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At least 919 records · Page 51

Exploring MPI Communication Models for Graph Applications Using Graph Matching as a Case Study

Traditional implementations of parallel graph operations on distributed memory platforms are written using Message Passing Interface (MPI) point to point communication primitives such as Send-Recv (blocking and nonblocking). Apart from this classical model, the MPI community has over the years added other communication models; however, their suitability for handling the irregular traffic workloads typical of graph operations remain comparatively less explored. Our aim in this paper is to study these relatively underutilized communication models of MPI for graph applications. More specifically, we evaluate MPI’s one-sided programming, or Remote Memory Access (RMA), and nearest neighborhood collectives using a process graph topology. There are features in these newer models that are intended to better map to irregular communication patterns, as exemplified in graph algorithms. As a concrete application for our case study, we use distributed memory implementations of a weighted graph matching algorithm to investigate performances of MPI-3 RMA and neighborhood collective operations compared to nonblocking Send- Recv. A matching in a graph is a subset of edges such that no two matched edges are incident on the same vertex. A maximum weight matching is a matching of maximum weight computed as the sum of the weights of matched edges. Algorithms for optimal matching have quadratic complexity and are difficult to parallelize. More importantly, execution of graph matching is dominated by high volume of irregular memory accesses, making it an ideal candidate for studying the effects of various MPI communication models on graph applications at scale. Our neighborhood collectives and RMA implementations yields up to 6× speedup over traditional optimized nonblocking Send-Recv implementations, on thousands of cores of the NERSC Cori supercomputer. We believe the lessons learned from this case study can be adopted to benefit a wider range of graph application codes.

Ghosh, Sayan↗

Application of DLT cybersecurity stack to TES applications for a scalable, cybersecure, and interoperable future

Transactive Energy Systems (TES) are expected to improve upon existing grid operations and capabilities by enabling the integration of traditional grid resources with distributed energy resources (DER). Distributed Ledger Technology or DLT (e.g., blockchain) presents itself as a viable instrument to support decentralized, autonomous, and tamper-evident applications, which can be leveraged within TES's ecosystem. DLTs can provide pertinent security controls including access controls, data immutability, and traceability in addition to other well-known advantages such as decentralization and scalability. This work demonstrates the DLT Cybersecurity stack and its applicability to TES-based use-cases/applications. The seven-layer DLT cybersecurity stack is a DLT-agnostic framework that can quickly be used to classify and group the individual needs of an application into the different processing and cybersecurity layers offered by a DLT using a common taxonomy and an architectural mapping framework. This enables application engineers to demystify and strengthen the overall security aspects of their systems while maintaining an open perspective towards features and drawbacks that may hinder their performance in real-world scenarios. The paper leverages the work performed by the IEEE P2418.5 - Blockchain for Energy Standards working group.

Blockchain, blockchain interoperability, Cybersecu↗

A GPU-accelerated and Monte Carlo-based intensity modulated proton therapy optimization system

Purpose: Conventional spot scanning intensity modulated proton therapy (IMPT) treatment planning systems (TPSs) optimize proton spot weights based on analytical dose calculations. These analytical dose calculations have been shown to have severe limitations in heterogeneous materials. Monte Carlo (MC) methods do not have these limitations; however, MC-based systems have been of limited clinical use due to the large number of beam spots in IMPT and the extremely long calculation time of traditional MC techniques. In this work, the authors present a clinically applicable IMPT TPS that utilizes a very fast MC calculation. Methods: An in-house graphics processing unit (GPU)-based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified least-squares optimization method was used to achieve the desired dose volume histograms (DVHs). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that resulted from maintaining the intrinsic CT resolution. The effects of tail cutoff and starting condition were studied and minimized in this work. Results: For relatively large and complex three-field head and neck cases, i.e., >100 000 spots with a target volume of ∼1000 cm{sup 3} and multiple surrounding critical structures, the optimization together with the initial MC dose influence map calculation was done in a clinically viable time frame (less than 30 min) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The in-house MC TPS plans were comparable to a commercial TPS plans based on DVH comparisons. Conclusions: A MC-based treatment planning system was developed. The treatment planning can be performed in a clinically viable time frame on a hardware system costing around 45 000 dollars. The fast calculation and optimization make the system easily expandable to robust and multicriteria optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A method for volumetric imaging in radiotherapy using single x-ray projection

Purpose: It is an intriguing problem to generate an instantaneous volumetric image based on the corresponding x-ray projection. The purpose of this study is to develop a new method to achieve this goal via a sparse learning approach. Methods: To extract motion information hidden in projection images, the authors partitioned a projection image into small rectangular patches. The authors utilized a sparse learning method to automatically select patches that have a high correlation with principal component analysis (PCA) coefficients of a lung motion model. A model that maps the patch intensity to the PCA coefficients was built along with the patch selection process. Based on this model, a measured projection can be used to predict the PCA coefficients, which are then further used to generate a motion vector field and hence a volumetric image. The authors have also proposed an intensity baseline correction method based on the partitioned projection, in which the first and the second moments of pixel intensities at a patch in a simulated projection image are matched with those in a measured one via a linear transformation. The proposed method has been validated in both simulated data and real phantom data. Results: The algorithm is able to identify patches that contain relevant motion information such as the diaphragm region. It is found that an intensity baseline correction step is important to remove the systematic error in the motion prediction. For the simulation case, the sparse learning model reduced the prediction error for the first PCA coefficient to 5%, compared to the 10% error when sparse learning was not used, and the 95th percentile error for the predicted motion vector was reduced from 2.40 to 0.92 mm. In the phantom case with a regular tumor motion, the predicted tumor trajectory was successfully reconstructed with a 0.82 mm error for tumor center localization compared to a 1.66 mm error without using the sparse learning method. When the tumor motion was driven by a real patient breathing signal with irregular periods and amplitudes, the average tumor center error was 0.6 mm. The algorithm robustness with respect to sparsity level, patch size, and presence or absence of diaphragm, as well as computation time, has also been studied. Conclusions: The authors have developed a new method that automatically identifies motion information from an x-ray projection, based on which a volumetric image is generated.

60 APPLIED LIFE SCIENCES↗

SU-F-P-04: Implementation of Dose Monitoring Software: Successes and Pitfalls

Purpose: to successfully install a dose monitoring software (DMS) application to assist in CT protocol and dose management. Methods: Upon selecting the DMS, we began our implementation of the application. A working group composed of Medical Physics, Radiology Administration, Information Technology, and CT technologists was formed. On-site training in the application was supplied by the vendor. The decision was made to apply the process for all the CT protocols on all platforms at all facilities. Protocols were painstakingly mapped to the correct masters, and the system went ‘live’. Results: We are routinely using DMS as a tool in our Clinical Performance CT QA program. It is useful in determining the effectiveness of revisions to existing protocols, and establishing performance baselines for new units. However, the implementation was not without difficulty. We identified several pitfalls and obstacles which frustrated progress. Including: Training deficiencies, Nomenclature problems, Communication, DICOM variability. Conclusion: Dose monitoring software can be a potent tool for QA. However, implementation of the program can be problematic and requires planning, organization and commitment.

60 APPLIED LIFE SCIENCES↗

Topology control of human fibroblast cells monolayer by liquid crystal elastomer

Eukaryotic cells in living tissues form dynamic patterns with spatially varying orientational order that affects important physiological processes such as apoptosis and cell migration. The challenge is how to impart a predesigned map of orientational order onto a growing tissue. Here, we demonstrate an approach to produce cell monolayers of human dermal fibroblasts with predesigned orientational patterns and topological defects using a photoaligned liquid crystal elastomer (LCE) that swells anisotropically in an aqueous medium. The patterns inscribed into the LCE are replicated by the tissue monolayer and cause a strong spatial variation of cells phenotype, their surface density, and number density fluctuations. Unbinding dynamics of defect pairs intrinsic to active matter is suppressed by anisotropic surface anchoring allowing the estimation of the elastic characteristics of the tissues. The demonstrated patterned LCE approach has potential to control the collective behavior of cells in living tissues, cell differentiation, and tissue morphogenesis.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Qubit noise deconvolution

We present a noise deconvolution technique to remove a wide class of noises when performing arbitrary measurements on qubit systems. In particular, we derive the inverse map of the most common single qubit noisy channels, and exploit it at the data processing step to obtain noise-free estimates of observables evaluated on a qubit system subject to known noise. We illustrate a self-consistency check to ensure that the noise characterization is accurate providing simulation results for the deconvolution of a generic Pauli channel, as well as experimental evidence of the deconvolution of decoherence noise occurring on Rigetti quantum hardware.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Status of Lattice QCD Determination of Nucleon Form Factors and Their Relevance for the Few-GeV Neutrino Program

Calculations of neutrino–nucleus cross sections begin with the neutrino–nucleon interaction, making the latter critically important to flagship neutrino oscillation experiments despite limited measurements with poor statistics. Alternatively, lattice quantum chromodynamics (LQCD) can be used to determine these interactions from the Standard Model with quantifiable theoretical uncertainties. Recent LQCD results of g A are in excellent agreement with data, and results for the (quasi-)elastic nucleon form factors with full uncertainty budgets are expected within a few years. We review the status of the field and LQCD results for the nucleon axial form factor, F A ( Q 2 ), a major source of uncertainty in modeling sub-GeV neutrino–nucleon interactions. Results from different LQCD calculations are consistent but collectively disagree with existing models, with potential implications for current and future neutrino oscillation experiments. We describe a road map to solidify confidence in the LQCD results and discuss future calculations of more complicated processes, which are important to few-GeV neutrino oscillation experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Non-contact imaging of terahertz surface currents with aperture-type near-field microscopy

Terahertz (THz) near-field imaging and spectroscopy provide valuable insights into the fundamental physical processes occurring in THz resonators and metasurfaces on the subwavelength scale. However, so far, the mapping of THz surface currents has remained outside the scope of THz near-field techniques. In this study, we demonstrate that aperture-type scanning near-field microscopy enables non-contact imaging of THz surface currents in subwavelength resonators. Through extensive near-field mapping of an asymmetric D-split-ring THz resonator and full electromagnetic simulations of the resonator and the probe, we demonstrate the correlation between the measured near-field images and the THz surface currents. The observed current dynamics in the interval of several picoseconds reveal the interplay between several excited modes, including dark modes, whereas broadband THz near-field spectroscopy analysis enables the characterization of electromagnetic resonances defined by the resonator geometry.

Norman, Sarah↗

Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fuid-fow pathways are relatively rare in the subsurface, but are critical components of hydrothermal systems like Brady and many other types of fuid-fow systems in fractured rock. Here, we analyze geologic data with ML methods to unravel the local geologic controls on these pathways. The ML method, non-negative matrix factorization with k-means clustering (NMFk), is applied to a library of 14 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate that macro-scale faults and a local step-over in the fault system preferentially occur along production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate: (1) the specific geologic controls on the Brady hydrothermal system and (2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes. This submission includes the published journal article detailing this work, the published 3D geologic map of the Brady Geothermal Area used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity, 3D well data, along which geologic data were sampled for PCA analyses, and associated metadata file. This work was done using the GeoThermalCloud framework, which is part of SmartTensors (both are linked below).

15 GEOTHERMAL ENERGY↗

Data Validation Package - June 2016 Groundwater and Surface Water Sampling at the Green River, Utah, Disposal Site

This event included annual sampling of groundwater and surface water locations at the Green River, Utah, Disposal Site. Sampling and analyses were conducted as specified in Sampling and Analysis Plan for US. Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated, http://energy.gov/lrnldownloads/sampling-and- analysis-plan-us-department-energy-office-legacy-management-sites). Samples were collected from 15 monitoring wells and two surface locations at the disposal site as specified in the draft 2011 Ground Water Compliance Action Plan for the Green River, Utah, Disposal Site. Planned monitoring locations are shown in Attachment 1, Sampling and Analysis Work Order. A duplicate sample was collected from location 0179. One equipment blank was collected during this sampling event. Water levels were measured at all monitoring wells that were sampled. See Attachment 2, Trip Reports for additional details. The analytical data and associated qualifiers can be viewed in environmental database reports and are also available for viewing with dynamic mapping via the GEMS (Geospatial Environmental Mapping System) website at http://gems.lm.doe.gov/#. No issues were identified during the data validation process that requires additional action or follow-up.

54 ENVIRONMENTAL SCIENCES↗

Data Validation Package - July 2016 Groundwater Sampling at the Gunnison, Colorado, Disposal Site

Groundwater sampling at the Gunnison, Colorado, Disposal Site is conducted every 5 years to monitor disposal cell performance. During this event, samples were collected from eight monitoring wells as specified in the 1997 Long-Term Surveillance Plan for the Gunnison, Colorado, Disposal Site. Sampling and analyses were conducted as specified in the Sampling and Analysis Plan for US Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated, http://energy.gov/lm/downloads/sampling-and­ analysis-plan-us-department-energy-office-legacy-management-sites). Planned monitoring locations are shown in Attachment 1, Sampling and Analysis Work Order. A duplicate sample was collected from location 0723. Water levels were measured at all monitoring wells that were sampled and seven additional wells. The analytical data and associated qualifiers can be viewed in environmental database reports and are also available for viewing with dynamic mapping via the GEMS (Geospatial Environmental Mapping System) website at http://gems.lm.doe.gov/#. No issues were identified during the data validation process that require additional action or follow-up.

54 ENVIRONMENTAL SCIENCES↗

Exploring the feasibility of crack detection in plate weldments through an interposed layer of viscoelastic material.

Development of new approaches in the nondestructive evaluation of welded steel plates for large naval structures continues to be an area of interest for the DoD and the military complex. In this report we will evaluate an elastic-microwave based detection and imaging method using both numerical finite element (3D FEM) and experimental methods. The evaluation was performed on two test articles that were designed to represent critical structural components with flaws of interest. Details of the materials and the mechanical drawings were provided with the test articles. Flaws, cracks and weld defects have been included in the test articles to determine detection sensitivity and accuracy of the proposed method. Our approach uses a microwave interferometer (MI) to record the scattered response of flaws in the steel plated as it is driven by an incident elastic field. The MI can “see” (penetrate) through the viscoelastic coating to the upper surface of the plate. Out-of-plane displacement amplitudes of 10nm in the frequency range (1kHz to 25kHz) are readily observable, with the key feature being, that the surface bond between the coating and the steel plate are undisturbed. The non-contact aspect of the interferometer allows for large surface regions to be accurately and efficiently scanned in space and time. Spatiotemporal data sets of this kind and specialized wavefield processing provide powerful detection and imaging modalities. From these wavefield data sets, a plate thickness mapping capability has been demonstrated that can detect thickness changes on the order of 0.79 mm (1/32”) with spatial resolution on the order of the spatial sampling rate, 15mm (~5/8”). We have also shown that a topological energy analysis of the wavefield data can detect and locate small flaws, on the order of 5-10 mm (0.025-0.40”) in the welded joint of a 1.5” thick T-plate. As before, these results are obtained through a 2” thick viscoelastic coating without altering the integrity of coating or the coating bond. These results show that we are detecting and locating damage (flaws) in the plate that are much smaller than the wavelength of the propagating guided modes. Classical scattering theory places a (λ/2) resolution limit on the detectability of flaws in terms of the incident field [22], however, since the spatial resolution of the scanned region is much smaller, (Δx=Δy=15mm) and the inherent natural focusing of the time reversal operation, we are able to detect smaller flaws on the order of (λ/10). It is important to realize that we are not imaging the flaw but detecting and localizing a difference between a reference (pristine) sample and the measured (damaged) sample, relative to a spatial grid on the surface. The current scan resolution is 15mm x 15mm. At present we cannot expect to resolve individual flaws within a grid space only their cumulative effect. Even with the current limitations, this imaging approach appears to be a promising alternative to current methods where the coating layer is removed.

36 MATERIALS SCIENCE↗

TNSL Overview

Thermal neutron scattering law (TNSL) data describe low-energy neutrons scattering off of bound materials, and can have a significant impact on modeling any system with slow neutrons, including nuclear reactors. Previous work to introduce TNSL data to neutron transport codes at LLNL focused on COG and TART [1], with the limitation that these codes require highly specialized data processing and formatting. We have recently increased efforts to process TNSL data with the central LLNL nuclear data processing code FUDGE, to be stored in the generalized nuclear database structure (GNDS) for use in any general transport code with the ability to read GNDS data. The first step in this effort is to verify that the TNSL processing with FUDGE yields results comparable to results obtained using the LANL nuclear data processing code NJOY. The next step is to verify the transport of thermal neutrons in Mercury (a Monte Carlo code) and Ardra (a deterministic code) against one another, as well as against the LANL Monte Carlo neutron transport code MCNP. This verification step has not been completed, due to a number of discrepancies between results obtained using differently processed data. There is ongoing effort to understand differences between FUDGE and NJOY. Finally, we map out our current capability to validate TNSL data against benchmark systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Immobilization of Uranium in a Wetland 8-km Downstream from an Industrial Source (Report)

A three-day walk-over survey with portable gamma detecting equipment was conducted over a uranium-contaminated wetland located 8-km downstream from a former fuel fabrication facility. 97,000 spectra were collected, individually processed to extract uranium activity data, and then integrated with topographical information (LIDAR) to create maps. These maps reveal that 50 years after being released into the environment, 11% of the uranium is retained in the 9-ha wetland area. Combined with measurement collected closer to the source, it was determined that 94% of the released uranium is presently being held in downstream wetlands. This demonstrates that wetlands can be very effective at immobilizing contaminants for long durations. The survey also showed that previous flyover maps overestimated the size of the contaminated areas by 140% but had the advantage of being completed in orders-of-magnitude fewer labor hours. Depending on project needs, the walk-over technique may be useful to include in tandem with flyover measurements to acquire maps with greater sensitivity and spatial resolution.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Heavy Flavor Physics at the sPHENIX Experiment

The sPHENIX experiment is a state-of-the-art jet and heavy flavor physics detector, which successfully recorded its first Au + Au collision data at 200 GeV at the Relativistic Heavy Ion Collider (RHIC). sPHENIX will provide heavy flavor physics measurements at RHIC, covering an unexplored kinematic region and unprecedented precision, to probe the parton energy loss mechanism, parton transport coefficients in quark–gluon plasma, and the hadronization process under various medium conditions. At the center of sPHENIX, the monolithic active pixel sensor (MAPS)-based VerTeX detector (MVTX) is a high-precision silicon pixel detector. The MVTX provides excellent position resolution and the capability of operating in continuous streaming readout mode, allowing precise vertex determination and recording a large data sample, both of which are particularly crucial for heavy flavor physics measurements. In this work, we will show the general performance of heavy-flavor hadron reconstruction. In addition, we will discuss the commissioning experience with sPHENIX. Finally, we will provide the projection of b-hadron and jet observables and discuss the estimated constraints on theoretical models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Visualizing Charge Transport and Nanoscale Electrochemistry by Hyperspectral Kelvin Probe Force Microscopy

Charge-transport and electrochemical processes are heavily influenced by the local microstructure. Kelvin probe force microscopy (KPFM) is a widely used technique to map electrochemical potentials at the nanometer scale; however, it offers little information on local charge dynamics. In this study, we implement a hyperspectral KPFM approach for spatially mapping bias-dependent charge dynamics in timescales ranging from the sub-millisecond to the second regime. As a proof of principle, we investigate the role mobile surface charges play in a three-unit-cell LaAlO 3 /SrTiO 3 oxide heterostructure. We explore machine learning approaches to assist with visualization, pattern recognition, and interpretation of the information-rich data sets. Linear unmixing methods reveal hidden bias-dependent interfacial processes, most likely water splitting, which are essentially unnoticed by functional fitting of the dynamic response alone. Hyperspectral KPFM will be beneficial for investigating nanoscale charge transport and local reactivity in systems involving a possible combination of electronic, ionic, and electrochemical phenomena.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Function-based Taxonomy Implementation

Function-based taxonomies are relational mapping tools used to clearly illustrate how an organization delivers Critical Functions by using various people, processes, technologies, information, and infrastructure (PPTII). Critical Functions are the actions or activities that make up the organization’s primary purpose. Enabling Functions are the combination of PPTII used by the organization to deliver their Critical Functions. A function-based taxonomy provides a framework to categorize information and related artifacts that document an organization’s unique implementation of PPTII for Critical Function delivery. The ideal state of a function-based taxonomy is to organize the existing knowledge the organization already has throughout their numerous systems, policies, people, procedures, and configurations. A well-organized taxonomy helps organizations to effectively leverage their knowledge by clearly identifying dependencies and connections. This document is the result of combined engineering and analytical experience and describes a repeatable method for producing function-based taxonomies.

42 ENGINEERING↗