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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A parallel workflow implementation for PEST version 13.6 in high-performance computing for WRF-Hydro version 5.0: a case study over the midwestern United States

The Weather Research and Forecasting Hydrological (WRF-Hydro) system is a state-of-the-art numerical model that models the entire hydrological cycle based on physical principles. As with other hydrological models, WRF-Hydro parameterizes many physical processes. Hence, WRF-Hydro needs to be calibrated to optimize its output with respect to observations for the application region. When applied to a relatively large domain, both WRF-Hydro simulations and calibrations require intensive computing resources and are best performed on multimode, multicore high-performance computing (HPC) systems. Typically, each physics-based model requires a calibration process that works specifically with that model and is not transferrable to a different process or model. The parameter estimation tool (PEST) is a flexible and generic calibration tool that can be used in principle to calibrate any of these models. In its existing configuration, however, PEST is not designed to work on the current generation of massively parallel HPC clusters. To address this issue, we ported the parallel PEST to HPCs and adapted it to work with WRF-Hydro. The porting involved writing scripts to modify the workflow for different workload managers and job schedulers, as well as to connect the parallel PEST to WRF-Hydro. To test the operational feasibility and the computational benefits of this first-of-its-kind HPC-enabled parallel PEST, we developed a case study using a flood in the midwestern United States in 2013. Results on a problem involving the calibration of 22 parameters show that on the same computing resources used for parallel WRF-Hydro, the HPC-enabled parallel PEST can speed up the calibration process by a factor of up to 15 compared with commonly used PEST in sequential mode. The speedup factor is expected to be greater with a larger calibration problem (e.g., more parameters to be calibrated or a larger size of study area).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Fluorescence Color by Data-Driven Design of Genomic Silver Clusters

DNA nucleobase sequence controls the size of DNA-stabilized silver clusters, leading to their well-known yet little understood sequence-tuned colors. The enormous space of possible DNA sequences for templating clusters has challenged the understanding of how sequence selects cluster properties and has limited the design of applications that employ these clusters. Here, we investigate the genomic role of DNA sequence for fluorescent silver clusters using a data-driven approach. Employing rapid parallel silver cluster synthesis and fluorimetry, we determine the fluorescence spectra of silver cluster products stabilized by 1432 distinct DNA oligomers. By applying pattern recognition algorithms to this large experimental data set, we discover certain DNA base patterns, or “motifs,” that correlate to silver clusters with similar fluorescence spectra. These motifs are employed in machine learning classifiers to predictively design DNA template sequences for specific fluorescence color bands. Our method improves selectivity of templates by 330% for silver clusters with peak emission wavelengths beyond 660 nm. The discovered base motifs also provide physical insights into how DNA sequence controls silver cluster size and color. Finally, this predictive design approach for color of DNA-stabilized silver clusters exhibits the potential of machine learning and data mining to increase the precision and efficiency of nanomaterials design, even for a soft-matter-inorganic hybrid system characterized by an extremely large parameter space.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1996

NAS Requirements Checklist for Job Queuing/Scheduling Software

The increasing reliability of parallel systems and clusters of computers has resulted in these systems becoming more attractive for true production workloads. Today, the primary obstacle to production use of clusters of computers is the lack of a functional and robust Job Management System for parallel applications. This document provides a checklist of NAS requirements for job queuing and scheduling in order to make most efficient use of parallel systems and clusters for parallel applications. Future requirements are also identified to assist software vendors with design planning.

Jones, James Patton↗
NASA NTRS1996

Evaluation of Job Queuing/Scheduling Software: Phase I Report

The recent proliferation of high performance work stations and the increased reliability of parallel systems have illustrated the need for robust job management systems to support parallel applications. To address this issue, the national Aerodynamic Simulation (NAS) supercomputer facility compiled a requirements checklist for job queuing/scheduling software. Next, NAS began an evaluation of the leading job management system (JMS) software packages against the checklist. This report describes the three-phase evaluation process, and presents the results of Phase 1: Capabilities versus Requirements. We show that JMS support for running parallel applications on clusters of workstations and parallel systems is still insufficient, even in the leading JMS's. However, by ranking each JMS evaluated against the requirements, we provide data that will be useful to other sites in selecting a JMS.

Jones, James Patton↗
NASA NTRS1997

Second Evaluation of Job Queuing/Scheduling Software

The recent proliferation of high performance workstations and the increased reliability of parallel systems have illustrated the need for robust job management systems to support parallel applications. To address this issue, NAS compiled a requirements checklist for job queuing/scheduling software. Next, NAS evaluated the leading job management system (JMS) software packages against the checklist. A year has now elapsed since the first comparison was published, and NAS has repeated the evaluation. This report describes this second evaluation, and presents the results of Phase 1: Capabilities versus Requirements. We show that JMS support for running parallel applications on clusters of workstations and parallel systems is still lacking, however, definite progress has been made by the vendors to correct the deficiencies. This report is supplemented by a WWW interface to the data collected, to aid other sites in extracting the evaluation information on specific requirements of interest.

Jones, James Patton↗
DOE OSTI2018

Criticality Evaluation of Low Density Product Oxides for Air Transport for the ES-3100 Package

This document presents the criticality safety evaluation of the Y-12 National Security Complex (Y-12) Model ES-3100 package for the addition of lower bulk density limits for HEU product oxides transported by air. The current authorized oxide density range for air transport is 2.0 to 6.54 g/cm 3 . The analysis in this report looks at lower densities, specifically in the range of 1.0 to 2.0 g/cm 3 . For reasons presented in this report, it was decided to present the entire range of oxide densities (1.0 to 6.54 g/cm 3 ) as a series of sub-ranges. The lowest density in each range was evaluated. Thus calculations were performed for the following oxide densities: 5.0 g/cm 3 , 4.0 g/cm 3 , 3.0 g/cm 3 , 2.0 g/cm 3 , 1.5 g/cm 3 and 1.0 g/cm 3 . Calculations presented herein were performed using a third generation computing platform; the Microway Parallel Linux Cluster ENGHPC workstation using the Monte Carlo Criticality Safety Analysis Sequence (CSAS5) criticality code sequence and 238-group ENDF/B-VII cross-section library of Standardized Computer Analysis for Licensing Evaluation (SCALE) 6.1.3 (ORNL/TM-2005/39, SCALE: A Comprehensive Modeling and Simulation Suite for Nuclear Safety Analysis and Design).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Type-Ia supernova rates to redshift 2.4 from clash: The cluster lensing and supernova survey with Hubble

We present the supernova (SN) sample and Type-Ia SN (SN Ia) rates from the Cluster Lensing And Supernova survey with Hubble (CLASH). Using the Advanced Camera for Surveys and the Wide Field Camera 3 on the Hubble Space Telescope (HST), we have imaged 25 galaxy-cluster fields and parallel fields of non-cluster galaxies. We report a sample of 27 SNe discovered in the parallel fields. Of these SNe, ∼13 are classified as SN Ia candidates, including four SN Ia candidates at redshifts z > 1.2. We measure volumetric SN Ia rates to redshift 1.8 and add the first upper limit on the SN Ia rate in the range 1.8 < z < 2.4. The results are consistent with the rates measured by the HST/GOODS and Subaru Deep Field SN surveys. We model these results together with previous measurements at z < 1 from the literature. The best-fitting SN Ia delay-time distribution (DTD; the distribution of times that elapse between a short burst of star formation and subsequent SN Ia explosions) is a power law with an index of −1.00{sub −0.06(0.10)}{sup +0.06(0.09)} (statistical){sub −0.08}{sup +0.12} (systematic), where the statistical uncertainty is a result of the 68% and 95% (in parentheses) statistical uncertainties reported for the various SN Ia rates (from this work and from the literature), and the systematic uncertainty reflects the range of possible cosmic star-formation histories. We also test DTD models produced by an assortment of published binary population synthesis (BPS) simulations. The shapes of all BPS double-degenerate DTDs are consistent with the volumetric SN Ia measurements, when the DTD models are scaled up by factors of 3-9. In contrast, all BPS single-degenerate DTDs are ruled out by the measurements at >99% significance level.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2014

Type-Ia Supernova Rates to Redshift 2.4 from Clash: The Cluster Lensing and Supernova Survey with Hubble

We present the supernova (SN) sample and Type-Ia SN (SN Ia) rates from the Cluster Lensing And Supernova survey with Hubble (CLASH). Using the Advanced Camera for Surveys and the Wide Field Camera 3 on the Hubble Space Telescope (HST), we have imaged 25 galaxy-cluster fields and parallel fields of non-cluster galaxies. We report a sample of 27 SNe discovered in the parallel fields. Of these SNe, approximately 13 are classified as SN Ia candidates, including four SN Ia candidates at redshifts z greater than 1.2.We measure volumetric SN Ia rates to redshift 1.8 and add the first upper limit on the SN Ia rate in the range z greater than 1.8 and less than 2.4. The results are consistent with the rates measured by the HST/ GOODS and Subaru Deep Field SN surveys.We model these results together with previous measurements at z less than 1 from the literature. The best-fitting SN Ia delay-time distribution (DTD; the distribution of times that elapse between a short burst of star formation and subsequent SN Ia explosions) is a power law with an index of 1.00 (+0.06(0.09))/(-0.06(0.10)) (statistical) (+0.12/−0.08) (systematic), where the statistical uncertainty is a result of the 68% and 95% (in parentheses) statistical uncertainties reported for the various SN Ia rates (from this work and from the literature), and the systematic uncertainty reflects the range of possible cosmic star-formation histories. We also test DTD models produced by an assortment of published binary population synthesis (BPS) simulations. The shapes of all BPS double-degenerate DTDs are consistent with the volumetric SN Ia measurements, when the DTD models are scaled up by factors of 3-9. In contrast, all BPS single-degenerate DTDs are ruled out by the measurements at greater than 99% significance level.

SUPERNOVA↗
DOE OSTI2018

Templating Growth of a Pseudomorphic Lepidocrocite Microshell at the Calcite–Water Interface

The growth of lepidocrocite (gamma-FeOOH) has been observed through oxidation of Fe(II) on calcite (CaCO 3 ). Here, we seek to understand the structural relation between lepidocrocite and the calcite substrate and its growth mechanism. The formation of iron oxyhydroxide layers having distinct morphologies was observed during the dissolution of calcite in acidic Fe(II)-rich solutions. A pseudomorphic lepidocrocite shell together with multiple iron oxyhydroxide layers encapsulated within the shell was imaged by optical and transmission X-ray microscopies. The presence of a several-nanometer-thick ordered lepidocrocite film was observed by X-ray reflectivity, with the lepidocrocite (100) plane oriented parallel to the calcite (104) surface. Lath-shaped lepidocrocite aggregates formed during the initial precipitation, which eventually grew into clusters of parallel platy crystals. The formation of a nanometer-thick well-ordered lepidocrocite film on a pristine calcite surface appears critical for the subsequent pseudomorphic overgrowth. Detachment of the lepidocrocite film from the dissolving calcite surface yielded a free-standing pseudomorphic iron oxyhydroxide shell, suggesting weak interactions between the shell and the calcite substrate. This growth mechanism yields the potential of using carbonate minerals as templates for pseudomorphic synthesis of iron oxyhydroxides having well-defined size and morphology.

25 ENERGY STORAGE↗
DOE OSTI2018

HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for large-scale networks

Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein–protein interaction networks, which hold information about functional affinities or structural similarities. Such networks have been expanding in size due to increasing scale and abundance of biological data. While various clustering algorithms have been proposed to find highly connected regions, Markov Clustering (MCL) has been one of the most successful approaches to cluster sequence similarity or expression networks. Despite its popularity, MCL’s scalability to cluster large datasets still remains a bottleneck due to high running times and memory demands. In this paper, we present High-performance MCL (HipMCL), a parallel implementation of the original MCL algorithm that can run on distributed-memory computers. We show that HipMCL can efficiently utilize 2000 compute nodes and cluster a network of ~70 million nodes with ~68 billion edges in ~2.4 h. By exploiting distributed-memory environments, HipMCL clusters large-scale networks several orders of magnitude faster than MCL and enables clustering of even bigger networks. Finally, HipMCL is based on MPI and OpenMP and is freely available under a modified BSD license.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

ION INJECTION AT QUASI-PARALLEL SHOCKS SEEN BY THE CLUSTER SPACECRAFT

Collisionless shocks in space plasma are known to be capable of accelerating ions to very high energies through diffusive shock acceleration (DSA). This process requires an injection of suprathermal ions, but the mechanisms producing such a suprathermal ion seed population are still not fully understood. We study acceleration of solar wind ions resulting from reflection off short large-amplitude magnetic structures (SLAMSs) in the quasi-parallel bow shock of Earth using in situ data from the four Cluster spacecraft. Nearly specularly reflected solar wind ions are observed just upstream of a SLAMS. The reflected ions are undergoing shock drift acceleration (SDA) and obtain energies higher than the solar wind energy upstream of the SLAMS. Our test particle simulations show that solar wind ions with lower energy are more likely to be reflected off the SLAMS, while high-energy ions pass through the SLAMS, which is consistent with the observations. The process of SDA at SLAMSs can provide an effective way of accelerating solar wind ions to suprathermal energies. Therefore, this could be a mechanism of ion injection into DSA in astrophysical plasmas.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

STABILITY OF SMALL SELF-INTERSTITIAL CLUSTERS IN TUNGSTEN

Density functional theory was employed to explore the stability of interstitial clusters in W up to size seven. For each cluster size, the most stable configuration consists of parallel dumbbells. For clusters larger than size three, parallel dumbbells prefer to form in a multilayer fashion, instead of a planar structure. For size-7 clusters, the most stable configuration is a complete octahedron. The binding energy of a [111] dumbbell to the most stable cluster increases with cluster size, namely 2.49, 3.68, 4.76, 4.82, 5.47, and 6.85 eV for clusters of size 1, 2, 3, 4, 5, and 6, respectively. For a size-2 cluster, collinear dumbbells are still repulsive at the maximum allowable distance of 13.8 Å (the fifth neighbor along [111]). On the other hand, parallel dumbbells are strongly bound together. Two parallel dumbbells in which the axis-to-axis distance is within a cylindrical radius of 5.2 Å still exhibit a considerable binding of 0.28 eV. The most stable cluster in each size will be used to explore interactions with transmutation products.

density functional theory↗
DOE OSTI2016

Parallel File System I/O Performance Testing On LANL Clusters

These are slides from a presentation on parallel file system I/O performance testing on LANL clusters. I/O is a known bottleneck for HPC applications. Performance optimization of I/O is often required. This summer project entailed integrating IOR under Pavilion and automating the results analysis. The slides cover the following topics: scope of the work, tools utilized, IOR-Pavilion test workflow, build script, IOR parameters, how parameters are passed to IOR, *run_ior: functionality, Python IOR-Output Parser, Splunk data format, Splunk dashboard and features, and future work.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

Development of Message Passing Routines for High Performance Parallel Computations

Computational Fluid Dynamics (CFD) calculations require a great deal of computing power for completing the detailed computations involved. In an effort shorten the time it takes to complete such calculations they are implemented on a parallel computer. In the case of a parallel computer some sort of message passing structure must be used to communicate between the computers because, unlike a single machine, each computer in a parallel computing cluster does not have access to all the data or run all the parts of the total program. Thus, message passing is used to divide up the data and send instructions to each machine. The nature of my work this summer involves programming the "message passing" aspect of the parallel computer. I am working on modifying an existing program, which was written with OpenMP, and does not use a multi-machine parallel computing structure, to work with Message Passing Interface (MPI) routines. The actual code is being written in the FORTRAN 90 programming language. My goal is to write a parameterized message passing structure that could be used for a variety of individual applications and implement it on Silicon Graphics Incorporated s (SGI) IRIX operating system. With this new parameterized structure engineers would be able to speed up computations for a wide variety of purposes without having to use larger and more expensive computing equipment from another division or another NASA center.

Summers, Edward K.↗
DOE OSTI2013

Massively parallel implementations of coupled-cluster methods for electron spin resonance spectra. I. Isotropic hyperfine coupling tensors in large radicals

Coupled cluster (CC) methods provide highly accurate predictions of molecular properties, but their high computational cost has precluded their routine application to large systems. Fortunately, recent computational developments in the ACES III program by the Bartlett group [the OED/ERD atomic integral package, the super instruction processor, and the super instruction architecture language] permit overcoming that limitation by providing a framework for massively parallel CC implementations. In that scheme, we are further extending those parallel CC efforts to systematically predict the three main electron spin resonance (ESR) tensors (A-, g-, and D-tensors) to be reported in a series of papers. In this paper inaugurating that series, we report our new ACES III parallel capabilities that calculate isotropic hyperfine coupling constants in 38 neutral, cationic, and anionic radicals that include the {sup 11}B, {sup 17}O, {sup 9}Be, {sup 19}F, {sup 1}H, {sup 13}C, {sup 35}Cl, {sup 33}S,{sup 14}N, {sup 31}P, and {sup 67}Zn nuclei. Present parallel calculations are conducted at the Hartree-Fock (HF), second-order many-body perturbation theory [MBPT(2)], CC singles and doubles (CCSD), and CCSD with perturbative triples [CCSD(T)] levels using Roos augmented double- and triple-zeta atomic natural orbitals basis sets. HF results consistently overestimate isotropic hyperfine coupling constants. However, inclusion of electron correlation effects in the simplest way via MBPT(2) provides significant improvements in the predictions, but not without occasional failures. In contrast, CCSD results are consistently in very good agreement with experimental results. Inclusion of perturbative triples to CCSD via CCSD(T) leads to small improvements in the predictions, which might not compensate for the extra computational effort at a non-iterative N{sup 7}-scaling in CCSD(T). The importance of these accurate computations of isotropic hyperfine coupling constants to elucidate experimental ESR spectra, to interpret spin-density distributions, and to characterize and identify radical species is illustrated with our results from large organic radicals. Those include species relevant for organic chemistry, petroleum industry, and biochemistry, such as the cyclo-hexyl, 1-adamatyl, and Zn-porphycene anion radicals, inter alia.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2000

Dynamic Load-Balancing for Distributed Heterogeneous Computing of Parallel CFD Problems

The developed methodology is aimed at improving the efficiency of executing block-structured algorithms on parallel, distributed, heterogeneous computers. The basic approach of these algorithms is to divide the flow domain into many sub- domains called blocks, and solve the governing equations over these blocks. Dynamic load balancing problem is defined as the efficient distribution of the blocks among the available processors over a period of several hours of computations. In environments with computers of different architecture, operating systems, CPU speed, memory size, load, and network speed, balancing the loads and managing the communication between processors becomes crucial. Load balancing software tools for mutually dependent parallel processes have been created to efficiently utilize an advanced computation environment and algorithms. These tools are dynamic in nature because of the chances in the computer environment during execution time. More recently, these tools were extended to a second operating system: NT. In this paper, the problems associated with this application will be discussed. Also, the developed algorithms were combined with the load sharing capability of LSF to efficiently utilize workstation clusters for parallel computing. Finally, results will be presented on running a NASA based code ADPAC to demonstrate the developed tools for dynamic load balancing.

Ecer, A.↗
NASA NTRS1989

Image segmentation by iterative parallel region growing and splitting

The spatially constrained clustering (SCC) iterative parallel region-growing technique is applied to image analysis. The SCC algorithm is implemented on the massively parallel processor at NASA Goddard. Most previous region-growing approaches have the drawback that the segmentation produced depends on the order in which portions of the image are processed. The ideal solution to this problem (merging only the single most similar pair of spatially adjacent regions in the image in each iteration) becomes impractical except for very small images, even on a massively parallel computer. The SCC algorithm overcomes these problems by performing, in parallel, the best merge within each of a set of local, possibly overlapping, subimages. A region-splitting stage is also incorporated into the algorithm, but experiments show that region splitting generally does not improve segmentation results. The SCC algorithm has been tested on various imagery data, and test results for a Landsat TM image are summarized.

Tilton, James C.↗
DOE OSTI2023

Massively parallel GPU enabled third-order cluster perturbation excitation energies for cost-effective large scale excitation energy calculations

We present here a massively parallel implementation of the recently developed CPS(D-3) excitation energy model that is based on cluster perturbation theory. The new algorithm extends the one developed in Baudin et al. [J. Chem. Phys., 150, 134110 (2019)] to leverage multiple nodes and utilize graphical processing units for the acceleration of heavy tensor contractions. Furthermore, we show that the extended algorithm scales efficiently with increasing amounts of computational resources and that the developed code enables CPS(D-3) excitation energy calculations on large molecular systems with a low time-to-solution. More specifically, calculations on systems with over 100 atoms and 1000 basis functions are possible in a few hours of wall clock time. This establishes CPS(D-3) excitation energies as a computationally efficient alternative to those obtained from the coupled-cluster singles and doubles model.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗