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At least 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Methods and apparatus for multi-resolution replication of files in a parallel computing system using semantic information

Techniques are provided for storing files in a parallel computing system using different resolutions. A method is provided for storing at least one file generated by a distributed application in a parallel computing system. The file comprises one or more of a complete file and a sub-file. The method comprises the steps of obtaining semantic information related to the file; generating a plurality of replicas of the file with different resolutions based on the semantic information; and storing the file and the plurality of replicas of the file in one or more storage nodes of the parallel computing system. The different resolutions comprise, for example, a variable number of bits and/or a different sub-set of data elements from the file. A plurality of the sub-files can be merged to reproduce the file.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Parallel sort with a ranged, partitioned key-value store in a high perfomance computing environment

Improved sorting techniques are provided that perform a parallel sort using a ranged, partitioned key-value store in a high performance computing (HPC) environment. A plurality of input data files comprising unsorted key-value data in a partitioned key-value store are sorted. The partitioned key-value store comprises a range server for each of a plurality of ranges. Each input data file has an associated reader thread. Each reader thread reads the unsorted key-value data in the corresponding input data file and performs a local sort of the unsorted key-value data to generate sorted key-value data. A plurality of sorted, ranged subsets of each of the sorted key-value data are generated based on the plurality of ranges. Each sorted, ranged subset corresponds to a given one of the ranges and is provided to one of the range servers corresponding to the range of the sorted, ranged subset. Each range server sorts the received sorted, ranged subsets and provides a sorted range. A plurality of the sorted ranges are concatenated to obtain a globally sorted result.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A Modeling Tool to Analyze the Performance of Industrial Cooling Towers

Energy efficiency and energy savings have become an important factor as industries look for ways to save energy and minimize their energy consumption while reducing their carbon footprint. Cooling towers are utilized significantly in industries for either serving chillers or process cooling. Depending on the size of the cooling tower, it can use a surprising amount of energy and water, which is why it is crucial to make sure that the facility has optimized their cooling tower.A modeling tool has been developed to perform a thorough analysis of a cooling tower and its various operations to ensure that the facility has optimized its cooling tower. This model analyzes an annual base case in comparison with the revised case of a cooling tower operation. This modeling tool simulates 8,760 hourly calculations for fan power for various fan controls, water consumption, and pumping energy consumption and demand based on the user’s location and its corresponding Typical Meteorological Year 3 (TMY3) weather data. This model is capable to simulate up to five cooling tower cells as one large tower utilizing one pump or parallel pumping. The successful validated cooling tower model should assist industry to save energy at their facility through their cooling tower, whether they use it for process cooling or heating, ventilation and air conditioning (HVAC) applications. The entering/leaving water temperatures based on a monthly operating schedule or a wet-bulb temperature schedule will be used as inputs, and the model can calculate savings in energy for various conditions including variable-frequency drive (VFD) on the fan/pump, drift eliminators, number of cycles of concentration, reduced water flow rate, etc.

Hooper, Josh↗
DOE OSTI2026

Controls Status of Fermilab's PIP-II Project

The Fermilab Proton Improvement Project II (PIP-II) is building a new Super Conducting Linear Accelerator (SCL) accelerating protons to 800 MeV for injection into the rest of the FNAL beam complex. Key progress since the last status report given at ICALEPCS includes the adoption of modern DevOps practices with continuous integration and GitOps-based deployments, commissioning of EPICS-based systems at the Cryomodule Test Facility, and integration of a Virtual Accelerator framework for application development ahead of installation. In parallel, web-based applications using Dart and Flutter have matured, providing secure, unified access to both EPICS and legacy ACNET data. Data acquisition and timing systems have also evolved. This paper presents the current state of controls, emphasizing these recent developments and outlining upcoming milestones as PIP-II approaches commissioning of its cryoplant in 2026 and the Warm Front End in 2027.

Crisp, D. B. [Fermilab]↗
DOE OSTI2014

Parallel ptychographic reconstruction

Ptychography is an imaging method whereby a coherent beam is scanned across an object, and an image is obtained by iterative phasing of the set of diffraction patterns. It is able to be used to image extended objects at a resolution limited by scattering strength of the object and detector geometry, rather than at an optics-imposed limit. As technical advances allow larger fields to be imaged, computational challenges arise for reconstructing the correspondingly larger data volumes, yet at the same time there is also a need to deliver reconstructed images immediately so that one can evaluate the next steps to take in an experiment. Here we present a parallel method for real-time ptychographic phase retrieval. It uses a hybrid parallel strategy to divide the computation between multiple graphics processing units (GPUs) and then employs novel techniques to merge sub-datasets into a single complex phase and amplitude image. Results are shown on a simulated specimen and a real dataset from an X-ray experiment conducted at a synchrotron light source.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Work stealing for GPU-accelerated parallel programs in a global address space framework

Task parallelism is an attractive approach to automatically load balance the computation in a parallel system and adapt to dynamism exhibited by parallel systems. Exploiting task parallelism through work stealing has been extensively studied in shared and distributed-memory contexts. In this paper, we study the design of a system that uses work stealing for dynamic load balancing of task-parallel programs executed on hybrid distributed-memory CPU-graphics processing unit (GPU) systems in a global-address space framework. We take into account the unique nature of the accelerator model employed by GPUs, the significant performance difference between GPU and CPU execution as a function of problem size, and the distinct CPU and GPU memory domains. We consider various alternatives in designing a distributed work stealing algorithm for CPU-GPU systems, while taking into account the impact of task distribution and data movement overheads. These strategies are evaluated using microbenchmarks that capture various execution configurations as well as the state-of-the-art CCSD(T) application module from the computational chemistry domain

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Turbulence-driven anisotropic electron tail generation during magnetic reconnection

Magnetic reconnection (MR) plays an important role in particle transport, energization, and acceleration in space, astrophysical, and laboratory plasmas. In the Madison Symmetric Torus reversed field pinch, discrete MR events release large amounts of energy from the equilibrium magnetic field, a fraction of which is transferred to electrons and ions. Previous experiments revealed an anisotropic electron tail that favors the perpendicular direction and is symmetric in the parallel. New profile measurements of x-ray emission show that the tail distribution is localized near the magnetic axis, consistent modeling of the bremsstrahlung emission. The tail appears first near the magnetic axis and then spreads radially, and the dynamics in the anisotropy and diffusion are discussed. The data presented imply that the electron tail formation likely results from a turbulent wave-particle interaction and provides evidence that high energy electrons are escaping the core-localized region through pitch angle scattering into the parallel direction, followed by stochastic parallel transport to the plasma edge. Finally, new measurements also show a strong correlation between high energy x-ray measurements and tearing mode dynamics, suggesting that the coupling between core and edge tearing modes is essential for energetic electron tail formation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Scalable subsurface inverse modeling of huge data sets with an application to tracer concentration breakthrough data from magnetic resonance imaging

When characterizing subsurface properties is crucial for reliable and cost-effective groundwater supply management and contaminant remediation. With recent advances in sensor technology, large volumes of hydro-geophysical and geochemical data can be obtained to achieve high-resolution images of subsurface properties. However, characterization with such a large amount of information requires prohibitive computational costs associated with “big data” processing and numerous large-scale numerical simulations. To tackle such difficulties, the Principal Component Geostatistical Approach (PCGA) has been proposed as a “Jacobian-free” inversion method that requires much smaller forward simulation runs for each iteration than the number of unknown parameters and measurements needed in the traditional inversion methods. PCGA can be conveniently linked to any multi-physics simulation software with independent parallel executions. In our paper, we extend PCGA to handle a large number of measurements (e.g. 106 or more) by constructing a fast preconditioner whose computational cost scales linearly with the data size. For illustration, we characterize the heterogeneous hydraulic conductivity (K) distribution in a laboratory-scale 3-D sand box using about 6 million transient tracer concentration measurements obtained using magnetic resonance imaging. Since each individual observation has little information on the K distribution, the data was compressed by the zero-th temporal moment of breakthrough curves, which is equivalent to the mean travel time under the experimental setting. Moreover, only about 2,000 forward simulations in total were required to obtain the best estimate with corresponding estimation uncertainty, and the estimated K field captured key patterns of the original packing design, showing the efficiency and effectiveness of the proposed method. This article is protected by copyright. All rights reserved.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

The character and amplitude of ‘discontinuous’ bottom-simulating reflections in marine seismic data

Bottom-simulating reflections (BSRs) identified in seismic data are well documented; and are commonly interpreted to indicate the presence of gas hydrates along continental margins, as well as to estimate regional volumes of gas hydrate. A BSR is defined as a reflection that sub-parallels the seafloor but is opposite in polarity and cross-cuts dipping sedimentary strata. BSRs form as a result of a strong negative acoustic impedance contrast. BSRs, however, are a diverse seismic phenomena that manifest in strikingly contrasting ways in different geological settings, and in different seismic data types. We investigate the characteristics of BSRs, using conventional and high resolution, 2D and 3D seismic data sets in three locations: the Terrebonne and Orca Basins in the Gulf of Mexico, and Blake Ridge on the US Atlantic Margin. The acquisition geometry and frequency content of the seismic data significantly impact the resultant character of BSRs, as observed with depth and amplitude maps of the BSRs. Furthermore, our amplitude maps reinforce the concept that the BSR represents a zone, over which the transition from hydrate to free gas occurs, as opposed to the conventional model of the BSR occurring at a single interface. Our results show that a BSR can be mapped in three dimensions but it is not spatially continuous, at least not at the basin scale. Rather, a BSR manifests itself as a discontinuous, or patchy, reflection and only at local scales is it continuous. We suggest the discontinuous nature of BSRs is the result of variable saturation and distribution of free gas and hydrate, acquisition geometry and frequency content of the recorded seismic data. Lastly, the commonly accepted definition of a BSR should be broadened with careful consideration of these factors, to represent the uppermost extent of enhanced amplitude at the shallowest occurrence of free gas trapped by overlying hydrate-bearing sediments.

03 NATURAL GAS↗
DOE OSTI2019

Transient and Steady-State Inverse Problems in Sierra/Aria

Inverse problems arise in a wide range of applications, whenever unknown model parameters cannot be measured directly. Instead, the unknown parameters are estimated using experimental data and forward simulations. Thermal inverse problems, such as material characterization problems, are often large-scale and transient. Therefore, they require intrusive adjoint-based gradient implementations in order to be solved efficiently. The capability to solve large-scale transient thermal inverse problems using an adjoint-based approach was recently implemented in SNL Sierra Mechanics, a massively parallel capable multiphysics code suite. This report outlines the theory, optimization formulation, and path taken to implement thermal inverse capabilities in Sierra within a unit test framework. The capability utilizes Sierra/Aria and Sierra/Fuego data structures, the Rapid Optimization Library, and an interface to the Sierra/InverseOpt library. The existing Sierra/Aria time integrator is leveraged to implement a time-dependent adjoint solver.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Technical Advances for Sustainable Remediation: In Situ Monitoring and Climate Resiliency - 18436

Recent advances in sustainable remediation techniques show promise as solutions for contaminant removal in soil and groundwater media. Although passive remediation (or natural attenuation) has gained momentum as an acceptable technique, there are still challenges in regulatory frameworks as well as in public acceptance. Leaving contaminants in subsurface requires increased burden of proof to show that plumes are stable and residual contaminants do not pose a significant health risk. Climate changes and frequent extreme climate events contribute another level of complexity and make it difficult to demonstrate system stability and predict future plume conditions. In this study, we show two coupled approaches to tackle this challenge: (1) in situ groundwater monitoring based on advanced sensor and data analytics technologies (i.e., Big Data), and (2) state-of-art modeling for optimizing monitoring and site closure strategies. In the new monitoring approach, in situ sensors are used to continuously measure the key variables that control contaminant plume mobility and its spatial and temporal distribution (such as pH, redox potential, electrical conductivity, and groundwater level). Coupled with a limited number of groundwater sampling, the data analytics methods - data mining and machine learning - allow us to estimate contaminant concentrations, and also to detect any significant changes associated with the plume mobility. In parallel, the state-of-art numerical flow and reactive transport model - ASCEM software under DOE Office of Environmental Management - provides a physical and mechanistic understanding of the system behavior, and predicts the long-term plume migration for optimizing the monitoring and closure strategies. In particular, we focus on the effects of extreme precipitation or drought on the site closure as well as monitoring strategies. We demonstrate this approach at the Savannah River Site (SRS) F-Area, where groundwater is contaminated by various radionuclides, including uranium, tritium and technetium. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

An Asynchronous Many-Task Implementation of In-Situ Statistical Analysis using Legion.

In this report, we propose a framework for the design and implementation of in-situ analy- ses using an asynchronous many-task (AMT) model, using the Legion programming model together with the MiniAero mini-application as a surrogate for full-scale parallel scientific computing applications. The bulk of this work consists of converting the Learn/Derive/Assess model which we had initially developed for parallel statistical analysis using MPI [PTBM11], from a SPMD to an AMT model. In this goal, we propose an original use of the concept of Legion logical regions as a replacement for the parallel communication schemes used for the only operation of the statistics engines that require explicit communication. We then evaluate this proposed scheme in a shared memory environment, using the Legion port of MiniAero as a proxy for a full-scale scientific application, as a means to provide input data sets of variable size for the in-situ statistical analyses in an AMT context. We demonstrate in particular that the approach has merit, and warrants further investigation, in collaboration with ongoing efforts to improve the overall parallel performance of the Legion system.

Pebay, Philippe Pierre↗
DOE OSTI2015

Complik: A versatile tool for automatizing the representation of material data in MCNP models - 14412

At the Paul Scherrer Institut, the CASMO/SIMULATE code system is used as reference scheme for core analyses of the Swiss reactors. Besides, Monte Carlo (MC) based neutron transport codes are in parallel being established both for out-of-core applications and full core analyses, in order to provide higher fidelity solutions to problems beyond the modelling capabilities of the standard core modelling methods. In this perspective, a necessity is to be able to conduct the MC calculations at any operating conditions, requiring thus proper initialisation of the thermal-hydraulic feedback as well as at any burnup, prompting the need for a detailed modelling of all material zones in the irradiated fuel assemblies. To tackle the later challenge, the development of the COMPLINK tool, aimed at initialising large-scale MC models of burned core configurations, using as basis upstream 2-D assembly/ 3-D core analyses results, was initiated and is presented in this paper. A main feature is the capability to extend in an automatic manner, a user given MC model in order to represent material data with a higher resolution, keeping track of the location of such materials also within nested repeated structures. This capability prevents the user from the burden of developing specific computational framework for a target application. Since the same functionalities are required to analyse out-of-core spent fuel managements systems, a first verification of COMPLINK is illustrated on the basis of a criticality safety evaluation (CSE) with MCNP6.1 of a Swiss PWR wet storage pool loaded with fresh and burned fuel assemblies. Starting from CASMO-5 depletion calculations at each axial layer of the depleted fuel assemblies and reconstructed based on realistic irradiation histories, COMPLINK is then applied to load the isotopic compositions into the material zones of the corresponding MCNP6.1 assembly models. On this basis, the CSE analyses are conducted with focus on investigating axial and radial modelling effects. All in all, the obtained results are found to be well in line with the impact on CSE expected at the considered burnup levels, providing thus confidence in the correct implementation of the COMPLINK functionalities and confirming its effectiveness as well as efficiency for the initialization of all material zones in large-scale MC models of complex and strongly heterogeneous burned configurations. (authors)

42 ENGINEERING↗
DOE OSTI2017

Efficient Delaunay Tessellation through K-D Tree Decomposition

Delaunay tessellations are fundamental data structures in computational geometry. They are important in data analysis, where they can represent the geometry of a point set or approximate its density. The algorithms for computing these tessellations at scale perform poorly when the input data is unbalanced. We investigate the use of k-d trees to evenly distribute points among processes and compare two strategies for picking split points between domain regions. Because resulting point distributions no longer satisfy the assumptions of existing parallel Delaunay algorithms, we develop a new parallel algorithm that adapts to its input and prove its correctness. We evaluate the new algorithm using two late-stage cosmology datasets. The new running times are up to 50 times faster using k-d tree compared with regular grid decomposition. Moreover, in the unbalanced data sets, decomposing the domain into a k-d tree is up to five times faster than decomposing it into a regular grid.

Morozov, Dmitriy↗
DOE OSTI2017

Considerations on the Use of Custom Accelerators for Big Data Analytics

Accelerators, including Graphic Processing Units (GPUs) for gen- eral purpose computation, many-core designs with wide vector units (e.g., Intel Phi), have become a common component of many high performance clusters. The appearance of more stable and reliable tools tools that can automatically convert code written in high-level specifications with annotations (such as C or C++) to hardware de- scription languages (High-Level Synthesis - HLS), is also setting the stage for a broader use of reconfigurable devices (e.g., Field Pro- grammable Gate Arrays - FPGAs) in high performance system for the implementation of custom accelerators, helped by the fact that new processors include advanced cache-coherent interconnects for these components. In this chapter, we briefly survey the status of the use of accelerators in high performance systems targeted at big data analytics applications. We argue that, although the progress in the use of accelerators for this class of applications has been sig- nificant, differently from scientific simulations there still are gaps to close. This is particularly true for the ”irregular” behaviors exhibited by no-SQL, graph databases. We focus our attention on the limits of HLS tools for data analytics and graph methods, and discuss a new architectural template that better fits the requirement of this class of applications. We validate the new architectural templates by mod- ifying the Graph Engine for Multithreaded System (GEMS) frame- work to support accelerators generated with such a methodology, and testing with queries coming from the Lehigh University Benchmark (LUBM). The architectural template enables better supporting the task and memory level parallelism present in graph methods by sup- porting a new control model and a enhanced memory interface. We show that out solution allows generating parallel accelerators, pro- viding speed ups with respect to conventional HLS flows. We finally draw conclusions and present a perspective on the use of reconfig- urable devices and Design Automation tools for data analytics.

Data Analytics↗
DOE OSTI2015

Assessing a mini-application as a performance proxy for a finite element method engineering application

The performance of a large-scale, production-quality science and engineering application (‘app’) is often dominated by a small subset of the code. Even within that subset, computational and data access patterns are often repeated, so that an even smaller portion can represent the performance-impacting features. If application developers, parallel computing experts, and computer architects can together identify this representative subset and then develop a small mini-application (‘miniapp’) that can capture these primary performance characteristics, then this miniapp can be used to both improve the performance of the app as well as provide a tool for co-design for the high-performance computing community. However, a critical question is whether a miniapp can effectively capture key performance behavior of an app. This study provides a comparison of an implicit finite element semiconductor device modeling app on unstructured meshes with an implicit finite element miniapp on unstructured meshes. The goal is to assess whether the miniapp is predictive of the performance of the app. Finally, single compute node performance will be compared, as well as scaling up to 16,000 cores. Results indicate that the miniapp can be reasonably predictive of the performance characteristics of the app for a single iteration of the solver on a single compute node.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems

Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).

autoregressive prediction↗
DOE OSTI2024

Magnetic ordering in Eu 2 In and Eu 2 Sn

Eu 2 In and Eu 2 Sn crystallize in the orthorhombic Co 2 Si-type structure (oP12, Pnma, No. 62) with In and Sn atoms occupying one 4c site and the Eu atoms filling two other 4c sites. Eu 2 In has a nearly ideal first-order magnetostructural transition (FOMT) at 55 K with a hysteresis of less than 0.1 K, a large entropy change and an adiabatic temperature change of 5.0 K in a field of 2 T. The anhysteretic nature of the FOMT is likely due to there being no change in cell symmetry and relatively small changes in the lattice parameters. There is no magnetostructural transition in Eu2Sn. In this work we present the results of powder neutron diffraction, magnetization, and Eu Mössbauer spectroscopy aimed to investigate the nature of magnetic order for both Eu 2 In and Eu 2 Sn. The Eu Mössbauer spectrum of Eu 2 In at 5 K shows two equal area components, consistent with Eu occupying two equal multiplicity crystallographic sites. However, the different hyperfine fields (B) of 27 T and 17 T suggest that the magnetic environments of the Eu moments on the two 4c sites are different. Neutron diffraction data at 2.5 K show that in Eu 2 In the order is ferromagnetic, with Eu moments on both Eu sites oriented parallel to the a-axis; moment values of 6.8 μB and 6.5 μB were found. For Eu 2 Sn measurements find two antiferromagnetic transitions, which are corroborated by neutron diffraction. Analysis of density-functional theory calculations shows negligible energy difference between differing magnetic configurations, indirectly supporting stability of multiple magnetic structures observed experimentally. While the transition at T N1 = 30 K corresponds to the formation of a simple k 1 = 0 antiferromagnetic structure with Eu-moments pointing along the b-axis, at T N2 = 13 K a coexisting second magnetic order with k 2 = [0, ½, ½] appears.

36 MATERIALS SCIENCE↗