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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

A hybrid computational strategy to address WGS variant analysis in >5000 samples

Abstract Background The decreasing costs of sequencing are driving the need for cost effective and real time variant calling of whole genome sequencing data. The scale of these projects are far beyond the capacity of typical computing resources available with most research labs. Other infrastructures like the cloud AWS environment and supercomputers also have limitations due to which large scale joint variant calling becomes infeasible, and infrastructure specific variant calling strategies either fail to scale up to large datasets or abandon joint calling strategies. Results We present a high throughput framework including multiple variant callers for single nucleotide variant (SNV) calling, which leverages hybrid computing infrastructure consisting of cloud AWS, supercomputers and local high performance computing infrastructures. We present a novel binning approach for large scale joint variant calling and imputation which can scale up to over 10,000 samples while producing SNV callsets with high sensitivity and specificity. As a proof of principle, we present results of analysis on Cohorts for Heart And Aging Research in Genomic Epidemiology (CHARGE) WGS freeze 3 dataset in which joint calling, imputation and phasing of over 5300 whole genome samples was produced in under 6 weeks using four state-of-the-art callers. The callers used were SNPTools, GATK-HaplotypeCaller, GATK-UnifiedGenotyper and GotCloud. We used Amazon AWS, a 4000-core in-house cluster at Baylor College of Medicine, IBM power PC Blue BioU at Rice and Rhea at Oak Ridge National Laboratory (ORNL) for the computation. AWS was used for joint calling of 180 TB of BAM files, and ORNL and Rice supercomputers were used for the imputation and phasing step. All other steps were carried out on the local compute cluster. The entire operation used 5.2 million core hours and only transferred a total of 6 TB of data across the platforms. Conclusions Even with increasing sizes of whole genome datasets, ensemble joint calling of SNVs for low coverage data can be accomplished in a scalable, cost effective and fast manner by using heterogeneous computing platforms without compromising on the quality of variants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Connected three-body terms in single-reference unitary many-body theories: Iterative and perturbative approximations

This work introduces various approaches to include connected three-body terms in unitary many-body theories, focusing on the driven similarity renormalization group (DSRG). Starting from the least approximate method—the linearized DSRG truncated to one-, two-, and three-body operators [LDSRG(3)]—we develop several approximate LDSRG(3) models with reduced computational cost. Through a perturbative analysis, we motivate a family of iterative LDSRG(3)-n and -n' (n = 1, 2, 3, 4) methods that contain a subset of the LDSRG(3) diagrams. Among these variants, the LDSRG(3)-2 scheme has the same computational complexity of coupled cluster theory with singles, doubles, and triples (CCSDT), but it outperforms CCSDT in the accuracy of the predicted correlation energies. We also propose and implement two perturbative triples corrections based on the linearized DSRG truncated to one- and two-body operators augmented with recursive semi-quadratic commutators [qDSRG(2)]. Overall, the resulting qDSRG(2)+(T) approach matches the accuracy of the “gold-standard” coupled cluster theory with singles, doubles, and perturbative triples model on the energetics of twenty-eight closed-shell atoms and small molecules.

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

Simulation of circularly polarized luminescence spectra using coupled cluster theory

We report the first computations of circularly polarized luminescence (CPL) rotatory strengths at the equation-of-motion coupled cluster singles and doubles (EOM-CCSD) level of theory. Using a test set of eight chiral ketones, we compare both dipole and rotatory strengths for absorption (electronic circular dichroism) and emission to the results from time-dependent density-functional theory (TD-DFT) and available experimental data for both valence and Rydberg transitions. For two of the compounds, we obtained optimized geometries of the lowest several excited states using both EOM-CCSD and TD-DFT and determined that structures and EOM-CCSD transition properties obtained with each structure were sufficiently similar that TD-DFT optimizations were acceptable for the remaining test cases. Agreement between EOM-CCSD and the Becke three-parameter exchange function and Lee-Yang-Parr correlation functional (B3LYP) corrected using the Coulomb attenuating method (CAM-B3LYP) is typically good for most of the transitions, though agreement with the uncorrected B3LYP functional is significantly worse for all reported properties. The choice of length vs. velocity representation of the electric dipole operator has little impact on the EOM-CCSD transition strengths for nearly all of the states we examined. For a pair of closely related β, γ-enones, (1R)-7-methylenebicyclo[2.2.1]heptan-2-one and (1S)-2-methylenebicyclo[2.2.1]heptan-7-one, we find that EOM-CCSD and CAM-B3LYP agree with the energetic ordering of the two possible excited-state conformations, resulting in good agreement with experimental rotatory strengths in both absorption and emission, whereas B3LYP yields a qualitatively incorrect result for the CPL signal of (1S)-2-methylenebicyclo[2.2.1]heptan-7-one. Finally, we predict that one of the compounds considered here, trans-bicyclo[3.3.0]octane-3,7-dione, is unique in that it exhibits an achiral ground state and a chiral first excited state, leading to a strong CPL signal but a weak circular dichroism signal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

The WFPC2 ultraviolet survey: The blue straggler population in NGC 5824

We have used a combination of high-resolution Hubble Space Telescope Wide Field Planetary Camera 2 and wide-field ground-based observations, in ultraviolet and optical bands, to study the blue straggler star population of the massive outer halo globular cluster NGC 5824 over its entire radial extent. We have computed the center of the cluster and constructed the radial density profile from detailed star counts. The profile is well reproduced by a Wilson model with a small core (r{sub c} ≅ 4.''4) and a concentration parameter c ≅ 2.74. We also present the first age determination for this cluster. From a comparison with isochrones, we find t = 13 ± 0.5 Gyr. We discuss this result in the context of the observed age-metallicity relation of Galactic globular clusters. A total of 60 bright blue stragglers has been identified. Their radial distribution is found to be bimodal, with a central peak, a well-defined minimum at r ∼ 20'', and an upturn at large radii. In the framework of the dynamical clock recently defined by Ferraro et al., this feature suggests that NGC 5824 is a cluster of intermediate dynamical age.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Machine learning based job status prediction in scientific clusters

Large high-performance computing systems are built with increasing number of components with more CPU cores, more memory, and more storage space. At the same time, scientific applications have been growing in complexity. Together, they are leading to more frequent unsuccessful job statuses on HPC systems. From measured job statuses, 23.4% of CPU time was spent to the unsuccessful jobs. Here, we set out to study whether these unsuccessful job statuses could be anticipated from known job characteristics. To explore this possibility, we have developed a job status prediction method for the execution of jobs on scientific clusters. The Random Forests algorithm was applied to extract and characterize the patterns of unsuccessful job statuses. Experimental results show that our method can predict the unsuccessful job statuses from the monitored ongoing job executions in 99.8% the cases with 83.6% recall and 94.8% precision. Lastly, this prediction accuracy can be sufficiently high that it can be used to mitigation procedures of predicted failures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Cluster Morphology-Polymer Dynamics Correlations in Sulfonated Polystyrene Melts: Computational Study

Reaching exceptionally long times up to 500 ns in equilibrium and nonequilibrium molecular dynamics simulations studies, we have attained a fundamental molecular understanding of the correlation of ionomer clusters structure and multiscale dynamics, providing new insight into one critical, long-standing challenge in ionic polymer physics. The cluster structure in melts of sulfonated polystyrene with Na + and Mg 2+ counterions are resolved and correlated with the dynamics on multiple length and time scales extracted from measurements of the dynamic structure factor and shear rheology. We find that as the morphology of the ionic clusters changes from ladderlike for Na + to disordered structures for Mg 2+ , the dynamic structure factor is affected on the length scale corresponding to the ionic clusters. Lastly, rheology studies show that the viscosity for Mg 2+ melts is higher than for Na + ones for all shear rates, which is well correlated with the larger ionic clusters’ size for the Mg 2+ melts.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Emergent properties of nuclei from ab initio coupled-cluster calculations

Emergent properties such as nuclear saturation and deformation, and the effects on shell structure due to the proximity of the scattering continuum and particle decay channels are fascinating phenomena in atomic nuclei. In recent years, ab initio approaches to nuclei have taken the first steps towards tackling the computational challenge of describing these phenomena from Hamiltonians with microscopic degrees of freedom. Our endeavor is now possible due to ideas from effective field theories, novel optimization strategies for nuclear interactions, ab initio methods exhibiting a soft scaling with mass number, and ever-increasing computational power. We review some of the recent accomplishments. We also present new results. The recently optimized chiral interaction NNLO${}_{{\rm{sat}}}$ is shown to provide an accurate description of both charge radii and binding energies in selected light- and medium-mass nuclei up to 56Ni. We derive an efficient scheme for including continuum effects in coupled-cluster computations of nuclei based on chiral nucleon–nucleon and three-nucleon forces, and present new results for unbound states in the neutron-rich isotopes of oxygen and calcium. Finally, the coupling to the continuum impacts the energies of the ${J}^{\pi }=1/{2}^{-},3/{2}^{-},7/{2}^{-},3/{2}^{+}$ states in ${}^{\mathrm{17,23,25}}$O, and—contrary to naive shell-model expectations—the level ordering of the ${J}^{\pi }=3/{2}^{+},5/{2}^{+},9/{2}^{+}$ states in ${}^{\mathrm{53,55,61}}$Ca.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

THE POWER OF IMAGING: CONSTRAINING THE PLASMA PROPERTIES OF GRMHD SIMULATIONS USING EHT OBSERVATIONS OF Sgr A*

Recent advances in general relativistic magnetohydrodynamic simulations have expanded and improved our understanding of the dynamics of black-hole accretion disks. However, current simulations do not capture the thermodynamics of electrons in the low density accreting plasma. This poses a significant challenge in predicting accretion flow images and spectra from first principles. Because of this, simplified emission models have often been used, with widely different configurations (e.g., disk- versus jet-dominated emission), and were able to account for the observed spectral properties of accreting black holes. Exploring the large parameter space introduced by such models, however, requires significant computational power that exceeds conventional computational facilities. In this paper, we use GRay, a fast graphics processing unit (GPU) based ray-tracing algorithm, on the GPU cluster El Gato, to compute images and spectra for a set of six general relativistic magnetohydrodynamic simulations with different magnetic field configurations and black-hole spins. We also employ two different parametric models for the plasma thermodynamics in each of the simulations. We show that, if only the spectral properties of Sgr A* are used, all 12 models tested here can fit the spectra equally well. However, when combined with the measurement of the image size of the emission using the Event Horizon Telescope, current observations rule out all models with strong funnel emission, because the funnels are typically very extended. Our study shows that images of accretion flows with horizon-scale resolution offer a powerful tool in understanding accretion flows around black holes and their thermodynamic properties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

FORMATION AND PROPERTIES OF ASTROPHYSICAL CARBONACEOUS DUST. I. AB-INITIO CALCULATIONS OF THE CONFIGURATION AND BINDING ENERGIES OF SMALL CARBON CLUSTERS

The binding energies of n < 100 carbon clusters are calculated using the ab initio density functional theory code Quantum Espresso. Carbon cluster geometries are determined using several levels of classical techniques and further refined using density functional theory. The resulting energies are used to compute the work of cluster formation and the nucleation rate in a saturated, hydrogen-poor carbon gas. Compared to classical calculations that adopt the capillary approximation, we find that nucleation of carbon clusters is enhanced at low temperatures and depressed at high temperatures. This difference is ascribed to the different behavior of the critical cluster size. We find that the critical cluster size is at n = 27 or n = 8 for a broad range of temperatures and saturations, instead of being a smooth function of such parameters. The results of our calculations can be used to follow carbonaceous cluster/grain formation, stability, and growth in hydrogen-poor environments, such as the inner layers of core-collapse supernovae and supernova remnants.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The HEPCloud Facility: elastic computing for High Energy Physics – The NOvA Use Case

The need for computing in the HEP community follows cycles of peaks and valleys mainly driven by conference dates, accelerator shutdown, holiday schedules, and other factors. Because of this, the classical method of provisioning these resources at providing facilities has drawbacks such as potential overprovisioning. As the appetite for computing increases, however, so does the need to maximize cost efficiency by developing a model for dynamically provisioning resources only when needed. To address this issue, the HEPCloud project was launched by the Fermilab Scientific Computing Division in June 2015. Its goal is to develop a facility that provides a common interface to a variety of resources, including local clusters, grids, high performance computers, and community and commercial Clouds. Initially targeted experiments include CMS and NOvA, as well as other Fermilab stakeholders. In its first phase, the project has demonstrated the use of the “elastic” provisioning model offered by commercial clouds, such as Amazon Web Services. In this model, resources are rented and provisioned automatically over the Internet upon request. In January 2016, the project demonstrated the ability to increase the total amount of global CMS resources by 58,000 cores from 150,000 cores - a 25 percent increase - in preparation for the Recontres de Moriond. In March 2016, the NOvA experiment has also demonstrated resource burst capabilities with an additional 7,300 cores, achieving a scale almost four times as large as the local allocated resources and utilizing the local AWS s3 storage to optimize data handling operations and costs. NOvA was using the same familiar services used for local computations, such as data handling and job submission, in preparation for the Neutrino 2016 conference. In both cases, the cost was contained by the use of the Amazon Spot Instance Market and the Decision Engine, a HEPCloud component that aims at minimizing cost and job interruption. This paper describes the Fermilab HEPCloud Facility and the challenges overcome for the CMS and NOvA communities.

Fuess, S.↗
DOE OSTI2014

Relaxed active space: Fixing tailored-CC with high order coupled cluster. II

Due to the steep increase in computational cost with the inclusion of higher-connected cluster operators in coupled-cluster applications, it is usually not practical to use such methods for larger systems or basis sets without an active space partitioning. This study generates an active space subject to unambiguous statistical criteria to define a space whose size permits treatment at the CCSDT level. The automated scheme makes it unnecessary for the user to judge whether a chosen active space is sufficient to correctly solve the problem. Two demanding applications are presented: twisted ethylene and the transition states for the bicyclo[1,1,0]butane isomerization. As bi-radicals both systems require at least a CCSDT level of theory for quantitative results, for the geometries and energies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Critical points of the random cluster model with Newman–Ziff sampling

Here, we present a method for computing transition points of the random cluster model using a generalization of the Newman–Ziff algorithm, a celebrated technique in numerical percolation, to the random cluster model. The new method is straightforward to implement and works for real cluster weight q > 0. Furthermore, results for an arbitrary number of values of q can be found at once within a single simulation. Because the algorithm used to sweep through bond configurations is identical to that of Newman and Ziff, which was conceived for percolation, the method loses accuracy for large lattices when q > 1. However, by sampling the critical polynomial, accurate estimates of critical points in two dimensions can be found using relatively small lattice sizes, which we demonstrate here by computing critical points for non-integer values of q on the square lattice, to compare with the exact solution, and on the unsolved non-planar square matching lattice. The latter results would be much more difficult to obtain using other techniques.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Investigating the crust of neutron stars with neural-network quantum states

An accurate description of low-density nuclear matter is crucial for explaining the physics of neutron star crusts. In the density range between approximately 0.01 fm −3 and 0.1 fm −3 , matter transitions from neutron-rich nuclei to various higher-density pasta shapes, before ultimately reaching a uniform liquid. In this work, we introduce a variational Monte Carlo method based on a neural Pfaffian-Jastrow quantum state, which allows us to model the transition from the liquid phase to neutron-rich nuclei microscopically. At low densities, nuclear clusters dynamically emerge from the microscopic interactions among protons and neutrons, which we model based on pionless effective field theory. Our variational Monte Carlo approach represents a significant improvement over the state-of-the-art auxiliary-field diffusion Monte Carlo method, which is severely hindered by the fermion-sign problem in this low-density regime and cannot capture the onset of clusters. In addition to computing the energy per particle of symmetric nuclear matter and pure neutron matter, we analyze an intermediate isospin-asymmetry configuration to elucidate the formation of nuclear clusters. We also provide evidence that the presence of such nuclear clusters influences the amount of protons in the crust compared to protons in beta-equilibrated, neutrino-transparent matter.

Nuclear astrophysics↗
DOE OSTI2023

Performance portable ice-sheet modeling with MALI

High-resolution simulations of polar ice sheets play a crucial role in the ongoing effort to develop more accurate and reliable Earth system models for probabilistic sea-level projections. These simulations often require a massive amount of memory and computation from large supercomputing clusters to provide sufficient accuracy and resolution; therefore, it has become essential to ensure performance on these platforms. Many of today’s supercomputers contain a diverse set of computing architectures and require specific programming interfaces in order to obtain optimal efficiency. In an effort to avoid architecture-specific programming and maintain productivity across platforms, the ice-sheet modeling code known as MPAS-Albany Land Ice (MALI) uses high-level abstractions to integrate Trilinos libraries and the Kokkos programming model for performance portable code across a variety of different architectures. In this article, we analyze the performance portable features of MALI via a performance analysis on current CPU-based and GPU-based supercomputers. The analysis highlights not only the performance portable improvements made in finite element assembly and multigrid preconditioning within MALI with speedups between 1.26 and 1.82x across CPU and GPU architectures but also identifies the need to further improve performance in software coupling and preconditioning on GPUs. We perform a weak scalability study and show that simulations on GPU-based machines perform 1.24–1.92x faster when utilizing the GPUs. The best performance is found in finite element assembly, which achieved a speedup of up to 8.65x and a weak scaling efficiency of 82.6% with GPUs. We additionally describe an automated performance testing framework developed for this code base using a changepoint detection method. The framework is used to make actionable decisions about performance within MALI. We provide several concrete examples of scenarios in which the framework has identified performance regressions, improvements, and algorithm differences over the course of 2 years of development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Quantum-Size Dependence of the Energy for Vacancy Formation in Charged Small Metal Clusters. Drop Model

Self-consistent computations of the monovacancy formation energy are performed for Na{sub N}, Mg{sub N}, and Al{sub N} (12 < N ≤ 168) spherical clusters in the drop model for stable jelly. Scenarios of the Schottky vacancy formation and “bubble vacancy blowing” are considered. It is shown that the asymptotic behavior of the size dependences of the energy for the vacancy formation by these two mechanisms is different and the difference between the characteristics of a charged and neutral cluster is entirely determined by the difference between the ionization potentials of clusters and the energies of electron attachment to them.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗