Search NASA⌕ Search

SEARCH · Search NASA

Results for “high performance and distributed computing”

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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The Kokkos Ecosystem [Brief]

In 2016/2017, the field of High-Performance Computing (HPC) entered a new era driven by fundamental physics challenges to produce ever more energy and cost-efficient processors. Since the convergence on the Message-Passing Interface (MPI) standard in the mid-1990s, application developers enjoyed a seemingly static view of the underlying machine — that of a distributed collection of homogeneous nodes executing in collaboration. However, after almost two decades of dominance, the sole use of MPI to derive parallelism acted as a limiter to improved future performance. While MPI is widely expected to continue to function as the basic mechanism for communication between compute nodes for the immediate future, additional parallelism is required on the computing node itself if high performance and efficiency goals are to be realized. When reviewing the architectures of the top HPC systems today, the change in paradigm is clear: the compute nodes of the leading machines in the world are either powered by many-core chips with a few dozen cores each, or use heterogeneous designs, where traditional CPUs marshal work to massively parallel compute accelerators which has as many as 200,000 processing threads in flight simultaneously. Complicating matters further for application developers, each processor vendor has its own preferred way of writing code for their architecture.The Kokkos EcoSystem was released by Sandia in 2017 to address this new era in HPC system design by providing a vendor independent performance portable programming system for scientific, engineering, and mathematical software applications written in the C++ programming language. Using Kokkos, application developers can be more productive because they will not have to create and maintain separate versions of their software for each architecture, nor will they have to be experts in each architecture's peculiar requirements. Instead, they will have a single method of programming for the diverse set of modern HPC architectures. While Kokkos started in 2011 as a programming model only, it soon became clear that complex applications needed more. It is also critical to have a portable mathematical functions and developers need tools to debug their applications, gain insight into the performance characteristics of their codes and tune algorithm performance parameters through automated processes. The Kokkos EcoSystem addresses those needs through its three main components: the Kokkos Core programming model, the Kokkos Kernels math library, and the Kokkos Tools project.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

PowderJet: Spherical metal powder production via multi-orifice droplet-on-demand metal jetting

Leading metal additive manufacturing techniques, such as laser powder bed fusion and directed energy deposition, rely on high-quality spherical metal powders. However, traditional powder production methods like gas atomization face limitations, including low in-spec yield, asphericity, and internal porosity. We introduce PowderJet, a powder production platform that uses electromagnetic pulses to eject liquid metal droplets from a multi-orifice nozzle. Unlike stochastic methods, PowderJet tightly controls powder size, distribution, and purity through a droplet-on-demand approach. We detail the system’s design, operation, and performance using a combined experimental and computational fluid dynamics (CFD) framework. Initial results with Al4008 and Cu110 alloys demonstrate successful production, yielding unsieved aluminum powder batches with a mean diameter of 200 µm and a narrow size distribution (15 µm standard deviation). The produced powders are highly spherical, achieving a roundness > 0.95. PowderJet operates with a small melt volume (3 mL) and supports continuous refilling, enabling production rates between 30 and 140 cm³/hr depending on jetting frequency, number of orifices and particle size. CFD simulations show that future systems could achieve rates exceeding 1000 cm³/hr for particle sizes as small as 40 µm. PowderJet’s high yield of in-spec powder makes it ideal for producing precious or hazardous materials that are inefficient to manufacture using conventional methods. This platform offers a scalable, precise, and efficient solution for producing high-quality powders tailored for advanced manufacturing applications.

Atomization↗
DOE OSTI2019

GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond

Recent progress in Artificial Intelligence (AI) techniques, the large-scale availability of high-quality data, as well as advances in both hardware and software to efficiently process these data, are transforming a range of fields from computer vision and natural language processing to autonomous driving and healthcare. For example, the availability of high-resolution geographic data and high-performance computing techniques together with deep learning fuel progress in fast and accurate object detection. Recent examples of GeoAI work include the detections of terrain features and densely-distributed building footprints, information extraction from scanned historical maps, semantic classification (e.g. LiDAR point clouds), novel methods for spatial interpolation, and advances in traffic forecasting. Similarly, machine learning and natural language processing are facilitating the extraction of geographic information from unstructured (textual) data, such as news articles and Wikipedia as well as the matching of natural features in multiple gazetteers.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Dynamic Species Reduction for Multi-Cycle CFD Simulations (Final Technical Report)

This project primarily sought to address some of the computational cost concerns of detailed simulations by developing improved methods of handling species transport, and chemical kinetics evaluation in a commercial 3D Computational Fluid Dynamics (CFD) environment. Secondary goals were to apply these techniques to fuels and conditions of interest to better understand the key species and reactions required to adequately capture cycle to cycle coupling. Improved modeling will lead to better understanding of these combustion modes and their dependence on fuel composition, which can then enable more clean and efficient engines, ultimately benefiting the consumer as well as the general public. Two approaches were used to address the computational cost. A “Dynamic Species Reduction” (DSR) procedure was developed to remove chemical species from the simulation during periods when chemical reactions were not expected to be important, particularly during gas exchange when temperatures are low and little fuel remains. This modelling procedure automatically detects relevant species to retain in the simulation domain based on their local concentration, removes species below a specified concentration threshold, and then adjusts the remaining species mass to conserve not only the number of H, C, and O atoms in each cell, but also the relative proportions between species and the heating value of the mixture in every cell. The second procedure was a “Product Directed Remapping” (PDR) updates the algorithm used to group individual computational cells for chemical kinetics evaluation to account for non-uniform temperature distributions and the CO to CO 2 ratio in the cells. The model techniques developed in this work successfully demonstrated computational performance improvements for a range of conditions relevant for Highly Dilute SI and HCCI engine operation. Runtime reductions of 10% were observed for small mechanisms, with further reductions of up to 36% observed for larger mechanisms. Improvements were primarily related to reducing the number of chemical species tracked during the gas exchange process using the Dynamic Species Reduction method. With smaller benefits observed from changes to the kinetics binning and evaluation strategy in the post combustion region using the PDR method. The results of this work show the potential for improved computational runtime for complicated simulations. They can and should be extended to additional conditions and new bio-derived and renewable fuels as they are developed and new kinetic mechanisms become available.

10 SYNTHETIC FUELS↗
DOE OSTI2026

Unitary Qubit Lattice Algorithms for Plasma Physics

This final technical report summarizes research conducted under DOE Award DE-SC0021653 to develop unitary Quantum Lattice Algorithms for modeling electromagnetic wave propagation and scattering in complex media, including plasmas. The project developed and validated quantum-inspired formulations of Maxwell's equations that preserve unitary evolution and can be evaluated on classical high-performance computing systems while providing a foundation for future quantum-computing implementations. Major accomplishments include the development of two- and three-dimensional algorithms for electromagnetic scattering; scalable, distributed-memory implementations demonstrated on the Perlmutter supercomputer; formulations for nonlinear lossless fluid dynamics and cold, lossless, inhomogeneous magnetized plasmas; and an explicit quantum algorithm for a time-discretized Lorenz model. Simulations reproduced a range of characteristic wave phenomena, including transient effects that are not readily apparent in conventional frequency-domain studies, demonstrating the effectiveness of the proposed approach for modeling complex electromagnetic and plasma systems. The work establishes a unified theoretical and computational framework for quantum and quantum-inspired simulation and provides a foundation for future implementation on fault-tolerant quantum systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1989

Atmospheric correction of high resolution land surface images

Algorithms to correct for atmospheric-scattering effects in high-spatial resolution land-surface images require the ability to perform rapid and accurate computations of the top-of-atmosphere diffuse radiance field for arbitrarily general surface reflectance distributions (which may be both heterogeneous and non-Lambertian) and atmospheric models. Using three-dimensional radiative transfer (3DRT) theory algorithms are being developed. The methodology used to perform the 3DRT calculations is described. It is shown how these calculations are used to perform atmospheric corrections, and the sensitivity of the retrieved surface reflectances to atmospheric structural parameters is illustrated.

Diner, D. J.↗
NASA NTRS1992

Design of advanced turbopump drive turbines for National Launch System application

The aerodynamic design of advanced fuel and oxidizer pump drive turbine systems being developed for application in the main propulsion system of the National Launch System are discussed. The detail design process is presented along with the final baseline fuel and oxidizer turbine configurations. Computed airfoil surface static pressure distributions and flow characteristics are shown. Both turbine configurations employ unconventional high turning blading (approximately 160 deg) and are expected to provide significant cost and performance benefits in comparison with traditional configurations.

Huber, F. W.↗
DOE OSTI2018

Development of a Kalman filter estimator for simulation and control of particulate matter distribution of a diesel catalyzed particulate filter

The knowledge of the temperature and particulate matter mass distribution is essential for monitoring the performance and durability of a catalyzed particulate filter. A catalyzed particulate filter model was developed, and it showed capability to accurately predict temperature and particulate matter mass distribution and pressure drop across the catalyzed particulate filter. However, the high-fidelity model is computationally demanding. Therefore, a reduced order multi-zone particulate filter model was developed to reduce computational complexity with an acceptable level of accuracy. In order to develop a reduced order model, a parametric study was carried out to determine the number of zones necessary for aftertreatment control applications. The catalyzed particulate filter model was further reduced by carrying out a sensitivity study of the selected model assumptions. The reduced order multi-zone particulate filter model with 5 × 5 zones was selected to develop a catalyzed particulate filter state estimator considering its computational time and accuracy. Next, a Kalman filter–based catalyzed particulate filter estimator was developed to estimate unknown states of the catalyzed particulate filter such as temperature and particulate matter mass distribution and pressure drop (Δ P) using the sensor inputs to the engine electronic control unit and the reduced order multi-zone particulate filter model. A diesel oxidation catalyst estimator was also integrated with the catalyzed particulate filter estimator in order to provide estimates of diesel oxidation catalyst outlet concentrations of NO 2 and hydrocarbons and inlet temperature for the catalyzed particulate filter estimator. The combined diesel oxidation catalyst–catalyzed particulate filter estimator was validated for an active regeneration experiment. The validation results for catalyzed particulate filter temperature distribution showed that the root mean square temperature error by using the diesel oxidation catalyst–catalyzed particulate filter estimator is within 3.2 °C compared to the experimental data. Similarly, the Δ P estimator closely simulated the measured total Δ P and the estimated cake pressure drop error is within 0.2 kPa compared to the high-fidelity catalyzed particulate filter model.

Engineering↗
DOE OSTI2018

On Data Transfers Over Wide-Area Dedicated Connections

Dedicated wide-area network connections are employed in big data and high-performance computing scenarios, since the absence of cross-traffic promises to make it easier to analyze and optimize data transfers over them. However, nonlinear transport dynamics and end-system complexity due to multi-core hosts and distributed file systems make these tasks surprisingly challenging. We present an overview of methods to analyze memory and disk file transfers using extensive measurements over 10 Gbps physical and emulated connections with 0–366 ms round trip times (RTTs). For memory transfers, we derive performance profiles of TCP and UDT throughput as a function of RTT, which show concave regions in contrast to entirely convex regions predicted by previous models. These highly desirable concave regions can be expanded by utilizing large buffers and more parallel flows. We also present Poincar´e maps and Lyapunov exponents of TCP and UDT throughputtraces that indicate complex throughput dynamics. For disk file transfers, we show that throughput can be optimized using a combination of parallel I/O and network threads under direct I/O mode. Our initial throughput measurements of Lustre filesystems mounted over long-haul connections using LNet routers show convex profiles indicative of I/O limits.

Rao, Nageswara S.↗
DOE OSTI2024

Porting ATLAS Fast Calorimeter Simulation to GPUs with Performance Portable Programming Models

FastCaloSim is a parameterized simulation of the particle energy response and of the energy distribution in the ATLAS calorimeter. It is a relatively small and self-contained package with massive inherent parallelism and captures the essence of GPU offloading via important operations like data transfer, memory initialization, floating point operations, and reduction. It was identified by the High Energy Physics Center for Computational Excellence project as a good testbed for evaluating the performance and ease of portability of programming models. In this paper, we will discuss the results of our evaluation of the porting process to Kokkos, SYCL, Alpaka, OpenMP and std::par (nvc++), and compare performance on NVIDIA, AMD and Intel GPUs, as well as multicore CPUs.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Monte Carlo computations of F-region incoherent radar spectra at high latitudes and the use of a simple method for non-Maxwellian spectral calculations

Monte Carlo simulations of ion velocity distributions in the high-latitude F region have been performed in order to improve the calculation of incoherent radar spectra in the auroral ionosphere. The results confirm that when the ion temperature becomes large due to frictional heating in the presence of collisions with the neutral background constituent, F region spectra evolve from a normal double hump, to a triple hump, to a spectrum with a single maximum. An empirical approach is developed to overcome the inadequacy of the Maxwellian assumption for the case of radar aspect angles of between 30 and 70 deg.

Kikuchi, K.↗
DOE OSTI2020

Multi-Agent Control of Lane-Switching Automated Vehicles for Energy Efficiency

The proliferation of automatic control systems and their connectivity accents the performance of their interactions. In particular, connected and automated vehicles could become high-impact examples thanks to their energy use and productivity effects. Ideally, a controller might collectively optimize all agents' control moves for a given objective. However, limits on computational complexity, incomplete knowledge of the central planner, and risks of a single point of failure make distributed control attractive as well. This paper proposes a collaborative heuristic to approach the performance of centralized control with decentralized-like computational effort. The related centralized controller is also described in detail and evaluated as a baseline. A collaboration-intensive obstacle avoidance scenario involving electric vehicles is simulated to demonstrate benefits over fully decentralized control. While centralized optimization performed best with an 8.6 % energy reduction, the collaborative decentralized scheme reached a favorable computation-performance tradeoff with a 6.7 % energy reduction.

Dollar, R. Austin↗
NASA NTRS1986

Computer-aided design and distributed system technology development for large space structures

Proposed large space structures have many characteristics that make them difficult to analyze and control. They are highly flexible, with components mathematically modeled by partial differential equations or very large systems of ordinary differential equations. They have many resonant frequencies, typically low and closely spaced. Natural damping may be low and/or improperly modeled. Coupled with stringent operational requirements of orientation, shape control, and vibration suppression, and the inability to perform adequate ground testing, these characteristics present an unconventional identification and control design problem to the systems theorist. Some of the research underway within Langley's Spacecraft Control Branch, Guidance and Control Division aimed at developing theory and algorithms to treat large space structures systems identification and control problems is described. The research areas to be considered are computer-aided design algorithms, and systems identification and control of distributed systems.

Armstrong, Ernest S.↗
DOE OSTI2024

Overview of the distributed image processing infrastructure to produce the Legacy Survey of Space and Time

The Vera C. Rubin Observatory is preparing to execute the most ambitious astronomical survey ever attempted, the Legacy Survey of Space and Time (LSST). Currently the final phase of construction is under way in the Chilean Andes, with the Observatory’s ten-year science mission scheduled to begin in 2025. Rubin’s 8.4-meter telescope will nightly scan the southern hemisphere collecting imagery in the wavelength range 320–1050 nm covering the entire observable sky every 4 nights using a 3.2 gigapixel camera, the largest imaging device ever built for astronomy. Automated detection and classification of celestial objects will be performed by sophisticated algorithms on high-resolution images to progressively produce an astronomical catalog eventually composed of 20 billion galaxies and 17 billion stars and their associated physical properties. In this article we present an overview of the system currently being constructed to perform data distribution as well as the annual campaigns which reprocess the entire image dataset collected since the beginning of the survey. These processing campaigns will utilize computing and storage resources provided by three Rubin data facilities (one in the US and two in Europe). Each year a Data Release will be produced and disseminated to science collaborations for use in studies comprising four main science pillars: probing dark matter and dark energy, taking inventory of solar system objects, exploring the transient optical sky and mapping the Milky Way. Also presented is the method by which we leverage some of the common tools and best practices used for management of large-scale distributed data processing projects in the high energy physics and astronomy communities. We also demonstrate how these tools and practices are utilized within the Rubin project in order to overcome the specific challenges faced by the Observatory.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

QCOR; A Language Extension Specification for the Heterogeneous Quantum-Classical Model of Computation

Quantum computing (QC) is an emerging computational paradigm that leverages the laws of quantum mechanics to perform elementary logic operations. Existing programming models for QC were designed with fault-tolerant hardware in mind, envisioning stand-alone applications. However, the susceptibility of near-term quantum computers to noise limits their stand-alone utility. To better leverage limited computational strengths of noisy quantum devices, hybrid algorithms have been suggested whereby quantum computers are used in tandem with their classical counterparts in a heterogeneous fashion. This modus operandi calls out for a programming model and a high-level programming language that natively and seamlessly supports heterogeneous quantum-classical hardware architectures in a single-source-code paradigm. Motivated by the lack of such a model, we introduce a language extension specification, called QCOR, which enables single-source quantum-classical programming. Programs written using the QCOR library–based language extensions can be compiled to produce functional hybrid binary executables. After defining QCOR’s programming model, memory model, and execution model, we discuss how QCOR enables variational, iterative, and feed-forward QC. Additionally, QCOR approaches quantum-classical computation in a hardware-agnostic heterogeneous fashion and strives to build on best practices of high-performance computing. The high level of abstraction in the language extension is intended to accelerate the adoption of QC by researchers familiar with classical high-performance computing.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

Navier-Stokes Simulation of Airconditioning Facility of a Large Modem Computer Room

NASA recently assembled one of the world's fastest operational supercomputers to meet the agency's new high performance computing needs. This large-scale system, named Columbia, consists of 20 interconnected SGI Altix 512-processor systems, for a total of 10,240 Intel Itanium-2 processors. High-fidelity CFD simulations were performed for the NASA Advanced Supercomputing (NAS) computer room at Ames Research Center. The purpose of the simulations was to assess the adequacy of the existing air handling and conditioning system and make recommendations for changes in the design of the system if needed. The simulations were performed with NASA's OVERFLOW-2 CFD code which utilizes overset structured grids. A new set of boundary conditions were developed and added to the flow solver for modeling the roomls air-conditioning and proper cooling of the equipment. Boundary condition parameters for the flow solver are based on cooler CFM (flow rate) ratings and some reasonable assumptions of flow and heat transfer data for the floor and central processing units (CPU) . The geometry modeling from blue prints and grid generation were handled by the NASA Ames software package Chimera Grid Tools (CGT). This geometric model was developed as a CGT-scripted template, which can be easily modified to accommodate any changes in shape and size of the room, locations and dimensions of the CPU racks, disk racks, coolers, power distribution units, and mass-storage system. The compute nodes are grouped in pairs of racks with an aisle in the middle. High-speed connection cables connect the racks with overhead cable trays. The cool air from the cooling units is pumped into the computer room from a sub-floor through perforated floor tiles. The CPU cooling fans draw cool air from the floor tiles, which run along the outside length of each rack, and eject warm air into the center isle between the racks. This warm air is eventually drawn into the cooling units located near the walls of the room. One major concern is that the hot air ejected to the middle isle might recirculate back into the cool rack side and cause thermal short-cycling. The simulations analyzed and addressed the following important elements of the computer room: 1) High-temperature build-up in certain regions of the room; 2) Areas of low air circulation in the room; 3) Potential short-cycling of the computer rack cooling system; 4) Effectiveness of the perforated cooling floor tiles; 5) Effect of changes in various aspects of the cooling units. Detailed flow visualization is performed to show temperature distribution, air-flow streamlines and velocities in the computer room.

Source record↗
NASA NTRS2010

High-Intensity Radiated Field Fault-Injection Experiment for a Fault-Tolerant Distributed Communication System

Safety-critical distributed flight control systems require robustness in the presence of faults. In general, these systems consist of a number of input/output (I/O) and computation nodes interacting through a fault-tolerant data communication system. The communication system transfers sensor data and control commands and can handle most faults under typical operating conditions. However, the performance of the closed-loop system can be adversely affected as a result of operating in harsh environments. In particular, High-Intensity Radiated Field (HIRF) environments have the potential to cause random fault manifestations in individual avionic components and to generate simultaneous system-wide communication faults that overwhelm existing fault management mechanisms. This paper presents the design of an experiment conducted at the NASA Langley Research Center's HIRF Laboratory to statistically characterize the faults that a HIRF environment can trigger on a single node of a distributed flight control system.

Yates, Amy M.↗
DOE OSTI2024

CP violation searches and distributed computing development with the Belle II Experiment at the University of Mississippi and Brookhaven National Laboratory (Final Report)

This report reflects the work performed at the University of Mississippi under the support of DOE EPSCoR grant DE‐SC0021274 during the period of September 2020 through August 2024, including a one-year, no-cost extension. A summary of the research outcomes is given, with reference to the project goals as stated in the proposal. This successful project supported the mission of the DOE High Energy Physics program by leveraging the complimentary expertise of researchers at the University of Mississippi and Brookhaven National Lab to search for CP violation in charmed baryon decays using data from the Belle II experiment and to provide vital support for Belle II distributed computing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗