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At least 649 records · Page 36

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DOE OSTI2016

Ultra-fast computation of electronic spectra for large systems by tight-binding based simplified Tamm-Dancoff approximation (sTDA-xTB)

The computational bottleneck of the extremely fast simplified Tamm-Dancoff approximated (sTDA) time-dependent density functional theory procedure [S. Grimme, J. Chem. Phys. 138, 244104 (2013)] for the computation of electronic spectra for large systems is the determination of the ground state Kohn-Sham orbitals and eigenvalues. This limits such treatments to single structures with a few hundred atoms and hence, e.g., sampling along molecular dynamics trajectories for flexible systems or the calculation of chromophore aggregates is often not possible. The aim of this work is to solve this problem by a specifically designed semi-empirical tight binding (TB) procedure similar to the well established self-consistent-charge density functional TB scheme. The new special purpose method provides orbitals and orbital energies of hybrid density functional character for a subsequent and basically unmodified sTDA procedure. Compared to many previous semi-empirical excited state methods, an advantage of the ansatz is that a general eigenvalue problem in a non-orthogonal, extended atomic orbital basis is solved and therefore correct occupied/virtual orbital energy splittings as well as Rydberg levels are obtained. A key idea for the success of the new model is that the determination of atomic charges (describing an effective electron-electron interaction) and the one-particle spectrum is decoupled and treated by two differently parametrized Hamiltonians/basis sets. The three-diagonalization-step composite procedure can routinely compute broad range electronic spectra (0-8 eV) within minutes of computation time for systems composed of 500-1000 atoms with an accuracy typical of standard time-dependent density functional theory (0.3-0.5 eV average error). An easily extendable parametrization based on coupled-cluster and density functional computed reference data for the elements H–Zn including transition metals is described. The accuracy of the method termed sTDA-xTB is first benchmarked for vertical excitation energies of open- and closed-shell systems in comparison to other semi-empirical methods and applied to exemplary problems in electronic spectroscopy. As side products of the development, a robust and efficient valence electron TB method for the accurate determination of atomic charges as well as a more accurate calculation scheme of dipole rotatory strengths within the Tamm-Dancoff approximation is proposed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Photoelectron Spectroscopy and Computational Study on Microsolvated [B 10 H 10 ] 2– Clusters and Comparisons to Their [B 12 H 12 ] 2– Analogues

Microhydrated closo-Boranes have attracted great interests due to their superchaotropic activity related to well-known Hofmeister effect and important applications in biomedical and battery fields. In this work, we report a combined negative ion photoelectron spectroscopy and quantum chemical investigation on hydrated closo-decaborate clusters [B 10 H 10 ] 2- ·nH 2 O (n = 1 – 7) with a direct comparison to their analogues [B 12 H 12 ] 2- ·nH 2 O and free water clusters. A single H 2 O molecule is found sufficient to stabilize the intrinsically unstable [B 10 H 10 ] 2- dianion. The first two water molecules strongly interact with the solute forming B-H···H-O dihydrogen bonds while additional water molecules show substantially reduced binding energies. Unlike [B 12 H 12 ] 2- ·nH 2 O possessing highly structured water network with the attached H 2 O molecules arranged in a unified pattern by maximizing B-H···H-O dihydrogen bonding, distinct structural arrangements of the water clusters within [B 10 H 10 ] 2– ·nH 2 O are achieved with the water cluster networks from trimer to heptamer resembling free water clusters. Such a distinct difference arises from the variations in size, symmetry, and charge distributions between these two dianions. Finally, the present finding again confirms the structural diversity of hydrogen-bonding networks in microhydrated closo-boranes and enrich our understanding of aqueous borate chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Microcarbonation of Naphthalene: An Experimental and Computational Study of Photoionization in Naphthalene-Carbon Dioxide Clusters

The photoionization of naphthalene (N)-carbon dioxide (CO 2 ) clusters was studied using tunable vacuum ultraviolet (VUV) radiation from a synchrotron in the photon range of 8.0 to 13.7 eV, in combination with time-of-flight mass spectrometry. Clusters of monomer, dimer, and trimer naphthalene with CO 2 (N(CO 2 ) 0–6 , N 2 (CO 2 ) 0–3 , N3) were observed. The lowest-energy conformers were obtained via a conformer search, followed by geometry optimizations at the ωB97X-V2/aug-cc-pVTZ (monomer) and ωB97X-V2/aug-cc-pVDZ (dimer) levels of theory. Carbon dioxide was found to preferentially cluster on top of the naphthalene molecule (in an out-of-plane configuration). From the mass spectra, photoionization intensity curves (PICs) were constructed, and appearance energies (AEs) were determined. No substantial trend in AE was observed with increasing size of the naphthalene-carbon dioxide clusters; rather, AE oscillations around the value for pure naphthalene were observed. These AE oscillations are also observed in a recently studied naphthalene-water cluster system, though in this system a slight downward trend in AE for pure naphthalene clusters (N1/2/3/4) was observed. The differences between the two systems are attributed to differing interaction strengths. In conclusion, understanding these differences may aid in determining how photoprocessing can proceed differently depending on the dominant matrix component in interstellar ices.

Wannenmacher, Anna [Lawrence Berkeley National Lab↗

DOE OSTI2023

A Multi-Armed Bayesian Ordinal Outcome Utility-Based Sequential Trial with a Pairwise Null Clustering Prior

A multi-armed trial based on ordinal outcomes is proposed that leverages a flexible non-proportional odds cumulative logit model and numerical utility scores for each outcome to determine treatment optimality. This trial design uses a Bayesian clustering prior on the treatment effects that encourages the pairwise null hypothesis of no differences between treatments. A group sequential design is proposed to determine which treatments are clinically different with an adaptive decision boundary that becomes more aggressive as the sample size or clinical significance grows, or the number of active treatments decreases. A simulation study is conducted for 3 and 5 treatment arms, which shows that the design has superior operating characteristics (family wise error rate, generalized power, average sample size) compared to utility designs that do not allow clustering, a frequentist proportional odds model, or a permutation test based on empirical mean utilities.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1979

On evaluating clustering procedures for use in classification

The problem of evaluating clustering algorithms and their respective computer programs for use in a preprocessing step for classification is addressed. In clustering for classification the probability of correct classification is suggested as the ultimate measure of accuracy on training data. A means of implementing this criterion and a measure of cluster purity are discussed. Examples are given. A procedure for cluster labeling that is based on cluster purity and sample size is presented.

Pore, M. D.↗

NASA NTRS1998

Navier-Stokes Computations on Commodity Computers

In this paper we discuss and demonstrate the feasibility of solving high-fidelity, nonlinear computational fluid dynamics (CFD) problems of practical interest on commodity machines, namely Pentium Pro PC's. Such calculations have now become possible due to the progress in computational power and memory of the off-the-shelf commodity computers, along with the growth in bandwidth and communication speeds of networks. A widely used CFD code known as TLNS3D, which was developed originally on large shared memory computers was selected for this effort. This code has recently been ported to massively parallel processor (MPP) type machines, where natural partitioning along grid blocks is adopted in which one or more blocks are distributed to each of the available processors. In this paper, a similar approach is adapted to port this code to a cluster of Pentium Pro computers. The message passing among the processors is accomplished through the use of standard message passing interface (MPI) libraries. Scaling studies indicate fairly high level of parallelism on such clusters of commodity machines, thus making solutions to Navier-Stokes equations for practical problems more affordable.

Vatsa, Veer N.↗

NASA NTRS1987

Simulation studies for surfaces and materials strength

A realistic potential energy function comprising angle dependent terms was employed to describe the potential surface of the N+O2 system. The potential energy parameters were obtained from high level ab-initio results using a nonlinear fitting procedure. It was shown that the potential function is able to reproduce a large number of points on the potential surface with a small rms deviation. A literature survey was conducted to analyze exclusively the status of current small cluster research. This survey turned out to be quite useful in understanding and finding out the existing relationship between theoretical as well as experimental investigative techniques employed by different researchers. Additionally, the importance of the role played by computer simulation in small cluster research, was documented.

Halicioglu, Timur↗

DOE OSTI2024

Streaming Matching and Edge Cover in Practice

Graph algorithms with polynomial space and time requirements often become infeasible for massive graphs with billions of edges or more. State-of-the-art approaches therefore employ approximate serial, parallel, and distributed algorithms to tackle these challenges. However, such approaches require storing the entire graph in memory and thus need access to costly computing resources such as clusters and supercomputers. In this paper, we present practical streaming approaches for solving massive graph problems using limited memory for two prototypical graph problems: maximum weighted matching and minimum weighted edge cover. For matching, we conduct a thorough computational study on two of the semi-streaming algorithms including a recent breakthrough result that achieves a $1/(2+\varepsilon)$-approximation of the weight while using $O( n \log W /\epsilon)$ memory (here $n$ is the number of vertices and $W$ is the maximum edge weight), designed by Paz and Schwartzman [SODA, 2017]. Empirically, we show that the semi-streaming algorithms produce matchings whose weight is close to the best $1/2$-approximate offline algorithm while requiring less time and an order-of-magnitude less memory. For minimum weighted edge cover, we develop three novel semi-streaming algorithms. Two of these algorithms require a single pass through the input graph, require $O(n \log n)$ memory, and provide a 2-approximation guarantee on the objective. We also leverage a relationship between approximate maximum weighted matching and approximate minimum weighted edge cover to develop a two-pass $3/2+\epsilon$-approximate algorithm with the memory requirement of Paz and Schwartzman's semi-streaming matching algorithm. These streaming approaches are compared against the state-of-the-art 3/2-approximate offline algorithm. The semi-streaming matching and the novel edge cover algorithms proposed in this paper can process graphs with several billions of edges in under 30 minutes using 6 GB of memory, which is at least an order of magnitude improvement from the offline (non-streaming) algorithms. For the largest graph, the best alternative offline parallel approximation algorithm (GPA+ROMA) could not finish in three hours even while employing hundreds of processors and 1 TB of memory. We also demonstrate an application of the semi-streaming algorithm by computing a matching using linearly bounded memory on item intersection graphs derived from three machine learning datasets, whereas the existing offline algorithms could not complete on one of these datasets since their memory requirements exceeded 1TB.

Ferdous, S M.↗

DOE OSTI2017

Compiling on Linux Clusters

This is a presentation for LANL's Parallel Computing Summer Research Internship that describes the process of compiling Linux clusters.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

A Generic Advanced Computing Framework for Executing Windows-based Dynamic Contingency Analysis Tool in Parallel on Cluster Machines

Dynamic contingency analysis tool (DCAT) has been developed to assess the impact and likelihood of extreme contingencies and potential cascading events across their systems and interconnections. By including more customized protection models and corrective actions into the Windows-based commercial tools, DCAT can help operators understand the cascading behavior and find mitigation approaches to reduce the risk of cascading outages in a more realistic manner. In order to further enhance the capability of DCAT, this paper presents a design of an advanced computing framework that enables DCAT to run on a cluster machine to improve its computational performance. This framework is generic and can be applied to other Windows-based simulation tools to fill the technical gap of applying advanced computing technology to vendors' Windows-based tools. The preliminary tests using medium to large power systems have shown the effectiveness of this framework and its potential for accelerating the adoption of advanced computing in utilities.

Advanced computing, dynamic contingency analysis, ↗

DOE OSTI2024

Community detection in hypergraphs via mutual information maximization

Abstract The hypergraph community detection problem seeks to identify groups of related vertices in hypergraph data. We propose an information-theoretic hypergraph community detection algorithm which compresses the observed data in terms of community labels and community-edge intersections. This algorithm can also be viewed as maximum-likelihood inference in a degree-corrected microcanonical stochastic blockmodel. We perform the compression/inference step via simulated annealing. Unlike several recent algorithms based on canonical models, our microcanonical algorithm does not require inference of statistical parameters such as vertex degrees or pairwise group connection rates. Through synthetic experiments, we find that our algorithm succeeds down to recently-conjectured thresholds for sparse random hypergraphs. We also find competitive performance in cluster recovery tasks on several hypergraph data sets.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1986

Analyzing Multidimensional Image Data

Six computer programs perform histogram cluster analysis. Histogram Cluster Analysis Procedure (HICAP) developed to perform unsupervised classification of multidimensional image data. Clustering approach used in HICAP based on algorithm which uses multidimensional histogram to perform unsupervised classification of four-dimensional Landsat multispectral-scanner data. HICAP generalizes this procedure to process up to 32-bit data with arbitrary number of dimensions. Also incorporates efficiency improvements so classification requires less computation than original algorithm. Computational savings afforded by HICAP increase with number of dimensions in data. HICAP programs written in FORTRAN 77 for batch or interactive execution.

Wharton, S. W.↗

DOE OSTI2017

Dark Energy Survey Year 1 Results: Cross-Correlation Redshifts in the DES -- Calibration of the Weak Lensing Source Redshift Distributions

We present the calibration of the Dark Energy Survey Year 1 (DES Y1) weak lensing source galaxy redshift distributions from clustering measurements. By cross-correlating the positions of source galaxies with luminous red galaxies selected by the redMaGiC algorithm we measure the redshift distributions of the source galaxies as placed into different tomographic bins. These measurements constrain any such shifts to an accuracy of $\sim0.02$ and can be computed even when the clustering measurements do not span the full redshift range. The highest-redshift source bin is not constrained by the clustering measurements because of the minimal redshift overlap with the redMaGiC galaxies. We compare our constraints with those obtained from $\texttt{COSMOS}$ 30-band photometry and find that our two very different methods produce consistent constraints.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Adaptive Conformer Sampling for Property Prediction Using the Conductor-like Screening Model for Real Solvents

The valorization of lignocellulose-derived bioproducts requires effective separation from excessive water. Liquid–liquid extraction is a promising low-energy separation technology, but effective extraction requires solvent selection based on the thermodynamic properties of the bioproduct and solvent components. We propose a computational framework for predicting such properties by developing an adaptive conformer selection approach for use with COSMO-RS (conductor-like screening model for real solvents) calculations. In this framework, molecular dynamics simulations are used to generate many molecular structures (conformers) at representative temperatures in varying solvent environments. Conformers are then clustered based on structural metrics in a low-dimensional space and selected using a mixed-integer quadratic programming problem to iteratively insert a sampled conformer. At each iteration, we determine bioproduct properties using COSMO-RS. Here, we demonstrate the capability of the proposed framework on representative bioproducts to show convergence of the adaptive sampling toward experimentally measured properties with fewer calculations than required by random conformer sampling, enabling the improved screening of solvent systems for liquid-phase separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1994

Fuzzy logic, neural networks, and soft computing

The past few years have witnessed a rapid growth of interest in a cluster of modes of modeling and computation which may be described collectively as soft computing. The distinguishing characteristic of soft computing is that its primary aims are to achieve tractability, robustness, low cost, and high MIQ (machine intelligence quotient) through an exploitation of the tolerance for imprecision and uncertainty. Thus, in soft computing what is usually sought is an approximate solution to a precisely formulated problem or, more typically, an approximate solution to an imprecisely formulated problem. A simple case in point is the problem of parking a car. Generally, humans can park a car rather easily because the final position of the car is not specified exactly. If it were specified to within, say, a few millimeters and a fraction of a degree, it would take hours or days of maneuvering and precise measurements of distance and angular position to solve the problem. What this simple example points to is the fact that, in general, high precision carries a high cost. The challenge, then, is to exploit the tolerance for imprecision by devising methods of computation which lead to an acceptable solution at low cost. By its nature, soft computing is much closer to human reasoning than the traditional modes of computation. At this juncture, the major components of soft computing are fuzzy logic (FL), neural network theory (NN), and probabilistic reasoning techniques (PR), including genetic algorithms, chaos theory, and part of learning theory. Increasingly, these techniques are used in combination to achieve significant improvement in performance and adaptability. Among the important application areas for soft computing are control systems, expert systems, data compression techniques, image processing, and decision support systems. It may be argued that it is soft computing, rather than the traditional hard computing, that should be viewed as the foundation for artificial intelligence. In the years ahead, this may well become a widely held position.

Zadeh, Lofti A.↗

DOE OSTI2016

Quantum Chemistry via Walks in Determinant Space

There are many chemical questions of practical interest to the DOE that could be answered if there were an electronic structure method that provided consistently accurate results for all systems at an affordable computational cost. The coupled cluster method with single, double and perturbative triple excitations (CCSD(T)) is the most frequently used high-order method, but it has known deficiencies, e.g., in the description of stretched bonds. The full configuration interaction (FCI) method is the most robust method for treating electronic correlations, but it is little used because its computational cost scales exponentially in the size of the system. The largest calculation that has been done to date employed 10 billion determinants. In this regard, there was a major advance in 2010. The Alavi group at Cambridge University developed a stochastic approach to FCI --- combining it with ideas from quantum Monte Carlo (QMC) --- called FCIQMC, that allows one to go to a far larger number of determinants in certain circumstances. The computational cost is exponential in the system and basis size but with a much reduced exponent compared to conventional FCI. In this project Umrigar's group made several major improvements to the FCIQMC method that increased its efficiency by many orders of magnitude. In addition this project resulted in a cross-fertilization of ideas between the FCIQMC method, the older phaseless auxilliary-field quantum Monte Carlo (AFQMC) method developed by Zhang and Krakauer (two of the PI's of this project), and symmetry-restored wavefunctions developed by Scuseria (also a PI of this project).

36 MATERIALS SCIENCE↗

DOE OSTI2015

Structure of overheated metal clusters: MD simulation study

The structure of overheated metal clusters appeared in condensation process was studied by computer simulation techniques. It was found that clusters with size larger than several tens of atoms have three layers: core part, intermediate dense packing layer and a gas- like shell with low density. The change of the size and structure of these layers with the variation of internal energy and the size of cluster is discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1995

The coupling of fluids, dynamics, and controls on advanced architecture computers

This grant provided for the demonstration of coupled controls, body dynamics, and fluids computations in a workstation cluster environment; and an investigation of the impact of peer-peer communication on flow solver performance and robustness. The findings of these investigations were documented in the conference articles.The attached publication, 'Towards Distributed Fluids/Controls Simulations', documents the solution and scaling of the coupled Navier-Stokes, Euler rigid-body dynamics, and state feedback control equations for a two-dimensional canard-wing. The poor scaling shown was due to serialized grid connectivity computation and Ethernet bandwidth limits. The scaling of a peer-to-peer communication flow code on an IBM SP-2 was also shown. The scaling of the code on the switched fabric-linked nodes was good, with a 2.4 percent loss due to communication of intergrid boundary point information. The code performance on 30 worker nodes was 1.7 (mu)s/point/iteration, or a factor of three over a Cray C-90 head. The attached paper, 'Nonlinear Fluid Computations in a Distributed Environment', documents the effect of several computational rate enhancing methods on convergence. For the cases shown, the highest throughput was achieved using boundary updates at each step, with the manager process performing communication tasks only. Constrained domain decomposition of the implicit fluid equations did not degrade the convergence rate or final solution. The scaling of a coupled body/fluid dynamics problem on an Ethernet-linked cluster was also shown.

Atwood, Christopher↗