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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Finite element analysis in a minicomputer/mainframe environment

Design considerations were evaluated for general purpose finite element systems to maximize performance when installed on distributed computer hardware/software systems. It is shown how the features of current minicomputers complement those of a modular implementation of the finite element method for increasing the control, speed, and visibility (interactive graphics) in solving structural problems at reduced cost. The approach used is to implement a finite element system in a distributed computer environment to solve structural problems and to explore alternatives in distributing finite element computations.

Storaasli, O. O.↗
DOE OSTI2025

Harnessing distributed GPU computing for generalizable graph convolutional networks in power grid reliability assessments

Although machine learning (ML) has emerged as a powerful tool for rapidly assessing grid contingencies, prior studies have largely considered a static grid topology in their analyses. This limits their application, since they need to be re-trained for every new topology. Here, this paper explores the development of generalizable graph convolutional network (GCN) models by pre-training them across a range of grid topologies and contingency types. We found that a GCN model with auto-regressive moving average (ARMA) layers with a line graph representation of the grid offered the best predictive performance in predicting voltage magnitudes (VM) and voltage angles (VA). We introduced the concept of phantom nodes to consider disparate grid topologies with a varying number of nodes and lines. For pre-training the GCN ARMA model across a variety of topologies, distributed graphics processing unit (GPU) computing afforded us significant training scalability. The predictive performance of this model on grid topologies that were part of the training data is substantially better than the direct current (DC) approximation. Although direct application of the pre-trained model to topologies that are not part of the grid is not particularly satisfactory, fine-tuning with small amounts of data from a specific topology of interest significantly improves predictive performance. In general, this paper highlights the feasibility of training large-scale GNN models to assess the reliability of power grids by considering a wide variety of grid topologies and contingency types. With the advent of foundational models in ML and the exponential increase in GPU computing clusters, generalizable ML models will significantly enhance how utilities manage power systems and make decisions in real-time or near-real-time.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1997

Distributed-Memory Computing With the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA)

The Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA), a Navier-Stokes solver, has been modified for use in a parallel, distributed-memory environment using the Message-Passing Interface (MPI) standard. A standard domain decomposition strategy is used in which the computational domain is divided into subdomains with each subdomain assigned to a processor. Performance is examined on dedicated parallel machines and a network of desktop workstations. The effect of domain decomposition and frequency of boundary updates on performance and convergence is also examined for several realistic configurations and conditions typical of large-scale computational fluid dynamic analysis.

Riley, Christopher J.↗
DOE OSTI2016

Staghorn: An Automated Large-Scale Distributed System Analysis Platform

Conducting experiments on large-scale distributed computing systems is becoming significantly easier with the assistance of emulation. Researchers can now create a model of a distributed computing environment and then generate a virtual, laboratory copy of the entire system composed of potentially thousands of virtual machines, switches, and software. The use of real software, running at clock rate in full virtual machines, allows experiments to produce meaningful results without necessitating a full understanding of all model components. However, the ability to inspect and modify elements within these models is bound by the limitation that such modifications must compete with the model, either running in or alongside it. This inhibits entire classes of analyses from being conducted upon these models. We developed a mechanism to snapshot an entire emulation-based model as it is running. This allows us to \freeze time" and subsequently fork execution, replay execution, modify arbitrary parts of the model, or deeply explore the model. This snapshot includes capturing packets in transit and other input/output state along with the running virtual machines. We were able to build this system in Linux using Open vSwitch and Kernel Virtual Machines on top of Sandia's emulation platform Firewheel. This primitive opens the door to numerous subsequent analyses on models, including state space exploration, debugging distributed systems, performance optimizations, improved training environments, and improved experiment repeatability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Deep Learning on Operational Facility Data Related to Large-Scale Distributed Area Scientific Workflows

Abstract—Distributed computing platforms provide a robust mechanism to perform large-scale computations by splitting the task and data among multiple locations, possibly located thousands of miles apart geographically. This distribution of resources can lead to benefits such as redundancy of data, engagement with scientific teams that involve a diverse group of domain experts distributed spatially around the globe. It allows scientists to share their expertise and data with everyone and achieve insights by deploying collective intelligence of entire team. However, this distributed computing comes with its associated problems such as rampant duplication of file transfers increasing congestion, long job completion times, unexpected site crashing, suboptimal data transfer rates, unpredictable reliability in a time range, overshooting congestion, suboptimal usage of storage elements. In addition, each sub-system becomes a potential failure node that can trigger system wide disruptions.

Machine Learning, Provenance, Time Series, Semanti↗
DOE OSTI2023

The globus compute dataset: An open function-as-a-service dataset from the edge to the cloud

Here we present a unique function-as-a-service (FaaS) dataset capturing the use of the Globus Compute (previously funcX) platform. Globus Compute implements a federated model via which users may deploy endpoints on arbitrary remote computers, from the edge to high performance computing (HPC) cluster, and they may then invoke Python functions on those endpoints via a reliable cloud -hosted service. The dataset covers 31 weeks and includes 2121472 task submissions from 252 users executed on 580 remote computing endpoints. It includes 277386 registered functions. We describe the dataset and various observations, some that are similar to other FaaS datasets, for example, that 74% of tasks run for less than 1 s, and some that are unique to Globus Compute, for example, that endpoints are used in different ways and that the majority of functions are related to scientific computing and machine learning. To the best of our knowledge, this dataset represents the first federated FaaS dataset that includes user workloads, distributed computing endpoints, and analysis of registered function bodies. We expect the dataset to be useful for researching FaaS architectures, workload modeling, container warming, and other distributed computing architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

EINSTEIN@HOME DISCOVERY OF FOUR YOUNG GAMMA-RAY PULSARS IN FERMI LAT DATA

We report the discovery of four gamma-ray pulsars, detected in computing-intensive blind searches of data from the Fermi Large Area Telescope (LAT). The pulsars were found using a novel search approach, combining volunteer distributed computing via Einstein@Home and methods originally developed in gravitational-wave astronomy. The pulsars PSRs J0554+3107, J1422–6138, J1522–5735, and J1932+1916 are young and energetic, with characteristic ages between 35 and 56 kyr and spin-down powers in the range 6 × 10{sup 34}—10{sup 36} erg s{sup –1}. They are located in the Galactic plane and have rotation rates of less than 10 Hz, among which the 2.1 Hz spin frequency of PSR J0554+3107 is the slowest of any known gamma-ray pulsar. For two of the new pulsars, we find supernova remnants coincident on the sky and discuss the plausibility of such associations. Deep radio follow-up observations found no pulsations, suggesting that all four pulsars are radio-quiet as viewed from Earth. These discoveries, the first gamma-ray pulsars found by volunteer computing, motivate continued blind pulsar searches of the many other unidentified LAT gamma-ray sources.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1978

Architectures for fault-tolerant spacecraft computers

This paper summarizes the results of a long-term research program in fault-tolerant computing for spacecraft on-board processing. In response to changing device technology this program has progressed from the design of a fault-tolerant uniprocessor to the development of fault-tolerant distributed computer systems. The unusual requirements of spacecraft computing are described along with the resulting real-time computer architectures. The following aspects of these designs are discussed: (1) architectural features to minimize complexity in the distributed computer system, (2) fault-detection and recovery, (3) techniques to enhance reliability and testability, and (4) design approaches for LSI implementation.

Rennels, D. A.↗
DOE OSTI2013

Solid Oxide Fuel Cell - Multi-Physics and GUI

SOFC-MP is a simulation tool developed at PNNL to evaluate the tightly coupled multi-physical phenomena in SOFCs. The purpose of the tool is to allow SOFC manufacturers to numerically test changes in planar stack design to meet DOE technical targets. The SOFC-MP 2D module is designed for computational efficiency to enable rapid engineering evaluations for operation of tall symmetric stacks. It can quickly compute distributions for the current density, voltage, temperature, and species composition in tall stacks with co-flow or counter-flow orientations. The 3D module computes distributions in entire 3D domain and handles all planner configurations: co-flow, counter-flow, and cross-flow. The detailed data from 3D simulation can be used as input for structural analysis. SOFC-MP GUI integrates both 2D and 3D modules, and it provides user friendly pre-processing and post-processing capabilities.

Lai, Kevin↗
DOE OSTI2022

Enabling machine learning-ready HPC ensembles with Merlin

With the growing complexity of computational and experimental facilities, many scientific researchers are turning to machine learning (ML) techniques to analyze large scale ensemble data. With complexities such as multi-component workflows, heterogeneous machine architectures, parallel file systems, and batch scheduling, care must be taken to facilitate this analysis in a high performance computing (HPC) environment. Here, we present Merlin, a workflow framework to enable large ML-friendly ensembles of scientific HPC simulations. By augmenting traditional HPC with distributed compute technologies, Merlin aims to lower the barrier for scientific subject matter experts to incorporate ML into their analysis. As a producer–consumer workflow model, Merlin enables multi-machine, cross-batch job, dynamically allocated yet persistent workflows capable of utilizing surge-compute resources. Key features of Merlin are a flexible HPC-centric interface, low per-task overhead, multi-tiered fault recovery, and a hierarchical sampling algorithm that allows for $\mathscr{O}$(N) task execution and $\mathscr{O}$(N ln N) task queuing to ensembles of millions of tasks. In addition to Merlin’s design, we test the algorithm’s performance in an HPC center and demonstrate the ability to enqueue 40 million simulations in 100 s, with a 30 millisecond per-task overhead that is independent of ensemble size. Finally, we describe some example applications that Merlin has enabled on leadership-class HPC resources, such as the ML-augmented optimization of nuclear fusion experiments and the calibration of infectious disease models to study the progression of and possible mitigation strategies for COVID-19.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

MOLNs: A Cloud Platform for Interactive, Reproducible, and Scalable Spatial Stochastic Computational Experiments in Systems Biology Using PyURDME

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. In conclusion, MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

Parallel processing for scientific computations

The scope of this project dealt with the investigation of the requirements to support distributed computing of scientific computations over a cluster of cooperative workstations. Various experiments on computations for the solution of simultaneous linear equations were performed in the early phase of the project to gain experience in the general nature and requirements of scientific applications. A specification of a distributed integrated computing environment, DICE, based on a distributed shared memory communication paradigm has been developed and evaluated. The distributed shared memory model facilitates porting existing parallel algorithms that have been designed for shared memory multiprocessor systems to the new environment. The potential of this new environment is to provide supercomputing capability through the utilization of the aggregate power of workstations cooperating in a cluster interconnected via a local area network. Workstations, generally, do not have the computing power to tackle complex scientific applications, making them primarily useful for visualization, data reduction, and filtering as far as complex scientific applications are concerned. There is a tremendous amount of computing power that is left unused in a network of workstations. Very often a workstation is simply sitting idle on a desk. A set of tools can be developed to take advantage of this potential computing power to create a platform suitable for large scientific computations. The integration of several workstations into a logical cluster of distributed, cooperative, computing stations presents an alternative to shared memory multiprocessor systems. In this project we designed and evaluated such a system.

Alkhatib, Hasan S.↗
NASA NTRS2005

Support for User Interfaces for Distributed Systems

An extensible Java(TradeMark) software framework supports the construction and operation of graphical user interfaces (GUIs) for distributed computing systems typified by ground control systems that send commands to, and receive telemetric data from, spacecraft. Heretofore, such GUIs have been custom built for each new system at considerable expense. In contrast, the present framework affords generic capabilities that can be shared by different distributed systems. Dynamic class loading, reflection, and other run-time capabilities of the Java language and JavaBeans component architecture enable the creation of a GUI for each new distributed computing system with a minimum of custom effort. By use of this framework, GUI components in control panels and menus can send commands to a particular distributed system with a minimum of system-specific code. The framework receives, decodes, processes, and displays telemetry data; custom telemetry data handling can be added for a particular system. The framework supports saving and later restoration of users configurations of control panels and telemetry displays with a minimum of effort in writing system-specific code. GUIs constructed within this framework can be deployed in any operating system with a Java run-time environment, without recompilation or code changes.

Eychaner, Glenn↗
DOE OSTI2011

Implementing High Performance Remote Method Invocation in CCA

We report our effort in engineering a high performance remote method invocation (RMI) mechanism for the Common Component Architecture (CCA). This mechanism provides a highly efficient and easy-to-use mechanism for distributed computing in CCA, enabling CCA applications to effectively leverage parallel systems to accelerate computations. This work is built on the previous work of Babel RMI. Babel is a high performance language interoperability tool that is used in CCA for scientific application writers to share, reuse, and compose applications from software components written in different programming languages. Babel provides a transparent and flexible RMI framework for distributed computing. However, the existing Babel RMI implementation is built on top of TCP and does not provide the level of performance required to distribute fine-grained tasks. We observed that the main reason the TCP based RMI does not perform well is because it does not utilize the high performance interconnect hardware on a cluster efficiently. We have implemented a high performance RMI protocol, HPCRMI. HPCRMI achieves low latency by building on top of a low-level portable communication library, Aggregated Remote Message Copy Interface (ARMCI), and minimizing communication for each RMI call. Our design allows a RMI operation to be completed by only two RDMA operations. We also aggressively optimize our system to reduce copying. In this paper, we discuss the design and our experimental evaluation of this protocol. Our experimental results show that our protocol can improve RMI performance by an order of magnitude.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2012

Clinical evaluation of a commercial orthopedic metal artifact reduction tool for CT simulations in radiation therapy

Purpose: Severe artifacts in kilovoltage-CT simulation images caused by large metallic implants can significantly degrade the conspicuity and apparent CT Hounsfield number of targets and anatomic structures, jeopardize the confidence of anatomical segmentation, and introduce inaccuracies into the radiation therapy treatment planning process. This study evaluated the performance of the first commercial orthopedic metal artifact reduction function (O-MAR) for radiation therapy, and investigated its clinical applications in treatment planning. Methods: Both phantom and clinical data were used for the evaluation. The CIRS electron density phantom with known physical (and electron) density plugs and removable titanium implants was scanned on a Philips Brilliance Big Bore 16-slice CT simulator. The CT Hounsfield numbers of density plugs on both uncorrected and O-MAR corrected images were compared. Treatment planning accuracy was evaluated by comparing simulated dose distributions computed using the true density images, uncorrected images, and O-MAR corrected images. Ten CT image sets of patients with large hip implants were processed with the O-MAR function and evaluated by two radiation oncologists using a five-point score for overall image quality, anatomical conspicuity, and CT Hounsfield number accuracy. By utilizing the same structure contours delineated from the O-MAR corrected images, clinical IMRT treatment plans for five patients were computed on the uncorrected and O-MAR corrected images, respectively, and compared. Results: Results of the phantom study indicated that CT Hounsfield number accuracy and noise were improved on the O-MAR corrected images, especially for images with bilateral metal implants. The {gamma} pass rates of the simulated dose distributions computed on the uncorrected and O-MAR corrected images referenced to those of the true densities were higher than 99.9% (even when using 1% and 3 mm distance-to-agreement criterion), suggesting that dose distributions were clinically identical. In all patient cases, radiation oncologists rated O-MAR corrected images as higher quality. Formerly obscured critical structures were able to be visualized. The overall image quality and the conspicuity in critical organs were significantly improved compared with the uncorrected images: overall quality score (1.35 vs 3.25, P= 0.0022); bladder (2.15 vs 3.7, P= 0.0023); prostate and seminal vesicles/vagina (1.3 vs 3.275, P= 0.0020); rectum (2.8 vs 3.9, P= 0.0021). The noise levels of the selected ROIs were reduced from 93.7 to 38.2 HU. On most cases (8/10), the average CT Hounsfield numbers of the prostate/vagina on the O-MAR corrected images were closer to the referenced value (41.2 HU, an average measured from patients without metal implants) than those on the uncorrected images. High {gamma} pass rates of the five IMRT dose distribution pairs indicated that the dose distributions were not significantly affected by the CT image improvements. Conclusions: Overall, this study indicated that the O-MAR function can remarkably reduce metal artifacts and improve both CT Hounsfield number accuracy and target and critical structure visualization. Although there was no significant impact of the O-MAR algorithm on the calculated dose distributions, we suggest that O-MAR corrected images are more suitable for the entire treatment planning process by offering better anatomical structure visualization, improving radiation oncologists' confidence in target delineation, and by avoiding subjective density overrides of artifact regions on uncorrected images.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS2000

Sensitivity of Age-of-Air Calculations to the Choice of Advection Scheme

The age of air has recently emerged as a diagnostic of atmospheric transport unaffected by chemical parameterizations, and the features in the age distributions computed in models have been interpreted in terms of the models' large-scale circulation field. This study shows, however, that in addition to the simulated large-scale circulation, three-dimensional age calculations can also be affected by the choice of advection scheme employed in solving the tracer continuity equation, Specifically, using the 3.0deg latitude X 3.6deg longitude and 40 vertical level version of the Geophysical Fluid Dynamics Laboratory SKYHI GCM and six online transport schemes ranging from Eulerian through semi-Lagrangian to fully Lagrangian, it will be demonstrated that the oldest ages are obtained using the nondiffusive centered-difference schemes while the youngest ages are computed with a semi-Lagrangian transport (SLT) scheme. The centered- difference schemes are capable of producing ages older than 10 years in the mesosphere, thus eliminating the "young bias" found in previous age-of-air calculations. At this stage, only limited intuitive explanations can be advanced for this sensitivity of age-of-air calculations to the choice of advection scheme, In particular, age distributions computed online with the National Center for Atmospheric Research Community Climate Model (MACCM3) using different varieties of the SLT scheme are substantially older than the SKYHI SLT distribution. The different varieties, including a noninterpolating-in-the-vertical version (which is essentially centered-difference in the vertical), also produce a narrower range of age distributions than the suite of advection schemes employed in the SKYHI model. While additional MACCM3 experiments with a wider range of schemes would be necessary to provide more definitive insights, the older and less variable MACCM3 age distributions can plausibly be interpreted as being due to the semi-implicit semi-Lagrangian dynamics employed in the MACCM3. This type of dynamical core (employed with a 60-min time step) is likely to reduce SLT's interpolation errors that are compounded by the short-term variability characteristic of the explicit centered-difference dynamics employed in the SKYHI model (time step of 3 min). In the extreme case of a very slowly varying circulation, the choice of advection scheme has no effect on two-dimensional (latitude-height) age-of-air calculations, owing to the smooth nature of the transport circulation in 2D models. These results suggest that nondiffusive schemes may be the preferred choice for multiyear simulations of tracers not overly sensitive to the requirement of monotonicity (this category includes many greenhouse gases). At the same time, age-of-air calculations offer a simple quantitative diagnostic of a scheme's long-term diffusive properties and may help in the evaluation of dynamical cores in multiyear integrations. On the other hand, the sensitivity of the computed ages to the model numerics calls for caution in using age of air as a diagnostic of a GCM's large-scale circulation field.

Eluszkiewicz, Janusz↗
NASA NTRS1994

Using PVM to host CLIPS in distributed environments

It is relatively easy to enhance CLIPS (C Language Integrated Production System) to support multiple expert systems running in a distributed environment with heterogeneous machines. The task is minimized by using the PVM (Parallel Virtual Machine) code from Oak Ridge Labs to provide the distributed utility. PVM is a library of C and FORTRAN subprograms that supports distributive computing on many different UNIX platforms. A PVM deamon is easily installed on each CPU that enters the virtual machine environment. Any user with rsh or rexec access to a machine can use the one PVM deamon to obtain a generous set of distributed facilities. The ready availability of both CLIPS and PVM makes the combination of software particularly attractive for budget conscious experimentation of heterogeneous distributive computing with multiple CLIPS executables. This paper presents a design that is sufficient to provide essential message passing functions in CLIPS and enable the full range of PVM facilities.

Myers, Leonard↗