SEARCH · Engineering Papers

Results for “Distributed computation”

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

SourceResearch connectionFrom yearThrough year

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

At least 1,135 records · Page 63

All sources NASA NTRS DOE OSTI

DOE OSTI2026

iDDS: intelligent distributed dispatch and scheduling for workflow orchestration

The intelligent distributed dispatch and scheduling (iDDS) service is a versatile workflow orchestration system designed for large-scale, distributed scientific computing. iDDS extends traditional workload and data management by integrating data-aware execution, conditional logic, and programmable workflows, enabling automation of complex and dynamic processing pipelines. Originally developed for the ATLAS experiment at the large hadron collider, iDDS has evolved into an experiment-agnostic platform that supports both template-driven workflows and a Function-as-a-Task model for Python-based orchestration. This paper presents the architecture and core components of iDDS, highlighting its scalability, modular message-driven design, and integration with systems such as PanDA and Rucio. We demonstrate its versatility through real-world use cases: fine-grained tape resource optimization for ATLAS, orchestration of large Directed Acyclic Graph (DAG) workflows for the Rubin Observatory, distributed hyperparameter optimization for machine learning applications, active learning for physics analyses, and AI-assisted detector design at the electron–ion collider. By unifying workload scheduling, data movement, and adaptive decision-making, iDDS reduces operational overhead and enables reproducible, high-throughput workflows across heterogeneous infrastructures. We conclude with current challenges and future directions, including interactive, cloud-native, and serverless workflow support.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

CT dose equilibration and energy absorption in polyethylene cylinders with diameters from 6 to 55 cm

Purpose: ICRU Report No. 87 Committee and AAPM Task Group 200 designed a three-sectional polyethylene phantom of 30 cm in diameter and 60 cm in length for evaluating the midpoint dose D{sub L}(0) and its rise-to-the-equilibrium curve H(L) = D{sub L}(0)/D{sub eq} from computed tomography (CT) scanning, where D{sub eq} is the equilibrium dose. To aid the use of the phantom in radiation dose assessment and to gain an understanding of dose equilibration and energy absorption in polyethylene, the authors evaluated the short (20 cm) to long (60 cm) phantom dose ratio with a polyethylene diameter of 30 cm, assessed H(L) in polyethylene cylinders of 6–55 cm in diameters, and examined energy absorption in these cylinders. Methods: A GEANT4-based Monte Carlo program was used to simulate the single axial scans of polyethylene cylinders (diameters 6–55 cm and length 90 cm, as well as diameter 30 cm and lengths 20 and 60 cm) on a clinical CT scanner (Somatom Definition dual source CT, Siemens Healthcare). Axial dose distributions were computed on the phantom central and peripheral axes. An average dose over the central 23 or 100 mm region was evaluated for modeling dose measurement using a 0.6 cm{sup 3} thimble chamber or a 10 cm long pencil ion chamber, respectively. The short (20 cm) to long (90 cm) phantom dose ratios were calculated for the 30 cm diameter polyethylene phantoms scanned at four tube voltages (80–140 kV) and a range of beam apertures (1–25 cm). H(L) was evaluated using the dose integrals computed with the 90 cm long phantoms. The resultant H(L) data were subsequently used to compute the fraction of the total energy absorbed inside or outside the scan range (E{sub in}/E or E{sub out}/E) on the phantom central and peripheral axes, where E = LD{sub eq} was the total energy absorbed along the z axis. Results: The midpoint dose in the 60 cm long polyethylene phantom was equal to that in the 90 cm long polyethylene phantom. The short-to-long phantom dose ratios changed with beam aperture and phantom axis but were insensitive to tube voltage. H(L) was insensitive to tube voltage and CT scanner model. As phantom diameter increased from 6 to 55 cm, E{sub in}/E generally decreased but asymptotically approached constant levels on the peripheral axes of large phantoms. The curve of E{sub in}/E versus scan length was almost identical to that of H(L). Similarly, E{sub out}/E increased with scan length and asymptotically approached the equilibrium for large scan lengths. E{sub out}/D{sub eq} was much less than the equilibrium length L{sub eq} where H(L) = 0.98, even with scan lengths much larger than L{sub eq}. Conclusions: The polyethylene phantom designed by ICRU Report No. 87 Committee and AAPM Task Group 200 is adequately long for assessing the midpoint dose and its equilibration in CT scanning. The short-to-long phantom dose ratios and the H(L) data provided in this paper allow easy evaluations of the midpoint dose, longitudinal dose distribution, and energy absorption in polyethylene phantoms. The results of dose equilibration and energy absorption presented herein may be insightful for the clinical CT scans with various subject sizes and scan lengths.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2021

Iteration-based Linearized Distribution-level Locational Marginal Price for Three-phase Unbalanced Distribution Systems

Distributed energy resources (DERs) are rocking the utilities’ business landscape. It calls for competitive market environments that incentivize DERs to form maximum operating efficiency. Among proposed pricing schemes, distribution-level locational marginal price (DLMP) is effective in signaling the marginal generation cost differences driven by energy losses and network constraints. It can be derived from a distribution-level optimal power flow (OPF) framework, as it essentially presents the sensitivity of optimized generation cost towards incremental loads. However, due to the high resistance-to-inductance ratio and unbalanced characteristics of distribution networks, computational affordable DLMPs are highly challenged. This article provides a linear-approximated DLMP that can be solved efficiently and generalized to account for reactive power flow, three-phase unbalanced loads and meshed network structure. The successive linear programming technique is introduced to enhance the model accuracy. Case studies on an IEEE 123-Bus system validate its accuracy against a nonlinear benchmark and capability in offering proper incentives.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Generating Massive Scale-free Networks: Novel Parallel Algorithms using the Preferential Attachment Model

Recently, there has been substantial interest in the study of various random networks as mathematical models of complex systems. As real-life complex systems grow larger, the ability to generate progressively large random networks becomes all the more important. This motivates the need for efficient parallel algorithms for generating such networks. Naïve parallelization of sequential algorithms for generating random networks is inefficient due to inherent dependencies among the edges and the possibility of creating duplicate (parallel) edges. In this article, we present message passing interface-based distributed memory parallel algorithms for generating random scale-free networks using the preferential-attachment model. Our algorithms are experimentally verified to scale very well to a large number of processing elements (PEs), providing near-linear speedups. The algorithms have been exercised with regard to scale and speed to generate scale-free networks with one trillion edges in 6 minutes using 1,000 PEs.

97 MATHEMATICS AND COMPUTING↗

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 OSTI2015

SU-E-T-94: An Advanced Rotating Gamma Ray System for Stereotactic Radiosurgery

Purpose: Co-60 beams have unique dosimetric properties that are ideally suited for cranial treatments. Co-60 sources with cone-shaped collimators provide conformal dose distributions allowing for ablative treatments with rapid dose falloff to spare nearby critical structures. This work investigates a novel, image-guided, rotational Gamma ray system that provides both superior dose conformity/gradient and accurate stereotaxy for stereotactic radiosurgery (SRS). Methods: The SupeRay system (Cyber Medical Corp., China) consists of a rotating source chamber containing 30 gamma sources focusing at the isocenter with 4 collimators measuring 3, 4, 8 and 16mm in diameter. A novel switch design enables the 30 Gamma sources to be turned off at any arbitrarily selected 60° interval in order to avoid critical structures. The 3D treatment couch provides automatic treatment positioning between individual shots and the kV imaging system provides orthogonal images with a spatial resolution of 0.24mm to facilitate target localization. Monte Carlo simulations were used to compute dose distributions and compare with measurements and other Gamma ray SRS systems. Results: Monte Carlo results confirmed the SupeRay design parameters including output factors and 3D dose distributions. Its beam penumbra/dose gradient is similar to or slightly better than that of the Elekta Gamma Knife. The penumbra in the (x,y,z) direction was (7.38mm,7.38mm,3.86mm) for the 16mm collimator, (4.83mm,4.83mm,3.12mm) for the 8mm collimator, and (3.03mm,3.03mm,2.38mm) for the 4mm collimator, respectively, on the SupeRay system while it was (9.5mm,10.0mm,2.9mm), (4.3mm,4.3mm,2.9mm) and (3.2mm,3.2mm,1.9mm) for the same collimator sizes, respectively, on the Perfexion system. The kV imaging system together with a non-invasive relocatable frame provides accurate target localization (<0.5mm) for cases requiring multiple treatment fractions. Conclusion: Because of the unique dosimetric properties of Co-60 sources and its accurate stereotaxy/dose delivery, SupeRay is ideally suited for single and multiple-session ablative treatments of cranial lesions. This work was partially supported by Cyber Medical Corp.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2013

Large-Scale Optimization for Bayesian Inference in Complex Systems

The SAGUARO (Scalable Algorithms for Groundwater Uncertainty Analysis and Robust Optimization) Project focused on the development of scalable numerical algorithms for large-scale Bayesian inversion in complex systems that capitalize on advances in large-scale simulation-based optimization and inversion methods. The project was a collaborative effort among MIT, the University of Texas at Austin, Georgia Institute of Technology, and Sandia National Laboratories. The research was directed in three complementary areas: efficient approximations of the Hessian operator, reductions in complexity of forward simulations via stochastic spectral approximations and model reduction, and employing large-scale optimization concepts to accelerate sampling. The MIT₋Sandia component of the SAGUARO Project addressed the intractability of conventional sampling methods for large-scale statistical inverse problems by devising reduced-order models that are faithful to the full-order model over a wide range of parameter values; sampling then employs the reduced model rather than the full model, resulting in very large computational savings. Results indicate little effect on the computed posterior distribution. On the other hand, in the Texas₋Georgia Tech component of the project, we retain the full-order model, but exploit inverse problem structure (adjoint-based gradients and partial Hessian information of the parameter-to-observation map) to implicitly extract lower dimensional information on the posterior distribution; this greatly speeds up sampling methods, so that fewer sampling points are needed. We can think of these two approaches as "reduce then sample" and "sample then reduce." In fact, these two approaches are complementary, and can be used in conjunction with each other. Moreover, they both exploit deterministic inverse problem structure, in the form of adjoint-based gradient and Hessian information of the underlying parameter-to-observation map, to achieve their speedups.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

GridAPPS-D Conceptual Design v1.0

The purpose of this document is to provide a conceptual design of the distribution system application development platform being developed for the U.S. Department of Energy’s Advanced Distribution Management System (ADMS) Program by the Grid Modernization Laboratory Consortium project GM0063. The platform will be referred to as GridAPPS-D. This document provides a high level, conceptual view of the platform and provides related background and contextual information. This document is intended to both educate readers about the technical work of the project and to serve as a point of reference for the project team. The document will be updated as the project progresses.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

T-FSM: A Scalable Distributed Task-Based System for Frequent Subgraph Pattern Mining from a Big Graph

Finding frequent subgraph patterns in a big graph is an important problem with many applications such as classifying chemical compounds and building indexes to speed up graph queries. Since this problem is NP-hard, some recent parallel and distributed systems have been developed to accelerate the mining. However, they often have a huge memory cost, very long running time, suboptimal load balancing, poor scale-out capability, and possibly inaccurate results. In this article, we propose an efficient system called T-FSM for parallel mining of frequent subgraph patterns in a big graph. T-FSM supports a new anti-monotonic frequentness measure called Fraction-Score, which is more accurate than the widely used MNI measure. The execution engine of T-FSM supports both intra-machine parallelism and inter-machine parallelism. For intra-machine parallelism, T-FSM adopts a novel task-based execution model to ensure high multithreading concurrency, bounded memory consumption, and effective load balancing. For inter-machine parallelism, T-FSM ensures good scale-out performance with a lightweight pattern rebalancing approach that reduces workload skewness of pattern evaluations among machines. To avoid recomputing the contexts for migrated patterns, we design a novel context cache table to support concurrent and asynchronous requesting and caching of remote context data, which can timely evict and garbage collect used pattern contexts that are no longer needed to keep memory consumption bounded. Extensive experiments show that T-FSM is orders of magnitude faster than existing state-of-the-art parallel systems (more than 10×, 51×, 131×, 55× speedup over ScaleMine, DistGraph, Pangolin and Peregrine, respectively) and distributed systems (more than 42× and 88× over ScaleMine and DistGraph, respectively) for frequent subgraph pattern mining, and it scales out satisfactorily to 512 CPU cores on the Polaris supercomputer at Argonne National Laboratory.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2010

Polyphony: A Workflow Orchestration Framework for Cloud Computing

Cloud Computing has delivered unprecedented compute capacity to NASA missions at affordable rates. Missions like the Mars Exploration Rovers (MER) and Mars Science Lab (MSL) are enjoying the elasticity that enables them to leverage hundreds, if not thousands, or machines for short durations without making any hardware procurements. In this paper, we describe Polyphony, a resilient, scalable, and modular framework that efficiently leverages a large set of computing resources to perform parallel computations. Polyphony can employ resources on the cloud, excess capacity on local machines, as well as spare resources on the supercomputing center, and it enables these resources to work in concert to accomplish a common goal. Polyphony is resilient to node failures, even if they occur in the middle of a transaction. We will conclude with an evaluation of a production-ready application built on top of Polyphony to perform image-processing operations of images from around the solar system, including Mars, Saturn, and Titan.

Space Exploration,↗

DOE OSTI2015

Spatial fractionation of the dose using neon and heavier ions: A Monte Carlo study

Purpose: This work explores a new radiation therapy approach which might trigger a renewed use of neon and heavier ions to treat cancers. These ions were shown to be extremely efficient in radioresistant tumor killing. Unfortunately, the efficient region also extends into the normal tissue in front of the tumor. The strategy the authors propose is to profit from the well-established sparing effect of thin spatially fractionated beams, so that the impact on normal tissues might be minimized while a high tumor control is achieved. The main goal of this work is to provide a proof of concept of this new approach. With that aim, a dosimetric study was carried out as a first step to evaluate the interest of further explorations of this avenue. Methods: The GATE/GEANT4 v.6.1 Monte Carlo simulation platform was employed to simulate arrays of rectangular minibeams (700 μm × 2 cm) of four ions (Ne, Si, Ar, and Fe). The irradiations were performed with a 2 cm-long spread-out Bragg peak centered at 7 cm-depth. Dose distributions in a water phantom were scored considering two minibeams center-to-center distances: 1400 and 3500 μm. Peak and valley doses, peak-to-valley dose ratios (PVDRs), beam penumbras, and relative contribution of nuclear fragments and electromagnetic processes were assessed as figures of merit. In addition, the type and proportion of the secondary nuclear fragments were evaluated in both peak and valley regions. Results: Extremely high PVDR values (>100) and low valley doses were obtained. The higher the atomic number (Z) of the primary ion is, the lower the valleys and the narrower the penumbras. Although the yield of secondary nuclear products increases with Z, the actual dose being deposited by the secondary nuclear fragments in the valleys starts to be the dominant contribution at deeper points, helping in the sparing of proximal normal tissues. Additionally, a wider center-to-center distance leads to a minimized contribution of heavier secondary fragments in valleys. Conclusions: The computed dose distributions suggest that a spatial fractionation of the dose combined to the use of submillimetric field sizes might allow profiting from the high efficiency of neon and heavier ions for the treatment of radioresistant tumors, while preserving normal tissues. The authors’ results support the further exploration of this avenue. Next steps include the realization of biological experiment to confirm the shifting of normal tissue complication probability curves.

60 APPLIED LIFE SCIENCES↗

NASA NTRSDate not supplied

Optimal Communication Topology Determination and Sensor Selection for Independent Airspace Surveillance

The paper presents an approach to sensors selection and network topology determination for independent airspace surveillance with maximum outcome and minimum cost using ground based distributed sensing, computing and communication network infrastructure. The selection criteria includes minimum estimation error, maximum airspace coverage, minimum communication time and power consumption while guaranteeing the system observability and providing in-time quality information to a monitoring observer. The developed algorithm uses multi-objective optimization strategy taking into account trade-offs between conflicting objectives and relaxations for in time implementation. It is implemented utilizing graph theoretic tools. The approach is validated in a desktop simulation environment using synthetic sensors data generated for a simulated multi-vehicle flight scenario in the selected regional airspace.

Distributed sensing↗

NASA NTRSDate not supplied

Separation and Transition on the ROTEX-T Cone-Flare

As part of NATO STO AVT-346 “Predicting Hypersonic Boundary-Layer Transition on Complex Geometries,” coordinated experimental and computational studies were conducted on the ROTEX-T, a cone-flare geometry used in a successful flight-test experiment. At the as-flown conditions, a separation bubble existed at the compression corner. Separation, reattachment, and the multifaceted linear instability paths leading this bubble to transition to turbulence are challenging to predict, but have significant impact on surface pressure and heat flux. High-resolution background-oriented schlieren and infrared thermography measurements were made in the AFOSR–Notre Dame Large Mach-6 Quiet Tunnel at freestream unit Reynolds numbers from 5.8×10(exp 6) to 12.2×10(exp 6) m-1and nominally zero angle of attack. High-speed self-aligned focusing schlieren, infrared thermography, and focused laser differential interferometry measurements were made in the AFRL Mach-6 Ludwieg Tube from 2.2×10(exp 6) to 24.7×10(exp 6) m-1and nominally zero degrees angle of attack. The surface heat-flux and Stanton number distributions were computed. Separation and reattachment locations, as well as the flow state at each, were determined from the combination of surface and off-wall measurements. The convective and global boundary-layer instabilities of the axisymmetric laminar flow at the experimental conditions were investigated computationally. Amplification of Mack’s first and second modes were observed to have logarithmic amplification factors between 5 to 7.5 at the separation location, depending on conditions. The flow was found to be globally unstable to stationary three-dimensional disturbances concentrated in the reattachment region. Previous analysis of the ROTEX-T flight data had not assessed reattachment location or the flow state upon reattachment. Thanks to the insights gained from the coordinated, on- and off-wall ground-test measurements, these evaluations have now been made. The separation location indicated by laminar simulations is consistently numerically predicted to be upstream of the experimentally observed location for a transitional separation bubble. The cause of this difference is understood to lie in the steady-state and axisymmetric assumptions made by both solvers employed to compute the basic states analyzed, as flow topology considerations assert that unsteady two-dimensional or axisymmetric separation bubbles are structurally unstable and will become three-dimensional. Computed laminar heating rates prior to separation agreed well with experiment; transitional heating rates after reattachment were between laminar and turbulent computations.

CFD Validation↗

NASA NTRSDate not supplied

Separation and Transition on the ROTEX-T Cone-Flare

CFD Validation↗

DOE OSTI2018

On Eigenfunctions of the Fourier Transform

A nontrivial example of an eigenfunction in the sense of the theory of distributions for the planar Fourier transform was described by the authors in their previous work. In this paper, a method for obtaining other eigenfunctions is proposed. Positive homogeneous distributions in ℝ{sup n} of order −n/2 are considered, and it is shown that F(ω)|x|{sup −n/2}, |ω| = 1, is an eigenfunction in the sense of the theory of distributions of the Fourier transform if and only if F(ω) is an eigenfunction of a certain singular integral operator on the unit sphere of ℝ{sup n}. Since Y{sub m,n}{sup (k)}(ω)|x|{sup −n/2}, where Y{sub m,n}{sup (k)} denote the spherical functions of order m in ℝ{sup n}, are eigenfunctions of the Fourier transform, it follows that Y{sub m,n}{sup (k)} are eigenfunctions of the above-mentioned singular integral operator. In the planar case, all eigenfunctions of the Fourier transform of the form F(ω)|x|{sup −1} are described by means of the Fourier coefficients of F(ω).

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Clustering at Massive Scale

ClaMS provides hierarchical clustering technology for use on massive, high-dimensional datasets that require distributed memory for processing. The algorithm employed is inspired by the popular HDBSCAN algorithm but makes use of computational kernels better suited for distributed computing. ClaMS is built on scalable nearest neighbor graph construction, metric forest completion, and approximate minimum spanning tree techniques.

Stanley, ThomasA [Lawrence Livermore National Labo↗

DOE OSTI2019

Using Computational Fluid Dynamics of Wind Simulations Coupled With Weather Data to Calculate Dynamic Line Ratings

Dynamic line rating is a technology that allows for the rating of electrical conductors to be calculated based on local weather conditions rather than using ”worst-case” assumptions of weather conditions. The static ratings are typically based on weather conditions that are conservative in nature, and thus dynamic line rating may provide room to increase the current capacity. The local weather conditions may estimate conditions more accurately near the transmission lines accounting for terrain such as nearby hills. One way to estimate the local weather conditions is through the use of computational fluid dynamics. The results of a wind field simulation can be coupled with sparsely located weather stations to provide an accurate assessment of the wind speeds along the path of the conductor. Here, the wind field simulations are calculated using a steady state Reynolds-averaged Navier-Stokes model. These results along with local solar radiance measurements can be used to provide estimates of the steady state ampacity with the standard IEEE equations. An advanced test case for this process involves performing these simulations in a complex terrain, Hells Canyon, the deepest river gorge in North America. The results show that by using weather-based sensors without considering localized wind conditions, the available ampacity may be over-predicted significantly.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Modular chip-integrated photonic control of artificial atoms in diamond waveguides

A central goal in creating long-distance quantum networks and distributed quantum computing is the development of interconnected and individually controlled qubit nodes. Atom-like emitters in diamond have emerged as a leading system for optically networked quantum memories, motivating the development of visible-spectrum, multi-channel photonic integrated circuit (PIC) systems for scalable atom control. However, it has remained an open challenge to realize optical programmability with a qubit layer that can achieve high optical detection probability over many optical channels. Here, we address this problem by introducing a modular architecture of piezoelectrically actuated atom-control PICs (APICs) and artificial atoms embedded in diamond nanostructures designed for high-efficiency free-space collection. The high-speed four-channel APIC is based on a splitting tree mesh with triple-phase shifter Mach–Zehnder interferometers. This design simultaneously achieves optically broadband operation at visible wavelengths, high-fidelity switching (>40dB) at low voltages, submicrosecond modulation timescales (>30MHz), and minimal channel-to-channel crosstalk for repeatable optical pulse carving. Via a reconfigurable free-space interconnect, we use the APIC to address single silicon vacancy color centers in individual diamond waveguides with inverse tapered couplers, achieving efficient single photon detection probabilities (∼15%) and second-order autocorrelation measurements g (2) (0)<0.14 for all channels. The modularity of this distributed APIC–quantum memory system simplifies the quantum control problem, potentially enabling further scaling to thousands of channels.

47 OTHER INSTRUMENTATION↗