNNL) needs an infrastructure for urban-scale building energy modeling. Such an infrastructure should be fast, scalable, and easy-to-use. Given a set of data from the Energy Information Administration’s Commercial Building Energy Consumption Survey (CBECS) and tool to translate survey data into simulation inputs, this project aimed to conduct the simulation of the entire dataset in parallel. Before running the simulations, the necessary software was bundled into a container for use on the PNNL supercomputing network. Then, the parallel simulation workflow was designed using GNU Make, a file creation software, and submitted to a supercomputing partition which could run hundreds of simulations simultaneously. The EnergyPlus simulations output hourly electric meter data for each CBECS sample, which represents the electricity consumption of similar commercial buildings across the United States. Analyzing and visualizing the meter data is important to the future of the work, and this project wrote code to make common analysis methods simple, fast, and accessible. Moving forwards, the model will need to be expanded to include data from other sources and its accuracy will need to be improved and eventually validated.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Performance portability study for massively parallel computational fluid dynamics application on scalable heterogeneous architectures
Patient-specific hemodynamic simulations have the possibility to greatly improve both the diagnosis and treatment of a variety of vascular diseases. Portability will enable wider adoption of computational fluid dynamics (CFD) applications in the biomedical research community and targeting to platforms ideally suited to different vascular regions. Here, we introduce a case study in performance portability that assesses (1) the ease of porting an MPI application optimized for one specific architecture to new platforms using variants of hybrid MPI+X programming models; (2) performance portability seen when simulating blood flow in three different vascular regions on diverse heterogeneous architectures; (3) model-based performance prediction for future architectures; and (4) performance scaling of the hybrid MPI+X programming on parallel heterogeneous systems. We report on the lessons learned in porting HARVEY, a massively parallel CFD application, from traditional multicore CPUs to diverse heterogeneous architectures ranging from NVIDIA/AMD GPUs to Intel MICs and Altera FPGAs.
97 MATHEMATICS AND COMPUTING↗
Implementation and analysis of a Navier-Stokes algorithm on parallel computers
The results of the implementation of a Navier-Stokes algorithm on three parallel/vector computers are presented. The object of this research is to determine how well, or poorly, a single numerical algorithm would map onto three different architectures. The algorithm is a compact difference scheme for the solution of the incompressible, two-dimensional, time-dependent Navier-Stokes equations. The computers were chosen so as to encompass a variety of architectures. They are the following: the MPP, an SIMD machine with 16K bit serial processors; Flex/32, an MIMD machine with 20 processors; and Cray/2. The implementation of the algorithm is discussed in relation to these architectures and measures of the performance on each machine are given. The basic comparison is among SIMD instruction parallelism on the MPP, MIMD process parallelism on the Flex/32, and vectorization of a serial code on the Cray/2. Simple performance models are used to describe the performance. These models highlight the bottlenecks and limiting factors for this algorithm on these architectures. Finally, conclusions are presented.
Fatoohi, Raad A.↗