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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 253 records · Page 14

A Shift Selection Strategy for Parallel Shift-invert Spectrum Slicing in Symmetric Self-consistent Eigenvalue Computation

The central importance of large-scale eigenvalue problems in scientific computation necessitates the development of massively parallel algorithms for their solution. Recent advances in dense numerical linear algebra have enabled the routine treatment of eigenvalue problems with dimensions on the order of hundreds of thousands on the world’s largest supercomputers. In cases where dense treatments are not feasible, Krylov subspace methods offer an attractive alternative due to the fact that they do not require storage of the problem matrices. However, demonstration of scalability of either of these classes of eigenvalue algorithms on computing architectures capable of expressing massive parallelism is non-trivial due to communication requirements and serial bottlenecks, respectively. In this work, we introduce the SISLICE method: a parallel shift-invert algorithm for the solution of the symmetric self-consistent field (SCF) eigenvalue problem. The SISLICE method drastically reduces the communication requirement of current parallel shift-invert eigenvalue algorithms through various shift selection and migration techniques based on density of states estimation and k-means clustering, respectively. This work demonstrates the robustness and parallel performance of the SISLICE method on a representative set of SCF eigenvalue problems and outlines research directions that will be explored in future work.

97 MATHEMATICS AND COMPUTING↗

A distributed version of the NASA Engine Performance Program

Distributed NEPP, a version of the NASA Engine Performance Program, uses the original NEPP code but executes it in a distributed computer environment. Multiple workstations connected by a network increase the program's speed and, more importantly, the complexity of the cases it can handle in a reasonable time. Distributed NEPP uses the public domain software package, called Parallel Virtual Machine, allowing it to execute on clusters of machines containing many different architectures. It includes the capability to link with other computers, allowing them to process NEPP jobs in parallel. This paper discusses the design issues and granularity considerations that entered into programming Distributed NEPP and presents the results of timing runs.

Cours, Jeffrey T.↗

Performance Evaluation of Three Distributed Computing Environments for Scientific Applications

We present performance results for three distributed computing environments using the three simulated CFD applications in the NAS Parallel Benchmark suite. These environments are the DCF cluster, the LACE cluster, and an Intel iPSC/860 machine. The DCF is a prototypic cluster of loosely coupled SGI R3000 machines connected by Ethernet. The LACE cluster is a tightly coupled cluster of 32 IBM RS6000/560 machines connected by Ethernet as well as by either FDDI or an IBM Allnode switch. Results of several parallel algorithms for the three simulated applications are presented and analyzed based on the interplay between the communication requirements of an algorithm and the characteristics of the communication network of a distributed system.

Fatoohi, Rod↗

A Shift Selection Strategy for Parallel Shift-Invert Spectrum Slicing in Symmetric Self-Consistent Eigenvalue Computation

The central importance of large scale eigenvalue problems in scientific computation necessitates the development massively parallel algorithms for their solution. Recent advances in dense numerical linear algebra have enabled the routine treatment of eigenvalue problems with dimensions on the order of hundreds of thousands on the world's largest supercomputers. In cases where dense treatments are not feasible, Krylov subspace methods offer an attractive alternative due to the fact that they do not require storage of the problem matrices. However, demonstration of scalability of either of these classes of eigenvalue algorithms on computing architectures capable of expressing excessive parallelism is non-trivial due to communication requirements and serial bottlenecks, respectively. In this work, we introduce the SISLICE method: a parallel shift-invert algorithm for the solution of the symmetric self-consistent field (SCF) eigenvalue problem. The SISLICE method drastically reduces the communication requirement of current parallel shift-invert eigenvalue algorithms through various shift selection and migration techniques based on density of states estimation and k-means clustering, respectively. This work demonstrates the robustness and parallel performance of the SISLICE method on a representative set of SCF eigenvalue problems and outlines research directions which will be explored in future work.

97 MATHEMATICS AND COMPUTING↗

Application of an Evolutionary Algorithm for Parameter Optimization in a Gully Erosion Model

Herein we demonstrate how to use model optimization to determine a set of best-fit parameters for a landform model simulating gully incision and headcut retreat. To achieve this result we employed the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), an iterative process in which samples are created based on a distribution of parameter values that evolve over time to better fit an objective function. CMA-ES efficiently finds optimal parameters, even with high-dimensional objective functions that are non-convex, multimodal, and non-separable. We ran model instances in parallel on a high-performance cluster, and from hundreds of model runs we obtained the best parameter choices. This method is far superior to brute-force search algorithms, and has great potential for many applications in earth science modeling. We found that parameters representing boundary conditions tended to converge toward an optimal single value, whereas parameters controlling geomorphic processes are defined by a range of optimal values.

97 MATHEMATICS AND COMPUTING↗

Magnetoresistance effects and spin-valve like behavior of an arrangement of two MnAs nanoclusters

We report on magnetotransport measurements on a MnAs nanocluster arrangement consisting of two elongated single-domain clusters connected by a metal spacer. The arrangement was grown on GaAs(111)B-substrates by selective-area metal organic vapor phase epitaxy. Its structural properties were investigated using scanning-electron microscopy and atomic-force microscopy, while its magnetic domain structure was analyzed by magnetic-force microscopy. The magnetoresistance of the arrangement was investigated at 120 K for two measurement geometries with the magnetic field oriented in the sample plane. For both geometries, discrete jumps of the magnetoresistance of the MnAs nanocluster arrangement were observed. These jumps can be explained by magnetic-field induced switching of the relative orientation of the magnetizations of the two clusters which affects the spin-dependent scattering in the interface region between the clusters. For a magnetic field orientation parallel to the nanoclusters' elongation direction a spin-valve like behavior was observed, showing that ferromagnetic nanoclusters may be suitable building blocks for planar magnetoelectronic devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Simulated evolution of fluorophores for light emitting diodes

Organic light emitting diodes based on fluorophores with a propensity for thermally activated delayed fluorescence (TADF) are able to circumvent limitations imposed on device efficiency by spin statistics. Molecules with a propensity for TADF necessarily have two properties: a small gap between the lowest lying singlet and triplet excited states and a large transition dipole moment for fluorescence. In this work, we demonstrate the use of a genetic algorithm to search a region of chemical space for molecules with these properties. This algorithm is based on a flexible and intuitive representation of the molecule as a tree data structure, in which the nodes correspond to molecular fragments. Our implementation takes advantage of hybrid parallel graphics processing unit accelerated computer clusters to allow efficient sampling while retaining a reasonably accurate description of the electronic structure (in this case, CAM-B3LYP/6-31G{sup ∗∗}). In total, we have identified 3792 promising candidate fluorophores from a chemical space containing 1.26 × 10{sup 6} molecules. This required performing electronic structure calculations on only 7518 molecules, a small fraction of the full space. Several novel classes of molecules which show promise as fluorophores are presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling the TrueBeam linac using a CAD to Geant4 geometry implementation: Dose and IAEA-compliant phase space calculations

Purpose: To create an accurate 6 MV Monte Carlo simulation phase space for the Varian TrueBeam treatment head geometry imported from cad (computer aided design) without adjusting the input electron phase space parameters. Methods: geant4 v4.9.2.p01 was employed to simulate the 6 MV beam treatment head geometry of the Varian TrueBeam linac. The electron tracks in the linear accelerator were simulated with Parmela, and the obtained electron phase space was used as an input to the Monte Carlo beam transport and dose calculations. The geometry components are tessellated solids included in geant4 as gdml (generalized dynamic markup language) files obtained via STEP (standard for the exchange of product) export from Pro/Engineering, followed by STEP import in Fastrad, a STEP-gdml converter. The linac has a compact treatment head and the small space between the shielding collimator and the divergent arc of the upper jaws forbids the implementation of a plane for storing the phase space. Instead, an IAEA (International Atomic Energy Agency) compliant phase space writer was implemented on a cylindrical surface. The simulation was run in parallel on a 1200 node Linux cluster. The 6 MV dose calculations were performed for field sizes varying from 4 x 4 to 40 x 40 cm{sup 2}. The voxel size for the 60x60x40 cm{sup 3} water phantom was 4x4x4 mm{sup 3}. For the 10x10 cm{sup 2} field, surface buildup calculations were performed using 4x4x2 mm{sup 3} voxels within 20 mm of the surface. Results: For the depth dose curves, 98% of the calculated data points agree within 2% with the experimental measurements for depths between 2 and 40 cm. For depths between 5 and 30 cm, agreement within 1% is obtained for 99% (4x4), 95% (10x10), 94% (20x20 and 30x30), and 89% (40x40) of the data points, respectively. In the buildup region, the agreement is within 2%, except at 1 mm depth where the deviation is 5% for the 10x10 cm{sup 2} open field. For the lateral dose profiles, within the field size for fields up to 30x30 cm{sup 2}, the agreement is within 2% for depths up to 10 cm. At 20 cm depth, the in-field maximum dose difference for the 30x30 cm{sup 2} open field is within 4%, while the smaller field sizes agree within 2%. Outside the field size, agreement within 1% of the maximum dose difference is obtained for all fields. The calculated output factors varied from 0.938{+-}0.015 for the 4x4 cm{sup 2} field to 1.088{+-}0.024 for the 40x40 cm{sup 2} field. Their agreement with the experimental output factors is within 1%. Conclusions: The authors have validated a geant4 simulated IAEA-compliant phase space of the TrueBeam linac for the 6 MV beam obtained using a high accuracy geometry implementation from cad. These files are publicly available and can be used for further research.

43 PARTICLE ACCELERATORS↗

ADG: automated generation and evaluation of many-body diagrams

The goal of the present paper is twofold. First, a novel expansion many-body method applicable to superfluid open-shell nuclei, the so-called Bogoliubov in-medium similarity renormalization group (BIMSRG) theory, is formulated. This generalization of standard single-reference IMSRG theory for closed-shell systems parallels the recent extensions of coupled cluster, self-consistent Green’s function or many-body perturbation theory. Within the realm of IMSRG theories, BIMSRG provides an interesting alternative to the already existing multi-reference IMSRG (MR-IMSRG) method applicable to open-shell nuclei. The algebraic equations for low-order approximations, i.e., BIMSRG(1) and BIMSRG(2), can be derived manually without much difficulty. However, such a methodology becomes already impractical and error prone for the derivation of the BIMSRG(3) equations, which are eventually needed to reach high accuracy. Based on a diagrammatic formulation of BIMSRG theory, the second objective of the present paper is thus to describe the third version (v3.0) of the code that automatically (1) generates all valid BIMSRG(n) diagrams and (2) evaluates their algebraic expressions in a matter of seconds. This is achieved in such a way that equations can easily be retrieved for both the flow equation and the Magnus expansion formulations of BIMSRG. Expanding on this work, the first future objective is to numerically implement BIMSRG(2) (eventually BIMSRG(3)) equations and perform ab initio calculations of mid-mass open-shell nuclei.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Framework for Load Balancing of Tensor Contraction Expressions via Dynamic Task Partitioning

In this paper, we introduce the Dynamic Load-balanced Tensor Contractions (DLTC), a domain-specific library for efficient task parallel execution of tensor contraction expressions, a class of computation encountered in quantum chemistry and physics. Our framework decomposes each contraction into smaller unit of tasks, represented by an abstraction referred to as iterators. We exploit an extra level of parallelism by having tasks across independent contractions executed concurrently through a dynamic load balancing run- time. We demonstrate the improved performance, scalability, and flexibility for the computation of tensor contraction expressions on parallel computers using examples from coupled cluster methods.

Tensor contraction, domain-specific language, dyna↗

WPGNN and PLayGen (Wind Plant Graph Neural Network and Plant Layout Generator) [SWR-21-90]

WPGNN is the graph neural network machine learning based surrogate model and software that provides a streamlined approximation of wind plant wake models. It can rapidly estimate the energy production of the plant and turbines for any arbitrarily sized wind plant and layout under any inflow condition. Associated tools include graphing and visualization capabilities as well as a wind plant generator capable of creating randomized realizations of canonical wind plant layouts. The WPGNN architecture and application is extendable to multiple wake models, turbine technologies and features, and supports downstream optimizations of wind plant layouts and control strategies. In addition to the WPGNN, we include the code for the plant layout generator (PLayGen) playgen.py. This generator can produce random realizations of realistic wind plant layouts from one of the four canonical styles: cluster, single string, multiple string, or parallel string. The PLayGen_demo.ipynb notebook provides a demonstration of how to use the generator tool.

Harrison-Atlas, Dylan↗

Developing highly scalable fluid solvers for enabling multiphysics simulation.

We performed an investigation into explicit algorithms for the simulation of incompressible flows using methods with a finite, but small amount of compressibility added. Such methods include the artificial compressibility method and the lattice-Boltzmann method. The impetus for investigating such techniques stems from the increasing use of parallel computation at all levels (processors, clusters, and graphics processing units). Explicit algorithms have the potential to leverage these resources. In our investigation, a new form of artificial compressibility was derived. This method, referred to as the Entropically Damped Artificial Compressibility (EDAC) method, demonstrated superior results to traditional artificial compressibility methods by damping the numerical acoustic waves associated with these methods. Performance nearing that of the lattice- Boltzmann technique was observed, without the requirement of recasting the problem in terms of particle distribution functions; continuum variables may be used. Several example problems were investigated using a finite-di erence and finite-element discretizations of the EDAC equations. Example problems included lid-driven cavity flow, a convecting Taylor-Green vortex, a doubly periodic shear layer, freely decaying turbulence, and flow over a square cylinder. Additionally, a scalability study was performed using in excess of one million processing cores. Explicit methods were found to have desirable scaling properties; however, some robustness and general applicability issues remained.

Clausen, Jonathan R↗

US Department of Energy, Office of Science High Performance Computing Facility Operational Assessment 2019 Oak Ridge Leadership Computing Facility

Oak Ridge National Laboratory's (ORNL's) Leadership Computing Facility (OLCF) continues to surpass its operational target goals: supporting users; delivering fast, reliable computational ecosystems; creating innovative solutions for high performance computing (HPC) needs; and managing risks, safety, and security associated with operating some of the most powerful computers in the world. The results can be seen in the cutting-edge science conducted by users and the praise from the research community. Calendar year (CY) 2019 was a big year as OLCF staff ran five world-class resources (the leadershipclass computers Titan and Summit, the large analysis cluster called Eos, and the massive parallel filesystems called Atlas and Alpine)) and also began power and cooling upgrades for a 2021 exascale system called Frontier. While continuing exceptional operation of Titan, Eos, and Rhea, the OLCF released the Summit supercomputer for production on January 1, 2019. Summit debuted as the most capable and efficient system in its class and has been recognized as the most powerful system in the world for its performance on both the high performance linpack (HPL) and conjugate gradient (HPCG) benchmark applications since June 2018 according to TOP500. Summit represents the culmination of a multiyear effort between the OLCF, IBM, NVIDIA, and Mellanox to deliver a system that is unmatched for modeling, simulation, data analysis, and learning. To hit the ground running with science-ready applications on day one, application teams worked closely with the OLCF through the Center for Accelerated Application Readiness (CAAR) program for years in advance of the Summit deployment. CY 2019 was filled with outstanding results and accomplishments: a very high rating from users on overall satisfaction for the sixth year in a row; a tremendous amount of core-hours delivered to researchers from two leadership-class systems; and success in delivering on the allocation split of roughly 60%, 30%, and 10% of core-hours offered for the Innovative and Novel Computational Impact on Theory and Experiment (INCITE), Advanced Scientific Computing Research Leadership Computing Challenge (ALCC), and Director's Discretionary (DD) programs, respectively (see Operational Performance section). These accomplishments, coupled with the high utilization rates (overall and capability usage), represent the fulfillment of the promise of both leadership-class machines: efficient facilitation of leadership-class computational applications. Table ES.1 presents a summary of the 2019 OLCF metric targets and the associated results. More information can be found in the Operational Performance section for each OLCF resource. The scientific accomplishments of OLCF users are a strong indication of long-term operational success, with publications this year in such notable journals and publications as Nature, Nature Physics, Nature Plants, Physical Review X, Journal of the American Physical Society, Cell, Nano Letters, and Trends in Biotechnology. Crucial domain-specific discoveries facilitated by resources at the OLCF are described in the High Performance Computing Facility Operational Assessment 2019 Oak Ridge Leadership Computing Facility (OAR) Strategic Results section. For example, researchers used Summit to pinpoint and understand the production of proteins from genetic information, including mutations and the functional expression of disease (Section 8.2).

97 MATHEMATICS AND COMPUTING↗

CephFS experiments on stria.sandia.gov

This report is an institutional record of experiments conducted to explore performance of a vendor installation of CephFS on the SNL stria cluster. Comparisons between CephFS, the Lustre parallel file system, and NFS were done using the IOR and MDTEST benchmarking tools, a test program which uses the SEACAS/Trilinos IOSS library, and the checkpointing activity performed by the LAMMPS molecular dynamics simulation.

74 ATOMIC AND MOLECULAR PHYSICS↗

CephFS experiments on stria.sandia.gov

This report is an institutional record of experiments conducted to explore performance of a vendor installation of CephFS on the SNL stria cluster. Comparisons between CephFS, the Lustre parallel file system, and NFS were done using the IOR and MDTEST benchmarking tools, a test program which uses the SEACAS/Trilinos IOSS library, and the checkpointing activity performed by the LAMMPS molecular dynamics simulation.

97 MATHEMATICS AND COMPUTING↗

Boundary and object detection in real world images

A solution to the problem of automatic location of objects in digital pictures by computer is presented. A self-scaling local edge detector which can be applied in parallel on a picture is described. Clustering algorithms and boundary following algorithms which are sequential in nature process the edge data to locate images of objects.

Yakimovsky, Y.↗

Climate Ocean Modeling on a Beowulf Class System

With the growing power and shrinking cost of personal computers. the availability of fast ethernet interconnections, and public domain software packages, it is now possible to combine them to build desktop parallel computers (named Beowulf or PC clusters) at a fraction of what it would cost to buy systems of comparable power front supercomputer companies. This led as to build and assemble our own sys tem. specifically for climate ocean modeling. In this article, we present our experience with such a system, discuss its network performance, and provide some performance comparison data with both HP SPP2000 and Cray T3E for an ocean Model used in present-day oceanographic research.

Cheng, B. N.↗