A work stealing based approach for enabling scalable optimal sequence homology detection
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Daily, Jeff↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Comparison of heat flux measurement techniques during the DIII-D metal ring campaign
The heat fluxes expected in the ITER divertor raise concerns about the damage tolerances of tungsten, especially due to thermal transients caused by edge localized modes (ELMs) as well as frequent temperature cycling from high to low extremes. Thus we are motivated to understand the heat flux conditions that can cause not only enhanced erosion but also bulk thermo-mechanical damage to a tungsten divertor. For the metal ring campaign in DIII-D, tungsten-coated TZM tile inserts were installed making two toroidal arrays of metal tile inserts in the lower divertor. This study examines the deposited heat flux on these rings with embedded thermocouples (TCs) sampling at 10 kHz and compares them to Langmuir probe (LP) and infrared thermography (IRTV) heat flux measurements. We see agreement of the TC, LP, and IRTV data within 20% of the heat flux averaged over the entire discharge, and that all three diagnostics suggest parallel heat flux at the OSP location increases linearly with input heating power. The TC and LP heat flux time traces during the discharge trend together during large changes to the average heat flux. By subtracting the LP measured inter-ELM heat flux from TC data, using a rectangular ELM energy pulse shape, and taking the relative size and duration of each ELM from ${{D}}_{\alpha }$ measurements, we extract the ELM heat fluxes from TC data. This over-estimates the IRTV measured ELM heat fluxes by a factor of 1.9, and could be due to the simplicity of the TC heat flux model and the assumed ELM energy pulse shape. ELM heat fluxes deposited on the inserts are used to model tungsten erosion in this campaign. These TC ELM heat flux estimates are used in addition to IRTV, especially in cases where the IRTV view to the metal ring is obstructed. We observe that some metal inserts were deformed due to exposed leading edges. The thermal conditions on these inserts are investigated with the thermal modeling code ABAQUS using our heat flux measurements when these edges were exposed. We report on how the thermal cycling on the ends of the inserts caused this deformation.
42 ENGINEERING↗
In‐memory integration of existing software components for parallel adaptive unstructured mesh workflows
Summary Reliable mesh‐based simulations are needed to solve complex engineering problems. Mesh adaptivity can increase reliability by reducing discretization errors but requires multiple software components to exchange information. Often, components exchange information by reading and writing a common file format. This file‐based approach becomes a problem on massively parallel computers where filesystem bandwidth is a critical performance bottleneck. Our approach using data streams and component interfaces avoids the filesystem bottleneck. In this paper, we present these techniques and their use for coupling mesh adaptivity to the PHASTA computational fluid dynamics solver, the Albany multi‐physics framework, and the Omega3P linear accelerator frequency analysis applications. Performance results are reported on up to 16,384 cores of an Intel Knights Landing‐based system.
Smith, Cameron W.↗
Tamoxifen affects glucose and lipid metabolism parameters, causes browning of subcutaneous adipose tissue and transient body composition changes in C57BL/6NTac mice
Tamoxifen is a selective estrogen receptor (ER) modulator which is widely used to generate inducible conditional transgenic mouse models. Activation of ER signaling plays an important role in the regulation of adipose tissue (AT) metabolism. We therefore tested the hypothesis that tamoxifen administration causes changes in AT biology in vivo. 12 weeks old male C57BL/6NTac mice were treated with either tamoxifen (n = 18) or vehicle (n = 18) for 5 consecutive days. Tamoxifen treatment effects on body composition, energy homeostasis, parameters of AT biology, glucose and lipid metabolism were investigated up to an age of 18 weeks. We found that tamoxifen treatment causes: I) significantly increased HbA{sub 1c}, triglyceride and free fatty acid serum concentrations (p < 0.01), II) browning of subcutaneous AT and increased UCP-1 expression, III) increased AT proliferation marker Ki67 mRNA expression, IV) changes in adipocyte size distribution, and V) transient body composition changes. Tamoxifen may induce changes in body composition, whole body glucose and lipid metabolism and has significant effects on AT biology, which need to be considered when using Tamoxifen as a tool to induce conditional transgenic mouse models. Our data further suggest that tamoxifen-treated wildtype mice should be characterized in parallel to experimental transgenic models to control for tamoxifen administration effects. - Highlights: • Tamoxifen treatment causes significantly increased HbA{sub 1c}, triglyceride and free fatty acid serum concentrations. • Tamoxifen induces browning of subcutaneous AT and increased UCP-1 expression. • Tamoxifen changes adipocyte size distribution, and transient body composition.
60 APPLIED LIFE SCIENCES↗
OsCAldOMT1 is a bifunctional O-methyltransferase involved in the biosynthesis of tricin-lignins in rice cell walls
Abstract Lignin is a phenylpropanoid polymer produced in the secondary cell walls of vascular plants. Although most eudicot and gymnosperm species generate lignins solely via polymerization of p -hydroxycinnamyl alcohols (monolignols), grasses additionally use a flavone, tricin, as a natural lignin monomer to generate tricin-incorporated lignin polymers in cell walls. We previously found that disruption of a rice 5-HYDROXYCONIFERALDEHYDE O -METHYLTRANSFERASE ( OsCAldOMT1 ) reduced extractable tricin-type metabolites in rice vegetative tissues. This same enzyme has also been implicated in the biosynthesis of sinapyl alcohol, a monolignol that constitutes syringyl lignin polymer units. Here, we further demonstrate through in-depth cell wall structural analyses that OsCAldOMT1 -deficient rice plants produce altered lignins largely depleted in both syringyl and tricin units. We also show that recombinant OsCAldOMT1 displayed comparable substrate specificities towards both 5-hydroxyconiferaldehyde and selgin intermediates in the monolignol and tricin biosynthetic pathways, respectively. These data establish OsCAldOMT1 as a bifunctional O -methyltransferase predominantly involved in the two parallel metabolic pathways both dedicated to the biosynthesis of tricin-lignins in rice cell walls. Given that cell wall digestibility was greatly enhanced in the OsCAldOMT1 -deficient rice plants, genetic manipulation of CAldOMT s conserved in grasses may serve as a potent strategy to improve biorefinery applications of grass biomass.
59 BASIC BIOLOGICAL SCIENCES↗
CO–0.30–0.07: A peculiar molecular clump with an extremely broad velocity width in the central molecular zone of the Milky Way
The high velocity dispersion compact cloud CO–0.30–0.07 is a peculiar molecular clump discovered in the central molecular zone of the Milky Way, which is characterized by its extremely broad velocity emissions (∼145 km s{sup −1}) despite the absence of internal energy sources. We present new interferometric maps of the cloud in multiple molecular lines in frequency ranges of 265–269 GHz and 276–280 GHz obtained using the Submillimeter Array, along with the single-dish images previously obtained with the ASTE 10 m telescope. The data show that the characteristic broad velocity emissions are predominantly confined in two parallel ridges running through the cloud center. The central ridges are tightly anticorrelated with each other in both space and velocity, thereby sharply dividing the entire cloud into two distinct velocity components (+15 and +55 km s{sup −1}). This morphology is consistent with a model in which the two velocity components collide with a relative velocity of 40 km s{sup −1} at the interface defined by the central ridges, although an alternative explanation with a highly inclined expanding-ring model is yet to be fully invalidated. We have also unexpectedly detected several compact clumps (≲0.1 pc in radius) likely formed by shock compression. The clumps have several features in common with typical star-forming clouds: high densities (10{sup 6.5−−7.5} cm{sup −3}), rich abundances of hot-core-type molecular species, and relatively narrow velocity widths apparently decoupled from the furious turbulence dominating the cloud. The cloud CO–0.30–0.07 is possibly at an early phase of star formation activity triggered by the shock impact.
79 ASTRONOMY AND ASTROPHYSICS↗
Inverse Normalization Method for Cross-Sectional Imaging and Velocimetry of Two-Phase Flows Based on Electrical Capacitance Tomography
Proper normalization of the measured capacitance data is a prerequisite in electrical capacitance tomography (ECT). Conventional methods, such as parallel and series normalization, assume a higher permittivity perturbation in a homogeneous (lower) permittivity background. Although this is applicable to a number of cases, some two-phase flows are better modeled instead as a lower permittivity perturbation in a homogeneous (higher) permittivity background. A different normalization method is proposed for such cases, which provides similar image quality as conventional, but is particularly beneficial for velocimetry applications based on sensitivity gradient of ECT sensor. Furthermore, simulation and experimental results are provided to illustrate the advantages for the proposed normalization technique.
47 OTHER INSTRUMENTATION↗
Spherical Region Queries on Multicore Architectures
In this short paper, we report the performance of multiple thread-parallel algorithms for spherical region queries on multicore architectures motivated by a challenging data analytics application in materials science. Performances of two tree-based algorithms and a naive algorithm are compared to identify the length scales at which these approaches perform optimally. The optimal algorithm is then used to scale the driving materials science application, which is shown to deliver over 17X speedup using 32 OpenMP threads on data sets containing many millions of atoms.
Lu, Hao↗
PFLOTRAN
PFLOTRAN is a GNU LGPL licensed code that simulates single phase water and multiphase (air, co2, water) flow, energy transport, geochemical reaction and biological reaction in the earth's subsurface environment. The problem may be discretized on structured and unstructured grids. The code is designed to run in parallel on supercomputers and leverages the open source PETSc library for solvers and data structures and open source HDF5 for binary file I/O. See www.pflotran.org and/or doc-dev.pflotran.org for further information. SAND2020-12161 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Hammond, Glenn↗
DARMA-MPI Interoperability WBS 2.3.1.04 Milestone 15 (ECP Milestone Report)
DARMA (Distributed Asynchronous Resilient Models for Applications) is a runtime library developed as part of the the Sandia ATDM (Advanced Technology Development and Mitigation) program. DARMA supports applications within 2.2.5.03 ADNN03-ASC ATDM SNL Application, which includes a number of applications featuring dynamic physics which requires load balancing and asynchronous communication for high performance. We have implemented a modern C++ programming model that can enable dynamic, asynchronous communication on top of existing data structures from a serial or MPI code. DARMA development has occurred in parallel with a verification milestone for ATDM in FY18. For FY19, DARMA will impact ATDM by enabling the performance benefits of a dynamic runtime through only incremental changes to existing verified MPI codes. The results presented here demonstrate the DARMA development process for an MPI mini-app, showing a 3-4x improvement in performance for a challenging problem relative to the parent MPI code and coming within 25 percent of the theoretically optimal performance achievable from a perfect, fine-grained load balancer for most cases.
97 MATHEMATICS AND COMPUTING↗
Coupled Electron-Photon Monte Carlo Radiation Transport for Next-Generation Computing Systems
Traditional Monte Carlo particle transport codes are expected to run inefficiently on next-generation architectures as they are memory-intensive and highly divergent. Since electrons and photons also behave differently, the future for coupled electron-photon radiation transport looks even worse. This project describes preliminary efforts to improve the performance of Monte Carlo particle transport codes when using accelerators like the graphics processing unit (GPU). Two key issues are addressed: how to handle memory-intensive tallies, and how to reduce divergence. Tallying on the GPU can be done efficiently by post-processing particle data, or by using a feature called warp shuffle for summing scores in parallel during the simulation. Reducing divergence is possible by using an event-based algorithm for particle tracking instead of the traditional history-based one. Although performance tests presented in this work show that the history-based algorithm generally outperformed the event-based one for simple problems, this outcome will likely change as the complexity of the code increases.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Data Acquisition in Wireless Router Link Testbed using GNU Radio Companion
An IEEE80-2.11g WLAN wireless-router link test-bed is under development at the Idaho National Laboratory-Wireless Research Center. The project objective is to generate repeatable, high-quality, controlled-noise wireless transmissions for software-defined radio (SDR) analysis and research. Signal acquisition for the data link will include both and Ettus X310 (with GNU Radio Companion) in parallel with a Tektronix RSA 306a spectrum analyzer. The integration and validation of the SDR is described. Preliminary results indicate the router test-bed comprised of readily-available WiFi and RF hardware will provide low-noise and repeatable signal captures.
47 OTHER INSTRUMENTATION↗
GentenMPI: Distributed Memory Sparse Tensor Decomposition
GentenMPl is a toolkit of sparse canonical polyadic (CP) tensor decomposition algorithms that is designed to run effectively on distributed-memory high-performance computers. Its use of distributed-memory parallelism enables it to efficiently decompose tensors that are too large for a single compute node's memory. GentenMPl leverages Sandia's decades-long investment in the Trilinos solver framework for much of its parallel-computation capability. Trilinos contains numerical algorithms and linear algebra classes that have been optimized for parallel simulation of complex physical phenomena. This work applies these tools to the data science problem of sparse tensor decomposition. In this report, we describe the use of Trilinos in GentenMPl, extensions needed for sparse tensor decomposition, and implementations of the CP-ALS (CP via alternating least squares) and GCP-SGD (generalized CP via stochastic gradient descent) sparse tensor decomposition algorithms. We show that GentenMPl can decompose sparse tensors of extreme size, e.g., a 12.6-terabyte tensor on 8192 computer cores. We demonstrate that the Trilinos backbone provides good strong and weak scaling of the tensor decomposition algorithms.
97 MATHEMATICS AND COMPUTING↗
Measurements at the Facility for Experiments of Nuclear Reactions in Stars (FENRIS) (Final Technical Report)
Nuclear reactions in stars have transformed the universe since the Big Bang, turning hydrogen and helium into all of the elements we see around us today. These reactions fuel a star throughout its lifetime. When the star burns out, its ashes are ejected into space to enrich the next generation of stars so to understand the origin of the elements in the cosmos, we must learn how stars burn their fuel. In this stellar burning, the rates of nuclear reactions are key. The rates can be determined by recreating the reactions in the laboratory, but often they occur too rarely to measure at the low energies characteristic of stellar burning. Novel, indirect measurements must be used. With support from the Department of Energy Office of Science, a research program has been developed to perform such measurements, primarily using the Enge split-pole spectrograph at the Triangle Universities Nuclear Laboratory (TUNL). High-energy nuclear reactions coupled with theoretical models were used to ascertain the rate of the low-energy nuclear reactions occurring in stars. Detailed analysis of the data reveals the structure of nuclei and how they affect stellar burning. In parallel to these experimental efforts, theoretical tools were developed to identify which nuclear reactions are most critical for understanding stars, thus discovering priorities for future measurements. This complementary suite of experiments and theoretical calculations can be used to help answer one of the key questions facing the physics community: How did visible matter come into being and how did it evolve?
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
EJFAT: Towards Intelligent Compute Destination Load Balancing
To handle increased data flow, Jefferson Lab (JLab) is partnering with ESnet for development of an AI/ML directed compute work Load Balancer (LB) of UDP streamed data. The LB is FPGA based featuring dynamically configurable, low latency and high throughput destination address switching. The LB provides integration of edge and core computing to support JLab experimental programs, the Electron-Ion Collider, as well as data centers of the future. In the ESnet/JLab FPGA Accelerated Transport (EJFAT) initiative, the function of the LB Data Plane (DP) is to redirect data streams to selectable (but unknown to sender) destination hosts based on current worload and within that host to destination ports as a function of sub- stream id. This effects hierarchical scaling, first across compute machines for processing over a series of events and second, across ports so different data source sub-streams may be assigned to different processors for further parallelization. The LB Control Plane (CP) programs the DP using compute farm telemetry to direct and balance workloads across a compute cluster as the operating conditions require. While Proportional/Integrative/Derivative (PID) controllers are often seen in similar applications, here we investigate the feasibility of a Reinforcement Learning (RL) based schedule manager running in the CP to provide dynamic updates to the DP scheduling policy.
Lawrence, David↗
AEOLUS: Advances in Experimental Design, Optimal Control, and Learning for Uncertain Complex Systems
Sustained advances in the mathematics of modeling and simulation have resulted in the capability today for routine simulation of a number of large scale complex DOE-relevant systems. As remarkable as this capability for solving the so-called forward problem is, it is typically only the first step-an inner loop within an outer loop that explores the simulation model's parameter space and decision space to characterize uncertainty in the model's predictions, learn unknown model parameters from data, design the most informative experiments, determine optimal control strategies, and create optimal designs. Broadly, what unifies all of these outer loop problems is that they are, in one form or another, optimization problems over parameter/control/design space that are constrained by complex uncertain models. To fully realize the power of scientific simulation as a basis for scientific discovery, technological innovation, and rational decision-making, it is imperative to move beyond simulation to tackle the outer loop of optimization for learning from data, experimental design, and control with complex uncertain models. When the models under consideration are large-scale and complex, and when the optimization variable and uncertain parameter spaces are high (or infinite) dimensional, this constitutes a grand challenge of the highest order, and is intractable with conventional methods. To overcome these challenges, the AEOLUS Center was established to develop a unified mathematical, computational, and statistical framework for (1) Learning predictive models from complex data via Bayesian inference and optimization, and (2) Optimizing experiments, processes, and designs using the resulting uncertain models. These problems are intractable with conventional methods, for several reasons: (1) The simulation problems that govern the inner loops of the optimization problems are expensive to execute (due to severe nonlinearity, heterogeneity, multiphysics/multiscale coupling); (2) The optimization variable and uncertain parameter spaces are high dimensional, often stemming from discretizations of infinite dimensional fields such as initial conditions, sources, or material properties. We argue that the key to overcoming these challenges is to develop new mathematical, computational, and statistical methods that exploit the structure of the Bayesian inference and optimization problems mediated by their underlying complex uncertain models. This structure includes the regularity, sparsity, geometry, low intrinsic dimensionality, and multifidelity nature of the maps from uncertain parameter/optimization variable spaces to the specific objectives targeted: Bayesian inference, optimal experimental design, and optimal control design. Black box methods developed as generic tools are incapable of exploiting this structure. To be successful, we must create, integrate, and cross-fertilize ideas across multiple areas of applied math--including approximation theory, Bayesian inference, data science, experimental design, information theory, machine learning, model reduction, optimal control theory, parallel algorithms, PDE-constrained optimization, randomized algorithms, stochastic optimization, and uncertainty quantification--all while exploiting the structure of the problems at hand. With this goal in mind, we have marshaled a team of leading authorities in these areas. While the methods we develop will be broadly applicable across a wide spectrum of DOE problems in which experiments inform models and the systems those models describe must be optimized under uncertainty, we have chosen a specific area, advanced manufacturing and materials, to drive our work. AMM is characterized by complex models across multiple scales, and is a rich source of challenging problems in inference, experimental design, and optimal control, requiring multifaceted and integrated advances in applied mathematics. As such, AMM serves as an excellent vehicle to motivate and demonstrate the advances in applied mathematics developed by our center.
97 MATHEMATICS AND COMPUTING↗
Energy scaling advantages of resistive memory crossbar based computation and its application to sparse coding
In this study, the exponential increase in data over the last decade presents a significant challenge to analytics efforts that seek to process and interpret such data for various applications. Neural-inspired computing approaches are being developed in order to leverage the computational properties of the analog, low-power data processing observed in biological systems. Analog resistive memory crossbars can perform a parallel read or a vector-matrix multiplication as well as a parallel write or a rank-1 update with high computational efficiency. For an N × N crossbar, these two kernels can be O(N) more energy efficient than a conventional digital memory-based architecture. If the read operation is noise limited, the energy to read a column can be independent of the crossbar size (O(1)). These two kernels form the basis of many neuromorphic algorithms such as image, text, and speech recognition. For instance, these kernels can be applied to a neural sparse coding algorithm to give an O(N) reduction in energy for the entire algorithm when run with finite precision. Sparse coding is a rich problem with a host of applications including computer vision, object tracking, and more generally unsupervised learning.
97 MATHEMATICS AND COMPUTING↗
Deploying Taller Turbines in Complex Terrain: A Hill Flow Study (HilFlowS) Perspective
Terrain-induced flow acceleration is presented for the summertime, peak power season at Lawrence Livermore National Laboratory’s Site 300 for the Hill Flow Study (HilFlowS). HilFlowS, designed as an adjunct field campaign to the Department of Energy’s Second Wind Forecasting Improvement Project (WFIP2), provides wind profile observations at a second location in complex terrain for validating numerical atmospheric model simulations and for better understanding flow behavior over hills for wind power generation. One unique feature of HilFlowS was the inclusion of an undergraduate university student who helped plan and execute the experiment as well as analyze wind data from two remote sensing laser detection and ranging (lidar) instruments deployed along parallel ridgelines. HilFlowS examines the trend of building higher into the atmosphere for the purpose of increasing wind turbine power production and evaluates the wind resource in the Altamont Pass Region of Northern California for a set of wind turbines of differing hub-heights and rotor-disk diameters found in the area. The wind profiles show strongly channeled onshore flow above both hills, enhanced by strong subsidence aloft, which produces a wind maximum (Umax) around z = 10 m and strong negative shear throughout all of the evaluated rotor-disks for much of the summer wind season. Under these conditions, shear becomes more negative with increasing hub-height and increasing rotor-disk size. Rotor-disk equivalent wind speed (Uequiv), a measure of the average wind speed across the entire rotor-disk, is compared to hub-height, rotor length, and rated capacity factor for the set of turbines. Uequiv is most closely related to turbine hub-height and is negatively correlated given the low altitude of Umax. Based on these results, building the largest capacity, large rotor-disk wind turbine at the lowest possible hub-height appears to provide turbines in the Altamont with a fast, near-surface, onshore wind resource during the peak power season.
17 WIND ENERGY↗