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At least 775 records · Page 43

Modeling and analysis of the TF30-P-3 compressor system with inlet pressure distortion

Circumferential inlet distortion testing of a TF30-P-3 afterburning turbofan engine was conducted at NASA-Lewis Research Center. Pratt and Whitney Aircraft analyzed the data using its multiple segment parallel compressor model and classical compressor theory. Distortion attenuation analysis resulted in a detailed flow field calculation with good agreement between multiple segment model predictions and the test data. Sensitivity of the engine stall line to circumferential inlet distortion was calculated on the basis of parallel compressor theory to be more severe than indicated by the data. However, the calculated stall site location was in agreement with high response instrumentation measurements.

Mazzawy, R. S.↗

Asynchronous In Situ Connected-Components Analysis for Complex Fluid flows, In: ISAV '16 Proceedings of the 2nd Workshop on In Situ Infrastructures for Enabling Extreme-scale Analysis and Visualization

The simulation of multiscale physics is an important challenge for scientific computing. For this class of problem, large three-dimensional simulations are performed to advance scientific inquiry. On massively parallel computing systems, the volume of data generated by such approaches can become a productivity bottleneck if the raw data generated from the simulation is analyzed in a post-processing step. To address this, we present a physics-based framework for in situ data reduction that is theoretically grounded in multiscale averaging theory. We show how task parallelism can be exploited to concurrently perform a variety of analysis tasks with data-dependent costs, including the generation of iso-surfaces, morphological analyses, and connected components analysis. All analyses are performed in parallel using distributed memory and use the same domain decomposition as the simulation. A task management framework is constructed to leverage available parallelism within a node for analysis. The capabilities of the framework are to launch asynchronous analysis threads, manage dependencies between different tasks, promote data locality and minimize the impact of data transfers. The framework is applied to analyze GPU-based simulations of two-fluid-phase flow in porous media, generating a set of averaged measures that represents the overall system behavior. We demonstrate how the approach can be applied to perform physically-consistent analysis over fluid sub-regions determined from connected components analysis. Simulations performed on Oak Ridge National Lab's Titan supercomputer are profiled to demonstrate the performance of the associated multi-threaded in situ analysis approach for typical production simulation of two-fluid-phase flow.

Computer Science↗

High Performance Input/Output for Parallel Computer Systems

The goal of our project is to study the I/O characteristics of parallel applications used in Earth Science data processing systems such as Regional Data Centers (RDCs) or EOSDIS. Our approach is to study the runtime behavior of typical programs and the effect of key parameters of the I/O subsystem both under simulation and with direct experimentation on parallel systems. Our three year activity has focused on two items: developing a test bed that facilitates experimentation with parallel I/O, and studying representative programs from the Earth science data processing application domain. The Parallel Virtual File System (PVFS) has been developed for use on a number of platforms including the Tiger Parallel Architecture Workbench (TPAW) simulator, The Intel Paragon, a cluster of DEC Alpha workstations, and the Beowulf system (at CESDIS). PVFS provides considerable flexibility in configuring I/O in a UNIX- like environment. Access to key performance parameters facilitates experimentation. We have studied several key applications fiom levels 1,2 and 3 of the typical RDC processing scenario including instrument calibration and navigation, image classification, and numerical modeling codes. We have also considered large-scale scientific database codes used to organize image data.

Ligon, W. B.↗

Antiferromagnetic spin correlations and pseudogaplike behavior in Ca(Fe 1-x Co x ) 2 As 2 studied by 75 As nuclear magnetic resonance and anisotropic resistivity

We report 75 As nuclear magnetic resonance (NMR) measurements of single-crystalline Ca(Fe 1–x Co x ) 2 As 2 (x=0.023, 0.028, 0.033, and 0.059) annealed at 350°C for 7 days. From the observation of a characteristic shape of 75 As NMR spectra in the stripe-type antiferromagnetic (AFM) state, as in the case of x=0 (T N =170 K), clear evidence for the commensurate AFM phase transition with the concomitant structural phase transition is observed in x=0.023 (T N =106 K) and x=0.028 (T N =53 K). Through the temperature dependence of the Knight shifts and the nuclear spin lattice relaxation rates (1/T 1 ), although stripe-type AFM spin fluctuations are realized in the paramagnetic state as in the case of other iron pnictide superconductors, we found a gradual decrease of the AFM spin fluctuations below a crossover temperature T* that was nearly independent of Co-substitution concentration, and it is attributed to a pseudogaplike behavior in the spin excitation spectra of these systems. The T* feature finds correlation with features in the temperature-dependent interplane resistivity, ρ c (T), but not with the in-plane resistivity ρ a (T). The temperature evolution of anisotropic stripe-type AFM spin fluctuations is tracked in the paramagnetic and pseudogap phases by the 1/T 1 data measured under magnetic fields parallel and perpendicular to the c axis. As a result, based on our NMR data, we have added a pseudogaplike phase to the magnetic and electronic phase diagram of Ca(Fe 1–x Co x ) 2 As 2 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

SU-E-T-255: Development of a Michigan Quality Assurance (MQA) Database for Clinical Machine Operations

Purpose: A unified database system was developed to allow accumulation, review and analysis of quality assurance (QA) data for measurement, treatment, imaging and simulation equipment in our department. Recording these data in a database allows a unified and structured approach to review and analysis of data gathered using commercial database tools. Methods: A clinical database was developed to track records of quality assurance operations on linear accelerators, a computed tomography (CT) scanner, high dose rate (HDR) afterloader and imaging systems such as on-board imaging (OBI) and Calypso in our department. The database was developed using Microsoft Access database and visual basic for applications (VBA) programming interface. Separate modules were written for accumulation, review and analysis of daily, monthly and annual QA data. All modules were designed to use structured query language (SQL) as the basis of data accumulation and review. The SQL strings are dynamically re-written at run time. The database also features embedded documentation, storage of documents produced during QA activities and the ability to annotate all data within the database. Tests are defined in a set of tables that define test type, specific value, and schedule. Results: Daily, Monthly and Annual QA data has been taken in parallel with established procedures to test MQA. The database has been used to aggregate data across machines to examine the consistency of machine parameters and operations within the clinic for several months. Conclusion: The MQA application has been developed as an interface to a commercially available SQL engine (JET 5.0) and a standard database back-end. The MQA system has been used for several months for routine data collection.. The system is robust, relatively simple to extend and can be migrated to a commercial SQL server.

60 APPLIED LIFE SCIENCES↗

Visualization and Data Analysis for High-Performance Computing

This is a set of slides from a guest lecture for a class at the University of Texas, El Paso on visualization and data analysis for high-performance computing. The topics covered are the following: trends in high-performance computing; scientific visualization, such as OpenGL, ray tracing and volume rendering, VTK, and ParaView; data science at scale, such as in-situ visualization, image databases, distributed memory parallelism, shared memory parallelism, VTK-m, "big data", and then an analysis example.

97 MATHEMATICS AND COMPUTING↗

Characterization of bandwidth requirements of algorithms for extreme scale science

Technology trends have resulted in widely different rates of improvement in computational throughput as compared to data movement rates in computer systems. With future systems, the cost of data movement through the memory hierarchy is expected to become even more dominant relative to the cost of performing arithmetic operations, both in terms of time and energy. Therefore, optimizing data access costs will become ever more critical in the coming years. However, unlike the well understood model of computational complexity in terms of the number of elementary operations to execute an algorithm, the inherent data-movement complexity of computations is unknown for most algorithms. Given the crucial importance of optimizing data access costs in scalable parallel systems, it is of great interest to develop techniques for understanding the inherent data movement complexity of an algorithm. In this project, we focus on this fundamental and significant problem.

97 MATHEMATICS AND COMPUTING↗

A parallel Householder tridiagonalization stratagem using scattered square decomposition

The parallel stratagem in this paper uses scattered square decomposition, introduced by Fox (1985), for its data assignment and then exploits parallelism in the solution steps of the sequential Householder tridiagonalization algorithm. One may condense a real symmetric full matrix A of order n into a tridiagonal form by the stratagem in concurrent machines where N(=D-squared) processors are used. Expressions for efficiency and speedup are given for the evaluation of the stratagem. An alternative stratagem which requires less data transmission but more computations is also discussed. The results shown that the Householder method of tridiagonalization may be implemented on a concurrent machine efficiently by scattered square decomposition provided that the number of matrix elements contained in each processor is much larger than the number of processors of the concurrent machine, and the ratio of the time to transmit one data item from one processor to any other processor to the time to perform a floating-point arithmetic operation is small enough.

Chang, H. Y.↗

Organizing Compression of Hyperspectral Imagery to Allow Efficient Parallel Decompression

family of schemes has been devised for organizing the output of an algorithm for predictive data compression of hyperspectral imagery so as to allow efficient parallelization in both the compressor and decompressor. In these schemes, the compressor performs a number of iterations, during each of which a portion of the data is compressed via parallel threads operating on independent portions of the data. The general idea is that for each iteration it is predetermined how much compressed data will be produced from each thread.

Klimesh, Matthew A.↗

Workflow-based automatic processing for Internet of Floating Things crowdsourced data

Data from sensors incorporated into mobile devices, such as networked navigational sensors, can be used to capture detailed environmental information. We describe here a workflow and framework for using sensors on boats to construct unique new datasets of underwater topography (bathymetry). Starting with a large number of measurements of position, depth, etc., obtained from such an Internet of Floating Things, we illustrate how, with a specialized protocol, data can be communicated to cloud resources, even when using delayed, intermittent, or disconnected networks. We then propose a method for automatic sensor calibration based on a novel reputation approach. Sampled depth data are interpolated efficiently on a cloud computing platform in order to provide a continuously updated bathymetric database. Our prototype implementation uses the FACE-IT Galaxy workflow engine to manage network communication and exploits the computational power of GPGPUs in a virtualized cloud environment, working with a CUDA-parallel algorithm, for efficient data processing. We report on an initial evaluation involving data from a sailing vessel in Italian coastal waters.

97 MATHEMATICS AND COMPUTING↗

On-board landmark navigation and attitude reference parallel processor system

An approach to autonomous navigation and attitude reference for earth observing spacecraft is described along with the landmark identification technique based on a sequential similarity detection algorithm (SSDA). Laboratory experiments undertaken to determine if better than one pixel accuracy in registration can be achieved consistent with onboard processor timing and capacity constraints are included. The SSDA is implemented using a multi-microprocessor system including synchronization logic and chip library. The data is processed in parallel stages, effectively reducing the time to match the small known image within a larger image as seen by the onboard image system. Shared memory is incorporated in the system to help communicate intermediate results among microprocessors. The functions include finding mean values and summation of absolute differences over the image search area. The hardware is a low power, compact unit suitable to onboard application with the flexibility to provide for different parameters depending upon the environment.

Gilbert, L. E.↗

Parallelization and Visual Analysis of Multidimensional Fields: Application to Ozone Production, Destruction, and Transport in Three Dimensions

The three-dimensional, spectral transport model used in the current project was first successfully integrated over climatological time scales by Dr. Guang Ping Lou for the simulation of atmospheric N2O using the United Kingdom Meteorological Office (UKMO) 4-dimensional, assimilated wind and temperature data set. A non-parallel, FORTRAN version of this integration using a fairly simple N2O chemistry package containing only photo-chemical reactions was used to verify our initial parallel model results. The integrations reproduced the gross features of the observed stratospheric climatological N2O distributions but also simulated the structure of the stratospheric Antarctic vortex and its evolution. Subsequently, Dr. Thomas Kindler, who produced much of the parallel version of our model, enlarged the N2O model chemistry package to include N2O reactions involving O(D-1) and also introduced assimilated wind data from NASA as well as UKMO. Initially, transport calculations without chemistry were run using Carbon-14 as a non-reactive tracer gas with the result that large differences in the transport properties of the two assimilated wind data sets were apparent from the resultant Carbon-14 distributions. Subsequent calculations for N2O, including its chemistry, with the two input winds data sets with verification from UARS satellite observations have refined the transport differences between the two such that the model's steering capabilities could be used to infer the correct climatological vertical velocity fields required to support the N2O observations. During this process, it was also discovered that both the NASA and the UKMO data contained spurious values in some of the higher frequency wave components, leading to incorrect local transport calculations and ultimately affecting the large scale properties of the model's N2O distributions, particularly at tropical latitudes. Subsequent model runs with wind data that had been filtered to remove some of the high frequency components produced much more realistic N2O distributions. During the past few months, the UKMO wind data base for a complete two-year period was processed into spectral form for model use. This new version of the input transport data base now includes complete temperature fields as well as the necessary wind data. This was done to facilitate advanced chemical calculations in the parallel model which often depend upon temperature. Additional UKMO data is being added as it becomes available.

Schwan, Karsten↗

MAUS: the MICE analysis user software

The Muon Ionization Cooling Experiment (MICE) collaboration has developed the MICE Analysis User Software (MAUS) to simulate and analyze experimental data. It serves as the primary codebase for the experiment, providing for offline batch simulation and reconstruction as well as online data quality checks. The software provides both traditional particle-physics functionalities such as track reconstruction and particle identification, and accelerator physics functions, such as calculating transfer matrices and emittances. The code design is object orientated, but has a top-level structure based on the Map-Reduce model. This allows for parallelization to support live data reconstruction during data-taking operations. MAUS allows users to develop in either Python or C++ and provides APIs for both. Various software engineering practices from industry are also used to ensure correct and maintainable code, including style, unit and integration tests, continuous integration and load testing, code reviews, and distributed version control. The software framework and the simulation and reconstruction capabilities are described.

47 OTHER INSTRUMENTATION↗

A comparison of ULF fluctuations in the solar wind, magnetosheath, and dayside magnetosphere. I - Magnetosheath morphology. II - Field and plasma conditions in the magnetosheath

Simultaneous data from ISEE 1 and 2 in the upstream solar wind, from AMPTE IRM in the subsolar magnetosheath, and from AMPTE CCE in the dayside magnetosphere are used to investigate the properties of the magnetosheath responsible for the transmission into the magnetosphere the ULF waves generated in the solar wind upstream of a quasi-parallel bow shock. The data are used to characterize the magnetosheath both during the periods when azimuthally polarized resonant harmonic ULF magnetic pulsations were observed in the dayside outer maagnetosphere, and when they were not. In addition, a detailed analysis is carried out of magnetic field and plasma conditions in the subsolar magnetosheath during these and other periods.

Engebretson, M. J.↗

Strong parallel evidence of selection during switchgrass sward establishment in hybrid and lowland ecotypes

Switchgrass sward establishment results in up to 90% seedling mortality. The degree of selection during sward establishment has not been reported using modern genetic methods. Pooled leaf samples were sequenced from replicated swards of 46 half-sib families from two breeding groups (lowland and hybrid) before and through 3 years of stand establishment. Pooled allele frequencies were then assessed using fixation indices (Fst) and an independent data set was used to predict the polygenic impact of establishment selection on two traits (heading date and winter survivorship). Last, the DNA pools were assigned survival rankings to predict the sward survival genomically estimated breeding values within the training data set. Strong and parallel selection occured in both breeding groups. Five genomic regions exceeded the significant threshold of 99.9% in >10 families, indicating consistent selection across families and breeding groups. Polygenic trait predictions determined that establishment selection was partially associated with winter survivorship but resulted in variable heading date alterations. The genomewide variation is consistent with selection for a small number of related parental lines. This study observed strong selection for a small number of hybrid and coastal ecotype individuals which are promising germplasm sources for improved sward survival. This confirms prior reports of sward selection during grassland establishment and highlights the strength of pooled DNA sequencing for survival traits.

54 ENVIRONMENTAL SCIENCES↗

Reinforcement Learning for Load-balanced Parallel Particle Tracing

We explore an online reinforcement learning (RL) paradigm to dynamically optimize parallel particle tracing performance in distributed-memory systems. Our method combines three novel components: (1) a work donation algorithm, (2) a high-order workload estimation model, and (3) a communication cost model. First, we design an RL-based work donation algorithm. Our algorithm monitors workloads of processes and creates RL agents to donate data blocks and particles from high-workload processes to low-workload processes to minimize program execution time. The agents learn the donation strategy on the fly based on reward and cost functions designed to consider processes' workload changes and data transfer costs of donation actions. Second, we propose a workload estimation model, helping RL agents estimate the workload distribution of processes in future computations. Third, we design a communication cost model that considers both block and particle data exchange costs, helping RL agents make effective decisions with minimized communication costs. We demonstrate that our algorithm adapts to different flow behaviors in large-scale fluid dynamics, ocean, and weather simulation data. Our algorithm improves parallel particle tracing performance in terms of parallel efficiency, load balance, and costs of I/O and communication for evaluations with up to 16,384 processors.

Distributed and parallel particle tracing↗