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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Efficient, Parallel At-scale Correlation Analysis for Atom Probe Tomography on Hybrid Architectures

Atom probe tomography (APT) is a material probing technique that has undergone dramatic improvements in its capability to map individual atoms within a material sample resulting in data files with hundreds of millions of atoms. Understanding the nano-structural features hidden in these massive amounts of atomic data is a crucial analysis task for materials scientists. However, fast analysis capabilities for large APT workloads remains a critical bottleneck. In this paper, we present the design, implementation and detailed performance evaluations of a parallel software capable of efficiently performing extremely time-consuming correlation analyses of massive high density APT data. Starting with shared memory implementations to motivate our design choices, we extend the implementation to hybrid architectures keeping realistic APT workloads in mind. Detailed performance analyses of three different parallel implementations of the software are supported by empirical results on a Cray XC30 and a Cray XC40 architecture. Its usefulness is demonstrated by reducing the turnaround time of an end-to-end APT correlation analysis on 100 millions atoms by three orders of magnitude using 2048 MPI ranks on 1024 nodes (24 cores per node) of a Cray XC30. The software reported here equips material scientists for the first time with a high-speed scalable capability for efficient and timely analyses of massive APT data.

Lu, Hao↗
DOE OSTI2018

Massively Parallel Simulation of Large Molecular Systems with Long-Range Interactions Final Report CRADA No. TC-0297-92-B

The purpose of this CRADA project is to develop and implement a large-scale molecular dynamics model for floppy molecules with long-ranged interaction on massively parallel supercomputers and accelerate the use of parallel supercomputers within the biomolecular and polymer industries. Within three years of the project, the partners will: create a new molecular dynamics computer simulation code (LAMMPS) from existing codes at SAndia National Laboratory-Albuquerque (SNL-A) and Lawrence Livermore National Laboratory (LLNL) and new algorithms and code developed during the CRADA project; design the resulting code to optimally use the emerging generation of massively parallel supercomputers; and apply the code to the solution of biomolecular problem suggested by Bristol-Myers Squibb (BMS) and polymer problems suggested by DuPont.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Massively parallel Monte Carlo for many-particle simulations on GPUs

Current trends in parallel processors call for the design of efficient massively parallel algorithms for scientific computing. Parallel algorithms for Monte Carlo simulations of thermodynamic ensembles of particles have received little attention because of the inherent serial nature of the statistical sampling. In this paper, we present a massively parallel method that obeys detailed balance and implement it for a system of hard disks on the GPU. We reproduce results of serial high-precision Monte Carlo runs to verify the method. This is a good test case because the hard disk equation of state over the range where the liquid transforms into the solid is particularly sensitive to small deviations away from the balance conditions. On a Tesla K20, our GPU implementation executes over one billion trial moves per second, which is 148 times faster than on a single Intel Xeon E5540 CPU core, enables 27 times better performance per dollar, and cuts energy usage by a factor of 13. With this improved performance we are able to calculate the equation of state for systems of up to one million hard disks. These large system sizes are required in order to probe the nature of the melting transition, which has been debated for the last forty years. In this paper we present the details of our computational method, and discuss the thermodynamics of hard disks separately in a companion paper.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Quantum vacuum processes in the extremely intense light of relativistic plasma mirror sources

Abstract The advent of petawatt-class laser systems allows generating electromagnetic fields of unprecedented strength in a controlled environment, driving increasingly more efforts to probe yet unobserved processes through their interaction with the quantum vacuum. Still, the lowest intensity scale governing these effects lies orders of magnitude beyond foreseen capabilities, so that such endeavor is expected to remain extremely challenging. In recent years, however, plasma mirrors have emerged as a promising bridge across this gap, by enabling the conversion of intense infrared laser pulses into coherently focused Doppler harmonic beams lying in the X-UV range. In this work, we present predictions on the quantum vacuum signatures produced when such beams are focused to intensities between 10 24 and 10 28 W cm −2 , specifically photon–photon scattering and electron–positron pair creation. These signatures are computed via the stimulated vacuum formalism, combined with a model of perfectly focused beam built from PIC-generated harmonics spectra, and implemented on state-of-the-art massively parallel numerical tools. In view of identifying experimentally favorable configurations, we also consider the coupling of the focused harmonic beam with an auxiliary optical beam, and provide comparison with other established schemes. Our results show that a single coherently focused harmonic beam can produce as much scattered photons as two infrared pulses in head-on collision, and confirm that the coupling of the harmonic beam to an auxiliary beam gives rise to significant levels of inelastic scattering, and hence holds the potential to strongly improve the attainable signal to noise ratios in experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

GPU-accelerated Tersoff potentials for massively parallel Molecular Dynamics simulations

The Tersoff potential is one of the empirical many-body potentials that has been widely used in simulation studies at atomic scales. Unlike pair-wise potentials, the Tersoff potential involves three-body terms, which require much more arithmetic operations and data dependency. In this contribution, we have implemented the GPU-accelerated version of several variants of the Tersoff potential for LAMMPS, an open-source massively parallel Molecular Dynamics code. Compared to the existing MPI implementation in LAMMPS, the GPU implementation exhibits a better scalability and offers a speedup of 2.2X when run on 1000 compute nodes on the Titan supercomputer. On a single node, the speedup ranges from 2.0 to 8.0 times, depending on the number of atoms per GPU and hardware configurations. The most notable features of our GPU-accelerated version include its design for MPI/accelerator heterogeneous parallelism, its compatibility with other functionalities in LAMMPS, its ability to give deterministic results and to support both NVIDIA CUDA- and OpenCL-enabled accelerators. Our implementation is now part of the GPU package in LAMMPS and accessible for public use.

Computer Science↗
DOE OSTI2022

Tracer Gas Model Development and Verification in PFLOTRAN

Tracer gases, whether they are chemical or isotopic in nature, are useful tools in examining the flow and transport of gaseous or volatile species in the underground. One application is using detection of short-lived argon and xenon radionuclides to monitor for underground nuclear explosions. However, even chemically inert species, such as the noble gases, have bene observed to exhibit non-conservative behavior when flowing through porous media containing certain materials, such as zeolites, due to gas adsorption processes. This report details the model developed, implemented, and tested in the open source and massively parallel subsurface flow and transport simulator PFLOTRAN for future use in modeling the transport of adsorbing tracer gases.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

Massively Parallel, Three-Dimensional Transport Solutions for the k-Eigenvalue Problem

We have implemented a new multilevel parallel decomposition in the Denovo dis- crete ordinates radiation transport code. In concert with Krylov subspace iterative solvers, the multilevel decomposition allows concurrency over energy in addition to space-angle, enabling scalability beyond the limits imposed by the traditional KBA space-angle partitioning. Furthermore, a new Arnoldi-based k-eigenvalue solver has been implemented. The added phase-space concurrency combined with the high- performance Krylov and Arnoldi solvers has enabled weak scaling to O(100K) cores on the Jaguar XK6 supercomputer. The multilevel decomposition provides sucient parallelism to scale to exascale computing and beyond.

Arnoldi↗
DOE OSTI2018

Accelerating nuclear configuration interaction calculations through a preconditioned block iterative eigensolver

We describe a number of recently developed techniques for improving the performance of large-scalenuclear configuration interaction calculations on high performance parallel computers. We show thebenefit of using a preconditioned block iterative method to replace the Lanczos algorithm that hastraditionally been used to perform this type of computation. The rapid convergence of the block iterativemethod is achieved by a proper choice of starting guesses of the eigenvectors and the construction of aneffective preconditioner. These acceleration techniques take advantage of special structure of the nuclearconfiguration interaction problem which we discuss in detail. The use of a block method also allows usto improve the concurrency of the computation, and take advantage of the memory hierarchy of modernmicroprocessors to increase the arithmetic intensity of the computation relative to data movement. Wealso discuss the implementation details that are critical to achieving high performance on massivelyparallel multi-core supercomputers, and demonstrate that the new block iterative solver is two to threetimes faster than the Lanczos based algorithm for problems of moderate sizes on a Cray XC30 system.

Shao, Meiyue↗
DOE OSTI2020

GPU acceleration of all-electron electronic structure theory using localized numeric atom-centered basis functions

We present an implementation of all-electron density-functional theory for massively parallel GPU-based platforms, using localized atom-centered basis functions and real-space integration grids. Special attention is paid to domain decomposition of the problem on non-uniform grids, which enables compute- and memory-parallel execution across thousands of nodes for real-space operations, e.g. the update of the electron density, the integration of the real-space Hamiltonian matrix, and calculation of Pulay forces. To assess the performance of our GPU implementation, we performed benchmarks on three different architectures using a 103-material test set. We find that operations which rely on dense serial linear algebra show dramatic speedups from GPU acceleration: in particular, SCF iterations including force and stress calculations exhibit speedups ranging from 4.5 to 6.6. For the architectures and problem types investigated here, this translates to an expected overall speedup between 3–4 for the entire calculation (including non-GPU accelerated parts), for problems featuring several tens to hundreds of atoms. Additional calculations for a 375-atom Bi2Se3 bilayer show that the present GPU strategy scales for large-scale distributed-parallel simulations.

42 ENGINEERING↗
DOE OSTI2013

Spacecraft charging analysis with the implicit particle-in-cell code iPic3D

We present the first results on the analysis of spacecraft charging with the implicit particle-in-cell code iPic3D, designed for running on massively parallel supercomputers. The numerical algorithm is presented, highlighting the implementation of the electrostatic solver and the immersed boundary algorithm; the latter which creates the possibility to handle complex spacecraft geometries. As a first step in the verification process, a comparison is made between the floating potential obtained with iPic3D and with Orbital Motion Limited theory for a spherical particle in a uniform stationary plasma. Second, the numerical model is verified for a CubeSat benchmark by comparing simulation results with those of PTetra for space environment conditions with increasing levels of complexity. In particular, we consider spacecraft charging from plasma particle collection, photoelectron and secondary electron emission. The influence of a background magnetic field on the floating potential profile near the spacecraft is also considered. Although the numerical approaches in iPic3D and PTetra are rather different, good agreement is found between the two models, raising the level of confidence in both codes to predict and evaluate the complex plasma environment around spacecraft.

42 ENGINEERING↗
DOE OSTI2016

Quantum transport modelling of silicon nanobeams using heterogeneous computing scheme

We report the development of a powerful method for quantum transport calculations of nanowire/nanobeam structures with large cross sectional area. Our approach to quantum transport is based on Green's functions and tight-binding potentials. A linear algebraic formulation allows us to harness the massively parallel nature of Graphics Processing Units (GPUs) and our implementation is based on a heterogeneous parallel computing scheme with traditional processors and GPUs working together. Using our software tool, the electronic and quantum transport properties of silicon nanobeams with a realistic cross sectional area of ∼22.7 nm{sup 2} and a length of ∼81.5 nm—comprising 105 000 Si atoms and 24 000 passivating H atoms in the scattering region—are investigated. The method also allows us to perform significant averaging over impurity configurations—all possible configurations were considered in the case of single impurities. Finally, the effect of the position and number of vacancy defects on the transport properties was considered. It is found that the configurations with the vacancies lying closer to the local density of states (LDOS) maxima have lower transmission functions than the configurations with the vacancies located at LDOS minima or far away from LDOS maxima, suggesting both a qualitative method to tune or estimate optimal impurity configurations as well as a physical picture that accounts for device variability. Finally, we provide performance benchmarks for structures as large as ∼42.5 nm{sup 2} cross section and ∼81.5 nm length.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Accelerated fast iterative shrinkage thresholding algorithms for sparsity-regularized cone-beam CT image reconstruction

Purpose: The development of iterative image reconstruction algorithms for cone-beam computed tomography (CBCT) remains an active and important research area. Even with hardware acceleration, the overwhelming majority of the available 3D iterative algorithms that implement nonsmooth regularizers remain computationally burdensome and have not been translated for routine use in time-sensitive applications such as image-guided radiation therapy (IGRT). In this work, two variants of the fast iterative shrinkage thresholding algorithm (FISTA) are proposed and investigated for accelerated iterative image reconstruction in CBCT. Methods: Algorithm acceleration was achieved by replacing the original gradient-descent step in the FISTAs by a subproblem that is solved by use of the ordered subset simultaneous algebraic reconstruction technique (OS-SART). Due to the preconditioning matrix adopted in the OS-SART method, two new weighted proximal problems were introduced and corresponding fast gradient projection-type algorithms were developed for solving them. We also provided efficient numerical implementations of the proposed algorithms that exploit the massive data parallelism of multiple graphics processing units. Results: The improved rates of convergence of the proposed algorithms were quantified in computer-simulation studies and by use of clinical projection data corresponding to an IGRT study. The accelerated FISTAs were shown to possess dramatically improved convergence properties as compared to the standard FISTAs. For example, the number of iterations to achieve a specified reconstruction error could be reduced by an order of magnitude. Volumetric images reconstructed from clinical data were produced in under 4 min. Conclusions: The FISTA achieves a quadratic convergence rate and can therefore potentially reduce the number of iterations required to produce an image of a specified image quality as compared to first-order methods. We have proposed and investigated accelerated FISTAs for use with two nonsmooth penalty functions that will lead to further reductions in image reconstruction times while preserving image quality. Moreover, with the help of a mixed sparsity-regularization, better preservation of soft-tissue structures can be potentially obtained. The algorithms were systematically evaluated by use of computer-simulated and clinical data sets.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Addressing numerical challenges in introducing a reactive transport code into a land surface model: a biogeochemical modeling proof-of-concept with CLM–PFLOTRAN 1.0

Abstract. We explore coupling to a configurable subsurface reactive transport code as a flexible and extensible approach to biogeochemistry in land surface models. A reaction network with the Community Land Model carbon–nitrogen (CLM-CN) decomposition, nitrification, denitrification, and plant uptake is used as an example. We implement the reactions in the open-source PFLOTRAN (massively parallel subsurface flow and reactive transport) code and couple it with the CLM. To make the rate formulae designed for use in explicit time stepping in CLMs compatible with the implicit time stepping used in PFLOTRAN, the Monod substrate rate-limiting function with a residual concentration is used to represent the limitation of nitrogen availability on plant uptake and immobilization. We demonstrate that CLM–PFLOTRAN predictions (without invoking PFLOTRAN transport) are consistent with CLM4.5 for Arctic, temperate, and tropical sites.Switching from explicit to implicit method increases rigor but introduces numerical challenges. Care needs to be taken to use scaling, clipping, or log transformation to avoid negative concentrations during the Newton iterations. With a tight relative update tolerance (STOL) to avoid false convergence, an accurate solution can be achieved with about 50 % more computing time than CLM in point mode site simulations using either the scaling or clipping methods. The log transformation method takes 60–100 % more computing time than CLM. The computing time increases slightly for clipping and scaling; it increases substantially for log transformation for half saturation decrease from 10-3 to 10-9 mol m-3, which normally results in decreasing nitrogen concentrations. The frequent occurrence of very low concentrations (e.g. below nanomolar) can increase the computing time for clipping or scaling by about 20 %, double for log transformation. Overall, the log transformation method is accurate and robust, and the clipping and scaling methods are efficient. When the reaction network is highly nonlinear or the half saturation or residual concentration is very low, the allowable time-step cuts may need to be increased for robustness for the log transformation method, or STOL may need to be tightened for the clipping and scaling methods to avoid false convergence.As some biogeochemical processes (e.g., methane and nitrous oxide reactions) involve very low half saturation and thresholds, this work provides insights for addressing nonphysical negativity issues and facilitates the representation of a mechanistic biogeochemical description in Earth system models to reduce climate prediction uncertainty.

58 GEOSCIENCES↗
DOE OSTI2014

Massively-parallel electron dynamics calculations in real-time and real-space: Toward applications to nanostructures of more than ten-nanometers in size

A highly efficient program of massively parallel calculations for electron dynamics has been developed in an effort to apply the method to optical response of nanostructures of more than ten-nanometers in size. The approach is based on time-dependent density functional theory calculations in real-time and real-space. The computational code is implemented by using simple algorithms with a finite-difference method in space derivative and Taylor expansion in time-propagation. Since the computational program is free from the algorithms of eigenvalue problems and fast-Fourier-transformation, which are usually implemented in conventional quantum chemistry or band structure calculations, it is highly suitable for massively parallel calculations. Benchmark calculations using the K computer at RIKEN demonstrate that the parallel efficiency of the program is very high on more than 60 000 CPU cores. The method is applied to optical response of arrays of C{sub 60} orderly nanostructures of more than 10 nm in size. The computed absorption spectrum is in good agreement with the experimental observation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Simulation of dilute polymeric fluids in a three-dimensional contraction using a multiscale FENE model

The multiscale FENE model is applied to a 3D square-square contraction flow problem. For this purpose, the stochastic Brownian configuration field method (BCF) has been coupled with our fully parallelized three-dimensional Navier-Stokes solver NaSt3DGPF. The robustness of the BCF method enables the numerical simulation of high Deborah number flows for which most macroscopic methods suffer from stability issues. The results of our simulations are compared with that of experimental measurements from literature and show a very good agreement. In particular, flow phenomena such as a strong vortex enhancement, streamline divergence and a flow inversion for highly elastic flows are reproduced. Due to their computational complexity, our simulations require massively parallel computations. Using a domain decomposition approach with MPI, the implementation achieves excellent scale-up results for up to 128 processors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Parallel Tensor Compression for Large-Scale Scientific Data.

As parallel computing trends towards the exascale, scientific data produced by high-fidelity simulations are growing increasingly massive. For instance, a simulation on a three-dimensional spatial grid with 512 points per dimension that tracks 64 variables per grid point for 128 time steps yields 8 TB of data. By viewing the data as a dense five way tensor, we can compute a Tucker decomposition to find inherent low-dimensional multilinear structure, achieving compression ratios of up to 10000 on real-world data sets with negligible loss in accuracy. So that we can operate on such massive data, we present the first-ever distributed memory parallel implementation for the Tucker decomposition, whose key computations correspond to parallel linear algebra operations, albeit with nonstandard data layouts. Our approach specifies a data distribution for tensors that avoids any tensor data redistribution, either locally or in parallel. We provide accompanying analysis of the computation and communication costs of the algorithms. To demonstrate the compression and accuracy of the method, we apply our approach to real-world data sets from combustion science simulations. We also provide detailed performance results, including parallel performance in both weak and strong scaling experiments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A parallel, distributed memory implementation of the adaptive sampling configuration interaction method

The many-body simulation of quantum systems is an active field of research that involves several different methods targeting various computing platforms. Many methods commonly employed, particularly coupled cluster methods, have been adapted to leverage the latest advances in modern high-performance computing. Selected configuration interaction (sCI) methods have seen extensive usage and development in recent years. However, the development of sCI methods targeting massively parallel resources has been explored only in a few research works. Here, we present a parallel, distributed memory implementation of the adaptive sampling configuration interaction approach (ASCI) for sCI. In particular, we will address the key concerns pertaining to the parallelization of the determinant search and selection, Hamiltonian formation, and the variational eigenvalue calculation for the ASCI method. Load balancing in the search step is achieved through the application of memory-efficient determinant constraints originally developed for the ASCI-PT2 method. The presented benchmarks demonstrate near optimal speedup for ASCI calculations of Cr 2 (24e, 30o) with 10 6 , 10 7 , and 3 × 10 8 variational determinants on up to 16 384 CPUs. Importantly, to the best of the authors’ knowledge, this is the largest variational ASCI calculation to date.

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

MapReduceXMT v. Beta 0.1

The MapReduceXMT library ports the MapReduce framework onto the Cray XMT. MapReduce is a programming paradigm and an approach to data management for unstructured problems. It has gained relevance due to its ability to map serial operations onto parallel distributed architectures, significantly improving developer/analyst productivity. The MapReduceXMT implements the key aspects of MapReduce for the Cray XMT, a massively threaded system that is inherently difficult to program. MapReduceXMT allows users to utilize the machine effectively and efficiently without extensive training in multi-threaded programming. The MapReduceXMT library ports the MapReduce framework onto the Cray XMT. MapReduce is a programming paradigm and an approach to data management for unstructured problems. It has gained relevance due to its ability to map serial operations onto parallel distributed architectures, significantly improving developer/analyst productivity. The MapReduceXMT implements the key aspects of MapReduce for the Cray XMT, a massively threaded system that is inherently difficult to program. MapReduceXMT allows users to utilize the machine effectively and efficiently without extensive training in multi-threaded programming.

Goodman, Eric↗