SEARCH · Search NASA

Results for “MPI”

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.

SourceResearch connectionFrom yearThrough year

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

At least 307 records · Page 17

All sources NASA NTRS DOE OSTI

NASA NTRS2018

A Single Thread to Fortran Coarray Transition Process for the Control Algorithm in the Space Radiation Code HZETRN

Exa-scale computing is the direction by industry and government are going to generate solutions to problems they deem necessary. Computing hardware is being developed to achieve the transition from Peta-scale to Exa-scale with more CPUs (Central Processing Units) that have more cores per CPU and more accelerators (GPGPUs (General Purpose Graphics Processing Units) and MICs (Many Integrated Cores)) per node. To fully utilize the hardware available now and in the future, algorithms must become multi-threaded. There are a few methods to generate multi-threaded software such as MPI (Message Passing Interface) and OpenMP (Multi-Processing) / OpenACC (ACCelerator). This paper concentrates on using Coarray Fortran to convert the Fortran 95 based HZETRN (High Z and Energy TRaNsport) code's control algorithm from a single threaded code to a multithreaded code. The resultant Coarray code was 32.5 times faster (with a theoretical speed-up of 74.5 times) than the single threaded version on the hardware tested, as reliable as the Fortran 95 version, and, as it uses native Fortran, was as maintainable as the Fortran 95 version. The Coarray code can be maintained by the same project engineers and scientists who created the original single threaded code. This transition process can be utilized on a C language based code with a compiler that has the UPC (Universal Parallel C) extensions to C.

Singleterry, Robert C., Jr.↗

NASA NTRS2018

An Innovative Control Allocation Scheme to Address Reaction Thruster Interactions on a 3U CubeSat

A wealth of literature exists on control allocation algorithms for over-actuated air vehicles, launch vehicles, and spacecraft's. Most of these algorithms focus primarily on minimizing some objective function such as command tracking error and/or control effector usage. Linear allocators (pseudo inverses) are usually the conventional choice due to their simplicity and the ability to achieve a significant portion of the theoretical moment/impulse space. Generally, it is assumed that there exists minimal interaction effects between control effectors. In fact, very few studies address the problem of control effector interactions in the context of control allocation, especially for small spacecraft's with a reaction control system (RCS). This paper presents a CubeSat RCS design with a four thruster tetrahedral layout such that when two or more thrusters re, the resultant impulse differs noticeably compared to the sum of the contributions from individual thruster rings. This undesirable effect is caused by the design of the propellant tank and regulator. To mitigate this issue, an innovative modified pseudo inverse (MPI) control allocation algorithm was developed that adjusts the pseudo inverse solution based on test data. The algorithm is iteration-free and superior to the standard pseudo inverse in minimizing the command tracking error.

Pei, Jing↗

NASA NTRS2019

Testing Scientific Software: Challenges and Remedies

Over the past two decades, the emergence of highly effective software testing frameworks has greatly simplified the development and use of unit tests and has led to new software development paradigms such as test driven development (TDD). However, scientific computing introduces a number of unique testing challenges, including numerical algorithms, distributed parallelism, and exascale environments. This presentation will begin with a brief introduction to unit testing, testing frameworks, and some simple examples using pFUnit, a unit testing framework for Fortran + MPI. I will then take a closer look at several of the obstacles one faces when testing technical software and suggest methodologies that can mitigate these difficulties.

Clune, Tom↗

NASA NTRS2018

Optimization of Elastodynamic Finite Integration Technique on Intel Xeon Phi Knights Landing Processors

This work describes the development and optimization of an implementation of an isotropic elastodynamic finite integration technique (EFIT) code for parallelized computation on Intel Knights Landing (KNL) hardware. EFIT is a numerical approach resulting in standard staggered-grid finite difference equations for the elastodynamic equations of motion to simulate bulk waves is solids. The computationally efficient simulation of elastodynamic wave propagation and interactions in aerospace materials is of high-interest in the fields of nondestructive evaluation (NDE) and structural health monitoring (SHM). Ultrasonic inspection uses an ultrasonic signal, generated at the surface of the material/structure via use of a piezoelectric transducer, to propagate sound waves into the material where it interacts with any existing defects, as well as with structural boundaries and any material inhomogeneity. Reflections from defects and boundaries are then measured by a transducer. Realistic ultrasound simulation tools can significantly aid the development and optimization of inspection techniques and can assist in the interpretation of experimental data. The optimization of an elastodynamics simulation code for the KNL Many Integrated Core processor was performed. The optimization focused on data locality and vectorization. Results show that tiling of the data to exploit the cache behavior and allow for significant utilization of the KNL hardware. The MPI implementation allows for a scalable implementation enabling large problems to be simulated. The model results were validated against theoretical dispersion curves to within 2% of the group velocity, and within 0.5% of the phase velocity of the A0 mode. Aggressive use of tiling, threading, and vectorization techniques allowed for dramatically improved time to solution.

William C. Schneck↗

NASA NTRS2019

High-Performance Computing Optimization for Aladyn – Adaptive Neural Network Molecular Dynamics Mini-Application

This report provides a description and performance evaluation of the optimization techniques for high performance computing (HPC) implementation of the open source Computational Materials mini-application Aladyn (https://github.com/nasa/aladyn). Aladyn is a basic molecular dynamics code written in FORTRAN 2003, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. While achieving orders of magnitude faster computational performance than DFT, the ANN-based approach was still very computationally demanding compared to the conventional approach of using empirically fitted energy functions. After its initial development, Aladyn was evaluated and optimized by experts at the NASA Advanced Supercomputing (NAS) division to exploit modern supercomputer architectures. The code has been optimized for execution on multicore central processing units (CPUs), including Intel® Skylake microarchitecture, and on graphic accelerators, such as Nvidia® V100 graphic processing units (GPUs), using Open Multi-Processing (OpenMP) and Open Accelerators (OpenACC) programming interfaces. The optimization achieved a speedup of 4.7 times the baseline version on CPU performance and an additional 2.4 times on CPU+GPU performance. Atomistic computer simulations are a fundamental tool in materials research to model material properties form physics-based first principles. Atomic interaction, governed by Quantum Mechanics (QM) require sophisticated and highly computationally demanding mathematical models to calculate [1]. Classical methods use approximate functional forms, empirically fitted through a set of variable parameters to emulate atomic energies as direct functions of atomic coordinates [2]. While empirical potentials are computationally much simpler, allowing simulations of large-scale systems of up to a trillion (1012) atoms [3], they are substantially less accurate compared to quantum calculations and applicable only to very specific atomic configurations or predefined crystallographic phases. A recently suggested approach is to use heuristic machine learning methods [4], such as those based on Adaptive Neural Networks (ANNs) to predict atomic energies, after being trained on a sufficiently large database of QM-calculated structures [5,6]. This approach reduces significantly the computational complexity, allowing for simulations of orders of magnitude larger systems compared to QM-based methods without compromising accuracy. Still, compared to classical methods using empirical energy functions, ANN methods remain two- to three orders of magnitude more computationally demanding. Hence, the computational cost of simulations, together with the need for extensive training of ANNs, still makes the practical implementation of ANN-based methods quite challenging. The purpose of the Aladyn mini-application software [7], available as open source at https://github.com/nasa/aladyn, is to be a testbed for exploring possible optimization strategies to develop highly scalable parallel algorithms for ANN-based atomistic simulations. Aladyn is aimed at utilizing the architecture of the high-end modern highperformance computing (HPC) hardware based on multicore central processing units (CPUs) equipped with graphic processing unit (GPU) accelerators. Specifically, the goal is to optimize the performance on a single HPC compute node, before implementing scaling to multi-node parallelization using message passing interface (MPI). At the same time, the open source code of Aladyn can serve as a training model for students and professors in academia.

Yamakov, Vesselin I.↗

NASA NTRS2019

Using Big Data Technologies with Earth Science Data in HDF5: HDF5 Scalable Solutions

HDF5 (Hierarchical Data Format 5) is open-source, high-performance software that consists of an abstract data model, library, and fileformat used for storing and managing extremely large and/or complex data collections. NASA Earth Observing System (EOS) Data and Information Systems use HDF5 as an archival format to store remote sensing data from EOS satellites. HDF5 is also used to store other types of Geoscience and Strophysical data, e.g., seismic data and data from Low-Frequency Array (LOFAR) radio telescopes. Data stored in HDF5 has reached tens of petabytes and is growing at an accelerated rate.With the growing amout of HDF5 Earth Science data to analyze and process, scientists need to adopt big data technologies including new storage paradigms such as cloud and object storage. To run models and perform data analysis they also need to utilizied efficient and diverse ways to access data, from high-performance computing's (HPC) Message Passing Interface (MPI) I/O and deep memory hierarchies (DMH) to non-HPC frameworks such as Apache Hadoop, Spark, and Drill. The HDF Group continually works to enable usage of big data technologies in HDF software.

Knox, Larry↗

NASA NTRS2020

LAURA Users Manual: 5.6

This users manual provides in-depth information concerning installation and execution of Laura, version 5. Laura is a structured, multiblock, computational aerothermodynamic simulation code. Version 5 represents a major refactoring of the original Fortran 77 Laura code toward a modular structure afforded by Fortran 95. The refactoring improved usability and maintainability by eliminating the requirement for problem-dependent recompilations, providing more intuitive distribution of functionality, and simplifying inter- faces required for multi-physics coupling. As a result, Laura now shares gas-physics modules, MPI modules, and other low-level modules with the Fun3D unstructured-grid code. In addition to internal refactoring, several new features and capabilities have been added, e.g., a GNU-standard installation process, parallel load balancing, automatic trajectory point sequencing, free-energy minimization, and coupled ablation and flow field radiation.

Aerodynamics↗

NASA NTRSDate not supplied

TPSAS-NF1676L-10767-DND

Version 2.1ae of the NASA CFD code OVERFLOW has been used to simulate the flow past tandem cylinders. The multiblock grid system consisted of 15 overset meshes with a total grid count of 15.7 million points. The grid extended 3 cylinder diameters in the spanwise direction with periodic boundary conditions at the ends. Riemann conditions were used at the outer boundaries, and a no-slip condition on the cylinder surfaces. The 3rd order HLLC upwind spatial discretization scheme was used with a dual-time stepping algorithm. A modified version of the Delayed Detached Eddy Simulation hybrid RANS/LES turbulence model proposed by Spalart was used in a fully turbulent mode. The code was run on 53 Core 2 Duo nodes using MPI across nodes and OPENMP within each node. Simulation results will be compared with the available experimental data.

David P. Lockard↗

NASA NTRSDate not supplied

Coupling a Particle Trajectory Capability to the US3D CFD Flow Solver

The purpose of the current research effort is to incorporate particle trajectory equations into the US3D CFD flow solver. The integrated code will allow higher-fidelity modeling of particle-fluid interactions and allow for the simulation of physical effects such as surface heating augmentation due to particle impacts. The key elements underpinning the current work are a robust tracking algorithm that can identify the encompassing mesh elements for individual particles and a point to point MPI frame-work. These developments combined with accurate property models and high-order time-stepping deliver realistic simulations on larger computational grids for a wide range of particle mass loadings. The coupled US3D-particle code will be applied to the Schiarparelli capsule and Earth-based experimental test cases.

A Sahai↗

NASA NTRSDate not supplied

Recent Improvements to the LAURA and HARA Codes

This paper describes recent improvements to the LAURA and HARA codes. LAURA is a CFD code for aerothermodynamics, and HARA evaluates the shock-layer radiation that provides the radiative source term for the flowfield energy equations and radiative heating to a surface. The next release of LAURA and HARA includes a variety of new capabilities. These new capabilities include an automated uncertainty quantification workflow for radiative heat transfer, options for specifying surface roughness and turbulent transition location in the algebraic turbulence models, and improved grid and solution interpolation techniques. Additionally, the computational efficiency of both LAURA and HARA have been improved. Optimization of the MPI communication routines in LAURA are shown to improve the parallel efficiency of the primary flow when running with multiple processes per block, and recent optimization of HARA leverage graphics processing unit (GPU) acceleration in the radiation calculations. Using GPU acceleration of HARA is shown to decrease the cost of the radiation line-of-sight calculation by approximately one order of magnitude for a 10.5 km/s Earth entry simulation.

LAURA HARA CFD 5.6↗

NASA NTRS1998

Use of the Microprecision Interferometer Testbed for Developing Control Technology for Spaceborne Optical Interferometer Missions

This paper describes the Micro-Precision Interferometer (MPI) testbed and its major achievements to date related to mitigating risk for future spaceborne optical interferometer missions.

testbed↗

NASA NTRSDate not supplied

Dust Particle Aeroheating Calculations for Mars Entry Hypersonic Flows

The purpose of the current research effort is to predict particle trajectories in a hypersonic flowfield while accounting for all relevant particle-fluid and particle-particle interactions. The resulting particle solver is titled DUst Simulation & Tracking (DUST) and works in conjunction with the US3D CFD flow solver. The key elements underpinning the current work are an efficient mesh-localiztion algorithm, time-driven hard-sphere model, point-to-point MPI framework, coarse-graining using computational parcels, and high-order Adams-Bashforth time stepping. The coupled US3D-DUST framework will be applied to conduct a multi-physics examination of dust-laden flows around the the Schiarparelli capsule.

Dusty Flows↗

NASA NTRSDate not supplied

Dust Particle Aeroheating Calculations for Mars Entry Hypersonic Flows

Dusty Flows↗

NASA NTRS2023

Effects of Forcing Differences and Initial Conditions on Inter-Model Agreement in the VolMIP Volc-Pinatubo-Full Experiment

This paper provides initial results from a multi-model ensemble analysis based on the volc-pinatubo-full experiment performed within the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP) as part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The volc-pinatubo-full experiment is based on an ensemble of volcanic forcing-only climate simulations with the same volcanic aerosol dataset across the participating models (the 1991–1993 Pinatubo period from the CMIP6-GloSSAC dataset). The simulations are conducted within an idealized experimental design where initial states are sampled consistently across models from the CMIP6-piControl simulation providing unperturbed preindustrial background conditions. The multi-model ensemble includes output from an initial set of six participating Earth system models (CanESM5, GISS-E2.1-G, IPSL-CM6A-LR, MIROC-E2SL, MPI-ESM1.2-LR and UKESM1). The results show overall good agreement between the different models on the global and hemispheric scales concerning the surface climate responses, thus demonstrating the overall effectiveness of VolMIP's experimental design. However, small yet significant inter-model discrepancies are found in radiative fluxes, especially in the tropics, that preliminary analyses link with minor differences in forcing implementation; model physics, notably aerosol–radiation interactions; the simulation and sampling of El Niño–Southern Oscillation (ENSO); and, possibly, the simulation of climate feedbacks operating in the tropics. We discuss the volc-pinatubo-full protocol and highlight the advantages of volcanic forcing experiments defined within a carefully designed protocol with respect to emerging modelling approaches based on large ensemble transient simulations. We identify how the VolMIP strategy could be improved in future phases of the initiative to ensure a cleaner sampling protocol with greater focus on the evolving state of ENSO in the pre-eruption period.

metadata↗

NASA NTRSDate not supplied

Adding GPU Support to the Markov Chain Monte Carlo Code Catmip

In geophysics, we are confronted with many under-determined inverse problems. For example, all of our observations of earthquakes are made at the Earth’s surface. So, when we try to infer how slip during an earthquake evolves in space and time, we find that there are many potential slip histories that are consistent with our limited observations and our understanding of earthquake physics. One way to approach these problems is with Bayesian analysis which allows us to infer the ensemble of all potential slip models that satisfy the observations and our prior knowledge of earthquake physics. In Bayesian analysis, our prior knowledge is known as the prior probability density function or prior PDF, the fit to the data is known as the data likelihood, and the target PDF that satisfies both the prior PDF and data likelihood is known as the posterior PDF. However, simulating the posterior PDF typically requires using Markov Chain Monte Carlo (MCMC) to draw tens of billions of random realizations of earthquake slip models, which may not be computationally feasible. To make this and similar geophysical inversions computationally tractable, we developed the Cascading Adaptive Transitional Metropolis In Parallel (CATMIP) algorithm. CATMIP is an efficient parallel Markov Chain Monte Carlo (MCMC) sampler that is used for model fitting and uncertainty quantification in geophysics. Example use cases are earthquake rupture modeling, determining mineral composition on Mars, reconstructing the history of ocean salinity, and historical earthquake relocation. CATMIP employs many parallel instances of the Metropolis algorithm for sampling in a transitioning framework. Transitioning is a process in which a set of random samples at equilibrium with a known probability density function (PDF) are used as seeds for the Markov chains to sample successive target PDFs that incrementally move the distribution from the starting seeds to the final desired PDF that describes the relative plausibility of potential values for the model parameters. The algorithm is implemented as a Master-Worker model employing MPI for communication. The worker processes are loosely coupled with global parameters periodically optimized by the master process. This provides a very high amount of parallelism with little communication between updates. During the presentation we will discuss the history of the algorithm and elaborate the earthquake rupture modeling use case for the CATMIP package. Our first step toward GPU optimization was to optimize the code for the CPU. CPU profiling revealed that most of the compute time is spent in calls to level 2 BLAS routines and calls to GSL random number generators. We revised the algorithm to employ level 3 BLAS routines instead. In our presentation we will describe how this was accomplished. Adding GPU support to CATMIP consisted mostly of replacing the calls to GSL with calls to GPU vendor-provided library routines. A small number of loops were directly implemented in CUDA. In the presentation will provide implementation details. Finally, we will discuss methods for profiling and opportunities for further optimizing GPU execution. By creating a code with the flexibility to run on either a CPU or GPU architecture, CATMIP can be used on systems ranging from large CPU-based HPC environments to single servers with GPU acceleration and everything in between.

HECC↗

NASA NTRS2022

VULCAN-CFD User Manual: Ver. 7.2.0

VULCAN-CFD offers a comprehensive set of capabilities to enable the simulation of continuum flowfields from subsonic to hypersonic conditions. The governing equations that are employed include allowances for both chemical and thermal nonequilibrium processes, coupled with a wide variety of turbulence models for both Reynolds-averaged and large eddy simulations. The software package can simulate two-dimensional, axisymmetric, or three-dimensional problems on structured multiblock meshes or fully unstructured meshes. A parabolic (i.e., space-marching) treatment can also be used for any subset of a structured mesh that can accommodate this solution strategy. The flow solver provides a significant level of geometric flexibility for structured grid simulations by allowing for arbitrary face-to-face C(0) continuous and non-C(0) continuous block interface connectivities. The unstructured grid paradigm allows for mixed element unstructured meshes that contain any combination of tetrahedral, prismatic, pyramidal, and hexahedral cell elements. The flow solver is also fully parallelized using MPI (Message Passing Interface) libraries in a data-parallel fashion, allowing for efficient simulations on modern High Performance Computing (HPC) systems. This document provides information related to the installation and execution of the VULCAN-CFD software package. A detailed description of the physical and numerical models available in the software are provided in the VULCAN-CFD Theory Manual.

VULCAN-CFD User Manual↗

NASA NTRSDate not supplied

New Features of the NEQAIR Radiation Code

The longest-lived code for predicting shock layer radiation, NEQAIR, is now in its 5th decade of service. Substantial changes to the code have been made over the previous decade, the most recent report of which was at the 5th Workshop on Radiation in High Temperature Gases in 2014, for the version referred to as NEQAIR14. This paper will review some of the improvements made to the NEQAIR code since then, which is now at v15.2. Some of these features are discussed briefly below. NEQAIR15 and subsequent versions have enabled parallel evaluation of multiple lines of sight. This is accomplished by utilizing the HDF5 file format and placing multiple lines into a single file, LOS.h5, which is used for both input and output. This approach enables straightforward parallel execution both over the number of lines of sight and the number of points per line. For large problems, runtime reduces linearly with the number of nodes deployed since each line is processed independently by a subset of MPI ranks. Three applications of the multi-line solver are discussed. The first has to do with performing loosely coupled radiation-flowfield solutions. In this case the computed absorption and emission coefficients are used to evaluate the total energy absorbed or emitted at each point, allowing evaluation of the volumetric source term in the flowfield. The second computation is for obtaining heat flux from nonuniform flows, which require integration over spherical co-ordinates. These are of particular interest for evaluating radiation on the vehicle backshell. This 3D option improves the angular integration scheme and allows adaptive line selection that together reduce the number of lines required by about an order of magnitude. The final application is for remote observation, which is essentially the 3D integration problem over a small solid angle. For all three of these computations, data can be stored in the HDF5 file which allows a NEQAIR run to be restarted when it times out, or to add atmospheric absorption or instrument scan functions. An additional level of parallelism is enabled in NEQAIR15.2 using GPU routines. The GPU parallelism has realized up to 8x speed-up when running on a single core but diminishes as CPU parallelism is increased. For running multi-line simulations, it may be easier to reserve a large number of CPU nodes than to obtain the number of GPU nodes required for similar performance. A GUI, known as NEQTPY, allows for reading and creating input files, running NEQAIR, and displaying results. A significant feature of NEQTPY is the ability to perform spectral fits to data. The fits can operate on a single line spectrum (radiance vs. wavelength) or a 3D input file with multiple columns of data. Other new features include improved constants, additional species, more detailed non-Boltzmann modelling, advanced user controls, the ability to read and calculate spectra from HITRAN datafiles, photodissociation and photoionization cross-sections. A “fast” automatic grid option may reduce the size and time of spectral calculations while still maintaining good accuracy for total heat flux.

Brett A Cruden↗

NASA NTRS2023

Framework for Extensible, Asynchronous Task Scheduling (FEATS) in Fortran

Most parallel scientific programs contain compiler directives (pragmas) such as those from OpenMP, explicit calls to runtime library procedures such as those implementing the Message Passing Interface (MPI), or compiler-specific language extensions such as those provided by CUDA. By contrast, the recent Fortran standards empower developers to express parallel algorithms without directly referencing lower-level parallel programming models. Fortran’s parallel features place the language within the Partitioned Global Address Space (PGAS) class of programming models. When writing programs that exploit data-parallelism, application developers often find it straightforward to develop custom parallel algorithms. Problems involving complex, heterogeneous, staged calculations, however, pose much greater challenges. Such applications require careful coordination of tasks in a manner that respects dependencies prescribed by a directed acyclic graph. When rolling one’s own solution proves difficult, extending a customizable framework becomes attractive. The paper presents the design, implementation, and use of the Framework for Extensible Asynchronous Task Scheduling (FEATS), which we believe to be the first task-scheduling tool written in modern Fortran. We describe the benefits and compromises associated with choosing Fortran as the implementation language, and we propose ways in which future Fortran standards can best support the use case in this paper.

Modern Fortran↗