Search NASA⌕ Search

SEARCH · Search NASA

Results for “Parallel Supercomputers”

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 145 records · Page 8

Stability-preserving Lossy Compression for Large-scale Partial Differential Equations

Checkpoint/Restart (C/R) strategies are vital for fault tolerance in PDE-based scientific simulations, yet traditional checkpointing incurs significant I/O overhead. Lossy compression offers a scalable solution by reducing checkpoint data size, but conventional methods often lack control over physical invariants (e.g., energy), leading to instability such as oscillations or divergence in Partial Differential Equations (PDE) systems. This paper introduces a stability-preserving compression approach tailored for PDE simulations by explicitly controlling kinetic and potential energy perturbations to ensure stable restarts. Extensive experiments conducted across diverse PDE configurations demonstrate that our method maintains numerical stability with minimal error magnification—even across multiple checkpoint-restart cycles—outperforming state-of-the-art lossy compressors. Parallel evaluations on the Frontier supercomputer show up to 8.4× improvement in checkpoint write performance and 6.3× in read performance, while maintaining relative L2 errors ∼ 2e-6 throughout continued simulation. These results provide practical guidance for balancing compression accuracy, stability, and computational efficiency in large-scale PDE applications.

Gong, Qian [ORNL] (ORCID:0000000235704142)↗

A Block-Structured Adaptive Mesh Framework to Solve Radiation Transfer Equation in Irregular Embedded Geometries

Radiation transport arises in various scientific, industrial, and medical fields, and understanding its effect in applications is needed to make accurate predictions, safety assessments and performance optimizations. Solving the Radiation Transport Equation (RTE) is challenging due to its integro-differential nature, which involves both differential and integral terms. The differential term describes the change in radiation intensity due to absorption and emission, while the integral term accounts for scattering. The accurate modeling of radiation is further complicated in many applications due to the complex, irregular geometries. Various methods exist for solving the RTE, including the zonal, Monte Carlo, spherical harmonics, discrete ordinates, and finite volume methods. Traditional mesh-based approaches, which rely on structured or unstructured meshes, struggle with irregular geometries due to: a) the difficulty of conforming structured grids to irregular domains, b) challenges in enforcing boundary conditions correctly, and c) the additional computational cost of unstructured mesh methods. This work presents a second-order accurate method for solving the RTE in irregular geometries. The radiation intensity is discretized using the finite-volume method in both spatial and angular directions on regular Cartesian grid blocks. Leveraging the block-structured adaptive mesh refinement (AMR) framework provided by AMReX, our method refines the grid locally to reduce spatial discretization error, ensuring a converged numerical solution while minimizing computational costs elsewhere. A two-stage deferred correction approach is employed: First, a first-order discretization on grid blocks is solved using an algebraic multigrid method in HYPRE. Second, a correction term is applied explicitly to achieve second-order accuracy. The correction term is calculated by approximating the radiation flux on cell faces using a Total Variation Diminishing (TVD) scheme. This approach ensures quick convergence of the multigrid method while preserving higher-order accuracy of the numerical solution. Irregular geometries are resolved as embedded boundaries (EB), resulting in both cut cells and regular cells. In cut cells, we modify the fluxes using face fractions and incorporate additional contributions from EB boundary conditions. To ensure higher-order convergence near the EB interface, the correction term is modified by interpolating the radiation intensity to fictitious ghost points. The implementation takes advantage of modern supercomputers by leveraging AMReX’sMPI/X parallelization strategy where X can be MPI or a GPU accelerator including CUDA, HIP and DPC++. We validate our solver using classical test cases, both with and without EB, demonstrating accuracy and efficiency. Additionally, we analyze the impact of adaptive mesh refinement on solution accuracy and computational cost, highlighting the advantages of our approach for high-resolution radiation transport simulations.

computational fluid dynamics (CFD)↗

Spectral Analysis of Integrated Pressures on Patches with Unsteady Pressure-Sensitive Paint Measurements

The technique of Pressure-Sensitive Paint (PSP) is commonly used in the aerospace industry to measure surface pressures on the model of launch vehicles and airplanes in the wind tunnel test. Recent research has demonstrated that Unsteady Pressure-Sensitive Paint (uPSP) can be an essential tool for the assessment of the unsteady, aerodynamic phenomena. The work described in this paper is a part of NASA’s development of a new state-of-the-art uPSP capability in production wind tunnels. This paper describes the spectral analysis of integrated pressures on patches of the scale model of the Space Launch System (SLS) Block 1 cargo vehicle with the uPSP measurements, which were collected in the Ascent Transient Aerodynamics Test (ATAT) with the Unitary Plan Wind Tunnel 11-by-11-foot Transonic Wind Tunnel in September 2019 at NASA Ames Research Center. The patches are defined with x station values, indicating the position along length of the SLS vehicle, and azimuth angles of the scale model. For each patch, the polygons are determined from the surface cells of the grid of the model, clipped with the edges of the patch, and each of the polygons is divided into triangles. The integrated pressure of the patch is determined as the ratio of the sum of the forces on the triangles over the sum of the areas of the triangles. For each run of the test, the Cross Power Spectral Density (CPSD) and magnitude squared coherence are computed from the time series of the integrated pressures on the patches. The pressure integration is coded in C++ and the spectral analysis is coded in MATLAB. The results were generated with the execution of the compiled C++ and MATLAB codes in parallel on the NASA Pleiades supercomputer. The results of pressure integration and spectral analysis are presented in this paper, and the data consistency of the test is also demonstrated. Funding for this research was provided by the NASA Aerosciences Evaluation and Test Capabilities Project.

Pressure-Sensitive Paint↗

The Profiled Feldman-Cousins Method for Confidence Interval Construction for the Nova 3-Flavor Oscillation Analysis

The small interaction cross-section of neutrinos makes experimental neutrino physics particularly responsive to technological advancements. A significant development leveraged by the NOvA experiment is large-scale parallel processing, enabling novel computational approaches to longstanding experimental challenges. Central to managing the resulting high-throughput data is NOvA’s implementation of the Freight Train model, designed for efficient data production and handling.This dissertation details the methodology and execution of the NOvA 2024 3-Flavor Oscillation Analysis, supported by a comprehensive dataset spanning ten years. It emphasizes frequentist results refined through the Feldman-Cousins (FC) technique, specifically addressing confidence interval corrections in parameter estimation. The computational intensity associated with Feldman-Cousins arises from extensive Monte Carlo simulations, which were substantially mitigated through parallel computing on the Perlmutter supercomputer at the National Energy Research Scientific Computing Center (NERSC), employing the MPI framework.To further enhance computational efficiency, an Importance Sampling method is introduced and evaluated, demonstrating significant potential to reduce complexity, particularly in exploring extreme parameter space regions. This thesis presents both the successful application of advanced computational resources and the development of sophisticated statistical techniques, aiming to enhance the precision and scope of neutrino oscillation analyses.

Dye ajdye11190@gmail.com, Andrew Joseph [Mississip↗

Massive parallelism in the future of science

Massive parallelism appears in three domains of action of concern to scientists, where it produces collective action that is not possible from any individual agent's behavior. In the domain of data parallelism, computers comprising very large numbers of processing agents, one for each data item in the result will be designed. These agents collectively can solve problems thousands of times faster than current supercomputers. In the domain of distributed parallelism, computations comprising large numbers of resource attached to the world network will be designed. The network will support computations far beyond the power of any one machine. In the domain of people parallelism collaborations among large groups of scientists around the world who participate in projects that endure well past the sojourns of individuals within them will be designed. Computing and telecommunications technology will support the large, long projects that will characterize big science by the turn of the century. Scientists must become masters in these three domains during the coming decade.

Denning, Peter J.↗

P2P Technology for High-Performance Computing: An Overview

The transition from cluster computing to peer-to-peer (P2P) high-performance computing has recently attracted the attention of the computer science community. It has been recognized that existing local networks and dedicated clusters of headless workstations can serve as inexpensive yet powerful virtual supercomputers. It has also been recognized that the vast number of lower-end computers connected to the Internet stay idle for as long as 90% of the time. The growing speed of Internet connections and the high availability of free CPU time encourage exploration of the possibility to use the whole Internet rather than local clusters as massively parallel yet almost freely available P2P supercomputer. As a part of a larger project on P2P high-performance computing, it has been my goal to compile an overview of the 2P2 paradigm. I have studied various P2P platforms and I have compiled systematic brief descriptions of their most important characteristics. I have also experimented and obtained hands-on experience with selected P2P platforms focusing on those that seem promising with respect to P2P high-performance computing. I have also compiled relevant literature and web references. I have prepared a draft technical report and I have summarized my findings in a poster paper.

Follen, Gregory J.↗

Beyond the supercomputer

A NASA-directed development of massively parallel processor (MPP) computers is outlined, noting intended applications for data processing for near term earth resource and environment mapping, radar, and television transmissions. The MPP is designed to perform 100 billion operations/sec to obtain satisfactory image processing, while separate processing units correct distortions, register images, calculate correlation functions, and classify multispectral characteristics. Arrays of 1s and 0s will be manipulated in analog-to-digital conversions generating separate planes corresponding to powers of binaries. Data wires are replaced by fiber-optic tubes or thousands of wires, and single logic gates are replaced by thousands of logic gates and every memory element by thousands of memory elements. Features of the interconnections and the images control processor units are detailed, along with implementation of sliders for program flexibility.

Schaefer, D. H.↗

Optics Program Modified for Multithreaded Parallel Computing

A powerful high-performance computer program for simulating and analyzing adaptive and controlled optical systems has been developed by modifying the serial version of the Modeling and Analysis for Controlled Optical Systems (MACOS) program to impart capabilities for multithreaded parallel processing on computing systems ranging from supercomputers down to Symmetric Multiprocessing (SMP) personal computers. The modifications included the incorporation of OpenMP, a portable and widely supported application interface software, that can be used to explicitly add multithreaded parallelism to an application program under a shared-memory programming model. OpenMP was applied to parallelize ray-tracing calculations, one of the major computing components in MACOS. Multithreading is also used in the diffraction propagation of light in MACOS based on pthreads [POSIX Thread, (where "POSIX" signifies a portable operating system for UNIX)]. In tests of the parallelized version of MACOS, the speedup in ray-tracing calculations was found to be linear, or proportional to the number of processors, while the speedup in diffraction calculations ranged from 50 to 60 percent, depending on the type and number of processors. The parallelized version of MACOS is portable, and, to the user, its interface is basically the same as that of the original serial version of MACOS.

Lou, John↗

Disk Failure Dataset from the Campaign Storage System

This dataset consists of 1,389 disk (HDD) failure events collected from the Campaign storage system at LANL. The Campaign system supported various compute platforms throughout its lifespan, including Cielo, Fire, Ice, and notably, the Trinity supercomputer. Each recorded event includes its detection timestamp (in ISO 8601 format) and details such as its location within the storage system—rack, enclosure, and drive slot number. The data, spanning from May 4, 2021, to July 25, 2023 (2 years, 2 months, and 22 days), represents failure events from the terminal years of Campaign's operational period, accounting for 26% of its total operational time.

97 MATHEMATICS AND COMPUTING↗

Applications of the massively parallel machine, the MasPar MP-1, to Earth sciences

The computational workload of upcoming NASA science missions, especially the ground data processing for the Earth Observing System, is projected to be quite large (in the 50 to 100 gigaFLOPS range) and corespondingly very expensive to perform using conventional supercomputer systems. High performance, general purpose massively parallel computer systems such as the MasPar MP-1 are being investigated by NASA as a more cost effective alternative. Massively parallel systems are targeted for accelerated development and maturation by NASA's upcoming five-year High Performance Computing and Communications Program. A summary of the broad range of applications currently running on the MP-1 at NASA/Goddard are presented in this paper along with descriptions of the parallel algorithmic techniques employed in five applications that have bearing on Earth sciences.

Fischer, James R.↗

Parallel implementation of an algorithm for Delaunay triangulation

This work concerns the theory and practice of implementing Tanemura's algorithm for 3D Delaunay triangulation on Intel's Gamma prototype, a 128 processor MIMD computer. Tanemura's algorithm does not vectorize to any significant degree and requires indirect addressing. Efficient implementation on a conventional, vector processing, supercomputer is problematic. Efficient implementation on a parallel architecture is possible, however. In this work, speeds in excess of 8 times a single processor Cray Y-mp are realized on 128 processors of the Intel Gamma prototype.

Merriam, Marshall L.↗

1993 Gordon Bell Prize Winners

The Gordon Bell Prize recognizes significant achievements in the application of supercomputers to scientific and engineering problems. In 1993, finalists were named for work in three categories: (1) Performance, which recognizes those who solved a real problem in the quickest elapsed time. (2) Price/performance, which encourages the development of cost-effective supercomputing. (3) Compiler-generated speedup, which measures how well compiler writers are facilitating the programming of parallel processors. The winners were announced November 17 at the Supercomputing 93 conference in Portland, Oregon. Gordon Bell, an independent consultant in Los Altos, California, is sponsoring $2,000 in prizes each year for 10 years to promote practical parallel processing research. This is the sixth year of the prize, which Computer administers. Something unprecedented in Gordon Bell Prize competition occurred this year: A computer manufacturer was singled out for recognition. Nine entries reporting results obtained on the Cray C90 were received, seven of the submissions orchestrated by Cray Research. Although none of these entries showed sufficiently high performance to win outright, the judges were impressed by the breadth of applications that ran well on this machine, all nine running at more than a third of the peak performance of the machine.

Karp, Alan H.↗

User Manual - HydraGNN v5.0: Distributed Implementation of Multi-Tasking Graph Neural Networks

This document serves as the user manual for HydraGNN v5.0, a scalable graph neural network (GNN) architecture for simultaneous prediction of multiple target properties using multi-task learning (MTL). This version of HydraGNN has been developed primarily to support the development, training, and deployment of predictive graph-based deep learning (DL) models for atomistic materials modeling. HydraGNN is templated over 13 message-passing policies, including invariant models (GIN, PNA, PNAPlus, GAT, MFC, CGCNN, SAGE, SchNet, DimeNet) and equivariant models (EGNN, PNAEq, PAINN, MACE), and supports distributed training via distributed data parallelism (DDP), DeepSpeed, and Fully Sharded Data Parallelism (FSDP) on leadership-class supercomputers. Although HydraGNN can be applied to problems beyond atomistic materials modeling, its current use is confined to homogeneous graphs. Additional capabilities include machine-learned interatomic potentials with energy-conserving forces, General, Powerful, and Scalable Graph Transformer (GraphGPS) global attention, periodic boundary conditions, hyperparameter optimization, mixed-precision training, and uncertainty quantification.

97 MATHEMATICS AND COMPUTING↗

Viskores: Integrating Parallel Scientific Visualization Research into Applications

Viskores is a scientific visualization library that is the primary deployment of such algorithms to the parallel accelerated processors of modern DOE supercomputers. In this paper, we review the capabilities provided by Viskores and how these capabilities are leveraged by other software in the high-performance computing ecosystem. We discuss the Viskores data representation and pay particular attention to array management. Through this array management we describe how data is adapted between Viskores and other software along with strategies for converting dynamic, polymorphic objects to static representations better suited to GPU processing. We conclude with several examples of Viskores integrating with high-performance software that is used in production today.

Moreland, Ken [ORNL] (ORCID:0000000270513288)↗

Scale-up Unlearnable Examples Learning with High-performance Computing

Recent advancements in AI models, like ChatGPT, are structured to retain user interactions, which could inadvertently include sensitive healthcare data. In the healthcare field, particularly when radiologists use AI-driven diagnostic tools hosted on online platforms, there is a risk that medical imaging data may be repurposed for future AI training without explicit consent, spotlighting critical privacy and intellectual property concerns around healthcare data usage. Addressing these privacy challenges, a novel approach known as Unlearnable Examples (UEs) has been introduced, aiming to make data unlearnable to deep learning models. A prominent method within this area, called Unlearnable Clustering (UC), has shown improved UE performance with larger batch sizes but was previously limited by computational resources (e.g., a single workstation). To push the boundaries of UE performance with theoretically unlimited resources, we scaled up UC learning across various datasets using Distributed Data Parallel (DDP) training on the Summit supercomputer. Our goal was to examine UE efficacy at high-performance computing (HPC) levels to prevent unauthorized learning and enhance data security, particularly exploring the impact of batch size on UE’s unlearnability. Utilizing the robust computational capabilities of the Summit, extensive experiments were conducted on diverse datasets such as Pets, MedMNist, Flowers, and Flowers102. Our findings reveal that both overly large and overly small batch sizes can lead to performance instability and affect accuracy. However, the relationship between batch size and unlearnability varied across datasets, highlighting the necessity for tailored batch size strategies to achieve optimal data protection. The use of Summit’s high-performance GPUs, along with the efficiency of the DDP framework, facilitated rapid updates of model parameters and consistent training across nodes. Our results underscore the critical role of selecting appropriate batch sizes based on the specific characteristics of each dataset to prevent learning and ensure data security in deep learning applications. The source code is publicly available at https: // github. com/ hrlblab/ UE_ HPC .

Zhu, Yanfan [Vanderbilt University, Nashville, TN,↗

The NAS Parallel Benchmarks 2.1 Results

We present performance results for version 2.1 of the NAS Parallel Benchmarks (NPB) on the following architectures: IBM SP2/66 MHz; SGI Power Challenge Array/90 MHz; Cray Research T3D; and Intel Paragon. The NAS Parallel Benchmarks are a widely-recognized suite of benchmarks originally designed to compare the performance of highly parallel computers with that of traditional supercomputers.

Saphir, William↗

Modeling of Radiative Transfer in Protostellar Disks

This program implements a spectral line, radiative transfer tool for interpreting Spitzer Space Telescope observations by matching them with models of protostellar disks for improved understanding of planet and star formation. The Spitzer Space Telescope detects gas phase molecules in the infrared spectra of protostellar disks, with spectral lines carrying information on the chemical composition of the material from which planets form. Input to the software includes chemical models developed at JPL. The products are synthetic images and spectra for comparison with Spitzer measurements. Radiative transfer in a protostellar disk is primarily affected by absorption and emission processes in the dust and in molecular gases such as H2, CO, and HCO. The magnitude of the optical absorption and emission is determined by the population of the electronic, vibrational, and rotational energy levels. The population of the molecular level is in turn determined by the intensity of the radiation field. Therefore, the intensity of the radiation field and the population of the molecular levels are inter-dependent quantities. To meet the computational challenges of solving for the coupled radiation field and electronic level populations in disks having wide ranges of optical depths and spatial scales, the tool runs in parallel on the JPL Dell Cluster supercomputer with C++ and Fortran compiler with a Message Passing Interface. Because this software has been developed on a distributed computing platform, the modeling of systems previously beyond the reach of available computational resources is possible.

VonAllmen, Paul↗

Lightforce Photon-Pressure Collision Avoidance: Efficiency Analysis in the Current Debris Environment and Long-Term Simulation Perspective

This work provides an efficiency analysis of the LightForce space debris collision avoidance scheme in the current debris environment and describes a simulation approach to assess its impact on the long-term evolution of the space debris environment. LightForce aims to provide just-in-time collision avoidance by utilizing photon pressure from ground-based industrial lasers. These ground stations impart minimal accelerations to increase the miss distance for a predicted conjunction between two objects. In the first part of this paper we will present research that investigates the short-term effect of a few systems consisting of 20-kilowatt-class lasers directed by 1.5-meter-diameter telescopes using adaptive optics. The results found such a network of ground stations to mitigate more than 85 percent of conjunctions and could lower the expected number of collisions in Low Earth Orbit (LEO) by an order of magnitude. While these are impressive numbers that indicate LightForce's utility in the short-term, the remaining 15 percent of possible collisions contain (among others) conjunctions between two massive objects that would add large amount of debris if they collide. Still, conjunctions between massive objects and smaller objects can be mitigated. Hence, we choose to expand the capabilities of the simulation software to investigate the overall effect of a network of LightForce stations on the long-term debris evolution. In the second part of this paper, we will present the planned simulation approach for that effort. For the efficiency analysis of collision avoidance in the current debris environment, we utilize a simulation approach that uses the entire Two Line Element (TLE) catalog in LEO for a given day as initial input. These objects are propagated for one year and an all-on-all conjunction analysis is performed. For conjunctions that fall below a range threshold, we calculate the probability of collision and record those values. To assess efficiency, we compare a baseline (without collision avoidance) conjunction analysis with an analysis where LightForce is active. Using that approach, we take into account that collision avoidance maneuvers could have effects on third objects. Performing all-on-all conjunction analyses for extended period of time requires significant computer resources; hence we implemented this simulation utilizing a highly parallel approach on the NASA Pleiades supercomputer.

space debris mitigation↗