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At least 577 records · Page 32

Self-focusing of Hermite-Gaussian laser beam with relativistic nonlinearity

This paper presents an investigation of self-focusing of Hermite-Gaussian laser beams in plasma considering relativistic nonlinearity. The differential equations for beam width parameters are obtained using the usual Wentzel–Kramers–Brillouin and paraxial approximations. The nonlinearity in the dielectric constant is assumed to be aroused mainly due to the relativistic mass correction of electron. To highlight the nature of focusing, graphical results of the behavior of beam-width parameters with the dimensionless distance of propagation is presented. The numerical computation is completed by using Taylor series method. The present work is helpful to understand issues related to the beam propagation in laser plasma interaction experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Multimode scanning X-ray diffraction microscopy for diamond anvil cell experiments

We have designed and implemented a new experimental system for fast mapping of crystal structures and other structural features of materials under high pressure at the High Pressure Collaborative Access Team, Sector 16 of the Advanced Photon Source. The system utilizes scanning X-ray diffraction microscopy (SXDM) and is optimized for use with diamond anvil cell devices. In SXDM, the X-ray diffraction (XRD) is collected in a forward scattering geometry from points on a two-dimensional grid by fly-scanning the sample with respect to a micro-focused X-ray beam. The recording of XRD is made during the continuous motion of the sample using a fast (millisecond) X-ray area detector in synchrony with the sample positioners, resulting in a highly efficient data collection for SXDM. A new computer program, X-ray Diffractive Imaging (XDI), has been developed with the SXDM system. The XDI program provides a graphical interface for constructing and displaying the SXDM images in several modes: (1) phase mapping based on structural information, (2) pressure visualization based on the equation of state, (3) microstructural features mapping based on peak shape parameters, and (4) grain size and preferred-orientation based on peak shape parameters. The XDI is a standalone program and can be generally used for displaying SXDM images. Two examples of iron and zirconium samples under high pressure are presented to demonstrate the applications of SXDM. Published under license by AIP Publishing.

47 OTHER INSTRUMENTATION↗

Portability for GPU-accelerated molecular docking applications for cloud and HPC: can portable compiler directives provide performance across all platforms?

High-throughput structure-based screening of drug-like molecules has become a common tool in biomedical research. Recently, acceleration with graphics processing units (GPUs) has provided a large performance boost for molecular docking programs. Both cloud and high-performance computing (HPC) resources have been used for large screens with molecular docking programs; while NVIDIA GPUs have dominated cloud and HPC resources, new vendors such as AMD and Intel are now entering the field, creating the problem of software portability across different GPUs. Ideally, software productivity could be maximized with portable programming models that are able to maintain high performance across architectures. While in many cases compiler directives have been used as an easy way to offload parallel regions of a CPU-based program to a GPU accelerator, they may also be an attractive programming model for providing portability across different GPU vendors, in which case the porting process may proceed in the reverse direction: from low-level, architecture-specific code to higher-level directive-based abstractions. MiniMDock is a new mini-application (miniapp) designed to capture the essential computational kernels found in molecular docking calculations, such as are used in phar-maceutical drug discovery efforts, in order to test different solutions for porting across GPU architectures. Here we extend MiniMDock to GPU offloading with OpenMP directives, and compare to performance of kernels using CUDA and HIP on NVIDIA and AMD GPUs, respectively, as well as across different compilers, exploring performance bottlenecks. We document this reverse-porting process, from highly optimized device code to a higher-level version using directives, compare code structure, and describe barriers that were overcome in this effort.

Thavappiragasam, Mathialakan↗

Performance Portable Graphics Processing Unit Acceleration of a High-Order Finite Element Multiphysics Application

The Lawrence Livermore National Laboratory (LLNL) will soon have in place the El Capitan exascale supercomputer, based on advanced micro devices (AMD) graphics processing units (GPUs). As part of a multiyear effort under the National Nuclear Security Administration (NNSA) Advanced Simulation and Computing (ASC) program, we have been developing marbl, a next generation, performance portable multiphysics application based on high-order finite elements. In previous years, we successfully ported the Arbitrary Lagrangian–Eulerian (ALE), multimaterial, compressible flow capabilities of marbl to nvidia GPUs as described in Vargas et al. Here, in this paper, we describe our ongoing effort in extending marbl's GPU capabilities with additional physics, including multigroup radiation diffusion and thermonuclear burn for high energy density physics (HEDP) and fusion modeling. We also describe how our portability abstraction approach based on the raja Portability Suite and the mfem finite element discretization library has enabled us to achieve high performance on AMD based GPUs with minimal effort in hardware-specific porting. Throughout this work, we highlight numerical and algorithmic developments that were required to achieve GPU performance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

SU-D-9A-03: STAMP: Simulator for Texture Analysis in MRI/PET

Purpose: To develop a convenient simulation platform to facilitate PET/MR image analysis with the prospect of gaining a better understanding of the influence of acquisition parameters on PET/MRI textural features. The simulation platform is demonstrated by showing textural variations of a representative case study using different image acquisition parameters. Methods: The simulation platform is composed of MRI simulators JEMRIS and SIMRI to achieve simulations of customized MRI sequences on sample tumor models. The PET simulator GATE is used to get 2D and 3D Monte Carlo acquisitions of voxelized PET sources using a phantom geometry and a customized scanner architecture. The platform incorporates a series of graphical user interfaces written in Matlab. Two GUIs are used to facilitate communication with the simulation executables installed on a computer cluster. A third GUI is used to collect and display the clinical and simulated images, as well as fused PET/MRI images, and perform computation of textural features.To illustrate the capabilities of this platform, one FDG-PET and T1-weighted (T1w) digitized tumor models were generated from clinical images of a soft-tissue sarcoma patient. Numerically simulated MR images were produced using 3 different echo times (TE) and 5 different repetition times (TR). PET 2D images were simulated using an OSEM algorithm with 1 to 32 iterations and a post-reconstruction Gaussian filter of 0, 2, 4 or 6 mm width. Results: STAMP was successfully used to produce numerically simulated FDG-PET and MRI images, and to calculate their corresponding textures. Three typical textures (GLCM-Contrast, GLSZM-ZSV and NGTDM-Coarseness) were found to vary by a range of 45% on average compared to reference scanning conditions in the case of FDG-PET, and by a range of 40% in the case of T1w MRI. Conclusion: We have successfully developed a Matlab-based simulation platform to facilitate PET/MRI texture image analysis for outcome prediction.

60 APPLIED LIFE SCIENCES↗

HiPACE++ v0.1

Hipace++ is the new implementation of the DESY-LBNL code Hipace (not distributed nor licensed) for plasma acceleration, relying on the quasi-static particle-in-cell (PIC) method, enabling fast and accurate simulations of plasma accelerators for problems satisfying the quasi-static approximation. Plasma acceleration is a priority in the ATAP division, and such problems represent a wide range of parameters. Hipace++ is an HPC (high-performance computing) code running on supercomputers and it provides the first efficient implementation of the quasi-static PIC method on Graphic Processing Units (GPU), showing 10x speedup and using much less resources than CPU implementations for production simulations. It currently runs on Nvidia GPUs and will ultimately be portable to more accelerated HPC platforms. The porting strategy is novel, and can be adapted to other flavors of quasi-static PIC. Besides, Hipace++ aims at using mesh refinement for higher efficiency, thus enabling simulations unfeasible today. For this purpose, Hipace++ depends on the open-source library AMReX (Adaptive Mesh Refinement at EXascale) developed at LBNL.

Vay, Jean-Luc↗

Molecular dynamics studies of the size and temperature dependence of the kinetics of freezing of Fe nanoparticles

Molecular dynamics (MD) computer simulations have been carried out and a novel modified technique of Voronoi polyhedra has been performed to identify solid-like particles in a molten nanoparticle. This technique works quite well in analyzing the effects of particle size on nucleation rates of iron nanoparticles in the temperature range of 750–1160 K. Nanoparticles with 1436 and 2133 Fe atoms have been examined and the results are compared with those obtained earlier with Fe{sub 331} nanoparticles. Nucleation rates for freezing obtained from MD simulations for Fe{sub 2133} vary from 8.8×10{sup 34} m{sup 3}/s to 4.1×10{sup 35} m{sup 3}/s at over a temperature range from 1160 K to 900 K, Rates for. Fe{sub 1436} and Fe{sub 331} are somewhat higher. Nucleation rates increase as supercooling deepens until the viscosity of the liquid increases sharply enough to slow down the rate. Bt applying classical nucleation theory, the interfacial free energy between solid and liquid cab be estimated From this and other thermodynamic information can be derived a theoretical expression for the size-dependence of the heat of fusion of nanoparticles. Results agreed quite well with those observed in our MD observations. An earlier expression in the literature for this size-dependence was shown to be incorrect. The size dependence of melting point is discussed. - Graphical abstract: Critical nuclei of crystallization. Display Omitted - Highlights: • Solid state material synthesis. • Material structure. • Experimental study of nucleation in condensed materials. • Computation study of nucleation in condensed materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TopoMS: Comprehensive topological exploration for molecular and condensed-matter systems

We introduce TopoMS, a computational tool enabling detailed topological analysis of molecular and condensed-matter systems, including the computation of atomic volumes and charges through the quantum theory of atoms in molecules, as well as the complete molecular graph. With roots in techniques from computational topology, and using a shared-memory parallel approach, TopoMS provides scalable, numerically robust, and topologically consistent analysis. TopoMS can be used as a command-line tool or with a GUI (graphical user interface), where the latter also enables an interactive exploration of the molecular graph. This paper presents algorithmic details of TopoMS and compares it with state-of-the-art tools: Bader charge analysis v1.0 (Arnaldsson et al., 01/11/17) and molecular graph extraction using Critic2 (Otero-de-la-Roza et al., Comput. Phys. Commun. 2014, 185, 1007). TopoMS not only combines the functionality of these individual codes but also demonstrates up to 4× performance gain on a standard laptop, faster convergence to fine-grid solution, robustness against lattice bias, and topological consistency. TopoMS is released publicly under BSD License.

97 MATHEMATICS AND COMPUTING↗

GPU-accelerated dislocation dynamics using subcycling time-integration

Discrete dislocation dynamics (DDD) simulations are being increasingly employed to investigate metal plasticity at the mesoscale. However, in spite of its ability to access beyond the length and time limits of atomistic methods, the DDD model is still limited by its high computational cost, with ranges of achievable strains too low and strain rates too high by several orders of magnitude compared with typical experimental conditions. By combining the efficiency of the recently developed subcycling time-integrator with the highly parallel architecture of graphics processing unit (GPU) devices, we developed a DDD model that provides significant acceleration compared to existing implementations. Our GPU-accelerated implementation enables large-scale DDD simulations that can reach relevant levels of strain using a moderate amount of computational resources.

36 MATERIALS SCIENCE↗

Visual HPC Workflows for the Analysis of System Dynamics Models

Visual analytics supported by high performance computing (HPC) accelerates and enhances the discovery, exploration, and analysis of causal patterns in complex system dynamics (SD) models. We present a suite of visualization-assisted ensemble-based techniques for hypothesis generation and testing, and for sensitivity analysis. By employing HPC to provide parallel, on-demand simulation of SD models, one can “steer” an ensemble of simulated scenarios in real time as one first formulates and then informally tests those hypotheses: this provides rapid feedback for analysts to refine their understanding of the causal relationships emergent from a model. Such understandings can be followed and augmented by rigorous application of statistical methods, namely global variance-based sensitivity analysis, Monte-Carlo filtering, adaptive regional sensitivity analysis, and self-organized maps: here timely computation relies on HPC, while effective presentation emphasizes high-dimensional multivariate data visualization. Immersive visualization in virtual 3D environments provides an excellent adjunct to the traditional 2D graphics typically used for SD models, as it generates an embodied understanding of model behavior and facilitates an active, collaborative critique of model structure and output. Finally, we summarize prospects for HPC-enabled visual analytics applied to SD modeling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Localized spin excitations in an antiferromagnetic spin system with D-M interaction

The existence of localized spin excitations and spin deviations along the site in a one-dimensional antiferromagnet with Dzyaloshinski-Moriya (D-M) interaction has been studied using quasiclassical approximation. By introducing the Holstein-Primakoff bosonic representation of spin operators, the coherent state ansatz, and the time dependent variational principle, a discrete set of coupled nonlinear partial differential equations governing the dynamics is derived. Employing the multiple-scale method, one, two and three solitary wave solutions are constructed and depicted graphically.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Rise of an argon bubble in liquid steel in the presence of a transverse magnetic field

The rise of gaseous bubbles in viscous liquids is a fundamental problem in fluid physics, and it is also a common phenomenon in many industrial applications such as materials processing, food processing, and fusion reactor cooling. In this work, the motion of a single argon gas bubble rising in quiescent liquid steel under an external magnetic field is studied numerically using a Volume-of-Fluid method. To mitigate spurious velocities normally generated during numerical simulation of multiphase flows with large density differences, an improved algorithm for surface tension modeling, originally proposed by Wang and Tong [“Deformation and oscillations of a single gas bubble rising in a narrow vertical tube,” Int. J. Therm. Sci. 47, 221–228 (2008)] is implemented, validated and used in the present computations. The governing equations are integrated by a second-order space and time accurate numerical scheme, and implemented on multiple Graphics Processing Units with high parallel efficiency. The motion and terminal velocities of the rising bubble under different magnetic fields are compared and a reduction in rise velocity is seen in cases with the magnetic field applied. The shape deformation and the path of the bubble are discussed. An elongation of the bubble along the field direction is seen, and the physics behind these phenomena is discussed. The wake structures behind the bubble are visualized and effects of the magnetic field on the wake structures are presented. A modified drag coefficient is obtained to include the additional resistance force caused by adding a transverse magnetic field.

42 ENGINEERING↗

Affordable and accurate large-scale hybrid-functional calculations on GPU-accelerated supercomputers

Performing high accuracy hybrid functional calculations for condensed matter systems containing a large number of atoms is at present computationally very demanding or even out of reach if high quality basis sets are used. We present a highly optimized multiple graphics processing unit implementation of the exact exchange operator which allows one to perform fast hybrid functional density-functional theory (DFT) calculations with systematic basis sets without additional approximations for up to a thousand atoms. With this method hybrid DFT calculations of high quality become accessible on state-of-the-art supercomputers within a time-to-solution that is of the same order of magnitude as traditional semilocal-GGA functionals. The method is implemented in a portable open-source library.

density functional theory↗

Accommodating Uncertainty in Prior Distributions

A fundamental premise of Bayesian methodology is that a priori information is accurately summarized by a single, precisely de ned prior distribution. In many cases, especially involving informative priors, this premise is false, and the (mis)application of Bayes methods produces posterior quantities whose apparent precisions are highly misleading. We examine the implications of uncertainty in prior distributions, and present graphical methods for dealing with them.

97 MATHEMATICS AND COMPUTING↗

Developing an Automated Uncertainty Quantification Tool to Improve Watershed-Scale Predictions of Water and Nutrient Cycling

Managing the flow of water, nutrients, and contaminants in watersheds is vital to addressing pressing issues related to water scarcity, access to clean drinking water, energy production, resilience to natural and anthropogenic perturbations, and ecological restoration. Decisions about the management of watersheds critically depend on the accuracy with which the flow of water and chemicals through the watershed can be predicted by computer models. Prediction uncertainty can be reduced by matching the model to data, which are collected in the field at great expense. The contribution of watershed characterization data to reducing uncertainty of relevant model predictions can be evaluated in a so-called data-worth analysis, which provides transparent, quantitative metrics about a data set’s value for the support of relevant watershed management objectives. To achieve this goal, we developed a software package that implements the data-worth analysis approach for use with state-of-the-art watershed models. The purpose of the proposed data-worth analysis is to help decision-makers allocate resources for watershed characterization such that the uncertainty in model predictions can be significantly reduced, which leads to better, more effective management decisions. At the same time, watershed characterization costs can be reduced. The specific technical objectives of this SBIR/STTR Phase II project were to develop a framework and associated software toolsets that implement the uncertainty quantification and data-worth analysis approach for use with state-of-the-art watershed models. This goal was achieved by (A) developing a user-friendly, robust software package that is accessible to a wide audience, including watershed managers, policy-makers, and public stakeholders; (B) by demonstrating application of the prototype on several use cases that are representative of complex watershed management challenges spanning a range of scales and that consider different open-source, DOE-based codes and other modeling platforms; and (C) by gathering information about the needs and requirements from potential users to help guide future developments, ensuring that the final product will be commercially viable. The developed software consists of a graphical user interface that guides the user through a sequence of analysis steps, supported by toolsets that leverage state-of-the-art computational simulation-optimization capabilities. A prototype of the software runs on multiple platforms (PC, Mac, multi-processor Linux environment), is linked to diverse watershed simulators (e.g., ECOSYS, TOUGH2, TOUGHREACT, Amanzi-ATS), performs multiple analysis tasks (predictive simulations, sensitivity analysis, uncertainty analysis, automatic parameter estimation, and data-worth analysis, multicomponent geothermometry), and is readily extensible to include external simulators and analysis tools. The software is being commercialized and will be continually updated to address user needs.

58 GEOSCIENCES↗

Large scale Brownian dynamics of confined suspensions of rigid particles

We introduce methods for large-scale Brownian Dynamics (BD) simulation of many rigid particles of arbitrary shape suspended in a fluctuating fluid. Our method adds Brownian motion to the rigid multiblob method [F. Balboa Usabiaga et al., Commun. Appl. Math. Comput. Sci. 11(2), 217–296 (2016)] at a cost comparable to the cost of deterministic simulations. We demonstrate that we can efficiently generate deterministic and random displacements for many particles using preconditioned Krylov iterative methods, if kernel methods to efficiently compute the action of the Rotne-Prager-Yamakawa (RPY) mobility matrix and its “square” root are available for the given boundary conditions. These kernel operations can be computed with near linear scaling for periodic domains using the positively split Ewald method. Here we study particles partially confined by gravity above a no-slip bottom wall using a graphical processing unit implementation of the mobility matrix-vector product, combined with a preconditioned Lanczos iteration for generating Brownian displacements. We address a major challenge in large-scale BD simulations, capturing the stochastic drift term that arises because of the configuration-dependent mobility. Unlike the widely used Fixman midpoint scheme, our methods utilize random finite differences and do not require the solution of resistance problems or the computation of the action of the inverse square root of the RPY mobility matrix. We construct two temporal schemes which are viable for large-scale simulations, an Euler-Maruyama traction scheme and a trapezoidal slip scheme, which minimize the number of mobility problems to be solved per time step while capturing the required stochastic drift terms. We validate and compare these schemes numerically by modeling suspensions of boomerang-shaped particles sedimented near a bottom wall. Using the trapezoidal scheme, we investigate the steady-state active motion in dense suspensions of confined microrollers, whose height above the wall is set by a combination of thermal noise and active flows. We find the existence of two populations of active particles, slower ones closer to the bottom and faster ones above them, and demonstrate that our method provides quantitative accuracy even with relatively coarse resolutions of the particle geometry.

97 MATHEMATICS AND COMPUTING↗

Scalable probabilistic estimates of electric vehicle charging given observed driver behavior

To prepare for rapid growth in global electric vehicle adoption, grid and policy planners depend on detailed forecasts of future charging demand. In this paper we propose a novel holistic, scalable, probabilistic framework to produce large-scale estimates of electric vehicle charging load for long-term planning that capture real drivers’ charging patterns. Our framework captures the uncertainty and stochasticity in charging demand by taking a graphical modeling approach. It has three core elements: driver groups, charging segment choices, and charging session time and energy requirements. The framework uses hierarchical clustering to group drivers by their charging histories, capturing their heterogeneous behaviors and preferences across different segments or types of charging. The framework uses probabilistic mixture models for each driver group’s sessions to identify the unique charging behaviors observed within each segment. We illustrate its application with a large data set from California, profiling the charging patterns and unique driver clusters it identifies. Using the model knobs representing drivers’ battery capacities, behavior, and segment access we present scenarios for California’s charging demand in 2030 with 8 million passenger electric vehicles. Peak charging demand ranged from 3.3 to 8.7 GW across scenarios. Furthermore, each was calculated in under 45 s on a laptop computer.

33 ADVANCED PROPULSION SYSTEMS↗

SU-D-18A-02: Towards Real-Time On-Board Volumetric Image Reconstruction for Intrafraction Target Verification in Radiation Therapy

Purpose: To expedite on-board volumetric image reconstruction from limited-angle kV—MV projections for intrafraction verification. Methods: A limited-angle intrafraction verification (LIVE) system has recently been developed for real-time volumetric verification of moving targets, using limited-angle kV—MV projections. Currently, it is challenged by the intensive computational load of the prior-knowledge-based reconstruction method. To accelerate LIVE, we restructure the software pipeline to make it adaptable to model and algorithm parameter changes, while enabling efficient utilization of rapidly advancing, modern computer architectures. In particular, an innovative two-level parallelization scheme has been designed: At the macroscopic level, data and operations are adaptively partitioned, taking into account algorithmic parameters and the processing capacity or constraints of underlying hardware. The control and data flows of the pipeline are scheduled in such a way as to maximize operation concurrency and minimize total processing time. At the microscopic level, the partitioned functions act as independent modules, operating on data partitions in parallel. Each module is pre-parallelized and optimized for multi-core processors (CPUs) and graphics processing units (GPUs). Results: We present results from a parallel prototype, where most of the controls and module parallelization are carried out via Matlab and its Parallel Computing Toolbox. The reconstruction is 5 times faster on a data-set of twice the size, compared to recently reported results, without compromising on algorithmic optimization control. Conclusion: The prototype implementation and its results have served to assess the efficacy of our system concept. While a production implementation will yield much higher processing rates by approaching full-capacity utilization of CPUs and GPUs, some mutual constraints between algorithmic flow and architecture specifics remain. Based on a careful analysis of the prototype performance, it will be feasible to resolve such issues through appropriate algorithmic modifications or special-purpose hardware, thus enabling target verification in seconds with the LIVE system. This work was partially supported by a research grant from Varian Medical Systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗