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At least 253 records · Page 14

Dynamic graph system for a semantic database

A method and system in a computer system for dynamically providing a graphical representation of a data store of entries via a matrix interface is disclosed. A dynamic graph system provides a matrix interface that exposes to an application program a graphical representation of data stored in a data store such as a semantic database storing triples. To the application program, the matrix interface represents the graph as a sparse adjacency matrix that is stored in compressed form. Each entry of the data store is considered to represent a link between nodes of the graph. Each entry has a first field and a second field identifying the nodes connected by the link and a third field with a value for the link that connects the identified nodes. The first, second, and third fields represent the rows, column, and elements of the adjacency matrix.

97 MATHEMATICS AND COMPUTING↗

Dynamic graph system for a semantic database

A method and system in a computer system for dynamically providing a graphical representation of a data store of entries via a matrix interface is disclosed. A dynamic graph system provides a matrix interface that exposes to an application program a graphical representation of data stored in a data store such as a semantic database storing triples. To the application program, the matrix interface represents the graph as a sparse adjacency matrix that is stored in compressed form. Each entry of the data store is considered to represent a link between nodes of the graph. Each entry has a first field and a second field identifying the nodes connected by the link and a third field with a value for the link that connects the identified nodes. The first, second, and third fields represent the rows, column, and elements of the adjacency matrix.

97 MATHEMATICS AND COMPUTING↗

A new efficient grain growth model using a random Gaussian-sampled mode filter

This paper presents the use of a Gaussian neighborhood mode filter for predicting grain growth in a manner similar to the solutions obtained by a Monte Carlo Potts model. This flexible grain growth model can quickly utilize modern, computationally optimized data science strategies on graphics processing units to simulate grain growth up to 100 times faster than the state-of-the-art, publicly available Monte Carlo Potts model. We show that, given the correct neighborhood, the mode filter can replicate normal grain growth in two or three dimensions. In addition, the paper briefly demonstrates the ability to model limited anisotropic in grain boundary energy and mobility. Anisotropic grain boundary energy is modeled by defining a weighted mode filter operation. Anisotropic grain boundary mobility is modeled by scaling and orienting the Gaussian neighborhood in a particular direction.

Anisotropy↗

microMS: A Python Platform for Image-Guided Mass Spectrometry Profiling

Image-guided mass spectrometry (MS) profiling provides a facile framework for analyzing samples ranging from single cells to tissue sections. The fundamental workflow utilizes a whole-slide microscopy image to select targets of interest, determine their spatial locations, and subsequently perform MS analysis at those locations. Improving upon prior reported methodology, a software package was developed for working with microscopy images. microMS, for microscopy-guided mass spectrometry, allows the user to select and profile diverse samples using a variety of target patterns and mass analyzers. Written in Python, the program provides an intuitive graphical user interface to simplify image-guided MS for novice users. The class hierarchy of instrument interactions permits integration of new MS systems while retaining the feature-rich image analysis framework. microMS is a versatile platform for performing targeted profiling experiments using a series of mass spectrometers. The flexibility in mass analyzers greatly simplifies serial analyses of the same targets by different instruments. The current capabilities of microMS are presented, and its application for off-line analysis of single cells on three distinct instruments is demonstrated. The software has been made freely available for research purposes. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Developing Digital Twin Visualizations: A Methodology and Case Study on Chemical Separation Processing

As advances in digital engineering continue to push the technological boundaries, digital twin (DT) visualizations for diagnostics and safeguards advancement become much more feasible and practical. DTs generate large and complex data streams that require effective user interfaces to provide monitoring and diagnostic capabilities. Unfortunately, while these frameworks exist, there is not much research on the systematic documentation of human–computer interaction (HCI) for DT visualization. This work presents a dual-mode visualization methodology (two dimensional [2D] graphical user interface dashboard and 3D mixed reality) designed to support diagnostic tasks in DT systems and building on a validated framework and applying established HCI principles. The methodology is demonstrated through a case study of aqueous processing at Idaho National Laboratory, using experimental data from the chemical solvent extraction runs. Our interfaces display real-time alerts and monitoring to inform users of safeguards anomalies. The interfaces use immersive 3D mixed-reality visualization for further system and experiment investigation. This work demonstrates how the systematic application of HCI principles can inform DT visualization design for diagnostic and safeguards applications. While formal user evaluation studies remain as future work, this paper documents the systematic design methodology and demonstrates a proof-of-concept implementation.

3D visualization↗

Development of a CPU/GPU portable software library for Lagrangian–Eulerian simulations of liquid sprays

The Lagrangian–Eulerian method is widely used for simulations of fuel sprays in turbulent combustion because of the advantage of treating the spray droplets as discrete points. One challenge of the Lagrangian–Eulerian method is the intense computational requirement when tracking the large number of Lagrangian particles needed for high fidelity. We have developed a performance-portable library, Grit, to track the Lagrangian particles in parallel on central processing unit (CPU) and graphics processing unit (GPU) accelerated high performance computing (HPC) architectures. Grit is a C++ library which employs Message Passing Interface (MPI) for distributed memory parallelism and Kokkos programming model for on-node shared memory parallelism with performance portability across different architectures of GPUs and multi-core/manycore CPUs. The parallel algorithms, key parallel kernels, and their performances on the pre-exascale supercomputer, Summit, are presented. Grit is coupled with a direct numerical simulation (DNS) solver, S3D, for multiphase simulations. A conservative formulation has been developed and implemented in Grit for phase coupling with thermodynamic consistency. The formulation separates the conservation of mass, momentum and energy from the physical models to prevent accidental violation of conservation laws due to inconsistent models. The formulation also enforces consistent definitions of enthalpies of the fuel for both phases and the latent heat of evaporation. Finally, simulations of turbulent particle-laden flow and the evaporation of dilute turbulent spray jet are performed to verify the software implementation, and to demonstrate the scalability of Grit for large-scale multiphase simulations.

97 MATHEMATICS AND COMPUTING↗

Extending SST vanadis to Add SIMT Functional Units

Sandia National Laboratories is currently investigating scalable architectural simulation capabilities, with a focus on simulating and evaluating highly scalable supercomputers for high-performance computing applications. This exploration is driven by the shift toward more specialized forms of compute and the need for a more diverse set of accurate models. This project will explore the use of General-Purpose Graphical Processing Units (GPGPUs) in high-performance computing using both physical systems and new simulator models – traditional GPUs as well as tightly-coupled SIMT accelerators.

97 MATHEMATICS AND COMPUTING↗

Symplectic multi-particle tracking on GPUs

A symplectic multi-particle tracking model is implemented on the Graphic Processing Units (GPUs) using the Compute Unified Device Architecture (CUDA) language. The symplectic tracking model can preserve phase space structure and reduce non-physical effects in long term simulation, which is important for beam property evaluation in particle accelerators. Though this model is computationally expensive, it is very suitable for parallelization and can be accelerated significantly by using GPUs. In this paper, we optimized the implementation of the symplectic tracking model on both single GPU and multiple GPUs. Using a single GPU processor, the code achieves a factor of 2-10 speedup for a range of problem sizes compared with the time on a single state-of-the-art Central Processing Unit (CPU) node with similar power consumption and semiconductor technology. It also shows good scalability on a multi-GPU cluster at Oak Ridge Leadership Computing Facility. In an application to beam dynamics simulation, the GPU implementation helps save more than a factor of two total computing time in comparison to the CPU implementation.

43 PARTICLE ACCELERATORS↗

Extending GPU-accelerated Gaussian integrals in the TeraChem software package to f type orbitals: Implementation and applications

Here, the increasing availability of graphics processing units (GPUs) for scientific computing has prompted interest in accelerating quantum chemical calculations through their use. However, the complexity of integral kernels for high angular momentum basis functions often limits the utility of GPU implementations with large basis sets or for metal containing systems. In this work, we report the implementation of f function support in the GPU-accelerated TeraChem software package through the development of efficient kernels for the evaluation of Hamiltonian integrals. The high efficiency of the resulting code is demonstrated through density functional theory (DFT) calculations on increasingly large organic molecules and transition metal complexes, as well as coupled cluster singles and doubles calculations on water clusters. Preliminary investigations into Ni(I) catalysis with DFT and the photochemistry of MnH(CH 3 ) with complete active space self-consistent field are also carried out. Overall, our GPU-accelerated software appears to be well-suited for fast simulation of large transition metal containing systems, as well as organic molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-Fidelity CFD Simulation of Mixed Convection and Forced Convection in a Pebble Bed Test Reactor Core

The Hermes low-power [35-MW(thermal)] reactor will be built and operated by Kairos Power LLC (KP) to demonstrate its fluoride salt-cooled high-temperature reactor (FHR) technology. In the KP FHR, the reactor core is composed of randomly packed pebbles with TRISO fuel particles inside with FLiBe flow upward through the core acting as a coolant. Previous numerical and experimental studies have been limited to either a small-size bed or to a lack of detailed measurements for heat transfer. Here, to address the lack of high-fidelity heat transfer data in a real-size FHR core, in this study, we simulated a pebble bed core with 34 374 pebbles randomly packed, similar to the Hermes reactor's size. The core radius was 14 times that of the pebble diameter, while the core height was 45 times. In this work, we were particularly interested in a mixed convection regime, where buoyancy is important. Therefore, we performed several large-eddy simulations at different Reynolds numbers (160 to 1000) with gravitational force included. The spectral element computational fluid dynamics code NekRS with graphics processing unit acceleration was used for this study. The low-Mach number approximation was applied to address property changes in the FLiBe and to account for buoyancy. A pure hexahedral mesh with 60 million elements was generated by the Voronoi cell method. At the polynomial order of 5, the total degrees of freedom was 7.5 billion. The developed case in this work is the first of its kind in terms of size and complexity. The local numerical data across the domain were obtained and compared with empirical correlations. After examining the data, we found the following conclusions. For pressure drop, the Reger correlation predicted less than a 5% error. On the other hand, for heat transfer, the Wakao correlation outperformed the others. Based on our findings, we recommend the use of the Wakao correlation for the Nusselt number calculation, and for pressure drop, the KTA (Kerntechnischer Ausschuss) correclation, among the available experimental correlations. In conclusion, the Reger direct numerical simulation-driven correlation for pressure drops should also be considered, given its best agreement with our calculations.

Mixed Convection↗

Big Data as a Service from an Urban Information System

Big Data has already proven itself as a valuable tool that lets geographers and urban researchers utilize large data re- sources to generate new insights. However, wider adoption of Big Data techniques in these areas is impeded by a number of difficulties in both knowledge discovery and data and sci- ence production. Typically users face such problems as dis- parate and scattered data, data management, spatial search- ing, insufficient computational capacity for data-driven anal- ysis and modelling, and the lack of tools to quickly visual- ize and summarize large data and analysis results. Here we propose an architecture for an Urban Information Sys- tem (UrbIS) that mitigates these problems by utilizing the Big Data as a Service (BDaaS) concept. With technolog- ical roots in High-performance Computing (HPC), BDaaS is based on the idea of outsourcing computations to dif- ferent computing paradigms, scalable to super-computers. UrbIS aims to incorporate federated metadata search, in- tegrated modeling and analysis, and geovisualization into a single seamless workflow. The system is under active devel- opment and is built around various emerging technologies that include hybrid and NoSQL databases, massively par- allel systems, GPGPU computing, and WebGL-based geo- graphic visualization. UrbIS is designed to facilitate using Big Data across multiple cities to better understand how ur- ban areas impact the environment and how climate change and other environmental change impact urban areas.

Sorokine, Alexandre↗

Porting a 3D seismic modeling code (SW4) to CORAL machines

Seismic waves fourth order (SW4) solves the seismic wave equations on Cartesian and curvilinear grids using large compute clusters with O (100,000) cores. In this article we discuss the porting of SW4 to run on the CORAL architecture using the RAJA performance portability abstraction layer. The performances of key kernels using RAJA and CUDA are compared to estimate the performance penalty of using the portability abstraction layer. Code changes required for efficiency on GPUs and minimizing time spent in Message Passing Interface (MPI) are discussed. This article describes a path for efficiently porting large code bases to GPU-based machines while avoiding the pitfalls of a new architecture in the early stages of its deployment. Current bottlenecks in the code are discussed along with possible architectural or software mitigations. SW4 runs 28× faster on one 4-GPU CORAL node than on a CTS-1 node (Dual Intel Xeon E5-2695 v4). SW4 is now in routine use on problems of unprecedented resolution (203 billion grid points) and scale on 1,200 nodes of Summit.

97 MATHEMATICS AND COMPUTING↗

A Study of Geodesic Distance Kernel on an Integrated GPU

Graphics processing units (GPUs) are commonly used for graphics and general-purpose (GPGPU) computation. Currently, NVIDIA’s GPUs, through its CUDA framework for GPGPU programming, are ubiquitous for highperformance computing. Another class of GPUs, with a central processing unit (CPU) and a GPU integrated on the same chip, is commonly used in laptops, desktop computers, and low-power servers. While they are not designed to outperform discrete GPUs due to the power, area, and thermal constrains [1], there is a need to better understand the performance of a processor with an integrated GPU for floating-point intensive applications. The study helps us better understand the characteristics of hardware and software development tools, and the benefit of offloading such applications to an integrated GPU.

97 MATHEMATICS AND COMPUTING↗

KBase: The DOE Systems Biology Knowledgebase: An Overview

The Department of Energy Systems Biology Knowledgebase (KBase) is a knowledge creation and discovery environment designed for both biologists and bioinformaticians. KBase integrates a large variety of public data and analysis tools into an easy-to-use graphical user interface and leverages DOE computational infrastructure to perform sophisticated systems biology analyses. KBase is a freely available system that enables scientists to upload their own data, analyze it alongside collaborator and public data, build validated systems biology models, and share workflows and conclusions.

59 BASIC BIOLOGICAL SCIENCES↗

Application of Structured Decision Making to Hanford Site Radiological Air Monitoring - 17924

Radiological air monitoring is a component of an Environmental Surveillance (ES) program that has been in operation at the Department of Energy Hanford Site for several decades. The primary objectives of the ES program are protection of human health and the environment (on and off-site) as well as regulatory compliance. The ES program was designed decades ago when the plutonium-production reactors and related facilities at the Hanford Site were operational and air emissions were more widespread and significant than today. We employed a structured decision making (SDM) approach that integrates science with values and preferences to a Hanford Site air monitoring program decision. Specifically, a decision was necessary pertaining to the possible replacement of three air monitoring stations located in the 100 Area of the Hanford Site because the power line that supports these stations was near the end of its lifecycle. Although focused on this specific decision, the SDM model is more broadly applicable to decisions pertaining to adapting the air monitoring network to current Hanford operations. The value focused thinking approach that underlies SDM facilitates transparent and defensible decision making, and aids in communicating monitoring rationale. Some of the fundamental objectives elicited from the decision makers regarding management options for the three air monitoring stations included maximizing the ability to measure releases, minimizing environmental impacts, and maximizing social and economic sustainability. The fundamental objectives were linked to six objectives that could be measured (quantified) to allow a decision-analytic solution to the decision problem. Value functions and preference weights were developed for each of the objectives measures based on information obtained during a project workshop as well as by review and analysis of environmental data. Lastly, a set of five management options was identified that might achieve at least one of the objectives. A Bayes Network was developed as a solution to the decision problem pertaining to the three air stations (the 3 air stations decision). The Bayes Network describes the decision model graphically, and also serves as the computational engine for the decision analysis. The Bayes Network defines the relationship among the five management options and six objectives measures. In addition to the weights and value functions noted above, key inputs to the Bayes Network include a set of probabilities related to the different model states defined by the network. These include the probability of a significant release occurring, the probability that a release would be detected under each of the five management options, and the probability of achieving the other objective measures under each management option. In this manner the Bayesian Network captures the uncertainty in the components of the decision model. Replacing the three air monitoring stations with thermoluminescent dosimeters was identified as the preferred management option. A brief report was developed documenting the SDM model, including the workshop notes and analyses that were used to develop the objectives and model input variable values. This application demonstrates SDM's utility for supporting monitoring program decisions and, critically, providing a transparent and traceable basis for the decision. This relatively simple SDM model also provides a basis for an SDM model for monitoring decisions related to the more complex and holistic goal of achieving ES program objectives. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

EXSAN: An Interactive Version of the Nuclear Cross Section Data Handbook - 25687

Neutron cross section measurements and data files have advanced significantly since 1989 when Los Alamos published 'A Nuclear Cross Section Data Handbook', a detailed compendium of point-wise cross section plots and pie charts of relative contributions of individual reactions to the total cross section for 129 isotopes. Other compendiums with similar data and analysis tools have also been published. The intent of this work is to develop a modern, open-source application for interactive exploration and analysis of Evaluated Nuclear Data File (ENDF) libraries that also allows users to create their own 'Nuclear Cross Section Data Handbooks'. EXSAN is an easy-to-use graphical user interface application for exploring ENDF photon and neutron cross sections developed in Python. In addition to interactive plotting, EXSAN includes methods for computing rank-order lists of cross section for any energy and calculating composite cross sections for isotopic and elemental compositions and additional batch automation features. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

Sparse matrix‐vector and matrix‐multivector products for the truncated SVD on graphics processors

Summary Many practical algorithms for numerical rank computations implement an iterative procedure that involves repeated multiplications of a vector, or a collection of vectors, with both a sparse matrix and its transpose. Unfortunately, the realization of these sparse products on current high performance libraries often deliver much lower arithmetic throughput when the matrix involved in the product is transposed. In this work, we propose a hybrid sparse matrix layout, named CSRC, that combines the flexibility of some well‐known sparse formats to offer a number of appealing properties: (1) CSRC can be obtained at low cost from the popular CSR (compressed sparse row) format; (2) CSRC has similar storage requirements as CSR; and especially, (3) the implementation of the sparse product kernels delivers high performance for both the direct product and its transposed variant on modern graphics accelerators thanks to a significant reduction of atomic operations compared to a conventional implementation based on CSR. This solution thus renders considerably higher performance when integrated into an iterative algorithm for the truncated singular value decomposition (SVD), such as the randomized SVD or, as demonstrated in the experimental results, the block Golub–Kahan–Lanczos algorithm.

Aliaga, José I.↗

Evaluation of Portable Programming Models to Accelerate LArTPC Detector Simulations

The Liquid Argon Time Projection Chamber (LArTPC) technology is widely used in high energy physics experiments, including the upcoming Deep Underground Neutrino Experiment (DUNE). Accurately simulating LArTPC detector responses is essential for analysis algorithm development and physics model interpretations. Accurate LArTPC detector response simulations are computationally demanding, and can become a bottleneck in the analysis workflow. Compute devices such as General-Purpose Graphics Processing Units (GPGPUs) have the potential to substantially accelerate simulations compared to traditional CPU-only processing. The software development that requires often carries the cost of specialized code refactorization and porting to match the target hardware architecture. With the rapid evolution and increased diversity of the computer architecture landscape, it is highly desirable to have a portable solution that also maintains reasonable performance. We report our ongoing effort in evaluating Kokkos as a basis for this portable programming model using LArTPC simulations in the context of the Wire-Cell Toolkit, a C++ library for LArTPC simulations, data analysis, reconstruction and visualization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗