Search NASA⌕ Search

SEARCH · Search NASA

Results for “Implementation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Multi-species collisions for delta-f gyrokinetic simulations: Implementation and verification with GENE

we report a multi-species linearized collision operator based on the model developed by Sugama et al. has been implemented in the nonlinear gyrokinetic code, GENE. Such a model conserves particles, momentum, and energy to machine precision, and is shown to have negative definite free energy dissipation characteristics, satisfying Boltzmann’s H-theorem, including for realistic mass ratio. Finite Larmor Radius (FLR) effects have also been implemented into the local version of the code. For the global version of the code, the collision operator has been developed to allow for block-structured velocity space grids, allowing for computationally tractable collisional global simulations. The validity of the collision operator has been demonstrated by relaxation and conservation tests, as well as appropriate benchmarks. The newly implemented operator shall be used in future simulations to study magnetically confined fusion plasma turbulence and transport in more extreme regions with higher collisionality.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

A higher-order finite-element implementation of the nonlinear Fokker–Planck collision operator for charged particle collisions in a low density plasma

Collisions between particles in a low density plasma are described by the Fokker–Planck collision operator. In applications, this nonlinear integro-differential operator is often approximated by linearised or ad-hoc model operators due to computational cost and complexity. In this work, we present an implementation of the nonlinear Fokker–Planck collision operator written in terms of Rosenbluth potentials in the Rosenbluth–MacDonald–Judd (RMJ) form. The Rosenbluth potentials may be obtained either by direct integration or by solving partial differential equations (PDEs) similar to Poisson's equation: we optimise for performance and scalability by using sparse matrices to solve the relevant PDEs. We represent the distribution function using a tensor-product continuous-Galerkin finite-element representation and we derive and describe the implementation of the weak form of the collision operator. We present tests demonstrating a successful implementation using an explicit time integrator and we comment on the speed and accuracy of the operator. Finally, we speculate on the potential for applications in the current and next generation of kinetic plasma models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

LuGo: An enhanced quantum phase estimation implementation

Quantum Phase Estimation (QPE) is a cardinal algorithm in quantum computing that plays a crucial role in various applications, including cryptography, molecular simulation, and solving systems of linear equations. However, the standard implementation of QPE faces challenges related to time complexity and circuit depth, which limit its practicality for large-scale computations. We introduce LuGo, a novel framework designed to enhance the performance of QPE by reducing circuit duplication, as well as using parallelization techniques to achieve faster generation of the QPE circuit and gate reduction. We validate the effectiveness of our framework by generating quantum linear solver circuits, which require both QPE and inverse QPE, to solve linear systems of equations. LuGo achieves significant improvements in both computational efficiency and hardware requirements without compromising on accuracy. Compared to a standard QPE implementation, LuGo reduces time consumption to generate a circuit that solves a 2 6 × 2 6 system matrix by a factor of 50.68 and over 31× reduction of quantum gates and circuit depth, with no fidelity loss on an ideal quantum simulator. Furthermore, we demonstrated the versatility and scalability of LuGo enabled HHL algorithm by simulating a canonical Hele-Shaw fluid problem using a quantum simulator. With these advantages, LuGo paves the way for more efficient implementations of QPE, enabling broader applications across several quantum computing domains.

Quantum algorithm↗
DOE OSTI2024

A robust spectral element implementation of the $k - τ$ RANS model in Nek5000/NekRS

The $k - ω$ Reynolds Averaged Navier Stokes (RANS) model is one of the industry standard approaches for modeling of turbulent flows. It performs better than the $k - ϵ$ model for low Reynolds number flows and is also more suitable for boundary layers with adverse pressure gradients. Major drawback of the model, however, is that the asymptotic value of $ω$ at the walls is singular, necessitating the use of a contrived “sufficiently” large value for $ω$ as the boundary condition for its transport equation. Here, this invariably leads to the solution being sensitive to near wall grid spacing. While an acceptable solution for low order (finite volume) methods, the excessive near wall gradients lead to persistent numerical stability issues in high order codes. To alleviate the problem, specifically in the context of the high order spectral element code Nek5000, a regularized $k - ω$ approach was formulated in our prior work (Tomboulides et al., 2018). The formulation, however, relies on the use of wall distance and its gradients for modeling the closure terms and can pose problems for simulations in complex geometries. This work presents a novel implementation of the $k - τ$ RANS model in Nek5000, where $τ = 1/ω$, eliminating the need for regularization, owing to the asymptotically bounded behavior of the source terms in the $τ$ transport equation, and also eliminating dependence on wall distance. Robustness and stability of the $k - τ$ model is ensured through implicit treatment of the source terms and their careful numerical implementation and demonstrated through several cases aimed at verification and validation. Studies include both canonical and engineering relevant problems, viz., turbulent channel flow, pipe flow, backward facing step, flow over NACA 0012 airfoil and flow in a T-junction. Results from the $k - τ$ model are shown to be consistent with regularized $k - ω$ model and also with the $k - ω$ SST model in OpenFOAM (for select studies). Comparison with experimental data is also shown, where available, to bolster validation efforts for the $k - τ$ model implementation through prediction of key turbulent quantities of interest.

Nek5000↗
DOE OSTI2021

Implementation of dietary methionine restriction using casein after selective, oxidative deletion of methionine

Dietary methionine restriction (MR) is normally implemented using diets formulated from elemental amino acids (AA) that reduce methionine content to 0.17%. However, translational implementation of MR with elemental AA-based diets is intractable due to poor palatability. To solve this problem and restrict methionine using intact proteins, casein was subjected to mild oxidation to selectively reduce methionine. Diets were then formulated using oxidized casein, adding back methionine to produce a final concentration of 0.17%. The biological efficacy of dietary MR using the oxidized casein (Ox Cas) diet was compared with the standard elemental MR diet in terms of the behavioral, metabolic, endocrine, and transcriptional responses to the four diets. The Ox Cas MR diet faithfully reproduced the expected physiological, biochemical, and transcriptional responses in liver and inguinal white adipose tissue. Collectively, these findings demonstrate that dietary MR can be effectively implemented using casein after selective oxidative reduction of methionine.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Efficient implementation of the many-body Reactive Bond Order (REBO) potential on GPU

The second generation Reactive Bond Order (REBO) empirical potential is commonly used to accurately model a wide range hydrocarbon materials. It is also extensible to other atom types and interactions. REBO potential assumes complex multi-body interaction model, that is difficult to represent efficiently in the SIMD or SIMT programming model. Hence, despite its importance, no efficient GPGPU implementation has been developed for this potential. Here we present a detailed description of a highly efficient GPGPU implementation of molecular dynamics algorithm using REBO potential. The presented algorithm takes advantage of rarely used properties of the SIMT architecture of a modern GPU to solve difficult synchronizations issues that arise in computations of multi-body potential. Techniques developed for this problem may be also used to achieve efficient solutions of different problems. The performance of proposed algorithm is assessed using a range of model systems. It is compared to highly optimized CPU implementation (both single core and OpenMP) available in LAMMPS package. These experiments show up to 6x improvement in forces computation time using single processor of the NVIDIA Tesla K80 compared to high end 16-core Intel Xeon processor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Multiresolution molecular mechanics: Implementation and efficiency

Atomistic/continuum coupling methods combine accurate atomistic methods and efficient continuum methods to simulate the behavior of highly ordered crystalline systems. Coupled methods utilize the advantages of both approaches to simulate systems at a lower computational cost, while retaining the accuracy associated with atomistic methods. Many concurrent atomistic/continuum coupling methods have been proposed in the past; however, their true computational efficiency has not been demonstrated. The present work presents an efficient implementation of a concurrent coupling method called the Multiresolution Molecular Mechanics (MMM) for serial, parallel, and adaptive analysis. First, we present the features of the software implemented along with the associated technologies. The scalability of the software implementation is demonstrated, and the competing effects of multiscale modeling and parallelization are discussed. Then, the algorithms contributing to the efficiency of the software are presented. These include algorithms for eliminating latent ghost atoms from calculations and measurement-based dynamic balancing of parallel workload. The efficiency improvements made by these algorithms are demonstrated by benchmark tests. The efficiency of the software is found to be on par with LAMMPS, a state-of-the-art Molecular Dynamics (MD) simulation code, when performing full atomistic simulations. Speed-up of the MMM method is shown to be directly proportional to the reduction of the number of the atoms visited in force computation. Finally, an adaptive MMM analysis on a nanoindentation problem, containing over a million atoms, is performed, yielding an improvement of 6.3–8.5 times in efficiency, over the full atomistic MD method. For the first time, the efficiency of a concurrent atomistic/continuum coupling method is comprehensively investigated and demonstrated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Efficient algorithms and implementations of entropy-based moment closures for rarefied gases

We present efficient algorithms and implementations of the 35-moment system equipped with the maximum-entropy closure in the context of rarefied gases. While closures based on the principle of entropy maximization have been shown to yield very promising results for moderately rarefied gas flows, the computational cost of these closures is in general much higher than for closure theories with explicit closed-form expressions of the closing fluxes, such as Grad's classical closure. Following a similar approach as Garrett et al. (2015) , we investigate efficient implementations of the computationally expensive numerical quadrature method used for the moment evaluations of the maximum-entropy distribution by exploiting its inherent fine-grained parallelism with the parallelism offered by multi-core processors and graphics cards. We show that using a single graphics card as an accelerator allows speed-ups of two orders of magnitude when compared to a serial CPU implementation. To accelerate the time-to-solution for steady-state problems, we propose a new semi-implicit time discretization scheme. The resulting nonlinear system of equations is solved with a Newton type method in the Lagrange multipliers of the dual optimization problem in order to reduce the computational cost. Additionally, fully explicit time-stepping schemes of first and second order accuracy are presented. We investigate the accuracy and efficiency of the numerical schemes for several numerical test cases, including a steady-state shock-structure problem.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Implementation of metal-friendly EAM/FS-type semi-empirical potentials in HOOMD-blue: A GPU-accelerated molecular dynamics software

We present an implementation of EAM and FS interatomic potentials, which are widely used in simulating metallic systems, in HOOMD-blue, a software designed to perform classical molecular dynamics simulations using GPU accelerations. We first discuss the details of our implementation and then report extensive benchmark tests. We demonstrate that single-precision floating point operations efficiently implemented on GPUs can produce sufficient accuracy when compared against double-precision codes, as demonstrated in test simulations of calculations of the glass-transition temperature of Cu 64.5 Zr 35.5 , and pair correlation function of liquid Ni 3 Al. Our code scales well with the size of the simulating system on NVIDIA Tesla M40 and P100 GPUs. Compared with another popular software LAMMPS running on 32 cores of AMD Opteron 6220 processors, the GPU/CPU performance ratio can reach as high as 4.6. In conclusion, the source code can be accessed through the HOOMD-blue web page for free by any interested user.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Semi-Empirical Shadow Molecular Dynamics: A PyTorch Implementation

Here, extended Lagrangian Born–Oppenheimer molecular dynamics (XL-BOMD) in its most recent shadow potential energy version has been implemented in the semiempirical PyTorch-based software PySeQM. The implementation includes finite electronic temperatures, canonical density matrix perturbation theory, and an adaptive Krylov subspace approximation for the integration of the electronic equations of motion within the XL-BOMB approach (KSA-XL-BOMD). The PyTorch implementation leverages the use of GPU and machine learning hardware accelerators for the simulations. The new XL-BOMD formulation allows studying more challenging chemical systems with charge instabilities and low electronic energy gaps. The current public release of PySeQM continues our development of modular architecture for large-scale simulations employing semi-empirical quantum-mechanical treatment. Applied to molecular dynamics, simulation of 840 carbon atoms, one integration time step executes in 4 s on a single Nvidia RTX A6000 GPU.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Cholesky Decomposition-Based Implementation of Relativistic Two-Component Coupled-Cluster Methods for Medium-Sized Molecules

A Cholesky decomposition (CD)-based implementation of relativistic two-component coupled-cluster (CC) and equation-of-motion CC (EOM-CC) methods using an exact two-component Hamiltonian augmented with atomic-mean-field integrals (the X2CAMF scheme) is reported. Furthermore, the present CD-based implementation of X2CAMF-CC and EOM-CC methods employs atomic-orbital-based algorithms to avoid the construction of two-electron integrals and intermediates involving three and four virtual indices. The CD-based implementation extends the applicability of X2CAMF-CC and EOMCC methods to medium-sized molecules with the correlation of around 1000 spinors. Benchmark calculations for uranium-containing small molecules have been performed to assess the dependence of CC results with respect to the Cholesky threshold. A Cholesky threshold of 10 –4 is shown to maintain chemical accuracy. Example calculations to illustrate the capability of the CD-based relativistic CC methods are reported for the bond dissociation energy of the uranium hexafluoride molecule, UF 6 , with up to quadruple-zeta basis sets and the lowest excitation energy in solvated uranyl ion [UO 2 2+ (H 2 O) 12 ].

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Static Subspace Approximation for Random Phase Approximation Correlation Energies: Implementation and Performance

Developing theoretical understanding of complex reactions and processes at interfaces requires using methods that go beyond semilocal density functional theory to accurately describe the interactions between solvent, reactants and substrates. Methods based on many-body perturbation theory, such as the random phase approximation (RPA), have previously been limited due to their computational complexity. However, this is now a surmountable barrier due to the advances in computational power available, in particular through modern GPU-based supercomputers. In this work, we describe the implementation of RPA calculations within BerkeleyGW and show its favorable computational performance on large complex systems relevant for catalysis and electrochemistry applications. Our implementation builds off of the static subspace approximation which, by employing a compressed representation of the frequency dependent polarizability, enables the evaluation of the RPA correlation energy with significant acceleration and systematically controllable accuracy. We find that the computational cost of calculating the RPA correlation energy scales only linearly with system size for systems containing up to 50 thousand bands, and is expected to scale quadratically thereafter. We also show excellent strong scaling results across several supercomputers, demonstrating the performance and portability of this implementation.

algorithmic development↗
DOE OSTI2023

Quantum reservoir computing implementation on coherently coupled quantum oscillators

Quantum reservoir computing is a promising approach for quantum neural networks, capable of solving hard learning tasks on both classical and quantum input data. However, current approaches with qubits suffer from limited connectivity. We propose an implementation for quantum reservoir that obtains a large number of densely connected neurons by using parametrically coupled quantum oscillators instead of physically coupled qubits. We analyze a specific hardware implementation based on superconducting circuits: with just two coupled quantum oscillators, we create a quantum reservoir comprising up to 81 neurons. We obtain state-of-the-art accuracy of 99% on benchmark tasks that otherwise require at least 24 classical oscillators to be solved. Our results give the coupling and dissipation requirements in the system and show how they affect the performance of the quantum reservoir. Beyond quantum reservoir computing, the use of parametrically coupled bosonic modes holds promise for realizing large quantum neural network architectures, with billions of neurons implemented with only 10 coupled quantum oscillators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Low cost, flexible, and distribution level universal grid analyser platform: designs and implementations

This study presents the designs and implementations of a distribution level open-universal grid analyser (Open-UGA) platform. The proposed Open-UGA platform consists of distribution-level phasor measurement units (PMUs), a standard signal generator, a router, and a server. Firstly, an overall introduction for the software, hardware, and server architectures of the Open-UGA platform is given. To give a detailed design, the software, hardware, server block diagrams, flowcharts, and printed circuit board photo of the Open-UGA platform are presented in detail. Then, four different types of distribution level PMU algorithms are introduced and implemented in the Open-UGA platform to verify the flexibility and reconfigurability. The flowcharts and functionalities of these four UGAs with different PMU algorithms are given as example implementations. Lastly, a performance comparison is conducted with both quantitative and illustrative results.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Implementation of Feldman-Cousins Corrections and Oscillation Calculations in the HPC Environment for the NOvA Experiment

Analysis of neutrino oscillation data involves a combination of complex fitting procedures and statistical correction techniques that are used to determine the full three-flavor PMNS parameters and constraint contours. These techniques rely on computationally intensive “multi-universe” stochastic modeling. The process of calculating these contours and corrections can dominate final stages of the data analysis and become a bottleneck for examining the ef-fect of systematic variations on the final results. As part of the DOE SciDAC-4 sponsored research program, we present a new implementation of a neutrino oscillation fitting and framework to carry out calculations of Feldman-Cousins corrections. This implementation is specifically designed and optimized to operate on modern High-Performance Computing (HPC) facilities. We present the performance of the system in calculating allowed regions for the NOvA experiment based on 8.9 x 1020 and 6.9 x 1020 protons-on-target (POT) neutrino and antineutrino datasets, and compare the performance of this new implementation run at the NERSC supercomputing facility with that from methods used previously by the NOvA collaboration running on grid computing facilities.

Sousa, Alexandre↗
DOE OSTI2025

Real Time implementation of Artificial Intelligence compression algorithm for High-Speed Streaming Readout signals

The new generation of high-energy physics experiments plans to acquire data in streaming mode. With this approach, it is possible to access the information of the whole detector (organized in time slices) for optimal and lossless triggering of data acquisitions. With this approach, data rates, especially in large detectors, are often very high, and the network is likely to be the bottleneck for the entire Streaming Read Out system. The aim of this work is to study the implementation of a lossy compression algorithm based on Artificial Intelligence: an Autoencoder. With Machine Learning it is possible to achieve a high compression ratio and fast inference time with only a small degradation of the signals, almost negligible for the specific application. This work explores different configurations of the Autoencoder and the implementation on different hardware. Different Autoencoder configurations are explored to find the best trade-off between compression ratio and reconstruction loss, both for signals and energy spectrum. Different hardware implementations are also explored to find the best platform to achieve real-time performance for the specific application.

Rossi, Fabio (ORCID:0009000385713885)↗
DOE OSTI2015

Development of intelligent instruments with embedded HTTP servers for control and data acquisition in a cryogenic setup—The hardware, firmware, and software implementation

The power of Ethernet for control and automation technology is being largely understood by the automation industry in recent times. Ethernet with HTTP (Hypertext Transfer Protocol) is one of the most widely accepted communication standards today. Ethernet is best known for being able to control through internet from anywhere in the globe. The Ethernet interface with built-in on-chip embedded servers ensures global connections for crate-less model of control and data acquisition systems which have several advantages over traditional crate-based control architectures for slow applications. This architecture will completely eliminate the use of any extra PLC (Programmable Logic Controller) or similar control hardware in any automation network as the control functions are firmware coded inside intelligent meters itself. Here, we describe the indigenously built project of a cryogenic control system built for linear accelerator at Inter University Accelerator Centre, known as “CADS,” which stands for “Complete Automation of Distribution System.” CADS deals with complete hardware, firmware, and software implementation of the automated linac cryogenic distribution system using many Ethernet based embedded cryogenic instruments developed in-house. Each instrument works as an intelligent meter called device-server which has the control functions and control loops built inside the firmware itself. Dedicated meters with built-in servers were designed out of ARM (Acorn RISC (Reduced Instruction Set Computer) Machine) and ATMEL processors and COTS (Commercially Off-the-Shelf) SMD (Surface Mount Devices) components, with analog sensor front-end and a digital back-end web server implementing remote procedure call over HTTP for digital control and readout functions. At present, 24 instruments which run 58 embedded servers inside, each specific to a particular type of sensor-actuator combination for closed loop operations, are now deployed and distributed across control LAN (Local Area Network). A group of six categories of such instruments have been identified for all cryogenic applications required for linac operation which were designed to build this medium-scale cryogenic automation setup. These devices have special features like remote rebooters, daughter boards for PIDs (Proportional Integral Derivative), etc., to operate them remotely in radiation areas and also have emergency switches by which each device can be taken to emergency mode temporarily. Finally, all the data are monitored, logged, controlled, and analyzed online at a central control room which has a user-friendly control interface developed using LabVIEW{sup ®}. This paper discusses the overall hardware, firmware, software design, and implementation for the cryogenics setup.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Discrete photon implementation for plasma simulations

The self-produced light emission from pulsed plasma discharges and its impact on plasma development are challenging to characterize through simulation and modeling, chiefly due to the large number of radiating species and limited computer memory. Often, photo-processes, such as photo-ionization or photo-emission of electrons, are implemented through over-simplifying approximations or neglected altogether. Here, a method applicable to plasma simulations is implemented in a Particle-in-Cell /Monte Carlo Collision model, which is capable of discretely tracking photons and their corresponding wavelengths. Combined with the appropriate cross sections or quantum yields, a wavelength dependent model for photo-ionization or photo-emission may be implemented. Additionally, by resolving the wavelengths of each photon, an emission spectrum for a region of interest may be generated. Simulations for a pure nitrogen environment reveal that the calculated emission profile of the second positive system agrees well with the experimental spectrum of a pulsed, nanosecond discharge in the same spectral region.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗