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At least 379 records · Page 21

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NASA NTRS1989

Unsteady interaction of a rotor with a vortex

The unsteady, three-dimensional flow field of a helicopter rotor blade encountering a passing vortex is calculated by solving the Euler/thin layer Navier-Stokes equations by a finite-difference numerical procedure. A prescribed vortex method is adopted to preserve the structure of the interacting vortex. The cases considered for computation correspond to the experimental model rotor test conditions of Caradonna, et al. and consist of parallel and oblique interactions. Comparison of the numerical results with test data show good agreement for both parallel and oblique interactions at subsonic and transonic tip speeds.

Srinivasan, G. R.↗

NASA NTRS1997

Mid-Infrared Observational and Theoretical Studies of Star Formation and Early Solar Systems

The first 2 years of this program were used to make mid-IR observations of regions of star formation in the Orion nebula with the UCSD mid-IR camera at the UCSD/University of Minnesota telescope at Mt. Lemmon. These observations attempted to make the first systematic study of an extended region, known to have newly forming stars, and expected to have complex mid-IR emission. We discovered, to our surprise, that most of the thermal emission originated from extended sources rather than from point sources. This interesting observation made the analysis of the data much more complex, since the chop/nod procedures used at these wavelengths produce a differential measurement of the emission in one region compared to that in the adjacent region. Disentangling complex extended emission in such a situation is very difficult. In parallel with this work we were also observing comets in the thermal infrared, the other component of the original proposal. Some spectacular data on the comet Swift-Tuttle was acquired and published. A changing jet structure observed over a 2 week period is described. The rotation period of the comet can be measured at 66 hours. The size of the nucleus can also be estimated (at 30 km) from the observed excess flux from the nucleus. These data have lead to the development of models describing the action of dust particles of differing sizes and composition leaving the nucleus. The spatial distribution of the predicted IR emission has been compared to the observed jet structures, leading to estimates of both particles sizes, relative amounts of silicate vs organic grains, and the amounts of dust emitted in the jets vs isotopic emission.

Jones, Barbara↗

NASA NTRS2011

Observations of Low-Latitude Plasma Density Enhancements and their Associated Plasma Drifts

Plasma density structures are frequently encountered in the nighttime low-latitude ionosphere by probes on the Communication/Navigation Outage Forecasting System (C/NOFS) satellite. Of particular interest to us here are plasma density enhancements, which are typically observed +/- 15 deg away from the magnetic equator. The low inclination of the C/NOFS satellite offers an unprecedented opportunity to examine these structures and their associated electric fields and plasma velocities, including their field-aligned components, along an east-west trajectory. Among other observations, the data reveal a clear asymmetry in the velocity structure within and around these density enhancements. Previous observations have shown that the peak change in drift velocity associated with a density enhancement occurs simultaneously both perpendicular and parallel to the magnetic field, while the 1results in this paper show that the peak change in parallel fl ow typically occurs 25-100 km to the east of the peak perpendicular ow. We discuss this and other aspects of the observations in relation to the characteristics of the plasma depletions formed near the magnetic equator detected by the same probes on the C/NOFS satellite and to previous observations and theories.

Klenzing, J. H.↗

NASA NTRS1980

RAMP: A fault tolerant distributed microcomputer structure for aircraft navigation and control

RAMP consists of distributed sets of parallel computers partioned on the basis of software and packaging constraints. To minimize hardware and software complexity, the processors operate asynchronously. It was shown that through the design of asymptotically stable control laws, data errors due to the asynchronism were minimized. It was further shown that by designing control laws with this property and making minor hardware modifications to the RAMP modules, the system became inherently tolerant to intermittent faults. A laboratory version of RAMP was constructed and is described in the paper along with the experimental results.

Dunn, W. R.↗

DOE OSTI2023

In-depth analysis on parallel processing patterns for high-performance Dataframes

The Data Science domain has expanded monumentally in both research and industry communities during the past decade, predominantly owing to the Big Data revolution. Artificial Intelligence (AI) and Machine Learning (ML) are bringing more complexities to data engineering applications, which are now integrated into data processing pipelines to process terabytes of data. Typically, a significant amount of time is spent on data preprocessing in these pipelines, and hence improving its efficiency directly impacts the overall pipeline performance. The community has recently embraced the concept of Dataframes as the de-facto data structure for data representation and manipulation. However, the most widely used serial Dataframes today (R, pandas) experience performance limitations while working on even moderately large data sets. We believe that there is plenty of room for improvement by taking a look at this problem from a high-performance computing point of view. In a prior publication, we presented a set of parallel processing patterns for distributed dataframe operators and the reference runtime implementation, Cylon. In this paper, we are expanding on the initial concept by introducing a cost model for evaluating the said patterns. Furthermore, we evaluate the performance of Cylon on the ORNL Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

An optimized FM-index library for nucleotide and amino acid search

Abstract Background Pattern matching is a key step in a variety of biological sequence analysis pipelines. The FM-index is a compressed data structure for pattern matching, with search run time that is independent of the length of the database text. Implementation of the FM-index is reasonably complicated, so that increased adoption will be aided by the availability of a fast and flexible FM-index library. Results We present AvxWindowedFMindex (AWFM-index), a lightweight, open-source, thread-parallel FM-index library written in C that is optimized for indexing nucleotide and amino acid sequences. AWFM-index introduces a new approach to storing FM-index data in a strided bit-vector format that enables extremely efficient computation of the FM-index occurrence function via AVX2 bitwise instructions, and combines this with optional on-disk storage of the index’s suffix array and a cache-efficient lookup table for partial k-mer searches. The AWFM-index performs exact match count and locate queries faster than SeqAn3’s FM-index implementation across a range of comparable memory footprints. When optimized for speed, AWFM-index is $$\sim $$ ∼ 2–4x faster than SeqAn3 for nucleotide search, and $$\sim $$ ∼ 2–6x faster for amino acid search; it is also $$\sim $$ ∼ 4x faster with similar memory footprint when storing the suffix array in on-disk SSD storage. Conclusions AWFM-index is easy to incorporate into bioinformatics software, offers run-time performance parameterization, and provides clients with FM-index functionality at both a high-level (count or locate all instances of a query string) and low-level (step-wise control of the FM-index backward-search process). The open-source library is available for download at https://github.com/TravisWheelerLab/AvxWindowFmIndex.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1972

Study on multi-satellite, multi-measurement of the structure of the earth's bow shock

The pulsation model of the earth's bow shock proposed a nonuniform shock having both perpendicular (abrupt, monotonic) and oblique (oscillatory, multigradient) properties simultaneously, depending on local orientation of the shock surface to the interplanetary field B sub sw in parallel planes defined by B sub sw and solar wind velocity. Multiple, concurrent, satellite observations of the shock and solar wind conditions were used. Twenty-six potentially useful intervals of concurrent Explorer 33 and 35 data acquisition were examined, of which six were selected for closer study. In addition, two years of OGO-5 and HEOS 1 magnetometer data were examined for possible conjunctions to these spacecraft having applicable data. One case of clear nonuniformity and several of field-dependent structure were documented. A computational aid, called pulsation index, was developed.

Source record↗

DOE OSTI2024

h5bench: A unified benchmark suite for evaluating HDF5 I/O performance on pre‐exascale platforms

Summary Parallel I/O is a critical technique for moving data between compute and storage subsystems of supercomputers. With massive amounts of data produced or consumed by compute nodes, high‐performant parallel I/O is essential. I/O benchmarks play an important role in this process; however, there is a scarcity of I/O benchmarks representative of current workloads on HPC systems. Toward creating representative I/O kernels from real‐world applications, we have created h5bench , a set of I/O kernels that exercise hierarchical data format version 5 (HDF5) I/O on parallel file systems in numerous dimensions. Our focus on HDF5 is due to the parallel I/O library's heavy usage in various scientific applications running on supercomputing systems. The various tests benchmarked in the h5bench suite include I/O operations (read and write), data locality (arrays of basic data types and arrays of structures), array dimensionality (one‐dimensional arrays, two‐dimensional meshes, three‐dimensional cubes), I/O modes (synchronous and asynchronous). In this paper, we present the observed performance of h5bench executed along several of these dimensions on existing supercomputers (Cori and Summit) and pre‐exascale platforms (Perlmutter, Theta, and Polaris). h5bench measurements can be used to identify performance bottlenecks and their root causes and evaluate I/O optimizations. As the I/O patterns of h5bench are diverse and capture the I/O behaviors of various HPC applications, this study will be helpful to the broader supercomputing and I/O community.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Thin film confinement reduces compatibility in symmetric ternary block copolymer/homopolymer blends

Here, the thin film phase behavior of ternary blends consisting of symmetric poly(styrene) (PS)– b –poly(dimethylsiloxane)(PDMS), PS, and PDMS was investigated using X–ray reflectivity (XRR) and atomic force microscopy (AFM). This system is strongly segregated, and the homopolymers are approximately the same length as the corresponding blocks of the copolymer. The XRR and AFM data are used to quantify changes in domain spacing ( L ) and morphology evolution with increasing homopolymer content (Φ H ). In 100 nm thick films, from Φ H = 0 to 0.20, the system maintains a perfect parallel lamellar structure and domains swell as predicted based on theory; however, from Φ H = 0.30 to 0.50, a morphology transition to a “dot pattern” morphology (tentatively identified as perforated lamellae) and mixed morphologies were observed before macrophase separation. In thicker films, dot patterns were observed for a broad range of Φ H before macrophase separation. The absence of the bicontinuous microemulsion phase reported for bulk blends and thin films of perpendicular lamellae and the presence of dot patterns/perforated lamellae are attributed to preferential migration of the PDMS homopolymer to the wetting layers located at the substrate and free air interfaces, which leads to an asymmetric composition within the film and morphology transition.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Interface capturing simulations of bubble population effects in PWR subchannels

As the computational power of high-performance computing (HPC) facilities grows, so too does the feasibility of using first principle based simulation to study turbulent two-phase flows within complex pressurized water reactor (PWR) geometries. Direct numerical simulation (DNS), integrated with an interface capturing method, allows for the collection of high-fidelity numerical data using advanced analysis techniques. The research presented here employs the massively parallel, finite-element based, unstructured mesh code, PHASTA, to simulate a set of two-phase bubbly flows through PWR subchannel geometries including auxiliary structures (spacer grids and mixing vanes). The main objective of the presented work is to analyze bubble dynamics and turbulence interactions at varying bubble concentrations to support the development of advanced two-phase flow closure models. Turbulent two-phase flows in PWR subchannels were simulated at hydraulic Reynolds numbers of 81,000 with bubble concentrations of 3%–15% by gas volume fraction (768–3928 resolved bubbles, respectively) and compared against a 1% void fraction case (262 bubbles) that had been previously simulated. The finite element mesh utilized for the study at higher bubble concentrations was composed of 1.55 billion elements, compared to the previous study which employed 1.11 billion elements, ensuring all turbulence scales and individual bubbles within the flow are fully resolved. For each case, the resolved initial bubble size was 0.65 mm in diameter (resolved with 25 grid points across the diameter). The simulations were analyzed to find flow features such as the mean velocity profile, bubble relative velocity and the effect of the bubbles on the turbulent conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2018

A scripting interface for GSAS-II

The GSAS-II suite is a complete crystallographic analysis package for all types of X-ray and neutron diffraction data, suited for fitting models ranging from simple materials to proteins, and designed around an integrated graphical user interface. This article describes a new module within GSAS-II , GSASIIscriptable , which provides access to the GSAS-II data structures and an extensible mechanism to run a significant fraction of GSAS-II functionality, particularly for powder diffraction applications, from within Python scripts or directly from commands in a shell/batch script. In conclusion, this allows parallelization in a high-performance computing environment; near ideal speedup is seen with up to 240 simultaneous processes.

47 OTHER INSTRUMENTATION↗

DOE OSTI2019

WISE-CASING: Frequency Domain EM Data from Cymric Oil Field, CA

Cymric oil field frequency domain electromagnetic (FEM) data with two parts of data labeled Part 1 and Part 2. Part 1 utilizes an electrical source line parallel to the receiver line, while Part 2 utilizes an electrical source line at a 75 deg angle to the receiver line. Data are plotted and compared to numerically modeled data to observe electric field response to well structure. In two configuration files are diagrams of the experiment layout.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

Measurement of ion temperature and toroidal flow during magnetic reconnection with a large guide field

Here, ion temperature and toroidal flow along the guide field direction are measured using a new ion tomographic diagnostic on the Magnetic Reconnection eXperiment (MRX) during magnetic reconnection with a guide field strength of about 1.4 and 2.1 times the strength of the reconnecting component. Strong toroidal flows, beyond what has been measured in anti-parallel and lower guide field conditions on MRX, are observed. Sustained ion heating with no discernible structure within the measurement region is also observed. Probe measurements including Langmuir and Mach probe measurements are made to support the tomographic inversion of line-integrated measurements, as well as to provide local measurements of plasma parameters. Measurements of toroidal velocity and ion temperature are supported with time series data. Energy flow into and out of the X-line region is estimated using a guiding center framework and presented in the Appendix of this manuscript, suggesting an outsized role played by parallel electric field in energizing ions. The guiding center approximation is not well satisfied in the region of interest; however, the estimates provide a springboard for future, further experimentation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Prediction of DIII-D Pedestal Structure from Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. An experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (ne) and electron temperature (Te) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (Ip), toroidal magnetic field (Bφ), neutral beam heating power (PNBI) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Prediction of DIII-D Pedestal Structure From Externally Controllable Parameters

The sharp increase of pressure at the edge of a high confinement mode (H-mode) plasma, the pedestal, strongly impacts overall plasma performance. Predicting the pedestal is a necessity to control and optimize tokamak operations. Here, an experimental data-driven machine learning (ML) approach is presented that predicts the pedestal heights and widths of electron density (n e ) and electron temperature (T e ) profiles as well as the separatrix ne from externally controllable parameters such as the plasma shape, heating method and power, and gas puff rate and integrated gas puff. The OMFIT framework was used with DIII-D data to efficiently, robustly, and automatically build a database of pedestal parameters to train machine learning models. Database creation was enabled by the search engine tool for DIII-D data, TokSearch, which parallelizes data fetching, enabling fast searches through basic signals of thousands of DIII-D shots and selection of relevant time intervals. Principal Component Analysis (PCA) separated the database into three clusters that represent classes of plasma shapes that are regularly used in DIII-D. The most important parameters for setting the pedestal structure were plasma current (I p ), toroidal magnetic field (B Φ ), neutral beam heating power (P NBI ) and shaping quantities. The Deep Jointly Informed Neural Networks (DJINN) algorithm was applied to identify suitable neural network (NN) architectures that appropriately capture the features of the pedestal database. Separate NNs were implemented for each pedestal parameter, and ensembling methods were used to improve the prediction accuracy and allowed estimation of the prediction uncertainty. The pedestal predictions of the test dataset lie within the measurement uncertainties of the pedestal parameters. The NN outperformed simple Linear Regression (LR) analysis, indicating non-linear dependencies in the pedestal structure. The presented achievements illustrate a promising path for future research, using feature extraction to infer experimental trends and thereby improve pedestal models as well as deploying NN for a fast pedestal prediction in DIII-D scenario development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization

In this paper, we propose a novel hardware accelerator for GCN inference called I-GCN that significantly improves data locality and reduces unnecessary computation through a new online graph restructuring algorithm we refer to as islandization. The proposed algorithm finds clusters of nodes with strong internal but weak external connections. The islandization process yields two major benefits. First, by processing islands rather than individual nodes, there is better on-chip data reuse and fewer off-chip memory accesses. Second, there is less redundant computation as aggregation for common/shared neighbors in an island can be reused. The parallel search, identification, and leverage of graph islands are all handled purely in hardware at runtime working in an incremental pipelined manner. This is done without any preprocessing of the graph data or adjustment of the GCN model structure.

Geng, Tong↗

NASA NTRS1989

Single-mode projection filters for modal parameter identification for flexible structures

Single-mode projection filters are developed for eigensystem parameter identification from both analytical results and test data. Explicit formulations of these projection filters are derived using the orthogonal matrices of the controllability and observability matrices in the general sense. A global minimum optimization algorithm is applied to update the filter parameters by using the interval analysis method. The updated modal parameters represent the characteristics of the test data. For illustration of this new approach, a numerical simulation for the MAST beam structure is shown by using a one-dimensional global optimization algorithm to identify modal frequencies and damping. The projection filters are practical for parallel processing implementation.

Huang, Jen-Kuang↗

NASA NTRS2001

Better, Cheaper, Faster Molecular Dynamics

Recent, revolutionary progress in genomics and structural, molecular and cellular biology has created new opportunities for molecular-level computer simulations of biological systems by providing vast amounts of data that require interpretation. These opportunities are further enhanced by the increasing availability of massively parallel computers. For many problems, the method of choice is classical molecular dynamics (iterative solving of Newton's equations of motion). It focuses on two main objectives. One is to calculate the relative stability of different states of the system. A typical problem that has' such an objective is computer-aided drug design. Another common objective is to describe evolution of the system towards a low energy (possibly the global minimum energy), "native" state. Perhaps the best example of such a problem is protein folding. Both types of problems share the same difficulty. Often, different states of the system are separated by high energy barriers, which implies that transitions between these states are rare events. This, in turn, can greatly impede exploration of phase space. In some instances this can lead to "quasi non-ergodicity", whereby a part of phase space is inaccessible on time scales of the simulation. To overcome this difficulty and to extend molecular dynamics to "biological" time scales (millisecond or longer) new physical formulations and new algorithmic developments are required. To be efficient they should account for natural limitations of multi-processor computer architecture. I will present work along these lines done in my group. In particular, I will focus on a new approach to calculating the free energies (stability) of different states and to overcoming "the curse of rare events". I will also discuss algorithmic improvements to multiple time step methods and to the treatment of slowly decaying, log-ranged, electrostatic effects.

Pohorille, Andrew↗