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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Implementation of Relativistic Coupled Cluster Theory for Massively Parallel GPU-Accelerated Computing Architectures

In this paper, we report reimplementation of the core algorithms of relativistic coupled cluster theory aimed at modern heterogeneous high-performance computational infrastructures. The code is designed for parallel execution on many compute nodes with optional GPU coprocessing, accomplished via the new ExaTENSOR back end. The resulting ExaCorr module is primarily intended for calculations of molecules with one or more heavy elements, as relativistic effects on the electronic structure are included from the outset. In the current work, we thereby focus on exact two-component methods and demonstrate the accuracy and performance of the software. The module can be used as a stand-alone program requiring a set of molecular orbital coefficients as the starting point, but it is also interfaced to the DIRAC program that can be used to generate these. We therefore also briefly discuss an improvement of the parallel computing aspects of the relativistic self-consistent field algorithm of the DIRAC program.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Panda: A Compiler Framework for Concurrent CPU $+$ GPU Execution of 3D Stencil Computations on GPU-accelerated Supercomputers

We present a new compiler framework for truly heterogeneous 3D stencil computation on GPU clusters. Our framework consists of a simple directive-based programming model and a tightly integrated source-to-source compiler. Annotated with a small number of directives, sequential stencil C codes can be automatically parallelized for large-scale GPU clusters. The most distinctive feature of the compiler is its capability to generate hybrid MPI$+$ CUDA$+$ OpenMP code that uses concurrent CPU$+$ GPU computing to unleash the full potential of powerful GPU clusters. The auto-generated hybrid codes hide the overhead of various data motion by overlapping them with computation. Test results on the Titan supercomputer and the Wilkes cluster show that auto-translated codes can achieve about 90 % of the performance of highly optimized handwritten codes, for both a simple stencil benchmark and a real-world application in cardiac modeling. The user-friendliness and performance of our domain-specific compiler framework allow harnessing the full power of GPU-accelerated supercomputing without painstaking coding effort.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Thermodynamic and morphological analysis of large silicon self-interstitial clusters using atomistic simulations

We study computationally the formation of thermodynamics and morphology of silicon self-interstitial clusters using a suite of methods driven by a recent parameterization of the Tersoff empirical potential. Formation free energies and cluster capture zones are computed across a wide range of cluster sizes (2 < N{sub i} < 150) and temperatures (0.65 < T/T{sub m} < 1). Self-interstitial clusters above a critical size (N{sub i} ∼ 25) are found to exhibit complex morphological behavior in which clusters can assume either a variety of disordered, three-dimensional configurations, or one of two macroscopically distinct planar configurations. The latter correspond to the well-known Frank and perfect dislocation loops observed experimentally in ion-implanted silicon. The relative importance of the different cluster morphologies is a function of cluster size and temperature and is dictated by a balance between energetic and entropic forces. The competition between these thermodynamic forces produces a sharp transition between the three-dimensional and planar configurations, and represents a type of order-disorder transition. By contrast, the smaller state space available to smaller clusters restricts the diversity of possible structures and inhibits this morphological transition.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Coulomb sum rule for 4 He and 16 O from coupled-cluster theory

We demonstrate the capability of coupled-cluster theory to compute the Coulomb sum rule for the 4 He and 16 O nuclei using interactions from chiral effective field theory. We perform several checks, including a few-body benchmark for 4He. We provide an analysis of the center-of-mass contaminations, which we are able to safely remove. We then compare with other theoretical results and experimental data available in the literature, obtaining a fair agreement. This is a first and necessary step towards initiating a program for computing neutrino-nucleus interactions from first principles in coupled-cluster theory and supporting the experimental long-baseline neutrino program with a state-of-the-art theory that can reach medium-mass nuclei.

6 ≤ A ≤ 19A ≤ 5↗
DOE OSTI2016

Computing the cross sections of nuclear reactions with nuclear clusters emission for proton energies between 30 MeV and 2.6 GeV

The cross sections of nuclear reactions involving emission of clusters of light nuclei in proton collisions with a heavy-metal target are computed for incident-proton energies between 30 MeV and 2.6 GeV. The calculation relies on the ALICE/ASH and CASCADE/INPE computer codes. The parameters determining the pre-equilibrium cluster emission are varied in the computation.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

Geometrical and magnetic structure of iron oxide clusters (FeO) n for n > 10

The structure and properties of stoichiometric iron oxide clusters (FeO) n are computed using all-electron density functional theory (DFT) for n > 10. The structures of (FeO) 11 , (FeO) 13 , (FeO) 14 , (FeO) 15 , and (FeO) 16 clusters are reported for the first time. Their lowest total energy states are found to possess spin multiplicities of 5, 5, 47, 27, and 15, respectively. The geometrical structure of the lowest total energy state of a (FeO) n cluster corresponds to chemisorption of oxygen atoms on the surface of the corresponding unary Fen cluster when n > 12. Computed properties of the iron oxide clusters are compared to the properties of the corresponding bare iron clusters. The average binding energy per atom of a (FeO) n cluster is substantially larger than that of Fen at all n. Surprisingly, the values of both polarizability and binding energy per atom of the iron oxide clusters change insignificantly when n increases from two to 16. In order to compare the performance of DFT methods in the iron and iron oxide series, the states of Fe 8 and (FeO) 8 were computed using five exchange–correlation functionals in the whole range of possible spin multiplicities. In conclusion, it is found that the results of computations of the (FeO) 8 cluster are more sensitive to the choice of a DFT functional than those of the Fe 8 cluster.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Predictive coupled-cluster isomer orderings for some Si{sub n}C{sub m} (m, n ≤ 12) clusters: A pragmatic comparison between DFT and complete basis limit coupled-cluster benchmarks

The accurate determination of the preferred Si{sub 12}C{sub 12} isomer is important to guide experimental efforts directed towards synthesizing SiC nano-wires and related polymer structures which are anticipated to be highly efficient exciton materials for the opto-electronic devices. In order to definitively identify preferred isomeric structures for silicon carbon nano-clusters, highly accurate geometries, energies, and harmonic zero point energies have been computed using coupled-cluster theory with systematic extrapolation to the complete basis limit for set of silicon carbon clusters ranging in size from SiC{sub 3} to Si{sub 12}C{sub 12}. It is found that post-MBPT(2) correlation energy plays a significant role in obtaining converged relative isomer energies, suggesting that predictions using low rung density functional methods will not have adequate accuracy. Utilizing the best composite coupled-cluster energy that is still computationally feasible, entailing a 3-4 SCF and coupled-cluster theory with singles and doubles extrapolation with triple-ζ (T) correlation, the closo Si{sub 12}C{sub 12} isomer is identified to be the preferred isomer in the support of previous calculations [X. F. Duan and L. W. Burggraf, J. Chem. Phys. 142, 034303 (2015)]. Additionally we have investigated more pragmatic approaches to obtaining accurate silicon carbide isomer energies, including the use of frozen natural orbital coupled-cluster theory and several rungs of standard and double-hybrid density functional theory. Frozen natural orbitals as a way to compute post-MBPT(2) correlation energy are found to be an excellent balance between efficiency and accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

TURBOMOLE: Modular program suite for ab initio quantum-chemical and condensed-matter simulations

TURBOMOLE is a collaborative, multi-national software development project aiming to provide highly efficient and stable computational tools for quantum chemical simulations of molecules, clusters, periodic systems, and solutions. The TURBOMOLE software suite is optimized for widely available, inexpensive, and resource-efficient hardware such as multi-core workstations and small computer clusters. TURBOMOLE specializes in electronic structure methods with outstanding accuracy–cost ratio, such as density functional theory including local hybrids and the random phase approximation (RPA), GW-Bethe–Salpeter methods, second-order Møller–Plesset theory, and explicitly correlated coupled-cluster methods. TURBOMOLE is based on Gaussian basis sets and has been pivotal for the development of many fast and low-scaling algorithms in the past three decades, such as integral-direct methods, fast multipole methods, the resolution-of-the-identity approximation, imaginary frequency integration, Laplace transform, and pair natural orbital methods. This review focuses on recent additions to TURBOMOLE’s functionality, including excited-state methods, RPA and Green’s function methods, relativistic approaches, high-order molecular properties, solvation effects, and periodic systems. A variety of illustrative applications along with accuracy and timing data are discussed. Moreover, available interfaces to users as well as other software are summarized. TURBOMOLE’s current licensing, distribution, and support model are discussed, and an overview of TURBOMOLE’s development workflow is provided. Challenges such as communication and outreach, software infrastructure, and funding are highlighted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Carnac for Emulytics (HPC Annual Report V.1.0)

Carnac, located at Sandia's California site, is an institutional cluster for Emulytics that provides security researchers with resources to model enterprise computer networks and evaluate how resilient they are from attacks. While multiple Emulytics cluster computers have been built at Sandia, Carnac is the first system that was developed as an institutional resource that can be shared among different groups with disparate requirements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Calculating the Symmetry Number of Flexible Sphere Clusters

We present a theoretical and computational framework to compute the symmetry number of a flexible sphere cluster in R 3 , using a definition of symmetry that arises naturally when calculating the equilibrium probability of a cluster of spheres in the sticky-sphere limit. We define the sticky symmetry group of the cluster as the set of permutations and inversions of the spheres which preserve adjacency and can be realized by continuous deformations of the cluster that do not change the set of contacts or cause particles to overlap. The symmetry number is the size of the sticky symmetry group. We introduce a numerical algorithm to compute the sticky symmetry group and symmetry number, and show it works well on several test cases. Furthermore, we show that once the sticky symmetry group has been calculated for indistinguishable spheres, the symmetry group for partially distinguishable spheres (those with nonidentical interactions) can be efficiently obtained without repeating the laborious parts of the computations. Finally, we use our algorithm to calculate the partition functions of every possible connected cluster of six identical sticky spheres, generating data that may be used to design interactions between spheres so they self-assemble into a desired structure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Equation-of-motion internally contracted multireference unitary coupled-cluster theory

The accurate computation of excited states remains a challenge in electronic structure theory, especially for systems with a ground state that requires a multireference treatment. In this work, we introduce a novel equation-of-motion (EOM) extension of the internally contracted multireference unitary coupled-cluster framework (ic-MRUCC), termed EOM-ic-MRUCC. EOM-ic-MRUCC follows the transform-then-diagonalize approach, in analogy to its non-unitary counterpart. By employing a projective approach to optimize the ground state, the method retains additive separability and proper scaling with system size. We show that excitation energies are size-intensive if the EOM operator satisfies the “killer” and the projective conditions. Furthermore, we propose to represent changes in the reference state upon electron excitation via projected many-body operators that span the active orbitals and show that the EOM equations formulated in this way are invariant with respect to active orbital rotations. We test the EOM-ic-MRUCC method truncated to single and double excitations by computing the potential energy curves for several excited states of a BeH2 model system, the HF molecule, and water undergoing symmetric dissociation. Across these systems, our method delivers accurate excitation energies and potential energy curves within 5 mE h (∼0.14 eV) from full configuration interaction. Here, we find that truncating the Baker–Campbell–Hausdorff series to fourfold commutators contributes negligible errors (on the order of 10 −5 E h or less), offering a practical route to highly accurate excited-state calculations with reduced computational overhead.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2015

Coarse-Grained Clustering Dynamics of Heterogeneously Coupled Neurons

The formation of oscillating phase clusters in a network of identical Hodgkin–Huxley neurons is studied, along with their dynamic behavior. The neurons are synaptically coupled in an all-to-all manner, yet the synaptic coupling characteristic time is heterogeneous across the connections. In a network of N neurons where this heterogeneity is characterized by a prescribed random variable, the oscillatory single-cluster state can transition—through (possibly perturbed) period-doubling and subsequent bifurcations—to a variety of multiple-cluster states. The clustering dynamic behavior is computationally studied both at the detailed and the coarse-grained levels, and a numerical approach that can enable studying the coarse-grained dynamics in a network of arbitrarily large size is suggested. Among a number of cluster states formed, double clusters, composed of nearly equal sub-network sizes are seen to be stable; interestingly, the heterogeneity parameter in each of the double-cluster components tends to be consistent with the random variable over the entire network: Given a double-cluster state, permuting the dynamical variables of the neurons can lead to a combinatorially large number of different, yet similar “fine” states that appear practically identical at the coarse-grained level. For weak heterogeneity we find that correlations rapidly develop, within each cluster, between the neuron’s “identity” (its own value of the heterogeneity parameter) and its dynamical state. For single- and double-cluster states we demonstrate an effective coarse-graining approach that uses the Polynomial Chaos expansion to succinctly describe the dynamics by these quickly established “identity-state” correlations. This coarse-graining approach is utilized, within the equation-free framework, to perform efficient computations of the neuron ensemble dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

FPDeep: Scalable Acceleration of CNN Training on Deeply-Pipelined FPGA Clusters

In this paper, we propose a framework called FPDeep, which uses a hybrid of model and layer paral- lelism to configure distributed reconfigurable clusters to train DNNs. This approach has numerous benefits. First, the design does not suffer from batch size growth. Second, novel workload and weight partitioning leads to balanced loads of both among nodes. And third, the entire system is fine-grained pipeline. This leads to high parallelism and utilization and also minimizes the time features need to be cached while waiting for back-propagation.

Wang, Tianqi↗
DOE OSTI2014

Parallel Optical Flow Processing of 4D Cardiac CT Data on Multicore Clusters, In: 2014 IEEE 17th International Conference on Computational Science and Engineering

Optical flow is the distribution of apparent velocities of movement of brightness patterns in a sequence of images. For large 3D image sequences, optical flow applications are time consuming and memory-bound. To cope with these problems, in this paper, we present parallel optical flow processing of 4D cardiac CT data on multicore cluster systems to significantly shorten the time for computing velocity fields of the heart in order to aid cardiologists in diagnosing heart disease such as myocardial infarction and cardiac dysrhythmia in time. First, we modify and extend two traditional 2D optical flow methods Horn-Schunck and Lucas-Kanade to three-dimensional cases to process the 4D cardiac CT data. Second, we extend Mat lab MPI to support parallel computing with Mat lab and Octave on these cluster systems. Then we develop the parallel Mat lab/Octave optical flow applications for the 4D cardiac CT data in detail. Our experimental results show that these parallel optical flow applications have good scalability with close to linear speedup, and are able to shorten the image processing time significantly from more than 5 hours on 4 cores to 1.5 minutes on 1024 cores.

Engineering↗
DOE OSTI2014

Evaluation of the Computing Systems for Yucca Mountain Repository TSPA-LA Model Operational Readiness

Sandia National Laboratories (SNL) was tasked to conduct an evaluation of the legacy computing systems of the now-closed Yucca Mountain Project (YMP) to maintain the operational readiness of the computing infrastructure (computer hardware and software) and knowledge capability for total system performance assessment (TSPA) type analysis, in the event that the License Application (LA) review by the U.S. Nuclear Regulatory Commission (NRC) is re-started and involves additional requests for information (RAIs). Six problem areas or components of the computing system were identified and subsequently resolved or improved to ensure the operational readiness of the TSPA-LA model capability on the server cluster. As part of this readiness review, the legacy TSPA computational cluster that was relocated from the SNL YMP Lead Lab Project Office in Las Vegas, Nevada to the SNL offices in Albuquerque, New Mexico was replaced with new hardware. Three floating licenses of Goldsim Version 9.60.300 were installed on the new cluster head node, and its distributed processing capability was mapped on the cluster processors. Other supporting software was tested and installed to support the TSPA- type analysis on the server cluster. TSPA-LA modeling cases were tested and verified for the model reproducibility on the current server cluster. All test runs were executed on multiple processors on the server cluster utilizing the Goldsim distributed processing capability, and all runs were completed successfully. The model reproducibility verification was evaluated by two approaches: numerical value comparison and graphical comparison, and the analysis demonstrated an excellent reproducibility of the TSPA-LA model runs on the server cluster. The current server cluster and supporting software systems are fully operational to support TSPA-LA type analysis.

97 MATHEMATICS AND COMPUTING↗