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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Implementation and Characterization of Three-Dimensional Particle-in-Cell Codes on Multiple-Instruction-Multiple-Data Massively Parallel Supercomputers

A three-dimensional electrostatic particle-in-cell (PIC) plasma simulation code has been developed on coarse-grain distributed-memory massively parallel computers with message passing communications. Our implementation is the generalization to three-dimensions of the general concurrent particle-in-cell (GCPIC) algorithm. In the GCPIC algorithm, the particle computation is divided among the processors using a domain decomposition of the simulation domain. In a three-dimensional simulation, the domain can be partitioned into one-, two-, or three-dimensional subdomains ("slabs," "rods," or "cubes") and we investigate the efficiency of the parallel implementation of the push for all three choices. The present implementation runs on the Intel Touchstone Delta machine at Caltech; a multiple-instruction-multiple-data (MIMD) parallel computer with 512 nodes. We find that the parallel efficiency of the push is very high, with the ratio of communication to computation time in the range 0.3%-10.0%. The highest efficiency (> 99%) occurs for a large, scaled problem with 64(sup 3) particles per processing node (approximately 134 million particles of 512 nodes) which has a push time of about 250 ns per particle per time step. We have also developed expressions for the timing of the code which are a function of both code parameters (number of grid points, particles, etc.) and machine-dependent parameters (effective FLOP rate, and the effective interprocessor bandwidths for the communication of particles and grid points). These expressions can be used to estimate the performance of scaled problems--including those with inhomogeneous plasmas--to other parallel machines once the machine-dependent parameters are known.

Lyster, P. M.↗
DOE OSTI2024

Optimizing High-Throughput Inference on Graph Neural Networks at Shared Computing Facilities with the NVIDIA Triton Inference Server

Abstract With machine learning applications now spanning a variety of computational tasks, multi-user shared computing facilities are devoting a rapidly increasing proportion of their resources to such algorithms. Graph neural networks (GNNs), for example, have provided astounding improvements in extracting complex signatures from data and are now widely used in a variety of applications, such as particle jet classification in high energy physics (HEP). However, GNNs also come with an enormous computational penalty that requires the use of GPUs to maintain reasonable throughput. At shared computing facilities, such as those used by physicists at Fermi National Accelerator Laboratory (Fermilab), methodical resource allocation and high throughput at the many-user scale are key to ensuring that resources are being used as efficiently as possible. These facilities, however, primarily provide CPU-only nodes, which proves detrimental to time-to-insight and computational throughput for workflows that include machine learning inference. In this work, we describe how a shared computing facility can use the NVIDIA Triton Inference Server to optimize its resource allocation and computing structure, recovering high throughput while scaling out to multiple users by massively parallelizing their machine learning inference. To demonstrate the effectiveness of this system in a realistic multi-user environment, we use the Fermilab Elastic Analysis Facility augmented with the Triton Inference Server to provide scalable and high-throughput access to a HEP-specific GNN and report on the outcome.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

HPC formulations of optimization algorithms for tensor completion

Tensor completion is a powerful tool used to estimate or recover missing values in multi-way data. It has seen great success in domains such as product recommendation and healthcare. Tensor completion is most often accomplished via low-rank sparse tensor factorization, a computationally expensive non-convex optimization problem which has only recently been studied in the context of parallel computing. In this work, we study three optimization algorithms that have been successfully applied to tensor completion: alternating least squares (ALS), stochastic gradient descent (SGD), and coordinate descent (CCD++). We explore opportunities for parallelism on shared- and distributed-memory systems and address challenges such as memory- and operation-efficiency, load balance, cache locality, and communication. Among our advancements are a communication-efficient CCD++ algorithm, an ALS algorithm rich in level-3 BLAS routines, and an SGD algorithm which combines stratification with asynchronous communication. Furthermore, we show that introducing randomization during ALS and CCD++ can accelerate convergence. We evaluate our parallel formulations on a variety of real datasets on a modern supercomputer and demonstrate speedups through 16384 cores. Further, these improvements reduce time-to-solution from hours to seconds on real-world datasets. We show that after our optimizations, ALS is advantageous on parallel systems of small-to-moderate scale, while both ALS and CCD++ provide the lowest time-to-solution on large-scale distributed systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Toroidal effect on runaway vortex and avalanche growth rate

The momentum-space dynamics of runaway electrons in a slab geometry, in terms of both the geometry and topological transition of the runaway vortex when synchrotron radiative damping is taking into account, have recently been shown to play a crucial role in runaway mitigation and avoidance. In a tokamak geometry, magnetic trapping arises from parallel motion along the magnetic field that scales as 1/R in strength with R the major radius. Since the transit time for a runaway electron moving along the field is of order 10 -8 sec while the collisional time is of ~ 0.01 sec in ITER-like plasmas, a bounce-averaged formulation can drastically reduce computational cost. Here the LAPS-RFP code’s implementation of a bounce-averaged relativistic Fokker- Planck model, along with the essential physics of synchrotron radiation damping and knock-on collisions, is described. It is found that the magnetic trapping can reduce the volume of the runaway vortex as the momentum-space fluxes are strongly modified inside the trapped-region. As a result, the avalanche growth rate is reduced at off-axis locations. In addition to benchmarking with previous calculations that did not take into account radiation damping, we also clarify how synchrotron radiation damping modifies the avalanche growth rate in a tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Generation of kinetic Alfvén waves in dayside magnetopause reconnection: A 3-D global-scale hybrid simulation

In this paper, we perform a three-dimensional (3-D) global-scale hybrid simulation to investigate the generation of kinetic Alfvén waves (KAWs) in reconnection at the dayside magnetopause. In the simulation, the magnetopause reconnection takes place due to a self-consistent interaction between the solar wind and Earth's magnetosphere, in which the solar wind is assumed to carry a southward interplanetary magnetic field. As multiple X-line reconnection occurs, shear Alfvénic perturbations are generated from reconnection, which propagate toward polar regions along the magnetic field lines. Our detailed analysis of the electromagnetic characteristics reveals the existence of kinetic Alfvén waves on the ion kinetic scales in these perturbations, in which the parallel electric field is generated. The 3-D structures and the Poynting fluxes in the shear Alfvén waves/KAWs in the global magnetopause are presented. It is shown that these KAWs carry electromagnetic energy into the cusp, which may lead to aurora brightening.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Cross-field electron diffusion due to the coupling of drift-driven microinstabilities

In this paper, the nonlinear interaction between kinetic instabilities driven by multiple ion beams and magnetized electrons is investigated. Electron diffusion across magnetic field lines is enhanced by the coupling of plasma instabilities. Here, a two-dimensional collisionless particle-in-cell simulation is performed accounting for singly and doubly charged ions in a cross-field configuration. Consistent with prior linear kinetic theory analysis and observations from coherent Thomson scattering experiments, the present simulations identify an ion-ion two-stream instability due to multiply charged ions (flowing in the direction parallel to the applied electric field) which coexists with the electron cyclotron drift instability (propagating perpendicular to the applied electric field and parallel to the ExB drift). Small-scale fluctuations due to the coupling of these naturally driven kinetic modes are found to be a mechanism that can enhance cross-field electron transport and contribute to the broadening of the ion velocity distribution functions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Scalable Distributed Memory Community Detection Using Vite

Graph clustering, popularly known as community detection, is a fundamental graph operation used in several applications of relevance for network analysis and cybersecurity. Community detection is an operation of partitioning a network into an arbitrary number of “communities” such that each com munity represents a tightly-knit group of nodes with relatively sparser connections to the rest of the nodes in the network. The need to compute clustering on large-scale networks necessitates the development of efficient parallel algorithms capable of exploiting modern parallel architectures. However, due to their irregular and inherently sequential nature, many of the current algorithms for community detection are challenging to parallelize. In response to the 2018 Graph Challenge, we present Vite which is a distributed-memory parallel community detection method. Vite is a parallelization of the algorithmic template provided by a widely-used serial method (Louvain). Alongside, it uses several heuristics aimed at significantly improving parallelism and performance, while preserving output quality. Using the inputs from the 2018 Graph Challenge (static and streaming), we demonstrate superior performance and high quality solutions based on four parallelization heuristics.

community detection↗
DOE OSTI2021

Butterfly Factorization Via Randomized Matrix-Vector Multiplications

This paper presents an adaptive randomized algorithm for computing the butterfly factorization of an m × n matrix with m ≈ n provided that both the matrix and its transpose can be rapidly applied to arbitrary vectors. The resulting factorization is composed of O(log n) sparse factors, each containing O(n) nonzero entries. The factorization can be attained using O(n 3/2 log n) computation and O(n log n) memory resources. Furthermore, the proposed algorithm can be implemented in parallel and can apply to matrices with strong or weak admissibility conditions arising from surface integral equation solvers as well as multi-frontal-based finite-difference, finite-element, or finite-volume solvers. A distributed-memory parallel implementation of the algorithm demonstrates excellent scaling behavior.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Ensuring statistical reproducibility of ocean model simulations in the age of hybrid computing

Novel high performance computing systems that feature hybrid architectures require large scale code refactoring to unravel underlying exploitable parallelism. Such redesign can often be accompanied with machine-precision changes as the order of computation cannot always be maintained. For chaotic systems like climate models, these round-off level differences can grow rapidly. Systematic errors may also manifest initially as machine-precision differences. Isolating genuine round off level differences from such errors remains a challenge. Here, we apply two-sample equality of distribution tests to evaluate statistical reproducibility of the ocean model component of US Department of Energy's Energy Exascale Earth System Model (E3SM). A 2-year control simulation ensemble is compared to a modified ensemble as a test case - after a known non-bit-for-bit change in a model component is introduced - to evaluate the null hypothesis that the two ensembles are statistically indistinguishable. To quantify the false negative rates of these tests, we conduct a formal power analysis using a targeted suite of short simulation ensembles. The ensemble suite contains several perturbed ensembles, each with a progressively different climate than the baseline ensemble - obtained by perturbing the magnitude of a single model tuning parameter, the Gent and McWilliams κ, in a controlled manner. The null hypothesis is evaluated for each of perturbed ensembles using these tests. The power analysis informs on the detection limits of the tests for given ensemble size allowing model developers to evaluate the impact of an introduced non-bit-for-bit change to the model.

Mahajan, Salil↗
DOE OSTI2025

Knowledge Oriented Graph Unified Transformer (KOGUT) v0.1

KOGUT — Knowledge Oriented Graph Unified Transformer KOGUT implements the Relational Graph Transformer (RelGT) architecture for knowledge graph link prediction in biological domains, with a primary focus on microbial growth media prediction. While the original RelGT (arXiv:2505.10960) targets relational tables, time series, and multi-table databases, KOGUT adapts this architecture for heterogeneous biological knowledge graphs, providing first-in-class AI predictive models for microbial cultivation. Key Adaptations Beyond Original RelGT: - Knowledge Graph Focus: Applied to biological KGs with semantic node types (taxa, chemicals, media, phenotypes, environments) versus generic relational database tables, trained on the KG-Microbe knowledge graph (1.3M entities, 2.9M edges, 24 relation types). - Multimodal Node Encoding: Integrates node labels, categories, descriptions, and synonyms from KG metadata through learned embedding layers—adapting relational column features to graph node attributes with textual semantics. - Extended K-Hop Subgraph Strategy: Optimized neighborhood sampling (3-hop default, configurable up to 200 nodes) tuned for sparse biological networks, building on the original local-global attention framework with biological relation preservation. - Biolink Predicate Preservation: Type-specific transformations for 24 biological edge semantics (occurs_in, consumes, produces, has_phenotype, subclass_of) beyond standard relational foreign keys, enabling multi-relation link prediction. - Inductive Learning Support: Enables zero-shot predictions for novel taxa through feature-based embeddings (temperature, oxygen requirements, gram stain, cell shape), extending the original transductive relational benchmark scope to uncultured microorganisms. CheapSOTA Performance Optimizations (This Distribution): - VQ-EMA Centroid Attention: Vector quantization with exponential moving average for improved global context modeling (+5-10% MRR improvement). - HDF5 Precomputed Data Loading: One-time preprocessing of k-hop subgraphs to eliminate redundant graph traversals (2-5× training speedup). - Distributed Data Parallel Training: Multi-GPU support for scaling to larger knowledge graphs (tested on 4× NVIDIA A100 GPUs at NERSC Perlmutter). - Mixed Precision Training: Automatic mixed precision (AMP) for memory efficiency and faster training. Advantages Over Standard Knowledge Graph Embedding Models: Combines RelGT's proven multi-element tokenization (features, type, hop, structure) with graph-native biological representations, enabling interpretable link prediction across heterogeneous entities that standard embedding models (TransE, RotatE, ComplEx) and table-based transformers cannot directly model. Achieves near-perfect performance on microbial growth media prediction (MRR: 0.9966, Precision@1: 0.9932, Hit@10: 1.0000) while maintaining explainability through attention-based reasoning over biological pathways. Training Data: - KG-Microbe merged knowledge graph: 1,379,337 nodes, 2,960,472 edges - 24 biological relation types including taxonomic hierarchies, metabolic interactions, phenotype associations, and environmental relationships - Primary prediction task: Growth media suitability for microbial taxa (biolink:occurs_in, 50K edges) - Multi-relation capability: Predicts links for any of the 24 relation types, including chemical consumption/production, phenotype associations, and taxonomic classification Citation: Original RelGT Architecture: Dwivedi et al., "Relational Graph Transformer", arXiv:2505.10960, 2025 KOGUT Implementation: Knowledge Oriented Graph Unified Transformer for Microbial Growth Media Prediction Developed at Lawrence Berkeley National Laboratory (LBNL) Trained on NERSC Perlmutter supercomputer

Joachimiak, Marcin [Lawrence Berkeley National Lab↗
DOE OSTI2025

VA EDH Advanced Software Pipeline Framework Report: Enhancing Automation and Scalability

The VA Environmental Determinants of Health (EDH) Advanced Software Pipeline Framework is designed to enhance the efficiency, scalability, and security of geospatial data processing workflows. This framework integrates modern data orchestration and containerization technologies, including Prefect for workflow automation, Docker for containerization, and PostgreSQL/PostGIS for geospatial data storage and analysis. It ensures standardized, reproducible, and automated data processing, supporting VA objectives related to substance use risk assessment and recovery research. The pipeline addresses key scalability and performance challenges through horizontal and vertical scaling, high-performance computing (HPC) integration, parallel processing, task caching, and dynamic resource allocation. These optimizations improve throughput and reduce latency, allowing the system to efficiently manage large and complex datasets. Additionally, security and compliance measures—such as data encryption (SSL), Role-Based Access Control (RBAC), and adherence to GDPR and HIPAA standards—safeguard sensitive information throughout data transmission and storage. A key implementation of this framework includes the automation of shelter list geolocation workflows, ensuring that up-to-date data is readily available for VA decision-making. Lessons learned from this project include the transition from in-memory processing to incremental storage writes, improving resource management and reliability. Future enhancements aim to expand automation, integrate AI-driven anomaly detection, and incorporate high-performance computing resources. This framework provides a scalable, secure, and adaptable solution for managing geospatial datasets, reinforcing the VA’s ability to support clinical and strategic initiatives through data-driven decision-making.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Validation of Modern Nuclear Data Processing in SCALE

The nuclear data (ND) community is continuously developing more accurate, diversified, and comprehensive data for radiation transport modeling to support the nuclear science community. As these community efforts progress, it is crucial that ND processing tools like AMPX (used for SCALE [1] ND) also be developed in parallel to incorporate these new data into transport codes and actually deliver those data to end users. AMPX is a mature, well-tested code that was developed by many people at Oak Ridge National Laboratory (ORNL) over the course of the past few decades. A large portion of the AMPX codebase, however, was outdated, difficult to maintain, and incompatible with modern code development tools. Some of the most important parts of the AMPX code have now been replaced with modern C++ code that can be maintained more cost-effectively and can be tested more rigorously.

AMPX↗
DOE OSTI2024

Electron Heating in 2D Particle-in-cell Simulations of Quasi-perpendicular Low-beta Shocks

Abstract We measure the thermal electron energization in 1D and 2D particle-in-cell simulations of quasi-perpendicular, low-beta ( β p = 0.25) collisionless ion–electron shocks with mass ratio m i / m e = 200, fast Mach number M ms = 1 –4, and upstream magnetic field angle θ Bn = 55°–85° from the shock normal n ˆ . It is known that shock electron heating is described by an ambipolar, B -parallel electric potential jump, Δ ϕ ∥ , that scales roughly linearly with the electron temperature jump. Our simulations have Δ ϕ ∥ / ( 0.5 m i u sh 2 ) ∼ 0.1 –0.2 in units of the pre-shock ions’ bulk kinetic energy, in agreement with prior measurements and simulations. Different ways to measure ϕ ∥ , including the use of de Hoffmann–Teller frame fields, agree to tens-of-percent accuracy. Neglecting off-diagonal electron pressure tensor terms can lead to a systematic underestimate of ϕ ∥ in our low- β p shocks. We further focus on two θ Bn = 65° shocks: a M s = 4 ( M A = 1.8 ) case with a long, 30 d i precursor of whistler waves along n ˆ , and a M s = 7 ( M A = 3.2 ) case with a shorter, 5 d i precursor of whistlers oblique to both n ˆ and B ; d i is the ion skin depth. Within the precursors, ϕ ∥ has a secular rise toward the shock along multiple whistler wavelengths and also has localized spikes within magnetic troughs. In a 1D simulation of the M s = 4 , θ Bn = 65° case, ϕ ∥ shows a weak dependence on the electron plasma-to-cyclotron frequency ratio ω pe /Ω ce , and ϕ ∥ decreases by a factor of 2 as m i / m e is raised to the true proton–electron value of 1836.

Tran, Aaron (ORCID:0000000334834890)↗
NASA NTRS1972

Monitoring changing geologic features along the Texas Gulf Coast

The author has identified the following significant results. Water truth observations, NASA aerial photography from an altitude of 60,000 feet, and ERTS-1 imagery made off the South Texas coast showed a mutually consistent pattern of water turbidity in the Gulf of Mexico. At the time of the measurements, plumes of turbid water were being formed by ebb-tidal discharges from the bays through tidal passes and were being diverted southward by the coastwise drift. The occurrence of the bands of turbid and relatively clear water suggests the existence of large scale helical circulation cells having axes almost parallel to shore with the outer turbid band probably being a zone of surface divergence and bottom water upwelling. The impingement of a turbid water mass onto the shoreline suggests that some, and perhaps most, of the suspended sediment in nearshore waters may not have been stirred up from the nearshore sea floor but may have traveled long distances in the water mass, perhaps even having remained in suspension from the time of its entry into the Gulf tidal inlets such as Aransas Pass.

Hunter, R. E.↗
NASA NTRS1982

Highlights of theoretical progress related to the International Magnetospheric Study

U.S. theoretical research efforts have addressed three areas within the International Magnetospheric Study. The first, solar wind/magnetosphere interaction, is presently concerned with the suggestion that magnetic merging may predominantly occur near the polar cusps rather than near the subsolar point. Mechanisms have been proposed for noncollisional diffusion of solar wind plasma across the closed magnetopause entailed by such a phenomenon. The second area considers the importance to magnetotail dynamics of a continuous source of solar wind plasma, and of sporadic plasma loss associated with an unsteady convection cycle. In the third area, the electrodynamic magnetosphere/ionosphere interaction, an advanced state has been reached in the understanding of the relevant physics, with respect both to coupling in the subauroral region and the large scale structure of auroral zone electric fields parallel, and perpendicular to, the magnetic field.

Hill, T. W.↗
NASA NTRS1984

Sonic-Pump Levitator

Audiospeaker drives gas and rapidly responds to corrective signals. Audiospeaker drives gas through plate opening and columnar outlets to levitate sphere. Exhaust flow dominated by gas momentum and essentially parallel to axis of outlets. With appropriate scaling up of hardware, sonic pump can function as levitator for containerless processing of more massive specimens of higher densities and of different materials.

Dunn, S. A.↗
NASA NTRS1988

An example of the association of X-ray and UV emission with H-alpha surges

From H-alpha UV, and X-ray data, the nature of a well-observed surge on November 12, 1980 has been studied to try to understand the relationships between the mechanical motions and the high-temperature emissions. The cool (H-alpha) and the hot (O v) parts of the surge plasma both show velocities in the range of 100-120 km/s. The kinetic and potential energies of the surge are two orders of magnitude higher than the radiative energy. The observations suggest that the surge occurs in open structures parallel to one leg of a large scale coronal magnetic loop. The energy is released principally in the open structure (surge) and only a small amount heats the coronal loop (X-ray signature). This energy division should probably not be treated as a general characteristic of surge events. Different events are expected to exhibit a different energy balance, and this can account for the lack of a consensus in the previous literature regarding surge/X-ray associations.

Schmieder, B.↗
NASA NTRS2003

Aircraft Engine Noise Scattering by Fuselage and Wings: A Computational Approach

The paper presents a time-domain method for computation of sound radiation from aircraft engine sources to the far field. The effects of non-uniform flow around the aircraft and scattering of sound by fuselage and wings are accounted for in the formulation. The approach is based on the discretization of the inviscid flow equations through a collocation form of the discontinuous Galerkin spectral element method. An isoparametric representation of the underlying geometry is used in order to take full advantage of the spectral accuracy of the method. Large-scale computations are made possible by a parallel implementation based on message passing. Results obtained for radiation from an axisymmetric nacelle alone are compared with those obtained when the same nacelle is installed in a generic configuration, with and without a wing. 0 2002 Elsevier Science Ltd. All rights reserved.

Farassat, F.↗