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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Temporal data system

A method for processing data is provided. Data is identified by a computer system. The data is processed in parallel by the computer system using temporal transformations to form pieces of temporal data. The pieces of temporal data are placed by the computer system in an order as the pieces of temporal data are generated by the temporal transformations to form a sequence of temporal data. The order of the sequence is based on a priority of when the pieces of temporal data should be processed, enabling performing an action.

Naegle, John H.↗
DOE OSTI2020

PREEMPT: Scalable Epidemic Interventions Using Submodular Optimization on Multi-GPU Systems

Preventing and slowing the spread of epidemics is achieved through techniques such as vaccination and social distancing. Given practical limitations on the number of vaccines and cost of administration, optimization becomes a necessity. Previous approaches using mathematical programming methods have shown to be effective but are limited by computational costs. In this work, we make several contributions: First, we present a new approach for intervention via maximizing the influence of vaccinated nodes on the network. We call this method \preempt. Next, we prove submodular properties associated with the objective function of our method so that it aids in construction of an efficient greedy approximation strategy. Consequently, we present a new parallel algorithm based on greedy hill climbing for \preempt, and present an efficient parallel implementation for distributed CPU-GPU heterogeneous platforms. Our results demonstrate that \preempt{} is able to achieve a significant reduction (up to 6.75$\times$) in the percentage of people infected on a city-scale network. We also show strong scaling results of \preempt{} on 128 nodes of the Summit supercomputer. Our parallel implementation is able to significantly reduce time to solution, from hours to minutes on large networks. This work represents a first-of-its-kind effort in parallelizing greedy hill climbing and applying it toward devising effective interventions for epidemics.

Minutoli, Marco↗
DOE OSTI2013

Reducing uncertainty in personnel dosimetry calculations in the VHTR plant using MAVRIC

This work analyzes the efficacy of the MAVRIC sequence of the Scale 6.1 code package with respect to the accuracy of results and the ability to utilize large-memory, parallel machines. MAVRIC implements the hybrid FW-CADIS methodology to solve neutron and photon transport for shielding applications. Using the discrete ordinates method to solve the Boltzmann transport equation, an importance map is generated which MAVRIC then uses to bias a stochastic Monte Carlo simulation. The MAVRIC sequence is applied to generate neutron and photon dose rate distributions of improved accuracy in a model of a proposed VHTR power plant. Problems like this one, with a size on the order of magnitude of a nuclear power plant, require a prohibitive amount of memory to store complete importance maps. The issue is addressed by refining the mesh in areas around the source through the detector regions, while leaving a coarse mesh elsewhere. Additionally through the use of parallel computing, the angular flux can be expanded in higher quadrature sets, which leads to a better importance map while requiring no extra memory requirements during the Monte Carlo portion of the sequence. The final Monte Carlo simulations can be run concurrently on several machines with results combined after the fact, emulating parallelism that is not yet available in MAVRIC sequence. Using a combination of strategies, the MAVRIC sequence is shown to be able to scale across available computational resources, allowing the user to more quickly obtain Monte Carlo results with lower relative uncertainties in large, deep-penetration shielding problems. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Mesoscopic Modeling and Rapid Simulation of Incremental Changes in Epidemic Scenarios on GPUs

In simulation-based studies and analyses of epidemics, a major challenge lies in resolving the conflict between fidelity of models and the speed of their simulation. Another related challenge arises in dealing with the large number of what–if scenarios that need to be explored. Here, we describe new computational methods that together provide an approach to dealing with both challenges. A mesoscopic modeling approach is described that strikes a middle ground between macroscopic models based on coupled differential equations and microscopic models built on fine-grained behaviors at the individual entity level. The mesoscopic approach offers the ability to incorporate complex compositions of multiple layers of dynamics even while retaining the potential for aggregate behaviors at varying levels. It also is an excellent match to the accelerator-based architectures of modern computing platforms in which graphical processing units (GPUs) can be exploited for fast simulation via the parallel execution mode of single instruction multiple thread (SIMT). The challenge of simulating a large number of scenarios is addressed via a method of sharing model state and computation across a tree of what–if scenarios that are localized, incremental changes to a large base simulation. A combination of the mesoscopic modeling approach and the incremental what–if scenario tree evaluation has been implemented in the software on modern GPUs. Synthetic simulation scenarios are presented to demonstrate the computational characteristics of our approach. Results from the experiments with large population data, including USA, UK, and India, illustrate the modeling methodology and computational performance on thousands of synthetically generated what–if scenarios. Execution of our implementation scaled to 8192 GPUs of supercomputing platforms demonstrates the ability to rapidly evaluate what–if scenarios several orders of magnitude faster than the conventional methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

TH-CD-201-05: Characterization of a Novel Light-Collimating Tank Optical-CT System for 3D Dosimetry

Purpose: Comprehensive 3D dosimetry is highly desirable for advanced clinical QA, but costly optical readout techniques have hindered widespread implementation. Here, we present the first results from a cost-effective Integrated-lens Dry-tank Optical Scanner (IDOS), designed for convenient 3D dosimetry readout of radiochromic plastic dosimeters (e.g. PRESAGE). Methods: The scanner incorporates a novel transparent light-collimating tank, which collimates a point light source into parallel-ray CT geometry. The tank was designed using an in-house Monte-Carlo optical ray-tracing simulation, and was cast in polyurethane using a 3D printed mould. IDOS spatial accuracy was evaluated by imaging a set of custom optical phantoms, with comparison to x-ray CT images. IDOS dose measurement performance was assessed by imaging PRESAGE dosimeters irradiated with simple known dose distributions (e.g., 4 field box 6MV treatment with Varian Linac). Direct comparisons were made to images from our gold standard DLOS scanner and calculated dose distributions from a commissioned Eclipse planning system. Results: All optical CT images were reconstructed at 1mm isotropic resolution. Comparison of IDOS and x-ray CT images of the geometric phantom demonstrated excellent IDOS geometric accuracy (sub-mm) throughout the dosimeter. IDOS measured 3D dose distribution agreed well with prediction from Eclipse, with 95% gamma pass rate at 3%/3mm. Cross-scanner dose measurement gamma analysis shows >90% of pixels passing at 3%/3mm. Conclusion: The first prototype of the IDOS system has demonstrated promising performance, with accurate dosimeter readout and negligible spatial distortion. The use of optical simulations and 3D printing to create a light collimating-tank has dramatically increased convenience and reduced costs by removing the need for expensive lenses and large volumes of refractive matching fluids.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Parallel Ellipsoidal Perfectly Matched Layers for Acoustic Helmholtz Problems on Exterior Domains

Exterior acoustic problems occur in a wide range of applications, making the finite element analysis of such problems a common practice in the engineering community. Various methods for truncating infinite exterior domains have been developed, including absorbing boundary conditions, infinite elements, and more recently, perfectly matched layers (PML). PML are gaining popularity due to their generality, ease of implementation, and effectiveness as an absorbing boundary condition. PML formulations have been developed in Cartesian, cylindrical, and spherical geometries, but not ellipsoidal. In addition, the parallel solution of PML formulations with iterative solvers for the solution of the Helmholtz equation, and how this compares with more traditional strategies such as infinite elements, has not been adequately investigated. In this study, we present a parallel, ellipsoidal PML formulation for acoustic Helmholtz problems. To faciliate the meshing process, the ellipsoidal PML layer is generated with an on-the-fly mesh extrusion. Though the complex stretching is defined along ellipsoidal contours, we modify the Jacobian to include an additional mapping back to Cartesian coordinates in the weak formulation of the finite element equations. This allows the equations to be solved in Cartesian coordinates, which is more compatible with existing finite element software, but without the necessity of dealing with corners in the PML formulation. Herein we also compare the conditioning and performance of the PML Helmholtz problem with infinite element approach that is based on high order basis functions. On a set of representative exterior acoustic examples, we show that high order infinite element basis functions lead to an increasing number of Helmholtz solver iterations, whereas for PML the number of iterations remains constant for the same level of accuracy. Finally, this provides an additional advantage of PML over the infinite element approach.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

WE-EF-207-10: Striped Ratio Grids: A New Concept for Scatter Estimation

Purpose: To propose a new method for estimating scatter in x-ray imaging. We propose the “striped ratio grid,” an anti-scatter grid with alternating stripes of high scatter rejection (attained, for example, by high grid ratio) and low scatter rejection. To minimize artifacts, stripes are oriented parallel to the direction of the ramp filter. Signal discontinuities at the boundaries between stripes provide information on local scatter content, although these discontinuities are contaminated by variation in primary radiation. Methods: We emulated a striped ratio grid by imaging phantoms with two sequential CT scans, one with and one without a conventional grid, and processed them together to mimic a striped ratio grid. Two phantoms were scanned with the emulated striped ratio grid and compared with a conventional anti-scatter grid and a fan-beam acquisition, which served as ground truth. A nonlinear image processing algorithm was developed to mitigate the problem of primary variation. Results: The emulated striped ratio grid reduced scatter more effectively than the conventional grid alone. Contrast is thereby improved in projection imaging. In CT imaging, cupping is markedly reduced. Artifacts introduced by the striped ratio grid appear to be minimal. Conclusion: Striped ratio grids could be a simple and effective evolution of conventional anti-scatter grids. Unlike several other approaches currently under investigation for scatter management, striped ratio grids require minimal computation, little new hardware (at least for systems which already use removable grids) and impose few assumptions on the nature of the object being scanned.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

High throughput parallel backside contacting and periodic texturing for high-efficiency solar cells

Disclosed are configurations of long-range ordered features of solar cell materials, and methods for forming same. Some features include electrical access openings through a backing layer to a photovoltaic material in the solar cell. Some features include textured features disposed adjacent a surface of a solar cell material. Typically the long-range ordered features are formed by ablating the solar cell material with a laser interference pattern from at least two laser beams.

14 SOLAR ENERGY↗
DOE OSTI2015

Method and apparatus for offloading compute resources to a flash co-processing appliance

Solid-State Drive (SSD) burst buffer nodes are interposed into a parallel supercomputing cluster to enable fast burst checkpoint of cluster memory to or from nearby interconnected solid-state storage with asynchronous migration between the burst buffer nodes and slower more distant disk storage. The SSD nodes also perform tasks offloaded from the compute nodes or associated with the checkpoint data. For example, the data for the next job is preloaded in the SSD node and very fast uploaded to the respective compute node just before the next job starts. During a job, the SSD nodes perform fast visualization and statistical analysis upon the checkpoint data. The SSD nodes can also perform data reduction and encryption of the checkpoint data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Parallel methodology to capture cyclic variability in motored engines

Numerical prediction of of cycle-to-cycle variability (CCV) in SI engines is extremely challenging for two key reasons: (i) high-fidelity methods such as large eddy simulation (LES) are require to accurately capture the in-cylinder turbulent flowfield, and (ii) CCV is experienced over long timescales and hence the simulations need to be performed for hundreds of consecutive cycles. In this study, a new methodology is proposed to dissociate this long time-scale problem into several shorter time-scale problems, which can considerably reduce the computational time without sacrificing the fidelity of the simulations. The strategy is to perform multiple single-cycle simulations in parallel by effectively perturbing the simulation parameters such as the initial and boundary conditions. It is shown that by perturbing the initial velocity field effectively based on the intensity of the in-cylinder turbulence, the mean and variance of the in-cylinder flowfield is captured reasonably well. Adding perturbations in the initial pressure field and the boundary pressure improves the predictions. It is shown that this new approach is able to give accurate predictions of the flowfield statistics in less than one-tenth of time required for the conventional approach of simulating consecutive engine cycles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Robotic Underwater Decontamination Services for Nuclear Applications-18464

Successful Underwater Robotic Decontamination Demonstrates Dose-Saving And Outage-Shortening Technology Diakont successfully provided underwater robotic decontamination services on a North American nuclear power plant's refueling cavity and dryer-separator pool in Spring 2017 using a new tool system. Historically, nuclear plant operators have conducted cleaning and decontamination of these surfaces manually, after draining water from the space. However manual decontamination is slow, and can result in excessive personnel dose exposure. The underwater robotic decontamination services present a vast improvement over manual decontamination because it reduces personnel dose exposure, reduces radwaste, doesn't impact plant chemistry, and doesn't risk inadvertently spreading contamination. Also the new decontamination method avoids the risk of personnel injury and component damage associated with hydrolasing. And by performing the decontamination robotically while the cavities are flooded, in many cases the critical path outage schedule can be shortened. Able to decontaminate horizontal, vertical, and curved surfaces, the decontamination tools easily navigate to areas within flooded cavities that are inaccessible to previous solutions, performing decontamination in parallel to other activities including fuel movement. Also, unlike other legacy solutions, the new tools do not require continuous use of an overhead crane or other method of suspension while performing the decontamination activities. The ROV-type decontamination tool attaches and drives along the cavity and component surfaces using a high-force, no-flow vortex generator, even in the presence of Residual Heat Removal (RHR) or shutdown cooling flow. Efficient, effective cleaning is performed using a rugged brushing action to detach the crud, while vacuuming it away at high flow rates to a submerged filter. At the Spring 2017 refueling outage, the decontamination services with the new methodology were so effective that no additional manual cavity decontamination was required after drain-down. Using the tool's ability to swim, attach, and crawl, field technicians decontaminated the majority of the surfaces designated by the plant operator. Preliminary surveys indicated that all contamination levels were reduced to <50 K dpm/100 cm{sup 2}, helping the utility meet their INPO/Industry collective radiation exposure goals. The new cleaning and decontamination services are ideal for servicing various underwater areas within nuclear power plants such as refueling cavities, BWR-6 drywell heads, spent fuel pools, cask loading pools and fuel transfer canals. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

Parallel Optical Flow Processing of 4D Cardiac CT Data on Multicore Clusters, In: 2014 IEEE 17th International Conference on Computational Science and Engineering

Optical flow is the distribution of apparent velocities of movement of brightness patterns in a sequence of images. For large 3D image sequences, optical flow applications are time consuming and memory-bound. To cope with these problems, in this paper, we present parallel optical flow processing of 4D cardiac CT data on multicore cluster systems to significantly shorten the time for computing velocity fields of the heart in order to aid cardiologists in diagnosing heart disease such as myocardial infarction and cardiac dysrhythmia in time. First, we modify and extend two traditional 2D optical flow methods Horn-Schunck and Lucas-Kanade to three-dimensional cases to process the 4D cardiac CT data. Second, we extend Mat lab MPI to support parallel computing with Mat lab and Octave on these cluster systems. Then we develop the parallel Mat lab/Octave optical flow applications for the 4D cardiac CT data in detail. Our experimental results show that these parallel optical flow applications have good scalability with close to linear speedup, and are able to shorten the image processing time significantly from more than 5 hours on 4 cores to 1.5 minutes on 1024 cores.

Engineering↗
DOE OSTI2020

Evaluation of a pair-based, joint-likelihood association approach for regional infrasound event identification

SUMMARY A Bayesian framework for the association of infrasonic detections is presented and evaluated for analysis at regional propagation scales. A pair-based, joint-likelihood association approach is developed that identifies events by computing the probability that individual detection pairs are attributable to a hypothetical common source and applying hierarchical clustering to identify events from the pair-based analysis. The framework is based on a Bayesian formulation introduced for infrasonic source localization and utilizes the propagation models developed for that application with modifications to improve the numerical efficiency of the analysis. Clustering analysis is completed using hierarchical analysis via weighted linkage for a non-Euclidean distance matrix defined by the negative log-joint-likelihood values. The method is evaluated using regional synthetic data with propagation distances of hundreds of kilometres in order to study the sensitivity of the method to uncertainties and errors in backazimuth and time of arrival. The method is found to be robust and stable for typical uncertainties, able to effectively distinguish noise detections within the data set from those in events, and can be made numerically efficient due to its ease of parallelization.

58 GEOSCIENCES↗
DOE OSTI2019

IMEX HDG-DG: A coupled implicit hybridized discontinuous Galerkin and explicit discontinuous Galerkin approach for shallow water systems

We propose IMEX HDG-DG schemes for planar and spherical shallow water systems. Of interest is subcritical flow, where the speed of the gravity wave is faster than that of nonlinear advection. In order to simulate these flows efficiently, we split the governing system into a stiff part describing the gravity wave and a non-stiff part associated with nonlinear advection. The former is discretized implicitly with the HDG method while an explicit Runge-Kutta DG discretization is employed for the latter. The proposed IMEX HDG-DG framework: 1) facilitates high-order solutions both in time and space; 2) avoids overly small time-step sizes; 3) requires only one linear system solve per time stage; 4) relative to DG generates smaller and sparser linear systems while promoting further parallelism; and 5) suppresses the fast modes in the system with a large time-step size. Numerical results for various test cases demonstrate that our methods are beneficial for applications where non-stiff terms are accurately treated while stiff terms are less accurately handled.

42 ENGINEERING↗
DOE OSTI2014

Quantum transport through the system of parallel quantum dots with Majorana bound states

We study the tunneling transport properties through a system of parallel quantum dots which are coupled to Majorana bound states (MBSs). The conductance and spectral function are computed using the retarded Green's function method based on the equation of motion. The conductance of the system is 2e{sup 2}/h at zero Fermi energy and is robust against the coupling between the MBSs and the quantum dots. The dependence of the Fermi energy on the spectral function is different for the first dot (dot1) than for the second dot (dot2) with fixed dot2-MBSs coupling. The influence of the Majorana bound states on the spectral function was studied for the series and parallel configurations of the system. It was found that when the configuration is in series, the Majorana bound states play an important role, resulting in a spectral function with three peaks. However, the spectral function shows two peaks when the system is in a parallel configuration. The zero Fermi energy spectral function is always 1/2 not only in series but also in the parallel configuration and robust against the coupling between the MBSs and the quantum dots. The phase diagram of the Fermi energy versus the quantum dot energy levels was also investigated.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Cholla-MHD: An Exascale-capable Magnetohydrodynamic Extension to the Cholla Astrophysical Simulation Code

Abstract We present an extension of the massively parallel, GPU native, astrophysical hydrodynamics code Cholla to magnetohydrodynamics (MHD). Cholla solves the ideal MHD equations in their Eulerian form on a static Cartesian mesh utilizing the Van Leer + constrained transport integrator, the HLLD Riemann solver, and reconstruction methods at second and third order. Cholla’s MHD module can perform ≈260 million cell updates per GPU-second on an NVIDIA A100 while using the HLLD Riemann solver and second order reconstruction. The inherently parallel nature of GPUs combined with increased memory in new hardware allows Cholla’s MHD module to perform simulations with resolutions ∼500 3 cells on a single high-end GPU (e.g., an NVIDIA A100 with 80 GB of memory). We employ GPU direct Message Passing Interface to attain excellent weak scaling on the exascale supercomputer Frontier, while using 74,088 GPUs and simulating a total grid size of over 7.2 trillion cells. A suite of test problems highlights the accuracy of Cholla’s MHD module and demonstrates that zero magnetic divergence in solutions is maintained to round off error. We also present new testing and CI tools using GoogleTest, GitHub Actions, and Jenkins that have made development more robust and accurate and ensure reliability in the future.

Astronomy & Astrophysics↗
DOE OSTI2017

Families of Graph Algorithms: SSSP Case Study

Single-Source Shortest Paths (SSSP) is a well-studied graph problem. Examples of SSSP algorithms include the original Dijkstra’s algorithm and the parallel Δ-stepping and KLA-SSSP algorithms. In this paper, we use a novel Abstract Graph Machine (AGM) model to show that all these algorithms share a common logic and differ from one another by the order in which they perform work. We use the AGM model to thoroughly analyze the family of algorithms that arises from the common logic. We start with the basic algorithm without any ordering (Chaotic), and then we derive the existing and new algorithms by methodically exploring semantic and spatial ordering of work. Our experimental results show that new derived algorithms show better performance than the existing distributed memory parallel algorithms, especially at higher scales.

distributed-memory graph algorithms↗
DOE OSTI2015

Bayesian 3D X-ray computed tomography image reconstruction with a scaled Gaussian mixture prior model

In order to improve quality of 3D X-ray tomography reconstruction for Non Destructive Testing (NDT), we investigate in this paper hierarchical Bayesian methods. In NDT, useful prior information on the volume like the limited number of materials or the presence of homogeneous area can be included in the iterative reconstruction algorithms. In hierarchical Bayesian methods, not only the volume is estimated thanks to the prior model of the volume but also the hyper parameters of this prior. This additional complexity in the reconstruction methods when applied to large volumes (from 512{sup 3} to 8192{sup 3} voxels) results in an increasing computational cost. To reduce it, the hierarchical Bayesian methods investigated in this paper lead to an algorithm acceleration by Variational Bayesian Approximation (VBA) [1] and hardware acceleration thanks to projection and back-projection operators paralleled on many core processors like GPU [2]. In this paper, we will consider a Student-t prior on the gradient of the image implemented in a hierarchical way [3, 4, 1]. Operators H (forward or projection) and H{sup t} (adjoint or back-projection) implanted in multi-GPU [2] have been used in this study. Different methods will be evalued on synthetic volume 'Shepp and Logan' in terms of quality and time of reconstruction. We used several simple regularizations of order 1 and order 2. Other prior models also exists [5]. Sometimes for a discrete image, we can do the segmentation and reconstruction at the same time, then the reconstruction can be done with less projections.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗