Search NASA⌕ Search

SEARCH · Search NASA

Results for “Cluster Computing”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

As-built design specification for proportion estimate software subsystem

The Proportion Estimate Processor evaluates four estimation techniques in order to get an improved estimate of the proportion of a scene that is planted in a selected crop. The four techniques to be evaluated were provided by the techniques development section and are: (1) random sampling; (2) proportional allocation, relative count estimate; (3) proportional allocation, Bayesian estimate; and (4) sequential Bayesian allocation. The user is given two options for computation of the estimated mean square error. These are referred to as the cluster calculation option and the segment calculation option. The software for the Proportion Estimate Processor is operational on the IBM 3031 computer.

Obrien, S.↗
DOE OSTI2018

The Archive Solution for Distributed Workflow Management Agents of the CMS Experiment at LHC

The CMS experiment at the CERN LHC developed the Workflow Management Archive system to persistently store unstructured framework job report documents produced by distributed workflow management agents. In this paper we present its architecture, implementation, deployment, and integration with the CMS and CERN computing infrastructures, such as central HDFS and Hadoop Spark cluster. The system leverages modern technologies such as a document oriented database and the Hadoop eco-system to provide the necessary flexibility to reliably process, store, and aggregate $\mathcal{O}$(1M) documents on a daily basis. We describe the data transformation, the short and long term storage layers, the query language, along with the aggregation pipeline developed to visualize various performance metrics to assist CMS data operators in assessing the performance of the CMS computing system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Efficient Step-Merged Quantum Imaginary Time Evolution Algorithm for Quantum Chemistry

In this work, we develop a resource-efficient step-merged quantum imaginary time evolution approach (smQITE) to solve for the ground state of a Hamiltonian on quantum computers. This heuristic method features a fixed shallow quantum circuit depth along the state evolution path. We use this algorithm to determine the binding energy curves of a set of molecules, including H 2 , H 4 , H 6 , LiH, HF, H 2 O, and BeH 2 , and find highly accurate results. The required quantum resources of smQITE calculations can be further reduced by adopting the circuit form of the variational quantum eigensolver (VQE) technique, such as the unitary coupled cluster ansatz. We demonstrate that smQITE achieves a similar computational accuracy as VQE at the same fixed-circuit ansatz, without requiring a generally complicated high-dimensional nonconvex optimization. Finally, smQITE calculations are carried out on Rigetti quantum processing units, demonstrating that the approach is readily applicable on current noisy intermediate-scale quantum devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

Fast parallel algorithms that compute transitive closure of a fuzzy relation

The notion of a transitive closure of a fuzzy relation is very useful for clustering in pattern recognition, for fuzzy databases, etc. The original algorithm proposed by L. Zadeh (1971) requires the computation time O(n(sup 4)), where n is the number of elements in the relation. In 1974, J. C. Dunn proposed a O(n(sup 2)) algorithm. Since we must compute n(n-1)/2 different values s(a, b) (a not equal to b) that represent the fuzzy relation, and we need at least one computational step to compute each of these values, we cannot compute all of them in less than O(n(sup 2)) steps. So, Dunn's algorithm is in this sense optimal. For small n, it is ok. However, for big n (e.g., for big databases), it is still a lot, so it would be desirable to decrease the computation time (this problem was formulated by J. Bezdek). Since this decrease cannot be done on a sequential computer, the only way to do it is to use a computer with several processors working in parallel. We show that on a parallel computer, transitive closure can be computed in time O((log(sub 2)(n))2).

Kreinovich, Vladik YA.↗
DOE OSTI2015

Quantum simulation of quantum field theory using continuous variables

Much progress has been made in the field of quantum computing using continuous variables over the last couple of years. This includes the generation of extremely large entangled cluster states (10,000 modes, in fact) as well as a fault tolerant architecture. This has lead to the point that continuous-variable quantum computing can indeed be thought of as a viable alternative for universal quantum computing. With that in mind, we present a new algorithm for continuous-variable quantum computers which gives an exponential speedup over the best known classical methods. Specifically, this relates to efficiently calculating the scattering amplitudes in scalar bosonic quantum field theory, a problem that is known to be hard using a classical computer. Thus, we give an experimental implementation based on cluster states that is feasible with today's technology.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

The electron affinity of the uranium atom

The results of a combined experimental and computational study of the uranium atom are presented with the aim of determining its electron affinity. Experimentally, the electron affinity of uranium was measured via negative ion photoelectron spectroscopy of the uranium atomic anion, U – . Computationally, the electron affinities of both thorium and uranium were calculated by conducting relativistic coupled-cluster and multi-reference configuration interaction calculations. The experimentally determined value of the electron affinity of the uranium atom was determined to be 0.309 ± 0.025 eV. The computationally predicted electron affinity of uranium based on composite coupled cluster calculations and full four-component spin–orbit coupling was found to be 0.232 eV. Predominately due to a better convergence of the coupled cluster sequence for Th and Th – , the final calculated electron affinity of Th, 0.565 eV, was in much better agreement with the accurate experimental value of 0.608 eV. In both scenarios, the ground state of the anion corresponds to electron attachment to the 6d orbital.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2016

Using Hybrid Model OpenSHMEM + CUDA to Implement the SHOC Benchmark Suite

This work describes the process of porting the Scalable HeterOgeneous Computing (SHOC) benchmark suite from the hybrid MPI + CUDA implementation to OpenSHMEM + CUDA. SHOC includes a wide variety of benchmark kernels used to measure accelerator performance in both single node and cluster configurations. The hybrid model implementation attempts to place all major computation on accelerator devices, and uses MPI to synchronize and aggregate results. In some cases, MPI Groups are used to gradually reduce the number of accelerators used for computation as the problem size drops. Porting this behavior to OpenSHMEM required implementing several synchronizing collective operations, and using SHMEM teams to replace MPI Group functionality. Benchmark results on a Cray XK7 system with one GPU per compute node show that SHMEM performance is equal to MPI performance in these hybrid tasks. These results and porting experience show that using OpenSHMEM for accelerator devices benefits from adding functionality for synchronization and teams, and would further benefit from adding support for communication within accelerator kernels.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1997

Computer Supported Indexing: A History and Evaluation of NASA's MAI System

Computer supported indexing systems may be categorized in several ways. One classification scheme refers to them as statistical, syntactic, semantic or knowledge-based. While a system may emphasize one of these aspects, most systems actually combine two or more of these mechanisms to maximize system efficiency. Statistical systems can be based on counts of words or word stems, statistical association, and correlation techniques that assign weights to word locations or provide lexical disambiguation, calculations regarding the likelihood of word co-occurrences, clustering of word stems and transformations, or any other computational method used to identify pertinent terms. If words are counted, the ones of median frequency become candidate index terms. Syntactical systems stress grammar and identify parts of speech. Concepts found in designated grammatical combinations, such as noun phrases, generate the suggested terms. Semantic systems are concerned with the context sensitivity of words in text. The primary goal of this type of indexing is to identify without regard to syntax the subject matter and the context-bearing words in the text being indexed. Knowledge-based systems provide a conceptual network that goes past thesaurus or equivalent relationships to knowing (e.g., in the National Library of Medicine (NLM) system) that because the tibia is part of the leg, a document relating to injuries to the tibia should he indexed to LEG INJURIES, not the broader MeSH term INJURIES, or knowing that the term FEMALE should automatically be added when the term PREGNANCY is assigned, and also that the indexer should be prompted to add either HUMAN or ANIMAL. Another way of categorizing indexing systems is to identify them as producing either assigned- or derived-term indexes.

Silvester, June P.↗
DOE OSTI2016

Diffusion Monte Carlo studies of MB-pol (H{sub 2}O){sub 2−6} and (D{sub 2}O){sub 2−6} clusters: Structures and binding energies

We employ the diffusion Monte Carlo (DMC) method in conjunction with the recently developed, ab initio-based MB-pol potential energy surface to characterize the ground states of small (H{sub 2}O){sub 2−6} clusters and their deuterated isotopomers. Observables, other than the ground state energies, are computed using the descendant weighting approach. Among those are various spatial correlation functions and relative isomer fractions. Interestingly, the ground states of all clusters considered in this study, except for the dimer, are delocalized over at least two conformations that differ by the orientation of one or more water monomers with the relative isomer populations being sensitive to the isotope substitution. Most remarkably, the ground state of the (H{sub 2}O){sub 6} hexamer is represented by four distinct cage structures, while that of (D{sub 2}O){sub 6} is dominated by the prism, i.e., the global minimum geometry, with a very small contribution from a prism-book geometry. In addition, for (H{sub 2}O){sub 6} and (D{sub 2}O){sub 6}, we performed DMC calculations to compute the ground states constrained to the cage and prism geometries. These calculations compared results for three different potentials, MB-pol, TTM3/F, and q-TIP4P/F.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

On a simple way to calculate electronic resonances for polyatomic molecules

We propose a simple method for calculation of low-lying shape electronic resonances of polyatomic molecules. The method introduces a perturbation potential and requires only routine bound-state type calculations in the real domain of energies. Such a calculation is accessible by most of the free or commercial quantum chemistry software. The presented method is based on the analytical continuation in a coupling constant model, but unlike its previous variants, we experience a very stable and robust behavior for higher-order extrapolation functions. Moreover, the present approach is independent of the correlation treatment used in quantum many-electron computations and therefore we are able to apply Coupled Clusters (CCSD-T) level of the correlation model. We demonstrate these properties on determination of the resonance position and width of the {sup 2}Π{sub u} temporary negative ion state of diacetylene using CCSD-T level of theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Alkyltin clusters: the less symmetric Keggin isomers

The Keggin structure is prevalent in nature and synthesis, self-assembled from many metals across the periodic table as both isolated clusters and building blocks of condensed framework oxides. Here we present a one-step synthesis to obtain the sodium-centered butyltin Keggin ion in high yield and high purity, important for mechanistic nanolithography studies. Extensive solution characterization (small-angle X-ray scattering, 1 H, 13 C and 119 Sn nuclear magnetic resonance, electrospray mass spectrometry) also confirms solutions contain only the Na-centered dodecamers. We report three butyltin Keggin structures: the β-isomer (β-NaSn 12 ), the γ-isomer (γ-NaSn 12 ), and a γ-isomer capped with an additional butyltin (γ-NaSn 13 ). All Keggin ions presented here have the general formula [NaO 4 BuSn 12 (OCH 3 ) 12 (O,OH) 12 ] (Bu = butyl), and are of neutral charge. The lack of counterions (OH – ) facilitates mechanistic lithographic studies without inference from hydrolysis chemistry. The methanol reaction media enables solubility and ligates the cluster, both important to obtain high purity materials. Despite the monospecific nature of the NaSn 12 solutions, NMR reveals both isomer interconversion and ligand exchange. DFT computational comparisons of our three isolated structures, the capped β-isomer (β-NaSn 13 ), along with hypothetical α-isomers (α-NaSn 12 and α-NaSn 13 ), showed that the stability ranks β-NaSn 12 > γ-NaSn 12 > α-NaSn 12 , consistent with experimental observation. The uncapped isomers were computationally determined to be more stable than the respective capped analogues. These clusters provide a unique opportunity to investigate the lower-symmetry Keggin isomers, and to determine structural factors that control isomer selectivity as well as isomer labilization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Impact of Soret effect on hydrogen and helium retention in PFC tungsten under ELM-like conditions

Abstract In our previous work, we have demonstrated using nonequilibrium molecular-dynamics simulations that the fluxes of helium and self-interstitial atoms in the presence of a thermal gradient in tungsten are directed opposite to the heat flux, indicating that species transport is governed by a Soret effect, namely, thermal-gradient-driven diffusion, characterized by a negative heat of transport that drives species transport uphill, i.e. from the cooler to the hot regions of the tungsten sample. In this work, the findings of our thermal and species transport analysis have been implemented in our cluster-dynamics code, Xolotl, which has been used to compute temperature and species profiles over spatiotemporal scales representative of plasma-facing component (PFC) tungsten under typical reactor operating conditions, including extreme heat loads at the plasma-facing surface characteristic of plasma instabilities that induce edge localized modes (ELMs). We demonstrate that the steady-state species profiles, when properly accounting for the Soret effect, vary significantly from those where temperature-gradient-driven transport is not accounted for and discuss the implications of such a Soret effect on the response to plasma exposure of plasma-facing tungsten. Although our cluster-dynamics simulations do not yet include self-clustering of helium or hydrogen blister formation, our simulation results show that the Soret effect substantially reduces helium and hydrogenic species retention inside PFC tungsten.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Advancing Understanding of Fission Gas Behavior in Nuclear Fuel through Leadership Class Computing

This report describes the outcome of the pilot SciDAC project jointly funded by the DOE Office of Nuclear Energy and the DOE Office of Science, Advanced Scientific Computing Research to advance understanding of fission gas behavior in nuclear fuel. The computational approach involved utilizing both a bottom up and top down multiscale materials modeling to evaluate the processes of xenon fission gas diffusion, xenon clustering and precipitation and the mechanisms of fission gas resolution by energetic fission fragments in uranium dioxide nuclear fuel. The computer science and applied mathematics research activities were focused on optimizing the uranium – oxygen – xenon interatomic potential implementation in the LAMMPS molecular dynamics code for large-scale simulations of fission gas resolution, in addition to improvements in visualization of accelerated molecular dynamics simulations and performance optimization of the Xolotl continuum cluster dynamics with a new grouping scheme to reduce the computational cost of modeling very large fission gas bubbles containing more than 10,000 xenon atoms. The most impactful result from this project stems from a systematic series of atomistic molecular dynamics to evaluate fission gas resolution from xenon bubbles that, combined with the fission product yields and consideration of electron-phonon coupling, informed a first principles model that predicts the magnitude of fission gas resolution in good agreement with empirical estimates.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2002

Computational Thermochemistry of Jet Fuels and Rocket Propellants

The design of new high-energy density molecules as candidates for jet and rocket fuels is an important goal of modern chemical thermodynamics. The NASA Glenn Research Center is home to a database of thermodynamic data for over 2000 compounds related to this goal, in the form of least-squares fits of heat capacities, enthalpies, and entropies as functions of temperature over the range of 300 - 6000 K. The chemical equilibrium with applications (CEA) program written and maintained by researchers at NASA Glenn over the last fifty years, makes use of this database for modeling the performance of potential rocket propellants. During its long history, the NASA Glenn database has been developed based on experimental results and data published in the scientific literature such as the standard JANAF tables. The recent development of efficient computational techniques based on quantum chemical methods provides an alternative source of information for expansion of such databases. For example, it is now possible to model dissociation or combustion reactions of small molecules to high accuracy using techniques such as coupled cluster theory or density functional theory. Unfortunately, the current applicability of reliable computational models is limited to relatively small molecules containing only around a dozen (non-hydrogen) atoms. We propose to extend the applicability of coupled cluster theory- often referred to as the 'gold standard' of quantum chemical methods- to molecules containing 30-50 non-hydrogen atoms. The centerpiece of this work is the concept of local correlation, in which the description of the electron interactions- known as electron correlation effects- are reduced to only their most important localized components. Such an advance has the potential to greatly expand the current reach of computational thermochemistry and thus to have a significant impact on the theoretical study of jet and rocket propellants.

Crawford, T. Daniel↗
DOE OSTI2019

Phonon localization in binary alloys with diagonal and off-diagonal disorder: A cluster Green's function approach

We report the development and application of a method for carrying out computational investigations of the effects of mass and force-constant (FC) disorder on phonon spectra. The method is based on the recently developed typical medium dynamical cluster approach, which is a Green's function approach. Excellent quantitative agreement with previous exact diagonalization results establishes the veracity of the method. Application of the method to a model system of binary mass and an FC-disordered system leads to several findings. A narrow resonance, significantly below the van Hove singularity, that has been termed the boson peak, is seen to emerge for low soft particle concentrations. We show, using the typical phonon spectrum, that the states constituting the boson peak cross over from being completely localized to being extended as a function of increasing soft particle concentration. In general, an interplay of mass and FC disorder is found to be cooperative in nature, enhancing phonon localization over all frequencies. However, for a certain range of frequencies, and depending on material parameters, FC disorder can delocalize the states that were localized by mass disorder, and vice versa. Modeling vacancies as weakly bonded sites with vanishing mass, we find that vacancies, even at very low concentrations, are extremely effective in localizing phonons. Thus, inducing vacancies is proposed as a promising route for efficient thermoelectrics. Lastly, we use model parameters corresponding to the alloy system, Ni 1- x Pt x , and we show that mass disorder alone is insufficient to explain the pseudogap in the phonon spectrum; the concomitant presence of FC disorder is necessary.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

THE SWIFT X-RAY TELESCOPE CLUSTER SURVEY. III. CLUSTER CATALOG FROM 2005-2012 ARCHIVAL DATA

We present the Swift X-ray Cluster Survey (SWXCS) catalog obtained using archival data from the X-ray telescope (XRT) on board the Swift satellite acquired from 2005 February to 2012 November, extending the first release of the SWXCS. The catalog provides positions, soft fluxes, and, when possible, optical counterparts for a flux-limited sample of X-ray group and cluster candidates. We consider the fields with Galactic latitude |b| > 20° to avoid high H I column densities. We discard all of the observations targeted at groups or clusters of galaxies, as well as particular extragalactic fields not suitable to search for faint extended sources. We finally select ∼3000 useful fields covering a total solid angle of ∼400 deg{sup 2}. We identify extended source candidates in the soft-band (0.5-2 keV) images of these fields using the software EXSdetect, which is specifically calibrated for the XRT data. Extensive simulations are used to evaluate contamination and completeness as a function of the source signal, allowing us to minimize the number of spurious detections and to robustly assess the selection function. Our catalog includes 263 candidate galaxy clusters and groups down to a flux limit of 7 × 10{sup –15} erg cm{sup –2} s{sup –1} in the soft band, and the logN-logS is in very good agreement with previous deep X-ray surveys. The final list of sources is cross-correlated with published optical, X-ray, and Sunyaev-Zeldovich catalogs of clusters. We find that 137 sources have been previously identified as clusters in the literature in independent surveys, while 126 are new detections. Currently, we have collected redshift information for 158 sources (60% of the entire sample). Once the optical follow-up and the X-ray spectral analysis of the sources are complete, the SWXCS will provide a large and well-defined catalog of groups and clusters of galaxies to perform statistical studies of cluster properties and tests of cosmological models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Revealing EDL-driven reduction mechanisms in binary, ternary, and quaternary fluorinated electrolytes via an integrated MD–DFT–ML framework

Accurately predicting solid electrolyte interphase (SEI) formation requires explicitly resolving the electric double layer (EDL) structure, which deviates significantly from that of the bulk electrolyte. Although an established molecular dynamics (MD) and Density Functional Theory (DFT) framework can model SEI formation by evaluating reduction reactions of local clusters in the EDL, it suffers from a combinatorial computational bottleneck. To overcome this limitation, we introduce a machine-learning-accelerated simulation workflow (MD–DFT–ML), integrating a gradient-boosted regression model trained on EDL composition data to efficiently predict reduction potentials. We apply this framework to seven fluorinated electrolytes comprising fluorinated anions, a fluorinated ester solvent, two types of diluent (ion-solvating ester vs. non-solvating ether), and an FEC additive. The analysis shows that the EDL selectively accumulates cation-binding species; consequently, the non–cation-binding ether diluent rarely enters the EDL and makes minimal contributions to SEI formation. DFT calculations on statistically representative EDL clusters provide reduction potentials and fluorine-release pathways, while the ML model, which substantially reduces the DFT workload, predicts cluster reduction energies with a mean absolute error of 0.1 eV. The combined MD–DFT–ML approach also quantifies contributions from different sources to LiF formation in the SEI. This methodology establishes a generalizable route for multiscale modeling electrolyte and interphase design for next-generation electrochemical energy-storage systems.

DFT-MD-ML workflow↗
DOE OSTI2022

Unitary Selective Coupled-Cluster Method

Simulating molecules using the Variational Quantum Eigensolver method is one of the promising applications for NISQ-era quantum computers. Designing an efficient ansatz to represent the electronic wave function is crucial in such simulations. Standard unitary coupled-cluster with singles and doubles (UCCSD) ansatz tends to have a large number of insignificant terms that do not lower the energy of the system. In this work, we present a unitary selective coupled-cluster method, a way to construct a unitary coupled-cluster ansatz iteratively using a selection procedure with excitations up to fourth order. This approach uses the electronic Hamiltonian matrix elements and the amplitudes for excitations already present in the ansatz to find the important excitations of higher order and to add them to the ansatz. The important feature of the method is that it systematically reduces the energy error with increasing ansatz size for a set of test molecules. {The main advantage of the proposed method is that the effort to increase the ansatz does not require any additional measurements on a quantum computer.}

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗