Search NASA⌕ Search

SEARCH · Search NASA

Results for “parallel, scaling”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A GPU-Accelerated Population Generation, Sorting, and Mutation Kernel for an Optimization-Based Causal Inference Model

We develop a GPU-accelerated machine learning generative adversarial network model that can be used with observational data for the purpose of constructing causal inferences. The theoretical basis of our machine learning model is novel and is conceptualized to be operable and scalable for high performance computing platforms. Our GPU-accelerated code enables large-scale parallelization of the computation within a common and accessible computing environment. This will expand the reach of our model and empower research in new substantive domains while maintaining the underlying theoretical properties.

Cho, Wendy K. Tam↗
DOE OSTI2024

Spinbox: tools for many-body quantum systems in a Monte Carlo context

Spinbox is a piece of software that facilitates quantum mechanical calculations relevant to Monte Carlo simulation of atomic nuclei. At the front lines of research on the nuclear many-body problem are a large number of supercomputer-scale simulation codes. These codes produce valuable results but can be hard to understand, especially for those without intimate knowledge of the relevant theoretical methods. Thus, tools that fill pedagogical roles are extremely valuable. Spinbox makes it easy for one to replicate and analyze the computational processes relevant to a Quantum Monte Carlo (QMC) simulation that may be difficult to understand/debug/analyze due to the scale of the corresponding simulation software. Spinbox is written in Python using other state-of-the-art Python modules for numerical calculations. While a number of Python libraries exist that are suited to general quantum many-body calculations, the motivation of Spinbox is quite particular. In Diffusion Monte Carlo methods (DMC, GFMC, AFDMC), the central calculation is the imaginary-time propagation of individual samples of the many-body wavefunction. Although quantum wavefunctions generally must be described by a probability distribution over a basis, DMC imbues particles (within one sample) with classical spatial coordinates. This method is unusual, so other Python packages are typically not set up to do this easily. Furthermore, the software has built-in options for nuclear systems assuming isospin symmetry, which can be set up with other libraries but is a nontrivial process to do so. Features: - numerical representation of samples of the many-body wavefunctions, including tensor-product states (used in AFDMC) - numerical representation of many-body operators, including tensor-product operators: general, spin, imaginary-time propagation, etc. - the correct associated arithmetic and algebra, implemented as class methods - classes for representing realistic nuclear two- and three-body Hamiltonians (e.g. Argonne V18, Illinois NNN) - large-scale parallel integration over random variables, crucial for the AFDMC method My goal is to make this package open source so that anyone may use it and contribute to it, particularly other researchers doing AFDMC calculations

Fox, Jordan↗
DOE OSTI2026

REDI – Readiness Engine for Data Integration

The Readiness Engine for Data Integration (REDI) is an open-source framework for automating, standardizing, and assessing the process of preparing scientific data for AI training. REDI implements a five-stage pipeline (ingest, preprocess, transform, structure, output) with per-stage provenance instrumentation via Flowcept, domain-aware transformation logic (PII anonymization, regridding, graph encoding, and more), and built-in readiness assessment and validation modes. REDI has been evaluated across climate, proteomics, materials science, and nuclear fusion datasets, demonstrating near-ideal parallel scaling to 100 nodes on OLCF's Frontier system. REDI is deployable as an agent-callable skill in coding environments such as Claude Code and OpenAI Codex, and is complemented by SetGo for FAIR compliance and catalog publication.

Brewer, Wesley [Oak Ridge National Laboratory (ORN↗
DOE OSTI2025

2D reactive transport model of shale chemical weathering and biogeochemical fluxes along a mountainous hillslope, East River Watershed, Colorado: Input files and simulation results

This data package contains input files and simulation results for a two-dimensional (2D) reactive transport model used to quantitatively analyze the coupled hydrological and biogeochemical processes governing shale weathering and associated biogeochemical fluxes under realistic environmental conditions in the high-elevation East River Watershed. These data support the conclusions presented in Stolze et al. (Water Resources Research, under review), "Model-based interpretation of solute exports and carbon partitioning during shale weathering in a mountainous hillslope". The model simulates atmospheric-subsurface gas exchange, subsurface water flow, and shale weathering processes under dynamic, year-scale conditions along a shale-underlain hillslope located in the East River watershed. The simulations were performed using the PFLOTRAN flow and reactive transport code and executed on the Perlmutter supercomputer to leverage its large-scale parallel computing capabilities. The data package contains two zipped folders, "model_input_files" and "simulation_results", and one readme.txt file. "model_input_files" contains the necessary input files to run the calibrated base-base model presented in Stolze et al. (Water Resources Research, under review). "simulation_results" contains a single hdf5 file ("Output_2D_hillslope_model.h5") which includes the results of simulation performed using the base-case model. This file can be opened with HDFView 3.1.4, Python, or MATLAB. "readme.txt" contains relevant information about the base-case model and provides guidelines on how to run the associated input files provided in the folder "model_input_files". Furthermore, readme.txt provides information regarding the model results provided in "Output_2D_hillslope_model.h5" such as matrix dimensionality and output units. Field datasets used to evaluate model performance were collected at three monitoring wells located along a hillslope transect (PLM1, PLM2, and PLM3). Dissolved ion concentration data were collected from November 2016 to October 2021 for Ca, Mg, DIC, Na, K, SO4 (Dong et al., 2025 - dic_npoc_data_2014_2024.zip - DOI:10.15485/1660459; Williams et al., 2025 - anion_data_2014_2024.zip - DOI:10.15485/1668054; Dong et al., 2025 - cation_data_2014_2024.zip - DOI:10.15485/1668055). Note that we used the files named er_PLM1_xx_yy, er_PLM2_xx_yy, and er_PLM3_xx_yy where xx stands for the name of the aqueous species and yy stands for the depth where the measurements were performed. Soil water content ([0 - 1] m) and water table depth were collected from November 2016 to October 2021 (Wan et al., 2024 - Dynamic_water_table__depthsFig2b.csv and Soil_water_content_Fig4e.csv - DOI:10.15485/2322567). Gaseous CO2 concentration were collected from October 2020 to December 2021(Wan et al., 2024 - Soil_CO2_concentrations_Fig4h.csv - DOI:10.15485/2322567) Gaseous CO2 flux from the subsurface to the atmosphere were collected in the vicinity of PLM2 from October 2019 to May 2022 (Wu et al., 2025). Soil microbial biomass concentration was measured from August 2016 to June 2017 (Sorensen et al., 2019 - 2017_East_River_Pumphouse_Microbial_Biomass__1_.csv - DOI:10.15485/1577267) All field data are published as CSV files compatible with Microsoft Excel, MATLAB, and Python, or as text files. The coordinates of the monitoring wells and the CO2(g) flux sensor in the coordinate system WGS84 are: -PLM1: [38.9197710 ; -106.9492750] -PLM2: [38.9201580 ; -106.9487170] -PLM3: [38.9207843 ; -106.9483668] -PLM4: 38.9210060 ; -106.9479528] -CO2(g) flux sensor: [38.9199180 ; -106.9489906] ------------------------------------------------------------------------------------------- This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a Department of Energy User Facility using NERSC award BER-ERCAP 23980, BER-ERCAP 28550, and BER-ERCAP 33789.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Simulating microgalvanic corrosion in alloys using the PRISMS phase-field framework

In this prospective paper, we first review the existing simulation tools to simulate microgalvanic corrosion during free immersion. Then, we describe a recently developed application that employs PRISMS-PF, an open-source, high-performance phase-field modeling framework. The model employed in the application accounts for the electrochemical reaction at the metal/electrolyte interface and ionic migration in the electrolyte to determine the evolution of the corrosion front. We present the implementation details for the application and discuss its features such as super-linear parallel scaling performance for a sufficiently large system. Finally, we demonstrate the capability of the application by simulating corrosion of the matrix phase of an alloy near a secondary phase particle in two and three dimensions.

36 MATERIALS SCIENCE↗
DOE OSTI2017

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↗
DOE OSTI2018

Project Final Report: The Institute for Sustained Performance, Energy, and Resilience (SUPER)

This project concentrated on various aspects of creating and applying tool infrastructure to make it easier to effectively use large-scale parallel computers. This project was collaborative with Argonne National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Livermore National Laboratory, Oak Ridge National Laboratory, U.C. San Diego, University of Maryland, University of North Carolina, University of Oregon, University Southern California, University of Tennessee, and University of Utah. The research conducted during this project at the University of Maryland is summarized in this report. The complete details of the work are available in the publications listed at the end of the report. Many of the concepts created during this project have been incorporated into tools and made available as freely downloadable software (www.dyninst.org/harmony). It also supported the studies of six graduate students, one undergraduate student, and two post-docs. The funding also provided summer support for the PI and part of the salary of a research staff member.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

PIPER: Performance Insight for Programmers and Exascale Runtimes (Final Technical Report)

This project concentrated on the development of novel performance tools and analysis techniques for large scale parallel systems and applications, eventually targeting exascale platforms. Activities conducted included work to novel root cause detection approaches and an auto-tuning framework for parallel systems. The work has led to several software solutions, which are available as open source.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1972

Application of an onboard processor to the OAO C spacecraft

The design of a stored program computer for spacecraft use and its application on the fourth Orbiting Astronomical Observatory (OAO) is reported. The computer is a medium scale, parallel machine with a memory capacity of 16384 words of 18 bits each. It possesses a comprehensive instruction repertoire and operates on 45 W of power (including the dc-to-dc converter). The machine operates at a 500-kHz rate and executes an add instruction in 10 microseconds. Its primary functions on OAO C will be auxiliary command storage, spacecraft monitoring and malfunction reporting, data compression and status summary, and possible performance of emergency corrective action for certain anomalous situations.

Stewart, W. N.↗
NASA NTRS1989

Oxygen acoustic solitary waves in a magnetized plasma

Ion-acoustic solitary waves in a magnetized plasma containing an arbitrary mixture of H(+) and O(+) ions are studied. A nonlinear wave equation has been derived from the Poisson-Vlasov equations, including a uniform magnetic field and dissipation due to reflected electrons. When dissipation is ignored, the equation has soliton solutions associated with both oxygen and hydrogen acoustic modes, which can be either rarefactive or compressive depending on the ion concentrations and the electron/ion temperature ratio and, more weakly, on the bulk drifts of the species. If electron reflection is included, the solitary wave can be intensified. Under somewhat restrictive conditions the oxygen solitary wave is rarefactive and propagates with a velocity comparable to that observed by the Viking satellite. The three-dimensional solitons obey a relation of scales parallel to the magnetic field and in the transverse direction. Computer simulations of one-dimensional versions of the nonlinear wave equation are presented.

Qian, S.↗
NASA NTRS1991

Hyperswitch communication network

The Hyperswitch Communication Network (HCN) is a large scale parallel computer prototype being developed at JPL. Commercial versions of the HCN computer are planned. The HCN computer being designed is a message passing multiple instruction multiple data (MIMD) computer, and offers many advantages in price-performance ratio, reliability and availability, and manufacturing over traditional uniprocessors and bus based multiprocessors. The design of the HCN operating system is a uniquely flexible environment that combines both parallel processing and distributed processing. This programming paradigm can achieve a balance among the following competing factors: performance in processing and communications, user friendliness, and fault tolerance. The prototype is being designed to accommodate a maximum of 64 state of the art microprocessors. The HCN is classified as a distributed supercomputer. The HCN system is described, and the performance/cost analysis and other competing factors within the system design are reviewed.

Peterson, J.↗
NASA NTRS1994

Building brains for bodies

We describe a project to capitalize on newly available levels of computational resources in order to understand human cognition. We will build an integrated physical system including vision, sound input and output, and dextrous manipulation, all controlled by a continuously operating large scale parallel MIMD computer. The resulting system will learn to 'think' by building on its bodily experiences to accomplish progressively more abstract tasks. Past experience suggests that in attempting to build such an integrated system we will have to fundamentally change the way artificial intelligence, cognitive science, linguistics, and philosophy think about the organization of intelligence. We expect to be able to better reconcile the theories that will be developed with current work in neuroscience.

Brooks, Rodney Allen↗
NASA NTRS1999

Dynamic Load Balancing for Adaptive Computations on Distributed-Memory Machines

Dynamic load balancing is central to adaptive mesh-based computations on large-scale parallel computers. The principal investigator has investigated various issues on the dynamic load balancing problem under NASA JOVE and JAG rants. The major accomplishments of the project are two graph partitioning algorithms and a load balancing framework. The S-HARP dynamic graph partitioner is known to be the fastest among the known dynamic graph partitioners to date. It can partition a graph of over 100,000 vertices in 0.25 seconds on a 64- processor Cray T3E distributed-memory multiprocessor while maintaining the scalability of over 16-fold speedup. Other known and widely used dynamic graph partitioners take over a second or two while giving low scalability of a few fold speedup on 64 processors. These results have been published in journals and peer-reviewed flagship conferences.

Source record↗
NASA NTRS2001

NASA Exhibits

A series of NASA presentations for the Supercomputing 2001 conference are summarized. The topics include: (1) Mars Surveyor Landing Sites "Collaboratory"; (2) Parallel and Distributed CFD for Unsteady Flows with Moving Overset Grids; (3) IP Multicast for Seamless Support of Remote Science; (4) Consolidated Supercomputing Management Office; (5) Growler: A Component-Based Framework for Distributed/Collaborative Scientific Visualization and Computational Steering; (6) Data Mining on the Information Power Grid (IPG); (7) Debugging on the IPG; (8) Debakey Heart Assist Device: (9) Unsteady Turbopump for Reusable Launch Vehicle; (10) Exploratory Computing Environments Component Framework; (11) OVERSET Computational Fluid Dynamics Tools; (12) Control and Observation in Distributed Environments; (13) Multi-Level Parallelism Scaling on NASA's Origin 1024 CPU System; (14) Computing, Information, & Communications Technology; (15) NAS Grid Benchmarks; (16) IPG: A Large-Scale Distributed Computing and Data Management System; and (17) ILab: Parameter Study Creation and Submission on the IPG.

Deardorff, Glenn↗
NASA NTRS2014

Traffic Flow Management and Optimization

This talk will present an overview of Traffic Flow Management (TFM) research at NASA Ames Research Center. Dr. Rios will focus on his work developing a large-scale, parallel approach to solving traffic flow management problems in the national airspace. In support of this talk, Dr. Rios will provide some background on operational aspects of TFM as well a discussion of some of the tools needed to perform such work including a high-fidelity airspace simulator. Current, on-going research related to TFM data services in the national airspace system and general aviation will also be presented.

linear programming↗
NASA NTRS2016

The Space-Time Conservative Schemes for Large-Scale, Time-Accurate Flow Simulations with Tetrahedral Meshes

Despite decades of development of unstructured mesh methods, high-fidelity time-accurate simulations are still predominantly carried out on structured, or unstructured hexahedral meshes by using high-order finite-difference, weighted essentially non-oscillatory (WENO), or hybrid schemes formed by their combinations. In this work, the space-time conservation element solution element (CESE) method is used to simulate several flow problems including supersonic jet/shock interaction and its impact on launch vehicle acoustics, and direct numerical simulations of turbulent flows using tetrahedral meshes. This paper provides a status report for the continuing development of the space-time conservation element solution element (CESE) numerical and software framework under the Revolutionary Computational Aerosciences (RCA) project. Solution accuracy and large-scale parallel performance of the numerical framework is assessed with the goal of providing a viable paradigm for future high-fidelity flow physics simulations.

Venkatachari, Balaji Shankar↗
NASA NTRS2016

Overview of the NASA Glenn Flux Reconstruction Based High-Order Unstructured Grid Code

A computational fluid dynamics code based on the flux reconstruction (FR) method is currently being developed at NASA Glenn Research Center to ultimately provide a large- eddy simulation capability that is both accurate and efficient for complex aeropropulsion flows. The FR approach offers a simple and efficient method that is easy to implement and accurate to an arbitrary order on common grid cell geometries. The governing compressible Navier-Stokes equations are discretized in time using various explicit Runge-Kutta schemes, with the default being the 3-stage/3rd-order strong stability preserving scheme. The code is written in modern Fortran (i.e., Fortran 2008) and parallelization is attained through MPI for execution on distributed-memory high-performance computing systems. An h- refinement study of the isentropic Euler vortex problem is able to empirically demonstrate the capability of the FR method to achieve super-accuracy for inviscid flows. Additionally, the code is applied to the Taylor-Green vortex problem, performing numerous implicit large-eddy simulations across a range of grid resolutions and solution orders. The solution found by a pseudo-spectral code is commonly used as a reference solution to this problem, and the FR code is able to reproduce this solution using approximately the same grid resolution. Finally, an examination of the code's performance demonstrates good parallel scaling, as well as an implementation of the FR method with a computational cost/degree- of-freedom/time-step that is essentially independent of the solution order of accuracy for structured geometries.

High-Order Methods↗
NASA NTRS2018

A Conservative, Scalable, Space-Time Blade Element Rotor Model for Multi-Rotor Vehicles

The development of a parallel blade-element rotor model and its implementation into an adaptive Cartesian method is described. The unsteady version of the rotor model applies a body force to all cells contained in the swept space-time volume at each timestep and special care is taken to maintain axisymmetry on the Cartesian grid. Mesh convergence of rotor thrust and torque is obtained with around 10000 cells in the disk for the steady model. Parallelization is accomplished using OpenMP and the rotor force computation is distributed across all available nodes. Simulations of an isolated XV-15 rotor in hover show good correlation with experimental data and predictions of multi-rotor thrust variation closely match previous high fidelity simulations. The final paper will also include results from the unsteady rotor model and parallel scaling tests.

Conservative↗