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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Multi‐dimensional lock‐free arrays for multithreaded mode‐directed tabling in Prolog

Summary This work proposes a new design for the supporting data structures used to implement multithreaded tabling in Prolog systems. Tabling is an implementation technique that improves the expressiveness of traditional Prolog systems in dealing with recursion and redundant computations. Mode‐directed tabling is an extension to the tabling technique that supports the definition of alternative criteria for specifying how answers are aggregated, thus being very suitable for problems where the goal is to dynamically calculate optimal or selective answers. In this work, we leverage the intrinsic potential that mode‐directed tabling has to express dynamic programming problems by creating a new design that improves the representation of multi‐dimensional arrays in the context of multithreaded tabling. To do so, we introduce a new mode for indexing arguments in mode‐directed tabled evaluations, named dim , where each dim argument features a uni‐dimensional lock‐free array. Experimental results using well‐known dynamic programming problems on a 32‐core machine show that the new design introduces less overheads and clearly improves the execution time for sequential and multithreaded tabled evaluations.

Areias, Miguel↗
DOE OSTI2021

Autotuning PolyBench benchmarks with LLVM Clang/Polly loop optimization pragmas using Bayesian optimization

Here, we develop a ytopt autotuning framework that leverages Bayesian optimization to explore the parameter space search and compare four different supervised learning methods within Bayesian optimization and evaluate their effectiveness. We select six of the most complex PolyBench benchmarks and apply the newly developed LLVM Clang/Polly loop optimization pragmas to the benchmarks to optimize them. We then use the autotuning framework to optimize the pragma parameters to improve their performance. The experimental results show that our autotuning approach outperforms the other compiling methods to provide the smallest execution time for the benchmarks syr2k, 3mm, heat-3d, lu, and covariance with two large datasets in 200 code evaluations for effectively searching the parameter spaces with up to 170,368 different configurations. We find that the Floyd-Warshall benchmark did not benefit from autotuning. To cope with this issue, we provide some compiler option solutions to improve the performance. Then we present loop autotuning without a user's knowledge using a simple mctree autotuning framework to further improve the performance of the Floyd-Warshall benchmark. We also extend the ytopt autotuning framework to tune a deep learning application.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Results of a Geant4 benchmarking study for bio‐medical applications, performed with the G4‐Med system

Geant4, a Monte Carlo Simulation Toolkit extensively used in bio-medical physics, is in continuous evolution to include newest research findings to improve its accuracy and to respond to the evolving needs of a very diverse user community. In 2014, the G4-Med benchmarking system was born from the effort of the Geant4 Medical Simulation Benchmarking Group, to benchmark and monitor the evolution of Geant4 for medical physics applications. The G4-Med system was first described in our Medical Physics Special Report published in 2021. Results of the tests were reported for Geant4 10.5. Purpose In this work, we describe the evolution of the G4-Med benchmarking system. Methods The G4-Med benchmarking suite currently includes 23 tests, which benchmark Geant4 from the calculation of basic physical quantities to the simulation of more clinically relevant set-ups. New tests concern the benchmarking of Geant4-DNA physics and chemistry components for regression testing purposes, dosimetry for brachytherapy with a 125 I source, dosimetry for external x-ray and electron FLASH radiotherapy, experimental microdosimetry for proton therapy, and in vivo PET for carbon and oxygen beams. Regression testing has been performed between Geant4 10.5 and 11.1. Finally, a simple Geant4 simulation has been developed and used to compare Geant4 EM physics constructors and physics lists in terms of execution times. Results In summary, our EM tests show that the parameters of the multiple scattering in the Geant4 EM constructor G4EmStandardPhysics_option3 in Geant4 11.1, while improving the modeling of the electron backscattering in high atomic number targets, are not adequate for dosimetry for clinical x-ray and electron beams. Therefore, these parameters have been reverted back to those of Geant4 10.5 in Geant4 11.2.1. The x-ray radiotherapy test shows significant differences in the modeling of the bremsstrahlung process, especially between G4EmPenelopePhysics and the other constructors under study (G4EmLivermorePhysics, G4EmStandardPhysics_option3, and G4EmStandardPhysics_option4). These differences will be studied in an in-depth investigation within our Group. Improvement in Geant4 11.1 has been observed for the modeling of the proton and carbon ion Bragg peak with energies of clinical interest, thanks to the adoption of ICRU90 to calculate the low energy proton stopping powers in water and of the Linhard–Sorensen ion model, available in Geant4 since version 11.0. Nuclear fragmentation tests of interest for carbon ion therapy show differences between Geant4 10.5 and 11.1 in terms of fragment yields. In particular, a higher production of boron fragments is observed with Geant4 11.1, leading to a better agreement with reference data for this fragment. Conclusions Based on the overall results of our tests, we recommend to use G4EmStandardPhysics_option4 as EM constructor and QGSP_BIC_HP with G4EmStandardPhysics_option4, for hadrontherapy applications. The Geant4-DNA physics lists report differences in modeling electron interactions in water, however, the tests have a pure regression testing purpose so no recommendation can be formulated.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Pairwise‐Parallel Entangling Gates on Orthogonal Modes in a Trapped‐Ion Chain

Abstract Parallel operations are important for both near‐term quantum computers and larger‐scale fault‐tolerant machines because they reduce execution time and qubit idling. This study proposes and implements a pairwise‐parallel gate scheme on a trapped‐ion quantum computer. The gates are driven simultaneously on different sets of orthogonal motional modes of a trapped‐ion chain. This work demonstrates the utility of this scheme by creating a Greenberger‐Horne‐Zeilinger (GHZ) state in one step using parallel gates with one overlapping qubit. It also shows its advantage for circuits by implementing a digital quantum simulation of the dynamics of an interacting spin system, the transverse‐field Ising model. This method effectively extends the available gate depth by up to two times with no overhead when no overlapping qubit is involved, apart from additional initial cooling. This scheme can be easily applied to different trapped‐ion qubits and gate schemes, broadly enhancing the capabilities of trapped‐ion quantum computers.

Optics↗
DOE OSTI2018

Evaluating Performance Portability of Accelerator Programming Models using SPEC ACCEL 1.2 Benchmarks

As heterogeneous architectures are becoming mainstream for HPC systems, application programmers are looking for programming model implementations that offer both performance and portability across platforms. Two directive-based programming models for accelerator programming that aim at doing this are OpenMP 4/4.5 and OpenACC. Many users want to know the difference between these two programming models, the state of their implementations, how to use them, and evaluate how suitable they are for their applications.The Standard Performance Evaluation Corporation (SPEC) ACCEL benchmarks, developed by the SPEC High Performance Group (HPG), recently released SPEC ACCEL 1.2 benchmark suite to help the evaluation of OpenCL, OpenMP 4.5 and OpenACC on different platforms. Inthis paper we present our preliminary results that evaluates OpenMP4.5 and OpenACC on a variety of accelerator-based systems: POWER9with NVIDIA V100 GPUs (Summit), Intel Xeon Phi 7230 (Percival), and AMD Bulldozer Opteron with NVIDIA K20x (Titan). Comparing these benchmarks on different systems gives us insight into the support for OpenMP and OpenACC and their execution times provide insights about their quality of implementations provided by different vendors. We also compare best of OpenMP and OpenACC to see if a particular programming model favors a particular type of benchmark kernel.

Boehm, Swen↗
DOE OSTI2020

3D Coded SUMMA: Communication-Efficient and Robust Parallel Matrix Multiplication

In this paper, we propose a novel fault-tolerant parallel matrix multiplication algorithm called 3D Coded SUMMA that achieves higher failure-tolerance than replication-based schemes for the same amount of redundancy. This work bridges the gap between recent developments in coded computing and fault-tolerance in high-performance computing (HPC). The core idea of coded computing is the same as algorithm-based fault-tolerance (ABFT), which is weaving redundancy in the computation using error-correcting codes. In particular, we show that MatDot codes, an innovative code construction for parallel matrix multiplications, can be integrated into three-dimensional SUMMA (Scalable Universal Matrix Multiplication Algorithm [30]) in a communication-avoiding manner. To tolerate any two node failures, the proposed 3D Coded SUMMA requires ~50% less redundancy than replication, while the overhead in execution time is only about 5–10%.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Mean-Field-Game Model for Botnet Defense in Cyber-Security

We initiate the analysis of the response of computer owners to various offers of defence systems against a cyber-hacker (for instance, a botnet attack), as a stochastic game of a large number of interacting agents. We introduce a simple mean-field game that models their behavior. It takes into account both the random process of the propagation of the infection (controlled by the botner herder) and the decision making process of customers. Its stationary version turns out to be exactly solvable (but not at all trivial) under an additional natural assumption that the execution time of the decisions of the customers (say, switch on or out the defence system) is much faster that the infection rates.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Prediction of Subsidence of Buildings as a Result of Earthquakes by Gaussian Process Regression

Subsidence of a foundation caused by liquefaction of sandy soil is a critical step in the creation of a building. Seven measured indicators of soil liquefaction in the course of an earthquake were selected as key impacting indicators that predict subsidence of a building. These indicators are the earthquake intensity EI, length–height ratio L/H, average contact pressure p, width-depth ratio, relative density D{sub R}, thickness of the non-liquefied layer, and the depth of the gravel layer. Furthermore, as a probabilistic machine learning kernel and powerful tool for solving highly nonlinear problems, Gaussian process regression (GPR model) can meet execution time requirements and assure a high level of precision of subsidence prediction due to the intrinsic defects of theoretical analysis and numerical calculation. A total of 41 groups of typical cases were first selected as a training sample and 20 groups of typical cases were defined as a test sample, where these cases possess input test value and were obtained at the yield of the prediction accuracy from the GPR model. Next, the PLS method, MLR method and LSSVM method were selected to verify the validity and reliability of the GPR model. Finally, the simulation result shows that the GPR model can improve the prediction precision for the case of the above problems and is of great value for practical applications.

58 GEOSCIENCES↗
DOE OSTI2016

HPC Node Performance and Energy Modeling with the Co-Location of Applications

Multicore processors have become an integral part of modern large-scale and high-performance parallel and distributed computing systems. This advance became necessary as the demand for increased system performance has exceeded the limits that single core processors can provide. Unfortunately, applications co-located on multicore processors can suffer from decreased performance and increased dynamic energy use as a result of access to shared resources, such as memory. Consequently, it is increasingly important to characterize the performance of applications that execute on these architectures. This work investigates some of the disadvantages of co-location, and presents a methodology for building models capable of utilizing varying amounts of information about a target application and its co-located applications to make predictions about the target application’s execution time and the system’s energy use under arbitrary co-locations of a wide range of application types. The proposed methodology is validated on three different server class Intel Xeon multicore processors using eleven applications from two scientific benchmark suites. The model’s utility for scheduling is also demonstrated in a simulated large-scale high-performance computing environment through the creation of a co-location aware scheduling heuristic. This heuristic demonstrates that scheduling using information generated with the proposed modeling methodology is capable of making significant improvements over a scheduling heuristic that is naive to co-location interference.

performance modeling, energy modeling, resource ma↗
DOE OSTI2018

A new hybrid algorithm combining a new chaos optimization approach with gradient descent for high dimensional optimization problems

Chaos optimization algorithm (COA) is a recently developed method for global optimization based on chaos theory. It has the features of easy implementation, short execution time and robust mechanisms of escaping from local optima compared with the existing stochastic searching algorithm. By integrating the gradient descent method with a new COA approach using new strategies including symmetrization and levelling, a novel hybrid method, called SCGD, is proposed in this paper. The main idea is to combine the good ability of exploitation of the gradient descent with the high ability of exploration of COA. The purpose is to avoid being trapped into local optima and to improve convergence in large space and high-dimension optimization problems. The simulation results based on a set of 50 benchmark functions with diverse properties and different dimensions show the efficiency and the abilities of the proposed method in finding the global optima compared with the existing methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Thermal hydraulic model of the molten salt reactor experiment with the NEAMS system analysis module

System analysis codes have a long history of providing best-estimate and conservative safety analysis for both light water and advanced reactor technologies, including molten salt reactors. As interest continues to expand with advanced reactor concepts, system analysis codes will need revisions to accommodate the behavior of these technologies. Legacy system analysis codes will need to be updated to the latest numerical techniques to shorten execution time and increase the accuracy of results. One example of a modern system analysis code that already encompasses these characteristics is the System Analysis Module (SAM). One key objective of this paper was to review available information for system code modeling of the Molten Salt Reactor Experiment (MSRE) from sources in the open literature and collect the information from these open sources in one place for the first time. This supports the potential objective of developing an open specification for system code analysis for MSRE steady state and transients with and without reactor kinetics. Data from actual MSRE tests will serve as the basis for code-to-code comparison exercises, including the MSRE zero power physics tests, the fuel pump start-up and coast down tests, and the natural circulation transient. The objective is to produce a code-to-code benchmark with a standardized set of comparison problems, recognizing the limitations of the original data. To demonstrate an initial application of this objective and the usefulness of compiling this open data, two Molten Salt Reactor Experiment (MSRE)-related models were developed to evaluate SAM for liquid fueled molten salt reactors. One model was the SAM MSRE hydraulic mockup, which provided experimental data for pressure drop measurements. The second model was the complete MSRE primary loop. The MSRE primary loop model incorporated a fluoride salt fuel/coolant with heat transfer in both the core and heat exchanger. For both the hydraulic mockup and MSRE primary loop models, a holistic 1-D system description was built using open documentation, an open description that can be readily modified and applied for any system analysis code. SAM results for the pressure drop of the hydraulic mockup model were within 6% with measurements. Coolant temperatures for the primary loop model matched the expected axial change in temperature from historical calculations. Using alternative coolant properties obtained from the literature, corresponding to salts with different actinide contents, returned similar trends in core temperature profiles. A thermal hydraulic demonstration of a loss-of-flow transient showed the importance of coupling SAM thermal hydraulic analysis to neutronics. Here, this coupling is essential for simulating MSR transients with system analysis codes.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Improved natural convection heat transfer correlations for reactor cavity cooling systems of high-temperature gas-cooled reactors: From computational fluid dynamics to Pronghorn

The Reactor Cavity Cooling System (RCCS) is a common reactor safety system in High Temperature Gas Cooled Reactors (HTGR) that removes heat from the Reactor Pressure Vessel (RPV) by radiation ($\sim 80\%$) and natural convection ($\sim 20\%$). For simulation of accident scenarios of HTGRs, intermediate fidelity and system codes models must be employed for limiting the models' execution time. While accurate quantification of the radiative heat transfer is available in these models, quantification of natural convection must rely on correlations of questionable accuracy for the Nusselt number. Commonly used correlations are based in experiments performed at low Rayleigh numbers and/or using isothermal walls in simplified geometries. Here, this work improves on the accuracy of natural convection heat transfer correlations in support for HTGR designs. These correlations include both local and average Nusselt numbers as a function of the global Rayleigh number, the local Rayleigh number, and the temperature profile at the hot wall of the RCCS. In the absence of dedicated experiments and the difficulty of performing high-fidelity simulations at realistic Rayleigh numbers, the data to fit the correlations are generated with Computational Fluid Dynamics (CFD) using Reynolds Averaged Navier-Stokes (RANS) models. First, a careful selection of the RANS turbulence model is performed by comparing the results obtained with different RANS turbulence models against high fidelity simulations of natural convection at $Ra \ 1 \times 10^{11}$ in a rectangular cavity. Next, the selected model is used to perform simulations of an HTGR cavity at different high Rayleigh numbers $\in [6.1 \times 10^{11},2.9 \times 10^{13}]$ to encompass several HTGR designs, assuming an isothermal RPV wall. The results obtained are used to fit a correlation for the average and space-varying Nusselt number as a function of the global and local Rayleigh numbers via a sparsity-promoting least-squares method. The selected RANS model is then used to perform simulations of a PBMR 400 HTGR cavity with the temperature profiles at the RPV wall obtained during a PLOFC transient. We use the results obtained to fit a temperature-dependent correction to the space-varying Nusselt number with the sparsity-promoting least-squares method. The results obtained in this work, enable system-level codes, such as Pronghorn, to perform higher-fidelity simulations of the heat exchange process in the RCCS while still maintaining a low computational cost.

42 ENGINEERING↗
DOE OSTI2017

Electric train energy consumption modeling

For this paper we develop an electric train energy consumption modeling framework considering instantaneous regenerative braking efficiency in support of a rail simulation system. The model is calibrated with data from Portland, Oregon using an unconstrained non-linear optimization procedure, and validated using data from Chicago, Illinois by comparing model predictions against the National Transit Database (NTD) estimates. The results demonstrate that regenerative braking efficiency varies as an exponential function of the deceleration level, rather than an average constant as assumed in previous studies. The model predictions are demonstrated to be consistent with the NTD estimates, producing a predicted error of 1.87% and -2.31%. The paper demonstrates that energy recovery reduces the overall power consumption by 20% for the tested Chicago route. Furthermore, the paper demonstrates that the proposed modeling approach is able to capture energy consumption differences associated with train, route and operational parameters, and thus is applicable for project-level analysis. The model can be easily implemented in traffic simulation software, used in smartphone applications and eco-transit programs given its fast execution time and easy integration in complex frameworks.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Discrete event cellular automata: A new approach to cellular automata for computational material science

Here, we explore the computational advantages of discrete event simulation for cellular automata models of grain growth. These benefits include a reduction in execution time by up to an order of magnitude and the elimination of numerical errors that stem from overshooting grain capture events and approximating a Poisson process with a Bernoulli process. The fundamental mechanisms speeding up the discrete event simulation are uncovered, and with these we create a speedup model that explains our experimental outcomes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Simulation toolkit for digital material characterization of large image-based microstructures

In this paper, an efficient image-based simulation toolkit for material characterization is presented, which is scalable to work from personal computers to workstations. The effective thermal conductivity, elasticity, and permeability are evaluated employing a computational homogenization framework based on the Finite Element Method (FEM). Two complementary open-source packages are presented: one developed in Python, which can convert digital images into voxel meshes (pyTomoviewer); the other developed in Julia, that can run numerical simulations to compute effective material properties (chpack). Also, a CUDA C version of chpack is provided (chfem_gpu). They were designed to deal with large multi-phase models, so strategies were devised to minimize their memory footprint, while avoiding a high toll on execution time. The voxel-based approach significantly simplifies the FEM meshes and allows efficient matrix-free implementations. In that sense, to handle large linear systems of equations, the element-by-element (EBE) technique is adopted, in conjunction with a low-memory implementation of the Preconditioned Conjugate Gradient (PCG) method. Finally, the code was thoroughly tested on an artificial geometry made of a square array of cylinders, for which analytical solutions exist, as well as on a real micro-tomographic reconstruction of FiberForm TM , a carbon preform commonly used in thermal protection systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

An improved methodology for modeling short pulse buried layer x-ray emission spectra

Radiation-hydrodynamic and spectroscopic modeling are important aspects of high energy density experimental design. In this paper, we improve the performance and capabilities over those obtainable with a previous methodology used for simulating x-ray emission spectra from buried layer targets heated by short pulse lasers. The improvement incorporates post-processing HYDRA radiation-hydrodynamic output with a non-local thermodynamic equilibrium atomic-kinetics radiation transport code, Cretin. Each code uses an independent radiation field which allows decoupling HYDRA's radiation group structure from Cretin's spectral output to improve the speed and flexibility of the design methodology. The execution time decreases from 2–3 days to a few hours while the flexibility of the improved methodology allows for performing sensitivity studies including a comparison of steady-state and time-dependent atomic kinetics and differences in the radiation group structure.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Neural network model of neutral beam injection in the EAST tokamak to enable fast transport simulations

The neutral beam injection (NBI) system in EAST produces energetic neutral particles, which collide with electrons and ions in tokamak plasmas and heat the plasmas through Coulomb collisions. Moreover, it drives a non-inductive source of current, due to the charge-exchange collision between neutral particles and ions, and injects toroidal torque, which generates a toroidal rotation of the plasma. The effect caused by the NBI system, such as plasma heating, current drive, total neutron rate, momentum transfer, and shine-through, are modeled by a comprehensive module called NUBEAM. However, NUBEAM is computationally intensive since it relies on Monte Carlo methods. In this work, a neural network model has been developed as a surrogate model for NUBEAM in EAST. The database for neural-network model training, validation and testing is generated by running TRANSP for experimental discharges from recent EAST campaigns (after the latest NBI upgrade) while using the NUBEAM module. Simulation results illustrate that the trained neural network has the capability of replicating the predictions made by NUBEAM while demanding a significantly shorter execution time. Finally, these results indicate that surrogate models like the one proposed in this work could enable fast transport simulations for EAST after integrating them into a control-oriented predictive code such as COTSIM.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Distributed Automatic Differentiation for Ptychography

Synchrotron radiation light source facilities are leading the way to ultrahigh resolution X-ray imaging. High resolution imaging is essential to understanding the fundamental structure and interaction of materials at the smallest length scale possible. Diffraction based methods achieve nanoscale imaging by replacing traditional objective lenses by pixelated area detectors and computational image reconstruction. Among these methods, ptychography is quickly becoming the standard for sub-30 nanometer imaging of extended samples, but at the expense of increasingly high data rates and volumes. This paper presents a new distributed algorithm for solving the ptychographic image reconstruction problem based on automatic differentiation. Input datasets are subdivided between multiple graphics processing units (GPUs); each subset of the problem is then solved either entirely independent of other subsets (asynchronously) or through sharing gradient information with other GPUs (synchronously). The algorithm was evaluated on simulated and real data acquired at the Advanced Photon Source, scaling up to 192 GPUs. The synchronous variant of our method outperformed an existing multi-GPU implementation in terms of accuracy while running at a comparable execution time.

distributed algorithms↗