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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 487 records · Page 27

Draco,Version 6.x.x

Draco is an object-oriented component library geared towards numerically intensive, radiation (particle) transport applications built for parallel computing hardware. It consists of semi-independent packages and a robust build system. The packages in Draco provide a set of components that can be used by multiple clients to build transport codes. The build system can also be extracted for use in clients. Software includes smart pointers, Design-by-Contract assertions, unit test framework, wrapped MPI functions, a file parser, unstructured mesh data structures, a random number generator, root finders and an angular quadrature component.

Thompson, Kelly↗

Deep Modeling: Circuit Characterization Using Theory Based Models in a Data Driven Framework

Analog computational circuits have been demonstrated to provide substantial improvements in power and speed relative to digital circuits, especially for applications requiring extreme parallelism but only modest precision. Deep machine learning is one such area and stands to benefit greatly from analog and mixed-signal implementations. However, even at modest precisions, offsets and non-linearity can degrade system performance. Furthermore, in all but the simplest systems, it is impossible to directly measure the intermediate outputs of all sub-circuits. The result is that circuit designers are unable to accurately evaluate the non-idealities of computational circuits in-situ and are therefore unable to fully utilize measurement results to improve future designs. In this paper we present a technique to use deep learning frameworks to model physical systems. Recently developed libraries like TensorFlow make it possible to use back propagation to learn parameters in the context of modeling circuit behavior. Offsets and scaling errors can be discovered even for sub-circuits that are deeply embedded in a computational system and not directly observable. The learned parameters can be used to refine simulation methods or to identify appropriate compensation strategies. We demonstrate the framework using a mixed-signal convolution operator as an example circuit.

Bolme, David S↗

Increasing Software Testing Coverage and Portability with Spack

Adequate testing coverage is critical for successful scientific software development. For numerically intensive codes, the test matrix should cover a variety of machines, compilers, third-party library dependencies, as well as possible other features such as memory testing, parallelization paradigms, and application options that may be enabled or disabled, as some examples. Such coverage can be a major burden on developers without powerful methods for managing the matrix. Spack is a great tool developed by Lawrence Livermore National Lab for managing software on a Unix-based system and in addition to this, we are leveraging Spack to simplify application testing development and management. Here we demonstrate exploiting many of Spack's features to orchestrate the test coverage for the Nalu-Wind application we are developing under the Exascale Computing Project. By using Spack underneath our testing infrastructure, we have increased our testing coverage, portability, robustness, and software quality. While we use our Nalu-Wind application as an example, the benefits of exploiting Spack for application testing can be had for other applications as well.

97 MATHEMATICS AND COMPUTING↗

Error Propagation for Response Matrix Methods in the Many Node Limit

The response matrix method has been a useful solution method for radiation transport problems for decades. The method is desirable for many reasons. It can be extended to both fixed source and eigenvalue problems. In addition, a key aspect of the method is a shift of computational expense to a precomputation phase. Methods and codes employing response matrix or response matrix-like methods have enjoyed formidable computational efficiency while solving large problems. However, current applications of the method rely on large node sizes and few nodes to maximize computational efficiency. As part of a desire to make these methods more amenable to applications such as parallel computing in the future, the number of nodes in problems may increase, and node size will decrease. The effect of this change has not been well studied except for a few cases. In the past, it was determined that a poor approximation of angular dependence of flux on node interfaces could lead to large error propagation for fixed source problems, but a newer study indicates that changing node sizes as well as number of nodes poses little challenge for response methods in the eigenvalue case. This paper presents the unintuitive result that for response matrix methods increasing the spatial resolution of the problem may dramatically decrease accuracy - this effect is demonstrated on a simple analytic 1-D benchmark problem. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Accelerated Adaptive MGS Phase Retrieval

The Modified Gerchberg-Saxton (MGS) algorithm is an image-based wavefront-sensing method that can turn any science instrument focal plane into a wavefront sensor. MGS characterizes optical systems by estimating the wavefront errors in the exit pupil using only intensity images of a star or other point source of light. This innovative implementation of MGS significantly accelerates the MGS phase retrieval algorithm by using stream-processing hardware on conventional graphics cards. Stream processing is a relatively new, yet powerful, paradigm to allow parallel processing of certain applications that apply single instructions to multiple data (SIMD). These stream processors are designed specifically to support large-scale parallel computing on a single graphics chip. Computationally intensive algorithms, such as the Fast Fourier Transform (FFT), are particularly well suited for this computing environment. This high-speed version of MGS exploits commercially available hardware to accomplish the same objective in a fraction of the original time. The exploit involves performing matrix calculations in nVidia graphic cards. The graphical processor unit (GPU) is hardware that is specialized for computationally intensive, highly parallel computation. From the software perspective, a parallel programming model is used, called CUDA, to transparently scale multicore parallelism in hardware. This technology gives computationally intensive applications access to the processing power of the nVidia GPUs through a C/C++ programming interface. The AAMGS (Accelerated Adaptive MGS) software takes advantage of these advanced technologies, to accelerate the optical phase error characterization. With a single PC that contains four nVidia GTX-280 graphic cards, the new implementation can process four images simultaneously to produce a JWST (James Webb Space Telescope) wavefront measurement 60 times faster than the previous code.

Lam, Raymond K.↗

Sculpt: Automatic Parallel Hexahedral Mesh Generation

Sculpt is a companion application to Cubit designed to run in parallel for generating all-hex meshes of complex geometry. It uses a unique overlay-grid procedure that extracts surfaces from a volume-fraction representation of the geometry. This allows for fast, automatic, fault-tolerant meshing in a high-performance computing (HPC) environment. Although Sculpt can be driven from Cubit as a GUI front-end, Sculpt was developed as a separate application so that it can be run independently from Cubit on HPC computing platforms. It was also designed as a separable software library so it can be easily integrated as an in-situ meshing solution within other codes. This work provides a brief technical discussion of the algorithms used in Sculpt as well as a complete user's manual. It includes details of the Cubit interface to Sculpt and the complete manual for the stand-alone application, including examples.

97 MATHEMATICS AND COMPUTING↗

Comparison of Parallel and Series Hybrid Power Trains for Transit Bus Applications

The fuel economy and emissions of conventional and hybrid buses equipped with emissions after treatment were evaluated via computational simulation for six representative city bus drive cycles. Both series and parallel configurations for the hybrid case were studied. The simulation results indicated that series hybrid buses have the greatest overall advantage in fuel economy. The series and parallel hybrid buses were predicted to produce similar carbon monoxide and hydrocarbon tailpipe emissions but were also predicted to have reduced tailpipe emissions of nitrogen oxides compared with the conventional bus in higher speed cycles. For the New York bus cycle, which has the lowest average speed among the cycles evaluated, the series bus tailpipe emissions were somewhat higher than they were for the conventional bus; the parallel hybrid bus had significantly lower tailpipe emissions. All three bus power trains were found to require periodic active diesel particulate filter regeneration to maintain control of particulate matter. Finally, plug-in operation of series hybrid buses appears to offer significant fuel economy benefits and is easily employed because of the relatively large battery capacity that is typical of the series hybrid configuration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Parallel transport dynamics for mixed quantum states with applications to time-dependent density functional theory

Direct simulation of the von Neumann dynamics for a general (pure or mixed) quantum state can often be expensive. One prominent example is the real-time time-dependent density functional theory (rt-TDDFT), a widely used framework for the first principle description of many-electron dynamics in chemical and materials systems. Practical rt-TDDFT calculations often avoid the direct simulation of the von Neumann equation, and solve instead a set of Schrödinger equations, of which the dynamics is equivalent to that of the von Neumann equation. However, the time step size employed by the Schrödinger dynamics is often much smaller. Here, in order to improve the time step size and the overall efficiency of the simulation, we generalize a recent work of the parallel transport (PT) dynamics for simulating pure states [An, Lin, Multiscale Model. Simul. 18, 612, 2020] to general quantum states. The PT dynamics provides the optimal gauge choice, and can employ a time step size comparable to that of the von Neumann dynamics. Going beyond the linear and near adiabatic regime in previous studies, we find that the error of the PT dynamics can be bounded by certain commutators between Hamiltonians, density matrices, and their derived quantities. Such a commutator structure is not present in the Schrödinger dynamics. We demonstrate that the parallel transport-implicit midpoint (PT-IM) method is a suitable method for simulating the PT dynamics, especially when the spectral radius of the Hamiltonian is large. The commutator structure of the error bound, and numerical results for model rt-TDDFT calculations in both linear and nonlinear regimes, confirm the advantage of the PT dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

PIPER: Performance Insight for Programmers and Exascale Runtimes: Guiding the Development of the Exascale Software Stack

The PIPER project set out to develop methodologies and software for measurement, analysis, attribution, and presentation of performance data for extreme-scale systems. Goals of the project were to support analysis of massive multi-scale parallelism, heterogeneous architectures, multi-faceted performance concerns, and to support both post-mortem performance analysis to identify program features that contribute to problematic performance and on-line performance analysis to drive adaptation. This final report summarizes the research and development activity at Rice University as part of the PIPER project. Producing a complete suite of performance tools for exascale platforms during the course of this project was impossible since both hardware and software for exascale systems is still a moving target. For that reason, the project focused broadly on the development of new techniques for measurement and analysis of performance on modern parallel architectures, enhancements to HPCToolkit’s software infrastructure to support our research goals or use on sophisticated applications, engaging developers of multithreaded runtimes to explore how support for tools should be integrated into their designs, engaging operating system developers with feature requests for enhanced monitoring support, engaging vendors with requests that they add hardware measure- ment capabilities and software interfaces needed by tools as they design new components of HPC platforms including processors, accelerators and networks, and finally collaborations with partners interested in using HPCToolkit to analyze and tune scalable parallel applications.

97 MATHEMATICS AND COMPUTING↗

High-performance parallel analysis of coupled problems for aircraft propulsion

Applications are described of high-performance parallel, computation for the analysis of complete jet engines, considering its multi-discipline coupled problem. The coupled problem involves interaction of structures with gas dynamics, heat conduction and heat transfer in aircraft engines. The methodology issues addressed include: consistent discrete formulation of coupled problems with emphasis on coupling phenomena; effect of partitioning strategies, augmentation and temporal solution procedures; sensitivity of response to problem parameters; and methods for interfacing multiscale discretizations in different single fields. The computer implementation issues addressed include: parallel treatment of coupled systems; domain decomposition and mesh partitioning strategies; data representation in object-oriented form and mapping to hardware driven representation, and tradeoff studies between partitioning schemes and fully coupled treatment.

Felippa, C. A.↗

ExaHDF5: Delivering Efficient Parallel I/O on Exascale Computing Systems

Scientific applications at exascale generate and analyze massive amounts of data. A critical requirement of these applications is the capability to access and manage this data efficiently on exascale systems. As such, parallel I/O, the key technology enables moving data between compute nodes and storage, faces monumental challenges from new applications, memory, and storage architectures considered in the designs of exascale systems. As the storage hierarchy is expanding to include node-local persistent memory, burst buffers, etc., as well as disk-based storage, data movement among these layers must be efficient. Parallel I/O libraries of the future should be capable of handling file sizes of many terabytes and beyond. In this paper, we describe new capabilities we have developed in Hierarchical Data Format version 5 (HDF5), the most popular parallel I/O library for scientific applications. HDF5 is one of the most used libraries at the leadership computing facilities for performing parallel I/O on existing HPC systems. The state-of-the-art features we describe include: Virtual Object Layer (VOL), Data Elevator, asynchronous I/O, full-featured single-writer and multiple-reader (Full SWMR), and parallel querying. In this paper, we introduce these features, their implementations, and the performance and feature benefits to applications and other libraries.

97 MATHEMATICS AND COMPUTING↗

A Comparison of Automatic Parallelization Tools/Compilers on the SGI Origin 2000 Using the NAS Benchmarks

Porting applications to new high performance parallel and distributed computing platforms is a challenging task. Since writing parallel code by hand is extremely time consuming and costly, porting codes would ideally be automated by using some parallelization tools and compilers. In this paper, we compare the performance of the hand written NAB Parallel Benchmarks against three parallel versions generated with the help of tools and compilers: 1) CAPTools: an interactive computer aided parallelization too] that generates message passing code, 2) the Portland Group's HPF compiler and 3) using compiler directives with the native FORTAN77 compiler on the SGI Origin2000.

Saini, Subhash↗

Massively Parallel Bayesian Model Calibration and Uncertainty Quantification with Applications to Nuclear Fuels and Materials

The U.S. Department of Energy (DOE)’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel cycle systems. This program has been providing engineering-scale support for the development of BISON, a high-fidelity and high-resolution fuel performance tool. Fuel behavior in a nuclear reactor is governed by a complex network of mechanisms interacting with various other physics aspects in the reactor system. Any model developed to represent the fuel behavior will likely be idealized resulting in uncertainties in their predictions compared to the observed data. As such, this report was motivated by the need to identify the sources of uncertainties and quantify and propagate them through the fuel model outputs. Such quantification of uncertainties will establish a level of model trustworthiness, identify approaches to improve the model trustworthiness, and even guide optimal experiment design for maximal information gain. To accomplish the uncertainty quantification for computational models, this report has relied on the Bayesian framework which provides probabilistic treatment of models their inputs and outputs. The current state-of-the-art on performing Bayesian Uncertainty Quantification (UQ) for nuclear engineering models using High Performance Computing (HPC) resources have been reviewed. Implementation of capabilities for massively parallel Bayesian UQ in Multiphysics Object-Oriented Simulation Environment (MOOSE) is discussed. Several verification cases are discussed to verify the accuracy of the quantified uncertainties using the developed computational capabilities in MOOSE. Then, the problem of quantifying the uncertainties in TRI-Structural isOtropic (TRISO) fuel silver release is addressed. For the first time, the uncertainties arising from the TRISO Fission Gas Release (FGR) model due to model inadequacy and experimental noise are quantified. Also, the Bayesian capabilities are applied to the calibration of the MATPRO creep model, a widely used model in several fuel assessment cases. The impact of the prediction uncertainties in the MATPRO model on the fuel cladding behavior as part of the TRIBULATION assessment case (which is an integral effects case) is investigated. This report concludes with a discussion on the future work for the UQ for computational models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Compact 50kW High Power Density, Hybrid 3-Level Paralleled T-type Inverter for More Electric Aircraft Applications

The demand for high performing, lightweight, reliable inverters, increased the scope of wide bandgap and high-switching frequency based solutions. To achieve such high efficiency inverters, it is vital to focus on the system level design considerations to maximize the benefits of these advanced technologies. This paper presents an improved design based on considerations to further reap the benefits of choosing the right inverter topology; increased capabilities through paralleling devices, with reduced total number of switches; and designing a planarized inverter with PCB based busbar. Appropriate thermal analysis and heatsink design has aided in increased system power density along with the overall efficiency. Demonstration of a 50kW 3-phase 3-level paralleled T-type SiC inverter operating at 40kHz switching frequency for aircraft applications is shown to evaluate the benefits of proposed design methodology. Here, the prototype achieves a high power density of 11kW/L.

42 ENGINEERING↗

Improving Resource Selection and Scheduling Using Predictions

The introduction of computational grids has resulted in several new problems in the area of scheduling that can be addressed using predictions. The first problem is selecting where to run an application on the many resources available in a grid. Our approach to help address this problem is to provide predictions of when an application would start to execute if submitted to specific scheduled computer systems. The second problem is gaining simultaneous access to multiple computer systems so that distributed applications can be executed. We help address this problem by investigating how to support advance reservations in local scheduling systems. Our approaches to both of these problems are based on predictions for the execution time of applications on space- shared parallel computers. As a side effect of this work, we also discuss how predictions of application run times can be used to improve scheduling performance.

Smith, Warren↗

Development and applications of supersonic unsteady consistent aerodynamics for interfering parallel wings: User's manual

The input data required to execute the computer program AIC/INT (aerodynamic influence coefficients with interference) are presented. The purpose of the computer program is to generate aerodynamic forces for a pair of plane and interfering nearly parallel, non-coplanar wings at supersonic Mach numbers. A finite element technique has been employed. Planforms are described by triangular elements and diaphragm regions are generated automatically.

Paine, A. A.↗