Scalable Predictive Analysis in Critically Ill Patients Using a Visual Open Data Analysis Platform.

PubMed

Van Poucke, Sven; Zhang, Zhongheng; Schmitz, Martin; Vukicevic, Milan; Laenen, Margot Vander; Celi, Leo Anthony; De Deyne, Cathy

2016-01-01

With the accumulation of large amounts of health related data, predictive analytics could stimulate the transformation of reactive medicine towards Predictive, Preventive and Personalized (PPPM) Medicine, ultimately affecting both cost and quality of care. However, high-dimensionality and high-complexity of the data involved, prevents data-driven methods from easy translation into clinically relevant models. Additionally, the application of cutting edge predictive methods and data manipulation require substantial programming skills, limiting its direct exploitation by medical domain experts. This leaves a gap between potential and actual data usage. In this study, the authors address this problem by focusing on open, visual environments, suited to be applied by the medical community. Moreover, we review code free applications of big data technologies. As a showcase, a framework was developed for the meaningful use of data from critical care patients by integrating the MIMIC-II database in a data mining environment (RapidMiner) supporting scalable predictive analytics using visual tools (RapidMiner's Radoop extension). Guided by the CRoss-Industry Standard Process for Data Mining (CRISP-DM), the ETL process (Extract, Transform, Load) was initiated by retrieving data from the MIMIC-II tables of interest. As use case, correlation of platelet count and ICU survival was quantitatively assessed. Using visual tools for ETL on Hadoop and predictive modeling in RapidMiner, we developed robust processes for automatic building, parameter optimization and evaluation of various predictive models, under different feature selection schemes. Because these processes can be easily adopted in other projects, this environment is attractive for scalable predictive analytics in health research.

Parallel Visualization Co-Processing of Overnight CFD Propulsion Applications

NASA Technical Reports Server (NTRS)

Edwards, David E.; Haimes, Robert

1999-01-01

An interactive visualization system pV3 is being developed for the investigation of advanced computational methodologies employing visualization and parallel processing for the extraction of information contained in large-scale transient engineering simulations. Visual techniques for extracting information from the data in terms of cutting planes, iso-surfaces, particle tracing and vector fields are included in this system. This paper discusses improvements to the pV3 system developed under NASA's Affordable High Performance Computing project.

AutoBD: Automated Bi-Level Description for Scalable Fine-Grained Visual Categorization.

PubMed

Yao, Hantao; Zhang, Shiliang; Yan, Chenggang; Zhang, Yongdong; Li, Jintao; Tian, Qi

Compared with traditional image classification, fine-grained visual categorization is a more challenging task, because it targets to classify objects belonging to the same species, e.g. , classify hundreds of birds or cars. In the past several years, researchers have made many achievements on this topic. However, most of them are heavily dependent on the artificial annotations, e.g., bounding boxes, part annotations, and so on . The requirement of artificial annotations largely hinders the scalability and application. Motivated to release such dependence, this paper proposes a robust and discriminative visual description named Automated Bi-level Description (AutoBD). "Bi-level" denotes two complementary part-level and object-level visual descriptions, respectively. AutoBD is "automated," because it only requires the image-level labels of training images and does not need any annotations for testing images. Compared with the part annotations labeled by the human, the image-level labels can be easily acquired, which thus makes AutoBD suitable for large-scale visual categorization. Specifically, the part-level description is extracted by identifying the local region saliently representing the visual distinctiveness. The object-level description is extracted from object bounding boxes generated with a co-localization algorithm. Although only using the image-level labels, AutoBD outperforms the recent studies on two public benchmark, i.e. , classification accuracy achieves 81.6% on CUB-200-2011 and 88.9% on Car-196, respectively. On the large-scale Birdsnap data set, AutoBD achieves the accuracy of 68%, which is currently the best performance to the best of our knowledge.Compared with traditional image classification, fine-grained visual categorization is a more challenging task, because it targets to classify objects belonging to the same species, e.g. , classify hundreds of birds or cars. In the past several years, researchers have made many achievements on this topic

Scalable and Interactive Segmentation and Visualization of Neural Processes in EM Datasets

PubMed Central

Jeong, Won-Ki; Beyer, Johanna; Hadwiger, Markus; Vazquez, Amelio; Pfister, Hanspeter; Whitaker, Ross T.

2011-01-01

Recent advances in scanning technology provide high resolution EM (Electron Microscopy) datasets that allow neuroscientists to reconstruct complex neural connections in a nervous system. However, due to the enormous size and complexity of the resulting data, segmentation and visualization of neural processes in EM data is usually a difficult and very time-consuming task. In this paper, we present NeuroTrace, a novel EM volume segmentation and visualization system that consists of two parts: a semi-automatic multiphase level set segmentation with 3D tracking for reconstruction of neural processes, and a specialized volume rendering approach for visualization of EM volumes. It employs view-dependent on-demand filtering and evaluation of a local histogram edge metric, as well as on-the-fly interpolation and ray-casting of implicit surfaces for segmented neural structures. Both methods are implemented on the GPU for interactive performance. NeuroTrace is designed to be scalable to large datasets and data-parallel hardware architectures. A comparison of NeuroTrace with a commonly used manual EM segmentation tool shows that our interactive workflow is faster and easier to use for the reconstruction of complex neural processes. PMID:19834227

Comparison of three-dimensional visualization techniques for depicting the scala vestibuli and scala tympani of the cochlea by using high-resolution MR imaging.

PubMed

Hans, P; Grant, A J; Laitt, R D; Ramsden, R T; Kassner, A; Jackson, A

1999-08-01

Cochlear implantation requires introduction of a stimulating electrode array into the scala vestibuli or scala tympani. Although these structures can be separately identified on many high-resolution scans, it is often difficult to ascertain whether these channels are patent throughout their length. The aim of this study was to determine whether an optimized combination of an imaging protocol and a visualization technique allows routine 3D rendering of the scala vestibuli and scala tympani. A submillimeter T2 fast spin-echo imaging sequence was designed to optimize the performance of 3D visualization methods. The spatial resolution was determined experimentally using primary images and 3D surface and volume renderings from eight healthy subjects. These data were used to develop the imaging sequence and to compare the quality and signal-to-noise dependency of four data visualization algorithms: maximum intensity projection, ray casting with transparent voxels, ray casting with opaque voxels, and isosurface rendering. The ability of these methods to produce 3D renderings of the scala tympani and scala vestibuli was also examined. The imaging technique was used in five patients with sensorineural deafness. Visualization techniques produced optimal results in combination with an isotropic volume imaging sequence. Clinicians preferred the isosurface-rendered images to other 3D visualizations. Both isosurface and ray casting displayed the scala vestibuli and scala tympani throughout their length. Abnormalities were shown in three patients, and in one of these, a focal occlusion of the scala tympani was confirmed at surgery. Three-dimensional images of the scala vestibuli and scala tympani can be routinely produced. The combination of an MR sequence optimized for use with isosurface rendering or ray-casting algorithms can produce 3D images with greater spatial resolution and anatomic detail than has been possible previously.

Visualizing the Positive-Negative Interface of Molecular Electrostatic Potentials as an Educational Tool for Assigning Chemical Polarity

ERIC Educational Resources Information Center

Schonborn, Konrad; Host, Gunnar; Palmerius, Karljohan

2010-01-01

To help in interpreting the polarity of a molecule, charge separation can be visualized by mapping the electrostatic potential at the van der Waals surface using a color gradient or by indicating positive and negative regions of the electrostatic potential using different colored isosurfaces. Although these visualizations capture the molecular…

JuxtaView - A tool for interactive visualization of large imagery on scalable tiled displays

USGS Publications Warehouse

Krishnaprasad, N.K.; Vishwanath, V.; Venkataraman, S.; Rao, A.G.; Renambot, L.; Leigh, J.; Johnson, A.E.; Davis, B.

2004-01-01

JuxtaView is a cluster-based application for viewing ultra-high-resolution images on scalable tiled displays. We present in JuxtaView, a new parallel computing and distributed memory approach for out-of-core montage visualization, using LambdaRAM, a software-based network-level cache system. The ultimate goal of JuxtaView is to enable a user to interactively roam through potentially terabytes of distributed, spatially referenced image data such as those from electron microscopes, satellites and aerial photographs. In working towards this goal, we describe our first prototype implemented over a local area network, where the image is distributed using LambdaRAM, on the memory of all nodes of a PC cluster driving a tiled display wall. Aggressive pre-fetching schemes employed by LambdaRAM help to reduce latency involved in remote memory access. We compare LambdaRAM with a more traditional memory-mapped file approach for out-of-core visualization. ?? 2004 IEEE.

Scalable Adaptive Graphics Environment (SAGE) Software for the Visualization of Large Data Sets on a Video Wall

NASA Technical Reports Server (NTRS)

Jedlovec, Gary; Srikishen, Jayanthi; Edwards, Rita; Cross, David; Welch, Jon; Smith, Matt

2013-01-01

The use of collaborative scientific visualization systems for the analysis, visualization, and sharing of "big data" available from new high resolution remote sensing satellite sensors or four-dimensional numerical model simulations is propelling the wider adoption of ultra-resolution tiled display walls interconnected by high speed networks. These systems require a globally connected and well-integrated operating environment that provides persistent visualization and collaboration services. This abstract and subsequent presentation describes a new collaborative visualization system installed for NASA's Shortterm Prediction Research and Transition (SPoRT) program at Marshall Space Flight Center and its use for Earth science applications. The system consists of a 3 x 4 array of 1920 x 1080 pixel thin bezel video monitors mounted on a wall in a scientific collaboration lab. The monitors are physically and virtually integrated into a 14' x 7' for video display. The display of scientific data on the video wall is controlled by a single Alienware Aurora PC with a 2nd Generation Intel Core 4.1 GHz processor, 32 GB memory, and an AMD Fire Pro W600 video card with 6 mini display port connections. Six mini display-to-dual DVI cables are used to connect the 12 individual video monitors. The open source Scalable Adaptive Graphics Environment (SAGE) windowing and media control framework, running on top of the Ubuntu 12 Linux operating system, allows several users to simultaneously control the display and storage of high resolution still and moving graphics in a variety of formats, on tiled display walls of any size. The Ubuntu operating system supports the open source Scalable Adaptive Graphics Environment (SAGE) software which provides a common environment, or framework, enabling its users to access, display and share a variety of data-intensive information. This information can be digital-cinema animations, high-resolution images, high-definition video

Scalable Adaptive Graphics Environment (SAGE) Software for the Visualization of Large Data Sets on a Video Wall

NASA Astrophysics Data System (ADS)

Jedlovec, G.; Srikishen, J.; Edwards, R.; Cross, D.; Welch, J. D.; Smith, M. R.

2013-12-01

The use of collaborative scientific visualization systems for the analysis, visualization, and sharing of 'big data' available from new high resolution remote sensing satellite sensors or four-dimensional numerical model simulations is propelling the wider adoption of ultra-resolution tiled display walls interconnected by high speed networks. These systems require a globally connected and well-integrated operating environment that provides persistent visualization and collaboration services. This abstract and subsequent presentation describes a new collaborative visualization system installed for NASA's Short-term Prediction Research and Transition (SPoRT) program at Marshall Space Flight Center and its use for Earth science applications. The system consists of a 3 x 4 array of 1920 x 1080 pixel thin bezel video monitors mounted on a wall in a scientific collaboration lab. The monitors are physically and virtually integrated into a 14' x 7' for video display. The display of scientific data on the video wall is controlled by a single Alienware Aurora PC with a 2nd Generation Intel Core 4.1 GHz processor, 32 GB memory, and an AMD Fire Pro W600 video card with 6 mini display port connections. Six mini display-to-dual DVI cables are used to connect the 12 individual video monitors. The open source Scalable Adaptive Graphics Environment (SAGE) windowing and media control framework, running on top of the Ubuntu 12 Linux operating system, allows several users to simultaneously control the display and storage of high resolution still and moving graphics in a variety of formats, on tiled display walls of any size. The Ubuntu operating system supports the open source Scalable Adaptive Graphics Environment (SAGE) software which provides a common environment, or framework, enabling its users to access, display and share a variety of data-intensive information. This information can be digital-cinema animations, high-resolution images, high-definition video

Scalable and portable visualization of large atomistic datasets

NASA Astrophysics Data System (ADS)

Sharma, Ashish; Kalia, Rajiv K.; Nakano, Aiichiro; Vashishta, Priya

2004-10-01

A scalable and portable code named Atomsviewer has been developed to interactively visualize a large atomistic dataset consisting of up to a billion atoms. The code uses a hierarchical view frustum-culling algorithm based on the octree data structure to efficiently remove atoms outside of the user's field-of-view. Probabilistic and depth-based occlusion-culling algorithms then select atoms, which have a high probability of being visible. Finally a multiresolution algorithm is used to render the selected subset of visible atoms at varying levels of detail. Atomsviewer is written in C++ and OpenGL, and it has been tested on a number of architectures including Windows, Macintosh, and SGI. Atomsviewer has been used to visualize tens of millions of atoms on a standard desktop computer and, in its parallel version, up to a billion atoms. Program summaryTitle of program: Atomsviewer Catalogue identifier: ADUM Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADUM Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computer for which the program is designed and others on which it has been tested: 2.4 GHz Pentium 4/Xeon processor, professional graphics card; Apple G4 (867 MHz)/G5, professional graphics card Operating systems under which the program has been tested: Windows 2000/XP, Mac OS 10.2/10.3, SGI IRIX 6.5 Programming languages used: C++, C and OpenGL Memory required to execute with typical data: 1 gigabyte of RAM High speed storage required: 60 gigabytes No. of lines in the distributed program including test data, etc.: 550 241 No. of bytes in the distributed program including test data, etc.: 6 258 245 Number of bits in a word: Arbitrary Number of processors used: 1 Has the code been vectorized or parallelized: No Distribution format: tar gzip file Nature of physical problem: Scientific visualization of atomic systems Method of solution: Rendering of atoms using computer graphic techniques, culling algorithms for data

Scientific Visualization for Atmospheric Data Analysis in Collaborative Virtual Environments

NASA Astrophysics Data System (ADS)

Engelke, Wito; Flatken, Markus; Garcia, Arturo S.; Bar, Christian; Gerndt, Andreas

2016-04-01

terabytes. The combination of different data sources (e.g., MOLA, HRSC, HiRISE) and selection of presented data (e.g., infrared, spectral, imagery) is also supported. Furthermore, the data is presented unchanged and with the highest possible resolution for the target setup (e.g., power-wall, workstation, laptop) and view distance. The visualization techniques for the volumetric data sets can handle VTK [6] based data sets and also support different grid types as well as a time component. In detail, the integrated volume rendering uses a GPU based ray casting algorithm which was adapted to work in spherical coordinate systems. This approach results in interactive frame-rates without compromising visual fidelity. Besides direct visualization via volume rendering the prototype supports interactive slicing, extraction of iso-surfaces and probing. The latter can also be used for side-by-side comparison and on-the-fly diagram generation within the application. Similarily to the surface data a combination of different data sources is supported as well. For example, the extracted iso-surface of a scalar pressure field can be used for the visualization of the temperature. The software development is supported by the ViSTA VR-toolkit [7] and supports different target systems as well as a wide range of VR-devices. Furthermore, the prototype is scalable to run on laptops, workstations and cluster setups. REFERENCES [1] A. S. Garcia, D. J. Roberts, T. Fernando, C. Bar, R. Wolff, J. Dodiya, W. Engelke, and A. Gerndt, "A collaborative workspace architecture for strengthening collaboration among space scientists," in IEEE Aerospace Conference, (Big Sky, Montana, USA), 7-14 March 2015. [2] W. Engelke, "Mars Cartography VR System 2/3." German Aerospace Center (DLR), 2015. Project Deliverable D4.2. [3] E. Hivon, F. K. Hansen, and A. J. Banday, "The healpix primer," arXivpreprint astro-ph/9905275, 1999. [4] K. M. Gorski, E. Hivon, A. Banday, B. D. Wandelt, F. K. Hansen, M. Reinecke, and M

Trident: scalable compute archives: workflows, visualization, and analysis

NASA Astrophysics Data System (ADS)

Gopu, Arvind; Hayashi, Soichi; Young, Michael D.; Kotulla, Ralf; Henschel, Robert; Harbeck, Daniel

2016-08-01

The Astronomy scientific community has embraced Big Data processing challenges, e.g. associated with time-domain astronomy, and come up with a variety of novel and efficient data processing solutions. However, data processing is only a small part of the Big Data challenge. Efficient knowledge discovery and scientific advancement in the Big Data era requires new and equally efficient tools: modern user interfaces for searching, identifying and viewing data online without direct access to the data; tracking of data provenance; searching, plotting and analyzing metadata; interactive visual analysis, especially of (time-dependent) image data; and the ability to execute pipelines on supercomputing and cloud resources with minimal user overhead or expertise even to novice computing users. The Trident project at Indiana University offers a comprehensive web and cloud-based microservice software suite that enables the straight forward deployment of highly customized Scalable Compute Archive (SCA) systems; including extensive visualization and analysis capabilities, with minimal amount of additional coding. Trident seamlessly scales up or down in terms of data volumes and computational needs, and allows feature sets within a web user interface to be quickly adapted to meet individual project requirements. Domain experts only have to provide code or business logic about handling/visualizing their domain's data products and about executing their pipelines and application work flows. Trident's microservices architecture is made up of light-weight services connected by a REST API and/or a message bus; a web interface elements are built using NodeJS, AngularJS, and HighCharts JavaScript libraries among others while backend services are written in NodeJS, PHP/Zend, and Python. The software suite currently consists of (1) a simple work flow execution framework to integrate, deploy, and execute pipelines and applications (2) a progress service to monitor work flows and sub

AstroBlend: Visualization package for use with Blender

NASA Astrophysics Data System (ADS)

Naiman, J. P.

2015-12-01

AstroBlend is a visualization package for use in the three dimensional animation and modeling software, Blender. It reads data in via a text file or can use pre-fab isosurface files stored as OBJ or Wavefront files. AstroBlend supports a variety of codes such as FLASH (ascl:1010.082), Enzo (ascl:1010.072), and Athena (ascl:1010.014), and combines artistic 3D models with computational astrophysics datasets to create models and animations.

Evaluating Alignment of Shapes by Ensemble Visualization

PubMed Central

Raj, Mukund; Mirzargar, Mahsa; Preston, J. Samuel; Kirby, Robert M.; Whitaker, Ross T.

2016-01-01

The visualization of variability in surfaces embedded in 3D, which is a type of ensemble uncertainty visualization, provides a means of understanding the underlying distribution of a collection or ensemble of surfaces. Although ensemble visualization for isosurfaces has been described in the literature, we conduct an expert-based evaluation of various ensemble visualization techniques in a particular medical imaging application: the construction of atlases or templates from a population of images. In this work, we extend contour boxplot to 3D, allowing us to evaluate it against an enumeration-style visualization of the ensemble members and other conventional visualizations used by atlas builders, namely examining the atlas image and the corresponding images/data provided as part of the construction process. We present feedback from domain experts on the efficacy of contour boxplot compared to other modalities when used as part of the atlas construction and analysis stages of their work. PMID:26186768

Dynamic full-scalability conversion in scalable video coding

NASA Astrophysics Data System (ADS)

Lee, Dong Su; Bae, Tae Meon; Thang, Truong Cong; Ro, Yong Man

2007-02-01

For outstanding coding efficiency with scalability functions, SVC (Scalable Video Coding) is being standardized. SVC can support spatial, temporal and SNR scalability and these scalabilities are useful to provide a smooth video streaming service even in a time varying network such as a mobile environment. But current SVC is insufficient to support dynamic video conversion with scalability, thereby the adaptation of bitrate to meet a fluctuating network condition is limited. In this paper, we propose dynamic full-scalability conversion methods for QoS adaptive video streaming in SVC. To accomplish full scalability dynamic conversion, we develop corresponding bitstream extraction, encoding and decoding schemes. At the encoder, we insert the IDR NAL periodically to solve the problems of spatial scalability conversion. At the extractor, we analyze the SVC bitstream to get the information which enable dynamic extraction. Real time extraction is achieved by using this information. Finally, we develop the decoder so that it can manage the changing scalability. Experimental results showed that dynamic full-scalability conversion was verified and it was necessary for time varying network condition.

3D Visualization of Global Ocean Circulation

NASA Astrophysics Data System (ADS)

Nelson, V. G.; Sharma, R.; Zhang, E.; Schmittner, A.; Jenny, B.

2015-12-01

Advanced 3D visualization techniques are seldom used to explore the dynamic behavior of ocean circulation. Streamlines are an effective method for visualization of flow, and they can be designed to clearly show the dynamic behavior of a fluidic system. We employ vector field editing and extraction software to examine the topology of velocity vector fields generated by a 3D global circulation model coupled to a one-layer atmosphere model simulating preindustrial and last glacial maximum (LGM) conditions. This results in a streamline-based visualization along multiple density isosurfaces on which we visualize points of vertical exchange and the distribution of properties such as temperature and biogeochemical tracers. Previous work involving this model examined the change in the energetics driving overturning circulation and mixing between simulations of LGM and preindustrial conditions. This visualization elucidates the relationship between locations of vertical exchange and mixing, as well as demonstrates the effects of circulation and mixing on the distribution of tracers such as carbon isotopes.

Visualization of a Large Set of Hydrogen Atomic Orbital Contours Using New and Expanded Sets of Parametric Equations

ERIC Educational Resources Information Center

Rhile, Ian J.

2014-01-01

Atomic orbitals are a theme throughout the undergraduate chemistry curriculum, and visualizing them has been a theme in this journal. Contour plots as isosurfaces or contour lines in a plane are the most familiar representations of the hydrogen wave functions. In these representations, a surface of a fixed value of the wave function ? is plotted…

3D Flow visualization in virtual reality

NASA Astrophysics Data System (ADS)

Pietraszewski, Noah; Dhillon, Ranbir; Green, Melissa

2017-11-01

By viewing fluid dynamic isosurfaces in virtual reality (VR), many of the issues associated with the rendering of three-dimensional objects on a two-dimensional screen can be addressed. In addition, viewing a variety of unsteady 3D data sets in VR opens up novel opportunities for education and community outreach. In this work, the vortex wake of a bio-inspired pitching panel was visualized using a three-dimensional structural model of Q-criterion isosurfaces rendered in virtual reality using the HTC Vive. Utilizing the Unity cross-platform gaming engine, a program was developed to allow the user to control and change this model's position and orientation in three-dimensional space. In addition to controlling the model's position and orientation, the user can ``scroll'' forward and backward in time to analyze the formation and shedding of vortices in the wake. Finally, the user can toggle between different quantities, while keeping the time step constant, to analyze flow parameter relationships at specific times during flow development. The information, data, or work presented herein was funded in part by an award from NYS Department of Economic Development (DED) through the Syracuse Center of Excellence.

Perspective: n-type oxide thermoelectrics via visual search strategies

DOE PAGES

Xing, Guangzong; Sun, Jifeng; Ong, Khuong P.; ...

2016-02-12

We discuss and present search strategies for finding new thermoelectric compositions based on first principles electronic structure and transport calculations. We illustrate them by application to a search for potential n-type oxide thermoelectric materials. This includes a screen based on visualization of electronic energy isosurfaces. Lastly, we report compounds that show potential as thermoelectric materials along with detailed properties, including SrTiO 3, which is a known thermoelectric, and appropriately doped KNbO 3 and rutile TiO 2.

Perspective: n-type oxide thermoelectrics via visual search strategies

NASA Astrophysics Data System (ADS)

Xing, Guangzong; Sun, Jifeng; Ong, Khuong P.; Fan, Xiaofeng; Zheng, Weitao; Singh, David J.

2016-05-01

We discuss and present search strategies for finding new thermoelectric compositions based on first principles electronic structure and transport calculations. We illustrate them by application to a search for potential n-type oxide thermoelectric materials. This includes a screen based on visualization of electronic energy isosurfaces. We report compounds that show potential as thermoelectric materials along with detailed properties, including SrTiO3, which is a known thermoelectric, and appropriately doped KNbO3 and rutile TiO2.

BactoGeNIE: A large-scale comparative genome visualization for big displays

DOE PAGES

Aurisano, Jillian; Reda, Khairi; Johnson, Andrew; ...

2015-08-13

The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE throughmore » a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. In conclusion, BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics.« less

BactoGeNIE: a large-scale comparative genome visualization for big displays

PubMed Central

2015-01-01

Background The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. Results In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE through a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. Conclusions BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics. PMID:26329021

BactoGeNIE: A large-scale comparative genome visualization for big displays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aurisano, Jillian; Reda, Khairi; Johnson, Andrew

The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE throughmore » a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. In conclusion, BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics.« less

Tools and Methods for Visualization of Mesoscale Ocean Eddies

NASA Astrophysics Data System (ADS)

Bemis, K. G.; Liu, L.; Silver, D.; Kang, D.; Curchitser, E.

2017-12-01

Mesoscale ocean eddies form in the Gulf Stream and transport heat and nutrients across the ocean basin. The internal structure of these three-dimensional eddies and the kinematics with which they move are critical to a full understanding of their transport capacity. A series of visualization tools have been developed to extract, characterize, and track ocean eddies from 3D modeling results, to visually show the ocean eddy story by applying various illustrative visualization techniques, and to interactively view results stored on a server from a conventional browser. In this work, we apply a feature-based method to track instances of ocean eddies through the time steps of a high-resolution multidecadal regional ocean model and generate a series of eddy paths which reflect the life cycle of individual eddy instances. The basic method uses the Okubu-Weiss parameter to define eddy cores but could be adapted to alternative specifications of an eddy. Stored results include pixel-lists for each eddy instance, tracking metadata for eddy paths, and physical and geometric properties. In the simplest view, isosurfaces are used to display eddies along an eddy path. Individual eddies can then be selected and viewed independently or an eddy path can be viewed in the context of all eddy paths (longer than a specified duration) and the ocean basin. To tell the story of mesoscale ocean eddies, we combined illustrative visualization techniques, including visual effectiveness enhancement, focus+context, and smart visibility, with the extracted volume features to explore eddy characteristics at multiple scales from ocean basin to individual eddy. An evaluation by domain experts indicates that combining our feature-based techniques with illustrative visualization techniques provides an insight into the role eddies play in ocean circulation. A web-based GUI is under development to facilitate easy viewing of stored results. The GUI provides the user control to choose amongst available

Visualizing Gyrokinetic Turbulence in a Tokamak

NASA Astrophysics Data System (ADS)

Stantchev, George

2005-10-01

Multi-dimensional data output from gyrokinetic microturbulence codes are often difficult to visualize, in part due to the non-trivial geometry of the underlying grids, in part due to high irregularity of the relevant scalar field structures in turbulent regions. For instance, traditional isosurface extraction methods are likely to fail for the electrostatic potential field whose level sets may exhibit various geometric pathologies. To address these issues we develop an advanced interactive 3D gyrokinetic turbulence visualization framework which we apply in the study of microtearing instabilities calculated with GS2 in the MAST and NSTX geometries. In these simulations GS2 uses field-line-following coordinates such that the computational domain maps in physical space to a long, twisting flux tube with strong cross-sectional shear. Using statistical wavelet analysis we create a sparse multiple-scale volumetric representation of the relevant scalar fields, which we visualize via a variation of the so called splatting technique. To handle the problem of highly anisotropic flux tube configurations we adapt a geometry-driven surface illumination algorithm that places local light sources for effective feature-enhanced visualization.

Real-time scalable visual analysis on mobile devices

NASA Astrophysics Data System (ADS)

Pattath, Avin; Ebert, David S.; May, Richard A.; Collins, Timothy F.; Pike, William

2008-02-01

Interactive visual presentation of information can help an analyst gain faster and better insight from data. When combined with situational or context information, visualization on mobile devices is invaluable to in-field responders and investigators. However, several challenges are posed by the form-factor of mobile devices in developing such systems. In this paper, we classify these challenges into two broad categories - issues in general mobile computing and issues specific to visual analysis on mobile devices. Using NetworkVis and Infostar as example systems, we illustrate some of the techniques that we employed to overcome many of the identified challenges. NetworkVis is an OpenVG-based real-time network monitoring and visualization system developed for Windows Mobile devices. Infostar is a flash-based interactive, real-time visualization application intended to provide attendees access to conference information. Linked time-synchronous visualization, stylus/button-based interactivity, vector graphics, overview-context techniques, details-on-demand and statistical information display are some of the highlights of these applications.

Scalable Domain Decomposed Monte Carlo Particle Transport

NASA Astrophysics Data System (ADS)

O'Brien, Matthew Joseph

In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation. The main algorithms we consider are: • Domain decomposition of constructive solid geometry: enables extremely large calculations in which the background geometry is too large to fit in the memory of a single computational node. • Load Balancing: keeps the workload per processor as even as possible so the calculation runs efficiently. • Global Particle Find: if particles are on the wrong processor, globally resolve their locations to the correct processor based on particle coordinate and background domain. • Visualizing constructive solid geometry, sourcing particles, deciding that particle streaming communication is completed and spatial redecomposition. These algorithms are some of the most important parallel algorithms required for domain decomposed Monte Carlo particle transport. We demonstrate that our previous algorithms were not scalable, prove that our new algorithms are scalable, and run some of the algorithms up to 2 million MPI processes on the Sequoia supercomputer.

Visualization in hydrological and atmospheric modeling and observation

NASA Astrophysics Data System (ADS)

Helbig, C.; Rink, K.; Kolditz, O.

2013-12-01

In recent years, visualization of geoscientific and climate data has become increasingly important due to challenges such as climate change, flood prediction or the development of water management schemes for arid and semi-arid regions. Models for simulations based on such data often have a large number of heterogeneous input data sets, ranging from remote sensing data and geometric information (such as GPS data) to sensor data from specific observations sites. Data integration using such information is not straightforward and a large number of potential problems may occur due to artifacts, inconsistencies between data sets or errors based on incorrectly calibrated or stained measurement devices. Algorithms to automatically detect various of such problems are often numerically expensive or difficult to parameterize. In contrast, combined visualization of various data sets is often a surprisingly efficient means for an expert to detect artifacts or inconsistencies as well as to discuss properties of the data. Therefore, the development of general visualization strategies for atmospheric or hydrological data will often support researchers during assessment and preprocessing of the data for model setup. When investigating specific phenomena, visualization is vital for assessing the progress of the ongoing simulation during runtime as well as evaluating the plausibility of the results. We propose a number of such strategies based on established visualization methods that - are applicable to a large range of different types of data sets, - are computationally inexpensive to allow application for time-dependent data - can be easily parameterized based on the specific focus of the research. Examples include the highlighting of certain aspects of complex data sets using, for example, an application-dependent parameterization of glyphs, iso-surfaces or streamlines. In addition, we employ basic rendering techniques allowing affine transformations, changes in opacity as well

Scalable nanohelices for predictive studies and enhanced 3D visualization.

PubMed

Meagher, Kwyn A; Doblack, Benjamin N; Ramirez, Mercedes; Davila, Lilian P

2014-11-12

Spring-like materials are ubiquitous in nature and of interest in nanotechnology for energy harvesting, hydrogen storage, and biological sensing applications. For predictive simulations, it has become increasingly important to be able to model the structure of nanohelices accurately. To study the effect of local structure on the properties of these complex geometries one must develop realistic models. To date, software packages are rather limited in creating atomistic helical models. This work focuses on producing atomistic models of silica glass (SiO₂) nanoribbons and nanosprings for molecular dynamics (MD) simulations. Using an MD model of "bulk" silica glass, two computational procedures to precisely create the shape of nanoribbons and nanosprings are presented. The first method employs the AWK programming language and open-source software to effectively carve various shapes of silica nanoribbons from the initial bulk model, using desired dimensions and parametric equations to define a helix. With this method, accurate atomistic silica nanoribbons can be generated for a range of pitch values and dimensions. The second method involves a more robust code which allows flexibility in modeling nanohelical structures. This approach utilizes a C++ code particularly written to implement pre-screening methods as well as the mathematical equations for a helix, resulting in greater precision and efficiency when creating nanospring models. Using these codes, well-defined and scalable nanoribbons and nanosprings suited for atomistic simulations can be effectively created. An added value in both open-source codes is that they can be adapted to reproduce different helical structures, independent of material. In addition, a MATLAB graphical user interface (GUI) is used to enhance learning through visualization and interaction for a general user with the atomistic helical structures. One application of these methods is the recent study of nanohelices via MD simulations for

Visualizing 3D data obtained from microscopy on the Internet.

PubMed

Pittet, J J; Henn, C; Engel, A; Heymann, J B

1999-01-01

The Internet is a powerful communication medium increasingly exploited by business and science alike, especially in structural biology and bioinformatics. The traditional presentation of static two-dimensional images of real-world objects on the limited medium of paper can now be shown interactively in three dimensions. Many facets of this new capability have already been developed, particularly in the form of VRML (virtual reality modeling language), but there is a need to extend this capability for visualizing scientific data. Here we introduce a real-time isosurfacing node for VRML, based on the marching cube approach, allowing interactive isosurfacing. A second node does three-dimensional (3D) texture-based volume-rendering for a variety of representations. The use of computers in the microscopic and structural biosciences is extensive, and many scientific file formats exist. To overcome the problem of accessing such data from VRML and other tools, we implemented extensions to SGI's IFL (image format library). IFL is a file format abstraction layer defining communication between a program and a data file. These technologies are developed in support of the BioImage project, aiming to establish a database prototype for multidimensional microscopic data with the ability to view the data within a 3D interactive environment. Copyright 1999 Academic Press.

Scalable metadata environments (MDE): artistically impelled immersive environments for large-scale data exploration

NASA Astrophysics Data System (ADS)

West, Ruth G.; Margolis, Todd; Prudhomme, Andrew; Schulze, Jürgen P.; Mostafavi, Iman; Lewis, J. P.; Gossmann, Joachim; Singh, Rajvikram

2014-02-01

Scalable Metadata Environments (MDEs) are an artistic approach for designing immersive environments for large scale data exploration in which users interact with data by forming multiscale patterns that they alternatively disrupt and reform. Developed and prototyped as part of an art-science research collaboration, we define an MDE as a 4D virtual environment structured by quantitative and qualitative metadata describing multidimensional data collections. Entire data sets (e.g.10s of millions of records) can be visualized and sonified at multiple scales and at different levels of detail so they can be explored interactively in real-time within MDEs. They are designed to reflect similarities and differences in the underlying data or metadata such that patterns can be visually/aurally sorted in an exploratory fashion by an observer who is not familiar with the details of the mapping from data to visual, auditory or dynamic attributes. While many approaches for visual and auditory data mining exist, MDEs are distinct in that they utilize qualitative and quantitative data and metadata to construct multiple interrelated conceptual coordinate systems. These "regions" function as conceptual lattices for scalable auditory and visual representations within virtual environments computationally driven by multi-GPU CUDA-enabled fluid dyamics systems.

Scalable and expressive medical terminologies.

PubMed

Mays, E; Weida, R; Dionne, R; Laker, M; White, B; Liang, C; Oles, F J

1996-01-01

The K-Rep system, based on description logic, is used to represent and reason with large and expressive controlled medical terminologies. Expressive concept descriptions incorporate semantically precise definitions composed using logical operators, together with important non-semantic information such as synonyms and codes. Examples are drawn from our experience with K-Rep in modeling the InterMed laboratory terminology and also developing a large clinical terminology now in production use at Kaiser-Permanente. System-level scalability of performance is achieved through an object-oriented database system which efficiently maps persistent memory to virtual memory. Equally important is conceptual scalability-the ability to support collaborative development, organization, and visualization of a substantial terminology as it evolves over time. K-Rep addresses this need by logically completing concept definitions and automatically classifying concepts in a taxonomy via subsumption inferences. The K-Rep system includes a general-purpose GUI environment for terminology development and browsing, a custom interface for formulary term maintenance, a C+2 application program interface, and a distributed client-server mode which provides lightweight clients with efficient run-time access to K-Rep by means of a scripting language.

NeuroLines: A Subway Map Metaphor for Visualizing Nanoscale Neuronal Connectivity.

PubMed

Al-Awami, Ali K; Beyer, Johanna; Strobelt, Hendrik; Kasthuri, Narayanan; Lichtman, Jeff W; Pfister, Hanspeter; Hadwiger, Markus

2014-12-01

We present NeuroLines, a novel visualization technique designed for scalable detailed analysis of neuronal connectivity at the nanoscale level. The topology of 3D brain tissue data is abstracted into a multi-scale, relative distance-preserving subway map visualization that allows domain scientists to conduct an interactive analysis of neurons and their connectivity. Nanoscale connectomics aims at reverse-engineering the wiring of the brain. Reconstructing and analyzing the detailed connectivity of neurons and neurites (axons, dendrites) will be crucial for understanding the brain and its development and diseases. However, the enormous scale and complexity of nanoscale neuronal connectivity pose big challenges to existing visualization techniques in terms of scalability. NeuroLines offers a scalable visualization framework that can interactively render thousands of neurites, and that supports the detailed analysis of neuronal structures and their connectivity. We describe and analyze the design of NeuroLines based on two real-world use-cases of our collaborators in developmental neuroscience, and investigate its scalability to large-scale neuronal connectivity data.

A Scalable Cloud Library Empowering Big Data Management, Diagnosis, and Visualization of Cloud-Resolving Models

NASA Astrophysics Data System (ADS)

Zhou, S.; Tao, W. K.; Li, X.; Matsui, T.; Sun, X. H.; Yang, X.

2015-12-01

A cloud-resolving model (CRM) is an atmospheric numerical model that can numerically resolve clouds and cloud systems at 0.25~5km horizontal grid spacings. The main advantage of the CRM is that it can allow explicit interactive processes between microphysics, radiation, turbulence, surface, and aerosols without subgrid cloud fraction, overlapping and convective parameterization. Because of their fine resolution and complex physical processes, it is challenging for the CRM community to i) visualize/inter-compare CRM simulations, ii) diagnose key processes for cloud-precipitation formation and intensity, and iii) evaluate against NASA's field campaign data and L1/L2 satellite data products due to large data volume (~10TB) and complexity of CRM's physical processes. We have been building the Super Cloud Library (SCL) upon a Hadoop framework, capable of CRM database management, distribution, visualization, subsetting, and evaluation in a scalable way. The current SCL capability includes (1) A SCL data model enables various CRM simulation outputs in NetCDF, including the NASA-Unified Weather Research and Forecasting (NU-WRF) and Goddard Cumulus Ensemble (GCE) model, to be accessed and processed by Hadoop, (2) A parallel NetCDF-to-CSV converter supports NU-WRF and GCE model outputs, (3) A technique visualizes Hadoop-resident data with IDL, (4) A technique subsets Hadoop-resident data, compliant to the SCL data model, with HIVE or Impala via HUE's Web interface, (5) A prototype enables a Hadoop MapReduce application to dynamically access and process data residing in a parallel file system, PVFS2 or CephFS, where high performance computing (HPC) simulation outputs such as NU-WRF's and GCE's are located. We are testing Apache Spark to speed up SCL data processing and analysis.With the SCL capabilities, SCL users can conduct large-domain on-demand tasks without downloading voluminous CRM datasets and various observations from NASA Field Campaigns and Satellite data to a

Fast 3D Surface Extraction 2 pages (including abstract)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sewell, Christopher Meyer; Patchett, John M.; Ahrens, James P.

Ocean scientists searching for isosurfaces and/or thresholds of interest in high resolution 3D datasets required a tedious and time-consuming interactive exploration experience. PISTON research and development activities are enabling ocean scientists to rapidly and interactively explore isosurfaces and thresholds in their large data sets using a simple slider with real time calculation and visualization of these features. Ocean Scientists can now visualize more features in less time, helping them gain a better understanding of the high resolution data sets they work with on a daily basis. Isosurface timings (512{sup 3} grid): VTK 7.7 s, Parallel VTK (48-core) 1.3 s, PISTONmore » OpenMP (48-core) 0.2 s, PISTON CUDA (Quadro 6000) 0.1 s.« less

Solid object visualization of 3D ultrasound data

NASA Astrophysics Data System (ADS)

Nelson, Thomas R.; Bailey, Michael J.

2000-04-01

Visualization of volumetric medical data is challenging. Rapid-prototyping (RP) equipment producing solid object prototype models of computer generated structures is directly applicable to visualization of medical anatomic data. The purpose of this study was to develop methods for transferring 3D Ultrasound (3DUS) data to RP equipment for visualization of patient anatomy. 3DUS data were acquired using research and clinical scanning systems. Scaling information was preserved and the data were segmented using threshold and local operators to extract features of interest, converted from voxel raster coordinate format to a set of polygons representing an iso-surface and transferred to the RP machine to create a solid 3D object. Fabrication required 30 to 60 minutes depending on object size and complexity. After creation the model could be touched and viewed. A '3D visualization hardcopy device' has advantages for conveying spatial relations compared to visualization using computer display systems. The hardcopy model may be used for teaching or therapy planning. Objects may be produced at the exact dimension of the original object or scaled up (or down) to facilitate matching the viewers reference frame more optimally. RP models represent a useful means of communicating important information in a tangible fashion to patients and physicians.

Scalable large format 3D displays

NASA Astrophysics Data System (ADS)

Chang, Nelson L.; Damera-Venkata, Niranjan

2010-02-01

We present a general framework for the modeling and optimization of scalable large format 3-D displays using multiple projectors. Based on this framework, we derive algorithms that can robustly optimize the visual quality of an arbitrary combination of projectors (e.g. tiled, superimposed, combinations of the two) without manual adjustment. The framework creates for the first time a new unified paradigm that is agnostic to a particular configuration of projectors yet robustly optimizes for the brightness, contrast, and resolution of that configuration. In addition, we demonstrate that our algorithms support high resolution stereoscopic video at real-time interactive frame rates achieved on commodity graphics hardware. Through complementary polarization, the framework creates high quality multi-projector 3-D displays at low hardware and operational cost for a variety of applications including digital cinema, visualization, and command-and-control walls.

Visual Analytics for Power Grid Contingency Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wong, Pak C.; Huang, Zhenyu; Chen, Yousu

2014-01-20

Contingency analysis is the process of employing different measures to model scenarios, analyze them, and then derive the best response to remove the threats. This application paper focuses on a class of contingency analysis problems found in the power grid management system. A power grid is a geographically distributed interconnected transmission network that transmits and delivers electricity from generators to end users. The power grid contingency analysis problem is increasingly important because of both the growing size of the underlying raw data that need to be analyzed and the urgency to deliver working solutions in an aggressive timeframe. Failure tomore » do so may bring significant financial, economic, and security impacts to all parties involved and the society at large. The paper presents a scalable visual analytics pipeline that transforms about 100 million contingency scenarios to a manageable size and form for grid operators to examine different scenarios and come up with preventive or mitigation strategies to address the problems in a predictive and timely manner. Great attention is given to the computational scalability, information scalability, visual scalability, and display scalability issues surrounding the data analytics pipeline. Most of the large-scale computation requirements of our work are conducted on a Cray XMT multi-threaded parallel computer. The paper demonstrates a number of examples using western North American power grid models and data.« less

Visualization for genomics: the Microbial Genome Viewer.

PubMed

Kerkhoven, Robert; van Enckevort, Frank H J; Boekhorst, Jos; Molenaar, Douwe; Siezen, Roland J

2004-07-22

A Web-based visualization tool, the Microbial Genome Viewer, is presented that allows the user to combine complex genomic data in a highly interactive way. This Web tool enables the interactive generation of chromosome wheels and linear genome maps from genome annotation data stored in a MySQL database. The generated images are in scalable vector graphics (SVG) format, which is suitable for creating high-quality scalable images and dynamic Web representations. Gene-related data such as transcriptome and time-course microarray experiments can be superimposed on the maps for visual inspection. The Microbial Genome Viewer 1.0 is freely available at http://www.cmbi.kun.nl/MGV

Visualization for Molecular Dynamics Simulation of Gas and Metal Surface Interaction

NASA Astrophysics Data System (ADS)

Puzyrkov, D.; Polyakov, S.; Podryga, V.

2016-02-01

The development of methods, algorithms and applications for visualization of molecular dynamics simulation outputs is discussed. The visual analysis of the results of such calculations is a complex and actual problem especially in case of the large scale simulations. To solve this challenging task it is necessary to decide on: 1) what data parameters to render, 2) what type of visualization to choose, 3) what development tools to use. In the present work an attempt to answer these questions was made. For visualization it was offered to draw particles in the corresponding 3D coordinates and also their velocity vectors, trajectories and volume density in the form of isosurfaces or fog. We tested the way of post-processing and visualization based on the Python language with use of additional libraries. Also parallel software was developed that allows processing large volumes of data in the 3D regions of the examined system. This software gives the opportunity to achieve desired results that are obtained in parallel with the calculations, and at the end to collect discrete received frames into a video file. The software package "Enthought Mayavi2" was used as the tool for visualization. This visualization application gave us the opportunity to study the interaction of a gas with a metal surface and to closely observe the adsorption effect.

Scalable Multi-Platform Distribution of Spatial 3d Contents

NASA Astrophysics Data System (ADS)

Klimke, J.; Hagedorn, B.; Döllner, J.

2013-09-01

Virtual 3D city models provide powerful user interfaces for communication of 2D and 3D geoinformation. Providing high quality visualization of massive 3D geoinformation in a scalable, fast, and cost efficient manner is still a challenging task. Especially for mobile and web-based system environments, software and hardware configurations of target systems differ significantly. This makes it hard to provide fast, visually appealing renderings of 3D data throughout a variety of platforms and devices. Current mobile or web-based solutions for 3D visualization usually require raw 3D scene data such as triangle meshes together with textures delivered from server to client, what makes them strongly limited in terms of size and complexity of the models they can handle. In this paper, we introduce a new approach for provisioning of massive, virtual 3D city models on different platforms namely web browsers, smartphones or tablets, by means of an interactive map assembled from artificial oblique image tiles. The key concept is to synthesize such images of a virtual 3D city model by a 3D rendering service in a preprocessing step. This service encapsulates model handling and 3D rendering techniques for high quality visualization of massive 3D models. By generating image tiles using this service, the 3D rendering process is shifted from the client side, which provides major advantages: (a) The complexity of the 3D city model data is decoupled from data transfer complexity (b) the implementation of client applications is simplified significantly as 3D rendering is encapsulated on server side (c) 3D city models can be easily deployed for and used by a large number of concurrent users, leading to a high degree of scalability of the overall approach. All core 3D rendering techniques are performed on a dedicated 3D rendering server, and thin-client applications can be compactly implemented for various devices and platforms.

Computing and Visualizing Reachable Volumes for Maneuvering Satellites

NASA Astrophysics Data System (ADS)

Jiang, M.; de Vries, W.; Pertica, A.; Olivier, S.

2011-09-01

Detecting and predicting maneuvering satellites is an important problem for Space Situational Awareness. The spatial envelope of all possible locations within reach of such a maneuvering satellite is known as the Reachable Volume (RV). As soon as custody of a satellite is lost, calculating the RV and its subsequent time evolution is a critical component in the rapid recovery of the satellite. In this paper, we present a Monte Carlo approach to computing the RV for a given object. Essentially, our approach samples all possible trajectories by randomizing thrust-vectors, thrust magnitudes and time of burn. At any given instance, the distribution of the "point-cloud" of the virtual particles defines the RV. For short orbital time-scales, the temporal evolution of the point-cloud can result in complex, multi-reentrant manifolds. Visualization plays an important role in gaining insight and understanding into this complex and evolving manifold. In the second part of this paper, we focus on how to effectively visualize the large number of virtual trajectories and the computed RV. We present a real-time out-of-core rendering technique for visualizing the large number of virtual trajectories. We also examine different techniques for visualizing the computed volume of probability density distribution, including volume slicing, convex hull and isosurfacing. We compare and contrast these techniques in terms of computational cost and visualization effectiveness, and describe the main implementation issues encountered during our development process. Finally, we will present some of the results from our end-to-end system for computing and visualizing RVs using examples of maneuvering satellites.

Visualization of AMR data with multi-level dual-mesh interpolation.

PubMed

Moran, Patrick J; Ellsworth, David

2011-12-01

We present a new technique for providing interpolation within cell-centered Adaptive Mesh Refinement (AMR) data that achieves C(0) continuity throughout the 3D domain. Our technique improves on earlier work in that it does not require that adjacent patches differ by at most one refinement level. Our approach takes the dual of each mesh patch and generates "stitching cells" on the fly to fill the gaps between dual meshes. We demonstrate applications of our technique with data from Enzo, an AMR cosmological structure formation simulation code. We show ray-cast visualizations that include contributions from particle data (dark matter and stars, also output by Enzo) and gridded hydrodynamic data. We also show results from isosurface studies, including surfaces in regions where adjacent patches differ by more than one refinement level. © 2011 IEEE

Three-dimensional visualization system as an aid for facial surgical planning

NASA Astrophysics Data System (ADS)

Barre, Sebastien; Fernandez-Maloigne, Christine; Paume, Patricia; Subrenat, Gilles

2001-05-01

We present an aid for facial deformities treatment. We designed a system for surgical planning and prediction of human facial aspect after maxillo-facial surgery. We study the 3D reconstruction process of the tissues involved in the simulation, starting from CT acquisitions. 3D iso-surfaces meshes of soft tissues and bone structures are built. A sparse set of still photographs is used to reconstruct a 360 degree(s) texture of the facial surface and increase its visual realism. Reconstructed objects are inserted into an object-oriented, portable and scriptable visualization software allowing the practitioner to manipulate and visualize them interactively. Several LODs (Level-Of- Details) techniques are used to ensure usability. Bone structures are separated and moved by means of cut planes matching orthognatic surgery procedures. We simulate soft tissue deformations by creating a physically-based springs model between both tissues. The new static state of the facial model is computed by minimizing the energy of the springs system to achieve equilibrium. This process is optimized by transferring informations like participation hints at vertex-level between a warped generic model and the facial mesh.

A Scalable Cyberinfrastructure for Interactive Visualization of Terascale Microscopy Data.

PubMed

Venkat, A; Christensen, C; Gyulassy, A; Summa, B; Federer, F; Angelucci, A; Pascucci, V

2016-08-01

The goal of the recently emerged field of connectomics is to generate a wiring diagram of the brain at different scales. To identify brain circuitry, neuroscientists use specialized microscopes to perform multichannel imaging of labeled neurons at a very high resolution. CLARITY tissue clearing allows imaging labeled circuits through entire tissue blocks, without the need for tissue sectioning and section-to-section alignment. Imaging the large and complex non-human primate brain with sufficient resolution to identify and disambiguate between axons, in particular, produces massive data, creating great computational challenges to the study of neural circuits. Researchers require novel software capabilities for compiling, stitching, and visualizing large imagery. In this work, we detail the image acquisition process and a hierarchical streaming platform, ViSUS, that enables interactive visualization of these massive multi-volume datasets using a standard desktop computer. The ViSUS visualization framework has previously been shown to be suitable for 3D combustion simulation, climate simulation and visualization of large scale panoramic images. The platform is organized around a hierarchical cache oblivious data layout, called the IDX file format, which enables interactive visualization and exploration in ViSUS, scaling to the largest 3D images. In this paper we showcase the VISUS framework used in an interactive setting with the microscopy data.

In-Situ Visualization Experiments with ParaView Cinema in RAGE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kares, Robert John

2015-10-15

A previous paper described some numerical experiments performed using the ParaView/Catalyst in-situ visualization infrastructure deployed in the Los Alamos RAGE radiation-hydrodynamics code to produce images from a running large scale 3D ICF simulation. One challenge of the in-situ approach apparent in these experiments was the difficulty of choosing parameters likes isosurface values for the visualizations to be produced from the running simulation without the benefit of prior knowledge of the simulation results and the resultant cost of recomputing in-situ generated images when parameters are chosen suboptimally. A proposed method of addressing this difficulty is to simply render multiple images atmore » runtime with a range of possible parameter values to produce a large database of images and to provide the user with a tool for managing the resulting database of imagery. Recently, ParaView/Catalyst has been extended to include such a capability via the so-called Cinema framework. Here I describe some initial experiments with the first delivery of Cinema and make some recommendations for future extensions of Cinema’s capabilities.« less

Integration of an intelligent systems behavior simulator and a scalable soldier-machine interface

NASA Astrophysics Data System (ADS)

Johnson, Tony; Manteuffel, Chris; Brewster, Benjamin; Tierney, Terry

2007-04-01

As the Army's Future Combat Systems (FCS) introduce emerging technologies and new force structures to the battlefield, soldiers will increasingly face new challenges in workload management. The next generation warfighter will be responsible for effectively managing robotic assets in addition to performing other missions. Studies of future battlefield operational scenarios involving the use of automation, including the specification of existing and proposed technologies, will provide significant insight into potential problem areas regarding soldier workload. The US Army Tank Automotive Research, Development, and Engineering Center (TARDEC) is currently executing an Army technology objective program to analyze and evaluate the effect of automated technologies and their associated control devices with respect to soldier workload. The Human-Robotic Interface (HRI) Intelligent Systems Behavior Simulator (ISBS) is a human performance measurement simulation system that allows modelers to develop constructive simulations of military scenarios with various deployments of interface technologies in order to evaluate operator effectiveness. One such interface is TARDEC's Scalable Soldier-Machine Interface (SMI). The scalable SMI provides a configurable machine interface application that is capable of adapting to several hardware platforms by recognizing the physical space limitations of the display device. This paper describes the integration of the ISBS and Scalable SMI applications, which will ultimately benefit both systems. The ISBS will be able to use the Scalable SMI to visualize the behaviors of virtual soldiers performing HRI tasks, such as route planning, and the scalable SMI will benefit from stimuli provided by the ISBS simulation environment. The paper describes the background of each system and details of the system integration approach.

A Scalable Cyberinfrastructure for Interactive Visualization of Terascale Microscopy Data

PubMed Central

Venkat, A.; Christensen, C.; Gyulassy, A.; Summa, B.; Federer, F.; Angelucci, A.; Pascucci, V.

2017-01-01

The goal of the recently emerged field of connectomics is to generate a wiring diagram of the brain at different scales. To identify brain circuitry, neuroscientists use specialized microscopes to perform multichannel imaging of labeled neurons at a very high resolution. CLARITY tissue clearing allows imaging labeled circuits through entire tissue blocks, without the need for tissue sectioning and section-to-section alignment. Imaging the large and complex non-human primate brain with sufficient resolution to identify and disambiguate between axons, in particular, produces massive data, creating great computational challenges to the study of neural circuits. Researchers require novel software capabilities for compiling, stitching, and visualizing large imagery. In this work, we detail the image acquisition process and a hierarchical streaming platform, ViSUS, that enables interactive visualization of these massive multi-volume datasets using a standard desktop computer. The ViSUS visualization framework has previously been shown to be suitable for 3D combustion simulation, climate simulation and visualization of large scale panoramic images. The platform is organized around a hierarchical cache oblivious data layout, called the IDX file format, which enables interactive visualization and exploration in ViSUS, scaling to the largest 3D images. In this paper we showcase the VISUS framework used in an interactive setting with the microscopy data. PMID:28638896

Vortex Filaments in Grids for Scalable, Fine Smoke Simulation.

PubMed

Meng, Zhang; Weixin, Si; Yinling, Qian; Hanqiu, Sun; Jing, Qin; Heng, Pheng-Ann

2015-01-01

Vortex modeling can produce attractive visual effects of dynamic fluids, which are widely applicable for dynamic media, computer games, special effects, and virtual reality systems. However, it is challenging to effectively simulate intensive and fine detailed fluids such as smoke with fast increasing vortex filaments and smoke particles. The authors propose a novel vortex filaments in grids scheme in which the uniform grids dynamically bridge the vortex filaments and smoke particles for scalable, fine smoke simulation with macroscopic vortex structures. Using the vortex model, their approach supports the trade-off between simulation speed and scale of details. After computing the whole velocity, external control can be easily exerted on the embedded grid to guide the vortex-based smoke motion. The experimental results demonstrate the efficiency of using the proposed scheme for a visually plausible smoke simulation with macroscopic vortex structures.

Toward a Scalable Visualization System for Network Traffic Monitoring

NASA Astrophysics Data System (ADS)

Malécot, Erwan Le; Kohara, Masayoshi; Hori, Yoshiaki; Sakurai, Kouichi

With the multiplication of attacks against computer networks, system administrators are required to monitor carefully the traffic exchanged by the networks they manage. However, that monitoring task is increasingly laborious because of the augmentation of the amount of data to analyze. And that trend is going to intensify with the explosion of the number of devices connected to computer networks along with the global rise of the available network bandwidth. So system administrators now heavily rely on automated tools to assist them and simplify the analysis of the data. Yet, these tools provide limited support and, most of the time, require highly skilled operators. Recently, some research teams have started to study the application of visualization techniques to the analysis of network traffic data. We believe that this original approach can also allow system administrators to deal with the large amount of data they have to process. In this paper, we introduce a tool for network traffic monitoring using visualization techniques that we developed in order to assist the system administrators of our corporate network. We explain how we designed the tool and some of the choices we made regarding the visualization techniques to use. The resulting tool proposes two linked representations of the network traffic and activity, one in 2D and the other in 3D. As 2D and 3D visualization techniques have different assets, we resulted in combining them in our tool to take advantage of their complementarity. We finally tested our tool in order to evaluate the accuracy of our approach.

Coalescent: an open-source and scalable framework for exact calculations in coalescent theory

PubMed Central

2012-01-01

Background Currently, there is no open-source, cross-platform and scalable framework for coalescent analysis in population genetics. There is no scalable GUI based user application either. Such a framework and application would not only drive the creation of more complex and realistic models but also make them truly accessible. Results As a first attempt, we built a framework and user application for the domain of exact calculations in coalescent analysis. The framework provides an API with the concepts of model, data, statistic, phylogeny, gene tree and recursion. Infinite-alleles and infinite-sites models are considered. It defines pluggable computations such as counting and listing all the ancestral configurations and genealogies and computing the exact probability of data. It can visualize a gene tree, trace and visualize the internals of the recursion algorithm for further improvement and attach dynamically a number of output processors. The user application defines jobs in a plug-in like manner so that they can be activated, deactivated, installed or uninstalled on demand. Multiple jobs can be run and their inputs edited. Job inputs are persisted across restarts and running jobs can be cancelled where applicable. Conclusions Coalescent theory plays an increasingly important role in analysing molecular population genetic data. Models involved are mathematically difficult and computationally challenging. An open-source, scalable framework that lets users immediately take advantage of the progress made by others will enable exploration of yet more difficult and realistic models. As models become more complex and mathematically less tractable, the need for an integrated computational approach is obvious. Object oriented designs, though has upfront costs, are practical now and can provide such an integrated approach. PMID:23033878

A transparently scalable visualization architecture for exploring the universe.

PubMed

Fu, Chi-Wing; Hanson, Andrew J

2007-01-01

Modern astronomical instruments produce enormous amounts of three-dimensional data describing the physical Universe. The currently available data sets range from the solar system to nearby stars and portions of the Milky Way Galaxy, including the interstellar medium and some extrasolar planets, and extend out to include galaxies billions of light years away. Because of its gigantic scale and the fact that it is dominated by empty space, modeling and rendering the Universe is very different from modeling and rendering ordinary three-dimensional virtual worlds at human scales. Our purpose is to introduce a comprehensive approach to an architecture solving this visualization problem that encompasses the entire Universe while seeking to be as scale-neutral as possible. One key element is the representation of model-rendering procedures using power scaled coordinates (PSC), along with various PSC-based techniques that we have devised to generalize and optimize the conventional graphics framework to the scale domains of astronomical visualization. Employing this architecture, we have developed an assortment of scale-independent modeling and rendering methods for a large variety of astronomical models, and have demonstrated scale-insensitive interactive visualizations of the physical Universe covering scales ranging from human scale to the Earth, to the solar system, to the Milky Way Galaxy, and to the entire observable Universe.

Scalability problems of simple genetic algorithms.

PubMed

Thierens, D

1999-01-01

Scalable evolutionary computation has become an intensively studied research topic in recent years. The issue of scalability is predominant in any field of algorithmic design, but it became particularly relevant for the design of competent genetic algorithms once the scalability problems of simple genetic algorithms were understood. Here we present some of the work that has aided in getting a clear insight in the scalability problems of simple genetic algorithms. Particularly, we discuss the important issue of building block mixing. We show how the need for mixing places a boundary in the GA parameter space that, together with the boundary from the schema theorem, delimits the region where the GA converges reliably to the optimum in problems of bounded difficulty. This region shrinks rapidly with increasing problem size unless the building blocks are tightly linked in the problem coding structure. In addition, we look at how straightforward extensions of the simple genetic algorithm-namely elitism, niching, and restricted mating are not significantly improving the scalability problems.

Visualizing Cloud Properties and Satellite Imagery: A Tool for Visualization and Information Integration

NASA Astrophysics Data System (ADS)

Chee, T.; Nguyen, L.; Smith, W. L., Jr.; Spangenberg, D.; Palikonda, R.; Bedka, K. M.; Minnis, P.; Thieman, M. M.; Nordeen, M.

2017-12-01

Providing public access to research products including cloud macro and microphysical properties and satellite imagery are a key concern for the NASA Langley Research Center Cloud and Radiation Group. This work describes a web based visualization tool and API that allows end users to easily create customized cloud product and satellite imagery, ground site data and satellite ground track information that is generated dynamically. The tool has two uses, one to visualize the dynamically created imagery and the other to provide access to the dynamically generated imagery directly at a later time. Internally, we leverage our practical experience with large, scalable application practices to develop a system that has the largest potential for scalability as well as the ability to be deployed on the cloud to accommodate scalability issues. We build upon NASA Langley Cloud and Radiation Group's experience with making real-time and historical satellite cloud product information, satellite imagery, ground site data and satellite track information accessible and easily searchable. This tool is the culmination of our prior experience with dynamic imagery generation and provides a way to build a "mash-up" of dynamically generated imagery and related kinds of information that are visualized together to add value to disparate but related information. In support of NASA strategic goals, our group aims to make as much scientific knowledge, observations and products available to the citizen science, research and interested communities as well as for automated systems to acquire the same information for data mining or other analytic purposes. This tool and the underlying API's provide a valuable research tool to a wide audience both as a standalone research tool and also as an easily accessed data source that can easily be mined or used with existing tools.

Immersive Visualization of the Solid Earth

NASA Astrophysics Data System (ADS)

Kreylos, O.; Kellogg, L. H.

2017-12-01

Immersive visualization using virtual reality (VR) display technology offers unique benefits for the visual analysis of complex three-dimensional data such as tomographic images of the mantle and higher-dimensional data such as computational geodynamics models of mantle convection or even planetary dynamos. Unlike "traditional" visualization, which has to project 3D scalar data or vectors onto a 2D screen for display, VR can display 3D data in a pseudo-holographic (head-tracked stereoscopic) form, and does therefore not suffer the distortions of relative positions, sizes, distances, and angles that are inherent in 2D projection and interfere with interpretation. As a result, researchers can apply their spatial reasoning skills to 3D data in the same way they can to real objects or environments, as well as to complex objects like vector fields. 3D Visualizer is an application to visualize 3D volumetric data, such as results from mantle convection simulations or seismic tomography reconstructions, using VR display technology and a strong focus on interactive exploration. Unlike other visualization software, 3D Visualizer does not present static visualizations, such as a set of cross-sections at pre-selected positions and orientations, but instead lets users ask questions of their data, for example by dragging a cross-section through the data's domain with their hands and seeing data mapped onto that cross-section in real time, or by touching a point inside the data domain, and immediately seeing an isosurface connecting all points having the same data value as the touched point. Combined with tools allowing 3D measurements of positions, distances, and angles, and with annotation tools that allow free-hand sketching directly in 3D data space, the outcome of using 3D Visualizer is not primarily a set of pictures, but derived data to be used for subsequent analysis. 3D Visualizer works best in virtual reality, either in high-end facility-scale environments such as CAVEs

Adaptive format conversion for scalable video coding

NASA Astrophysics Data System (ADS)

Wan, Wade K.; Lim, Jae S.

2001-12-01

The enhancement layer in many scalable coding algorithms is composed of residual coding information. There is another type of information that can be transmitted instead of (or in addition to) residual coding. Since the encoder has access to the original sequence, it can utilize adaptive format conversion (AFC) to generate the enhancement layer and transmit the different format conversion methods as enhancement data. This paper investigates the use of adaptive format conversion information as enhancement data in scalable video coding. Experimental results are shown for a wide range of base layer qualities and enhancement bitrates to determine when AFC can improve video scalability. Since the parameters needed for AFC are small compared to residual coding, AFC can provide video scalability at low enhancement layer bitrates that are not possible with residual coding. In addition, AFC can also be used in addition to residual coding to improve video scalability at higher enhancement layer bitrates. Adaptive format conversion has not been studied in detail, but many scalable applications may benefit from it. An example of an application that AFC is well-suited for is the migration path for digital television where AFC can provide immediate video scalability as well as assist future migrations.

VRML and Collaborative Environments: New Tools for Networked Visualization

NASA Astrophysics Data System (ADS)

Crutcher, R. M.; Plante, R. L.; Rajlich, P.

We present two new applications that engage the network as a tool for astronomical research and/or education. The first is a VRML server which allows users over the Web to interactively create three-dimensional visualizations of FITS images contained in the NCSA Astronomy Digital Image Library (ADIL). The server's Web interface allows users to select images from the ADIL, fill in processing parameters, and create renderings featuring isosurfaces, slices, contours, and annotations; the often extensive computations are carried out on an NCSA SGI supercomputer server without the user having an individual account on the system. The user can then download the 3D visualizations as VRML files, which may be rotated and manipulated locally on virtually any class of computer. The second application is the ADILBrowser, a part of the NCSA Horizon Image Data Browser Java package. ADILBrowser allows a group of participants to browse images from the ADIL within a collaborative session. The collaborative environment is provided by the NCSA Habanero package which includes text and audio chat tools and a white board. The ADILBrowser is just an example of a collaborative tool that can be built with the Horizon and Habanero packages. The classes provided by these packages can be assembled to create custom collaborative applications that visualize data either from local disk or from anywhere on the network.

Network-aware scalable video monitoring system for emergency situations with operator-managed fidelity control

NASA Astrophysics Data System (ADS)

Al Hadhrami, Tawfik; Nightingale, James M.; Wang, Qi; Grecos, Christos

2014-05-01

In emergency situations, the ability to remotely monitor unfolding events using high-quality video feeds will significantly improve the incident commander's understanding of the situation and thereby aids effective decision making. This paper presents a novel, adaptive video monitoring system for emergency situations where the normal communications network infrastructure has been severely impaired or is no longer operational. The proposed scheme, operating over a rapidly deployable wireless mesh network, supports real-time video feeds between first responders, forward operating bases and primary command and control centers. Video feeds captured on portable devices carried by first responders and by static visual sensors are encoded in H.264/SVC, the scalable extension to H.264/AVC, allowing efficient, standard-based temporal, spatial, and quality scalability of the video. A three-tier video delivery system is proposed, which balances the need to avoid overuse of mesh nodes with the operational requirements of the emergency management team. In the first tier, the video feeds are delivered at a low spatial and temporal resolution employing only the base layer of the H.264/SVC video stream. Routing in this mode is designed to employ all nodes across the entire mesh network. In the second tier, whenever operational considerations require that commanders or operators focus on a particular video feed, a `fidelity control' mechanism at the monitoring station sends control messages to the routing and scheduling agents in the mesh network, which increase the quality of the received picture using SNR scalability while conserving bandwidth by maintaining a low frame rate. In this mode, routing decisions are based on reliable packet delivery with the most reliable routes being used to deliver the base and lower enhancement layers; as fidelity is increased and more scalable layers are transmitted they will be assigned to routes in descending order of reliability. The third tier

Provenance Storage, Querying, and Visualization in PBase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kianmajd, Parisa; Ludascher, Bertram; Missier, Paolo

2015-01-01

We present PBase, a repository for scientific workflows and their corresponding provenance information that facilitates the sharing of experiments among the scientific community. PBase is interoperable since it uses ProvONE, a standard provenance model for scientific workflows. Workflows and traces are stored in RDF, and with the support of SPARQL and the tree cover encoding, the repository provides a scalable infrastructure for querying the provenance data. Furthermore, through its user interface, it is possible to: visualize workflows and execution traces; visualize reachability relations within these traces; issue SPARQL queries; and visualize query results.

UpSetR: an R package for the visualization of intersecting sets and their properties.

PubMed

Conway, Jake R; Lex, Alexander; Gehlenborg, Nils

2017-09-15

Venn and Euler diagrams are a popular yet inadequate solution for quantitative visualization of set intersections. A scalable alternative to Venn and Euler diagrams for visualizing intersecting sets and their properties is needed. We developed UpSetR, an open source R package that employs a scalable matrix-based visualization to show intersections of sets, their size, and other properties. UpSetR is available at https://github.com/hms-dbmi/UpSetR/ and released under the MIT License. A Shiny app is available at https://gehlenborglab.shinyapps.io/upsetr/ . nils@hms.harvard.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

UpSetR: an R package for the visualization of intersecting sets and their properties

PubMed Central

Conway, Jake R.; Lex, Alexander; Gehlenborg, Nils

2017-01-01

Abstract Motivation: Venn and Euler diagrams are a popular yet inadequate solution for quantitative visualization of set intersections. A scalable alternative to Venn and Euler diagrams for visualizing intersecting sets and their properties is needed. Results: We developed UpSetR, an open source R package that employs a scalable matrix-based visualization to show intersections of sets, their size, and other properties. Availability and implementation: UpSetR is available at https://github.com/hms-dbmi/UpSetR/ and released under the MIT License. A Shiny app is available at https://gehlenborglab.shinyapps.io/upsetr/. Contact: nils@hms.harvard.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28645171

Volumetric visualization algorithm development for an FPGA-based custom computing machine

NASA Astrophysics Data System (ADS)

Sallinen, Sami J.; Alakuijala, Jyrki; Helminen, Hannu; Laitinen, Joakim

1998-05-01

Rendering volumetric medical images is a burdensome computational task for contemporary computers due to the large size of the data sets. Custom designed reconfigurable hardware could considerably speed up volume visualization if an algorithm suitable for the platform is used. We present an algorithm and speedup techniques for visualizing volumetric medical CT and MR images with a custom-computing machine based on a Field Programmable Gate Array (FPGA). We also present simulated performance results of the proposed algorithm calculated with a software implementation running on a desktop PC. Our algorithm is capable of generating perspective projection renderings of single and multiple isosurfaces with transparency, simulated X-ray images, and Maximum Intensity Projections (MIP). Although more speedup techniques exist for parallel projection than for perspective projection, we have constrained ourselves to perspective viewing, because of its importance in the field of radiotherapy. The algorithm we have developed is based on ray casting, and the rendering is sped up by three different methods: shading speedup by gradient precalculation, a new generalized version of Ray-Acceleration by Distance Coding (RADC), and background ray elimination by speculative ray selection.

Scalable and Manageable Storage Systems

DTIC Science & Technology

2000-12-01

Despite our long- distance relationship, my brothers and sisters, Charfeddine, Amel, Ghazi, Hajer, Nabeel , and Ines overwhelmed me with more love and...that enable storage sys - tems to be more cost-effectively scalable. Furthermore, the dissertation proposes an approach to ensure automatic load...and addresses three key technical challenges to making storage sys - tems more cost-effectively scalable and manageable. 1.2 Dissertation research The

Scalable L-infinite coding of meshes.

PubMed

Munteanu, Adrian; Cernea, Dan C; Alecu, Alin; Cornelis, Jan; Schelkens, Peter

2010-01-01

The paper investigates the novel concept of local-error control in mesh geometry encoding. In contrast to traditional mesh-coding systems that use the mean-square error as target distortion metric, this paper proposes a new L-infinite mesh-coding approach, for which the target distortion metric is the L-infinite distortion. In this context, a novel wavelet-based L-infinite-constrained coding approach for meshes is proposed, which ensures that the maximum error between the vertex positions in the original and decoded meshes is lower than a given upper bound. Furthermore, the proposed system achieves scalability in L-infinite sense, that is, any decoding of the input stream will correspond to a perfectly predictable L-infinite distortion upper bound. An instantiation of the proposed L-infinite-coding approach is demonstrated for MESHGRID, which is a scalable 3D object encoding system, part of MPEG-4 AFX. In this context, the advantages of scalable L-infinite coding over L-2-oriented coding are experimentally demonstrated. One concludes that the proposed L-infinite mesh-coding approach guarantees an upper bound on the local error in the decoded mesh, it enables a fast real-time implementation of the rate allocation, and it preserves all the scalability features and animation capabilities of the employed scalable mesh codec.

Wanted: Scalable Tracers for Diffusion Measurements

PubMed Central

2015-01-01

Scalable tracers are potentially a useful tool to examine diffusion mechanisms and to predict diffusion coefficients, particularly for hindered diffusion in complex, heterogeneous, or crowded systems. Scalable tracers are defined as a series of tracers varying in size but with the same shape, structure, surface chemistry, deformability, and diffusion mechanism. Both chemical homology and constant dynamics are required. In particular, branching must not vary with size, and there must be no transition between ordinary diffusion and reptation. Measurements using scalable tracers yield the mean diffusion coefficient as a function of size alone; measurements using nonscalable tracers yield the variation due to differences in the other properties. Candidate scalable tracers are discussed for two-dimensional (2D) diffusion in membranes and three-dimensional diffusion in aqueous solutions. Correlations to predict the mean diffusion coefficient of globular biomolecules from molecular mass are reviewed briefly. Specific suggestions for the 3D case include the use of synthetic dendrimers or random hyperbranched polymers instead of dextran and the use of core–shell quantum dots. Another useful tool would be a series of scalable tracers varying in deformability alone, prepared by varying the density of crosslinking in a polymer to make say “reinforced Ficoll” or “reinforced hyperbranched polyglycerol.” PMID:25319586

WebGL-enabled 3D visualization of a Solar Flare Simulation

NASA Astrophysics Data System (ADS)

Chen, A.; Cheung, C. M. M.; Chintzoglou, G.

2016-12-01

The visualization of magnetohydrodynamic (MHD) simulations of astrophysical systems such as solar flares often requires specialized software packages (e.g. Paraview and VAPOR). A shortcoming of using such software packages is the inability to share our findings with the public and scientific community in an interactive and engaging manner. By using the javascript-based WebGL application programming interface (API) and the three.js javascript package, we create an online in-browser experience for rendering solar flare simulations that will be interactive and accessible to the general public. The WebGL renderer displays objects such as vector flow fields, streamlines and textured isosurfaces. This allows the user to explore the spatial relation between the solar coronal magnetic field and the thermodynamic structure of the plasma in which the magnetic field is embedded. Plans for extending the features of the renderer will also be presented.

Amira: Multi-Dimensional Scientific Visualization for the GeoSciences in the 21st Century

NASA Astrophysics Data System (ADS)

Bartsch, H.; Erlebacher, G.

2003-12-01

amira (www.amiravis.com) is a general purpose framework for 3D scientific visualization that meets the needs of the non-programmer, the script writer, and the advanced programmer alike. Provided modules may be visually assembled in an interactive manner to create complex visual displays. These modules and their associated user interfaces are controlled either through a mouse, or via an interactive scripting mechanism based on Tcl. We provide interactive demonstrations of the various features of Amira and explain how these may be used to enhance the comprehension of datasets in use in the Earth Sciences community. Its features will be illustrated on scalar and vector fields on grid types ranging from Cartesian to fully unstructured. Specialized extension modules developed by some of our collaborators will be illustrated [1]. These include a module to automatically choose values for salient isosurface identification and extraction, and color maps suitable for volume rendering. During the session, we will present several demonstrations of remote networking, processing of very large spatio-temporal datasets, and various other projects that are underway. In particular, we will demonstrate WEB-IS, a java-applet interface to Amira that allows script editing via the web, and selected data analysis [2]. [1] G. Erlebacher, D. A. Yuen, F. Dubuffet, "Case Study: Visualization and Analysis of High Rayleigh Number -- 3D Convection in the Earth's Mantle", Proceedings of Visualization 2002, pp. 529--532. [2] Y. Wang, G. Erlebacher, Z. A. Garbow, D. A. Yuen, "Web-Based Service of a Visualization Package 'amira' for the Geosciences", Visual Geosciences, 2003.

Rethinking Visual Analytics for Streaming Data Applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crouser, R. Jordan; Franklin, Lyndsey; Cook, Kris

In the age of data science, the use of interactive information visualization techniques has become increasingly ubiquitous. From online scientific journals to the New York Times graphics desk, the utility of interactive visualization for both storytelling and analysis has become ever more apparent. As these techniques have become more readily accessible, the appeal of combining interactive visualization with computational analysis continues to grow. Arising out of a need for scalable, human-driven analysis, primary objective of visual analytics systems is to capitalize on the complementary strengths of human and machine analysis, using interactive visualization as a medium for communication between themore » two. These systems leverage developments from the fields of information visualization, computer graphics, machine learning, and human-computer interaction to support insight generation in areas where purely computational analyses fall short. Over the past decade, visual analytics systems have generated remarkable advances in many historically challenging analytical contexts. These include areas such as modeling political systems [Crouser et al. 2012], detecting financial fraud [Chang et al. 2008], and cybersecurity [Harrison et al. 2012]. In each of these contexts, domain expertise and human intuition is a necessary component of the analysis. This intuition is essential to building trust in the analytical products, as well as supporting the translation of evidence into actionable insight. In addition, each of these examples also highlights the need for scalable analysis. In each case, it is infeasible for a human analyst to manually assess the raw information unaided, and the communication overhead to divide the task between a large number of analysts makes simple parallelism intractable. Regardless of the domain, visual analytics tools strive to optimize the allocation of human analytical resources, and to streamline the sensemaking process on data that is

The Scalable Checkpoint/Restart Library

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moody, A.

The Scalable Checkpoint/Restart (SCR) library provides an interface that codes may use to worite our and read in application-level checkpoints in a scalable fashion. In the current implementation, checkpoint files are cached in local storage (hard disk or RAM disk) on the compute nodes. This technique provides scalable aggregate bandwidth and uses storage resources that are fully dedicated to the job. This approach addresses the two common drawbacks of checkpointing a large-scale application to a shared parallel file system, namely, limited bandwidth and file system contention. In fact, on current platforms, SCR scales linearly with the number of compute nodes.more » It has been benchmarked as high as 720GB/s on 1094 nodes of Atlas, which is nearly two orders of magnitude faster thanthe parallel file system.« less

Earthscape, a Multi-Purpose Interactive 3d Globe Viewer for Hybrid Data Visualization and Analysis

NASA Astrophysics Data System (ADS)

Sarthou, A.; Mas, S.; Jacquin, M.; Moreno, N.; Salamon, A.

2015-08-01

The hybrid visualization and interaction tool EarthScape is presented here. The software is able to display simultaneously LiDAR point clouds, draped videos with moving footprint, volume scientific data (using volume rendering, isosurface and slice plane), raster data such as still satellite images, vector data and 3D models such as buildings or vehicles. The application runs on touch screen devices such as tablets. The software is based on open source libraries, such as OpenSceneGraph, osgEarth and OpenCV, and shader programming is used to implement volume rendering of scientific data. The next goal of EarthScape is to perform data analysis using ENVI Services Engine, a cloud data analysis solution. EarthScape is also designed to be a client of Jagwire which provides multisource geo-referenced video fluxes. When all these components will be included, EarthScape will be a multi-purpose platform that will provide at the same time data analysis, hybrid visualization and complex interactions. The software is available on demand for free at france@exelisvis.com.

Visualization of time-varying MRI data for MS lesion analysis

NASA Astrophysics Data System (ADS)

Tory, Melanie K.; Moeller, Torsten; Atkins, M. Stella

2001-05-01

Conventional methods to diagnose and follow treatment of Multiple Sclerosis require radiologists and technicians to compare current images with older images of a particular patient, on a slic-by-slice basis. Although there has been progress in creating 3D displays of medical images, little attempt has been made to design visual tools that emphasize change over time. We implemented several ideas that attempt to address this deficiency. In one approach, isosurfaces of segmented lesions at each time step were displayed either on the same image (each time step in a different color), or consecutively in an animation. In a second approach, voxel- wise differences between time steps were calculated and displayed statically using ray casting. Animation was used to show cumulative changes over time. Finally, in a method borrowed from computational fluid dynamics (CFD), glyphs (small arrow-like objects) were rendered with a surface model of the lesions to indicate changes at localized points.

A Scalable Distributed Approach to Mobile Robot Vision

NASA Technical Reports Server (NTRS)

Kuipers, Benjamin; Browning, Robert L.; Gribble, William S.

1997-01-01

This paper documents our progress during the first year of work on our original proposal entitled 'A Scalable Distributed Approach to Mobile Robot Vision'. We are pursuing a strategy for real-time visual identification and tracking of complex objects which does not rely on specialized image-processing hardware. In this system perceptual schemas represent objects as a graph of primitive features. Distributed software agents identify and track these features, using variable-geometry image subwindows of limited size. Active control of imaging parameters and selective processing makes simultaneous real-time tracking of many primitive features tractable. Perceptual schemas operate independently from the tracking of primitive features, so that real-time tracking of a set of image features is not hurt by latency in recognition of the object that those features make up. The architecture allows semantically significant features to be tracked with limited expenditure of computational resources, and allows the visual computation to be distributed across a network of processors. Early experiments are described which demonstrate the usefulness of this formulation, followed by a brief overview of our more recent progress (after the first year).

NEXUS Scalable and Distributed Next-Generation Avionics Bus for Space Missions

NASA Technical Reports Server (NTRS)

He, Yutao; Shalom, Eddy; Chau, Savio N.; Some, Raphael R.; Bolotin, Gary S.

2011-01-01

A paper discusses NEXUS, a common, next-generation avionics interconnect that is transparently compatible with wired, fiber-optic, and RF physical layers; provides a flexible, scalable, packet switched topology; is fault-tolerant with sub-microsecond detection/recovery latency; has scalable bandwidth from 1 Kbps to 10 Gbps; has guaranteed real-time determinism with sub-microsecond latency/jitter; has built-in testability; features low power consumption (< 100 mW per Gbps); is lightweight with about a 5,000-logic-gate footprint; and is implemented in a small Bus Interface Unit (BIU) with reconfigurable back-end providing interface to legacy subsystems. NEXUS enhances a commercial interconnect standard, Serial RapidIO, to meet avionics interconnect requirements without breaking the standard. This unified interconnect technology can be used to meet performance, power, size, and reliability requirements of all ranges of equipment, sensors, and actuators at chip-to-chip, board-to-board, or box-to-box boundary. Early results from in-house modeling activity of Serial RapidIO using VisualSim indicate that the use of a switched, high-performance avionics network will provide a quantum leap in spacecraft onboard science and autonomy capability for science and exploration missions.

Disparity : scalable anomaly detection for clusters.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Desai, N.; Bradshaw, R.; Lusk, E.

2008-01-01

In this paper, we describe disparity, a tool that does parallel, scalable anomaly detection for clusters. Disparity uses basic statistical methods and scalable reduction operations to perform data reduction on client nodes and uses these results to locate node anomalies. We discuss the implementation of disparity and present results of its use on a SiCortex SC5832 system.

Performance-scalable volumetric data classification for online industrial inspection

NASA Astrophysics Data System (ADS)

Abraham, Aby J.; Sadki, Mustapha; Lea, R. M.

2002-03-01

Non-intrusive inspection and non-destructive testing of manufactured objects with complex internal structures typically requires the enhancement, analysis and visualization of high-resolution volumetric data. Given the increasing availability of fast 3D scanning technology (e.g. cone-beam CT), enabling on-line detection and accurate discrimination of components or sub-structures, the inherent complexity of classification algorithms inevitably leads to throughput bottlenecks. Indeed, whereas typical inspection throughput requirements range from 1 to 1000 volumes per hour, depending on density and resolution, current computational capability is one to two orders-of-magnitude less. Accordingly, speeding up classification algorithms requires both reduction of algorithm complexity and acceleration of computer performance. A shape-based classification algorithm, offering algorithm complexity reduction, by using ellipses as generic descriptors of solids-of-revolution, and supporting performance-scalability, by exploiting the inherent parallelism of volumetric data, is presented. A two-stage variant of the classical Hough transform is used for ellipse detection and correlation of the detected ellipses facilitates position-, scale- and orientation-invariant component classification. Performance-scalability is achieved cost-effectively by accelerating a PC host with one or more COTS (Commercial-Off-The-Shelf) PCI multiprocessor cards. Experimental results are reported to demonstrate the feasibility and cost-effectiveness of the data-parallel classification algorithm for on-line industrial inspection applications.

Ultrascale collaborative visualization using a display-rich global cyberinfrastructure.

PubMed

Jeong, Byungil; Leigh, Jason; Johnson, Andrew; Renambot, Luc; Brown, Maxine; Jagodic, Ratko; Nam, Sungwon; Hur, Hyejung

2010-01-01

The scalable adaptive graphics environment (SAGE) is high-performance graphics middleware for ultrascale collaborative visualization using a display-rich global cyberinfrastructure. Dozens of sites worldwide use this cyberinfrastructure middleware, which connects high-performance-computing resources over high-speed networks to distributed ultraresolution displays.

High-Speed and Scalable Whole-Brain Imaging in Rodents and Primates.

PubMed

Seiriki, Kaoru; Kasai, Atsushi; Hashimoto, Takeshi; Schulze, Wiebke; Niu, Misaki; Yamaguchi, Shun; Nakazawa, Takanobu; Inoue, Ken-Ichi; Uezono, Shiori; Takada, Masahiko; Naka, Yuichiro; Igarashi, Hisato; Tanuma, Masato; Waschek, James A; Ago, Yukio; Tanaka, Kenji F; Hayata-Takano, Atsuko; Nagayasu, Kazuki; Shintani, Norihito; Hashimoto, Ryota; Kunii, Yasuto; Hino, Mizuki; Matsumoto, Junya; Yabe, Hirooki; Nagai, Takeharu; Fujita, Katsumasa; Matsuda, Toshio; Takuma, Kazuhiro; Baba, Akemichi; Hashimoto, Hitoshi

2017-06-21

Subcellular resolution imaging of the whole brain and subsequent image analysis are prerequisites for understanding anatomical and functional brain networks. Here, we have developed a very high-speed serial-sectioning imaging system named FAST (block-face serial microscopy tomography), which acquires high-resolution images of a whole mouse brain in a speed range comparable to that of light-sheet fluorescence microscopy. FAST enables complete visualization of the brain at a resolution sufficient to resolve all cells and their subcellular structures. FAST renders unbiased quantitative group comparisons of normal and disease model brain cells for the whole brain at a high spatial resolution. Furthermore, FAST is highly scalable to non-human primate brains and human postmortem brain tissues, and can visualize neuronal projections in a whole adult marmoset brain. Thus, FAST provides new opportunities for global approaches that will allow for a better understanding of brain systems in multiple animal models and in human diseases. Copyright © 2017 Elsevier Inc. All rights reserved.

Embedded DCT and wavelet methods for fine granular scalable video: analysis and comparison

NASA Astrophysics Data System (ADS)

van der Schaar-Mitrea, Mihaela; Chen, Yingwei; Radha, Hayder

2000-04-01

Video transmission over bandwidth-varying networks is becoming increasingly important due to emerging applications such as streaming of video over the Internet. The fundamental obstacle in designing such systems resides in the varying characteristics of the Internet (i.e. bandwidth variations and packet-loss patterns). In MPEG-4, a new SNR scalability scheme, called Fine-Granular-Scalability (FGS), is currently under standardization, which is able to adapt in real-time (i.e. at transmission time) to Internet bandwidth variations. The FGS framework consists of a non-scalable motion-predicted base-layer and an intra-coded fine-granular scalable enhancement layer. For example, the base layer can be coded using a DCT-based MPEG-4 compliant, highly efficient video compression scheme. Subsequently, the difference between the original and decoded base-layer is computed, and the resulting FGS-residual signal is intra-frame coded with an embedded scalable coder. In order to achieve high coding efficiency when compressing the FGS enhancement layer, it is crucial to analyze the nature and characteristics of residual signals common to the SNR scalability framework (including FGS). In this paper, we present a thorough analysis of SNR residual signals by evaluating its statistical properties, compaction efficiency and frequency characteristics. The signal analysis revealed that the energy compaction of the DCT and wavelet transforms is limited and the frequency characteristic of SNR residual signals decay rather slowly. Moreover, the blockiness artifacts of the low bit-rate coded base-layer result in artificial high frequencies in the residual signal. Subsequently, a variety of wavelet and embedded DCT coding techniques applicable to the FGS framework are evaluated and their results are interpreted based on the identified signal properties. As expected from the theoretical signal analysis, the rate-distortion performances of the embedded wavelet and DCT-based coders are very

Architecture Knowledge for Evaluating Scalable Databases

DTIC Science & Technology

2015-01-16

problems, arising from the proliferation of new data models and distributed technologies for building scalable, available data stores . Architects must...longer are relational databases the de facto standard for building data repositories. Highly distributed, scalable “ NoSQL ” databases [11] have emerged...This is especially challenging at the data storage layer. The multitude of competing NoSQL database technologies creates a complex and rapidly

In situ visualization for large-scale combustion simulations.

PubMed

Yu, Hongfeng; Wang, Chaoli; Grout, Ray W; Chen, Jacqueline H; Ma, Kwan-Liu

2010-01-01

As scientific supercomputing moves toward petascale and exascale levels, in situ visualization stands out as a scalable way for scientists to view the data their simulations generate. This full picture is crucial particularly for capturing and understanding highly intermittent transient phenomena, such as ignition and extinction events in turbulent combustion.

Power-Scalable Blue-Green Bessel Beams

DTIC Science & Technology

2016-02-23

19b. TELEPHONE NUMBER (Include area code) 02/23/2016 Final Technical JAN 2011 - DEC 2013 Power-Scalable Blue -Green Bessel Beams Siddharth Ramachandran...fiber lasers, non-traditional emission wavelengths, high-power blue -green tunabel lasers U U U SAR 11 Siddharth Ramachandran 617-353-9811 1 Power...Scalable Blue -Green Bessel Beams Siddharth Ramachandran Photonics Center, Boston University, 8 Saint Mary’s Street, Boston, MA 02215 phone: (617) 353

Scalable 3D image conversion and ergonomic evaluation

NASA Astrophysics Data System (ADS)

Kishi, Shinsuke; Kim, Sang Hyun; Shibata, Takashi; Kawai, Takashi; Häkkinen, Jukka; Takatalo, Jari; Nyman, Göte

2008-02-01

Digital 3D cinema has recently become popular and a number of high-quality 3D films have been produced. However, in contrast with advances in 3D display technology, it has been pointed out that there is a lack of suitable 3D content and content creators. Since 3D display methods and viewing environments vary widely, there is expectation that high-quality content will be multi-purposed. On the other hand, there is increasing interest in the bio-medical effects of image content of various types and there are moves toward international standardization, so 3D content production needs to take into consideration safety and conformity with international guidelines. The aim of the authors' research is to contribute to the production and application of 3D content that is safe and comfortable to watch by developing a scalable 3D conversion technology. In this paper, the authors focus on the process of changing the screen size, examining a conversion algorithm and its effectiveness. The authors evaluated the visual load imposed during the viewing of various 3D content converted by the prototype algorithm as compared with ideal conditions and with content expanded without conversion. Sheffe's paired comparison method was used for evaluation. To examine the effects of screen size reduction on viewers, changes in user impression and experience were elucidated using the IBQ methodology. The results of the evaluation are presented along with a discussion of the effectiveness and potential of the developed scalable 3D conversion algorithm and future research tasks.

Medusa: A Scalable MR Console Using USB

PubMed Central

Stang, Pascal P.; Conolly, Steven M.; Santos, Juan M.; Pauly, John M.; Scott, Greig C.

2012-01-01

MRI pulse sequence consoles typically employ closed proprietary hardware, software, and interfaces, making difficult any adaptation for innovative experimental technology. Yet MRI systems research is trending to higher channel count receivers, transmitters, gradient/shims, and unique interfaces for interventional applications. Customized console designs are now feasible for researchers with modern electronic components, but high data rates, synchronization, scalability, and cost present important challenges. Implementing large multi-channel MR systems with efficiency and flexibility requires a scalable modular architecture. With Medusa, we propose an open system architecture using the Universal Serial Bus (USB) for scalability, combined with distributed processing and buffering to address the high data rates and strict synchronization required by multi-channel MRI. Medusa uses a modular design concept based on digital synthesizer, receiver, and gradient blocks, in conjunction with fast programmable logic for sampling and synchronization. Medusa is a form of synthetic instrument, being reconfigurable for a variety of medical/scientific instrumentation needs. The Medusa distributed architecture, scalability, and data bandwidth limits are presented, and its flexibility is demonstrated in a variety of novel MRI applications. PMID:21954200

A New, Scalable and Low Cost Multi-Channel Monitoring System for Polymer Electrolyte Fuel Cells.

PubMed

Calderón, Antonio José; González, Isaías; Calderón, Manuel; Segura, Francisca; Andújar, José Manuel

2016-03-09

In this work a new, scalable and low cost multi-channel monitoring system for Polymer Electrolyte Fuel Cells (PEFCs) has been designed, constructed and experimentally validated. This developed monitoring system performs non-intrusive voltage measurement of each individual cell of a PEFC stack and it is scalable, in the sense that it is capable to carry out measurements in stacks from 1 to 120 cells (from watts to kilowatts). The developed system comprises two main subsystems: hardware devoted to data acquisition (DAQ) and software devoted to real-time monitoring. The DAQ subsystem is based on the low-cost open-source platform Arduino and the real-time monitoring subsystem has been developed using the high-level graphical language NI LabVIEW. Such integration can be considered a novelty in scientific literature for PEFC monitoring systems. An original amplifying and multiplexing board has been designed to increase the Arduino input port availability. Data storage and real-time monitoring have been performed with an easy-to-use interface. Graphical and numerical visualization allows a continuous tracking of cell voltage. Scalability, flexibility, easy-to-use, versatility and low cost are the main features of the proposed approach. The system is described and experimental results are presented. These results demonstrate its suitability to monitor the voltage in a PEFC at cell level.

A New, Scalable and Low Cost Multi-Channel Monitoring System for Polymer Electrolyte Fuel Cells

PubMed Central

Calderón, Antonio José; González, Isaías; Calderón, Manuel; Segura, Francisca; Andújar, José Manuel

2016-01-01

In this work a new, scalable and low cost multi-channel monitoring system for Polymer Electrolyte Fuel Cells (PEFCs) has been designed, constructed and experimentally validated. This developed monitoring system performs non-intrusive voltage measurement of each individual cell of a PEFC stack and it is scalable, in the sense that it is capable to carry out measurements in stacks from 1 to 120 cells (from watts to kilowatts). The developed system comprises two main subsystems: hardware devoted to data acquisition (DAQ) and software devoted to real-time monitoring. The DAQ subsystem is based on the low-cost open-source platform Arduino and the real-time monitoring subsystem has been developed using the high-level graphical language NI LabVIEW. Such integration can be considered a novelty in scientific literature for PEFC monitoring systems. An original amplifying and multiplexing board has been designed to increase the Arduino input port availability. Data storage and real-time monitoring have been performed with an easy-to-use interface. Graphical and numerical visualization allows a continuous tracking of cell voltage. Scalability, flexibility, easy-to-use, versatility and low cost are the main features of the proposed approach. The system is described and experimental results are presented. These results demonstrate its suitability to monitor the voltage in a PEFC at cell level. PMID:27005630

Declarative language design for interactive visualization.

PubMed

Heer, Jeffrey; Bostock, Michael

2010-01-01

We investigate the design of declarative, domain-specific languages for constructing interactive visualizations. By separating specification from execution, declarative languages can simplify development, enable unobtrusive optimization, and support retargeting across platforms. We describe the design of the Protovis specification language and its implementation within an object-oriented, statically-typed programming language (Java). We demonstrate how to support rich visualizations without requiring a toolkit-specific data model and extend Protovis to enable declarative specification of animated transitions. To support cross-platform deployment, we introduce rendering and event-handling infrastructures decoupled from the runtime platform, letting designers retarget visualization specifications (e.g., from desktop to mobile phone) with reduced effort. We also explore optimizations such as runtime compilation of visualization specifications, parallelized execution, and hardware-accelerated rendering. We present benchmark studies measuring the performance gains provided by these optimizations and compare performance to existing Java-based visualization tools, demonstrating scalability improvements exceeding an order of magnitude.

WIFIRE: A Scalable Data-Driven Monitoring, Dynamic Prediction and Resilience Cyberinfrastructure for Wildfires

NASA Astrophysics Data System (ADS)

Altintas, I.; Block, J.; Braun, H.; de Callafon, R. A.; Gollner, M. J.; Smarr, L.; Trouve, A.

2013-12-01

Recent studies confirm that climate change will cause wildfires to increase in frequency and severity in the coming decades especially for California and in much of the North American West. The most critical sustainability issue in the midst of these ever-changing dynamics is how to achieve a new social-ecological equilibrium of this fire ecology. Wildfire wind speeds and directions change in an instant, and first responders can only be effective when they take action as quickly as the conditions change. To deliver information needed for sustainable policy and management in this dynamically changing fire regime, we must capture these details to understand the environmental processes. We are building an end-to-end cyberinfrastructure (CI), called WIFIRE, for real-time and data-driven simulation, prediction and visualization of wildfire behavior. The WIFIRE integrated CI system supports social-ecological resilience to the changing fire ecology regime in the face of urban dynamics and climate change. Networked observations, e.g., heterogeneous satellite data and real-time remote sensor data is integrated with computational techniques in signal processing, visualization, modeling and data assimilation to provide a scalable, technological, and educational solution to monitor weather patterns to predict a wildfire's Rate of Spread. Our collaborative WIFIRE team of scientists, engineers, technologists, government policy managers, private industry, and firefighters architects implement CI pathways that enable joint innovation for wildfire management. Scientific workflows are used as an integrative distributed programming model and simplify the implementation of engineering modules for data-driven simulation, prediction and visualization while allowing integration with large-scale computing facilities. WIFIRE will be scalable to users with different skill-levels via specialized web interfaces and user-specified alerts for environmental events broadcasted to receivers before

Perovskite Technology is Scalable, But Questions Remain about the Best

Science.gov Websites

Methods | News | NREL Perovskite Technology is Scalable, But Questions Remain about the Best Methods News Release: Perovskite Technology is Scalable, But Questions Remain about the Best Methods NREL be used on a larger surface. The NREL researchers examined potential scalable deposition methods

Scalable cloud without dedicated storage

NASA Astrophysics Data System (ADS)

Batkovich, D. V.; Kompaniets, M. V.; Zarochentsev, A. K.

2015-05-01

We present a prototype of a scalable computing cloud. It is intended to be deployed on the basis of a cluster without the separate dedicated storage. The dedicated storage is replaced by the distributed software storage. In addition, all cluster nodes are used both as computing nodes and as storage nodes. This solution increases utilization of the cluster resources as well as improves fault tolerance and performance of the distributed storage. Another advantage of this solution is high scalability with a relatively low initial and maintenance cost. The solution is built on the basis of the open source components like OpenStack, CEPH, etc.

Scalability enhancement of AODV using local link repairing

NASA Astrophysics Data System (ADS)

Jain, Jyoti; Gupta, Roopam; Bandhopadhyay, T. K.

2014-09-01

Dynamic change in the topology of an ad hoc network makes it difficult to design an efficient routing protocol. Scalability of an ad hoc network is also one of the important criteria of research in this field. Most of the research works in ad hoc network focus on routing and medium access protocols and produce simulation results for limited-size networks. Ad hoc on-demand distance vector (AODV) is one of the best reactive routing protocols. In this article, modified routing protocols based on local link repairing of AODV are proposed. Method of finding alternate routes for next-to-next node is proposed in case of link failure. These protocols are beacon-less, means periodic hello message is removed from the basic AODV to improve scalability. Few control packet formats have been changed to accommodate suggested modification. Proposed protocols are simulated to investigate scalability performance and compared with basic AODV protocol. This also proves that local link repairing of proposed protocol improves scalability of the network. From simulation results, it is clear that scalability performance of routing protocol is improved because of link repairing method. We have tested protocols for different terrain area with approximate constant node densities and different traffic load.

SPV: a JavaScript Signaling Pathway Visualizer.

PubMed

Calderone, Alberto; Cesareni, Gianni

2018-03-24

The visualization of molecular interactions annotated in web resources is useful to offer to users such information in a clear intuitive layout. These interactions are frequently represented as binary interactions that are laid out in free space where, different entities, cellular compartments and interaction types are hardly distinguishable. SPV (Signaling Pathway Visualizer) is a free open source JavaScript library which offers a series of pre-defined elements, compartments and interaction types meant to facilitate the representation of signaling pathways consisting of causal interactions without neglecting simple protein-protein interaction networks. freely available under Apache version 2 license; Source code: https://github.com/Sinnefa/SPV_Signaling_Pathway_Visualizer_v1.0. Language: JavaScript; Web technology: Scalable Vector Graphics; Libraries: D3.js. sinnefa@gmail.com.

Scalable Power-Component Models for Concept Testing

DTIC Science & Technology

2011-08-17

Scalable Power-Component Models for Concept Testing, Mazzola, et al . UNCLASSIFIED: Dist A. Approved for public release 2011 NDIA GROUND VEHICLE...Power-Component Models for Concept Testing, Mazzola, et al . UNCLASSIFIED: Dist A. Approved for public release Page 2 of 8 technology that has yet...Technology Symposium (GVSETS) Scalable Power-Component Models for Concept Testing, Mazzola, et al . UNCLASSIFIED: Dist A. Approved for public release

Modular Universal Scalable Ion-trap Quantum Computer

DTIC Science & Technology

2016-06-02

SECURITY CLASSIFICATION OF: The main goal of the original MUSIQC proposal was to construct and demonstrate a modular and universally- expandable ion...Distribution Unlimited UU UU UU UU 02-06-2016 1-Aug-2010 31-Jan-2016 Final Report: Modular Universal Scalable Ion-trap Quantum Computer The views...P.O. Box 12211 Research Triangle Park, NC 27709-2211 Ion trap quantum computation, scalable modular architectures REPORT DOCUMENTATION PAGE 11

Scalable data management, analysis and visualization (SDAV) Institute. Final Scientific/Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Geveci, Berk

The purpose of the SDAV institute is to provide tools and expertise in scientific data management, analysis, and visualization to DOE’s application scientists. Our goal is to actively work with application teams to assist them in achieving breakthrough science, and to provide technical solutions in the data management, analysis, and visualization regimes that are broadly used by the computational science community. Over the last 5 years members of our institute worked directly with application scientists and DOE leadership-class facilities to assist them by applying the best tools and technologies at our disposal. We also enhanced our tools based on inputmore » from scientists on their needs. Many of the applications we have been working with are based on connections with scientists established in previous years. However, we contacted additional scientists though our outreach activities, as well as engaging application teams running on leading DOE computing systems. Our approach is to employ an evolutionary development and deployment process: first considering the application of existing tools, followed by the customization necessary for each particular application, and then the deployment in real frameworks and infrastructures. The institute is organized into three areas, each with area leaders, who keep track of progress, engagement of application scientists, and results. The areas are: (1) Data Management, (2) Data Analysis, and (3) Visualization. Kitware has been involved in the Visualization area. This report covers Kitware’s contributions over the last 5 years (February 2012 – February 2017). For details on the work performed by the SDAV institute as a whole, please see the SDAV final report.« less

Scalable Performance Environments for Parallel Systems

NASA Technical Reports Server (NTRS)

Reed, Daniel A.; Olson, Robert D.; Aydt, Ruth A.; Madhyastha, Tara M.; Birkett, Thomas; Jensen, David W.; Nazief, Bobby A. A.; Totty, Brian K.

1991-01-01

As parallel systems expand in size and complexity, the absence of performance tools for these parallel systems exacerbates the already difficult problems of application program and system software performance tuning. Moreover, given the pace of technological change, we can no longer afford to develop ad hoc, one-of-a-kind performance instrumentation software; we need scalable, portable performance analysis tools. We describe an environment prototype based on the lessons learned from two previous generations of performance data analysis software. Our environment prototype contains a set of performance data transformation modules that can be interconnected in user-specified ways. It is the responsibility of the environment infrastructure to hide details of module interconnection and data sharing. The environment is written in C++ with the graphical displays based on X windows and the Motif toolkit. It allows users to interconnect and configure modules graphically to form an acyclic, directed data analysis graph. Performance trace data are represented in a self-documenting stream format that includes internal definitions of data types, sizes, and names. The environment prototype supports the use of head-mounted displays and sonic data presentation in addition to the traditional use of visual techniques.

A scalable multi-DLP pico-projector system for virtual reality

NASA Astrophysics Data System (ADS)

Teubl, F.; Kurashima, C.; Cabral, M.; Fels, S.; Lopes, R.; Zuffo, M.

2014-03-01

Virtual Reality (VR) environments can offer immersion, interaction and realistic images to users. A VR system is usually expensive and requires special equipment in a complex setup. One approach is to use Commodity-Off-The-Shelf (COTS) desktop multi-projectors manually or camera based calibrated to reduce the cost of VR systems without significant decrease of the visual experience. Additionally, for non-planar screen shapes, special optics such as lenses and mirrors are required thus increasing costs. We propose a low-cost, scalable, flexible and mobile solution that allows building complex VR systems that projects images onto a variety of arbitrary surfaces such as planar, cylindrical and spherical surfaces. This approach combines three key aspects: 1) clusters of DLP-picoprojectors to provide homogeneous and continuous pixel density upon arbitrary surfaces without additional optics; 2) LED lighting technology for energy efficiency and light control; 3) smaller physical footprint for flexibility purposes. Therefore, the proposed system is scalable in terms of pixel density, energy and physical space. To achieve these goals, we developed a multi-projector software library called FastFusion that calibrates all projectors in a uniform image that is presented to viewers. FastFusion uses a camera to automatically calibrate geometric and photometric correction of projected images from ad-hoc positioned projectors, the only requirement is some few pixels overlapping amongst them. We present results with eight Pico-projectors, with 7 lumens (LED) and DLP 0.17 HVGA Chipset.

Visual Analytics for Heterogeneous Geoscience Data

NASA Astrophysics Data System (ADS)

Pan, Y.; Yu, L.; Zhu, F.; Rilee, M. L.; Kuo, K. S.; Jiang, H.; Yu, H.

2017-12-01

Geoscience data obtained from diverse sources have been routinely leveraged by scientists to study various phenomena. The principal data sources include observations and model simulation outputs. These data are characterized by spatiotemporal heterogeneity originated from different instrument design specifications and/or computational model requirements used in data generation processes. Such inherent heterogeneity poses several challenges in exploring and analyzing geoscience data. First, scientists often wish to identify features or patterns co-located among multiple data sources to derive and validate certain hypotheses. Heterogeneous data make it a tedious task to search such features in dissimilar datasets. Second, features of geoscience data are typically multivariate. It is challenging to tackle the high dimensionality of geoscience data and explore the relations among multiple variables in a scalable fashion. Third, there is a lack of transparency in traditional automated approaches, such as feature detection or clustering, in that scientists cannot intuitively interact with their analysis processes and interpret results. To address these issues, we present a new scalable approach that can assist scientists in analyzing voluminous and diverse geoscience data. We expose a high-level query interface that allows users to easily express their customized queries to search features of interest across multiple heterogeneous datasets. For identified features, we develop a visualization interface that enables interactive exploration and analytics in a linked-view manner. Specific visualization techniques such as scatter plots to parallel coordinates are employed in each view to allow users to explore various aspects of features. Different views are linked and refreshed according to user interactions in any individual view. In such a manner, a user can interactively and iteratively gain understanding into the data through a variety of visual analytics operations. We

geoKepler Workflow Module for Computationally Scalable and Reproducible Geoprocessing and Modeling

NASA Astrophysics Data System (ADS)

Cowart, C.; Block, J.; Crawl, D.; Graham, J.; Gupta, A.; Nguyen, M.; de Callafon, R.; Smarr, L.; Altintas, I.

2015-12-01

The NSF-funded WIFIRE project has developed an open-source, online geospatial workflow platform for unifying geoprocessing tools and models for for fire and other geospatially dependent modeling applications. It is a product of WIFIRE's objective to build an end-to-end cyberinfrastructure for real-time and data-driven simulation, prediction and visualization of wildfire behavior. geoKepler includes a set of reusable GIS components, or actors, for the Kepler Scientific Workflow System (https://kepler-project.org). Actors exist for reading and writing GIS data in formats such as Shapefile, GeoJSON, KML, and using OGC web services such as WFS. The actors also allow for calling geoprocessing tools in other packages such as GDAL and GRASS. Kepler integrates functions from multiple platforms and file formats into one framework, thus enabling optimal GIS interoperability, model coupling, and scalability. Products of the GIS actors can be fed directly to models such as FARSITE and WRF. Kepler's ability to schedule and scale processes using Hadoop and Spark also makes geoprocessing ultimately extensible and computationally scalable. The reusable workflows in geoKepler can be made to run automatically when alerted by real-time environmental conditions. Here, we show breakthroughs in the speed of creating complex data for hazard assessments with this platform. We also demonstrate geoKepler workflows that use Data Assimilation to ingest real-time weather data into wildfire simulations, and for data mining techniques to gain insight into environmental conditions affecting fire behavior. Existing machine learning tools and libraries such as R and MLlib are being leveraged for this purpose in Kepler, as well as Kepler's Distributed Data Parallel (DDP) capability to provide a framework for scalable processing. geoKepler workflows can be executed via an iPython notebook as a part of a Jupyter hub at UC San Diego for sharing and reporting of the scientific analysis and results from

Optimizing Performance of Scientific Visualization Software to Support Frontier-Class Computations

DTIC Science & Technology

2015-08-01

Hypersonic Sciences Branch) for providing sample datasets and permission to use an image of Q_Criterion isosurface for this report; Dr Anders Grimsrud...10.1. EnSight CSM and CFD Post processing; c2014 [accessed 2015 July 6] http:// www.ceisoftware.com. Main Page. XDMF; 2014 Nov 7 [2015 July 6] http

A Scalable Analysis Toolkit

NASA Technical Reports Server (NTRS)

Aiken, Alexander

2001-01-01

The Scalable Analysis Toolkit (SAT) project aimed to demonstrate that it is feasible and useful to statically detect software bugs in very large systems. The technical focus of the project was on a relatively new class of constraint-based techniques for analysis software, where the desired facts about programs (e.g., the presence of a particular bug) are phrased as constraint problems to be solved. At the beginning of this project, the most successful forms of formal software analysis were limited forms of automatic theorem proving (as exemplified by the analyses used in language type systems and optimizing compilers), semi-automatic theorem proving for full verification, and model checking. With a few notable exceptions these approaches had not been demonstrated to scale to software systems of even 50,000 lines of code. Realistic approaches to large-scale software analysis cannot hope to make every conceivable formal method scale. Thus, the SAT approach is to mix different methods in one application by using coarse and fast but still adequate methods at the largest scales, and reserving the use of more precise but also more expensive methods at smaller scales for critical aspects (that is, aspects critical to the analysis problem under consideration) of a software system. The principled method proposed for combining a heterogeneous collection of formal systems with different scalability characteristics is mixed constraints. This idea had been used previously in small-scale applications with encouraging results: using mostly coarse methods and narrowly targeted precise methods, useful information (meaning the discovery of bugs in real programs) was obtained with excellent scalability.

Scuba: scalable kernel-based gene prioritization.

PubMed

Zampieri, Guido; Tran, Dinh Van; Donini, Michele; Navarin, Nicolò; Aiolli, Fabio; Sperduti, Alessandro; Valle, Giorgio

2018-01-25

The uncovering of genes linked to human diseases is a pressing challenge in molecular biology and precision medicine. This task is often hindered by the large number of candidate genes and by the heterogeneity of the available information. Computational methods for the prioritization of candidate genes can help to cope with these problems. In particular, kernel-based methods are a powerful resource for the integration of heterogeneous biological knowledge, however, their practical implementation is often precluded by their limited scalability. We propose Scuba, a scalable kernel-based method for gene prioritization. It implements a novel multiple kernel learning approach, based on a semi-supervised perspective and on the optimization of the margin distribution. Scuba is optimized to cope with strongly unbalanced settings where known disease genes are few and large scale predictions are required. Importantly, it is able to efficiently deal both with a large amount of candidate genes and with an arbitrary number of data sources. As a direct consequence of scalability, Scuba integrates also a new efficient strategy to select optimal kernel parameters for each data source. We performed cross-validation experiments and simulated a realistic usage setting, showing that Scuba outperforms a wide range of state-of-the-art methods. Scuba achieves state-of-the-art performance and has enhanced scalability compared to existing kernel-based approaches for genomic data. This method can be useful to prioritize candidate genes, particularly when their number is large or when input data is highly heterogeneous. The code is freely available at https://github.com/gzampieri/Scuba .

PhyloDet: a scalable visualization tool for mapping multiple traits to large evolutionary trees

PubMed Central

Lee, Bongshin; Nachmanson, Lev; Robertson, George; Carlson, Jonathan M.; Heckerman, David

2009-01-01

Summary: Evolutionary biologists are often interested in finding correlations among biological traits across a number of species, as such correlations may lead to testable hypotheses about the underlying function. Because some species are more closely related than others, computing and visualizing these correlations must be done in the context of the evolutionary tree that relates species. In this note, we introduce PhyloDet (short for PhyloDetective), an evolutionary tree visualization tool that enables biologists to visualize multiple traits mapped to the tree. Availability: http://research.microsoft.com/cue/phylodet/ Contact: bongshin@microsoft.com. PMID:19633096

A scalable healthcare information system based on a service-oriented architecture.

PubMed

Yang, Tzu-Hsiang; Sun, Yeali S; Lai, Feipei

2011-06-01

Many existing healthcare information systems are composed of a number of heterogeneous systems and face the important issue of system scalability. This paper first describes the comprehensive healthcare information systems used in National Taiwan University Hospital (NTUH) and then presents a service-oriented architecture (SOA)-based healthcare information system (HIS) based on the service standard HL7. The proposed architecture focuses on system scalability, in terms of both hardware and software. Moreover, we describe how scalability is implemented in rightsizing, service groups, databases, and hardware scalability. Although SOA-based systems sometimes display poor performance, through a performance evaluation of our HIS based on SOA, the average response time for outpatient, inpatient, and emergency HL7Central systems are 0.035, 0.04, and 0.036 s, respectively. The outpatient, inpatient, and emergency WebUI average response times are 0.79, 1.25, and 0.82 s. The scalability of the rightsizing project and our evaluation results show that the SOA HIS we propose provides evidence that SOA can provide system scalability and sustainability in a highly demanding healthcare information system.

Scalable Quantum Networks for Distributed Computing and Sensing

DTIC Science & Technology

2016-04-01

probabilistic measurement , so we developed quantum memories and guided-wave implementations of same, demonstrating controlled delay of a heralded single...Second, fundamental scalability requires a method to synchronize protocols based on quantum measurements , which are inherently probabilistic. To meet...AFRL-AFOSR-UK-TR-2016-0007 Scalable Quantum Networks for Distributed Computing and Sensing Ian Walmsley THE UNIVERSITY OF OXFORD Final Report 04/01

Novel Scalable 3-D MT Inverse Solver

NASA Astrophysics Data System (ADS)

Kuvshinov, A. V.; Kruglyakov, M.; Geraskin, A.

2016-12-01

We present a new, robust and fast, three-dimensional (3-D) magnetotelluric (MT) inverse solver. As a forward modelling engine a highly-scalable solver extrEMe [1] is used. The (regularized) inversion is based on an iterative gradient-type optimization (quasi-Newton method) and exploits adjoint sources approach for fast calculation of the gradient of the misfit. The inverse solver is able to deal with highly detailed and contrasting models, allows for working (separately or jointly) with any type of MT (single-site and/or inter-site) responses, and supports massive parallelization. Different parallelization strategies implemented in the code allow for optimal usage of available computational resources for a given problem set up. To parameterize an inverse domain a mask approach is implemented, which means that one can merge any subset of forward modelling cells in order to account for (usually) irregular distribution of observation sites. We report results of 3-D numerical experiments aimed at analysing the robustness, performance and scalability of the code. In particular, our computational experiments carried out at different platforms ranging from modern laptops to high-performance clusters demonstrate practically linear scalability of the code up to thousands of nodes. 1. Kruglyakov, M., A. Geraskin, A. Kuvshinov, 2016. Novel accurate and scalable 3-D MT forward solver based on a contracting integral equation method, Computers and Geosciences, in press.

DSPCP: A Data Scalable Approach for Identifying Relationships in Parallel Coordinates.

PubMed

Nguyen, Hoa; Rosen, Paul

2018-03-01

Parallel coordinates plots (PCPs) are a well-studied technique for exploring multi-attribute datasets. In many situations, users find them a flexible method to analyze and interact with data. Unfortunately, using PCPs becomes challenging as the number of data items grows large or multiple trends within the data mix in the visualization. The resulting overdraw can obscure important features. A number of modifications to PCPs have been proposed, including using color, opacity, smooth curves, frequency, density, and animation to mitigate this problem. However, these modified PCPs tend to have their own limitations in the kinds of relationships they emphasize. We propose a new data scalable design for representing and exploring data relationships in PCPs. The approach exploits the point/line duality property of PCPs and a local linear assumption of data to extract and represent relationship summarizations. This approach simultaneously shows relationships in the data and the consistency of those relationships. Our approach supports various visualization tasks, including mixed linear and nonlinear pattern identification, noise detection, and outlier detection, all in large data. We demonstrate these tasks on multiple synthetic and real-world datasets.

TriG: Next Generation Scalable Spaceborne GNSS Receiver

NASA Technical Reports Server (NTRS)

Tien, Jeffrey Y.; Okihiro, Brian Bachman; Esterhuizen, Stephan X.; Franklin, Garth W.; Meehan, Thomas K.; Munson, Timothy N.; Robison, David E.; Turbiner, Dmitry; Young, Lawrence E.

2012-01-01

TriG is the next generation NASA scalable space GNSS Science Receiver. It will track all GNSS and additional signals (i.e. GPS, GLONASS, Galileo, Compass and Doris). Scalable 3U architecture and fully software and firmware recofigurable, enabling optimization to meet specific mission requirements. TriG GNSS EM is currently undergoing testing and is expected to complete full performance testing later this year.

Validation of a Scalable Solar Sailcraft

NASA Technical Reports Server (NTRS)

Murphy, D. M.

2006-01-01

The NASA In-Space Propulsion (ISP) program sponsored intensive solar sail technology and systems design, development, and hardware demonstration activities over the past 3 years. Efforts to validate a scalable solar sail system by functional demonstration in relevant environments, together with test-analysis correlation activities on a scalable solar sail system have recently been successfully completed. A review of the program, with descriptions of the design, results of testing, and analytical model validations of component and assembly functional, strength, stiffness, shape, and dynamic behavior are discussed. The scaled performance of the validated system is projected to demonstrate the applicability to flight demonstration and important NASA road-map missions.

The Application of the Montage Image Mosaic Engine To The Visualization Of Astronomical Images

NASA Astrophysics Data System (ADS)

Berriman, G. Bruce; Good, J. C.

2017-05-01

The Montage Image Mosaic Engine was designed as a scalable toolkit, written in C for performance and portability across *nix platforms, that assembles FITS images into mosaics. This code is freely available and has been widely used in the astronomy and IT communities for research, product generation, and for developing next-generation cyber-infrastructure. Recently, it has begun finding applicability in the field of visualization. This development has come about because the toolkit design allows easy integration into scalable systems that process data for subsequent visualization in a browser or client. The toolkit it includes a visualization tool suitable for automation and for integration into Python: mViewer creates, with a single command, complex multi-color images overlaid with coordinate displays, labels, and observation footprints, and includes an adaptive image histogram equalization method that preserves the structure of a stretched image over its dynamic range. The Montage toolkit contains functionality originally developed to support the creation and management of mosaics, but which also offers value to visualization: a background rectification algorithm that reveals the faint structure in an image; and tools for creating cutout and downsampled versions of large images. Version 5 of Montage offers support for visualizing data written in HEALPix sky-tessellation scheme, and functionality for processing and organizing images to comply with the TOAST sky-tessellation scheme required for consumption by the World Wide Telescope (WWT). Four online tutorials allow readers to reproduce and extend all the visualizations presented in this paper.

A Principled Way of Assessing Visualization Literacy.

PubMed

Boy, Jeremy; Rensink, Ronald A; Bertini, Enrico; Fekete, Jean-Daniel

2014-12-01

We describe a method for assessing the visualization literacy (VL) of a user. Assessing how well people understand visualizations has great value for research (e. g., to avoid confounds), for design (e. g., to best determine the capabilities of an audience), for teaching (e. g., to assess the level of new students), and for recruiting (e. g., to assess the level of interviewees). This paper proposes a method for assessing VL based on Item Response Theory. It describes the design and evaluation of two VL tests for line graphs, and presents the extension of the method to bar charts and scatterplots. Finally, it discusses the reimplementation of these tests for fast, effective, and scalable web-based use.

Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis

DOE PAGES

Pavlopoulos, Georgios A.; Paez-Espino, David; Kyrpides, Nikos C.; ...

2017-07-18

Gene expression, signal transduction, protein/chemical interactions, biomedical literature cooccurrences, and other concepts are often captured in biological network representations where nodes represent a certain bioentity and edges the connections between them. While many tools to manipulate, visualize, and interactively explore such networks already exist, only few of them can scale up and follow today’s indisputable information growth. In this review, we shortly list a catalog of available network visualization tools and, from a user-experience point of view, we identify four candidate tools suitable for larger-scale network analysis, visualization, and exploration. Lastly, we comment on their strengths and their weaknesses andmore » empirically discuss their scalability, user friendliness, and postvisualization capabilities.« less

Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pavlopoulos, Georgios A.; Paez-Espino, David; Kyrpides, Nikos C.

Gene expression, signal transduction, protein/chemical interactions, biomedical literature cooccurrences, and other concepts are often captured in biological network representations where nodes represent a certain bioentity and edges the connections between them. While many tools to manipulate, visualize, and interactively explore such networks already exist, only few of them can scale up and follow today’s indisputable information growth. In this review, we shortly list a catalog of available network visualization tools and, from a user-experience point of view, we identify four candidate tools suitable for larger-scale network analysis, visualization, and exploration. Lastly, we comment on their strengths and their weaknesses andmore » empirically discuss their scalability, user friendliness, and postvisualization capabilities.« less

Scalable Robust Principal Component Analysis Using Grassmann Averages.

PubMed

Hauberg, Sren; Feragen, Aasa; Enficiaud, Raffi; Black, Michael J

2016-11-01

In large datasets, manual data verification is impossible, and we must expect the number of outliers to increase with data size. While principal component analysis (PCA) can reduce data size, and scalable solutions exist, it is well-known that outliers can arbitrarily corrupt the results. Unfortunately, state-of-the-art approaches for robust PCA are not scalable. We note that in a zero-mean dataset, each observation spans a one-dimensional subspace, giving a point on the Grassmann manifold. We show that the average subspace corresponds to the leading principal component for Gaussian data. We provide a simple algorithm for computing this Grassmann Average ( GA), and show that the subspace estimate is less sensitive to outliers than PCA for general distributions. Because averages can be efficiently computed, we immediately gain scalability. We exploit robust averaging to formulate the Robust Grassmann Average (RGA) as a form of robust PCA. The resulting Trimmed Grassmann Average ( TGA) is appropriate for computer vision because it is robust to pixel outliers. The algorithm has linear computational complexity and minimal memory requirements. We demonstrate TGA for background modeling, video restoration, and shadow removal. We show scalability by performing robust PCA on the entire Star Wars IV movie; a task beyond any current method. Source code is available online.

SFT: Scalable Fault Tolerance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petrini, Fabrizio; Nieplocha, Jarek; Tipparaju, Vinod

2006-04-15

In this paper we will present a new technology that we are currently developing within the SFT: Scalable Fault Tolerance FastOS project which seeks to implement fault tolerance at the operating system level. Major design goals include dynamic reallocation of resources to allow continuing execution in the presence of hardware failures, very high scalability, high efficiency (low overhead), and transparency—requiring no changes to user applications. Our technology is based on a global coordination mechanism, that enforces transparent recovery lines in the system, and TICK, a lightweight, incremental checkpointing software architecture implemented as a Linux kernel module. TICK is completely user-transparentmore » and does not require any changes to user code or system libraries; it is highly responsive: an interrupt, such as a timer interrupt, can trigger a checkpoint in as little as 2.5μs; and it supports incremental and full checkpoints with minimal overhead—less than 6% with full checkpointing to disk performed as frequently as once per minute.« less

Scalable hierarchical PDE sampler for generating spatially correlated random fields using nonmatching meshes: Scalable hierarchical PDE sampler using nonmatching meshes

DOE PAGES

Osborn, Sarah; Zulian, Patrick; Benson, Thomas; ...

2018-01-30

This work describes a domain embedding technique between two nonmatching meshes used for generating realizations of spatially correlated random fields with applications to large-scale sampling-based uncertainty quantification. The goal is to apply the multilevel Monte Carlo (MLMC) method for the quantification of output uncertainties of PDEs with random input coefficients on general and unstructured computational domains. We propose a highly scalable, hierarchical sampling method to generate realizations of a Gaussian random field on a given unstructured mesh by solving a reaction–diffusion PDE with a stochastic right-hand side. The stochastic PDE is discretized using the mixed finite element method on anmore » embedded domain with a structured mesh, and then, the solution is projected onto the unstructured mesh. This work describes implementation details on how to efficiently transfer data from the structured and unstructured meshes at coarse levels, assuming that this can be done efficiently on the finest level. We investigate the efficiency and parallel scalability of the technique for the scalable generation of Gaussian random fields in three dimensions. An application of the MLMC method is presented for quantifying uncertainties of subsurface flow problems. Here, we demonstrate the scalability of the sampling method with nonmatching mesh embedding, coupled with a parallel forward model problem solver, for large-scale 3D MLMC simulations with up to 1.9·109 unknowns.« less

Scalable hierarchical PDE sampler for generating spatially correlated random fields using nonmatching meshes: Scalable hierarchical PDE sampler using nonmatching meshes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Osborn, Sarah; Zulian, Patrick; Benson, Thomas

This work describes a domain embedding technique between two nonmatching meshes used for generating realizations of spatially correlated random fields with applications to large-scale sampling-based uncertainty quantification. The goal is to apply the multilevel Monte Carlo (MLMC) method for the quantification of output uncertainties of PDEs with random input coefficients on general and unstructured computational domains. We propose a highly scalable, hierarchical sampling method to generate realizations of a Gaussian random field on a given unstructured mesh by solving a reaction–diffusion PDE with a stochastic right-hand side. The stochastic PDE is discretized using the mixed finite element method on anmore » embedded domain with a structured mesh, and then, the solution is projected onto the unstructured mesh. This work describes implementation details on how to efficiently transfer data from the structured and unstructured meshes at coarse levels, assuming that this can be done efficiently on the finest level. We investigate the efficiency and parallel scalability of the technique for the scalable generation of Gaussian random fields in three dimensions. An application of the MLMC method is presented for quantifying uncertainties of subsurface flow problems. Here, we demonstrate the scalability of the sampling method with nonmatching mesh embedding, coupled with a parallel forward model problem solver, for large-scale 3D MLMC simulations with up to 1.9·109 unknowns.« less

Novel Visual Sensor Coverage and Deployment in Time Aware PTZ Wireless Visual Sensor Networks.

PubMed

Yap, Florence G H; Yen, Hong-Hsu

2016-12-30

In this paper, we consider the visual sensor deployment algorithm in Pan-Tilt-Zoom (PTZ) Wireless Visual Sensor Networks (WVSNs). With PTZ capability, a sensor's visual coverage can be extended to reduce the number of visual sensors that need to be deployed. The coverage zone of a visual sensor in PTZ WVSN is composed of two regions, a Direct Coverage Region (DCR) and a PTZ Coverage Region (PTZCR). In the PTZCR, a visual sensor needs a mechanical pan-tilt-zoom operation to cover an object. This mechanical operation can take seconds, so the sensor might not be able to adjust the camera in time to capture the visual data. In this paper, for the first time, we study this PTZ time-aware PTZ WVSN deployment problem. We formulate this PTZ time-aware PTZ WVSN deployment problem as an optimization problem where the objective is to minimize the total visual sensor deployment cost so that each area is either covered in the DCR or in the PTZCR while considering the PTZ time constraint. The proposed Time Aware Coverage Zone (TACZ) model successfully captures the PTZ visual sensor coverage in terms of camera focal range, angle span zone coverage and camera PTZ time. Then a novel heuristic, called Time Aware Deployment with PTZ camera (TADPTZ) algorithm, is proposed to solve the problem. From our computational experiments, we found out that TACZ model outperforms the existing M coverage model under all network scenarios. In addition, as compared to the optimal solutions, the TACZ model is scalable and adaptable to the different PTZ time requirements when deploying large PTZ WVSNs.

Novel Visual Sensor Coverage and Deployment in Time Aware PTZ Wireless Visual Sensor Networks

PubMed Central

Yap, Florence G. H.; Yen, Hong-Hsu

2016-01-01

In this paper, we consider the visual sensor deployment algorithm in Pan-Tilt-Zoom (PTZ) Wireless Visual Sensor Networks (WVSNs). With PTZ capability, a sensor’s visual coverage can be extended to reduce the number of visual sensors that need to be deployed. The coverage zone of a visual sensor in PTZ WVSN is composed of two regions, a Direct Coverage Region (DCR) and a PTZ Coverage Region (PTZCR). In the PTZCR, a visual sensor needs a mechanical pan-tilt-zoom operation to cover an object. This mechanical operation can take seconds, so the sensor might not be able to adjust the camera in time to capture the visual data. In this paper, for the first time, we study this PTZ time-aware PTZ WVSN deployment problem. We formulate this PTZ time-aware PTZ WVSN deployment problem as an optimization problem where the objective is to minimize the total visual sensor deployment cost so that each area is either covered in the DCR or in the PTZCR while considering the PTZ time constraint. The proposed Time Aware Coverage Zone (TACZ) model successfully captures the PTZ visual sensor coverage in terms of camera focal range, angle span zone coverage and camera PTZ time. Then a novel heuristic, called Time Aware Deployment with PTZ camera (TADPTZ) algorithm, is proposed to solve the problem. From our computational experiments, we found out that TACZ model outperforms the existing M coverage model under all network scenarios. In addition, as compared to the optimal solutions, the TACZ model is scalable and adaptable to the different PTZ time requirements when deploying large PTZ WVSNs. PMID:28042829

DISP: Optimizations towards Scalable MPI Startup

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fu, Huansong; Pophale, Swaroop S; Gorentla Venkata, Manjunath

2016-01-01

Despite the popularity of MPI for high performance computing, the startup of MPI programs faces a scalability challenge as both the execution time and memory consumption increase drastically at scale. We have examined this problem using the collective modules of Cheetah and Tuned in Open MPI as representative implementations. Previous improvements for collectives have focused on algorithmic advances and hardware off-load. In this paper, we examine the startup cost of the collective module within a communicator and explore various techniques to improve its efficiency and scalability. Accordingly, we have developed a new scalable startup scheme with three internal techniques, namelymore » Delayed Initialization, Module Sharing and Prediction-based Topology Setup (DISP). Our DISP scheme greatly benefits the collective initialization of the Cheetah module. At the same time, it helps boost the performance of non-collective initialization in the Tuned module. We evaluate the performance of our implementation on Titan supercomputer at ORNL with up to 4096 processes. The results show that our delayed initialization can speed up the startup of Tuned and Cheetah by an average of 32.0% and 29.2%, respectively, our module sharing can reduce the memory consumption of Tuned and Cheetah by up to 24.1% and 83.5%, respectively, and our prediction-based topology setup can speed up the startup of Cheetah by up to 80%.« less

Towards a Scalable, Biomimetic, Antibacterial Coating

NASA Astrophysics Data System (ADS)

Dickson, Mary Nora

Corneal afflictions are the second leading cause of blindness worldwide. When a corneal transplant is unavailable or contraindicated, an artificial cornea device is the only chance to save sight. Bacterial or fungal biofilm build up on artificial cornea devices can lead to serious complications including the need for systemic antibiotic treatment and even explantation. As a result, much emphasis has been placed on anti-adhesion chemical coatings and antibiotic leeching coatings. These methods are not long-lasting, and microorganisms can eventually circumvent these measures. Thus, I have developed a surface topographical antimicrobial coating. Various surface structures including rough surfaces, superhydrophobic surfaces, and the natural surfaces of insects' wings and sharks' skin are promising anti-biofilm candidates, however none meet the criteria necessary for implementation on the surface of an artificial cornea device. In this thesis I: 1) developed scalable fabrication protocols for a library of biomimetic nanostructure polymer surfaces 2) assessed the potential these for poly(methyl methacrylate) nanopillars to kill or prevent formation of biofilm by E. coli bacteria and species of Pseudomonas and Staphylococcus bacteria and improved upon a proposed mechanism for the rupture of Gram-negative bacterial cell walls 3) developed a scalable, commercially viable method for producing antibacterial nanopillars on a curved, PMMA artificial cornea device and 4) developed scalable fabrication protocols for implantation of antibacterial nanopatterned surfaces on the surfaces of thermoplastic polyurethane materials, commonly used in catheter tubings. This project constitutes a first step towards fabrication of the first entirely PMMA artificial cornea device. The major finding of this work is that by precisely controlling the topography of a polymer surface at the nano-scale, we can kill adherent bacteria and prevent biofilm formation of certain pathogenic bacteria

Wavelet-based scalable L-infinity-oriented compression.

PubMed

Alecu, Alin; Munteanu, Adrian; Cornelis, Jan P H; Schelkens, Peter

2006-09-01

Among the different classes of coding techniques proposed in literature, predictive schemes have proven their outstanding performance in near-lossless compression. However, these schemes are incapable of providing embedded L(infinity)-oriented compression, or, at most, provide a very limited number of potential L(infinity) bit-stream truncation points. We propose a new multidimensional wavelet-based L(infinity)-constrained scalable coding framework that generates a fully embedded L(infinity)-oriented bit stream and that retains the coding performance and all the scalability options of state-of-the-art L2-oriented wavelet codecs. Moreover, our codec instantiation of the proposed framework clearly outperforms JPEG2000 in L(infinity) coding sense.

A graphics to scalable vector graphics adaptation framework for progressive remote line rendering on mobile devices

NASA Astrophysics Data System (ADS)

Le, Minh Tuan; Nguyen, Congdu; Yoon, Dae-Il; Jung, Eun Ku; Kim, Hae-Kwang

2007-12-01

In this paper, we introduce a graphics to Scalable Vector Graphics (SVG) adaptation framework with a mechanism of vector graphics transmission to overcome the shortcoming of real-time representation and interaction experiences of 3D graphics application running on mobile devices. We therefore develop an interactive 3D visualization system based on the proposed framework for rapidly representing a 3D scene on mobile devices without having to download it from the server. Our system scenario is composed of a client viewer and a graphic to SVG adaptation server. The client viewer offers the user to access to the same 3D contents with different devices according to consumer interactions.

Scalability and Validation of Big Data Bioinformatics Software.

PubMed

Yang, Andrian; Troup, Michael; Ho, Joshua W K

2017-01-01

This review examines two important aspects that are central to modern big data bioinformatics analysis - software scalability and validity. We argue that not only are the issues of scalability and validation common to all big data bioinformatics analyses, they can be tackled by conceptually related methodological approaches, namely divide-and-conquer (scalability) and multiple executions (validation). Scalability is defined as the ability for a program to scale based on workload. It has always been an important consideration when developing bioinformatics algorithms and programs. Nonetheless the surge of volume and variety of biological and biomedical data has posed new challenges. We discuss how modern cloud computing and big data programming frameworks such as MapReduce and Spark are being used to effectively implement divide-and-conquer in a distributed computing environment. Validation of software is another important issue in big data bioinformatics that is often ignored. Software validation is the process of determining whether the program under test fulfils the task for which it was designed. Determining the correctness of the computational output of big data bioinformatics software is especially difficult due to the large input space and complex algorithms involved. We discuss how state-of-the-art software testing techniques that are based on the idea of multiple executions, such as metamorphic testing, can be used to implement an effective bioinformatics quality assurance strategy. We hope this review will raise awareness of these critical issues in bioinformatics.

Scalable Implementation of Finite Elements by NASA _ Implicit (ScIFEi)

NASA Technical Reports Server (NTRS)

Warner, James E.; Bomarito, Geoffrey F.; Heber, Gerd; Hochhalter, Jacob D.

2016-01-01

Scalable Implementation of Finite Elements by NASA (ScIFEN) is a parallel finite element analysis code written in C++. ScIFEN is designed to provide scalable solutions to computational mechanics problems. It supports a variety of finite element types, nonlinear material models, and boundary conditions. This report provides an overview of ScIFEi (\\Sci-Fi"), the implicit solid mechanics driver within ScIFEN. A description of ScIFEi's capabilities is provided, including an overview of the tools and features that accompany the software as well as a description of the input and output le formats. Results from several problems are included, demonstrating the efficiency and scalability of ScIFEi by comparing to finite element analysis using a commercial code.

Providing scalable system software for high-end simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greenberg, D.

1997-12-31

Detailed, full-system, complex physics simulations have been shown to be feasible on systems containing thousands of processors. In order to manage these computer systems it has been necessary to create scalable system services. In this talk Sandia`s research on scalable systems will be described. The key concepts of low overhead data movement through portals and of flexible services through multi-partition architectures will be illustrated in detail. The talk will conclude with a discussion of how these techniques can be applied outside of the standard monolithic MPP system.

Multi-Purpose, Application-Centric, Scalable I/O Proxy Application

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, M. C.

2015-06-15

MACSio is a Multi-purpose, Application-Centric, Scalable I/O proxy application. It is designed to support a number of goals with respect to parallel I/O performance testing and benchmarking including the ability to test and compare various I/O libraries and I/O paradigms, to predict scalable performance of real applications and to help identify where improvements in I/O performance can be made within the HPC I/O software stack.

Interactive Correlation Analysis and Visualization of Climate Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Kwan-Liu

The relationship between our ability to analyze and extract insights from visualization of climate model output and the capability of the available resources to make those visualizations has reached a crisis point. The large volume of data currently produced by climate models is overwhelming the current, decades-old visualization workflow. The traditional methods for visualizing climate output also have not kept pace with changes in the types of grids used, the number of variables involved, and the number of different simulations performed with a climate model or the feature-richness of high-resolution simulations. This project has developed new and faster methods formore » visualization in order to get the most knowledge out of the new generation of high-resolution climate models. While traditional climate images will continue to be useful, there is need for new approaches to visualization and analysis of climate data if we are to gain all the insights available in ultra-large data sets produced by high-resolution model output and ensemble integrations of climate models such as those produced for the Coupled Model Intercomparison Project. Towards that end, we have developed new visualization techniques for performing correlation analysis. We have also introduced highly scalable, parallel rendering methods for visualizing large-scale 3D data. This project was done jointly with climate scientists and visualization researchers at Argonne National Laboratory and NCAR.« less

A scalable architecture for extracting, aligning, linking, and visualizing multi-Int data

NASA Astrophysics Data System (ADS)

Knoblock, Craig A.; Szekely, Pedro

2015-05-01

An analyst today has a tremendous amount of data available, but each of the various data sources typically exists in their own silos, so an analyst has limited ability to see an integrated view of the data and has little or no access to contextual information that could help in understanding the data. We have developed the Domain-Insight Graph (DIG) system, an innovative architecture for extracting, aligning, linking, and visualizing massive amounts of domain-specific content from unstructured sources. Under the DARPA Memex program we have already successfully applied this architecture to multiple application domains, including the enormous international problem of human trafficking, where we extracted, aligned and linked data from 50 million online Web pages. DIG builds on our Karma data integration toolkit, which makes it easy to rapidly integrate structured data from a variety of sources, including databases, spreadsheets, XML, JSON, and Web services. The ability to integrate Web services allows Karma to pull in live data from the various social media sites, such as Twitter, Instagram, and OpenStreetMaps. DIG then indexes the integrated data and provides an easy to use interface for query, visualization, and analysis.

A Scalability Model for ECS's Data Server

NASA Technical Reports Server (NTRS)

Menasce, Daniel A.; Singhal, Mukesh

1998-01-01

This report presents in four chapters a model for the scalability analysis of the Data Server subsystem of the Earth Observing System Data and Information System (EOSDIS) Core System (ECS). The model analyzes if the planned architecture of the Data Server will support an increase in the workload with the possible upgrade and/or addition of processors, storage subsystems, and networks. The approaches in the report include a summary of the architecture of ECS's Data server as well as a high level description of the Ingest and Retrieval operations as they relate to ECS's Data Server. This description forms the basis for the development of the scalability model of the data server and the methodology used to solve it.

A Systems Approach to Scalable Transportation Network Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perumalla, Kalyan S

2006-01-01

Emerging needs in transportation network modeling and simulation are raising new challenges with respect to scal-ability of network size and vehicular traffic intensity, speed of simulation for simulation-based optimization, and fidel-ity of vehicular behavior for accurate capture of event phe-nomena. Parallel execution is warranted to sustain the re-quired detail, size and speed. However, few parallel simulators exist for such applications, partly due to the challenges underlying their development. Moreover, many simulators are based on time-stepped models, which can be computationally inefficient for the purposes of modeling evacuation traffic. Here an approach is presented to de-signing a simulator with memory andmore » speed efficiency as the goals from the outset, and, specifically, scalability via parallel execution. The design makes use of discrete event modeling techniques as well as parallel simulation meth-ods. Our simulator, called SCATTER, is being developed, incorporating such design considerations. Preliminary per-formance results are presented on benchmark road net-works, showing scalability to one million vehicles simu-lated on one processor.« less

Scalable Integrated Region-Based Image Retrieval Using IRM and Statistical Clustering.

ERIC Educational Resources Information Center

Wang, James Z.; Du, Yanping

Statistical clustering is critical in designing scalable image retrieval systems. This paper presents a scalable algorithm for indexing and retrieving images based on region segmentation. The method uses statistical clustering on region features and IRM (Integrated Region Matching), a measure developed to evaluate overall similarity between images…

Design and implementation of scalable tape archiver

NASA Technical Reports Server (NTRS)

Nemoto, Toshihiro; Kitsuregawa, Masaru; Takagi, Mikio

1996-01-01

In order to reduce costs, computer manufacturers try to use commodity parts as much as possible. Mainframes using proprietary processors are being replaced by high performance RISC microprocessor-based workstations, which are further being replaced by the commodity microprocessor used in personal computers. Highly reliable disks for mainframes are also being replaced by disk arrays, which are complexes of disk drives. In this paper we try to clarify the feasibility of a large scale tertiary storage system composed of 8-mm tape archivers utilizing robotics. In the near future, the 8-mm tape archiver will be widely used and become a commodity part, since recent rapid growth of multimedia applications requires much larger storage than disk drives can provide. We designed a scalable tape archiver which connects as many 8-mm tape archivers (element archivers) as possible. In the scalable archiver, robotics can exchange a cassette tape between two adjacent element archivers mechanically. Thus, we can build a large scalable archiver inexpensively. In addition, a sophisticated migration mechanism distributes frequently accessed tapes (hot tapes) evenly among all of the element archivers, which improves the throughput considerably. Even with the failures of some tape drives, the system dynamically redistributes hot tapes to the other element archivers which have live tape drives. Several kinds of specially tailored huge archivers are on the market, however, the 8-mm tape scalable archiver could replace them. To maintain high performance in spite of high access locality when a large number of archivers are attached to the scalable archiver, it is necessary to scatter frequently accessed cassettes among the element archivers and to use the tape drives efficiently. For this purpose, we introduce two cassette migration algorithms, foreground migration and background migration. Background migration transfers cassettes between element archivers to redistribute frequently accessed

Scalability study of solid xenon

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoo, J.; Cease, H.; Jaskierny, W. F.

2015-04-01

We report a demonstration of the scalability of optically transparent xenon in the solid phase for use as a particle detector above a kilogram scale. We employed a cryostat cooled by liquid nitrogen combined with a xenon purification and chiller system. A modified {\\it Bridgeman's technique} reproduces a large scale optically transparent solid xenon.

Visualization tool for three-dimensional plasma velocity distributions (ISEE_3D) as a plug-in for SPEDAS

NASA Astrophysics Data System (ADS)

Keika, Kunihiro; Miyoshi, Yoshizumi; Machida, Shinobu; Ieda, Akimasa; Seki, Kanako; Hori, Tomoaki; Miyashita, Yukinaga; Shoji, Masafumi; Shinohara, Iku; Angelopoulos, Vassilis; Lewis, Jim W.; Flores, Aaron

2017-12-01

This paper introduces ISEE_3D, an interactive visualization tool for three-dimensional plasma velocity distribution functions, developed by the Institute for Space-Earth Environmental Research, Nagoya University, Japan. The tool provides a variety of methods to visualize the distribution function of space plasma: scatter, volume, and isosurface modes. The tool also has a wide range of functions, such as displaying magnetic field vectors and two-dimensional slices of distributions to facilitate extensive analysis. The coordinate transformation to the magnetic field coordinates is also implemented in the tool. The source codes of the tool are written as scripts of a widely used data analysis software language, Interactive Data Language, which has been widespread in the field of space physics and solar physics. The current version of the tool can be used for data files of the plasma distribution function from the Geotail satellite mission, which are publicly accessible through the Data Archives and Transmission System of the Institute of Space and Astronautical Science (ISAS)/Japan Aerospace Exploration Agency (JAXA). The tool is also available in the Space Physics Environment Data Analysis Software to visualize plasma data from the Magnetospheric Multiscale and the Time History of Events and Macroscale Interactions during Substorms missions. The tool is planned to be applied to data from other missions, such as Arase (ERG) and Van Allen Probes after replacing or adding data loading plug-ins. This visualization tool helps scientists understand the dynamics of space plasma better, particularly in the regions where the magnetohydrodynamic approximation is not valid, for example, the Earth's inner magnetosphere, magnetopause, bow shock, and plasma sheet.

: A Scalable and Transparent System for Simulating MPI Programs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perumalla, Kalyan S

2010-01-01

is a scalable, transparent system for experimenting with the execution of parallel programs on simulated computing platforms. The level of simulated detail can be varied for application behavior as well as for machine characteristics. Unique features of are repeatability of execution, scalability to millions of simulated (virtual) MPI ranks, scalability to hundreds of thousands of host (real) MPI ranks, portability of the system to a variety of host supercomputing platforms, and the ability to experiment with scientific applications whose source-code is available. The set of source-code interfaces supported by is being expanded to support a wider set of applications, andmore » MPI-based scientific computing benchmarks are being ported. In proof-of-concept experiments, has been successfully exercised to spawn and sustain very large-scale executions of an MPI test program given in source code form. Low slowdowns are observed, due to its use of purely discrete event style of execution, and due to the scalability and efficiency of the underlying parallel discrete event simulation engine, sik. In the largest runs, has been executed on up to 216,000 cores of a Cray XT5 supercomputer, successfully simulating over 27 million virtual MPI ranks, each virtual rank containing its own thread context, and all ranks fully synchronized by virtual time.« less

Evaluation of 3D printed anatomically scalable transfemoral prosthetic knee.

PubMed

Ramakrishnan, Tyagi; Schlafly, Millicent; Reed, Kyle B

2017-07-01

This case study compares a transfemoral amputee's gait while using the existing Ossur Total Knee 2000 and our novel 3D printed anatomically scalable transfemoral prosthetic knee. The anatomically scalable transfemoral prosthetic knee is 3D printed out of a carbon-fiber and nylon composite that has a gear-mesh coupling with a hard-stop weight-actuated locking mechanism aided by a cross-linked four-bar spring mechanism. This design can be scaled using anatomical dimensions of a human femur and tibia to have a unique fit for each user. The transfemoral amputee who was tested is high functioning and walked on the Computer Assisted Rehabilitation Environment (CAREN) at a self-selected pace. The motion capture and force data that was collected showed that there were distinct differences in the gait dynamics. The data was used to perform the Combined Gait Asymmetry Metric (CGAM), where the scores revealed that the overall asymmetry of the gait on the Ossur Total Knee was more asymmetric than the anatomically scalable transfemoral prosthetic knee. The anatomically scalable transfemoral prosthetic knee had higher peak knee flexion that caused a large step time asymmetry. This made walking on the anatomically scalable transfemoral prosthetic knee more strenuous due to the compensatory movements in adapting to the different dynamics. This can be overcome by tuning the cross-linked spring mechanism to emulate the dynamics of the subject better. The subject stated that the knee would be good for daily use and has the potential to be adapted as a running knee.

Discretized Streams: A Fault-Tolerant Model for Scalable Stream Processing

DTIC Science & Technology

2012-12-14

Discretized Streams: A Fault-Tolerant Model for Scalable Stream Processing Matei Zaharia Tathagata Das Haoyuan Li Timothy Hunter Scott Shenker Ion...SUBTITLE Discretized Streams: A Fault-Tolerant Model for Scalable Stream Processing 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER...time. However, current programming models for distributed stream processing are relatively low-level often leaving the user to worry about consistency of

Energy-absorption capability and scalability of square cross section composite tube specimens

NASA Technical Reports Server (NTRS)

Farley, Gary L.

1987-01-01

Static crushing tests were conducted on graphite/epoxy and Kevlar/epoxy square cross section tubes to study the influence of specimen geometry on the energy-absorption capability and scalability of composite materials. The tube inside width-to-wall thickness (W/t) ratio was determined to significantly affect the energy-absorption capability of composite materials. As W/t ratio decreases, the energy-absorption capability increases nonlinearly. The energy-absorption capability of Kevlar epoxy tubes was found to be geometrically scalable, but the energy-absorption capability of graphite/epoxy tubes was not geometrically scalable.

Combining textual and visual information for image retrieval in the medical domain.

PubMed

Gkoufas, Yiannis; Morou, Anna; Kalamboukis, Theodore

2011-01-01

In this article we have assembled the experience obtained from our participation in the imageCLEF evaluation task over the past two years. Exploitation on the use of linear combinations for image retrieval has been attempted by combining visual and textual sources of images. From our experiments we conclude that a mixed retrieval technique that applies both textual and visual retrieval in an interchangeably repeated manner improves the performance while overcoming the scalability limitations of visual retrieval. In particular, the mean average precision (MAP) has increased from 0.01 to 0.15 and 0.087 for 2009 and 2010 data, respectively, when content-based image retrieval (CBIR) is performed on the top 1000 results from textual retrieval based on natural language processing (NLP).

UpSet: Visualization of Intersecting Sets

PubMed Central

Lex, Alexander; Gehlenborg, Nils; Strobelt, Hendrik; Vuillemot, Romain; Pfister, Hanspeter

2016-01-01

Understanding relationships between sets is an important analysis task that has received widespread attention in the visualization community. The major challenge in this context is the combinatorial explosion of the number of set intersections if the number of sets exceeds a trivial threshold. In this paper we introduce UpSet, a novel visualization technique for the quantitative analysis of sets, their intersections, and aggregates of intersections. UpSet is focused on creating task-driven aggregates, communicating the size and properties of aggregates and intersections, and a duality between the visualization of the elements in a dataset and their set membership. UpSet visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes. Sorting according to various measures enables a task-driven analysis of relevant intersections and aggregates. The elements represented in the sets and their associated attributes are visualized in a separate view. Queries based on containment in specific intersections, aggregates or driven by attribute filters are propagated between both views. We also introduce several advanced visual encodings and interaction methods to overcome the problems of varying scales and to address scalability. UpSet is web-based and open source. We demonstrate its general utility in multiple use cases from various domains. PMID:26356912

AstroVis: Visualizing astronomical data cubes

NASA Astrophysics Data System (ADS)

Finniss, Stephen; Tyler, Robin; Questiaux, Jacques

2016-08-01

AstroVis enables rapid visualization of large data files on platforms supporting the OpenGL rendering library. Radio astronomical observations are typically three dimensional and stored as data cubes. AstroVis implements a scalable approach to accessing these files using three components: a File Access Component (FAC) that reduces the impact of reading time, which speeds up access to the data; the Image Processing Component (IPC), which breaks up the data cube into smaller pieces that can be processed locally and gives a representation of the whole file; and Data Visualization, which implements an approach of Overview + Detail to reduces the dimensions of the data being worked with and the amount of memory required to store it. The result is a 3D display paired with a 2D detail display that contains a small subsection of the original file in full resolution without reducing the data in any way.

CASTOR: Widely Distributed Scalable Infospaces

DTIC Science & Technology

2008-11-01

1  i Progress against Planned Objectives Enable nimble apps that react fast as...generation of scalable, reliable, ultra- fast event notification in Linux data centers. • Maelstrom, a spin-off from Ricochet, offers a powerful new option...out potential enhancements to WS-EVENTING and WS-NOTIFICATION based on our work. Potential impact for the warflighter. QSM achieves extremely fast

Cloud Based Resource for Data Hosting, Visualization and Analysis Using UCSC Cancer Genomics Browser | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

The Cancer Analysis Virtual Machine (CAVM) project will leverage cloud technology, the UCSC Cancer Genomics Browser, and the Galaxy analysis workflow system to provide investigators with a flexible, scalable platform for hosting, visualizing and analyzing their own genomic data.

Scalable Motion Estimation Processor Core for Multimedia System-on-Chip Applications

NASA Astrophysics Data System (ADS)

Lai, Yeong-Kang; Hsieh, Tian-En; Chen, Lien-Fei

2007-04-01

In this paper, we describe a high-throughput and scalable motion estimation processor architecture for multimedia system-on-chip applications. The number of processing elements (PEs) is scalable according to the variable algorithm parameters and the performance required for different applications. Using the PE rings efficiently and an intelligent memory-interleaving organization, the efficiency of the architecture can be increased. Moreover, using efficient on-chip memories and a data management technique can effectively decrease the power consumption and memory bandwidth. Techniques for reducing the number of interconnections and external memory accesses are also presented. Our results demonstrate that the proposed scalable PE-ringed architecture is a flexible and high-performance processor core in multimedia system-on-chip applications.

Mobile Virtual Reality : A Solution for Big Data Visualization

NASA Astrophysics Data System (ADS)

Marshall, E.; Seichter, N. D.; D'sa, A.; Werner, L. A.; Yuen, D. A.

2015-12-01

Pursuits in geological sciences and other branches of quantitative sciences often require data visualization frameworks that are in continual need of improvement and new ideas. Virtual reality is a medium of visualization that has large audiences originally designed for gaming purposes; Virtual reality can be captured in Cave-like environment but they are unwieldy and expensive to maintain. Recent efforts by major companies such as Facebook have focussed more on a large market , The Oculus is the first of such kind of mobile devices The operating system Unity makes it possible for us to convert the data files into a mesh of isosurfaces and be rendered into 3D. A user is immersed inside of the virtual reality and is able to move within and around the data using arrow keys and other steering devices, similar to those employed in XBox.. With introductions of products like the Oculus Rift and Holo Lens combined with ever increasing mobile computing strength, mobile virtual reality data visualization can be implemented for better analysis of 3D geological and mineralogical data sets. As more new products like the Surface Pro 4 and other high power yet very mobile computers are introduced to the market, the RAM and graphics card capacity necessary to run these models is more available, opening doors to this new reality. The computing requirements needed to run these models are a mere 8 GB of RAM and 2 GHz of CPU speed, which many mobile computers are starting to exceed. Using Unity 3D software to create a virtual environment containing a visual representation of the data, any data set converted into FBX or OBJ format which can be traversed by wearing the Oculus Rift device. This new method for analysis in conjunction with 3D scanning has potential applications in many fields, including the analysis of precious stones or jewelry. Using hologram technology to capture in high-resolution the 3D shape, color, and imperfections of minerals and stones, detailed review and

JBrowse: a dynamic web platform for genome visualization and analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buels, Robert; Yao, Eric; Diesh, Colin M.

JBrowse is a fast and full-featured genome browser built with JavaScript and HTML5. It is easily embedded into websites or apps but can also be served as a standalone web page. Overall improvements to speed and scalability are accompanied by specific enhancements that support complex interactive queries on large track sets. Analysis functions can readily be added using the plugin framework; most visual aspects of tracks can also be customized, along with clicks, mouseovers, menus, and popup boxes. JBrowse can also be used to browse local annotation files offline and to generate high-resolution figures for publication. JBrowse is a maturemore » web application suitable for genome visualization and analysis.« less

JBrowse: a dynamic web platform for genome visualization and analysis.

PubMed

Buels, Robert; Yao, Eric; Diesh, Colin M; Hayes, Richard D; Munoz-Torres, Monica; Helt, Gregg; Goodstein, David M; Elsik, Christine G; Lewis, Suzanna E; Stein, Lincoln; Holmes, Ian H

2016-04-12

JBrowse is a fast and full-featured genome browser built with JavaScript and HTML5. It is easily embedded into websites or apps but can also be served as a standalone web page. Overall improvements to speed and scalability are accompanied by specific enhancements that support complex interactive queries on large track sets. Analysis functions can readily be added using the plugin framework; most visual aspects of tracks can also be customized, along with clicks, mouseovers, menus, and popup boxes. JBrowse can also be used to browse local annotation files offline and to generate high-resolution figures for publication. JBrowse is a mature web application suitable for genome visualization and analysis.

Scalable fabrication of perovskite solar cells

DOE PAGES

Li, Zhen; Klein, Talysa R.; Kim, Dong Hoe; ...

2018-03-27

Perovskite materials use earth-abundant elements, have low formation energies for deposition and are compatible with roll-to-roll and other high-volume manufacturing techniques. These features make perovskite solar cells (PSCs) suitable for terawatt-scale energy production with low production costs and low capital expenditure. Demonstrations of performance comparable to that of other thin-film photovoltaics (PVs) and improvements in laboratory-scale cell stability have recently made scale up of this PV technology an intense area of research focus. Here, we review recent progress and challenges in scaling up PSCs and related efforts to enable the terawatt-scale manufacturing and deployment of this PV technology. We discussmore » common device and module architectures, scalable deposition methods and progress in the scalable deposition of perovskite and charge-transport layers. We also provide an overview of device and module stability, module-level characterization techniques and techno-economic analyses of perovskite PV modules.« less

Scalable and balanced dynamic hybrid data assimilation

NASA Astrophysics Data System (ADS)

Kauranne, Tuomo; Amour, Idrissa; Gunia, Martin; Kallio, Kari; Lepistö, Ahti; Koponen, Sampsa

2017-04-01

Scalability of complex weather forecasting suites is dependent on the technical tools available for implementing highly parallel computational kernels, but to an equally large extent also on the dependence patterns between various components of the suite, such as observation processing, data assimilation and the forecast model. Scalability is a particular challenge for 4D variational assimilation methods that necessarily couple the forecast model into the assimilation process and subject this combination to an inherently serial quasi-Newton minimization process. Ensemble based assimilation methods are naturally more parallel, but large models force ensemble sizes to be small and that results in poor assimilation accuracy, somewhat akin to shooting with a shotgun in a million-dimensional space. The Variational Ensemble Kalman Filter (VEnKF) is an ensemble method that can attain the accuracy of 4D variational data assimilation with a small ensemble size. It achieves this by processing a Gaussian approximation of the current error covariance distribution, instead of a set of ensemble members, analogously to the Extended Kalman Filter EKF. Ensemble members are re-sampled every time a new set of observations is processed from a new approximation of that Gaussian distribution which makes VEnKF a dynamic assimilation method. After this a smoothing step is applied that turns VEnKF into a dynamic Variational Ensemble Kalman Smoother VEnKS. In this smoothing step, the same process is iterated with frequent re-sampling of the ensemble but now using past iterations as surrogate observations until the end result is a smooth and balanced model trajectory. In principle, VEnKF could suffer from similar scalability issues as 4D-Var. However, this can be avoided by isolating the forecast model completely from the minimization process by implementing the latter as a wrapper code whose only link to the model is calling for many parallel and totally independent model runs, all of them

Feature and Region Selection for Visual Learning.

PubMed

Zhao, Ji; Wang, Liantao; Cabral, Ricardo; De la Torre, Fernando

2016-03-01

Visual learning problems, such as object classification and action recognition, are typically approached using extensions of the popular bag-of-words (BoWs) model. Despite its great success, it is unclear what visual features the BoW model is learning. Which regions in the image or video are used to discriminate among classes? Which are the most discriminative visual words? Answering these questions is fundamental for understanding existing BoW models and inspiring better models for visual recognition. To answer these questions, this paper presents a method for feature selection and region selection in the visual BoW model. This allows for an intermediate visualization of the features and regions that are important for visual learning. The main idea is to assign latent weights to the features or regions, and jointly optimize these latent variables with the parameters of a classifier (e.g., support vector machine). There are four main benefits of our approach: 1) our approach accommodates non-linear additive kernels, such as the popular χ(2) and intersection kernel; 2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; 3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; and 4) we point out strong connections with multiple kernel learning and multiple instance learning approaches. Experimental results in the PASCAL VOC 2007, MSR Action Dataset II and YouTube illustrate the benefits of our approach.

Scalable Node Monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Drotar, Alexander P.; Quinn, Erin E.; Sutherland, Landon D.

2012-07-30

Project description is: (1) Build a high performance computer; and (2) Create a tool to monitor node applications in Component Based Tool Framework (CBTF) using code from Lightweight Data Metric Service (LDMS). The importance of this project is that: (1) there is a need a scalable, parallel tool to monitor nodes on clusters; and (2) New LDMS plugins need to be able to be easily added to tool. CBTF stands for Component Based Tool Framework. It's scalable and adjusts to different topologies automatically. It uses MRNet (Multicast/Reduction Network) mechanism for information transport. CBTF is flexible and general enough to bemore » used for any tool that needs to do a task on many nodes. Its components are reusable and 'EASILY' added to a new tool. There are three levels of CBTF: (1) frontend node - interacts with users; (2) filter nodes - filters or concatenates information from backend nodes; and (3) backend nodes - where the actual work of the tool is done. LDMS stands for lightweight data metric servies. It's a tool used for monitoring nodes. Ltool is the name of the tool we derived from LDMS. It's dynamically linked and includes the following components: Vmstat, Meminfo, Procinterrupts and more. It works by: Ltool command is run on the frontend node; Ltool collects information from the backend nodes; backend nodes send information to the filter nodes; and filter nodes concatenate information and send to a database on the front end node. Ltool is a useful tool when it comes to monitoring nodes on a cluster because the overhead involved with running the tool is not particularly high and it will automatically scale to any size cluster.« less

Joint source-channel coding for motion-compensated DCT-based SNR scalable video.

PubMed

Kondi, Lisimachos P; Ishtiaq, Faisal; Katsaggelos, Aggelos K

2002-01-01

In this paper, we develop an approach toward joint source-channel coding for motion-compensated DCT-based scalable video coding and transmission. A framework for the optimal selection of the source and channel coding rates over all scalable layers is presented such that the overall distortion is minimized. The algorithm utilizes universal rate distortion characteristics which are obtained experimentally and show the sensitivity of the source encoder and decoder to channel errors. The proposed algorithm allocates the available bit rate between scalable layers and, within each layer, between source and channel coding. We present the results of this rate allocation algorithm for video transmission over a wireless channel using the H.263 Version 2 signal-to-noise ratio (SNR) scalable codec for source coding and rate-compatible punctured convolutional (RCPC) codes for channel coding. We discuss the performance of the algorithm with respect to the channel conditions, coding methodologies, layer rates, and number of layers.

Performances of the PIPER scalable child human body model in accident reconstruction

PubMed Central

Giordano, Chiara; Kleiven, Svein

2017-01-01

Human body models (HBMs) have the potential to provide significant insights into the pediatric response to impact. This study describes a scalable/posable approach to perform child accident reconstructions using the Position and Personalize Advanced Human Body Models for Injury Prediction (PIPER) scalable child HBM of different ages and in different positions obtained by the PIPER tool. Overall, the PIPER scalable child HBM managed reasonably well to predict the injury severity and location of the children involved in real-life crash scenarios documented in the medical records. The developed methodology and workflow is essential for future work to determine child injury tolerances based on the full Child Advanced Safety Project for European Roads (CASPER) accident reconstruction database. With the workflow presented in this study, the open-source PIPER scalable HBM combined with the PIPER tool is also foreseen to have implications for improved safety designs for a better protection of children in traffic accidents. PMID:29135997

Data Fusion and Visualization with the OpenEarth Framework (OEF)

NASA Astrophysics Data System (ADS)

Nadeau, D. R.; Baru, C.; Fouch, M. J.; Crosby, C. J.

2010-12-01

sliced by multiple oriented cutting planes and isosurfaced to create 3D skins that trace feature boundaries within the data. Topography may be overlaid with satellite imagery along with data such as gravity and magnetics measurements. Multiple data sets may be visualized simultaneously using overlapping layers and a common 3D+time coordinate space. Data management within the OEF handles and hides the quirks of differing file formats, web protocols, storage structures, coordinate spaces, and metadata representations. Derived data are computed automatically to support interaction and visualization while the original data is left unchanged in its original form. Data is cached for better memory and network efficiency, and all visualization is accelerated by 3D graphics hardware found on today’s computers. The OpenEarth Framework project is currently prototyping the software for use in the visualization, and integration of continental scale geophysical data being produced by EarthScope-related research in the Western US. The OEF is providing researchers with new ways to display and interrogate their data and is anticipated to be a valuable tool for future EarthScope-related research.

Web-based visual analysis for high-throughput genomics

PubMed Central

2013-01-01

Background Visualization plays an essential role in genomics research by making it possible to observe correlations and trends in large datasets as well as communicate findings to others. Visual analysis, which combines visualization with analysis tools to enable seamless use of both approaches for scientific investigation, offers a powerful method for performing complex genomic analyses. However, there are numerous challenges that arise when creating rich, interactive Web-based visualizations/visual analysis applications for high-throughput genomics. These challenges include managing data flow from Web server to Web browser, integrating analysis tools and visualizations, and sharing visualizations with colleagues. Results We have created a platform simplifies the creation of Web-based visualization/visual analysis applications for high-throughput genomics. This platform provides components that make it simple to efficiently query very large datasets, draw common representations of genomic data, integrate with analysis tools, and share or publish fully interactive visualizations. Using this platform, we have created a Circos-style genome-wide viewer, a generic scatter plot for correlation analysis, an interactive phylogenetic tree, a scalable genome browser for next-generation sequencing data, and an application for systematically exploring tool parameter spaces to find good parameter values. All visualizations are interactive and fully customizable. The platform is integrated with the Galaxy (http://galaxyproject.org) genomics workbench, making it easy to integrate new visual applications into Galaxy. Conclusions Visualization and visual analysis play an important role in high-throughput genomics experiments, and approaches are needed to make it easier to create applications for these activities. Our framework provides a foundation for creating Web-based visualizations and integrating them into Galaxy. Finally, the visualizations we have created using the

Superlinearly scalable noise robustness of redundant coupled dynamical systems.

PubMed

Kohar, Vivek; Kia, Behnam; Lindner, John F; Ditto, William L

2016-03-01

We illustrate through theory and numerical simulations that redundant coupled dynamical systems can be extremely robust against local noise in comparison to uncoupled dynamical systems evolving in the same noisy environment. Previous studies have shown that the noise robustness of redundant coupled dynamical systems is linearly scalable and deviations due to noise can be minimized by increasing the number of coupled units. Here, we demonstrate that the noise robustness can actually be scaled superlinearly if some conditions are met and very high noise robustness can be realized with very few coupled units. We discuss these conditions and show that this superlinear scalability depends on the nonlinearity of the individual dynamical units. The phenomenon is demonstrated in discrete as well as continuous dynamical systems. This superlinear scalability not only provides us an opportunity to exploit the nonlinearity of physical systems without being bogged down by noise but may also help us in understanding the functional role of coupled redundancy found in many biological systems. Moreover, engineers can exploit superlinear noise suppression by starting a coupled system near (not necessarily at) the appropriate initial condition.

Diskless supercomputers: Scalable, reliable I/O for the Tera-Op technology base

NASA Technical Reports Server (NTRS)

Katz, Randy H.; Ousterhout, John K.; Patterson, David A.

1993-01-01

Computing is seeing an unprecedented improvement in performance; over the last five years there has been an order-of-magnitude improvement in the speeds of workstation CPU's. At least another order of magnitude seems likely in the next five years, to machines with 500 MIPS or more. The goal of the ARPA Teraop program is to realize even larger, more powerful machines, executing as many as a trillion operations per second. Unfortunately, we have seen no comparable breakthroughs in I/O performance; the speeds of I/O devices and the hardware and software architectures for managing them have not changed substantially in many years. We have completed a program of research to demonstrate hardware and software I/O architectures capable of supporting the kinds of internetworked 'visualization' workstations and supercomputers that will appear in the mid 1990s. The project had three overall goals: high performance, high reliability, and scalable, multipurpose system.

Progressive Dictionary Learning with Hierarchical Predictive Structure for Scalable Video Coding.

PubMed

Dai, Wenrui; Shen, Yangmei; Xiong, Hongkai; Jiang, Xiaoqian; Zou, Junni; Taubman, David

2017-04-12

Dictionary learning has emerged as a promising alternative to the conventional hybrid coding framework. However, the rigid structure of sequential training and prediction degrades its performance in scalable video coding. This paper proposes a progressive dictionary learning framework with hierarchical predictive structure for scalable video coding, especially in low bitrate region. For pyramidal layers, sparse representation based on spatio-temporal dictionary is adopted to improve the coding efficiency of enhancement layers (ELs) with a guarantee of reconstruction performance. The overcomplete dictionary is trained to adaptively capture local structures along motion trajectories as well as exploit the correlations between neighboring layers of resolutions. Furthermore, progressive dictionary learning is developed to enable the scalability in temporal domain and restrict the error propagation in a close-loop predictor. Under the hierarchical predictive structure, online learning is leveraged to guarantee the training and prediction performance with an improved convergence rate. To accommodate with the stateof- the-art scalable extension of H.264/AVC and latest HEVC, standardized codec cores are utilized to encode the base and enhancement layers. Experimental results show that the proposed method outperforms the latest SHVC and HEVC simulcast over extensive test sequences with various resolutions.

Scalable free energy calculation of proteins via multiscale essential sampling

NASA Astrophysics Data System (ADS)

Moritsugu, Kei; Terada, Tohru; Kidera, Akinori

2010-12-01

A multiscale simulation method, "multiscale essential sampling (MSES)," is proposed for calculating free energy surface of proteins in a sizable dimensional space with good scalability. In MSES, the configurational sampling of a full-dimensional model is enhanced by coupling with the accelerated dynamics of the essential degrees of freedom. Applying the Hamiltonian exchange method to MSES can remove the biasing potential from the coupling term, deriving the free energy surface of the essential degrees of freedom. The form of the coupling term ensures good scalability in the Hamiltonian exchange. As a test application, the free energy surface of the folding process of a miniprotein, chignolin, was calculated in the continuum solvent model. Results agreed with the free energy surface derived from the multicanonical simulation. Significantly improved scalability with the MSES method was clearly shown in the free energy calculation of chignolin in explicit solvent, which was achieved without increasing the number of replicas in the Hamiltonian exchange.

JBrowse: A dynamic web platform for genome visualization and analysis

DOE PAGES

Buels, Robert; Yao, Eric; Diesh, Colin M.; ...

2016-04-12

Background: JBrowse is a fast and full-featured genome browser built with JavaScript and HTML5. It is easily embedded into websites or apps but can also be served as a standalone web page. Results: Overall improvements to speed and scalability are accompanied by specific enhancements that support complex interactive queries on large track sets. Analysis functions can readily be added using the plugin framework; most visual aspects of tracks can also be customized, along with clicks, mouseovers, menus, and popup boxes. JBrowse can also be used to browse local annotation files offline and to generate high-resolution figures for publication. Conclusions: JBrowsemore » is a mature web application suitable for genome visualization and analysis.« less

Algorithmic psychometrics and the scalable subject.

PubMed

Stark, Luke

2018-04-01

Recent public controversies, ranging from the 2014 Facebook 'emotional contagion' study to psychographic data profiling by Cambridge Analytica in the 2016 American presidential election, Brexit referendum and elsewhere, signal watershed moments in which the intersecting trajectories of psychology and computer science have become matters of public concern. The entangled history of these two fields grounds the application of applied psychological techniques to digital technologies, and an investment in applying calculability to human subjectivity. Today, a quantifiable psychological subject position has been translated, via 'big data' sets and algorithmic analysis, into a model subject amenable to classification through digital media platforms. I term this position the 'scalable subject', arguing it has been shaped and made legible by algorithmic psychometrics - a broad set of affordances in digital platforms shaped by psychology and the behavioral sciences. In describing the contours of this 'scalable subject', this paper highlights the urgent need for renewed attention from STS scholars on the psy sciences, and on a computational politics attentive to psychology, emotional expression, and sociality via digital media.

Scalable software-defined optical networking with high-performance routing and wavelength assignment algorithms.

PubMed

Lee, Chankyun; Cao, Xiaoyuan; Yoshikane, Noboru; Tsuritani, Takehiro; Rhee, June-Koo Kevin

2015-10-19

The feasibility of software-defined optical networking (SDON) for a practical application critically depends on scalability of centralized control performance. The paper, highly scalable routing and wavelength assignment (RWA) algorithms are investigated on an OpenFlow-based SDON testbed for proof-of-concept demonstration. Efficient RWA algorithms are proposed to achieve high performance in achieving network capacity with reduced computation cost, which is a significant attribute in a scalable centralized-control SDON. The proposed heuristic RWA algorithms differ in the orders of request processes and in the procedures of routing table updates. Combined in a shortest-path-based routing algorithm, a hottest-request-first processing policy that considers demand intensity and end-to-end distance information offers both the highest throughput of networks and acceptable computation scalability. We further investigate trade-off relationship between network throughput and computation complexity in routing table update procedure by a simulation study.

Scalable, full-colour and controllable chromotropic plasmonic printing.

PubMed

Xue, Jiancai; Zhou, Zhang-Kai; Wei, Zhiqiang; Su, Rongbin; Lai, Juan; Li, Juntao; Li, Chao; Zhang, Tengwei; Wang, Xue-Hua

2015-11-16

Plasmonic colour printing has drawn wide attention as a promising candidate for the next-generation colour-printing technology. However, an efficient approach to realize full colour and scalable fabrication is still lacking, which prevents plasmonic colour printing from practical applications. Here we present a scalable and full-colour plasmonic printing approach by combining conjugate twin-phase modulation with a plasmonic broadband absorber. More importantly, our approach also demonstrates controllable chromotropic capability, that is, the ability of reversible colour transformations. This chromotropic capability affords enormous potentials in building functionalized prints for anticounterfeiting, special label, and high-density data encryption storage. With such excellent performances in functional colour applications, this colour-printing approach could pave the way for plasmonic colour printing in real-world commercial utilization.

Scalable, full-colour and controllable chromotropic plasmonic printing

PubMed Central

Xue, Jiancai; Zhou, Zhang-Kai; Wei, Zhiqiang; Su, Rongbin; Lai, Juan; Li, Juntao; Li, Chao; Zhang, Tengwei; Wang, Xue-Hua

2015-01-01

Plasmonic colour printing has drawn wide attention as a promising candidate for the next-generation colour-printing technology. However, an efficient approach to realize full colour and scalable fabrication is still lacking, which prevents plasmonic colour printing from practical applications. Here we present a scalable and full-colour plasmonic printing approach by combining conjugate twin-phase modulation with a plasmonic broadband absorber. More importantly, our approach also demonstrates controllable chromotropic capability, that is, the ability of reversible colour transformations. This chromotropic capability affords enormous potentials in building functionalized prints for anticounterfeiting, special label, and high-density data encryption storage. With such excellent performances in functional colour applications, this colour-printing approach could pave the way for plasmonic colour printing in real-world commercial utilization. PMID:26567803

Scalable Domain Decomposed Monte Carlo Particle Transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Brien, Matthew Joseph

2013-12-05

In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation.

Interactive Volume Exploration of Petascale Microscopy Data Streams Using a Visualization-Driven Virtual Memory Approach.

PubMed

Hadwiger, M; Beyer, J; Jeong, Won-Ki; Pfister, H

2012-12-01

This paper presents the first volume visualization system that scales to petascale volumes imaged as a continuous stream of high-resolution electron microscopy images. Our architecture scales to dense, anisotropic petascale volumes because it: (1) decouples construction of the 3D multi-resolution representation required for visualization from data acquisition, and (2) decouples sample access time during ray-casting from the size of the multi-resolution hierarchy. Our system is designed around a scalable multi-resolution virtual memory architecture that handles missing data naturally, does not pre-compute any 3D multi-resolution representation such as an octree, and can accept a constant stream of 2D image tiles from the microscopes. A novelty of our system design is that it is visualization-driven: we restrict most computations to the visible volume data. Leveraging the virtual memory architecture, missing data are detected during volume ray-casting as cache misses, which are propagated backwards for on-demand out-of-core processing. 3D blocks of volume data are only constructed from 2D microscope image tiles when they have actually been accessed during ray-casting. We extensively evaluate our system design choices with respect to scalability and performance, compare to previous best-of-breed systems, and illustrate the effectiveness of our system for real microscopy data from neuroscience.

Scalable domain decomposition solvers for stochastic PDEs in high performance computing

DOE PAGES

Desai, Ajit; Khalil, Mohammad; Pettit, Chris; ...

2017-09-21

Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolutionmore » in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.« less

Scalable domain decomposition solvers for stochastic PDEs in high performance computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Desai, Ajit; Khalil, Mohammad; Pettit, Chris

Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolutionmore » in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.« less

Faceted Visualization of Three Dimensional Neuroanatomy By Combining Ontology with Faceted Search

PubMed Central

Veeraraghavan, Harini; Miller, James V.

2013-01-01

In this work, we present a faceted-search based approach for visualization of anatomy by combining a three dimensional digital atlas with an anatomy ontology. Specifically, our approach provides a drill-down search interface that exposes the relevant pieces of information (obtained by searching the ontology) for a user query. Hence, the user can produce visualizations starting with minimally specified queries. Furthermore, by automatically translating the user queries into the controlled terminology our approach eliminates the need for the user to use controlled terminology. We demonstrate the scalability of our approach using an abdominal atlas and the same ontology. We implemented our visualization tool on the opensource 3D Slicer software. We present results of our visualization approach by combining a modified Foundational Model of Anatomy (FMA) ontology with the Surgical Planning Laboratory (SPL) Brain 3D digital atlas, and geometric models specific to patients computed using the SPL brain tumor dataset. PMID:24006207

Faceted visualization of three dimensional neuroanatomy by combining ontology with faceted search.

PubMed

Veeraraghavan, Harini; Miller, James V

2014-04-01

In this work, we present a faceted-search based approach for visualization of anatomy by combining a three dimensional digital atlas with an anatomy ontology. Specifically, our approach provides a drill-down search interface that exposes the relevant pieces of information (obtained by searching the ontology) for a user query. Hence, the user can produce visualizations starting with minimally specified queries. Furthermore, by automatically translating the user queries into the controlled terminology our approach eliminates the need for the user to use controlled terminology. We demonstrate the scalability of our approach using an abdominal atlas and the same ontology. We implemented our visualization tool on the opensource 3D Slicer software. We present results of our visualization approach by combining a modified Foundational Model of Anatomy (FMA) ontology with the Surgical Planning Laboratory (SPL) Brain 3D digital atlas, and geometric models specific to patients computed using the SPL brain tumor dataset.

Optimal bit allocation for hybrid scalable/multiple-description video transmission over wireless channels

NASA Astrophysics Data System (ADS)

Jubran, Mohammad K.; Bansal, Manu; Kondi, Lisimachos P.

2006-01-01

In this paper, we consider the problem of optimal bit allocation for wireless video transmission over fading channels. We use a newly developed hybrid scalable/multiple-description codec that combines the functionality of both scalable and multiple-description codecs. It produces a base layer and multiple-description enhancement layers. Any of the enhancement layers can be decoded (in a non-hierarchical manner) with the base layer to improve the reconstructed video quality. Two different channel coding schemes (Rate-Compatible Punctured Convolutional (RCPC)/Cyclic Redundancy Check (CRC) coding and, product code Reed Solomon (RS)+RCPC/CRC coding) are used for unequal error protection of the layered bitstream. Optimal allocation of the bitrate between source and channel coding is performed for discrete sets of source coding rates and channel coding rates. Experimental results are presented for a wide range of channel conditions. Also, comparisons with classical scalable coding show the effectiveness of using hybrid scalable/multiple-description coding for wireless transmission.

PERCEPT: indoor navigation for the blind and visually impaired.

PubMed

Ganz, Aura; Gandhi, Siddhesh Rajan; Schafer, James; Singh, Tushar; Puleo, Elaine; Mullett, Gary; Wilson, Carole

2011-01-01

In order to enhance the perception of indoor and unfamiliar environments for the blind and visually-impaired, we introduce the PERCEPT system that supports a number of unique features such as: a) Low deployment and maintenance cost; b) Scalability, i.e. we can deploy the system in very large buildings; c) An on-demand system that does not overwhelm the user, as it offers small amounts of information on demand; and d) Portability and ease-of-use, i.e., the custom handheld device carried by the user is compact and instructions are received audibly.

Scalability of grid- and subbasin-based land surface modeling approaches for hydrologic simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tesfa, Teklu K.; Ruby Leung, L.; Huang, Maoyi

2014-03-27

This paper investigates the relative merits of grid- and subbasin-based land surface modeling approaches for hydrologic simulations, with a focus on their scalability (i.e., abilities to perform consistently across a range of spatial resolutions) in simulating runoff generation. Simulations produced by the grid- and subbasin-based configurations of the Community Land Model (CLM) are compared at four spatial resolutions (0.125o, 0.25o, 0.5o and 1o) over the topographically diverse region of the U.S. Pacific Northwest. Using the 0.125o resolution simulation as the “reference”, statistical skill metrics are calculated and compared across simulations at 0.25o, 0.5o and 1o spatial resolutions of each modelingmore » approach at basin and topographic region levels. Results suggest significant scalability advantage for the subbasin-based approach compared to the grid-based approach for runoff generation. Basin level annual average relative errors of surface runoff at 0.25o, 0.5o, and 1o compared to 0.125o are 3%, 4%, and 6% for the subbasin-based configuration and 4%, 7%, and 11% for the grid-based configuration, respectively. The scalability advantages of the subbasin-based approach are more pronounced during winter/spring and over mountainous regions. The source of runoff scalability is found to be related to the scalability of major meteorological and land surface parameters of runoff generation. More specifically, the subbasin-based approach is more consistent across spatial scales than the grid-based approach in snowfall/rainfall partitioning, which is related to air temperature and surface elevation. Scalability of a topographic parameter used in the runoff parameterization also contributes to improved scalability of the rain driven saturated surface runoff component, particularly during winter. Hence this study demonstrates the importance of spatial structure for multi-scale modeling of hydrological processes, with implications to surface heat fluxes in

A look at scalable dense linear algebra libraries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dongarra, J.J.; Van de Geijn, R.A.; Walker, D.W.

1992-01-01

We discuss the essential design features of a library of scalable software for performing dense linear algebra computations on distributed memory concurrent computers. The square block scattered decomposition is proposed as a flexible and general-purpose way of decomposing most, if not all, dense matrix problems. An object- oriented interface to the library permits more portable applications to be written, and is easy to learn and use, since details of the parallel implementation are hidden from the user. Experiments on the Intel Touchstone Delta system with a prototype code that uses the square block scattered decomposition to perform LU factorization aremore » presented and analyzed. It was found that the code was both scalable and efficient, performing at about 14 GFLOPS (double precision) for the largest problem considered.« less

A look at scalable dense linear algebra libraries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dongarra, J.J.; Van de Geijn, R.A.; Walker, D.W.

1992-08-01

We discuss the essential design features of a library of scalable software for performing dense linear algebra computations on distributed memory concurrent computers. The square block scattered decomposition is proposed as a flexible and general-purpose way of decomposing most, if not all, dense matrix problems. An object- oriented interface to the library permits more portable applications to be written, and is easy to learn and use, since details of the parallel implementation are hidden from the user. Experiments on the Intel Touchstone Delta system with a prototype code that uses the square block scattered decomposition to perform LU factorization aremore » presented and analyzed. It was found that the code was both scalable and efficient, performing at about 14 GFLOPS (double precision) for the largest problem considered.« less

Scalable quantum memory in the ultrastrong coupling regime.

PubMed

Kyaw, T H; Felicetti, S; Romero, G; Solano, E; Kwek, L-C

2015-03-02

Circuit quantum electrodynamics, consisting of superconducting artificial atoms coupled to on-chip resonators, represents a prime candidate to implement the scalable quantum computing architecture because of the presence of good tunability and controllability. Furthermore, recent advances have pushed the technology towards the ultrastrong coupling regime of light-matter interaction, where the qubit-resonator coupling strength reaches a considerable fraction of the resonator frequency. Here, we propose a qubit-resonator system operating in that regime, as a quantum memory device and study the storage and retrieval of quantum information in and from the Z2 parity-protected quantum memory, within experimentally feasible schemes. We are also convinced that our proposal might pave a way to realize a scalable quantum random-access memory due to its fast storage and readout performances.

Scalable quantum memory in the ultrastrong coupling regime

PubMed Central

Kyaw, T. H.; Felicetti, S.; Romero, G.; Solano, E.; Kwek, L.-C.

2015-01-01

Circuit quantum electrodynamics, consisting of superconducting artificial atoms coupled to on-chip resonators, represents a prime candidate to implement the scalable quantum computing architecture because of the presence of good tunability and controllability. Furthermore, recent advances have pushed the technology towards the ultrastrong coupling regime of light-matter interaction, where the qubit-resonator coupling strength reaches a considerable fraction of the resonator frequency. Here, we propose a qubit-resonator system operating in that regime, as a quantum memory device and study the storage and retrieval of quantum information in and from the Z2 parity-protected quantum memory, within experimentally feasible schemes. We are also convinced that our proposal might pave a way to realize a scalable quantum random-access memory due to its fast storage and readout performances. PMID:25727251

A scalable and operationally simple radical trifluoromethylation

PubMed Central

Beatty, Joel W.; Douglas, James J.; Cole, Kevin P.; Stephenson, Corey R. J.

2015-01-01

The large number of reagents that have been developed for the synthesis of trifluoromethylated compounds is a testament to the importance of the CF3 group as well as the associated synthetic challenge. Current state-of-the-art reagents for appending the CF3 functionality directly are highly effective; however, their use on preparative scale has minimal precedent because they require multistep synthesis for their preparation, and/or are prohibitively expensive for large-scale application. For a scalable trifluoromethylation methodology, trifluoroacetic acid and its anhydride represent an attractive solution in terms of cost and availability; however, because of the exceedingly high oxidation potential of trifluoroacetate, previous endeavours to use this material as a CF3 source have required the use of highly forcing conditions. Here we report a strategy for the use of trifluoroacetic anhydride for a scalable and operationally simple trifluoromethylation reaction using pyridine N-oxide and photoredox catalysis to affect a facile decarboxylation to the CF3 radical. PMID:26258541

Scalable architecture for a room temperature solid-state quantum information processor.

PubMed

Yao, N Y; Jiang, L; Gorshkov, A V; Maurer, P C; Giedke, G; Cirac, J I; Lukin, M D

2012-04-24

The realization of a scalable quantum information processor has emerged over the past decade as one of the central challenges at the interface of fundamental science and engineering. Here we propose and analyse an architecture for a scalable, solid-state quantum information processor capable of operating at room temperature. Our approach is based on recent experimental advances involving nitrogen-vacancy colour centres in diamond. In particular, we demonstrate that the multiple challenges associated with operation at ambient temperature, individual addressing at the nanoscale, strong qubit coupling, robustness against disorder and low decoherence rates can be simultaneously achieved under realistic, experimentally relevant conditions. The architecture uses a novel approach to quantum information transfer and includes a hierarchy of control at successive length scales. Moreover, it alleviates the stringent constraints currently limiting the realization of scalable quantum processors and will provide fundamental insights into the physics of non-equilibrium many-body quantum systems.

Scalability of voltage-controlled filamentary and nanometallic resistance memory devices.

PubMed

Lu, Yang; Lee, Jong Ho; Chen, I-Wei

2017-08-31

Much effort has been devoted to device and materials engineering to realize nanoscale resistance random access memory (RRAM) for practical applications, but a rational physical basis to be relied on to design scalable devices spanning many length scales is still lacking. In particular, there is no clear criterion for switching control in those RRAM devices in which resistance changes are limited to localized nanoscale filaments that experience concentrated heat, electric current and field. Here, we demonstrate voltage-controlled resistance switching, always at a constant characteristic critical voltage, for macro and nanodevices in both filamentary RRAM and nanometallic RRAM, and the latter switches uniformly and does not require a forming process. As a result, area-scalability can be achieved under a device-area-proportional current compliance for the low resistance state of the filamentary RRAM, and for both the low and high resistance states of the nanometallic RRAM. This finding will help design area-scalable RRAM at the nanoscale. It also establishes an analogy between RRAM and synapses, in which signal transmission is also voltage-controlled.

Image retrieval by information fusion based on scalable vocabulary tree and robust Hausdorff distance

NASA Astrophysics Data System (ADS)

Che, Chang; Yu, Xiaoyang; Sun, Xiaoming; Yu, Boyang

2017-12-01

In recent years, Scalable Vocabulary Tree (SVT) has been shown to be effective in image retrieval. However, for general images where the foreground is the object to be recognized while the background is cluttered, the performance of the current SVT framework is restricted. In this paper, a new image retrieval framework that incorporates a robust distance metric and information fusion is proposed, which improves the retrieval performance relative to the baseline SVT approach. First, the visual words that represent the background are diminished by using a robust Hausdorff distance between different images. Second, image matching results based on three image signature representations are fused, which enhances the retrieval precision. We conducted intensive experiments on small-scale to large-scale image datasets: Corel-9, Corel-48, and PKU-198, where the proposed Hausdorff metric and information fusion outperforms the state-of-the-art methods by about 13, 15, and 15%, respectively.

PM2006: a highly scalable urban planning management information system--Case study: Suzhou Urban Planning Bureau

NASA Astrophysics Data System (ADS)

Jing, Changfeng; Liang, Song; Ruan, Yong; Huang, Jie

2008-10-01

During the urbanization process, when facing complex requirements of city development, ever-growing urban data, rapid development of planning business and increasing planning complexity, a scalable, extensible urban planning management information system is needed urgently. PM2006 is such a system that can deal with these problems. In response to the status and problems in urban planning, the scalability and extensibility of PM2006 are introduced which can be seen as business-oriented workflow extensibility, scalability of DLL-based architecture, flexibility on platforms of GIS and database, scalability of data updating and maintenance and so on. It is verified that PM2006 system has good extensibility and scalability which can meet the requirements of all levels of administrative divisions and can adapt to ever-growing changes in urban planning business. At the end of this paper, the application of PM2006 in Urban Planning Bureau of Suzhou city is described.

Visualizing Article Similarities via Sparsified Article Network and Map Projection for Systematic Reviews.

PubMed

Ji, Xiaonan; Machiraju, Raghu; Ritter, Alan; Yen, Po-Yin

2017-01-01

Systematic Reviews (SRs) of biomedical literature summarize evidence from high-quality studies to inform clinical decisions, but are time and labor intensive due to the large number of article collections. Article similarities established from textual features have been shown to assist in the identification of relevant articles, thus facilitating the article screening process efficiently. In this study, we visualized article similarities to extend its utilization in practical settings for SR researchers, aiming to promote human comprehension of article distributions and hidden patterns. To prompt an effective visualization in an interpretable, intuitive, and scalable way, we implemented a graph-based network visualization with three network sparsification approaches and a distance-based map projection via dimensionality reduction. We evaluated and compared three network sparsification approaches and the visualization types (article network vs. article map). We demonstrated the effectiveness in revealing article distribution and exhibiting clustering patterns of relevant articles with practical meanings for SRs.

STRING 3: An Advanced Groundwater Flow Visualization Tool

NASA Astrophysics Data System (ADS)

Schröder, Simon; Michel, Isabel; Biedert, Tim; Gräfe, Marius; Seidel, Torsten; König, Christoph

2016-04-01

The visualization of 3D groundwater flow is a challenging task. Previous versions of our software STRING [1] solely focused on intuitive visualization of complex flow scenarios for non-professional audiences. STRING, developed by Fraunhofer ITWM (Kaiserslautern, Germany) and delta h Ingenieurgesellschaft mbH (Witten, Germany), provides the necessary means for visualization of both 2D and 3D data on planar and curved surfaces. In this contribution we discuss how to extend this approach to a full 3D tool and its challenges in continuation of Michel et al. [2]. This elevates STRING from a post-production to an exploration tool for experts. In STRING moving pathlets provide an intuition of velocity and direction of both steady-state and transient flows. The visualization concept is based on the Lagrangian view of the flow. To capture every detail of the flow an advanced method for intelligent, time-dependent seeding is used building on the Finite Pointset Method (FPM) developed by Fraunhofer ITWM. Lifting our visualization approach from 2D into 3D provides many new challenges. With the implementation of a seeding strategy for 3D one of the major problems has already been solved (see Schröder et al. [3]). As pathlets only provide an overview of the velocity field other means are required for the visualization of additional flow properties. We suggest the use of Direct Volume Rendering and isosurfaces for scalar features. In this regard we were able to develop an efficient approach for combining the rendering through raytracing of the volume and regular OpenGL geometries. This is achieved through the use of Depth Peeling or A-Buffers for the rendering of transparent geometries. Animation of pathlets requires a strict boundary of the simulation domain. Hence, STRING needs to extract the boundary, even from unstructured data, if it is not provided. In 3D we additionally need a good visualization of the boundary itself. For this the silhouette based on the angle of

Scalable Video Streaming Relay for Smart Mobile Devices in Wireless Networks

PubMed Central

Kwon, Dongwoo; Je, Huigwang; Kim, Hyeonwoo; Ju, Hongtaek; An, Donghyeok

2016-01-01

Recently, smart mobile devices and wireless communication technologies such as WiFi, third generation (3G), and long-term evolution (LTE) have been rapidly deployed. Many smart mobile device users can access the Internet wirelessly, which has increased mobile traffic. In 2014, more than half of the mobile traffic around the world was devoted to satisfying the increased demand for the video streaming. In this paper, we propose a scalable video streaming relay scheme. Because many collisions degrade the scalability of video streaming, we first separate networks to prevent excessive contention between devices. In addition, the member device controls the video download rate in order to adapt to video playback. If the data are sufficiently buffered, the member device stops the download. If not, it requests additional video data. We implemented apps to evaluate the proposed scheme and conducted experiments with smart mobile devices. The results showed that our scheme improves the scalability of video streaming in a wireless local area network (WLAN). PMID:27907113

Scalable Video Streaming Relay for Smart Mobile Devices in Wireless Networks.

PubMed

Kwon, Dongwoo; Je, Huigwang; Kim, Hyeonwoo; Ju, Hongtaek; An, Donghyeok

2016-01-01

Recently, smart mobile devices and wireless communication technologies such as WiFi, third generation (3G), and long-term evolution (LTE) have been rapidly deployed. Many smart mobile device users can access the Internet wirelessly, which has increased mobile traffic. In 2014, more than half of the mobile traffic around the world was devoted to satisfying the increased demand for the video streaming. In this paper, we propose a scalable video streaming relay scheme. Because many collisions degrade the scalability of video streaming, we first separate networks to prevent excessive contention between devices. In addition, the member device controls the video download rate in order to adapt to video playback. If the data are sufficiently buffered, the member device stops the download. If not, it requests additional video data. We implemented apps to evaluate the proposed scheme and conducted experiments with smart mobile devices. The results showed that our scheme improves the scalability of video streaming in a wireless local area network (WLAN).

Rocinante, a virtual collaborative visualizer

DOE Office of Scientific and Technical Information (OSTI.GOV)

McDonald, M.J.; Ice, L.G.

1996-12-31

With the goal of improving the ability of people around the world to share the development and use of intelligent systems, Sandia National Laboratories` Intelligent Systems and Robotics Center is developing new Virtual Collaborative Engineering (VCE) and Virtual Collaborative Control (VCC) technologies. A key area of VCE and VCC research is in shared visualization of virtual environments. This paper describes a Virtual Collaborative Visualizer (VCV), named Rocinante, that Sandia developed for VCE and VCC applications. Rocinante allows multiple participants to simultaneously view dynamic geometrically-defined environments. Each viewer can exclude extraneous detail or include additional information in the scene as desired.more » Shared information can be saved and later replayed in a stand-alone mode. Rocinante automatically scales visualization requirements with computer system capabilities. Models with 30,000 polygons and 4 Megabytes of texture display at 12 to 15 frames per second (fps) on an SGI Onyx and at 3 to 8 fps (without texture) on Indigo 2 Extreme computers. In its networked mode, Rocinante synchronizes its local geometric model with remote simulators and sensory systems by monitoring data transmitted through UDP packets. Rocinante`s scalability and performance make it an ideal VCC tool. Users throughout the country can monitor robot motions and the thinking behind their motion planners and simulators.« less

SeqPig: simple and scalable scripting for large sequencing data sets in Hadoop.

PubMed

Schumacher, André; Pireddu, Luca; Niemenmaa, Matti; Kallio, Aleksi; Korpelainen, Eija; Zanetti, Gianluigi; Heljanko, Keijo

2014-01-01

Hadoop MapReduce-based approaches have become increasingly popular due to their scalability in processing large sequencing datasets. However, as these methods typically require in-depth expertise in Hadoop and Java, they are still out of reach of many bioinformaticians. To solve this problem, we have created SeqPig, a library and a collection of tools to manipulate, analyze and query sequencing datasets in a scalable and simple manner. SeqPigscripts use the Hadoop-based distributed scripting engine Apache Pig, which automatically parallelizes and distributes data processing tasks. We demonstrate SeqPig's scalability over many computing nodes and illustrate its use with example scripts. Available under the open source MIT license at http://sourceforge.net/projects/seqpig/

Scalable Optical-Fiber Communication Networks

NASA Technical Reports Server (NTRS)

Chow, Edward T.; Peterson, John C.

1993-01-01

Scalable arbitrary fiber extension network (SAFEnet) is conceptual fiber-optic communication network passing digital signals among variety of computers and input/output devices at rates from 200 Mb/s to more than 100 Gb/s. Intended for use with very-high-speed computers and other data-processing and communication systems in which message-passing delays must be kept short. Inherent flexibility makes it possible to match performance of network to computers by optimizing configuration of interconnections. In addition, interconnections made redundant to provide tolerance to faults.

Space Situational Awareness Data Processing Scalability Utilizing Google Cloud Services

NASA Astrophysics Data System (ADS)

Greenly, D.; Duncan, M.; Wysack, J.; Flores, F.

Space Situational Awareness (SSA) is a fundamental and critical component of current space operations. The term SSA encompasses the awareness, understanding and predictability of all objects in space. As the population of orbital space objects and debris increases, the number of collision avoidance maneuvers grows and prompts the need for accurate and timely process measures. The SSA mission continually evolves to near real-time assessment and analysis demanding the need for higher processing capabilities. By conventional methods, meeting these demands requires the integration of new hardware to keep pace with the growing complexity of maneuver planning algorithms. SpaceNav has implemented a highly scalable architecture that will track satellites and debris by utilizing powerful virtual machines on the Google Cloud Platform. SpaceNav algorithms for processing CDMs outpace conventional means. A robust processing environment for tracking data, collision avoidance maneuvers and various other aspects of SSA can be created and deleted on demand. Migrating SpaceNav tools and algorithms into the Google Cloud Platform will be discussed and the trials and tribulations involved. Information will be shared on how and why certain cloud products were used as well as integration techniques that were implemented. Key items to be presented are: 1.Scientific algorithms and SpaceNav tools integrated into a scalable architecture a) Maneuver Planning b) Parallel Processing c) Monte Carlo Simulations d) Optimization Algorithms e) SW Application Development/Integration into the Google Cloud Platform 2. Compute Engine Processing a) Application Engine Automated Processing b) Performance testing and Performance Scalability c) Cloud MySQL databases and Database Scalability d) Cloud Data Storage e) Redundancy and Availability

Scalability, Timing, and System Design Issues for Intrinsic Evolvable Hardware

NASA Technical Reports Server (NTRS)

Hereford, James; Gwaltney, David

2004-01-01

In this paper we address several issues pertinent to intrinsic evolvable hardware (EHW). The first issue is scalability; namely, how the design space scales as the programming string for the programmable device gets longer. We develop a model for population size and the number of generations as a function of the programming string length, L, and show that the number of circuit evaluations is an O(L2) process. We compare our model to several successful intrinsic EHW experiments and discuss the many implications of our model. The second issue that we address is the timing of intrinsic EHW experiments. We show that the processing time is a small part of the overall time to derive or evolve a circuit and that major improvements in processor speed alone will have only a minimal impact on improving the scalability of intrinsic EHW. The third issue we consider is the system-level design of intrinsic EHW experiments. We review what other researchers have done to break the scalability barrier and contend that the type of reconfigurable platform and the evolutionary algorithm are tied together and impose limits on each other.

OIPAV: an integrated software system for ophthalmic image processing, analysis and visualization

NASA Astrophysics Data System (ADS)

Zhang, Lichun; Xiang, Dehui; Jin, Chao; Shi, Fei; Yu, Kai; Chen, Xinjian

2018-03-01

OIPAV (Ophthalmic Images Processing, Analysis and Visualization) is a cross-platform software which is specially oriented to ophthalmic images. It provides a wide range of functionalities including data I/O, image processing, interaction, ophthalmic diseases detection, data analysis and visualization to help researchers and clinicians deal with various ophthalmic images such as optical coherence tomography (OCT) images and color photo of fundus, etc. It enables users to easily access to different ophthalmic image data manufactured from different imaging devices, facilitate workflows of processing ophthalmic images and improve quantitative evaluations. In this paper, we will present the system design and functional modules of the platform and demonstrate various applications. With a satisfying function scalability and expandability, we believe that the software can be widely applied in ophthalmology field.

QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics.

PubMed

O'Reilly, Paul G; Wen, Qing; Bankhead, Peter; Dunne, Philip D; McArt, Darragh G; McPherson, Suzanne; Hamilton, Peter W; Mills, Ken I; Zhang, Shu-Dong

2016-05-04

Gene expression connectivity mapping has proven to be a powerful and flexible tool for research. Its application has been shown in a broad range of research topics, most commonly as a means of identifying potential small molecule compounds, which may be further investigated as candidates for repurposing to treat diseases. The public release of voluminous data from the Library of Integrated Cellular Signatures (LINCS) programme further enhanced the utilities and potentials of gene expression connectivity mapping in biomedicine. We describe QUADrATiC ( http://go.qub.ac.uk/QUADrATiC ), a user-friendly tool for the exploration of gene expression connectivity on the subset of the LINCS data set corresponding to FDA-approved small molecule compounds. It enables the identification of compounds for repurposing therapeutic potentials. The software is designed to cope with the increased volume of data over existing tools, by taking advantage of multicore computing architectures to provide a scalable solution, which may be installed and operated on a range of computers, from laptops to servers. This scalability is provided by the use of the modern concurrent programming paradigm provided by the Akka framework. The QUADrATiC Graphical User Interface (GUI) has been developed using advanced Javascript frameworks, providing novel visualization capabilities for further analysis of connections. There is also a web services interface, allowing integration with other programs or scripts. QUADrATiC has been shown to provide an improvement over existing connectivity map software, in terms of scope (based on the LINCS data set), applicability (using FDA-approved compounds), usability and speed. It offers potential to biological researchers to analyze transcriptional data and generate potential therapeutics for focussed study in the lab. QUADrATiC represents a step change in the process of investigating gene expression connectivity and provides more biologically-relevant results than

Adaptive UEP and Packet Size Assignment for Scalable Video Transmission over Burst-Error Channels

NASA Astrophysics Data System (ADS)

Lee, Chen-Wei; Yang, Chu-Sing; Su, Yih-Ching

2006-12-01

This work proposes an adaptive unequal error protection (UEP) and packet size assignment scheme for scalable video transmission over a burst-error channel. An analytic model is developed to evaluate the impact of channel bit error rate on the quality of streaming scalable video. A video transmission scheme, which combines the adaptive assignment of packet size with unequal error protection to increase the end-to-end video quality, is proposed. Several distinct scalable video transmission schemes over burst-error channel have been compared, and the simulation results reveal that the proposed transmission schemes can react to varying channel conditions with less and smoother quality degradation.

Error-Resilient Unequal Error Protection of Fine Granularity Scalable Video Bitstreams

NASA Astrophysics Data System (ADS)

Cai, Hua; Zeng, Bing; Shen, Guobin; Xiong, Zixiang; Li, Shipeng

2006-12-01

This paper deals with the optimal packet loss protection issue for streaming the fine granularity scalable (FGS) video bitstreams over IP networks. Unlike many other existing protection schemes, we develop an error-resilient unequal error protection (ER-UEP) method that adds redundant information optimally for loss protection and, at the same time, cancels completely the dependency among bitstream after loss recovery. In our ER-UEP method, the FGS enhancement-layer bitstream is first packetized into a group of independent and scalable data packets. Parity packets, which are also scalable, are then generated. Unequal protection is finally achieved by properly shaping the data packets and the parity packets. We present an algorithm that can optimally allocate the rate budget between data packets and parity packets, together with several simplified versions that have lower complexity. Compared with conventional UEP schemes that suffer from bit contamination (caused by the bit dependency within a bitstream), our method guarantees successful decoding of all received bits, thus leading to strong error-resilience (at any fixed channel bandwidth) and high robustness (under varying and/or unclean channel conditions).

Scalable digital hardware for a trapped ion quantum computer

NASA Astrophysics Data System (ADS)

Mount, Emily; Gaultney, Daniel; Vrijsen, Geert; Adams, Michael; Baek, So-Young; Hudek, Kai; Isabella, Louis; Crain, Stephen; van Rynbach, Andre; Maunz, Peter; Kim, Jungsang

2016-12-01

Many of the challenges of scaling quantum computer hardware lie at the interface between the qubits and the classical control signals used to manipulate them. Modular ion trap quantum computer architectures address scalability by constructing individual quantum processors interconnected via a network of quantum communication channels. Successful operation of such quantum hardware requires a fully programmable classical control system capable of frequency stabilizing the continuous wave lasers necessary for loading, cooling, initialization, and detection of the ion qubits, stabilizing the optical frequency combs used to drive logic gate operations on the ion qubits, providing a large number of analog voltage sources to drive the trap electrodes, and a scheme for maintaining phase coherence among all the controllers that manipulate the qubits. In this work, we describe scalable solutions to these hardware development challenges.

Efficient Prediction Structures for H.264 Multi View Coding Using Temporal Scalability

NASA Astrophysics Data System (ADS)

Guruvareddiar, Palanivel; Joseph, Biju K.

2014-03-01

Prediction structures with "disposable view components based" hierarchical coding have been proven to be efficient for H.264 multi view coding. Though these prediction structures along with the QP cascading schemes provide superior compression efficiency when compared to the traditional IBBP coding scheme, the temporal scalability requirements of the bit stream could not be met to the fullest. On the other hand, a fully scalable bit stream, obtained by "temporal identifier based" hierarchical coding, provides a number of advantages including bit rate adaptations and improved error resilience, but lacks in compression efficiency when compared to the former scheme. In this paper it is proposed to combine the two approaches such that a fully scalable bit stream could be realized with minimal reduction in compression efficiency when compared to state-of-the-art "disposable view components based" hierarchical coding. Simulation results shows that the proposed method enables full temporal scalability with maximum BDPSNR reduction of only 0.34 dB. A novel method also has been proposed for the identification of temporal identifier for the legacy H.264/AVC base layer packets. Simulation results also show that this enables the scenario where the enhancement views could be extracted at a lower frame rate (1/2nd or 1/4th of base view) with average extraction time for a view component of only 0.38 ms.

Visualizing the spinal neuronal dynamics of locomotion

NASA Astrophysics Data System (ADS)

Subramanian, Kalpathi R.; Bashor, D. P.; Miller, M. T.; Foster, J. A.

2004-06-01

Modern imaging and simulation techniques have enhanced system-level understanding of neural function. In this article, we present an application of interactive visualization to understanding neuronal dynamics causing locomotion of a single hip joint, based on pattern generator output of the spinal cord. Our earlier work visualized cell-level responses of multiple neuronal populations. However, the spatial relationships were abstract, making communication with colleagues difficult. We propose two approaches to overcome this: (1) building a 3D anatomical model of the spinal cord with neurons distributed inside, animated by the simulation and (2) adding limb movements predicted by neuronal activity. The new system was tested using a cat walking central pattern generator driving a pair of opposed spinal motoneuron pools. Output of opposing motoneuron pools was combined into a single metric, called "Net Neural Drive", which generated angular limb movement in proportion to its magnitude. Net neural drive constitutes a new description of limb movement control. The combination of spatial and temporal information in the visualizations elegantly conveys the neural activity of the output elements (motoneurons), as well as the resulting movement. The new system encompasses five biological levels of organization from ion channels to observed behavior. The system is easily scalable, and provides an efficient interactive platform for rapid hypothesis testing.

A Lightweight Remote Parallel Visualization Platform for Interactive Massive Time-varying Climate Data Analysis

NASA Astrophysics Data System (ADS)

Li, J.; Zhang, T.; Huang, Q.; Liu, Q.

2014-12-01

Today's climate datasets are featured with large volume, high degree of spatiotemporal complexity and evolving fast overtime. As visualizing large volume distributed climate datasets is computationally intensive, traditional desktop based visualization applications fail to handle the computational intensity. Recently, scientists have developed remote visualization techniques to address the computational issue. Remote visualization techniques usually leverage server-side parallel computing capabilities to perform visualization tasks and deliver visualization results to clients through network. In this research, we aim to build a remote parallel visualization platform for visualizing and analyzing massive climate data. Our visualization platform was built based on Paraview, which is one of the most popular open source remote visualization and analysis applications. To further enhance the scalability and stability of the platform, we have employed cloud computing techniques to support the deployment of the platform. In this platform, all climate datasets are regular grid data which are stored in NetCDF format. Three types of data access methods are supported in the platform: accessing remote datasets provided by OpenDAP servers, accessing datasets hosted on the web visualization server and accessing local datasets. Despite different data access methods, all visualization tasks are completed at the server side to reduce the workload of clients. As a proof of concept, we have implemented a set of scientific visualization methods to show the feasibility of the platform. Preliminary results indicate that the framework can address the computation limitation of desktop based visualization applications.

MicROS-drt: supporting real-time and scalable data distribution in distributed robotic systems.

PubMed

Ding, Bo; Wang, Huaimin; Fan, Zedong; Zhang, Pengfei; Liu, Hui

A primary requirement in distributed robotic software systems is the dissemination of data to all interested collaborative entities in a timely and scalable manner. However, providing such a service in a highly dynamic and resource-limited robotic environment is a challenging task, and existing robot software infrastructure has limitations in this aspect. This paper presents a novel robot software infrastructure, micROS-drt, which supports real-time and scalable data distribution. The solution is based on a loosely coupled data publish-subscribe model with the ability to support various time-related constraints. And to realize this model, a mature data distribution standard, the data distribution service for real-time systems (DDS), is adopted as the foundation of the transport layer of this software infrastructure. By elaborately adapting and encapsulating the capability of the underlying DDS middleware, micROS-drt can meet the requirement of real-time and scalable data distribution in distributed robotic systems. Evaluation results in terms of scalability, latency jitter and transport priority as well as the experiment on real robots validate the effectiveness of this work.

Scalable graphene coatings for enhanced condensation heat transfer.

PubMed

Preston, Daniel J; Mafra, Daniela L; Miljkovic, Nenad; Kong, Jing; Wang, Evelyn N

2015-05-13

Water vapor condensation is commonly observed in nature and routinely used as an effective means of transferring heat with dropwise condensation on nonwetting surfaces exhibiting heat transfer improvement compared to filmwise condensation on wetting surfaces. However, state-of-the-art techniques to promote dropwise condensation rely on functional hydrophobic coatings that either have challenges with chemical stability or are so thick that any potential heat transfer improvement is negated due to the added thermal resistance of the coating. In this work, we show the effectiveness of ultrathin scalable chemical vapor deposited (CVD) graphene coatings to promote dropwise condensation while offering robust chemical stability and maintaining low thermal resistance. Heat transfer enhancements of 4× were demonstrated compared to filmwise condensation, and the robustness of these CVD coatings was superior to typical hydrophobic monolayer coatings. Our results indicate that graphene is a promising surface coating to promote dropwise condensation of water in industrial conditions with the potential for scalable application via CVD.

A high-quality high-fidelity visualization of the September 11 attack on the World Trade Center.

PubMed

Rosen, Paul; Popescu, Voicu; Hoffmann, Christoph; Irfanoglu, Ayhan

2008-01-01

In this application paper, we describe the efforts of a multidisciplinary team towards producing a visualization of the September 11 Attack on the North Tower of New York's World Trade Center. The visualization was designed to meet two requirements. First, the visualization had to depict the impact with high fidelity, by closely following the laws of physics. Second, the visualization had to be eloquent to a nonexpert user. This was achieved by first designing and computing a finite-element analysis (FEA) simulation of the impact between the aircraft and the top 20 stories of the building, and then by visualizing the FEA results with a state-of-the-art commercial animation system. The visualization was enabled by an automatic translator that converts the simulation data into an animation system 3D scene. We built upon a previously developed translator. The translator was substantially extended to enable and control visualization of fire and of disintegrating elements, to better scale with the number of nodes and number of states, to handle beam elements with complex profiles, and to handle smoothed particle hydrodynamics liquid representation. The resulting translator is a powerful automatic and scalable tool for high-quality visualization of FEA results.

Scalable microreactors and methods for using same

DOEpatents

Lawal, Adeniyi; Qian, Dongying

2010-03-02

The present invention provides a scalable microreactor comprising a multilayered reaction block having alternating reaction plates and heat exchanger plates that have a plurality of microchannels; a multilaminated reactor input manifold, a collecting reactor output manifold, a heat exchange input manifold and a heat exchange output manifold. The present invention also provides methods of using the microreactor for multiphase chemical reactions.

Data Visualization Using Immersive Virtual Reality Tools

NASA Astrophysics Data System (ADS)

Cioc, Alexandru; Djorgovski, S. G.; Donalek, C.; Lawler, E.; Sauer, F.; Longo, G.

2013-01-01

The growing complexity of scientific data poses serious challenges for an effective visualization. Data sets, e.g., catalogs of objects detected in sky surveys, can have a very high dimensionality, ~ 100 - 1000. Visualizing such hyper-dimensional data parameter spaces is essentially impossible, but there are ways of visualizing up to ~ 10 dimensions in a pseudo-3D display. We have been experimenting with the emerging technologies of immersive virtual reality (VR) as a platform for a scientific, interactive, collaborative data visualization. Our initial experiments used the virtual world of Second Life, and more recently VR worlds based on its open source code, OpenSimulator. There we can visualize up to ~ 100,000 data points in ~ 7 - 8 dimensions (3 spatial and others encoded as shapes, colors, sizes, etc.), in an immersive virtual space where scientists can interact with their data and with each other. We are now developing a more scalable visualization environment using the popular (practically an emerging standard) Unity 3D Game Engine, coded using C#, JavaScript, and the Unity Scripting Language. This visualization tool can be used through a standard web browser, or a standalone browser of its own. Rather than merely plotting data points, the application creates interactive three-dimensional objects of various shapes, colors, and sizes, and of course the XYZ positions, encoding various dimensions of the parameter space, that can be associated interactively. Multiple users can navigate through this data space simultaneously, either with their own, independent vantage points, or with a shared view. At this stage ~ 100,000 data points can be easily visualized within seconds on a simple laptop. The displayed data points can contain linked information; e.g., upon a clicking on a data point, a webpage with additional information can be rendered within the 3D world. A range of functionalities has been already deployed, and more are being added. We expect to make this

Slices: A Scalable Partitioner for Finite Element Meshes

NASA Technical Reports Server (NTRS)

Ding, H. Q.; Ferraro, R. D.

1995-01-01

A parallel partitioner for partitioning unstructured finite element meshes on distributed memory architectures is developed. The element based partitioner can handle mixtures of different element types. All algorithms adopted in the partitioner are scalable, including a communication template for unpredictable incoming messages, as shown in actual timing measurements.

Visualization of Time-Series Sensor Data to Inform the Design of Just-In-Time Adaptive Stress Interventions.

PubMed

Sharmin, Moushumi; Raij, Andrew; Epstien, David; Nahum-Shani, Inbal; Beck, J Gayle; Vhaduri, Sudip; Preston, Kenzie; Kumar, Santosh

2015-09-01

We investigate needs, challenges, and opportunities in visualizing time-series sensor data on stress to inform the design of just-in-time adaptive interventions (JITAIs). We identify seven key challenges: massive volume and variety of data, complexity in identifying stressors, scalability of space, multifaceted relationship between stress and time, a need for representation at multiple granularities, interperson variability, and limited understanding of JITAI design requirements due to its novelty. We propose four new visualizations based on one million minutes of sensor data (n=70). We evaluate our visualizations with stress researchers (n=6) to gain first insights into its usability and usefulness in JITAI design. Our results indicate that spatio-temporal visualizations help identify and explain between- and within-person variability in stress patterns and contextual visualizations enable decisions regarding the timing, content, and modality of intervention. Interestingly, a granular representation is considered informative but noise-prone; an abstract representation is the preferred starting point for designing JITAIs.

Visualization of Time-Series Sensor Data to Inform the Design of Just-In-Time Adaptive Stress Interventions

PubMed Central

Sharmin, Moushumi; Raij, Andrew; Epstien, David; Nahum-Shani, Inbal; Beck, J. Gayle; Vhaduri, Sudip; Preston, Kenzie; Kumar, Santosh

2015-01-01

We investigate needs, challenges, and opportunities in visualizing time-series sensor data on stress to inform the design of just-in-time adaptive interventions (JITAIs). We identify seven key challenges: massive volume and variety of data, complexity in identifying stressors, scalability of space, multifaceted relationship between stress and time, a need for representation at multiple granularities, interperson variability, and limited understanding of JITAI design requirements due to its novelty. We propose four new visualizations based on one million minutes of sensor data (n=70). We evaluate our visualizations with stress researchers (n=6) to gain first insights into its usability and usefulness in JITAI design. Our results indicate that spatio-temporal visualizations help identify and explain between- and within-person variability in stress patterns and contextual visualizations enable decisions regarding the timing, content, and modality of intervention. Interestingly, a granular representation is considered informative but noise-prone; an abstract representation is the preferred starting point for designing JITAIs. PMID:26539566

Towards Scalable Graph Computation on Mobile Devices.

PubMed

Chen, Yiqi; Lin, Zhiyuan; Pienta, Robert; Kahng, Minsuk; Chau, Duen Horng

2014-10-01

Mobile devices have become increasingly central to our everyday activities, due to their portability, multi-touch capabilities, and ever-improving computational power. Such attractive features have spurred research interest in leveraging mobile devices for computation. We explore a novel approach that aims to use a single mobile device to perform scalable graph computation on large graphs that do not fit in the device's limited main memory, opening up the possibility of performing on-device analysis of large datasets, without relying on the cloud. Based on the familiar memory mapping capability provided by today's mobile operating systems, our approach to scale up computation is powerful and intentionally kept simple to maximize its applicability across the iOS and Android platforms. Our experiments demonstrate that an iPad mini can perform fast computation on large real graphs with as many as 272 million edges (Google+ social graph), at a speed that is only a few times slower than a 13″ Macbook Pro. Through creating a real world iOS app with this technique, we demonstrate the strong potential application for scalable graph computation on a single mobile device using our approach.

Towards Scalable Graph Computation on Mobile Devices

PubMed Central

Chen, Yiqi; Lin, Zhiyuan; Pienta, Robert; Kahng, Minsuk; Chau, Duen Horng

2015-01-01

Mobile devices have become increasingly central to our everyday activities, due to their portability, multi-touch capabilities, and ever-improving computational power. Such attractive features have spurred research interest in leveraging mobile devices for computation. We explore a novel approach that aims to use a single mobile device to perform scalable graph computation on large graphs that do not fit in the device's limited main memory, opening up the possibility of performing on-device analysis of large datasets, without relying on the cloud. Based on the familiar memory mapping capability provided by today's mobile operating systems, our approach to scale up computation is powerful and intentionally kept simple to maximize its applicability across the iOS and Android platforms. Our experiments demonstrate that an iPad mini can perform fast computation on large real graphs with as many as 272 million edges (Google+ social graph), at a speed that is only a few times slower than a 13″ Macbook Pro. Through creating a real world iOS app with this technique, we demonstrate the strong potential application for scalable graph computation on a single mobile device using our approach. PMID:25859564

NPTool: Towards Scalability and Reliability of Business Process Management

NASA Astrophysics Data System (ADS)

Braghetto, Kelly Rosa; Ferreira, João Eduardo; Pu, Calton

Currently one important challenge in business process management is provide at the same time scalability and reliability of business process executions. This difficulty becomes more accentuated when the execution control assumes complex countless business processes. This work presents NavigationPlanTool (NPTool), a tool to control the execution of business processes. NPTool is supported by Navigation Plan Definition Language (NPDL), a language for business processes specification that uses process algebra as formal foundation. NPTool implements the NPDL language as a SQL extension. The main contribution of this paper is a description of the NPTool showing how the process algebra features combined with a relational database model can be used to provide a scalable and reliable control in the execution of business processes. The next steps of NPTool include reuse of control-flow patterns and support to data flow management.

SeqPig: simple and scalable scripting for large sequencing data sets in Hadoop

PubMed Central

Schumacher, André; Pireddu, Luca; Niemenmaa, Matti; Kallio, Aleksi; Korpelainen, Eija; Zanetti, Gianluigi; Heljanko, Keijo

2014-01-01

Summary: Hadoop MapReduce-based approaches have become increasingly popular due to their scalability in processing large sequencing datasets. However, as these methods typically require in-depth expertise in Hadoop and Java, they are still out of reach of many bioinformaticians. To solve this problem, we have created SeqPig, a library and a collection of tools to manipulate, analyze and query sequencing datasets in a scalable and simple manner. SeqPigscripts use the Hadoop-based distributed scripting engine Apache Pig, which automatically parallelizes and distributes data processing tasks. We demonstrate SeqPig’s scalability over many computing nodes and illustrate its use with example scripts. Availability and Implementation: Available under the open source MIT license at http://sourceforge.net/projects/seqpig/ Contact: andre.schumacher@yahoo.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24149054

The OpenEarth Framework (OEF) for the 3D Visualization of Integrated Earth Science Data

NASA Astrophysics Data System (ADS)

Nadeau, David; Moreland, John; Baru, Chaitan; Crosby, Chris

2010-05-01

seismic tomography may be sliced by multiple oriented cutting planes and isosurfaced to create 3D skins that trace feature boundaries within the data. Topography may be overlaid with satellite imagery, maps, and data such as gravity and magnetics measurements. Multiple data sets may be visualized simultaneously using overlapping layers within a common 3D coordinate space. Data management within the OEF handles and hides the inevitable quirks of differing file formats, web protocols, storage structures, coordinate spaces, and metadata representations. Heuristics are used to extract necessary metadata used to guide data and visual operations. Derived data representations are computed to better support fluid interaction and visualization while the original data is left unchanged in its original form. Data is cached for better memory and network efficiency, and all visualization makes use of 3D graphics hardware support found on today's computers. The OpenEarth Framework project is currently prototyping the software for use in the visualization, and integration of continental scale geophysical data being produced by EarthScope-related research in the Western US. The OEF is providing researchers with new ways to display and interrogate their data and is anticipated to be a valuable tool for future EarthScope-related research.

Optimized scalable network switch

DOEpatents

Blumrich, Matthias A [Ridgefield, CT; Chen, Dong [Croton On Hudson, NY; Coteus, Paul W [Yorktown Heights, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Takken, Todd E [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

2007-12-04

In a massively parallel computing system having a plurality of nodes configured in m multi-dimensions, each node including a computing device, a method for routing packets towards their destination nodes is provided which includes generating at least one of a 2m plurality of compact bit vectors containing information derived from downstream nodes. A multilevel arbitration process in which downstream information stored in the compact vectors, such as link status information and fullness of downstream buffers, is used to determine a preferred direction and virtual channel for packet transmission. Preferred direction ranges are encoded and virtual channels are selected by examining the plurality of compact bit vectors. This dynamic routing method eliminates the necessity of routing tables, thus enhancing scalability of the switch.

Optimized scalable network switch

DOEpatents

Blumrich, Matthias A.; Chen, Dong; Coteus, Paul W.

2010-02-23

In a massively parallel computing system having a plurality of nodes configured in m multi-dimensions, each node including a computing device, a method for routing packets towards their destination nodes is provided which includes generating at least one of a 2m plurality of compact bit vectors containing information derived from downstream nodes. A multilevel arbitration process in which downstream information stored in the compact vectors, such as link status information and fullness of downstream buffers, is used to determine a preferred direction and virtual channel for packet transmission. Preferred direction ranges are encoded and virtual channels are selected by examining the plurality of compact bit vectors. This dynamic routing method eliminates the necessity of routing tables, thus enhancing scalability of the switch.

Impact of packet losses in scalable 3D holoscopic video coding

NASA Astrophysics Data System (ADS)

Conti, Caroline; Nunes, Paulo; Ducla Soares, Luís.

2014-05-01

Holoscopic imaging became a prospective glassless 3D technology to provide more natural 3D viewing experiences to the end user. Additionally, holoscopic systems also allow new post-production degrees of freedom, such as controlling the plane of focus or the viewing angle presented to the user. However, to successfully introduce this technology into the consumer market, a display scalable coding approach is essential to achieve backward compatibility with legacy 2D and 3D displays. Moreover, to effectively transmit 3D holoscopic content over error-prone networks, e.g., wireless networks or the Internet, error resilience techniques are required to mitigate the impact of data impairments in the user quality perception. Therefore, it is essential to deeply understand the impact of packet losses in terms of decoding video quality for the specific case of 3D holoscopic content, notably when a scalable approach is used. In this context, this paper studies the impact of packet losses when using a three-layer display scalable 3D holoscopic video coding architecture previously proposed, where each layer represents a different level of display scalability (i.e., L0 - 2D, L1 - stereo or multiview, and L2 - full 3D holoscopic). For this, a simple error concealment algorithm is used, which makes use of inter-layer redundancy between multiview and 3D holoscopic content and the inherent correlation of the 3D holoscopic content to estimate lost data. Furthermore, a study of the influence of 2D views generation parameters used in lower layers on the performance of the used error concealment algorithm is also presented.

WORDGRAPH: Keyword-in-Context Visualization for NETSPEAK's Wildcard Search.

PubMed

Riehmann, Patrick; Gruendl, Henning; Potthast, Martin; Trenkmann, Martin; Stein, Benno; Froehlich, Benno

2012-09-01

The WORDGRAPH helps writers in visually choosing phrases while writing a text. It checks for the commonness of phrases and allows for the retrieval of alternatives by means of wildcard queries. To support such queries, we implement a scalable retrieval engine, which returns high-quality results within milliseconds using a probabilistic retrieval strategy. The results are displayed as WORDGRAPH visualization or as a textual list. The graphical interface provides an effective means for interactive exploration of search results using filter techniques, query expansion, and navigation. Our observations indicate that, of three investigated retrieval tasks, the textual interface is sufficient for the phrase verification task, wherein both interfaces support context-sensitive word choice, and the WORDGRAPH best supports the exploration of a phrase's context or the underlying corpus. Our user study confirms these observations and shows that WORDGRAPH is generally the preferred interface over the textual result list for queries containing multiple wildcards.

Toward Scalable Trustworthy Computing Using the Human-Physiology-Immunity Metaphor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hively, Lee M; Sheldon, Frederick T

The cybersecurity landscape consists of an ad hoc patchwork of solutions. Optimal cybersecurity is difficult for various reasons: complexity, immense data and processing requirements, resource-agnostic cloud computing, practical time-space-energy constraints, inherent flaws in 'Maginot Line' defenses, and the growing number and sophistication of cyberattacks. This article defines the high-priority problems and examines the potential solution space. In that space, achieving scalable trustworthy computing and communications is possible through real-time knowledge-based decisions about cyber trust. This vision is based on the human-physiology-immunity metaphor and the human brain's ability to extract knowledge from data and information. The article outlines future steps towardmore » scalable trustworthy systems requiring a long-term commitment to solve the well-known challenges.« less

Scalable cluster administration - Chiba City I approach and lessons learned.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Navarro, J. P.; Evard, R.; Nurmi, D.

2002-07-01

Systems administrators of large clusters often need to perform the same administrative activity hundreds or thousands of times. Often such activities are time-consuming, especially the tasks of installing and maintaining software. By combining network services such as DHCP, TFTP, FTP, HTTP, and NFS with remote hardware control, cluster administrators can automate all administrative tasks. Scalable cluster administration addresses the following challenge: What systems design techniques can cluster builders use to automate cluster administration on very large clusters? We describe the approach used in the Mathematics and Computer Science Division of Argonne National Laboratory on Chiba City I, a 314-node Linuxmore » cluster; and we analyze the scalability, flexibility, and reliability benefits and limitations from that approach.« less

On scalable lossless video coding based on sub-pixel accurate MCTF

NASA Astrophysics Data System (ADS)

Yea, Sehoon; Pearlman, William A.

2006-01-01

We propose two approaches to scalable lossless coding of motion video. They achieve SNR-scalable bitstream up to lossless reconstruction based upon the subpixel-accurate MCTF-based wavelet video coding. The first approach is based upon a two-stage encoding strategy where a lossy reconstruction layer is augmented by a following residual layer in order to obtain (nearly) lossless reconstruction. The key advantages of our approach include an 'on-the-fly' determination of bit budget distribution between the lossy and the residual layers, freedom to use almost any progressive lossy video coding scheme as the first layer and an added feature of near-lossless compression. The second approach capitalizes on the fact that we can maintain the invertibility of MCTF with an arbitrary sub-pixel accuracy even in the presence of an extra truncation step for lossless reconstruction thanks to the lifting implementation. Experimental results show that the proposed schemes achieve compression ratios not obtainable by intra-frame coders such as Motion JPEG-2000 thanks to their inter-frame coding nature. Also they are shown to outperform the state-of-the-art non-scalable inter-frame coder H.264 (JM) lossless mode, with the added benefit of bitstream embeddedness.

A repeatable and scalable fabrication method for sharp, hollow silicon microneedles

NASA Astrophysics Data System (ADS)

Kim, H.; Theogarajan, L. S.; Pennathur, S.

2018-03-01

Scalability and manufacturability are impeding the mass commercialization of microneedles in the medical field. Specifically, microneedle geometries need to be sharp, beveled, and completely controllable, difficult to achieve with microelectromechanical fabrication techniques. In this work, we performed a parametric study using silicon etch chemistries to optimize the fabrication of scalable and manufacturable beveled silicon hollow microneedles. We theoretically verified our parametric results with diffusion reaction equations and created a design guideline for a various set of miconeedles (80-160 µm needle base width, 100-1000 µm pitch, 40-50 µm inner bore diameter, and 150-350 µm height) to show the repeatability, scalability, and manufacturability of our process. As a result, hollow silicon microneedles with any dimensions can be fabricated with less than 2% non-uniformity across a wafer and 5% deviation between different processes. The key to achieving such high uniformity and consistency is a non-agitated HF-HNO3 bath, silicon nitride masks, and surrounding silicon filler materials with well-defined dimensions. Our proposed method is non-labor intensive, well defined by theory, and straightforward for wafer scale mass production, opening doors to a plethora of potential medical and biosensing applications.

A Real-time 3D Visualization of Global MHD Simulation for Space Weather Forecasting

NASA Astrophysics Data System (ADS)

Murata, K.; Matsuoka, D.; Kubo, T.; Shimazu, H.; Tanaka, T.; Fujita, S.; Watari, S.; Miyachi, H.; Yamamoto, K.; Kimura, E.; Ishikura, S.

2006-12-01

Recently, many satellites for communication networks and scientific observation are launched in the vicinity of the Earth (geo-space). The electromagnetic (EM) environments around the spacecraft are always influenced by the solar wind blowing from the Sun and induced electromagnetic fields. They occasionally cause various troubles or damages, such as electrification and interference, to the spacecraft. It is important to forecast the geo-space EM environment as well as the ground weather forecasting. Owing to the recent remarkable progresses of super-computer technologies, numerical simulations have become powerful research methods in the solar-terrestrial physics. For the necessity of space weather forecasting, NICT (National Institute of Information and Communications Technology) has developed a real-time global MHD simulation system of solar wind-magnetosphere-ionosphere couplings, which has been performed on a super-computer SX-6. The real-time solar wind parameters from the ACE spacecraft at every one minute are adopted as boundary conditions for the simulation. Simulation results (2-D plots) are updated every 1 minute on a NICT website. However, 3D visualization of simulation results is indispensable to forecast space weather more accurately. In the present study, we develop a real-time 3D webcite for the global MHD simulations. The 3-D visualization results of simulation results are updated every 20 minutes in the following three formats: (1)Streamlines of magnetic field lines, (2)Isosurface of temperature in the magnetosphere and (3)Isoline of conductivity and orthogonal plane of potential in the ionosphere. For the present study, we developed a 3-D viewer application working on Internet Explorer browser (ActiveX) is implemented, which was developed on the AVS/Express. Numerical data are saved in the HDF5 format data files every 1 minute. Users can easily search, retrieve and plot past simulation results (3D visualization data and numerical data) by using

Fabrication of Scalable Indoor Light Energy Harvester and Study for Agricultural IoT Applications

NASA Astrophysics Data System (ADS)

Watanabe, M.; Nakamura, A.; Kunii, A.; Kusano, K.; Futagawa, M.

2015-12-01

A scalable indoor light energy harvester was fabricated by microelectromechanical system (MEMS) and printing hybrid technology and evaluated for agricultural IoT applications under different environmental input power density conditions, such as outdoor farming under the sun, greenhouse farming under scattered lighting, and a plant factory under LEDs. We fabricated and evaluated a dye- sensitized-type solar cell (DSC) as a low cost and “scalable” optical harvester device. We developed a transparent conductive oxide (TCO)-less process with a honeycomb metal mesh substrate fabricated by MEMS technology. In terms of the electrical and optical properties, we achieved scalable harvester output power by cell area sizing. Second, we evaluated the dependence of the input power scalable characteristics on the input light intensity, spectrum distribution, and light inlet direction angle, because harvested environmental input power is unstable. The TiO2 fabrication relied on nanoimprint technology, which was designed for optical optimization and fabrication, and we confirmed that the harvesters are robust to a variety of environments. Finally, we studied optical energy harvesting applications for agricultural IoT systems. These scalable indoor light harvesters could be used in many applications and situations in smart agriculture.

OligoIS: Scalable Instance Selection for Class-Imbalanced Data Sets.

PubMed

García-Pedrajas, Nicolás; Perez-Rodríguez, Javier; de Haro-García, Aida

2013-02-01

In current research, an enormous amount of information is constantly being produced, which poses a challenge for data mining algorithms. Many of the problems in extremely active research areas, such as bioinformatics, security and intrusion detection, or text mining, share the following two features: large data sets and class-imbalanced distribution of samples. Although many methods have been proposed for dealing with class-imbalanced data sets, most of these methods are not scalable to the very large data sets common to those research fields. In this paper, we propose a new approach to dealing with the class-imbalance problem that is scalable to data sets with many millions of instances and hundreds of features. This proposal is based on the divide-and-conquer principle combined with application of the selection process to balanced subsets of the whole data set. This divide-and-conquer principle allows the execution of the algorithm in linear time. Furthermore, the proposed method is easy to implement using a parallel environment and can work without loading the whole data set into memory. Using 40 class-imbalanced medium-sized data sets, we will demonstrate our method's ability to improve the results of state-of-the-art instance selection methods for class-imbalanced data sets. Using three very large data sets, we will show the scalability of our proposal to millions of instances and hundreds of features.

Parallel scalability and efficiency of vortex particle method for aeroelasticity analysis of bluff bodies

NASA Astrophysics Data System (ADS)

Tolba, Khaled Ibrahim; Morgenthal, Guido

2018-01-01

This paper presents an analysis of the scalability and efficiency of a simulation framework based on the vortex particle method. The code is applied for the numerical aerodynamic analysis of line-like structures. The numerical code runs on multicore CPU and GPU architectures using OpenCL framework. The focus of this paper is the analysis of the parallel efficiency and scalability of the method being applied to an engineering test case, specifically the aeroelastic response of a long-span bridge girder at the construction stage. The target is to assess the optimal configuration and the required computer architecture, such that it becomes feasible to efficiently utilise the method within the computational resources available for a regular engineering office. The simulations and the scalability analysis are performed on a regular gaming type computer.

A scalable infrastructure for CMS data analysis based on OpenStack Cloud and Gluster file system

NASA Astrophysics Data System (ADS)

Toor, S.; Osmani, L.; Eerola, P.; Kraemer, O.; Lindén, T.; Tarkoma, S.; White, J.

2014-06-01

The challenge of providing a resilient and scalable computational and data management solution for massive scale research environments requires continuous exploration of new technologies and techniques. In this project the aim has been to design a scalable and resilient infrastructure for CERN HEP data analysis. The infrastructure is based on OpenStack components for structuring a private Cloud with the Gluster File System. We integrate the state-of-the-art Cloud technologies with the traditional Grid middleware infrastructure. Our test results show that the adopted approach provides a scalable and resilient solution for managing resources without compromising on performance and high availability.

Scalable Planning and Learning for Multiagent POMDPs

DTIC Science & Technology

2015-01-01

Scalable Planning and Learning for Multiagent POMDPs Christopher Amato CSAIL, MIT Cambridge, MA 02139 camato@csail.mit.edu Frans A. Oliehoek...state of a special POMDP, called a BA- POMDP. The BA-POMDP can be extended to the multiagent setting ( Amato and Oliehoek 2013), yielding the Bayes...2012; Amato et al. 2013) in the form of factored Dec-POMDPs (Oliehoek, Whiteson, and Spaan 2013; Pajarinen and Pel- tonen 2011) and networked

Heat-treated stainless steel felt as scalable anode material for bioelectrochemical systems.

PubMed

Guo, Kun; Soeriyadi, Alexander H; Feng, Huajun; Prévoteau, Antonin; Patil, Sunil A; Gooding, J Justin; Rabaey, Korneel

2015-11-01

This work reports a simple and scalable method to convert stainless steel (SS) felt into an effective anode for bioelectrochemical systems (BESs) by means of heat treatment. X-ray photoelectron spectroscopy and cyclic voltammetry elucidated that the heat treatment generated an iron oxide rich layer on the SS felt surface. The iron oxide layer dramatically enhanced the electroactive biofilm formation on SS felt surface in BESs. Consequently, the sustained current densities achieved on the treated electrodes (1 cm(2)) were around 1.5±0.13 mA/cm(2), which was seven times higher than the untreated electrodes (0.22±0.04 mA/cm(2)). To test the scalability of this material, the heat-treated SS felt was scaled up to 150 cm(2) and similar current density (1.5 mA/cm(2)) was achieved on the larger electrode. The low cost, straightforwardness of the treatment, high conductivity and high bioelectrocatalytic performance make heat-treated SS felt a scalable anodic material for BESs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Engineering scalable biological systems

PubMed Central

2010-01-01

Synthetic biology is focused on engineering biological organisms to study natural systems and to provide new solutions for pressing medical, industrial and environmental problems. At the core of engineered organisms are synthetic biological circuits that execute the tasks of sensing inputs, processing logic and performing output functions. In the last decade, significant progress has been made in developing basic designs for a wide range of biological circuits in bacteria, yeast and mammalian systems. However, significant challenges in the construction, probing, modulation and debugging of synthetic biological systems must be addressed in order to achieve scalable higher-complexity biological circuits. Furthermore, concomitant efforts to evaluate the safety and biocontainment of engineered organisms and address public and regulatory concerns will be necessary to ensure that technological advances are translated into real-world solutions. PMID:21468204

Intelligent video storage of visual evidences on site in fast deployment

NASA Astrophysics Data System (ADS)

Desurmont, Xavier; Bastide, Arnaud; Delaigle, Jean-Francois

2004-07-01

In this article we present a generic, flexible, scalable and robust approach for an intelligent real-time forensic visual system. The proposed implementation could be rapidly deployable and integrates minimum logistic support as it embeds low complexity devices (PCs and cameras) that communicate through wireless network. The goal of these advanced tools is to provide intelligent video storage of potential video evidences for fast intervention during deployment around a hazardous sector after a terrorism attack, a disaster, an air crash or before attempt of it. Advanced video analysis tools, such as segmentation and tracking are provided to support intelligent storage and annotation.

Scalable load balancing for massively parallel distributed Monte Carlo particle transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Brien, M. J.; Brantley, P. S.; Joy, K. I.

2013-07-01

In order to run computer simulations efficiently on massively parallel computers with hundreds of thousands or millions of processors, care must be taken that the calculation is load balanced across the processors. Examining the workload of every processor leads to an unscalable algorithm, with run time at least as large as O(N), where N is the number of processors. We present a scalable load balancing algorithm, with run time 0(log(N)), that involves iterated processor-pair-wise balancing steps, ultimately leading to a globally balanced workload. We demonstrate scalability of the algorithm up to 2 million processors on the Sequoia supercomputer at Lawrencemore » Livermore National Laboratory. (authors)« less

Scalability of transport parameters with pore sizes in isodense disordered media

NASA Astrophysics Data System (ADS)

Reginald, S. William; Schmitt, V.; Vallée, R. A. L.

2014-09-01

We study light multiple scattering in complex disordered porous materials. High internal phase emulsion-based isodense polystyrene foams are designed. Two types of samples, exhibiting different pore size distributions, are investigated for different slab thicknesses varying from L = 1 \\text{mm} to 10 \\text{mm} . Optical measurements combining steady-state and time-resolved detection are used to characterize the photon transport parameters. Very interestingly, a clear scalability of the transport mean free path \\ellt with the average size of the pores S is observed, featuring a constant velocity of the transport energy in these isodense structures. This study strongly motivates further investigations into the limits of validity of this scalability as the scattering strength of the system increases.

Efficient and Scalable Graph Similarity Joins in MapReduce

PubMed Central

Chen, Yifan; Zhang, Weiming; Tang, Jiuyang

2014-01-01

Along with the emergence of massive graph-modeled data, it is of great importance to investigate graph similarity joins due to their wide applications for multiple purposes, including data cleaning, and near duplicate detection. This paper considers graph similarity joins with edit distance constraints, which return pairs of graphs such that their edit distances are no larger than a given threshold. Leveraging the MapReduce programming model, we propose MGSJoin, a scalable algorithm following the filtering-verification framework for efficient graph similarity joins. It relies on counting overlapping graph signatures for filtering out nonpromising candidates. With the potential issue of too many key-value pairs in the filtering phase, spectral Bloom filters are introduced to reduce the number of key-value pairs. Furthermore, we integrate the multiway join strategy to boost the verification, where a MapReduce-based method is proposed for GED calculation. The superior efficiency and scalability of the proposed algorithms are demonstrated by extensive experimental results. PMID:25121135

Efficient and scalable graph similarity joins in MapReduce.

PubMed

Chen, Yifan; Zhao, Xiang; Xiao, Chuan; Zhang, Weiming; Tang, Jiuyang

2014-01-01

Along with the emergence of massive graph-modeled data, it is of great importance to investigate graph similarity joins due to their wide applications for multiple purposes, including data cleaning, and near duplicate detection. This paper considers graph similarity joins with edit distance constraints, which return pairs of graphs such that their edit distances are no larger than a given threshold. Leveraging the MapReduce programming model, we propose MGSJoin, a scalable algorithm following the filtering-verification framework for efficient graph similarity joins. It relies on counting overlapping graph signatures for filtering out nonpromising candidates. With the potential issue of too many key-value pairs in the filtering phase, spectral Bloom filters are introduced to reduce the number of key-value pairs. Furthermore, we integrate the multiway join strategy to boost the verification, where a MapReduce-based method is proposed for GED calculation. The superior efficiency and scalability of the proposed algorithms are demonstrated by extensive experimental results.

Scalable parallel distance field construction for large-scale applications

DOE PAGES

Yu, Hongfeng; Xie, Jinrong; Ma, Kwan -Liu; ...

2015-10-01

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. Anew distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking overtime, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate itsmore » efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. In conclusion, our work greatly extends the usability of distance fields for demanding applications.« less

Scalable Parallel Distance Field Construction for Large-Scale Applications.

PubMed

Yu, Hongfeng; Xie, Jinrong; Ma, Kwan-Liu; Kolla, Hemanth; Chen, Jacqueline H

2015-10-01

Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. A new distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking over time, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate its efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. Our work greatly extends the usability of distance fields for demanding applications.

Scalable Unix tools on parallel processors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gropp, W.; Lusk, E.

1994-12-31

The introduction of parallel processors that run a separate copy of Unix on each process has introduced new problems in managing the user`s environment. This paper discusses some generalizations of common Unix commands for managing files (e.g. 1s) and processes (e.g. ps) that are convenient and scalable. These basic tools, just like their Unix counterparts, are text-based. We also discuss a way to use these with a graphical user interface (GUI). Some notes on the implementation are provided. Prototypes of these commands are publicly available.

Scalable descriptive and correlative statistics with Titan.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, David C.; Pebay, Philippe Pierre

This report summarizes the existing statistical engines in VTK/Titan and presents the parallel versions thereof which have already been implemented. The ease of use of these parallel engines is illustrated by the means of C++ code snippets. Furthermore, this report justifies the design of these engines with parallel scalability in mind; then, this theoretical property is verified with test runs that demonstrate optimal parallel speed-up with up to 200 processors.

Estimates of the Sampling Distribution of Scalability Coefficient H

ERIC Educational Resources Information Center

Van Onna, Marieke J. H.

2004-01-01

Coefficient "H" is used as an index of scalability in nonparametric item response theory (NIRT). It indicates the degree to which a set of items rank orders examinees. Theoretical sampling distributions, however, have only been derived asymptotically and only under restrictive conditions. Bootstrap methods offer an alternative possibility to…

Scalability improvements to NRLMOL for DFT calculations of large molecules

NASA Astrophysics Data System (ADS)

Diaz, Carlos Manuel

Advances in high performance computing (HPC) have provided a way to treat large, computationally demanding tasks using thousands of processors. With the development of more powerful HPC architectures, the need to create efficient and scalable code has grown more important. Electronic structure calculations are valuable in understanding experimental observations and are routinely used for new materials predictions. For the electronic structure calculations, the memory and computation time are proportional to the number of atoms. Memory requirements for these calculations scale as N2, where N is the number of atoms. While the recent advances in HPC offer platforms with large numbers of cores, the limited amount of memory available on a given node and poor scalability of the electronic structure code hinder their efficient usage of these platforms. This thesis will present some developments to overcome these bottlenecks in order to study large systems. These developments, which are implemented in the NRLMOL electronic structure code, involve the use of sparse matrix storage formats and the use of linear algebra using sparse and distributed matrices. These developments along with other related development now allow ground state density functional calculations using up to 25,000 basis functions and the excited state calculations using up to 17,000 basis functions while utilizing all cores on a node. An example on a light-harvesting triad molecule is described. Finally, future plans to further improve the scalability will be presented.

LoRa Scalability: A Simulation Model Based on Interference Measurements.

PubMed

Haxhibeqiri, Jetmir; Van den Abeele, Floris; Moerman, Ingrid; Hoebeke, Jeroen

2017-05-23

LoRa is a long-range, low power, low bit rate and single-hop wireless communication technology. It is intended to be used in Internet of Things (IoT) applications involving battery-powered devices with low throughput requirements. A LoRaWAN network consists of multiple end nodes that communicate with one or more gateways. These gateways act like a transparent bridge towards a common network server. The amount of end devices and their throughput requirements will have an impact on the performance of the LoRaWAN network. This study investigates the scalability in terms of the number of end devices per gateway of single-gateway LoRaWAN deployments. First, we determine the intra-technology interference behavior with two physical end nodes, by checking the impact of an interfering node on a transmitting node. Measurements show that even under concurrent transmission, one of the packets can be received under certain conditions. Based on these measurements, we create a simulation model for assessing the scalability of a single gateway LoRaWAN network. We show that when the number of nodes increases up to 1000 per gateway, the losses will be up to 32%. In such a case, pure Aloha will have around 90% losses. However, when the duty cycle of the application layer becomes lower than the allowed radio duty cycle of 1%, losses will be even lower. We also show network scalability simulation results for some IoT use cases based on real data.

Scalable Performance Measurement and Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gamblin, Todd

2009-01-01

Concurrency levels in large-scale, distributed-memory supercomputers are rising exponentially. Modern machines may contain 100,000 or more microprocessor cores, and the largest of these, IBM's Blue Gene/L, contains over 200,000 cores. Future systems are expected to support millions of concurrent tasks. In this dissertation, we focus on efficient techniques for measuring and analyzing the performance of applications running on very large parallel machines. Tuning the performance of large-scale applications can be a subtle and time-consuming task because application developers must measure and interpret data from many independent processes. While the volume of the raw data scales linearly with the number ofmore » tasks in the running system, the number of tasks is growing exponentially, and data for even small systems quickly becomes unmanageable. Transporting performance data from so many processes over a network can perturb application performance and make measurements inaccurate, and storing such data would require a prohibitive amount of space. Moreover, even if it were stored, analyzing the data would be extremely time-consuming. In this dissertation, we present novel methods for reducing performance data volume. The first draws on multi-scale wavelet techniques from signal processing to compress systemwide, time-varying load-balance data. The second uses statistical sampling to select a small subset of running processes to generate low-volume traces. A third approach combines sampling and wavelet compression to stratify performance data adaptively at run-time and to reduce further the cost of sampled tracing. We have integrated these approaches into Libra, a toolset for scalable load-balance analysis. We present Libra and show how it can be used to analyze data from large scientific applications scalably.« less

Scalable Light Module for Low-Cost, High-Efficiency Light- Emitting Diode Luminaires

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tarsa, Eric

2015-08-31

During this two-year program Cree developed a scalable, modular optical architecture for low-cost, high-efficacy light emitting diode (LED) luminaires. Stated simply, the goal of this architecture was to efficiently and cost-effectively convey light from LEDs (point sources) to broad luminaire surfaces (area sources). By simultaneously developing warm-white LED components and low-cost, scalable optical elements, a high system optical efficiency resulted. To meet program goals, Cree evaluated novel approaches to improve LED component efficacy at high color quality while not sacrificing LED optical efficiency relative to conventional packages. Meanwhile, efficiently coupling light from LEDs into modular optical elements, followed by optimallymore » distributing and extracting this light, were challenges that were addressed via novel optical design coupled with frequent experimental evaluations. Minimizing luminaire bill of materials and assembly costs were two guiding principles for all design work, in the effort to achieve luminaires with significantly lower normalized cost ($/klm) than existing LED fixtures. Chief project accomplishments included the achievement of >150 lm/W warm-white LEDs having primary optics compatible with low-cost modular optical elements. In addition, a prototype Light Module optical efficiency of over 90% was measured, demonstrating the potential of this scalable architecture for ultra-high-efficacy LED luminaires. Since the project ended, Cree has continued to evaluate optical element fabrication and assembly methods in an effort to rapidly transfer this scalable, cost-effective technology to Cree production development groups. The Light Module concept is likely to make a strong contribution to the development of new cost-effective, high-efficacy luminaries, thereby accelerating widespread adoption of energy-saving SSL in the U.S.« less

Improved inter-layer prediction for light field content coding with display scalability

NASA Astrophysics Data System (ADS)

Conti, Caroline; Ducla Soares, Luís.; Nunes, Paulo

2016-09-01

Light field imaging based on microlens arrays - also known as plenoptic, holoscopic and integral imaging - has recently risen up as feasible and prospective technology due to its ability to support functionalities not straightforwardly available in conventional imaging systems, such as: post-production refocusing and depth of field changing. However, to gradually reach the consumer market and to provide interoperability with current 2D and 3D representations, a display scalable coding solution is essential. In this context, this paper proposes an improved display scalable light field codec comprising a three-layer hierarchical coding architecture (previously proposed by the authors) that provides interoperability with 2D (Base Layer) and 3D stereo and multiview (First Layer) representations, while the Second Layer supports the complete light field content. For further improving the compression performance, novel exemplar-based inter-layer coding tools are proposed here for the Second Layer, namely: (i) an inter-layer reference picture construction relying on an exemplar-based optimization algorithm for texture synthesis, and (ii) a direct prediction mode based on exemplar texture samples from lower layers. Experimental results show that the proposed solution performs better than the tested benchmark solutions, including the authors' previous scalable codec.

Air-stable ink for scalable, high-throughput layer deposition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weil, Benjamin D; Connor, Stephen T; Cui, Yi

A method for producing and depositing air-stable, easily decomposable, vulcanized ink on any of a wide range of substrates is disclosed. The ink enables high-volume production of optoelectronic and/or electronic devices using scalable production methods, such as roll-to-roll transfer, fast rolling processes, and the like.

Scalability Assessments for the Malicious Activity Simulation Tool (MAST)

DTIC Science & Technology

2012-09-01

the scalability characteristics of MAST. Specifically, we show that an exponential increase in clients using the MAST software does not impact...an exponential increase in clients using the MAST software does not impact network and system resources significantly. Additionally, we...31 1. Hardware .....................................31 2. Software .....................................32 3. Common PC

Efficient and scalable ionization of neutral atoms by an orderly array of gold-doped silicon nanowires

NASA Astrophysics Data System (ADS)

Bucay, Igal; Helal, Ahmed; Dunsky, David; Leviyev, Alex; Mallavarapu, Akhila; Sreenivasan, S. V.; Raizen, Mark

2017-04-01

Ionization of atoms and molecules is an important process in many applications and processes such as mass spectrometry. Ionization is typically accomplished by electron bombardment, and while it is scalable to large volumes, is also very inefficient due to the small cross section of electron-atom collisions. Photoionization methods can be highly efficient, but are not scalable due to the small ionization volume. Electric field ionization is accomplished using ultra-sharp conducting tips biased to a few kilovolts, but suffers from a low ionization volume and tip fabrication limitations. We report on our progress towards an efficient, robust, and scalable method of atomic and molecular ionization using orderly arrays of sharp, gold-doped silicon nanowires. As demonstrated in earlier work, the presence of the gold greatly enhances the ionization probability, which was attributed to an increase in available acceptor surface states. We present here a novel process used to fabricate the nanowire array, results of simulations aimed at optimizing the configuration of the array, and our progress towards demonstrating efficient and scalable ionization.

Cheetah: A Framework for Scalable Hierarchical Collective Operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graham, Richard L; Gorentla Venkata, Manjunath; Ladd, Joshua S

2011-01-01

Collective communication operations, used by many scientific applications, tend to limit overall parallel application performance and scalability. Computer systems are becoming more heterogeneous with increasing node and core-per-node counts. Also, a growing number of data-access mechanisms, of varying characteristics, are supported within a single computer system. We describe a new hierarchical collective communication framework that takes advantage of hardware-specific data-access mechanisms. It is flexible, with run-time hierarchy specification, and sharing of collective communication primitives between collective algorithms. Data buffers are shared between levels in the hierarchy reducing collective communication management overhead. We have implemented several versions of the Message Passingmore » Interface (MPI) collective operations, MPI Barrier() and MPI Bcast(), and run experiments using up to 49, 152 processes on a Cray XT5, and a small InfiniBand based cluster. At 49, 152 processes our barrier implementation outperforms the optimized native implementation by 75%. 32 Byte and one Mega-Byte broadcasts outperform it by 62% and 11%, respectively, with better scalability characteristics. Improvements relative to the default Open MPI implementation are much larger.« less

Scalable tuning of building models to hourly data

DOE PAGES

Garrett, Aaron; New, Joshua Ryan

2015-03-31

Energy models of existing buildings are unreliable unless calibrated so they correlate well with actual energy usage. Manual tuning requires a skilled professional, is prohibitively expensive for small projects, imperfect, non-repeatable, non-transferable, and not scalable to the dozens of sensor channels that smart meters, smart appliances, and cheap/ubiquitous sensors are beginning to make available today. A scalable, automated methodology is needed to quickly and intelligently calibrate building energy models to all available data, increase the usefulness of those models, and facilitate speed-and-scale penetration of simulation-based capabilities into the marketplace for actualized energy savings. The "Autotune'' project is a novel, model-agnosticmore » methodology which leverages supercomputing, large simulation ensembles, and big data mining with multiple machine learning algorithms to allow automatic calibration of simulations that match measured experimental data in a way that is deployable on commodity hardware. This paper shares several methodologies employed to reduce the combinatorial complexity to a computationally tractable search problem for hundreds of input parameters. Furthermore, accuracy metrics are provided which quantify model error to measured data for either monthly or hourly electrical usage from a highly-instrumented, emulated-occupancy research home.« less

Scalable Multiprocessor for High-Speed Computing in Space

NASA Technical Reports Server (NTRS)

Lux, James; Lang, Minh; Nishimoto, Kouji; Clark, Douglas; Stosic, Dorothy; Bachmann, Alex; Wilkinson, William; Steffke, Richard

2004-01-01

A report discusses the continuing development of a scalable multiprocessor computing system for hard real-time applications aboard a spacecraft. "Hard realtime applications" signifies applications, like real-time radar signal processing, in which the data to be processed are generated at "hundreds" of pulses per second, each pulse "requiring" millions of arithmetic operations. In these applications, the digital processors must be tightly integrated with analog instrumentation (e.g., radar equipment), and data input/output must be synchronized with analog instrumentation, controlled to within fractions of a microsecond. The scalable multiprocessor is a cluster of identical commercial-off-the-shelf generic DSP (digital-signal-processing) computers plus generic interface circuits, including analog-to-digital converters, all controlled by software. The processors are computers interconnected by high-speed serial links. Performance can be increased by adding hardware modules and correspondingly modifying the software. Work is distributed among the processors in a parallel or pipeline fashion by means of a flexible master/slave control and timing scheme. Each processor operates under its own local clock; synchronization is achieved by broadcasting master time signals to all the processors, which compute offsets between the master clock and their local clocks.

NASA's Global Imagery Browse Services - Technologies for Visualizing Earth Science Data

NASA Astrophysics Data System (ADS)

Cechini, M. F.; Boller, R. A.; Baynes, K.; Schmaltz, J. E.; Thompson, C. K.; Roberts, J. T.; Rodriguez, J.; Wong, M. M.; King, B. A.; King, J.; De Luca, A. P.; Pressley, N. N.

2017-12-01

For more than 20 years, the NASA Earth Observing System (EOS) has collected earth science data for thousands of scientific parameters now totaling nearly 15 Petabytes of data. In 2013, NASA's Global Imagery Browse Services (GIBS) formed its vision to "transform how end users interact and discover [EOS] data through visualizations." This vision included leveraging scientific and community best practices and standards to provide a scalable, compliant, and authoritative source for EOS earth science data visualizations. Since that time, GIBS has grown quickly and now services millions of daily requests for over 500 imagery layers representing hundreds of earth science parameters to a broad community of users. For many of these parameters, visualizations are available within hours of acquisition from the satellite. For others, visualizations are available for the entire mission of the satellite. The GIBS system is built upon the OnEarth and MRF open source software projects, which are provided by the GIBS team. This software facilitates standards-based access for compliance with existing GIS tools. The GIBS imagery layers are predominantly rasterized images represented in two-dimensional coordinate systems, though multiple projections are supported. The OnEarth software also supports the GIBS ingest pipeline to facilitate low latency updates to new or updated visualizations. This presentation will focus on the following topics: Overview of GIBS visualizations and user community Current benefits and limitations of the OnEarth and MRF software projects and related standards GIBS access methods and their in/compatibilities with existing GIS libraries and applications Considerations for visualization accuracy and understandability Future plans for more advanced visualization concepts including Vertical Profiles and Vector-Based Representations Future plans for Amazon Web Service support and deployments

Scalable SCPPM Decoder

NASA Technical Reports Server (NTRS)

Quir, Kevin J.; Gin, Jonathan W.; Nguyen, Danh H.; Nguyen, Huy; Nakashima, Michael A.; Moision, Bruce E.

2012-01-01

A decoder was developed that decodes a serial concatenated pulse position modulation (SCPPM) encoded information sequence. The decoder takes as input a sequence of four bit log-likelihood ratios (LLR) for each PPM slot in a codeword via a XAUI 10-Gb/s quad optical fiber interface. If the decoder is unavailable, it passes the LLRs on to the next decoder via a XAUI 10-Gb/s quad optical fiber interface. Otherwise, it decodes the sequence and outputs information bits through a 1-GB/s Ethernet UDP/IP (User Datagram Protocol/Internet Protocol) interface. The throughput for a single decoder unit is 150-Mb/s at an average of four decoding iterations; by connecting a number of decoder units in series, a decoding rate equal to that of the aggregate rate is achieved. The unit is controlled through a 1-GB/s Ethernet UDP/IP interface. This ground station decoder was developed to demonstrate a deep space optical communication link capability, and is unique in the scalable design to achieve real-time SCPP decoding at the aggregate data rate.

Scalable Anonymous Group Communication in the Anytrust Model

DTIC Science & Technology

2012-04-10

Scalable Anonymous Group Communication in the Anytrust Model David Isaac Wolinsky, Henry Corrigan-Gibbs, and Bryan Ford Yale University...12th KDD, Aug. 2006. [10] D. Chaum . Untraceable electronic mail, return addresses, and digital pseudonyms. Communications of the ACM, 24(2), Feb...1981. [11] D. Chaum . The dining cryptographers problem: Unconditional sender and recipient untraceability. Journal of Cryptology, 1(1):65–75, Jan. 1988

SVGenes: a library for rendering genomic features in scalable vector graphic format.

PubMed

Etherington, Graham J; MacLean, Daniel

2013-08-01

Drawing genomic features in attractive and informative ways is a key task in visualization of genomics data. Scalable Vector Graphics (SVG) format is a modern and flexible open standard that provides advanced features including modular graphic design, advanced web interactivity and animation within a suitable client. SVGs do not suffer from loss of image quality on re-scaling and provide the ability to edit individual elements of a graphic on the whole object level independent of the whole image. These features make SVG a potentially useful format for the preparation of publication quality figures including genomic objects such as genes or sequencing coverage and for web applications that require rich user-interaction with the graphical elements. SVGenes is a Ruby-language library that uses SVG primitives to render typical genomic glyphs through a simple and flexible Ruby interface. The library implements a simple Page object that spaces and contains horizontal Track objects that in turn style, colour and positions features within them. Tracks are the level at which visual information is supplied providing the full styling capability of the SVG standard. Genomic entities like genes, transcripts and histograms are modelled in Glyph objects that are attached to a track and take advantage of SVG primitives to render the genomic features in a track as any of a selection of defined glyphs. The feature model within SVGenes is simple but flexible and not dependent on particular existing gene feature formats meaning graphics for any existing datasets can easily be created without need for conversion. The library is provided as a Ruby Gem from https://rubygems.org/gems/bio-svgenes under the MIT license, and open source code is available at https://github.com/danmaclean/bioruby-svgenes also under the MIT License. dan.maclean@tsl.ac.uk.

Tip-Based Nanofabrication for Scalable Manufacturing

DOE PAGES

Hu, Huan; Kim, Hoe; Somnath, Suhas

2017-03-16

Tip-based nanofabrication (TBN) is a family of emerging nanofabrication techniques that use a nanometer scale tip to fabricate nanostructures. Here in this review, we first introduce the history of the TBN and the technology development. We then briefly review various TBN techniques that use different physical or chemical mechanisms to fabricate features and discuss some of the state-of-the-art techniques. Subsequently, we focus on those TBN methods that have demonstrated potential to scale up the manufacturing throughput. Finally, we discuss several research directions that are essential for making TBN a scalable nano-manufacturing technology.

Tip-Based Nanofabrication for Scalable Manufacturing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Huan; Kim, Hoe; Somnath, Suhas

Tip-based nanofabrication (TBN) is a family of emerging nanofabrication techniques that use a nanometer scale tip to fabricate nanostructures. Here in this review, we first introduce the history of the TBN and the technology development. We then briefly review various TBN techniques that use different physical or chemical mechanisms to fabricate features and discuss some of the state-of-the-art techniques. Subsequently, we focus on those TBN methods that have demonstrated potential to scale up the manufacturing throughput. Finally, we discuss several research directions that are essential for making TBN a scalable nano-manufacturing technology.

A generic, cost-effective, and scalable cell lineage analysis platform

PubMed Central

Biezuner, Tamir; Spiro, Adam; Raz, Ofir; Amir, Shiran; Milo, Lilach; Adar, Rivka; Chapal-Ilani, Noa; Berman, Veronika; Fried, Yael; Ainbinder, Elena; Cohen, Galit; Barr, Haim M.; Halaban, Ruth; Shapiro, Ehud

2016-01-01

Advances in single-cell genomics enable commensurate improvements in methods for uncovering lineage relations among individual cells. Current sequencing-based methods for cell lineage analysis depend on low-resolution bulk analysis or rely on extensive single-cell sequencing, which is not scalable and could be biased by functional dependencies. Here we show an integrated biochemical-computational platform for generic single-cell lineage analysis that is retrospective, cost-effective, and scalable. It consists of a biochemical-computational pipeline that inputs individual cells, produces targeted single-cell sequencing data, and uses it to generate a lineage tree of the input cells. We validated the platform by applying it to cells sampled from an ex vivo grown tree and analyzed its feasibility landscape by computer simulations. We conclude that the platform may serve as a generic tool for lineage analysis and thus pave the way toward large-scale human cell lineage discovery. PMID:27558250

New Algorithm and Software (BNOmics) for Inferring and Visualizing Bayesian Networks from Heterogeneous Big Biological and Genetic Data

PubMed Central

Gogoshin, Grigoriy; Boerwinkle, Eric

2017-01-01

Abstract Bayesian network (BN) reconstruction is a prototypical systems biology data analysis approach that has been successfully used to reverse engineer and model networks reflecting different layers of biological organization (ranging from genetic to epigenetic to cellular pathway to metabolomic). It is especially relevant in the context of modern (ongoing and prospective) studies that generate heterogeneous high-throughput omics datasets. However, there are both theoretical and practical obstacles to the seamless application of BN modeling to such big data, including computational inefficiency of optimal BN structure search algorithms, ambiguity in data discretization, mixing data types, imputation and validation, and, in general, limited scalability in both reconstruction and visualization of BNs. To overcome these and other obstacles, we present BNOmics, an improved algorithm and software toolkit for inferring and analyzing BNs from omics datasets. BNOmics aims at comprehensive systems biology—type data exploration, including both generating new biological hypothesis and testing and validating the existing ones. Novel aspects of the algorithm center around increasing scalability and applicability to varying data types (with different explicit and implicit distributional assumptions) within the same analysis framework. An output and visualization interface to widely available graph-rendering software is also included. Three diverse applications are detailed. BNOmics was originally developed in the context of genetic epidemiology data and is being continuously optimized to keep pace with the ever-increasing inflow of available large-scale omics datasets. As such, the software scalability and usability on the less than exotic computer hardware are a priority, as well as the applicability of the algorithm and software to the heterogeneous datasets containing many data types—single-nucleotide polymorphisms and other genetic/epigenetic/transcriptome variables

New Algorithm and Software (BNOmics) for Inferring and Visualizing Bayesian Networks from Heterogeneous Big Biological and Genetic Data.

PubMed

Gogoshin, Grigoriy; Boerwinkle, Eric; Rodin, Andrei S

2017-04-01

Bayesian network (BN) reconstruction is a prototypical systems biology data analysis approach that has been successfully used to reverse engineer and model networks reflecting different layers of biological organization (ranging from genetic to epigenetic to cellular pathway to metabolomic). It is especially relevant in the context of modern (ongoing and prospective) studies that generate heterogeneous high-throughput omics datasets. However, there are both theoretical and practical obstacles to the seamless application of BN modeling to such big data, including computational inefficiency of optimal BN structure search algorithms, ambiguity in data discretization, mixing data types, imputation and validation, and, in general, limited scalability in both reconstruction and visualization of BNs. To overcome these and other obstacles, we present BNOmics, an improved algorithm and software toolkit for inferring and analyzing BNs from omics datasets. BNOmics aims at comprehensive systems biology-type data exploration, including both generating new biological hypothesis and testing and validating the existing ones. Novel aspects of the algorithm center around increasing scalability and applicability to varying data types (with different explicit and implicit distributional assumptions) within the same analysis framework. An output and visualization interface to widely available graph-rendering software is also included. Three diverse applications are detailed. BNOmics was originally developed in the context of genetic epidemiology data and is being continuously optimized to keep pace with the ever-increasing inflow of available large-scale omics datasets. As such, the software scalability and usability on the less than exotic computer hardware are a priority, as well as the applicability of the algorithm and software to the heterogeneous datasets containing many data types-single-nucleotide polymorphisms and other genetic/epigenetic/transcriptome variables, metabolite

Progress toward scalable tomography of quantum maps using twirling-based methods and information hierarchies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lopez, Cecilia C.; Theoretische Physik, Universitaet des Saarlandes, D-66041 Saarbruecken; Departament de Fisica, Universitat Autonoma de Barcelona, E-08193 Bellaterra

2010-06-15

We present in a unified manner the existing methods for scalable partial quantum process tomography. We focus on two main approaches: the one presented in Bendersky et al. [Phys. Rev. Lett. 100, 190403 (2008)] and the ones described, respectively, in Emerson et al. [Science 317, 1893 (2007)] and Lopez et al. [Phys. Rev. A 79, 042328 (2009)], which can be combined together. The methods share an essential feature: They are based on the idea that the tomography of a quantum map can be efficiently performed by studying certain properties of a twirling of such a map. From this perspective, inmore » this paper we present extensions, improvements, and comparative analyses of the scalable methods for partial quantum process tomography. We also clarify the significance of the extracted information, and we introduce interesting and useful properties of the {chi}-matrix representation of quantum maps that can be used to establish a clearer path toward achieving full tomography of quantum processes in a scalable way.« less

Efficient visualization of high-throughput targeted proteomics experiments: TAPIR.

PubMed

Röst, Hannes L; Rosenberger, George; Aebersold, Ruedi; Malmström, Lars

2015-07-15

Targeted mass spectrometry comprises a set of powerful methods to obtain accurate and consistent protein quantification in complex samples. To fully exploit these techniques, a cross-platform and open-source software stack based on standardized data exchange formats is required. We present TAPIR, a fast and efficient Python visualization software for chromatograms and peaks identified in targeted proteomics experiments. The input formats are open, community-driven standardized data formats (mzML for raw data storage and TraML encoding the hierarchical relationships between transitions, peptides and proteins). TAPIR is scalable to proteome-wide targeted proteomics studies (as enabled by SWATH-MS), allowing researchers to visualize high-throughput datasets. The framework integrates well with existing automated analysis pipelines and can be extended beyond targeted proteomics to other types of analyses. TAPIR is available for all computing platforms under the 3-clause BSD license at https://github.com/msproteomicstools/msproteomicstools. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Visual analysis of inter-process communication for large-scale parallel computing.

PubMed

Muelder, Chris; Gygi, Francois; Ma, Kwan-Liu

2009-01-01

In serial computation, program profiling is often helpful for optimization of key sections of code. When moving to parallel computation, not only does the code execution need to be considered but also communication between the different processes which can induce delays that are detrimental to performance. As the number of processes increases, so does the impact of the communication delays on performance. For large-scale parallel applications, it is critical to understand how the communication impacts performance in order to make the code more efficient. There are several tools available for visualizing program execution and communications on parallel systems. These tools generally provide either views which statistically summarize the entire program execution or process-centric views. However, process-centric visualizations do not scale well as the number of processes gets very large. In particular, the most common representation of parallel processes is a Gantt char t with a row for each process. As the number of processes increases, these charts can become difficult to work with and can even exceed screen resolution. We propose a new visualization approach that affords more scalability and then demonstrate it on systems running with up to 16,384 processes.

Highly scalable multichannel mesh electronics for stable chronic brain electrophysiology

PubMed Central

Fu, Tian-Ming; Hong, Guosong; Viveros, Robert D.; Zhou, Tao

2017-01-01

Implantable electrical probes have led to advances in neuroscience, brain−machine interfaces, and treatment of neurological diseases, yet they remain limited in several key aspects. Ideally, an electrical probe should be capable of recording from large numbers of neurons across multiple local circuits and, importantly, allow stable tracking of the evolution of these neurons over the entire course of study. Silicon probes based on microfabrication can yield large-scale, high-density recording but face challenges of chronic gliosis and instability due to mechanical and structural mismatch with the brain. Ultraflexible mesh electronics, on the other hand, have demonstrated negligible chronic immune response and stable long-term brain monitoring at single-neuron level, although, to date, it has been limited to 16 channels. Here, we present a scalable scheme for highly multiplexed mesh electronics probes to bridge the gap between scalability and flexibility, where 32 to 128 channels per probe were implemented while the crucial brain-like structure and mechanics were maintained. Combining this mesh design with multisite injection, we demonstrate stable 128-channel local field potential and single-unit recordings from multiple brain regions in awake restrained mice over 4 mo. In addition, the newly integrated mesh is used to validate stable chronic recordings in freely behaving mice. This scalable scheme for mesh electronics together with demonstrated long-term stability represent important progress toward the realization of ideal implantable electrical probes allowing for mapping and tracking single-neuron level circuit changes associated with learning, aging, and neurodegenerative diseases. PMID:29109247

Highly scalable multichannel mesh electronics for stable chronic brain electrophysiology.

PubMed

Fu, Tian-Ming; Hong, Guosong; Viveros, Robert D; Zhou, Tao; Lieber, Charles M

2017-11-21

Implantable electrical probes have led to advances in neuroscience, brain-machine interfaces, and treatment of neurological diseases, yet they remain limited in several key aspects. Ideally, an electrical probe should be capable of recording from large numbers of neurons across multiple local circuits and, importantly, allow stable tracking of the evolution of these neurons over the entire course of study. Silicon probes based on microfabrication can yield large-scale, high-density recording but face challenges of chronic gliosis and instability due to mechanical and structural mismatch with the brain. Ultraflexible mesh electronics, on the other hand, have demonstrated negligible chronic immune response and stable long-term brain monitoring at single-neuron level, although, to date, it has been limited to 16 channels. Here, we present a scalable scheme for highly multiplexed mesh electronics probes to bridge the gap between scalability and flexibility, where 32 to 128 channels per probe were implemented while the crucial brain-like structure and mechanics were maintained. Combining this mesh design with multisite injection, we demonstrate stable 128-channel local field potential and single-unit recordings from multiple brain regions in awake restrained mice over 4 mo. In addition, the newly integrated mesh is used to validate stable chronic recordings in freely behaving mice. This scalable scheme for mesh electronics together with demonstrated long-term stability represent important progress toward the realization of ideal implantable electrical probes allowing for mapping and tracking single-neuron level circuit changes associated with learning, aging, and neurodegenerative diseases. Copyright © 2017 the Author(s). Published by PNAS.

LoRa Scalability: A Simulation Model Based on Interference Measurements

PubMed Central

Haxhibeqiri, Jetmir; Van den Abeele, Floris; Moerman, Ingrid; Hoebeke, Jeroen

2017-01-01

LoRa is a long-range, low power, low bit rate and single-hop wireless communication technology. It is intended to be used in Internet of Things (IoT) applications involving battery-powered devices with low throughput requirements. A LoRaWAN network consists of multiple end nodes that communicate with one or more gateways. These gateways act like a transparent bridge towards a common network server. The amount of end devices and their throughput requirements will have an impact on the performance of the LoRaWAN network. This study investigates the scalability in terms of the number of end devices per gateway of single-gateway LoRaWAN deployments. First, we determine the intra-technology interference behavior with two physical end nodes, by checking the impact of an interfering node on a transmitting node. Measurements show that even under concurrent transmission, one of the packets can be received under certain conditions. Based on these measurements, we create a simulation model for assessing the scalability of a single gateway LoRaWAN network. We show that when the number of nodes increases up to 1000 per gateway, the losses will be up to 32%. In such a case, pure Aloha will have around 90% losses. However, when the duty cycle of the application layer becomes lower than the allowed radio duty cycle of 1%, losses will be even lower. We also show network scalability simulation results for some IoT use cases based on real data. PMID:28545239

Scalable metagenomic taxonomy classification using a reference genome database

PubMed Central

Ames, Sasha K.; Hysom, David A.; Gardner, Shea N.; Lloyd, G. Scott; Gokhale, Maya B.; Allen, Jonathan E.

2013-01-01

Motivation: Deep metagenomic sequencing of biological samples has the potential to recover otherwise difficult-to-detect microorganisms and accurately characterize biological samples with limited prior knowledge of sample contents. Existing metagenomic taxonomic classification algorithms, however, do not scale well to analyze large metagenomic datasets, and balancing classification accuracy with computational efficiency presents a fundamental challenge. Results: A method is presented to shift computational costs to an off-line computation by creating a taxonomy/genome index that supports scalable metagenomic classification. Scalable performance is demonstrated on real and simulated data to show accurate classification in the presence of novel organisms on samples that include viruses, prokaryotes, fungi and protists. Taxonomic classification of the previously published 150 giga-base Tyrolean Iceman dataset was found to take <20 h on a single node 40 core large memory machine and provide new insights on the metagenomic contents of the sample. Availability: Software was implemented in C++ and is freely available at http://sourceforge.net/projects/lmat Contact: allen99@llnl.gov Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23828782

NOA: A Scalable Multi-Parent Clustering Hierarchy for WSNs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cree, Johnathan V.; Delgado-Frias, Jose; Hughes, Michael A.

2012-08-10

NOA is a multi-parent, N-tiered, hierarchical clustering algorithm that provides a scalable, robust and reliable solution to autonomous configuration of large-scale wireless sensor networks. The novel clustering hierarchy's inherent benefits can be utilized by in-network data processing techniques to provide equally robust, reliable and scalable in-network data processing solutions capable of reducing the amount of data sent to sinks. Utilizing a multi-parent framework, NOA reduces the cost of network setup when compared to hierarchical beaconing solutions by removing the expense of r-hop broadcasting (r is the radius of the cluster) needed to build the network and instead passes network topologymore » information among shared children. NOA2, a two-parent clustering hierarchy solution, and NOA3, the three-parent variant, saw up to an 83% and 72% reduction in overhead, respectively, when compared to performing one round of a one-parent hierarchical beaconing, as well as 92% and 88% less overhead when compared to one round of two- and three-parent hierarchical beaconing hierarchy.« less

AEGIS: a robust and scalable real-time public health surveillance system.

PubMed

Reis, Ben Y; Kirby, Chaim; Hadden, Lucy E; Olson, Karen; McMurry, Andrew J; Daniel, James B; Mandl, Kenneth D

2007-01-01

In this report, we describe the Automated Epidemiological Geotemporal Integrated Surveillance system (AEGIS), developed for real-time population health monitoring in the state of Massachusetts. AEGIS provides public health personnel with automated near-real-time situational awareness of utilization patterns at participating healthcare institutions, supporting surveillance of bioterrorism and naturally occurring outbreaks. As real-time public health surveillance systems become integrated into regional and national surveillance initiatives, the challenges of scalability, robustness, and data security become increasingly prominent. A modular and fault tolerant design helps AEGIS achieve scalability and robustness, while a distributed storage model with local autonomy helps to minimize risk of unauthorized disclosure. The report includes a description of the evolution of the design over time in response to the challenges of a regional and national integration environment.

A Scalable Data Access Layer to Manage Structured Heterogeneous Biomedical Data.

PubMed

Delussu, Giovanni; Lianas, Luca; Frexia, Francesca; Zanetti, Gianluigi

2016-01-01

This work presents a scalable data access layer, called PyEHR, designed to support the implementation of data management systems for secondary use of structured heterogeneous biomedical and clinical data. PyEHR adopts the openEHR's formalisms to guarantee the decoupling of data descriptions from implementation details and exploits structure indexing to accelerate searches. Data persistence is guaranteed by a driver layer with a common driver interface. Interfaces for two NoSQL Database Management Systems are already implemented: MongoDB and Elasticsearch. We evaluated the scalability of PyEHR experimentally through two types of tests, called "Constant Load" and "Constant Number of Records", with queries of increasing complexity on synthetic datasets of ten million records each, containing very complex openEHR archetype structures, distributed on up to ten computing nodes.

A Scalable Data Access Layer to Manage Structured Heterogeneous Biomedical Data

PubMed Central

Lianas, Luca; Frexia, Francesca; Zanetti, Gianluigi

2016-01-01

This work presents a scalable data access layer, called PyEHR, designed to support the implementation of data management systems for secondary use of structured heterogeneous biomedical and clinical data. PyEHR adopts the openEHR’s formalisms to guarantee the decoupling of data descriptions from implementation details and exploits structure indexing to accelerate searches. Data persistence is guaranteed by a driver layer with a common driver interface. Interfaces for two NoSQL Database Management Systems are already implemented: MongoDB and Elasticsearch. We evaluated the scalability of PyEHR experimentally through two types of tests, called “Constant Load” and “Constant Number of Records”, with queries of increasing complexity on synthetic datasets of ten million records each, containing very complex openEHR archetype structures, distributed on up to ten computing nodes. PMID:27936191

Scalable Metadata Management for a Large Multi-Source Seismic Data Repository

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gaylord, J. M.; Dodge, D. A.; Magana-Zook, S. A.

In this work, we implemented the key metadata management components of a scalable seismic data ingestion framework to address limitations in our existing system, and to position it for anticipated growth in volume and complexity.

Scalable Management of Enterprise and Data-Center Networks

DTIC Science & Technology

2011-09-01

To the best of our knowledge , there is no systematic and efficient solution for handling overlapping wildcard rules in network-wide flow- management ...and D. Maltz, “Unraveling the complexity of network management ,” in NSDI, 2009. [4] P. Mahadevan, P. Sharma, S. Banerjee, and P. Ranganathan , “A...Scalable Management of Enterprise and Data-Center Networks Minlan Yu A Dissertation Presented to the Faculty of Princeton University in Candidacy for

Analyzing Living Surveys: Visualization Beyond the Data Release

NASA Astrophysics Data System (ADS)

Buddelmeijer, H.; Noorishad, P.; Williams, D.; Ivanova, M.; Roerdink, J. B. T. M.; Valentijn, E. A.

2015-09-01

Surveys need to provide more than periodic data releases. Science often requires data that is not captured in such releases. This mismatch between the constraints set by a fixed data release and the needs of the scientists is solved in the Astro-WISE information system by extending its request-driven data handling into the analysis domain. This leads to Query-Driven Visualization, where all data handling is automated and scalable by exploiting the strengths of data pulling. Astro-WISE is data-centric: new data creates itself automatically, if no suitable existing data can be found to fulfill a request. This approach allows scientists to visualize exactly the data they need, without any manual data management, freeing their time for research. The benefits of query-driven visualization are highlighted by searching for distant quasars in KiDS, a 1500 square degree optical survey. KiDS needs to be treated as a living survey to minimize the time between observation and (spectral) followup. The first window of opportunity would be missed if it were necessary to wait for data releases. The results from the default processing pipelines are used for a quick and broad selection of quasar candidates. More precise measurements of source properties can subsequently be requested to downsize the candidate set, requiring partial reprocessing of the images. Finally, the raw and reduced pixels themselves are inspected by eye to rank the final candidate list. The quality of the resulting candidate list and the speed of its creation were only achievable due to query driven-visualization of the living archive.

Semantic Integrative Digital Pathology: Insights into Microsemiological Semantics and Image Analysis Scalability.

PubMed

Racoceanu, Daniel; Capron, Frédérique

2016-01-01

be devoted to morphological microsemiology (microscopic morphology semantics). Besides insuring the traceability of the results (second opinion) and supporting the orchestration of high-content image analysis modules, the role of semantics will be crucial for the correlation between digital pathology and noninvasive medical imaging modalities. In addition, semantics has an important role in modelling the links between traditional microscopy and recent label-free technologies. The massive amount of visual data is challenging and represents a characteristic intrinsic to digital pathology. The design of an operational integrative microscopy framework needs to focus on scalable multiscale imaging formalism. In this sense, we prospectively consider some of the most recent scalable methodologies adapted to digital pathology as marked point processes for nuclear atypia and point-set mathematical morphology for architecture grading. To orchestrate this scalable framework, semantics-based WSI management (analysis, exploration, indexing, retrieval and report generation support) represents an important means towards approaches to integrating big data into biomedicine. This insight reflects our vision through an instantiation of essential bricks of this type of architecture. The generic approach introduced here is applicable to a number of challenges related to molecular imaging, high-content image management and, more generally, bioinformatics. © 2016 S. Karger AG, Basel.

A Numerical Study of Scalable Cardiac Electro-Mechanical Solvers on HPC Architectures

PubMed Central

Colli Franzone, Piero; Pavarino, Luca F.; Scacchi, Simone

2018-01-01

We introduce and study some scalable domain decomposition preconditioners for cardiac electro-mechanical 3D simulations on parallel HPC (High Performance Computing) architectures. The electro-mechanical model of the cardiac tissue is composed of four coupled sub-models: (1) the static finite elasticity equations for the transversely isotropic deformation of the cardiac tissue; (2) the active tension model describing the dynamics of the intracellular calcium, cross-bridge binding and myofilament tension; (3) the anisotropic Bidomain model describing the evolution of the intra- and extra-cellular potentials in the deforming cardiac tissue; and (4) the ionic membrane model describing the dynamics of ionic currents, gating variables, ionic concentrations and stretch-activated channels. This strongly coupled electro-mechanical model is discretized in time with a splitting semi-implicit technique and in space with isoparametric finite elements. The resulting scalable parallel solver is based on Multilevel Additive Schwarz preconditioners for the solution of the Bidomain system and on BDDC preconditioned Newton-Krylov solvers for the non-linear finite elasticity system. The results of several 3D parallel simulations show the scalability of both linear and non-linear solvers and their application to the study of both physiological excitation-contraction cardiac dynamics and re-entrant waves in the presence of different mechano-electrical feedbacks. PMID:29674971

Scalable splitting algorithms for big-data interferometric imaging in the SKA era

NASA Astrophysics Data System (ADS)

Onose, Alexandru; Carrillo, Rafael E.; Repetti, Audrey; McEwen, Jason D.; Thiran, Jean-Philippe; Pesquet, Jean-Christophe; Wiaux, Yves

2016-11-01

In the context of next-generation radio telescopes, like the Square Kilometre Array (SKA), the efficient processing of large-scale data sets is extremely important. Convex optimization tasks under the compressive sensing framework have recently emerged and provide both enhanced image reconstruction quality and scalability to increasingly larger data sets. We focus herein mainly on scalability and propose two new convex optimization algorithmic structures able to solve the convex optimization tasks arising in radio-interferometric imaging. They rely on proximal splitting and forward-backward iterations and can be seen, by analogy, with the CLEAN major-minor cycle, as running sophisticated CLEAN-like iterations in parallel in multiple data, prior, and image spaces. Both methods support any convex regularization function, in particular, the well-studied ℓ1 priors promoting image sparsity in an adequate domain. Tailored for big-data, they employ parallel and distributed computations to achieve scalability, in terms of memory and computational requirements. One of them also exploits randomization, over data blocks at each iteration, offering further flexibility. We present simulation results showing the feasibility of the proposed methods as well as their advantages compared to state-of-the-art algorithmic solvers. Our MATLAB code is available online on GitHub.

From Field Notes to Data Portal - A Scalable Data QA/QC Framework for Tower Networks: Progress and Preliminary Results

NASA Astrophysics Data System (ADS)

Sturtevant, C.; Hackley, S.; Lee, R.; Holling, G.; Bonarrigo, S.

2017-12-01

Quality assurance and control (QA/QC) is one of the most important yet challenging aspects of producing research-quality data. Data quality issues are multi-faceted, including sensor malfunctions, unmet theoretical assumptions, and measurement interference from humans or the natural environment. Tower networks such as Ameriflux, ICOS, and NEON continue to grow in size and sophistication, yet tools for robust, efficient, scalable QA/QC have lagged. Quality control remains a largely manual process heavily relying on visual inspection of data. In addition, notes of measurement interference are often recorded on paper without an explicit pathway to data flagging. As such, an increase in network size requires a near-proportional increase in personnel devoted to QA/QC, quickly stressing the human resources available. We present a scalable QA/QC framework in development for NEON that combines the efficiency and standardization of automated checks with the power and flexibility of human review. This framework includes fast-response monitoring of sensor health, a mobile application for electronically recording maintenance activities, traditional point-based automated quality flagging, and continuous monitoring of quality outcomes and longer-term holistic evaluations. This framework maintains the traceability of quality information along the entirety of the data generation pipeline, and explicitly links field reports of measurement interference to quality flagging. Preliminary results show that data quality can be effectively monitored and managed for a multitude of sites with a small group of QA/QC staff. Several components of this framework are open-source, including a R-Shiny application for efficiently monitoring, synthesizing, and investigating data quality issues.

An OpenEarth Framework (OEF) for Integrating and Visualizing Earth Science Data

NASA Astrophysics Data System (ADS)

Moreland, J. L.; Nadeau, D. R.; Baru, C.; Crosby, C. J.

2009-12-01

no convention or embedded data yields a suitable answer, the user is prompted to fill in the blanks. The OEF’s interaction libraries assist in the construction of user interfaces for data management. These libraries support data import, data prompting, data introspection, the management of the contents of a common data model, and the creation of derived data to support visualization. Finally, visualization libraries provide interactive visualization using an extended version of NASA WorldWind. The OEF viewer supports visualization of terrains, point clouds, 3D volumes, imagery, cutting planes, isosurfaces, and more. Data may be color coded, shaded, and displayed above, or below the terrain, and always registered into a common coordinate space. The OEF architecture is open and cross-platform software libraries are available separately for use with other software projects, while modules from other projects may be integrated into the OEF to extend its features. The OEF is currently being used to visualize data from EarthScope-related research in the Western US.

Enhancing radiological volumes with symbolic anatomy using image fusion and collaborative virtual reality.

PubMed

Silverstein, Jonathan C; Dech, Fred; Kouchoukos, Philip L

2004-01-01

Radiological volumes are typically reviewed by surgeons using cross-sections and iso-surface reconstructions. Applications that combine collaborative stereo volume visualization with symbolic anatomic information and data fusions would expand surgeons' capabilities in interpretation of data and in planning treatment. Such an application has not been seen clinically. We are developing methods to systematically combine symbolic anatomy (term hierarchies and iso-surface atlases) with patient data using data fusion. We describe our progress toward integrating these methods into our collaborative virtual reality application. The fully combined application will be a feature-rich stereo collaborative volume visualization environment for use by surgeons in which DICOM datasets will self-report underlying anatomy with visual feedback. Using hierarchical navigation of SNOMED-CT anatomic terms integrated with our existing Tele-immersive DICOM-based volumetric rendering application, we will display polygonal representations of anatomic systems on the fly from menus that query a database. The methods and tools involved in this application development are SNOMED-CT, DICOM, VISIBLE HUMAN, volumetric fusion and C++ on a Tele-immersive platform. This application will allow us to identify structures and display polygonal representations from atlas data overlaid with the volume rendering. First, atlas data is automatically translated, rotated, and scaled to the patient data during loading using a public domain volumetric fusion algorithm. This generates a modified symbolic representation of the underlying canonical anatomy. Then, through the use of collision detection or intersection testing of various transparent polygonal representations, the polygonal structures are highlighted into the volumetric representation while the SNOMED names are displayed. Thus, structural names and polygonal models are associated with the visualized DICOM data. This novel juxtaposition of information

Developing a scalable artificial photosynthesis technology through nanomaterials by design

NASA Astrophysics Data System (ADS)

Lewis, Nathan S.

2016-12-01

An artificial photosynthetic system that directly produces fuels from sunlight could provide an approach to scalable energy storage and a technology for the carbon-neutral production of high-energy-density transportation fuels. A variety of designs are currently being explored to create a viable artificial photosynthetic system, and the most technologically advanced systems are based on semiconducting photoelectrodes. Here, I discuss the development of an approach that is based on an architecture, first conceived around a decade ago, that combines arrays of semiconducting microwires with flexible polymeric membranes. I highlight the key steps that have been taken towards delivering a fully functional solar fuels generator, which have exploited advances in nanotechnology at all hierarchical levels of device construction, and include the discovery of earth-abundant electrocatalysts for fuel formation and materials for the stabilization of light absorbers. Finally, I consider the remaining scientific and engineering challenges facing the fulfilment of an artificial photosynthetic system that is simultaneously safe, robust, efficient and scalable.

Scalable Parallel Computation for Extended MHD Modeling of Fusion Plasmas

NASA Astrophysics Data System (ADS)

Glasser, Alan H.

2008-11-01

Parallel solution of a linear system is scalable if simultaneously doubling the number of dependent variables and the number of processors results in little or no increase in the computation time to solution. Two approaches have this property for parabolic systems: multigrid and domain decomposition. Since extended MHD is primarily a hyperbolic rather than a parabolic system, additional steps must be taken to parabolize the linear system to be solved by such a method. Such physics-based preconditioning (PBP) methods have been pioneered by Chac'on, using finite volumes for spatial discretization, multigrid for solution of the preconditioning equations, and matrix-free Newton-Krylov methods for the accurate solution of the full nonlinear preconditioned equations. The work described here is an extension of these methods using high-order spectral element methods and FETI-DP domain decomposition. Application of PBP to a flux-source representation of the physics equations is discussed. The resulting scalability will be demonstrated for simple wave and for ideal and Hall MHD waves.

Adding sound to theory of mind: Comparing children's development of mental-state understanding in the auditory and visual realms.

PubMed

Hasni, Anita A; Adamson, Lauren B; Williamson, Rebecca A; Robins, Diana L

2017-12-01

Theory of mind (ToM) gradually develops during the preschool years. Measures of ToM usually target visual experience, but auditory experiences also provide valuable social information. Given differences between the visual and auditory modalities (e.g., sights persist, sounds fade) and the important role environmental input plays in social-cognitive development, we asked whether modality might influence the progression of ToM development. The current study expands Wellman and Liu's ToM scale (2004) by testing 66 preschoolers using five standard visual ToM tasks and five newly crafted auditory ToM tasks. Age and gender effects were found, with 4- and 5-year-olds demonstrating greater ToM abilities than 3-year-olds and girls passing more tasks than boys; there was no significant effect of modality. Both visual and auditory tasks formed a scalable set. These results indicate that there is considerable consistency in when children are able to use visual and auditory inputs to reason about various aspects of others' mental states. Copyright © 2017 Elsevier Inc. All rights reserved.

Extreme Performance Scalable Operating Systems Final Progress Report (July 1, 2008 - October 31, 2011)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Malony, Allen D; Shende, Sameer

This is the final progress report for the FastOS (Phase 2) (FastOS-2) project with Argonne National Laboratory and the University of Oregon (UO). The project started at UO on July 1, 2008 and ran until April 30, 2010, at which time a six-month no-cost extension began. The FastOS-2 work at UO delivered excellent results in all research work areas: * scalable parallel monitoring * kernel-level performance measurement * parallel I/0 system measurement * large-scale and hybrid application performance measurement * onlne scalable performance data reduction and analysis * binary instrumentation

A scalable neuroinformatics data flow for electrophysiological signals using MapReduce.

PubMed

Jayapandian, Catherine; Wei, Annan; Ramesh, Priya; Zonjy, Bilal; Lhatoo, Samden D; Loparo, Kenneth; Zhang, Guo-Qiang; Sahoo, Satya S

2015-01-01

Data-driven neuroscience research is providing new insights in progression of neurological disorders and supporting the development of improved treatment approaches. However, the volume, velocity, and variety of neuroscience data generated from sophisticated recording instruments and acquisition methods have exacerbated the limited scalability of existing neuroinformatics tools. This makes it difficult for neuroscience researchers to effectively leverage the growing multi-modal neuroscience data to advance research in serious neurological disorders, such as epilepsy. We describe the development of the Cloudwave data flow that uses new data partitioning techniques to store and analyze electrophysiological signal in distributed computing infrastructure. The Cloudwave data flow uses MapReduce parallel programming algorithm to implement an integrated signal data processing pipeline that scales with large volume of data generated at high velocity. Using an epilepsy domain ontology together with an epilepsy focused extensible data representation format called Cloudwave Signal Format (CSF), the data flow addresses the challenge of data heterogeneity and is interoperable with existing neuroinformatics data representation formats, such as HDF5. The scalability of the Cloudwave data flow is evaluated using a 30-node cluster installed with the open source Hadoop software stack. The results demonstrate that the Cloudwave data flow can process increasing volume of signal data by leveraging Hadoop Data Nodes to reduce the total data processing time. The Cloudwave data flow is a template for developing highly scalable neuroscience data processing pipelines using MapReduce algorithms to support a variety of user applications.

A scalable neuroinformatics data flow for electrophysiological signals using MapReduce

PubMed Central

Jayapandian, Catherine; Wei, Annan; Ramesh, Priya; Zonjy, Bilal; Lhatoo, Samden D.; Loparo, Kenneth; Zhang, Guo-Qiang; Sahoo, Satya S.

2015-01-01

Data-driven neuroscience research is providing new insights in progression of neurological disorders and supporting the development of improved treatment approaches. However, the volume, velocity, and variety of neuroscience data generated from sophisticated recording instruments and acquisition methods have exacerbated the limited scalability of existing neuroinformatics tools. This makes it difficult for neuroscience researchers to effectively leverage the growing multi-modal neuroscience data to advance research in serious neurological disorders, such as epilepsy. We describe the development of the Cloudwave data flow that uses new data partitioning techniques to store and analyze electrophysiological signal in distributed computing infrastructure. The Cloudwave data flow uses MapReduce parallel programming algorithm to implement an integrated signal data processing pipeline that scales with large volume of data generated at high velocity. Using an epilepsy domain ontology together with an epilepsy focused extensible data representation format called Cloudwave Signal Format (CSF), the data flow addresses the challenge of data heterogeneity and is interoperable with existing neuroinformatics data representation formats, such as HDF5. The scalability of the Cloudwave data flow is evaluated using a 30-node cluster installed with the open source Hadoop software stack. The results demonstrate that the Cloudwave data flow can process increasing volume of signal data by leveraging Hadoop Data Nodes to reduce the total data processing time. The Cloudwave data flow is a template for developing highly scalable neuroscience data processing pipelines using MapReduce algorithms to support a variety of user applications. PMID:25852536

Sustainability and scalability of a volunteer-based primary care intervention (Health TAPESTRY): a mixed-methods analysis.

PubMed

Kastner, Monika; Sayal, Radha; Oliver, Doug; Straus, Sharon E; Dolovich, Lisa

2017-08-01

Chronic diseases are a significant public health concern, particularly in older adults. To address the delivery of health care services to optimally meet the needs of older adults with multiple chronic diseases, Health TAPESTRY (Teams Advancing Patient Experience: Strengthening Quality) uses a novel approach that involves patient home visits by trained volunteers to collect and transmit relevant health information using e-health technology to inform appropriate care from an inter-professional healthcare team. Health TAPESTRY was implemented, pilot tested, and evaluated in a randomized controlled trial (analysis underway). Knowledge translation (KT) interventions such as Health TAPESTRY should involve an investigation of their sustainability and scalability determinants to inform further implementation. However, this is seldom considered in research or considered early enough, so the objectives of this study were to assess the sustainability and scalability potential of Health TAPESTRY from the perspective of the team who developed and pilot-tested it. Our objectives were addressed using a sequential mixed-methods approach involving the administration of a validated, sustainability survey developed by the National Health Service (NHS) to all members of the Health TAPESTRY team who were actively involved in the development, implementation and pilot evaluation of the intervention (Phase 1: n = 38). Mean sustainability scores were calculated to identify the best potential for improvement across sustainability factors. Phase 2 was a qualitative study of interviews with purposively selected Health TAPESTRY team members to gain a more in-depth understanding of the factors that influence the sustainability and scalability Health TAPESTRY. Two independent reviewers coded transcribed interviews and completed a multi-step thematic analysis. Outcomes were participant perceptions of the determinants influencing the sustainability and scalability of Health TAPESTRY. Twenty

Computational scalability of large size image dissemination

NASA Astrophysics Data System (ADS)

Kooper, Rob; Bajcsy, Peter

2011-01-01

We have investigated the computational scalability of image pyramid building needed for dissemination of very large image data. The sources of large images include high resolution microscopes and telescopes, remote sensing and airborne imaging, and high resolution scanners. The term 'large' is understood from a user perspective which means either larger than a display size or larger than a memory/disk to hold the image data. The application drivers for our work are digitization projects such as the Lincoln Papers project (each image scan is about 100-150MB or about 5000x8000 pixels with the total number to be around 200,000) and the UIUC library scanning project for historical maps from 17th and 18th century (smaller number but larger images). The goal of our work is understand computational scalability of the web-based dissemination using image pyramids for these large image scans, as well as the preservation aspects of the data. We report our computational benchmarks for (a) building image pyramids to be disseminated using the Microsoft Seadragon library, (b) a computation execution approach using hyper-threading to generate image pyramids and to utilize the underlying hardware, and (c) an image pyramid preservation approach using various hard drive configurations of Redundant Array of Independent Disks (RAID) drives for input/output operations. The benchmarks are obtained with a map (334.61 MB, JPEG format, 17591x15014 pixels). The discussion combines the speed and preservation objectives.

A scalable parallel black oil simulator on distributed memory parallel computers

NASA Astrophysics Data System (ADS)

Wang, Kun; Liu, Hui; Chen, Zhangxin

2015-11-01

This paper presents our work on developing a parallel black oil simulator for distributed memory computers based on our in-house parallel platform. The parallel simulator is designed to overcome the performance issues of common simulators that are implemented for personal computers and workstations. The finite difference method is applied to discretize the black oil model. In addition, some advanced techniques are employed to strengthen the robustness and parallel scalability of the simulator, including an inexact Newton method, matrix decoupling methods, and algebraic multigrid methods. A new multi-stage preconditioner is proposed to accelerate the solution of linear systems from the Newton methods. Numerical experiments show that our simulator is scalable and efficient, and is capable of simulating extremely large-scale black oil problems with tens of millions of grid blocks using thousands of MPI processes on parallel computers.

The P-Mesh: A Commodity-based Scalable Network Architecture for Clusters

NASA Technical Reports Server (NTRS)

Nitzberg, Bill; Kuszmaul, Chris; Stockdale, Ian; Becker, Jeff; Jiang, John; Wong, Parkson; Tweten, David (Technical Monitor)

1998-01-01

We designed a new network architecture, the P-Mesh which combines the scalability and fault resilience of a torus with the performance of a switch. We compare the scalability, performance, and cost of the hub, switch, torus, tree, and P-Mesh architectures. The latter three are capable of scaling to thousands of nodes, however, the torus has severe performance limitations with that many processors. The tree and P-Mesh have similar latency, bandwidth, and bisection bandwidth, but the P-Mesh outperforms the switch architecture (a lower bound for tree performance) on 16-node NAB Parallel Benchmark tests by up to 23%, and costs 40% less. Further, the P-Mesh has better fault resilience characteristics. The P-Mesh architecture trades increased management overhead for lower cost, and is a good bridging technology while the price of tree uplinks is expensive.

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

NASA Astrophysics Data System (ADS)

Yu, Leiming; Nina-Paravecino, Fanny; Kaeli, David; Fang, Qianqian

2018-01-01

We present a highly scalable Monte Carlo (MC) three-dimensional photon transport simulation platform designed for heterogeneous computing systems. Through the development of a massively parallel MC algorithm using the Open Computing Language framework, this research extends our existing graphics processing unit (GPU)-accelerated MC technique to a highly scalable vendor-independent heterogeneous computing environment, achieving significantly improved performance and software portability. A number of parallel computing techniques are investigated to achieve portable performance over a wide range of computing hardware. Furthermore, multiple thread-level and device-level load-balancing strategies are developed to obtain efficient simulations using multiple central processing units and GPUs.

VPLS: an effective technology for building scalable transparent LAN services

NASA Astrophysics Data System (ADS)

Dong, Ximing; Yu, Shaohua

2005-02-01

Virtual Private LAN Service (VPLS) is generating considerable interest with enterprises and service providers as it offers multipoint transparent LAN service (TLS) over MPLS networks. This paper describes an effective technology - VPLS, which links virtual switch instances (VSIs) through MPLS to form an emulated Ethernet switch and build Scalable Transparent Lan Services. It first focuses on the architecture of VPLS with Ethernet bridging technique at the edge and MPLS at the core, then it tries to elucidate the data forwarding mechanism within VPLS domain, including learning and aging MAC addresses on a per LSP basis, flooding of unknown frames and replication for unknown, multicast, and broadcast frames. The loop-avoidance mechanism, known as split horizon forwarding, is also analyzed. Another important aspect of VPLS service is its basic operation, including autodiscovery and signaling, is discussed. From the perspective of efficiency and scalability the paper compares two important signaling mechanism, BGP and LDP, which are used to set up a PW between the PEs and bind the PWs to a particular VSI. With the extension of VPLS and the increase of full mesh of PWs between PE devices (n*(n-1)/2 PWs in all, a n2 complete problem), VPLS instance could have a large number of remote PE associations, resulting in an inefficient use of network bandwidth and system resources as the ingress PE has to replicate each frame and append MPLS labels for remote PE. So the latter part of this paper focuses on the scalability issue: the Hierarchical VPLS. Within the architecture of HVPLS, this paper addresses two ways to cope with a possibly large number of MAC addresses, which make VPLS operate more efficiently.

Scalability of Classical Terramechanics Models for Lightweight Vehicle Applications

DTIC Science & Technology

2013-08-01

Models for Lightweight Vehicle Applications Paramsothy Jayakumar Daniel Melanz Jamie MacLennan U.S. Army TARDEC Warren, MI, USA Carmine...NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Paramsothy Jayakumar ; Daniel Melanz; Jamie MacLennan; Carmine Senatore; Karl Iagnemma 5d. PROJECT...GVSETS), UNCLASSIFIED Scalability of Classical Terramechanics Models for Lightweight Vehicle Applications, Jayakumar , et al., UNCLASSIFIED Page 1 of 19

LVFS: A Scalable Petabye/Exabyte Data Storage System

NASA Astrophysics Data System (ADS)

Golpayegani, N.; Halem, M.; Masuoka, E. J.; Ye, G.; Devine, N. K.

2013-12-01

Managing petabytes of data with hundreds of millions of files is the first step necessary towards an effective big data computing and collaboration environment in a distributed system. We describe here the MODAPS LAADS Virtual File System (LVFS), a new storage architecture which replaces the previous MODAPS operational Level 1 Land Atmosphere Archive Distribution System (LAADS) NFS based approach to storing and distributing datasets from several instruments, such as MODIS, MERIS, and VIIRS. LAADS is responsible for the distribution of over 4 petabytes of data and over 300 million files across more than 500 disks. We present here the first LVFS big data comparative performance results and new capabilities not previously possible with the LAADS system. We consider two aspects in addressing inefficiencies of massive scales of data. First, is dealing in a reliable and resilient manner with the volume and quantity of files in such a dataset, and, second, minimizing the discovery and lookup times for accessing files in such large datasets. There are several popular file systems that successfully deal with the first aspect of the problem. Their solution, in general, is through distribution, replication, and parallelism of the storage architecture. The Hadoop Distributed File System (HDFS), Parallel Virtual File System (PVFS), and Lustre are examples of such file systems that deal with petabyte data volumes. The second aspect deals with data discovery among billions of files, the largest bottleneck in reducing access time. The metadata of a file, generally represented in a directory layout, is stored in ways that are not readily scalable. This is true for HDFS, PVFS, and Lustre as well. Recent experimental file systems, such as Spyglass or Pantheon, have attempted to address this problem through redesign of the metadata directory architecture. LVFS takes a radically different architectural approach by eliminating the need for a separate directory within the file system

On-chip detection of non-classical light by scalable integration of single-photon detectors

PubMed Central

Najafi, Faraz; Mower, Jacob; Harris, Nicholas C.; Bellei, Francesco; Dane, Andrew; Lee, Catherine; Hu, Xiaolong; Kharel, Prashanta; Marsili, Francesco; Assefa, Solomon; Berggren, Karl K.; Englund, Dirk

2015-01-01

Photonic-integrated circuits have emerged as a scalable platform for complex quantum systems. A central goal is to integrate single-photon detectors to reduce optical losses, latency and wiring complexity associated with off-chip detectors. Superconducting nanowire single-photon detectors (SNSPDs) are particularly attractive because of high detection efficiency, sub-50-ps jitter and nanosecond-scale reset time. However, while single detectors have been incorporated into individual waveguides, the system detection efficiency of multiple SNSPDs in one photonic circuit—required for scalable quantum photonic circuits—has been limited to <0.2%. Here we introduce a micrometer-scale flip-chip process that enables scalable integration of SNSPDs on a range of photonic circuits. Ten low-jitter detectors are integrated on one circuit with 100% device yield. With an average system detection efficiency beyond 10%, and estimated on-chip detection efficiency of 14–52% for four detectors operated simultaneously, we demonstrate, to the best of our knowledge, the first on-chip photon correlation measurements of non-classical light. PMID:25575346

Reimagining the microscope in the 21(st) century using the scalable adaptive graphics environment.

PubMed

Mateevitsi, Victor; Patel, Tushar; Leigh, Jason; Levy, Bruce

2015-01-01

Whole-slide imaging (WSI), while technologically mature, remains in the early adopter phase of the technology adoption lifecycle. One reason for this current situation is that current methods of visualizing and using WSI closely follow long-existing workflows for glass slides. We set out to "reimagine" the digital microscope in the era of cloud computing by combining WSI with the rich collaborative environment of the Scalable Adaptive Graphics Environment (SAGE). SAGE is a cross-platform, open-source visualization and collaboration tool that enables users to access, display and share a variety of data-intensive information, in a variety of resolutions and formats, from multiple sources, on display walls of arbitrary size. A prototype of a WSI viewer app in the SAGE environment was created. While not full featured, it enabled the testing of our hypothesis that these technologies could be blended together to change the essential nature of how microscopic images are utilized for patient care, medical education, and research. Using the newly created WSI viewer app, demonstration scenarios were created in the patient care and medical education scenarios. This included a live demonstration of a pathology consultation at the International Academy of Digital Pathology meeting in Boston in November 2014. SAGE is well suited to display, manipulate and collaborate using WSIs, along with other images and data, for a variety of purposes. It goes beyond how glass slides and current WSI viewers are being used today, changing the nature of digital pathology in the process. A fully developed WSI viewer app within SAGE has the potential to encourage the wider adoption of WSI throughout pathology.

Reimagining the microscope in the 21st century using the scalable adaptive graphics environment

PubMed Central

Mateevitsi, Victor; Patel, Tushar; Leigh, Jason; Levy, Bruce

2015-01-01

Background: Whole-slide imaging (WSI), while technologically mature, remains in the early adopter phase of the technology adoption lifecycle. One reason for this current situation is that current methods of visualizing and using WSI closely follow long-existing workflows for glass slides. We set out to “reimagine” the digital microscope in the era of cloud computing by combining WSI with the rich collaborative environment of the Scalable Adaptive Graphics Environment (SAGE). SAGE is a cross-platform, open-source visualization and collaboration tool that enables users to access, display and share a variety of data-intensive information, in a variety of resolutions and formats, from multiple sources, on display walls of arbitrary size. Methods: A prototype of a WSI viewer app in the SAGE environment was created. While not full featured, it enabled the testing of our hypothesis that these technologies could be blended together to change the essential nature of how microscopic images are utilized for patient care, medical education, and research. Results: Using the newly created WSI viewer app, demonstration scenarios were created in the patient care and medical education scenarios. This included a live demonstration of a pathology consultation at the International Academy of Digital Pathology meeting in Boston in November 2014. Conclusions: SAGE is well suited to display, manipulate and collaborate using WSIs, along with other images and data, for a variety of purposes. It goes beyond how glass slides and current WSI viewers are being used today, changing the nature of digital pathology in the process. A fully developed WSI viewer app within SAGE has the potential to encourage the wider adoption of WSI throughout pathology. PMID:26110092

Improving the scalability of hyperspectral imaging applications on heterogeneous platforms using adaptive run-time data compression

NASA Astrophysics Data System (ADS)

Plaza, Antonio; Plaza, Javier; Paz, Abel

2010-10-01

Latest generation remote sensing instruments (called hyperspectral imagers) are now able to generate hundreds of images, corresponding to different wavelength channels, for the same area on the surface of the Earth. In previous work, we have reported that the scalability of parallel processing algorithms dealing with these high-dimensional data volumes is affected by the amount of data to be exchanged through the communication network of the system. However, large messages are common in hyperspectral imaging applications since processing algorithms are pixel-based, and each pixel vector to be exchanged through the communication network is made up of hundreds of spectral values. Thus, decreasing the amount of data to be exchanged could improve the scalability and parallel performance. In this paper, we propose a new framework based on intelligent utilization of wavelet-based data compression techniques for improving the scalability of a standard hyperspectral image processing chain on heterogeneous networks of workstations. This type of parallel platform is quickly becoming a standard in hyperspectral image processing due to the distributed nature of collected hyperspectral data as well as its flexibility and low cost. Our experimental results indicate that adaptive lossy compression can lead to improvements in the scalability of the hyperspectral processing chain without sacrificing analysis accuracy, even at sub-pixel precision levels.

Adapting for Scalability: Automating the Video Assessment of Instructional Learning

ERIC Educational Resources Information Center

Roberts , Amy M.; LoCasale-Crouch, Jennifer; Hamre, Bridget K.; Buckrop, Jordan M.

2017-01-01

Although scalable programs, such as online courses, have the potential to reach broad audiences, they may pose challenges to evaluating learners' knowledge and skills. Automated scoring offers a possible solution. In the current paper, we describe the process of creating and testing an automated means of scoring a validated measure of teachers'…

Scalable asynchronous execution of cellular automata

NASA Astrophysics Data System (ADS)

Folino, Gianluigi; Giordano, Andrea; Mastroianni, Carlo

2016-10-01

The performance and scalability of cellular automata, when executed on parallel/distributed machines, are limited by the necessity of synchronizing all the nodes at each time step, i.e., a node can execute only after the execution of the previous step at all the other nodes. However, these synchronization requirements can be relaxed: a node can execute one step after synchronizing only with the adjacent nodes. In this fashion, different nodes can execute different time steps. This can be a notable advantageous in many novel and increasingly popular applications of cellular automata, such as smart city applications, simulation of natural phenomena, etc., in which the execution times can be different and variable, due to the heterogeneity of machines and/or data and/or executed functions. Indeed, a longer execution time at a node does not slow down the execution at all the other nodes but only at the neighboring nodes. This is particularly advantageous when the nodes that act as bottlenecks vary during the application execution. The goal of the paper is to analyze the benefits that can be achieved with the described asynchronous implementation of cellular automata, when compared to the classical all-to-all synchronization pattern. The performance and scalability have been evaluated through a Petri net model, as this model is very useful to represent the synchronization barrier among nodes. We examined the usual case in which the territory is partitioned into a number of regions, and the computation associated with a region is assigned to a computing node. We considered both the cases of mono-dimensional and two-dimensional partitioning. The results show that the advantage obtained through the asynchronous execution, when compared to the all-to-all synchronous approach is notable, and it can be as large as 90% in terms of speedup.

Volume-scalable high-brightness three-dimensional visible light source

DOEpatents

Subramania, Ganapathi; Fischer, Arthur J; Wang, George T; Li, Qiming

2014-02-18

A volume-scalable, high-brightness, electrically driven visible light source comprises a three-dimensional photonic crystal (3DPC) comprising one or more direct bandgap semiconductors. The improved light emission performance of the invention is achieved based on the enhancement of radiative emission of light emitters placed inside a 3DPC due to the strong modification of the photonic density-of-states engendered by the 3DPC.

Scalable graphene production: perspectives and challenges of plasma applications

NASA Astrophysics Data System (ADS)

Levchenko, Igor; Ostrikov, Kostya (Ken); Zheng, Jie; Li, Xingguo; Keidar, Michael; B. K. Teo, Kenneth

2016-05-01

Graphene, a newly discovered and extensively investigated material, has many unique and extraordinary properties which promise major technological advances in fields ranging from electronics to mechanical engineering and food production. Unfortunately, complex techniques and high production costs hinder commonplace applications. Scaling of existing graphene production techniques to the industrial level without compromising its properties is a current challenge. This article focuses on the perspectives and challenges of scalability, equipment, and technological perspectives of the plasma-based techniques which offer many unique possibilities for the synthesis of graphene and graphene-containing products. The plasma-based processes are amenable for scaling and could also be useful to enhance the controllability of the conventional chemical vapour deposition method and some other techniques, and to ensure a good quality of the produced graphene. We examine the unique features of the plasma-enhanced graphene production approaches, including the techniques based on inductively-coupled and arc discharges, in the context of their potential scaling to mass production following the generic scaling approaches applicable to the existing processes and systems. This work analyses a large amount of the recent literature on graphene production by various techniques and summarizes the results in a tabular form to provide a simple and convenient comparison of several available techniques. Our analysis reveals a significant potential of scalability for plasma-based technologies, based on the scaling-related process characteristics. Among other processes, a greater yield of 1 g × h-1 m-2 was reached for the arc discharge technology, whereas the other plasma-based techniques show process yields comparable to the neutral-gas based methods. Selected plasma-based techniques show lower energy consumption than in thermal CVD processes, and the ability to produce graphene flakes of various

Scalable graphene production: perspectives and challenges of plasma applications.

PubMed

Levchenko, Igor; Ostrikov, Kostya Ken; Zheng, Jie; Li, Xingguo; Keidar, Michael; B K Teo, Kenneth

2016-05-19

Graphene, a newly discovered and extensively investigated material, has many unique and extraordinary properties which promise major technological advances in fields ranging from electronics to mechanical engineering and food production. Unfortunately, complex techniques and high production costs hinder commonplace applications. Scaling of existing graphene production techniques to the industrial level without compromising its properties is a current challenge. This article focuses on the perspectives and challenges of scalability, equipment, and technological perspectives of the plasma-based techniques which offer many unique possibilities for the synthesis of graphene and graphene-containing products. The plasma-based processes are amenable for scaling and could also be useful to enhance the controllability of the conventional chemical vapour deposition method and some other techniques, and to ensure a good quality of the produced graphene. We examine the unique features of the plasma-enhanced graphene production approaches, including the techniques based on inductively-coupled and arc discharges, in the context of their potential scaling to mass production following the generic scaling approaches applicable to the existing processes and systems. This work analyses a large amount of the recent literature on graphene production by various techniques and summarizes the results in a tabular form to provide a simple and convenient comparison of several available techniques. Our analysis reveals a significant potential of scalability for plasma-based technologies, based on the scaling-related process characteristics. Among other processes, a greater yield of 1 g × h(-1) m(-2) was reached for the arc discharge technology, whereas the other plasma-based techniques show process yields comparable to the neutral-gas based methods. Selected plasma-based techniques show lower energy consumption than in thermal CVD processes, and the ability to produce graphene flakes of

Advanced technologies for scalable ATLAS conditions database access on the grid

NASA Astrophysics Data System (ADS)

Basset, R.; Canali, L.; Dimitrov, G.; Girone, M.; Hawkings, R.; Nevski, P.; Valassi, A.; Vaniachine, A.; Viegas, F.; Walker, R.; Wong, A.

2010-04-01

During massive data reprocessing operations an ATLAS Conditions Database application must support concurrent access from numerous ATLAS data processing jobs running on the Grid. By simulating realistic work-flow, ATLAS database scalability tests provided feedback for Conditions Db software optimization and allowed precise determination of required distributed database resources. In distributed data processing one must take into account the chaotic nature of Grid computing characterized by peak loads, which can be much higher than average access rates. To validate database performance at peak loads, we tested database scalability at very high concurrent jobs rates. This has been achieved through coordinated database stress tests performed in series of ATLAS reprocessing exercises at the Tier-1 sites. The goal of database stress tests is to detect scalability limits of the hardware deployed at the Tier-1 sites, so that the server overload conditions can be safely avoided in a production environment. Our analysis of server performance under stress tests indicates that Conditions Db data access is limited by the disk I/O throughput. An unacceptable side-effect of the disk I/O saturation is a degradation of the WLCG 3D Services that update Conditions Db data at all ten ATLAS Tier-1 sites using the technology of Oracle Streams. To avoid such bottlenecks we prototyped and tested a novel approach for database peak load avoidance in Grid computing. Our approach is based upon the proven idea of pilot job submission on the Grid: instead of the actual query, an ATLAS utility library sends to the database server a pilot query first.

Efficient scalable solid-state neutron detector.

PubMed

Moses, Daniel

2015-06-01

We report on scalable solid-state neutron detector system that is specifically designed to yield high thermal neutron detection sensitivity. The basic detector unit in this system is made of a (6)Li foil coupled to two crystalline silicon diodes. The theoretical intrinsic efficiency of a detector-unit is 23.8% and that of detector element comprising a stack of five detector-units is 60%. Based on the measured performance of this detector-unit, the performance of a detector system comprising a planar array of detector elements, scaled to encompass effective area of 0.43 m(2), is estimated to yield the minimum absolute efficiency required of radiological portal monitors used in homeland security.

Scalable graphene aptasensors for drug quantification

NASA Astrophysics Data System (ADS)

Vishnubhotla, Ramya; Ping, Jinglei; Gao, Zhaoli; Lee, Abigail; Saouaf, Olivia; Vrudhula, Amey; Johnson, A. T. Charlie

2017-11-01

Simpler and more rapid approaches for therapeutic drug-level monitoring are highly desirable to enable use at the point-of-care. We have developed an all-electronic approach for detection of the HIV drug tenofovir based on scalable fabrication of arrays of graphene field-effect transistors (GFETs) functionalized with a commercially available DNA aptamer. The shift in the Dirac voltage of the GFETs varied systematically with the concentration of tenofovir in deionized water, with a detection limit less than 1 ng/mL. Tests against a set of negative controls confirmed the specificity of the sensor response. This approach offers the potential for further development into a rapid and convenient point-of-care tool with clinically relevant performance.

Visualizing Human Migration Trhough Space and Time

NASA Astrophysics Data System (ADS)

Zambotti, G.; Guan, W.; Gest, J.

2015-07-01

Human migration has been an important activity in human societies since antiquity. Since 1890, approximately three percent of the world's population has lived outside of their country of origin. As globalization intensifies in the modern era, human migration persists even as governments seek to more stringently regulate flows. Understanding this phenomenon, its causes, processes and impacts often starts from measuring and visualizing its spatiotemporal patterns. This study builds a generic online platform for users to interactively visualize human migration through space and time. This entails quickly ingesting human migration data in plain text or tabular format; matching the records with pre-established geographic features such as administrative polygons; symbolizing the migration flow by circular arcs of varying color and weight based on the flow attributes; connecting the centroids of the origin and destination polygons; and allowing the user to select either an origin or a destination feature to display all flows in or out of that feature through time. The method was first developed using ArcGIS Server for world-wide cross-country migration, and later applied to visualizing domestic migration patterns within China between provinces, and between states in the United States, all through multiple years. The technical challenges of this study include simplifying the shapes of features to enhance user interaction, rendering performance and application scalability; enabling the temporal renderers to provide time-based rendering of features and the flow among them; and developing a responsive web design (RWD) application to provide an optimal viewing experience. The platform is available online for the public to use, and the methodology is easily adoptable to visualizing any flow, not only human migration but also the flow of goods, capital, disease, ideology, etc., between multiple origins and destinations across space and time.

'tomo_display' and 'vol_tools': IDL VM Packages for Tomography Data Reconstruction, Processing, and Visualization

NASA Astrophysics Data System (ADS)

Rivers, M. L.; Gualda, G. A.

2009-05-01

One of the challenges in tomography is the availability of suitable software for image processing and analysis in 3D. We present here 'tomo_display' and 'vol_tools', two packages created in IDL that enable reconstruction, processing, and visualization of tomographic data. They complement in many ways the capabilities offered by Blob3D (Ketcham 2005 - Geosphere, 1: 32-41, DOI: 10.1130/GES00001.1) and, in combination, allow users without programming knowledge to perform all steps necessary to obtain qualitative and quantitative information using tomographic data. The package 'tomo_display' was created and is maintained by Mark Rivers. It allows the user to: (1) preprocess and reconstruct parallel beam tomographic data, including removal of anomalous pixels, ring artifact reduction, and automated determination of the rotation center, (2) visualization of both raw and reconstructed data, either as individual frames, or as a series of sequential frames. The package 'vol_tools' consists of a series of small programs created and maintained by Guilherme Gualda to perform specific tasks not included in other packages. Existing modules include simple tools for cropping volumes, generating histograms of intensity, sample volume measurement (useful for porous samples like pumice), and computation of volume differences (for differential absorption tomography). The module 'vol_animate' can be used to generate 3D animations using rendered isosurfaces around objects. Both packages use the same NetCDF format '.volume' files created using code written by Mark Rivers. Currently, only 16-bit integer volumes are created and read by the packages, but floating point and 8-bit data can easily be stored in the NetCDF format as well. A simple GUI to convert sequences of tiffs into '.volume' files is available within 'vol_tools'. Both 'tomo_display' and 'vol_tools' include options to (1) generate onscreen output that allows for dynamic visualization in 3D, (2) save sequences of tiffs to disk

Scalable and sustainable electrochemical allylic C-H oxidation

NASA Astrophysics Data System (ADS)

Horn, Evan J.; Rosen, Brandon R.; Chen, Yong; Tang, Jiaze; Chen, Ke; Eastgate, Martin D.; Baran, Phil S.

2016-05-01

New methods and strategies for the direct functionalization of C-H bonds are beginning to reshape the field of retrosynthetic analysis, affecting the synthesis of natural products, medicines and materials. The oxidation of allylic systems has played a prominent role in this context as possibly the most widely applied C-H functionalization, owing to the utility of enones and allylic alcohols as versatile intermediates, and their prevalence in natural and unnatural materials. Allylic oxidations have featured in hundreds of syntheses, including some natural product syntheses regarded as “classics”. Despite many attempts to improve the efficiency and practicality of this transformation, the majority of conditions still use highly toxic reagents (based around toxic elements such as chromium or selenium) or expensive catalysts (such as palladium or rhodium). These requirements are problematic in industrial settings; currently, no scalable and sustainable solution to allylic oxidation exists. This oxidation strategy is therefore rarely used for large-scale synthetic applications, limiting the adoption of this retrosynthetic strategy by industrial scientists. Here we describe an electrochemical C-H oxidation strategy that exhibits broad substrate scope, operational simplicity and high chemoselectivity. It uses inexpensive and readily available materials, and represents a scalable allylic C-H oxidation (demonstrated on 100 grams), enabling the adoption of this C-H oxidation strategy in large-scale industrial settings without substantial environmental impact.

GPU accelerated particle visualization with Splotch

NASA Astrophysics Data System (ADS)

Rivi, M.; Gheller, C.; Dykes, T.; Krokos, M.; Dolag, K.

2014-07-01

Splotch is a rendering algorithm for exploration and visual discovery in particle-based datasets coming from astronomical observations or numerical simulations. The strengths of the approach are production of high quality imagery and support for very large-scale datasets through an effective mix of the OpenMP and MPI parallel programming paradigms. This article reports our experiences in re-designing Splotch for exploiting emerging HPC architectures nowadays increasingly populated with GPUs. A performance model is introduced to guide our re-factoring of Splotch. A number of parallelization issues are discussed, in particular relating to race conditions and workload balancing, towards achieving optimal performances. Our implementation was accomplished by using the CUDA programming paradigm. Our strategy is founded on novel schemes achieving optimized data organization and classification of particles. We deploy a reference cosmological simulation to present performance results on acceleration gains and scalability. We finally outline our vision for future work developments including possibilities for further optimizations and exploitation of hybrid systems and emerging accelerators.

3D visualization of ultra-fine ICON climate simulation data

NASA Astrophysics Data System (ADS)

Röber, Niklas; Spickermann, Dela; Böttinger, Michael

2016-04-01

Advances in high performance computing and model development allow the simulation of finer and more detailed climate experiments. The new ICON model is based on an unstructured triangular grid and can be used for a wide range of applications, ranging from global coupled climate simulations down to very detailed and high resolution regional experiments. It consists of an atmospheric and an oceanic component and scales very well for high numbers of cores. This allows us to conduct very detailed climate experiments with ultra-fine resolutions. ICON is jointly developed in partnership with DKRZ by the Max Planck Institute for Meteorology and the German Weather Service. This presentation discusses our current workflow for analyzing and visualizing this high resolution data. The ICON model has been used for eddy resolving (<10km) ocean simulations, as well as for ultra-fine cloud resolving (120m) atmospheric simulations. This results in very large 3D time dependent multi-variate data that need to be displayed and analyzed. We have developed specific plugins for the free available visualization software ParaView and Vapor, which allows us to read and handle that much data. Within ParaView, we can additionally compare prognostic variables with performance data side by side to investigate the performance and scalability of the model. With the simulation running in parallel on several hundred nodes, an equal load balance is imperative. In our presentation we show visualizations of high-resolution ICON oceanographic and HDCP2 atmospheric simulations that were created using ParaView and Vapor. Furthermore we discuss our current efforts to improve our visualization capabilities, thereby exploring the potential of regular in-situ visualization, as well as of in-situ compression / post visualization.

Intrinsically Stretchable and Conductive Textile by a Scalable Process for Elastic Wearable Electronics.

PubMed

Wang, Chunya; Zhang, Mingchao; Xia, Kailun; Gong, Xueqin; Wang, Huimin; Yin, Zhe; Guan, Baolu; Zhang, Yingying

2017-04-19

The prosperous development of stretchable electronics poses a great demand on stretchable conductive materials that could maintain their electrical conductivity under tensile strain. Previously reported strategies to obtain stretchable conductors usually involve complex structure-fabricating processes or utilization of high-cost nanomaterials. It remains a great challenge to produce stretchable and conductive materials via a scalable and cost-effective process. Herein, a large-scalable pyrolysis strategy is developed for the fabrication of intrinsically stretchable and conductive textile in utilizing low-cost and mass-produced weft-knitted textiles as raw materials. Due to the intrinsic stretchability of the weft-knitted structure and the excellent mechanical and electrical properties of the as-obtained carbonized fibers, the obtained flexible and durable textile could sustain tensile strains up to 125% while keeping a stable electrical conductivity (as shown by a Modal-based textile), thus ensuring its applications in elastic electronics. For demonstration purposes, stretchable supercapacitors and wearable thermal-therapy devices that showed stable performance with the loading of tensile strains have been fabricated. Considering the simplicity and large scalability of the process, the low-cost and mass production of the raw materials, and the superior performances of the as-obtained elastic and conductive textile, this strategy would contribute to the development and industrial production of wearable electronics.

A Secure and Efficient Scalable Secret Image Sharing Scheme with Flexible Shadow Sizes

PubMed Central

Xie, Dong; Li, Lixiang; Peng, Haipeng; Yang, Yixian

2017-01-01

In a general (k, n) scalable secret image sharing (SSIS) scheme, the secret image is shared by n participants and any k or more than k participants have the ability to reconstruct it. The scalability means that the amount of information in the reconstructed image scales in proportion to the number of the participants. In most existing SSIS schemes, the size of each image shadow is relatively large and the dealer does not has a flexible control strategy to adjust it to meet the demand of differen applications. Besides, almost all existing SSIS schemes are not applicable under noise circumstances. To address these deficiencies, in this paper we present a novel SSIS scheme based on a brand-new technique, called compressed sensing, which has been widely used in many fields such as image processing, wireless communication and medical imaging. Our scheme has the property of flexibility, which means that the dealer can achieve a compromise between the size of each shadow and the quality of the reconstructed image. In addition, our scheme has many other advantages, including smooth scalability, noise-resilient capability, and high security. The experimental results and the comparison with similar works demonstrate the feasibility and superiority of our scheme. PMID:28072851

A Secure and Efficient Scalable Secret Image Sharing Scheme with Flexible Shadow Sizes.

PubMed

Xie, Dong; Li, Lixiang; Peng, Haipeng; Yang, Yixian

2017-01-01

In a general (k, n) scalable secret image sharing (SSIS) scheme, the secret image is shared by n participants and any k or more than k participants have the ability to reconstruct it. The scalability means that the amount of information in the reconstructed image scales in proportion to the number of the participants. In most existing SSIS schemes, the size of each image shadow is relatively large and the dealer does not has a flexible control strategy to adjust it to meet the demand of differen applications. Besides, almost all existing SSIS schemes are not applicable under noise circumstances. To address these deficiencies, in this paper we present a novel SSIS scheme based on a brand-new technique, called compressed sensing, which has been widely used in many fields such as image processing, wireless communication and medical imaging. Our scheme has the property of flexibility, which means that the dealer can achieve a compromise between the size of each shadow and the quality of the reconstructed image. In addition, our scheme has many other advantages, including smooth scalability, noise-resilient capability, and high security. The experimental results and the comparison with similar works demonstrate the feasibility and superiority of our scheme.

Scalable software architecture for on-line multi-camera video processing

NASA Astrophysics Data System (ADS)

Camplani, Massimo; Salgado, Luis

2011-03-01

In this paper we present a scalable software architecture for on-line multi-camera video processing, that guarantees a good trade off between computational power, scalability and flexibility. The software system is modular and its main blocks are the Processing Units (PUs), and the Central Unit. The Central Unit works as a supervisor of the running PUs and each PU manages the acquisition phase and the processing phase. Furthermore, an approach to easily parallelize the desired processing application has been presented. In this paper, as case study, we apply the proposed software architecture to a multi-camera system in order to efficiently manage multiple 2D object detection modules in a real-time scenario. System performance has been evaluated under different load conditions such as number of cameras and image sizes. The results show that the software architecture scales well with the number of camera and can easily works with different image formats respecting the real time constraints. Moreover, the parallelization approach can be used in order to speed up the processing tasks with a low level of overhead.

Programming time-multiplexed reconfigurable hardware using a scalable neuromorphic compiler.

PubMed

Minkovich, Kirill; Srinivasa, Narayan; Cruz-Albrecht, Jose M; Cho, Youngkwan; Nogin, Aleksey

2012-06-01

Scalability and connectivity are two key challenges in designing neuromorphic hardware that can match biological levels. In this paper, we describe a neuromorphic system architecture design that addresses an approach to meet these challenges using traditional complementary metal-oxide-semiconductor (CMOS) hardware. A key requirement in realizing such neural architectures in hardware is the ability to automatically configure the hardware to emulate any neural architecture or model. The focus for this paper is to describe the details of such a programmable front-end. This programmable front-end is composed of a neuromorphic compiler and a digital memory, and is designed based on the concept of synaptic time-multiplexing (STM). The neuromorphic compiler automatically translates any given neural architecture to hardware switch states and these states are stored in digital memory to enable desired neural architectures. STM enables our proposed architecture to address scalability and connectivity using traditional CMOS hardware. We describe the details of the proposed design and the programmable front-end, and provide examples to illustrate its capabilities. We also provide perspectives for future extensions and potential applications.

Simplex-stochastic collocation method with improved scalability

NASA Astrophysics Data System (ADS)

Edeling, W. N.; Dwight, R. P.; Cinnella, P.

2016-04-01

The Simplex-Stochastic Collocation (SSC) method is a robust tool used to propagate uncertain input distributions through a computer code. However, it becomes prohibitively expensive for problems with dimensions higher than 5. The main purpose of this paper is to identify bottlenecks, and to improve upon this bad scalability. In order to do so, we propose an alternative interpolation stencil technique based upon the Set-Covering problem, and we integrate the SSC method in the High-Dimensional Model-Reduction framework. In addition, we address the issue of ill-conditioned sample matrices, and we present an analytical map to facilitate uniformly-distributed simplex sampling.

Software complex for geophysical data visualization

NASA Astrophysics Data System (ADS)

Kryukov, Ilya A.; Tyugin, Dmitry Y.; Kurkin, Andrey A.; Kurkina, Oxana E.

2013-04-01

feature of geophysical data is their size. Detailed maps used in the simulations are large, thus rendering in real time can be difficult task even for powerful modern computers. Therefore, the performance of the software complex is an important aspect of this work. Complex is based on the latest version of graphic API: Microsoft - DirectX 11, which reduces overhead and harness the power of modern hardware. Each geophysical calculation is the adjustment of the mathematical model for a particular case, so the architecture of the complex visualization is created with the scalability and the ability to customize visualization objects, for better visibility and comfort. In the present study, software complex 'GeoVisual' was developed. One of the main features of this research is the use of bleeding-edge techniques of computer graphics in scientific visualization. The research was supported by The Ministry of education and science of Russian Federation, project 14.B37.21.0642.

VisANT 3.0: new modules for pathway visualization, editing, prediction and construction.

PubMed

Hu, Zhenjun; Ng, David M; Yamada, Takuji; Chen, Chunnuan; Kawashima, Shuichi; Mellor, Joe; Linghu, Bolan; Kanehisa, Minoru; Stuart, Joshua M; DeLisi, Charles

2007-07-01

With the integration of the KEGG and Predictome databases as well as two search engines for coexpressed genes/proteins using data sets obtained from the Stanford Microarray Database (SMD) and Gene Expression Omnibus (GEO) database, VisANT 3.0 supports exploratory pathway analysis, which includes multi-scale visualization of multiple pathways, editing and annotating pathways using a KEGG compatible visual notation and visualization of expression data in the context of pathways. Expression levels are represented either by color intensity or by nodes with an embedded expression profile. Multiple experiments can be navigated or animated. Known KEGG pathways can be enriched by querying either coexpressed components of known pathway members or proteins with known physical interactions. Predicted pathways for genes/proteins with unknown functions can be inferred from coexpression or physical interaction data. Pathways produced in VisANT can be saved as computer-readable XML format (VisML), graphic images or high-resolution Scalable Vector Graphics (SVG). Pathways in the format of VisML can be securely shared within an interested group or published online using a simple Web link. VisANT is freely available at http://visant.bu.edu.

Network selection, Information filtering and Scalable computation

NASA Astrophysics Data System (ADS)

Ye, Changqing

-complete factorizations, possibly with a high percentage of missing values. This promotes additional sparsity beyond rank reduction. Computationally, we design methods based on a ``decomposition and combination'' strategy, to break large-scale optimization into many small subproblems to solve in a recursive and parallel manner. On this basis, we implement the proposed methods through multi-platform shared-memory parallel programming, and through Mahout, a library for scalable machine learning and data mining, for mapReduce computation. For example, our methods are scalable to a dataset consisting of three billions of observations on a single machine with sufficient memory, having good timings. Both theoretical and numerical investigations show that the proposed methods exhibit significant improvement in accuracy over state-of-the-art scalable methods.

Assessment of the scalability of a microtiter plate system for screening of oleaginous microorganisms.

PubMed

Kosa, Gergely; Vuoristo, Kiira S; Horn, Svein Jarle; Zimmermann, Boris; Afseth, Nils Kristian; Kohler, Achim; Shapaval, Volha

2018-06-01

Recent developments in molecular biology and metabolic engineering have resulted in a large increase in the number of strains that need to be tested, positioning high-throughput screening of microorganisms as an important step in bioprocess development. Scalability is crucial for performing reliable screening of microorganisms. Most of the scalability studies from microplate screening systems to controlled stirred-tank bioreactors have been performed so far with unicellular microorganisms. We have compared cultivation of industrially relevant oleaginous filamentous fungi and microalga in a Duetz-microtiter plate system to benchtop and pre-pilot bioreactors. Maximal glucose consumption rate, biomass concentration, lipid content of the biomass, biomass, and lipid yield values showed good scalability for Mucor circinelloides (less than 20% differences) and Mortierella alpina (less than 30% differences) filamentous fungi. Maximal glucose consumption and biomass production rates were identical for Crypthecodinium cohnii in microtiter plate and benchtop bioreactor. Most likely due to shear stress sensitivity of this microalga in stirred bioreactor, biomass concentration and lipid content of biomass were significantly higher in the microtiter plate system than in the benchtop bioreactor. Still, fermentation results obtained in the Duetz-microtiter plate system for Crypthecodinium cohnii are encouraging compared to what has been reported in literature. Good reproducibility (coefficient of variation less than 15% for biomass growth, glucose consumption, lipid content, and pH) were achieved in the Duetz-microtiter plate system for Mucor circinelloides and Crypthecodinium cohnii. Mortierella alpina cultivation reproducibility might be improved with inoculation optimization. In conclusion, we have presented suitability of the Duetz-microtiter plate system for the reproducible, scalable, and cost-efficient high-throughput screening of oleaginous microorganisms.

Optimized bit extraction using distortion modeling in the scalable extension of H.264/AVC.

PubMed

Maani, Ehsan; Katsaggelos, Aggelos K

2009-09-01

The newly adopted scalable extension of H.264/AVC video coding standard (SVC) demonstrates significant improvements in coding efficiency in addition to an increased degree of supported scalability relative to the scalable profiles of prior video coding standards. Due to the complicated hierarchical prediction structure of the SVC and the concept of key pictures, content-aware rate adaptation of SVC bit streams to intermediate bit rates is a nontrivial task. The concept of quality layers has been introduced in the design of the SVC to allow for fast content-aware prioritized rate adaptation. However, existing quality layer assignment methods are suboptimal and do not consider all network abstraction layer (NAL) units from different layers for the optimization. In this paper, we first propose a technique to accurately and efficiently estimate the quality degradation resulting from discarding an arbitrary number of NAL units from multiple layers of a bitstream by properly taking drift into account. Then, we utilize this distortion estimation technique to assign quality layers to NAL units for a more efficient extraction. Experimental results show that a significant gain can be achieved by the proposed scheme.

Scalable Generation of Universal Platelets from Human Induced Pluripotent Stem Cells

PubMed Central

Feng, Qiang; Shabrani, Namrata; Thon, Jonathan N.; Huo, Hongguang; Thiel, Austin; Machlus, Kellie R.; Kim, Kyungho; Brooks, Julie; Li, Feng; Luo, Chenmei; Kimbrel, Erin A.; Wang, Jiwu; Kim, Kwang-Soo; Italiano, Joseph; Cho, Jaehyung; Lu, Shi-Jiang; Lanza, Robert

2014-01-01

Summary Human induced pluripotent stem cells (iPSCs) provide a potentially replenishable source for the production of transfusable platelets. Here, we describe a method to generate megakaryocytes (MKs) and functional platelets from iPSCs in a scalable manner under serum/feeder-free conditions. The method also permits the cryopreservation of MK progenitors, enabling a rapid “surge” capacity when large numbers of platelets are needed. Ultrastructural/morphological analyses show no major differences between iPSC platelets and human blood platelets. iPSC platelets form aggregates, lamellipodia, and filopodia after activation and circulate in macrophage-depleted animals and incorporate into developing mouse thrombi in a manner identical to human platelets. By knocking out the β2-microglobulin gene, we have generated platelets that are negative for the major histocompatibility antigens. The scalable generation of HLA-ABC-negative platelets from a renewable cell source represents an important step toward generating universal platelets for transfusion as well as a potential strategy for the management of platelet refractoriness. PMID:25418726

Scalable generation of universal platelets from human induced pluripotent stem cells.

PubMed

Feng, Qiang; Shabrani, Namrata; Thon, Jonathan N; Huo, Hongguang; Thiel, Austin; Machlus, Kellie R; Kim, Kyungho; Brooks, Julie; Li, Feng; Luo, Chenmei; Kimbrel, Erin A; Wang, Jiwu; Kim, Kwang-Soo; Italiano, Joseph; Cho, Jaehyung; Lu, Shi-Jiang; Lanza, Robert

2014-11-11

Human induced pluripotent stem cells (iPSCs) provide a potentially replenishable source for the production of transfusable platelets. Here, we describe a method to generate megakaryocytes (MKs) and functional platelets from iPSCs in a scalable manner under serum/feeder-free conditions. The method also permits the cryopreservation of MK progenitors, enabling a rapid "surge" capacity when large numbers of platelets are needed. Ultrastructural/morphological analyses show no major differences between iPSC platelets and human blood platelets. iPSC platelets form aggregates, lamellipodia, and filopodia after activation and circulate in macrophage-depleted animals and incorporate into developing mouse thrombi in a manner identical to human platelets. By knocking out the β2-microglobulin gene, we have generated platelets that are negative for the major histocompatibility antigens. The scalable generation of HLA-ABC-negative platelets from a renewable cell source represents an important step toward generating universal platelets for transfusion as well as a potential strategy for the management of platelet refractoriness.

Scalable electrophysiology in intact small animals with nanoscale suspended electrode arrays

NASA Astrophysics Data System (ADS)

Gonzales, Daniel L.; Badhiwala, Krishna N.; Vercosa, Daniel G.; Avants, Benjamin W.; Liu, Zheng; Zhong, Weiwei; Robinson, Jacob T.

2017-07-01

Electrical measurements from large populations of animals would help reveal fundamental properties of the nervous system and neurological diseases. Small invertebrates are ideal for these large-scale studies; however, patch-clamp electrophysiology in microscopic animals typically requires invasive dissections and is low-throughput. To overcome these limitations, we present nano-SPEARs: suspended electrodes integrated into a scalable microfluidic device. Using this technology, we have made the first extracellular recordings of body-wall muscle electrophysiology inside an intact roundworm, Caenorhabditis elegans. We can also use nano-SPEARs to record from multiple animals in parallel and even from other species, such as Hydra littoralis. Furthermore, we use nano-SPEARs to establish the first electrophysiological phenotypes for C. elegans models for amyotrophic lateral sclerosis and Parkinson's disease, and show a partial rescue of the Parkinson's phenotype through drug treatment. These results demonstrate that nano-SPEARs provide the core technology for microchips that enable scalable, in vivo studies of neurobiology and neurological diseases.

Parallel and Scalable Clustering and Classification for Big Data in Geosciences

NASA Astrophysics Data System (ADS)

Riedel, M.

2015-12-01

Machine learning, data mining, and statistical computing are common techniques to perform analysis in earth sciences. This contribution will focus on two concrete and widely used data analytics methods suitable to analyse 'big data' in the context of geoscience use cases: clustering and classification. From the broad class of available clustering methods we focus on the density-based spatial clustering of appliactions with noise (DBSCAN) algorithm that enables the identification of outliers or interesting anomalies. A new open source parallel and scalable DBSCAN implementation will be discussed in the light of a scientific use case that detects water mixing events in the Koljoefjords. The second technique we cover is classification, with a focus set on the support vector machines algorithm (SVMs), as one of the best out-of-the-box classification algorithm. A parallel and scalable SVM implementation will be discussed in the light of a scientific use case in the field of remote sensing with 52 different classes of land cover types.

A Scalable Software Architecture Booting and Configuring Nodes in the Whitney Commodity Computing Testbed

NASA Technical Reports Server (NTRS)

Fineberg, Samuel A.; Kutler, Paul (Technical Monitor)

1997-01-01

The Whitney project is integrating commodity off-the-shelf PC hardware and software technology to build a parallel supercomputer with hundreds to thousands of nodes. To build such a system, one must have a scalable software model, and the installation and maintenance of the system software must be completely automated. We describe the design of an architecture for booting, installing, and configuring nodes in such a system with particular consideration given to scalability and ease of maintenance. This system has been implemented on a 40-node prototype of Whitney and is to be used on the 500 processor Whitney system to be built in 1998.

Interface-Free Area-Scalable Self-Powered Electroluminescent System Driven by Triboelectric Generator

PubMed Central

Yan Wei, Xiao; Kuang, Shuang Yang; Yang Li, Hua; Pan, Caofeng; Zhu, Guang; Wang, Zhong Lin

2015-01-01

Self-powered system that is interface-free is greatly desired for area-scalable application. Here we report a self-powered electroluminescent system that consists of a triboelectric generator (TEG) and a thin-film electroluminescent (TFEL) lamp. The TEG provides high-voltage alternating electric output, which fits in well with the needs of the TFEL lamp. Induced charges pumped onto the lamp by the TEG generate an electric field that is sufficient to excite luminescence without an electrical interface circuit. Through rational serial connection of multiple TFEL lamps, effective and area-scalable luminescence is realized. It is demonstrated that multiple types of TEGs are applicable to the self-powered system, indicating that the system can make use of diverse mechanical sources and thus has potentially broad applications in illumination, display, entertainment, indication, surveillance and many others. PMID:26338365

Three-Dimensional Online Visualization and Engagement Tools for the Geosciences

NASA Astrophysics Data System (ADS)

Cockett, R.; Moran, T.; Pidlisecky, A.

2013-12-01

Educational tools often sacrifice interactivity in favour of scalability so they can reach more users. This compromise leads to tools that may be viewed as second tier when compared to more engaging activities performed in a laboratory; however, the resources required to deliver laboratory exercises that are scalable is often impractical. Geoscience education is well situated to benefit from interactive online learning tools that allow users to work in a 3D environment. Visible Geology (http://3ptscience.com/visiblegeology) is an innovative web-based application designed to enable visualization of geologic structures and processes through the use of interactive 3D models. The platform allows users to conceptualize difficult, yet important geologic principles in a scientifically accurate manner by developing unique geologic models. The environment allows students to interactively practice their visualization and interpretation skills by creating and interacting with their own models and terrains. Visible Geology has been designed from a user centric perspective resulting in a simple and intuitive interface. The platform directs students to build there own geologic models by adding beds and creating geologic events such as tilting, folding, or faulting. The level of ownership and interactivity encourages engagement, leading learners to discover geologic relationships on their own, in the context of guided assignments. In January 2013, an interactive geologic history assignment was developed for a 700-student introductory geology class at The University of British Columbia. The assignment required students to distinguish the relative age of geologic events to construct a geologic history. Traditionally this type of exercise has been taught through the use of simple geologic cross-sections showing crosscutting relationships; from these cross-sections students infer the relative age of geologic events. In contrast, the Visible Geology assignment offers students a unique

Scalable microcarrier-based manufacturing of mesenchymal stem/stromal cells.

PubMed

de Soure, António M; Fernandes-Platzgummer, Ana; da Silva, Cláudia L; Cabral, Joaquim M S

2016-10-20

Due to their unique features, mesenchymal stem/stromal cells (MSC) have been exploited in clinical settings as therapeutic candidates for the treatment of a variety of diseases. However, the success in obtaining clinically-relevant MSC numbers for cell-based therapies is dependent on efficient isolation and ex vivo expansion protocols, able to comply with good manufacturing practices (GMP). In this context, the 2-dimensional static culture systems typically used for the expansion of these cells present several limitations that may lead to reduced cell numbers and compromise cell functions. Furthermore, many studies in the literature report the expansion of MSC using fetal bovine serum (FBS)-supplemented medium, which has been critically rated by regulatory agencies. Alternative platforms for the scalable manufacturing of MSC have been developed, namely using microcarriers in bioreactors, with also a considerable number of studies now reporting the production of MSC using xenogeneic/serum-free medium formulations. In this review we provide a comprehensive overview on the scalable manufacturing of human mesenchymal stem/stromal cells, depicting the various steps involved in the process from cell isolation to ex vivo expansion, using different cell tissue sources and culture medium formulations and exploiting bioprocess engineering tools namely microcarrier technology and bioreactors. Copyright © 2016 Elsevier B.V. All rights reserved.

Scalable Nernst thermoelectric power using a coiled galfenol wire

NASA Astrophysics Data System (ADS)

Yang, Zihao; Codecido, Emilio A.; Marquez, Jason; Zheng, Yuanhua; Heremans, Joseph P.; Myers, Roberto C.

2017-09-01

The Nernst thermopower usually is considered far too weak in most metals for waste heat recovery. However, its transverse orientation gives it an advantage over the Seebeck effect on non-flat surfaces. Here, we experimentally demonstrate the scalable generation of a Nernst voltage in an air-cooled metal wire coiled around a hot cylinder. In this geometry, a radial temperature gradient generates an azimuthal electric field in the coil. A Galfenol (Fe0.85Ga0.15) wire is wrapped around a cartridge heater, and the voltage drop across the wire is measured as a function of axial magnetic field. As expected, the Nernst voltage scales linearly with the length of the wire. Based on heat conduction and fluid dynamic equations, finite-element method is used to calculate the temperature gradient across the Galfenol wire and determine the Nernst coefficient. A giant Nernst coefficient of -2.6 μV/KT at room temperature is estimated, in agreement with measurements on bulk Galfenol. We expect that the giant Nernst effect in Galfenol arises from its magnetostriction, presumably through enhanced magnon-phonon coupling. Our results demonstrate the feasibility of a transverse thermoelectric generator capable of scalable output power from non-flat heat sources.

Scalable Nanostructured Carbon Electrode Arrays for Enhanced Dopamine Detection.

PubMed

Demuru, Silvia; Nela, Luca; Marchack, Nathan; Holmes, Steven J; Farmer, Damon B; Tulevski, George S; Lin, Qinghuang; Deligianni, Hariklia

2018-04-27

Dopamine is a neurotransmitter that modulates arousal and motivation in humans and animals. It plays a central role in the brain "reward" system. Its dysregulation is involved in several debilitating disorders such as addiction, depression, Parkinson's disease, and schizophrenia. Dopamine neurotransmission and its reuptake in extracellular space takes place with millisecond temporal and nanometer spatial resolution. Novel nanoscale electrodes are needed with superior sensitivity and improved spatial resolution to gain an improved understanding of dopamine dysregulation. We report on a scalable fabrication of dopamine neurochemical probes of a nanostructured glassy carbon that is smaller than any existing dopamine sensor and arrays of more than 6000 nanorod probes. We also report on the electrochemical dopamine sensing of the glassy carbon nanorod electrode. Compared with a carbon fiber, the nanostructured glassy carbon nanorods provide about 2× higher sensitivity per unit area for dopamine sensing and more than 5× higher signal per unit area at low concentration of dopamine, with comparable LOD and time response. These glassy carbon nanorods were fabricated by pyrolysis of a lithographically defined polymeric nanostructure with an industry standard semiconductor fabrication infrastructure. The scalable fabrication strategy offers the potential to integrate these nanoscale carbon rods with an integrated circuit control system and with other complementary metal oxide semiconductor (CMOS) compatible sensors.

TreeVector: scalable, interactive, phylogenetic trees for the web.

PubMed

Pethica, Ralph; Barker, Gary; Kovacs, Tim; Gough, Julian

2010-01-28

Phylogenetic trees are complex data forms that need to be graphically displayed to be human-readable. Traditional techniques of plotting phylogenetic trees focus on rendering a single static image, but increases in the production of biological data and large-scale analyses demand scalable, browsable, and interactive trees. We introduce TreeVector, a Scalable Vector Graphics-and Java-based method that allows trees to be integrated and viewed seamlessly in standard web browsers with no extra software required, and can be modified and linked using standard web technologies. There are now many bioinformatics servers and databases with a range of dynamic processes and updates to cope with the increasing volume of data. TreeVector is designed as a framework to integrate with these processes and produce user-customized phylogenies automatically. We also address the strengths of phylogenetic trees as part of a linked-in browsing process rather than an end graphic for print. TreeVector is fast and easy to use and is available to download precompiled, but is also open source. It can also be run from the web server listed below or the user's own web server. It has already been deployed on two recognized and widely used database Web sites.

Scalable Data Management, Analysis, and Visualization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shen, Han-Wei

This report is the entire final report for the SciDAC project authored by the whole team. OSU is part of the contributors to the report. This report is organized into sections and subsections, each covering an area of development and deployment of technologies applied to scientific applications of interest to the Department of Energy. Each sub-section includes: 1) a summary description of the research, development, and deployment carried out, the results and the extent to which the stated project objectives were met; 2) significant results, including major findings, developments, or conclusions; 3) products, such as publications and presentations, software developed,more » project website(s), technologies or techniques, inventions, awards, etc., and 4) conclusions of the projects and future directions for research, development, and deployment in this technology area.« less

Scalable Multicast Protocols for Overlapped Groups in Broker-Based Sensor Networks

NASA Astrophysics Data System (ADS)

Kim, Chayoung; Ahn, Jinho

In sensor networks, there are lots of overlapped multicast groups because of many subscribers, associated with their potentially varying specific interests, querying every event to sensors/publishers. And gossip based communication protocols are promising as one of potential solutions providing scalability in P(Publish)/ S(Subscribe) paradigm in sensor networks. Moreover, despite the importance of both guaranteeing message delivery order and supporting overlapped multicast groups in sensor or P2P networks, there exist little research works on development of gossip-based protocols to satisfy all these requirements. In this paper, we present two versions of causally ordered delivery guaranteeing protocols for overlapped multicast groups. The one is based on sensor-broker as delegates and the other is based on local views and delegates representing subscriber subgroups. In the sensor-broker based protocol, sensor-broker might lead to make overlapped multicast networks organized by subscriber's interests. The message delivery order has been guaranteed consistently and all multicast messages are delivered to overlapped subscribers using gossip based protocols by sensor-broker. Therefore, these features of the sensor-broker based protocol might be significantly scalable rather than those of the protocols by hierarchical membership list of dedicated groups like traditional committee protocols. And the subscriber-delegate based protocol is much stronger rather than fully decentralized protocols guaranteeing causally ordered delivery based on only local views because the message delivery order has been guaranteed consistently by all corresponding members of the groups including delegates. Therefore, this feature of the subscriber-delegate protocol is a hybrid approach improving the inherent scalability of multicast nature by gossip-based technique in all communications.

XCluSim: a visual analytics tool for interactively comparing multiple clustering results of bioinformatics data

PubMed Central

2015-01-01

Background Though cluster analysis has become a routine analytic task for bioinformatics research, it is still arduous for researchers to assess the quality of a clustering result. To select the best clustering method and its parameters for a dataset, researchers have to run multiple clustering algorithms and compare them. However, such a comparison task with multiple clustering results is cognitively demanding and laborious. Results In this paper, we present XCluSim, a visual analytics tool that enables users to interactively compare multiple clustering results based on the Visual Information Seeking Mantra. We build a taxonomy for categorizing existing techniques of clustering results visualization in terms of the Gestalt principles of grouping. Using the taxonomy, we choose the most appropriate interactive visualizations for presenting individual clustering results from different types of clustering algorithms. The efficacy of XCluSim is shown through case studies with a bioinformatician. Conclusions Compared to other relevant tools, XCluSim enables users to compare multiple clustering results in a more scalable manner. Moreover, XCluSim supports diverse clustering algorithms and dedicated visualizations and interactions for different types of clustering results, allowing more effective exploration of details on demand. Through case studies with a bioinformatics researcher, we received positive feedback on the functionalities of XCluSim, including its ability to help identify stably clustered items across multiple clustering results. PMID:26328893

Scalable algorithms for 3D extended MHD.

NASA Astrophysics Data System (ADS)

Chacon, Luis

2007-11-01

In the modeling of plasmas with extended MHD (XMHD), the challenge is to resolve long time scales while rendering the whole simulation manageable. In XMHD, this is particularly difficult because fast (dispersive) waves are supported, resulting in a very stiff set of PDEs. In explicit schemes, such stiffness results in stringent numerical stability time-step constraints, rendering them inefficient and algorithmically unscalable. In implicit schemes, it yields very ill-conditioned algebraic systems, which are difficult to invert. In this talk, we present recent theoretical and computational progress that demonstrate a scalable 3D XMHD solver (i.e., CPU ˜N, with N the number of degrees of freedom). The approach is based on Newton-Krylov methods, which are preconditioned for efficiency. The preconditioning stage admits suitable approximations without compromising the quality of the overall solution. In this work, we employ optimal (CPU ˜N) multilevel methods on a parabolized XMHD formulation, which renders the whole algorithm scalable. The (crucial) parabolization step is required to render XMHD multilevel-friendly. Algebraically, the parabolization step can be interpreted as a Schur factorization of the Jacobian matrix, thereby providing a solid foundation for the current (and future extensions of the) approach. We will build towards 3D extended MHDootnotetextL. Chac'on, Comput. Phys. Comm., 163 (3), 143-171 (2004)^,ootnotetextL. Chac'on et al., 33rd EPS Conf. Plasma Physics, Rome, Italy, 2006 by discussing earlier algorithmic breakthroughs in 2D reduced MHDootnotetextL. Chac'on et al., J. Comput. Phys. 178 (1), 15- 36 (2002) and 2D Hall MHD.ootnotetextL. Chac'on et al., J. Comput. Phys., 188 (2), 573-592 (2003)

Towards Scalable Strain Gauge-Based Joint Torque Sensors

PubMed Central

D’Imperio, Mariapaola; Cannella, Ferdinando; Caldwell, Darwin G.; Cuschieri, Alfred

2017-01-01

During recent decades, strain gauge-based joint torque sensors have been commonly used to provide high-fidelity torque measurements in robotics. Although measurement of joint torque/force is often required in engineering research and development, the gluing and wiring of strain gauges used as torque sensors pose difficulties during integration within the restricted space available in small joints. The problem is compounded by the need for a scalable geometric design to measure joint torque. In this communication, we describe a novel design of a strain gauge-based mono-axial torque sensor referred to as square-cut torque sensor (SCTS), the significant features of which are high degree of linearity, symmetry, and high scalability in terms of both size and measuring range. Most importantly, SCTS provides easy access for gluing and wiring of the strain gauges on sensor surface despite the limited available space. We demonstrated that the SCTS was better in terms of symmetry (clockwise and counterclockwise rotation) and more linear. These capabilities have been shown through finite element modeling (ANSYS) confirmed by observed data obtained by load testing experiments. The high performance of SCTS was confirmed by studies involving changes in size, material and/or wings width and thickness. Finally, we demonstrated that the SCTS can be successfully implementation inside the hip joints of miniaturized hydraulically actuated quadruped robot-MiniHyQ. This communication is based on work presented at the 18th International Conference on Climbing and Walking Robots (CLAWAR). PMID:28820446

Towards Scalable Strain Gauge-Based Joint Torque Sensors.

PubMed

Khan, Hamza; D'Imperio, Mariapaola; Cannella, Ferdinando; Caldwell, Darwin G; Cuschieri, Alfred; Semini, Claudio

2017-08-18

During recent decades, strain gauge-based joint torque sensors have been commonly used to provide high-fidelity torque measurements in robotics. Although measurement of joint torque/force is often required in engineering research and development, the gluing and wiring of strain gauges used as torque sensors pose difficulties during integration within the restricted space available in small joints. The problem is compounded by the need for a scalable geometric design to measure joint torque. In this communication, we describe a novel design of a strain gauge-based mono-axial torque sensor referred to as square-cut torque sensor (SCTS) , the significant features of which are high degree of linearity, symmetry, and high scalability in terms of both size and measuring range. Most importantly, SCTS provides easy access for gluing and wiring of the strain gauges on sensor surface despite the limited available space. We demonstrated that the SCTS was better in terms of symmetry (clockwise and counterclockwise rotation) and more linear. These capabilities have been shown through finite element modeling (ANSYS) confirmed by observed data obtained by load testing experiments. The high performance of SCTS was confirmed by studies involving changes in size, material and/or wings width and thickness. Finally, we demonstrated that the SCTS can be successfully implementation inside the hip joints of miniaturized hydraulically actuated quadruped robot- MiniHyQ . This communication is based on work presented at the 18th International Conference on Climbing and Walking Robots (CLAWAR).

Scalable and Sustainable Electrochemical Allylic C–H Oxidation

PubMed Central

Chen, Yong; Tang, Jiaze; Chen, Ke; Eastgate, Martin D.; Baran, Phil S.

2016-01-01

New methods and strategies for the direct functionalization of C–H bonds are beginning to reshape the fabric of retrosynthetic analysis, impacting the synthesis of natural products, medicines, and even materials1. The oxidation of allylic systems has played a prominent role in this context as possibly the most widely applied C–H functionalization due to the utility of enones and allylic alcohols as versatile intermediates, along with their prevalence in natural and unnatural materials2. Allylic oxidations have been featured in hundreds of syntheses, including some natural product syntheses regarded as “classics”3. Despite many attempts to improve the efficiency and practicality of this powerful transformation, the vast majority of conditions still employ highly toxic reagents (based around toxic elements such as chromium, selenium, etc.) or expensive catalysts (palladium, rhodium, etc.)2. These requirements are highly problematic in industrial settings; currently, no scalable and sustainable solution to allylic oxidation exists. As such, this oxidation strategy is rarely embraced for large-scale synthetic applications, limiting the adoption of this important retrosynthetic strategy by industrial scientists. In this manuscript, we describe an electrochemical solution to this problem that exhibits broad substrate scope, operational simplicity, and high chemoselectivity. This method employs inexpensive and readily available materials, representing the first example of a scalable allylic C–H oxidation (demonstrated on 100 grams), finally opening the door for the adoption of this C–H oxidation strategy in large-scale industrial settings without significant environmental impact. PMID:27096371

Vocal activity as a low cost and scalable index of seabird colony size

USGS Publications Warehouse

Borker, Abraham L.; McKown, Matthew W.; Ackerman, Joshua T.; Eagles-Smith, Collin A.; Tershy, Bernie R.; Croll, Donald A.

2014-01-01

Although wildlife conservation actions have increased globally in number and complexity, the lack of scalable, cost-effective monitoring methods limits adaptive management and the evaluation of conservation efficacy. Automated sensors and computer-aided analyses provide a scalable and increasingly cost-effective tool for conservation monitoring. A key assumption of automated acoustic monitoring of birds is that measures of acoustic activity at colony sites are correlated with the relative abundance of nesting birds. We tested this assumption for nesting Forster's terns (Sterna forsteri) in San Francisco Bay for 2 breeding seasons. Sensors recorded ambient sound at 7 colonies that had 15–111 nests in 2009 and 2010. Colonies were spaced at least 250 m apart and ranged from 36 to 2,571 m2. We used spectrogram cross-correlation to automate the detection of tern calls from recordings. We calculated mean seasonal call rate and compared it with mean active nest count at each colony. Acoustic activity explained 71% of the variation in nest abundance between breeding sites and 88% of the change in colony size between years. These results validate a primary assumption of acoustic indices; that is, for terns, acoustic activity is correlated to relative abundance, a fundamental step toward designing rigorous and scalable acoustic monitoring programs to measure the effectiveness of conservation actions for colonial birds and other acoustically active wildlife.

Design for Scalability: A Case Study of the River City Curriculum

ERIC Educational Resources Information Center

Clarke, Jody; Dede, Chris

2009-01-01

One-size-fits-all educational innovations do not work because they ignore contextual factors that determine an intervention's efficacy in a particular local situation. This paper presents a framework on how to design educational innovations for scalability through enhancing their adaptability for effective usage in a wide variety of settings. The…

ExSTraCS 2.0: Description and Evaluation of a Scalable Learning Classifier System.

PubMed

Urbanowicz, Ryan J; Moore, Jason H

2015-09-01

Algorithmic scalability is a major concern for any machine learning strategy in this age of 'big data'. A large number of potentially predictive attributes is emblematic of problems in bioinformatics, genetic epidemiology, and many other fields. Previously, ExS-TraCS was introduced as an extended Michigan-style supervised learning classifier system that combined a set of powerful heuristics to successfully tackle the challenges of classification, prediction, and knowledge discovery in complex, noisy, and heterogeneous problem domains. While Michigan-style learning classifier systems are powerful and flexible learners, they are not considered to be particularly scalable. For the first time, this paper presents a complete description of the ExS-TraCS algorithm and introduces an effective strategy to dramatically improve learning classifier system scalability. ExSTraCS 2.0 addresses scalability with (1) a rule specificity limit, (2) new approaches to expert knowledge guided covering and mutation mechanisms, and (3) the implementation and utilization of the TuRF algorithm for improving the quality of expert knowledge discovery in larger datasets. Performance over a complex spectrum of simulated genetic datasets demonstrated that these new mechanisms dramatically improve nearly every performance metric on datasets with 20 attributes and made it possible for ExSTraCS to reliably scale up to perform on related 200 and 2000-attribute datasets. ExSTraCS 2.0 was also able to reliably solve the 6, 11, 20, 37, 70, and 135 multiplexer problems, and did so in similar or fewer learning iterations than previously reported, with smaller finite training sets, and without using building blocks discovered from simpler multiplexer problems. Furthermore, ExS-TraCS usability was made simpler through the elimination of previously critical run parameters.

Operationalizing the Reciprocal Engagement Model of Genetic Counseling Practice: a Framework for the Scalable Delivery of Genomic Counseling and Testing.

PubMed

Schmidlen, Tara; Sturm, Amy C; Hovick, Shelly; Scheinfeldt, Laura; Scott Roberts, J; Morr, Lindsey; McElroy, Joseph; Toland, Amanda E; Christman, Michael; O'Daniel, Julianne M; Gordon, Erynn S; Bernhardt, Barbara A; Ormond, Kelly E; Sweet, Kevin

2018-02-19

With the advent of widespread genomic testing for diagnostic indications and disease risk assessment, there is increased need to optimize genetic counseling services to support the scalable delivery of precision medicine. Here, we describe how we operationalized the reciprocal engagement model of genetic counseling practice to develop a framework of counseling components and strategies for the delivery of genomic results. This framework was constructed based upon qualitative research with patients receiving genomic counseling following online receipt of potentially actionable complex disease and pharmacogenomics reports. Consultation with a transdisciplinary group of investigators, including practicing genetic counselors, was sought to ensure broad scope and applicability of these strategies for use with any large-scale genomic testing effort. We preserve the provision of pre-test education and informed consent as established in Mendelian/single-gene disease genetic counseling practice. Following receipt of genomic results, patients are afforded the opportunity to tailor the counseling agenda by selecting the specific test results they wish to discuss, specifying questions for discussion, and indicating their preference for counseling modality. The genetic counselor uses these patient preferences to set the genomic counseling session and to personalize result communication and risk reduction recommendations. Tailored visual aids and result summary reports divide areas of risk (genetic variant, family history, lifestyle) for each disease to facilitate discussion of multiple disease risks. Post-counseling, session summary reports are actively routed to both the patient and their physician team to encourage review and follow-up. Given the breadth of genomic information potentially resulting from genomic testing, this framework is put forth as a starting point to meet the need for scalable genetic counseling services in the delivery of precision medicine.

High performance geospatial and climate data visualization using GeoJS

NASA Astrophysics Data System (ADS)

Chaudhary, A.; Beezley, J. D.

2015-12-01

GeoJS (https://github.com/OpenGeoscience/geojs) is an open-source library developed to support interactive scientific and geospatial visualization of climate and earth science datasets in a web environment. GeoJS has a convenient application programming interface (API) that enables users to harness the fast performance of WebGL and Canvas 2D APIs with sophisticated Scalable Vector Graphics (SVG) features in a consistent and convenient manner. We started the project in response to the need for an open-source JavaScript library that can combine traditional geographic information systems (GIS) and scientific visualization on the web. Many libraries, some of which are open source, support mapping or other GIS capabilities, but lack the features required to visualize scientific and other geospatial datasets. For instance, such libraries are not be capable of rendering climate plots from NetCDF files, and some libraries are limited in regards to geoinformatics (infovis in a geospatial environment). While libraries such as d3.js are extremely powerful for these kinds of plots, in order to integrate them into other GIS libraries, the construction of geoinformatics visualizations must be completed manually and separately, or the code must somehow be mixed in an unintuitive way.We developed GeoJS with the following motivations:• To create an open-source geovisualization and GIS library that combines scientific visualization with GIS and informatics• To develop an extensible library that can combine data from multiple sources and render them using multiple backends• To build a library that works well with existing scientific visualizations tools such as VTKWe have successfully deployed GeoJS-based applications for multiple domains across various projects. The ClimatePipes project funded by the Department of Energy, for example, used GeoJS to visualize NetCDF datasets from climate data archives. Other projects built visualizations using GeoJS for interactively exploring

Scalability of a Low-Cost Multi-Teraflop Linux Cluster for High-End Classical Atomistic and Quantum Mechanical Simulations

NASA Technical Reports Server (NTRS)

Kikuchi, Hideaki; Kalia, Rajiv K.; Nakano, Aiichiro; Vashishta, Priya; Shimojo, Fuyuki; Saini, Subhash

2003-01-01

Scalability of a low-cost, Intel Xeon-based, multi-Teraflop Linux cluster is tested for two high-end scientific applications: Classical atomistic simulation based on the molecular dynamics method and quantum mechanical calculation based on the density functional theory. These scalable parallel applications use space-time multiresolution algorithms and feature computational-space decomposition, wavelet-based adaptive load balancing, and spacefilling-curve-based data compression for scalable I/O. Comparative performance tests are performed on a 1,024-processor Linux cluster and a conventional higher-end parallel supercomputer, 1,184-processor IBM SP4. The results show that the performance of the Linux cluster is comparable to that of the SP4. We also study various effects, such as the sharing of memory and L2 cache among processors, on the performance.

Wafer-scalable high-performance CVD graphene devices and analog circuits

NASA Astrophysics Data System (ADS)

Tao, Li; Lee, Jongho; Li, Huifeng; Piner, Richard; Ruoff, Rodney; Akinwande, Deji

2013-03-01

Graphene field effect transistors (GFETs) will serve as an essential component for functional modules like amplifier and frequency doublers in analog circuits. The performance of these modules is directly related to the mobility of charge carriers in GFETs, which per this study has been greatly improved. Low-field electrostatic measurements show field mobility values up to 12k cm2/Vs at ambient conditions with our newly developed scalable CVD graphene. For both hole and electron transport, fabricated GFETs offer substantial amplification for small and large signals at quasi-static frequencies limited only by external capacitances at high-frequencies. GFETs biased at the peak transconductance point featured high small-signal gain with eventual output power compression similar to conventional transistor amplifiers. GFETs operating around the Dirac voltage afforded positive conversion gain for the first time, to our knowledge, in experimental graphene frequency doublers. This work suggests a realistic prospect for high performance linear and non-linear analog circuits based on the unique electron-hole symmetry and fast transport now accessible in wafer-scalable CVD graphene. *Support from NSF CAREER award (ECCS-1150034) and the W. M. Keck Foundation are appreicated.

Collaborative Visualization and Analysis of Multi-dimensional, Time-dependent and Distributed Data in the Geosciences Using the Unidata Integrated Data Viewer

NASA Astrophysics Data System (ADS)

Meertens, C. M.; Murray, D.; McWhirter, J.

2004-12-01

Over the last five years, UNIDATA has developed an extensible and flexible software framework for analyzing and visualizing geoscience data and models. The Integrated Data Viewer (IDV), initially developed for visualization and analysis of atmospheric data, has broad interdisciplinary application across the geosciences including atmospheric, ocean, and most recently, earth sciences. As part of the NSF-funded GEON Information Technology Research project, UNAVCO has enhanced the IDV to display earthquakes, GPS velocity vectors, and plate boundary strain rates. These and other geophysical parameters can be viewed simultaneously with three-dimensional seismic tomography and mantle geodynamic model results. Disparate data sets of different formats, variables, geographical projections and scales can automatically be displayed in a common projection. The IDV is efficient and fully interactive allowing the user to create and vary 2D and 3D displays with contour plots, vertical and horizontal cross-sections, plan views, 3D isosurfaces, vector plots and streamlines, as well as point data symbols or numeric values. Data probes (values and graphs) can be used to explore the details of the data and models. The IDV is a freely available Java application using Java3D and VisAD and runs on most computers. UNIDATA provides easy-to-follow instructions for download, installation and operation of the IDV. The IDV primarily uses netCDF, a self-describing binary file format, to store multi-dimensional data, related metadata, and source information. The IDV is designed to work with OPeNDAP-equipped data servers that provide real-time observations and numerical models from distributed locations. Users can capture and share screens and animations, or exchange XML "bundles" that contain the state of the visualization and embedded links to remote data files. A real-time collaborative feature allows groups of users to remotely link IDV sessions via the Internet and simultaneously view and

Aero-MINE (Motionless INtegrated Energy) for Distributed Scalable Wind Power.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Houchens, Brent C.; Blaylock, Myra L.

The proposed Aero-MINE technology will extract energy from wind without any exterior moving parts. Aero-MINEs can be integrated into buildings or function stand-alone, and are scalable. This gives them advantages similar to solar panels, but with the added benefit of operation in cloudy or dark conditions. Furthermore, compared to solar panels, Aero-MINEs can be manufactured at lower cost and with less environmental impact. Power generation is isolated internally by the pneumatic transmission of air and the outlet air-jet nozzles amplify the effectiveness. Multiple units can be connected to one centrally located electric generator. Aero-MINEs are ideal for the built-environment, withmore » numerous possible configurations ranging from architectural integration to modular bolt-on products. Traditional wind turbines suffer from many fundamental challenges. The fast-moving blades produce significant aero-acoustic noise, visual disturbances, light-induced flickering and impose wildlife mortality risks. The conversion of massive mechanical torque to electricity is a challenge for gears, generators and power conversion electronics. In addition, the installation, operation and maintenance of wind turbines is required at significant height. Furthermore, wind farms are often in remote locations far from dense regions of electricity customers. These technical and logistical challenges add significantly to the cost of the electricity produced by utility-scale wind farms. In contrast, distributed wind energy eliminates many of the logistical challenges. However, solutions such as micro-turbines produce relatively small amounts of energy due to the reduction in swept area and still suffer from the motion-related disadvantages of utility-scale turbines. Aero-MINEs combine the best features of distributed generation, while eliminating the disadvantages.« less

Development, Verification and Validation of Parallel, Scalable Volume of Fluid CFD Program for Propulsion Applications

NASA Technical Reports Server (NTRS)

West, Jeff; Yang, H. Q.

2014-01-01

There are many instances involving liquid/gas interfaces and their dynamics in the design of liquid engine powered rockets such as the Space Launch System (SLS). Some examples of these applications are: Propellant tank draining and slosh, subcritical condition injector analysis for gas generators, preburners and thrust chambers, water deluge mitigation for launch induced environments and even solid rocket motor liquid slag dynamics. Commercially available CFD programs simulating gas/liquid interfaces using the Volume of Fluid approach are currently limited in their parallel scalability. In 2010 for instance, an internal NASA/MSFC review of three commercial tools revealed that parallel scalability was seriously compromised at 8 cpus and no additional speedup was possible after 32 cpus. Other non-interface CFD applications at the time were demonstrating useful parallel scalability up to 4,096 processors or more. Based on this review, NASA/MSFC initiated an effort to implement a Volume of Fluid implementation within the unstructured mesh, pressure-based algorithm CFD program, Loci-STREAM. After verification was achieved by comparing results to the commercial CFD program CFD-Ace+, and validation by direct comparison with data, Loci-STREAM-VoF is now the production CFD tool for propellant slosh force and slosh damping rate simulations at NASA/MSFC. On these applications, good parallel scalability has been demonstrated for problems sizes of tens of millions of cells and thousands of cpu cores. Ongoing efforts are focused on the application of Loci-STREAM-VoF to predict the transient flow patterns of water on the SLS Mobile Launch Platform in order to support the phasing of water for launch environment mitigation so that vehicle determinantal effects are not realized.

Towards scalable quantum communication and computation: Novel approaches and realizations

NASA Astrophysics Data System (ADS)

Jiang, Liang

Quantum information science involves exploration of fundamental laws of quantum mechanics for information processing tasks. This thesis presents several new approaches towards scalable quantum information processing. First, we consider a hybrid approach to scalable quantum computation, based on an optically connected network of few-qubit quantum registers. Specifically, we develop a novel scheme for scalable quantum computation that is robust against various imperfections. To justify that nitrogen-vacancy (NV) color centers in diamond can be a promising realization of the few-qubit quantum register, we show how to isolate a few proximal nuclear spins from the rest of the environment and use them for the quantum register. We also demonstrate experimentally that the nuclear spin coherence is only weakly perturbed under optical illumination, which allows us to implement quantum logical operations that use the nuclear spins to assist the repetitive-readout of the electronic spin. Using this technique, we demonstrate more than two-fold improvement in signal-to-noise ratio. Apart from direct application to enhance the sensitivity of the NV-based nano-magnetometer, this experiment represents an important step towards the realization of robust quantum information processors using electronic and nuclear spin qubits. We then study realizations of quantum repeaters for long distance quantum communication. Specifically, we develop an efficient scheme for quantum repeaters based on atomic ensembles. We use dynamic programming to optimize various quantum repeater protocols. In addition, we propose a new protocol of quantum repeater with encoding, which efficiently uses local resources (about 100 qubits) to identify and correct errors, to achieve fast one-way quantum communication over long distances. Finally, we explore quantum systems with topological order. Such systems can exhibit remarkable phenomena such as quasiparticles with anyonic statistics and have been proposed as

Scalable problems and memory bounded speedup

NASA Technical Reports Server (NTRS)

Sun, Xian-He; Ni, Lionel M.

1992-01-01

In this paper three models of parallel speedup are studied. They are fixed-size speedup, fixed-time speedup and memory-bounded speedup. The latter two consider the relationship between speedup and problem scalability. Two sets of speedup formulations are derived for these three models. One set considers uneven workload allocation and communication overhead and gives more accurate estimation. Another set considers a simplified case and provides a clear picture on the impact of the sequential portion of an application on the possible performance gain from parallel processing. The simplified fixed-size speedup is Amdahl's law. The simplified fixed-time speedup is Gustafson's scaled speedup. The simplified memory-bounded speedup contains both Amdahl's law and Gustafson's scaled speedup as special cases. This study leads to a better understanding of parallel processing.

Parallel scalability of Hartree-Fock calculations

NASA Astrophysics Data System (ADS)

Chow, Edmond; Liu, Xing; Smelyanskiy, Mikhail; Hammond, Jeff R.

2015-03-01

Quantum chemistry is increasingly performed using large cluster computers consisting of multiple interconnected nodes. For a fixed molecular problem, the efficiency of a calculation usually decreases as more nodes are used, due to the cost of communication between the nodes. This paper empirically investigates the parallel scalability of Hartree-Fock calculations. The construction of the Fock matrix and the density matrix calculation are analyzed separately. For the former, we use a parallelization of Fock matrix construction based on a static partitioning of work followed by a work stealing phase. For the latter, we use density matrix purification from the linear scaling methods literature, but without using sparsity. When using large numbers of nodes for moderately sized problems, density matrix computations are network-bandwidth bound, making purification methods potentially faster than eigendecomposition methods.

Towards scalable Byzantine fault-tolerant replication

NASA Astrophysics Data System (ADS)

Zbierski, Maciej

2017-08-01

Byzantine fault-tolerant (BFT) replication is a powerful technique, enabling distributed systems to remain available and correct even in the presence of arbitrary faults. Unfortunately, existing BFT replication protocols are mostly load-unscalable, i.e. they fail to respond with adequate performance increase whenever new computational resources are introduced into the system. This article proposes a universal architecture facilitating the creation of load-scalable distributed services based on BFT replication. The suggested approach exploits parallel request processing to fully utilize the available resources, and uses a load balancer module to dynamically adapt to the properties of the observed client workload. The article additionally provides a discussion on selected deployment scenarios, and explains how the proposed architecture could be used to increase the dependability of contemporary large-scale distributed systems.

Particle Communication and Domain Neighbor Coupling: Scalable Domain Decomposed Algorithms for Monte Carlo Particle Transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Brien, M. J.; Brantley, P. S.

2015-01-20

In order to run Monte Carlo particle transport calculations on new supercomputers with hundreds of thousands or millions of processors, care must be taken to implement scalable algorithms. This means that the algorithms must continue to perform well as the processor count increases. In this paper, we examine the scalability of:(1) globally resolving the particle locations on the correct processor, (2) deciding that particle streaming communication has finished, and (3) efficiently coupling neighbor domains together with different replication levels. We have run domain decomposed Monte Carlo particle transport on up to 2 21 = 2,097,152 MPI processes on the IBMmore » BG/Q Sequoia supercomputer and observed scalable results that agree with our theoretical predictions. These calculations were carefully constructed to have the same amount of work on every processor, i.e. the calculation is already load balanced. We also examine load imbalanced calculations where each domain’s replication level is proportional to its particle workload. In this case we show how to efficiently couple together adjacent domains to maintain within workgroup load balance and minimize memory usage.« less

Efficient temporal and interlayer parameter prediction for weighted prediction in scalable high efficiency video coding

NASA Astrophysics Data System (ADS)

Tsang, Sik-Ho; Chan, Yui-Lam; Siu, Wan-Chi

2017-01-01

Weighted prediction (WP) is an efficient video coding tool that was introduced since the establishment of the H.264/AVC video coding standard, for compensating the temporal illumination change in motion estimation and compensation. WP parameters, including a multiplicative weight and an additive offset for each reference frame, are required to be estimated and transmitted to the decoder by slice header. These parameters cause extra bits in the coded video bitstream. High efficiency video coding (HEVC) provides WP parameter prediction to reduce the overhead. Therefore, WP parameter prediction is crucial to research works or applications, which are related to WP. Prior art has been suggested to further improve the WP parameter prediction by implicit prediction of image characteristics and derivation of parameters. By exploiting both temporal and interlayer redundancies, we propose three WP parameter prediction algorithms, enhanced implicit WP parameter, enhanced direct WP parameter derivation, and interlayer WP parameter, to further improve the coding efficiency of HEVC. Results show that our proposed algorithms can achieve up to 5.83% and 5.23% bitrate reduction compared to the conventional scalable HEVC in the base layer for SNR scalability and 2× spatial scalability, respectively.

The development of a scalable parallel 3-D CFD algorithm for turbomachinery. M.S. Thesis Final Report

NASA Technical Reports Server (NTRS)

Luke, Edward Allen

1993-01-01

Two algorithms capable of computing a transonic 3-D inviscid flow field about rotating machines are considered for parallel implementation. During the study of these algorithms, a significant new method of measuring the performance of parallel algorithms is developed. The theory that supports this new method creates an empirical definition of scalable parallel algorithms that is used to produce quantifiable evidence that a scalable parallel application was developed. The implementation of the parallel application and an automated domain decomposition tool are also discussed.

A Scalable Framework to Detect Personal Health Mentions on Twitter.

PubMed

Yin, Zhijun; Fabbri, Daniel; Rosenbloom, S Trent; Malin, Bradley

2015-06-05

Biomedical research has traditionally been conducted via surveys and the analysis of medical records. However, these resources are limited in their content, such that non-traditional domains (eg, online forums and social media) have an opportunity to supplement the view of an individual's health. The objective of this study was to develop a scalable framework to detect personal health status mentions on Twitter and assess the extent to which such information is disclosed. We collected more than 250 million tweets via the Twitter streaming API over a 2-month period in 2014. The corpus was filtered down to approximately 250,000 tweets, stratified across 34 high-impact health issues, based on guidance from the Medical Expenditure Panel Survey. We created a labeled corpus of several thousand tweets via a survey, administered over Amazon Mechanical Turk, that documents when terms correspond to mentions of personal health issues or an alternative (eg, a metaphor). We engineered a scalable classifier for personal health mentions via feature selection and assessed its potential over the health issues. We further investigated the utility of the tweets by determining the extent to which Twitter users disclose personal health status. Our investigation yielded several notable findings. First, we find that tweets from a small subset of the health issues can train a scalable classifier to detect health mentions. Specifically, training on 2000 tweets from four health issues (cancer, depression, hypertension, and leukemia) yielded a classifier with precision of 0.77 on all 34 health issues. Second, Twitter users disclosed personal health status for all health issues. Notably, personal health status was disclosed over 50% of the time for 11 out of 34 (33%) investigated health issues. Third, the disclosure rate was dependent on the health issue in a statistically significant manner (P<.001). For instance, more than 80% of the tweets about migraines (83/100) and allergies (85

Scalability issues in evolutionary synthesis of electronic circuits: lessons learned and challenges ahead

NASA Technical Reports Server (NTRS)

Stoica, A.; Keymeulen, D.; Zebulum, R. S.; Ferguson, M. I.

2003-01-01

This paper describes scalability issues of evolutionary-driven automatic synthesis of electronic circuits. The article begins by reviewing the concepts of circuit evolution and discussing the limitations of this technique when trying to achieve more complex systems.

Scalable manufacturing of biomimetic moldable hydrogels for industrial applications.

PubMed

Yu, Anthony C; Chen, Haoxuan; Chan, Doreen; Agmon, Gillie; Stapleton, Lyndsay M; Sevit, Alex M; Tibbitt, Mark W; Acosta, Jesse D; Zhang, Tony; Franzia, Paul W; Langer, Robert; Appel, Eric A

2016-12-13

Hydrogels are a class of soft material that is exploited in many, often completely disparate, industrial applications, on account of their unique and tunable properties. Advances in soft material design are yielding next-generation moldable hydrogels that address engineering criteria in several industrial settings such as complex viscosity modifiers, hydraulic or injection fluids, and sprayable carriers. Industrial implementation of these viscoelastic materials requires extreme volumes of material, upwards of several hundred million gallons per year. Here, we demonstrate a paradigm for the scalable fabrication of self-assembled moldable hydrogels using rationally engineered, biomimetic polymer-nanoparticle interactions. Cellulose derivatives are linked together by selective adsorption to silica nanoparticles via dynamic and multivalent interactions. We show that the self-assembly process for gel formation is easily scaled in a linear fashion from 0.5 mL to over 15 L without alteration of the mechanical properties of the resultant materials. The facile and scalable preparation of these materials leveraging self-assembly of inexpensive, renewable, and environmentally benign starting materials, coupled with the tunability of their properties, make them amenable to a range of industrial applications. In particular, we demonstrate their utility as injectable materials for pipeline maintenance and product recovery in industrial food manufacturing as well as their use as sprayable carriers for robust application of fire retardants in preventing wildland fires.

Scalable manufacturing of biomimetic moldable hydrogels for industrial applications

NASA Astrophysics Data System (ADS)

Yu, Anthony C.; Chen, Haoxuan; Chan, Doreen; Agmon, Gillie; Stapleton, Lyndsay M.; Sevit, Alex M.; Tibbitt, Mark W.; Acosta, Jesse D.; Zhang, Tony; Franzia, Paul W.; Langer, Robert; Appel, Eric A.

2016-12-01

Hydrogels are a class of soft material that is exploited in many, often completely disparate, industrial applications, on account of their unique and tunable properties. Advances in soft material design are yielding next-generation moldable hydrogels that address engineering criteria in several industrial settings such as complex viscosity modifiers, hydraulic or injection fluids, and sprayable carriers. Industrial implementation of these viscoelastic materials requires extreme volumes of material, upwards of several hundred million gallons per year. Here, we demonstrate a paradigm for the scalable fabrication of self-assembled moldable hydrogels using rationally engineered, biomimetic polymer-nanoparticle interactions. Cellulose derivatives are linked together by selective adsorption to silica nanoparticles via dynamic and multivalent interactions. We show that the self-assembly process for gel formation is easily scaled in a linear fashion from 0.5 mL to over 15 L without alteration of the mechanical properties of the resultant materials. The facile and scalable preparation of these materials leveraging self-assembly of inexpensive, renewable, and environmentally benign starting materials, coupled with the tunability of their properties, make them amenable to a range of industrial applications. In particular, we demonstrate their utility as injectable materials for pipeline maintenance and product recovery in industrial food manufacturing as well as their use as sprayable carriers for robust application of fire retardants in preventing wildland fires.

Scalable manufacturing of biomimetic moldable hydrogels for industrial applications

PubMed Central

Yu, Anthony C.; Chen, Haoxuan; Chan, Doreen; Agmon, Gillie; Stapleton, Lyndsay M.; Sevit, Alex M.; Tibbitt, Mark W.; Acosta, Jesse D.; Zhang, Tony; Franzia, Paul W.; Langer, Robert

2016-01-01

Hydrogels are a class of soft material that is exploited in many, often completely disparate, industrial applications, on account of their unique and tunable properties. Advances in soft material design are yielding next-generation moldable hydrogels that address engineering criteria in several industrial settings such as complex viscosity modifiers, hydraulic or injection fluids, and sprayable carriers. Industrial implementation of these viscoelastic materials requires extreme volumes of material, upwards of several hundred million gallons per year. Here, we demonstrate a paradigm for the scalable fabrication of self-assembled moldable hydrogels using rationally engineered, biomimetic polymer–nanoparticle interactions. Cellulose derivatives are linked together by selective adsorption to silica nanoparticles via dynamic and multivalent interactions. We show that the self-assembly process for gel formation is easily scaled in a linear fashion from 0.5 mL to over 15 L without alteration of the mechanical properties of the resultant materials. The facile and scalable preparation of these materials leveraging self-assembly of inexpensive, renewable, and environmentally benign starting materials, coupled with the tunability of their properties, make them amenable to a range of industrial applications. In particular, we demonstrate their utility as injectable materials for pipeline maintenance and product recovery in industrial food manufacturing as well as their use as sprayable carriers for robust application of fire retardants in preventing wildland fires. PMID:27911849

The Political Economy of E-Learning Educational Development Strategies, Standardisation and Scalability

ERIC Educational Resources Information Center

Kenney, Jacqueline; Hermens, Antoine; Clarke, Thomas

2004-01-01

The development of e-learning by government through policy, funding allocations, research-based collaborative projects and alliances has increased recently in both developed and under-developed nations. The paper notes that government, industry and corporate users are increasingly focusing on standardisation issues and the scalability of…

Digital quantum simulators in a scalable architecture of hybrid spin-photon qubits

PubMed Central

Chiesa, Alessandro; Santini, Paolo; Gerace, Dario; Raftery, James; Houck, Andrew A.; Carretta, Stefano

2015-01-01

Resolving quantum many-body problems represents one of the greatest challenges in physics and physical chemistry, due to the prohibitively large computational resources that would be required by using classical computers. A solution has been foreseen by directly simulating the time evolution through sequences of quantum gates applied to arrays of qubits, i.e. by implementing a digital quantum simulator. Superconducting circuits and resonators are emerging as an extremely promising platform for quantum computation architectures, but a digital quantum simulator proposal that is straightforwardly scalable, universal, and realizable with state-of-the-art technology is presently lacking. Here we propose a viable scheme to implement a universal quantum simulator with hybrid spin-photon qubits in an array of superconducting resonators, which is intrinsically scalable and allows for local control. As representative examples we consider the transverse-field Ising model, a spin-1 Hamiltonian, and the two-dimensional Hubbard model and we numerically simulate the scheme by including the main sources of decoherence. PMID:26563516

Development of a Web-Based Visualization Platform for Climate Research Using Google Earth

NASA Technical Reports Server (NTRS)

Sun, Xiaojuan; Shen, Suhung; Leptoukh, Gregory G.; Wang, Panxing; Di, Liping; Lu, Mingyue

2011-01-01

Recently, it has become easier to access climate data from satellites, ground measurements, and models from various data centers, However, searching. accessing, and prc(essing heterogeneous data from different sources are very tim -consuming tasks. There is lack of a comprehensive visual platform to acquire distributed and heterogeneous scientific data and to render processed images from a single accessing point for climate studies. This paper. documents the design and implementation of a Web-based visual, interoperable, and scalable platform that is able to access climatological fields from models, satellites, and ground stations from a number of data sources using Google Earth (GE) as a common graphical interface. The development is based on the TCP/IP protocol and various data sharing open sources, such as OPeNDAP, GDS, Web Processing Service (WPS), and Web Mapping Service (WMS). The visualization capability of integrating various measurements into cE extends dramatically the awareness and visibility of scientific results. Using embedded geographic information in the GE, the designed system improves our understanding of the relationships of different elements in a four dimensional domain. The system enables easy and convenient synergistic research on a virtual platform for professionals and the general public, gr$tly advancing global data sharing and scientific research collaboration.

Performance and Scalability of the NAS Parallel Benchmarks in Java

NASA Technical Reports Server (NTRS)

Frumkin, Michael A.; Schultz, Matthew; Jin, Haoqiang; Yan, Jerry; Biegel, Bryan A. (Technical Monitor)

2002-01-01

Several features make Java an attractive choice for scientific applications. In order to gauge the applicability of Java to Computational Fluid Dynamics (CFD), we have implemented the NAS (NASA Advanced Supercomputing) Parallel Benchmarks in Java. The performance and scalability of the benchmarks point out the areas where improvement in Java compiler technology and in Java thread implementation would position Java closer to Fortran in the competition for scientific applications.

Understanding Graphics on a Scalable Latching Assistive Haptic Display Using a Shape Memory Polymer Membrane.

PubMed

Besse, Nadine; Rosset, Samuel; Zarate, Juan Jose; Ferrari, Elisabetta; Brayda, Luca; Shea, Herbert

2018-01-01

We present a fully latching and scalable 4 × 4 haptic display with 4 mm pitch, 5 s refresh time, 400 mN holding force, and 650 μm displacement per taxel. The display serves to convey dynamic graphical information to blind and visually impaired users. Combining significant holding force with high taxel density and large amplitude motion in a very compact overall form factor was made possible by exploiting the reversible, fast, hundred-fold change in the stiffness of a thin shape memory polymer (SMP) membrane when heated above its glass transition temperature. Local heating is produced using an addressable array of 3 mm in diameter stretchable microheaters patterned on the SMP. Each taxel is selectively and independently actuated by synchronizing the local Joule heating with a single pressure supply. Switching off the heating locks each taxel into its position (up or down), enabling holding any array configuration with zero power consumption. A 3D-printed pin array is mounted over the SMP membrane, providing the user with a smooth and room temperature array of movable pins to explore by touch. Perception tests were carried out with 24 blind users resulting in 70 percent correct pattern recognition over a 12-word tactile dictionary.

Scalable shear-exfoliation of high-quality phosphorene nanoflakes with reliable electrochemical cycleability in nano batteries

NASA Astrophysics Data System (ADS)

Xu, Feng; Ge, Binghui; Chen, Jing; Nathan, Arokia; Xin, Linhuo L.; Ma, Hongyu; Min, Huihua; Zhu, Chongyang; Xia, Weiwei; Li, Zhengrui; Li, Shengli; Yu, Kaihao; Wu, Lijun; Cui, Yiping; Sun, Litao; Zhu, Yimei

2016-06-01

Atomically thin black phosphorus (called phosphorene) holds great promise as an alternative to graphene and other two-dimensional transition-metal dichalcogenides as an anode material for lithium-ion batteries (LIBs). However, bulk black phosphorus (BP) suffers from rapid capacity fading and poor rechargeable performance. This work reports for the first time the use of in situ transmission electron microscopy (TEM) to construct nanoscale phosphorene LIBs. This enables direct visualization of the mechanisms underlying capacity fading in thick multilayer phosphorene through real-time capture of delithiation-induced structural decomposition, which serves to reduce electrical conductivity thus causing irreversibility of the lithiated phases. We further demonstrate that few-layer-thick phosphorene successfully circumvents the structural decomposition and holds superior structural restorability, even when subject to multi-cycle lithiation/delithiation processes and concomitant huge volume expansion. This finding provides breakthrough insights into thickness-dependent lithium diffusion kinetics in phosphorene. More importantly, a scalable liquid-phase shear exfoliation route has been developed to produce high-quality ultrathin phosphorene using simple means such as a high-speed shear mixer or even a household kitchen blender with the shear rate threshold of ˜1.25 × 104 s-1. The results reported here will pave the way for industrial-scale applications of rechargeable phosphorene LIBs.

Scalable shear-exfoliation of high-quality phosphorene nanoflakes with reliable electrochemical cycleability in nano batteries

DOE PAGES

Xu, Feng; Ge, Binghui; Chen, Jing; ...

2016-03-30

Atomically thin black phosphorus (called phosphorene) holds great promise as an alternative to graphene and other two-dimensional transition-metal dichalcogenides as an anode material for lithium-ion batteries (LIBs). But, bulk black phosphorus (BP) suffers from rapid capacity fading and poor rechargeable performance. This work reports for the first time the use of in situ transmission electron microscopy (TEM) to construct nanoscale phosphorene LIBs. This enables direct visualization of the mechanisms underlying capacity fading in thick multilayer phosphorene through real-time capture of delithiation-induced structural decomposition, which serves to reduce electrical conductivity thus causing irreversibility of the lithiated phases. Furthermore, we demonstrate thatmore » few-layer-thick phosphorene successfully circumvents the structural decomposition and holds superior structural restorability, even when subject to multi-cycle lithiation/delithiation processes and concomitant huge volume expansion. This finding provides breakthrough insights into thickness-dependent lithium diffusion kinetics in phosphorene. More importantly, a scalable liquid-phase shear exfoliation route has been developed to produce high-quality ultrathin phosphorene using simple means such as a high-speed shear mixer or even a household kitchen blender with the shear rate threshold of ~1.25 × 10 4 s -1. Our results reported here will pave the way for industrial-scale applications of rechargeable phosphorene LIBs.« less

An Intelligent Cooperative Visual Sensor Network for Urban Mobility.

PubMed

Leone, Giuseppe Riccardo; Moroni, Davide; Pieri, Gabriele; Petracca, Matteo; Salvetti, Ovidio; Azzarà, Andrea; Marino, Francesco

2017-11-10

Smart cities are demanding solutions for improved traffic efficiency, in order to guarantee optimal access to mobility resources available in urban areas. Intelligent video analytics deployed directly on board embedded sensors offers great opportunities to gather highly informative data about traffic and transport, allowing reconstruction of a real-time neat picture of urban mobility patterns. In this paper, we present a visual sensor network in which each node embeds computer vision logics for analyzing in real time urban traffic. The nodes in the network share their perceptions and build a global and comprehensive interpretation of the analyzed scenes in a cooperative and adaptive fashion. This is possible thanks to an especially designed Internet of Things (IoT) compliant middleware which encompasses in-network event composition as well as full support of Machine-2-Machine (M2M) communication mechanism. The potential of the proposed cooperative visual sensor network is shown with two sample applications in urban mobility connected to the estimation of vehicular flows and parking management. Besides providing detailed results of each key component of the proposed solution, the validity of the approach is demonstrated by extensive field tests that proved the suitability of the system in providing a scalable, adaptable and extensible data collection layer for managing and understanding mobility in smart cities.

Scalable implementation of boson sampling with trapped ions.

PubMed

Shen, C; Zhang, Z; Duan, L-M

2014-02-07

Boson sampling solves a classically intractable problem by sampling from a probability distribution given by matrix permanents. We propose a scalable implementation of boson sampling using local transverse phonon modes of trapped ions to encode the bosons. The proposed scheme allows deterministic preparation and high-efficiency readout of the bosons in the Fock states and universal mode mixing. With the state-of-the-art trapped ion technology, it is feasible to realize boson sampling with tens of bosons by this scheme, which would outperform the most powerful classical computers and constitute an effective disproof of the famous extended Church-Turing thesis.

A Scalable Architecture of a Structured LDPC Decoder

NASA Technical Reports Server (NTRS)

Lee, Jason Kwok-San; Lee, Benjamin; Thorpe, Jeremy; Andrews, Kenneth; Dolinar, Sam; Hamkins, Jon

2004-01-01

We present a scalable decoding architecture for a certain class of structured LDPC codes. The codes are designed using a small (n,r) protograph that is replicated Z times to produce a decoding graph for a (Z x n, Z x r) code. Using this architecture, we have implemented a decoder for a (4096,2048) LDPC code on a Xilinx Virtex-II 2000 FPGA, and achieved decoding speeds of 31 Mbps with 10 fixed iterations. The implemented message-passing algorithm uses an optimized 3-bit non-uniform quantizer that operates with 0.2dB implementation loss relative to a floating point decoder.

Casimir effect and graphene: Tunability, scalability, Casimir rotor

NASA Astrophysics Data System (ADS)

Martinez, J. C.; Chen, X.; Jalil, M. B. A.

2018-01-01

We study the combined effects of separated parallel disks, birefringence and surface currents on the Casimir force and torque. All three contribute to the Casimir force and surface currents from graphene permit tuning and switching from attraction to repulsion thus allowing for an oscillating Casimir force which can be relevant to parametric amplification applications. Only the latter two contribute to the Casimir torque and their combined effect can enhance the torque by at least tenfold (possibly more) compared to that due to birefringence alone, a hint at a scalable Casimir torque. We also consider a feasible non-contact rotor.

Scalable and Resilient Middleware to Handle Information Exchange during Environment Crisis

NASA Astrophysics Data System (ADS)

Tao, R.; Poslad, S.; Moßgraber, J.; Middleton, S.; Hammitzsch, M.

2012-04-01

The EU FP7 TRIDEC project focuses on enabling real-time, intelligent, information management of collaborative, complex, critical decision processes for earth management. A key challenge is to promote a communication infrastructure to facilitate interoperable environment information services during environment events and crises such as tsunamis and drilling, during which increasing volumes and dimensionality of disparate information sources, including sensor-based and human-based ones, can result, and need to be managed. Such a system needs to support: scalable, distributed messaging; asynchronous messaging; open messaging to handling changing clients such as new and retired automated system and human information sources becoming online or offline; flexible data filtering, and heterogeneous access networks (e.g., GSM, WLAN and LAN). In addition, the system needs to be resilient to handle the ICT system failures, e.g. failure, degradation and overloads, during environment events. There are several system middleware choices for TRIDEC based upon a Service-oriented-architecture (SOA), Event-driven-Architecture (EDA), Cloud Computing, and Enterprise Service Bus (ESB). In an SOA, everything is a service (e.g. data access, processing and exchange); clients can request on demand or subscribe to services registered by providers; more often interaction is synchronous. In an EDA system, events that represent significant changes in state can be processed simply, or as streams or more complexly. Cloud computing is a virtualization, interoperable and elastic resource allocation model. An ESB, a fundamental component for enterprise messaging, supports synchronous and asynchronous message exchange models and has inbuilt resilience against ICT failure. Our middleware proposal is an ESB based hybrid architecture model: an SOA extension supports more synchronous workflows; EDA assists the ESB to handle more complex event processing; Cloud computing can be used to increase and

A scalable variational inequality approach for flow through porous media models with pressure-dependent viscosity

NASA Astrophysics Data System (ADS)

Mapakshi, N. K.; Chang, J.; Nakshatrala, K. B.

2018-04-01

Mathematical models for flow through porous media typically enjoy the so-called maximum principles, which place bounds on the pressure field. It is highly desirable to preserve these bounds on the pressure field in predictive numerical simulations, that is, one needs to satisfy discrete maximum principles (DMP). Unfortunately, many of the existing formulations for flow through porous media models do not satisfy DMP. This paper presents a robust, scalable numerical formulation based on variational inequalities (VI), to model non-linear flows through heterogeneous, anisotropic porous media without violating DMP. VI is an optimization technique that places bounds on the numerical solutions of partial differential equations. To crystallize the ideas, a modification to Darcy equations by taking into account pressure-dependent viscosity will be discretized using the lowest-order Raviart-Thomas (RT0) and Variational Multi-scale (VMS) finite element formulations. It will be shown that these formulations violate DMP, and, in fact, these violations increase with an increase in anisotropy. It will be shown that the proposed VI-based formulation provides a viable route to enforce DMP. Moreover, it will be shown that the proposed formulation is scalable, and can work with any numerical discretization and weak form. A series of numerical benchmark problems are solved to demonstrate the effects of heterogeneity, anisotropy and non-linearity on DMP violations under the two chosen formulations (RT0 and VMS), and that of non-linearity on solver convergence for the proposed VI-based formulation. Parallel scalability on modern computational platforms will be illustrated through strong-scaling studies, which will prove the efficiency of the proposed formulation in a parallel setting. Algorithmic scalability as the problem size is scaled up will be demonstrated through novel static-scaling studies. The performed static-scaling studies can serve as a guide for users to be able to select

A Scalable O(N) Algorithm for Large-Scale Parallel First-Principles Molecular Dynamics Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Osei-Kuffuor, Daniel; Fattebert, Jean-Luc

2014-01-01

Traditional algorithms for first-principles molecular dynamics (FPMD) simulations only gain a modest capability increase from current petascale computers, due to their O(N 3) complexity and their heavy use of global communications. To address this issue, we are developing a truly scalable O(N) complexity FPMD algorithm, based on density functional theory (DFT), which avoids global communications. The computational model uses a general nonorthogonal orbital formulation for the DFT energy functional, which requires knowledge of selected elements of the inverse of the associated overlap matrix. We present a scalable algorithm for approximately computing selected entries of the inverse of the overlap matrix,more » based on an approximate inverse technique, by inverting local blocks corresponding to principal submatrices of the global overlap matrix. The new FPMD algorithm exploits sparsity and uses nearest neighbor communication to provide a computational scheme capable of extreme scalability. Accuracy is controlled by the mesh spacing of the finite difference discretization, the size of the localization regions in which the electronic orbitals are confined, and a cutoff beyond which the entries of the overlap matrix can be omitted when computing selected entries of its inverse. We demonstrate the algorithm's excellent parallel scaling for up to O(100K) atoms on O(100K) processors, with a wall-clock time of O(1) minute per molecular dynamics time step.« less

Level-2 Milestone 3504: Scalable Applications Preparations and Outreach for the Sequoia ID (Dawn)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Futral, W. Scott; Gyllenhaal, John C.; Hedges, Richard M.

2010-07-02

This report documents LLNL SAP project activities in anticipation of the ASC Sequoia system, ASC L2 milestone 3504: Scalable Applications Preparations and Outreach for the Sequoia ID (Dawn), due June 30, 2010.

Using Swarming Agents for Scalable Security in Large Network Environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crouse, Michael; White, Jacob L.; Fulp, Errin W.

2011-09-23

The difficulty of securing computer infrastructures increases as they grow in size and complexity. Network-based security solutions such as IDS and firewalls cannot scale because of exponentially increasing computational costs inherent in detecting the rapidly growing number of threat signatures. Hostbased solutions like virus scanners and IDS suffer similar issues, and these are compounded when enterprises try to monitor these in a centralized manner. Swarm-based autonomous agent systems like digital ants and artificial immune systems can provide a scalable security solution for large network environments. The digital ants approach offers a biologically inspired design where each ant in the virtualmore » colony can detect atoms of evidence that may help identify a possible threat. By assembling the atomic evidences from different ant types the colony may detect the threat. This decentralized approach can require, on average, fewer computational resources than traditional centralized solutions; however there are limits to its scalability. This paper describes how dividing a large infrastructure into smaller managed enclaves allows the digital ant framework to effectively operate in larger environments. Experimental results will show that using smaller enclaves allows for more consistent distribution of agents and results in faster response times.« less

Visual Aggregate Analysis of Eligibility Features of Clinical Trials

PubMed Central

He, Zhe; Carini, Simona; Sim, Ida; Weng, Chunhua

2015-01-01

Objective To develop a method for profiling the collective populations targeted for recruitment by multiple clinical studies addressing the same medical condition using one eligibility feature each time. Methods Using a previously published database COMPACT as the backend, we designed a scalable method for visual aggregate analysis of clinical trial eligibility features. This method consists of four modules for eligibility feature frequency analysis, query builder, distribution analysis, and visualization, respectively. This method is capable of analyzing (1) frequently used qualitative and quantitative features for recruiting subjects for a selected medical condition, (2) distribution of study enrollment on consecutive value points or value intervals of each quantitative feature, and (3) distribution of studies on the boundary values, permissible value ranges, and value range widths of each feature. All analysis results were visualized using Google Charts API. Five recruited potential users assessed the usefulness of this method for identifying common patterns in any selected eligibility feature for clinical trial participant selection. Results We implemented this method as a Web-based analytical system called VITTA (Visual Analysis Tool of Clinical Study Target Populations). We illustrated the functionality of VITTA using two sample queries involving quantitative features BMI and HbA1c for conditions “hypertension” and “Type 2 diabetes”, respectively. The recruited potential users rated the user-perceived usefulness of VITTA with an average score of 86.4/100. Conclusions We contributed a novel aggregate analysis method to enable the interrogation of common patterns in quantitative eligibility criteria and the collective target populations of multiple related clinical studies. A larger-scale study is warranted to formally assess the usefulness of VITTA among clinical investigators and sponsors in various therapeutic areas. PMID:25615940

Visual aggregate analysis of eligibility features of clinical trials.

PubMed

He, Zhe; Carini, Simona; Sim, Ida; Weng, Chunhua

2015-04-01

To develop a method for profiling the collective populations targeted for recruitment by multiple clinical studies addressing the same medical condition using one eligibility feature each time. Using a previously published database COMPACT as the backend, we designed a scalable method for visual aggregate analysis of clinical trial eligibility features. This method consists of four modules for eligibility feature frequency analysis, query builder, distribution analysis, and visualization, respectively. This method is capable of analyzing (1) frequently used qualitative and quantitative features for recruiting subjects for a selected medical condition, (2) distribution of study enrollment on consecutive value points or value intervals of each quantitative feature, and (3) distribution of studies on the boundary values, permissible value ranges, and value range widths of each feature. All analysis results were visualized using Google Charts API. Five recruited potential users assessed the usefulness of this method for identifying common patterns in any selected eligibility feature for clinical trial participant selection. We implemented this method as a Web-based analytical system called VITTA (Visual Analysis Tool of Clinical Study Target Populations). We illustrated the functionality of VITTA using two sample queries involving quantitative features BMI and HbA1c for conditions "hypertension" and "Type 2 diabetes", respectively. The recruited potential users rated the user-perceived usefulness of VITTA with an average score of 86.4/100. We contributed a novel aggregate analysis method to enable the interrogation of common patterns in quantitative eligibility criteria and the collective target populations of multiple related clinical studies. A larger-scale study is warranted to formally assess the usefulness of VITTA among clinical investigators and sponsors in various therapeutic areas. Copyright © 2015 Elsevier Inc. All rights reserved.

Electrophysiological signal analysis and visualization using Cloudwave for epilepsy clinical research.

PubMed

Jayapandian, Catherine P; Chen, Chien-Hung; Bozorgi, Alireza; Lhatoo, Samden D; Zhang, Guo-Qiang; Sahoo, Satya S

2013-01-01

Epilepsy is the most common serious neurological disorder affecting 50-60 million persons worldwide. Electrophysiological data recordings, such as electroencephalogram (EEG), are the gold standard for diagnosis and pre-surgical evaluation in epilepsy patients. The increasing trend towards multi-center clinical studies require signal visualization and analysis tools to support real time interaction with signal data in a collaborative environment, which cannot be supported by traditional desktop-based standalone applications. As part of the Prevention and Risk Identification of SUDEP Mortality (PRISM) project, we have developed a Web-based electrophysiology data visualization and analysis platform called Cloudwave using highly scalable open source cloud computing infrastructure. Cloudwave is integrated with the PRISM patient cohort identification tool called MEDCIS (Multi-modality Epilepsy Data Capture and Integration System). The Epilepsy and Seizure Ontology (EpSO) underpins both Cloudwave and MEDCIS to support query composition and result retrieval. Cloudwave is being used by clinicians and research staff at the University Hospital - Case Medical Center (UH-CMC) Epilepsy Monitoring Unit (EMU) and will be progressively deployed at four EMUs in the United States and the United Kingdomas part of the PRISM project.

pcircle - A Suite of Scalable Parallel File System Tools

DOE Office of Scientific and Technical Information (OSTI.GOV)

WANG, FEIYI

2015-10-01

Most of the software related to file system are written for conventional local file system, they are serialized and can't take advantage of the benefit of a large scale parallel file system. "pcircle" software builds on top of ubiquitous MPI in cluster computing environment and "work-stealing" pattern to provide a scalable, high-performance suite of file system tools. In particular - it implemented parallel data copy and parallel data checksumming, with advanced features such as async progress report, checkpoint and restart, as well as integrity checking.

Scalability of Robotic Controllers: An Evaluation of Controller Options-Experiment II

DTIC Science & Technology

2011-09-01

for the Soldier, to ensure mission success while maximizing the survivability and lethality through the synergistic interaction of equipment...based touch interface for gloved finger interactions . This interface had to have larger-than-normal touch-screen buttons for commanding the robot...C.; Hill, S.; Pillalamarri, K. Extreme Scalability: Designing Interfaces and Algorithms for Soldier-Robotic Swarm Interaction , Year 2; ARL- TR

Fast and Scalable Computation of the Forward and Inverse Discrete Periodic Radon Transform.

PubMed

Carranza, Cesar; Llamocca, Daniel; Pattichis, Marios

2016-01-01

The discrete periodic radon transform (DPRT) has extensively been used in applications that involve image reconstructions from projections. Beyond classic applications, the DPRT can also be used to compute fast convolutions that avoids the use of floating-point arithmetic associated with the use of the fast Fourier transform. Unfortunately, the use of the DPRT has been limited by the need to compute a large number of additions and the need for a large number of memory accesses. This paper introduces a fast and scalable approach for computing the forward and inverse DPRT that is based on the use of: a parallel array of fixed-point adder trees; circular shift registers to remove the need for accessing external memory components when selecting the input data for the adder trees; an image block-based approach to DPRT computation that can fit the proposed architecture to available resources; and fast transpositions that are computed in one or a few clock cycles that do not depend on the size of the input image. As a result, for an N × N image (N prime), the proposed approach can compute up to N(2) additions per clock cycle. Compared with the previous approaches, the scalable approach provides the fastest known implementations for different amounts of computational resources. For example, for a 251×251 image, for approximately 25% fewer flip-flops than required for a systolic implementation, we have that the scalable DPRT is computed 36 times faster. For the fastest case, we introduce optimized just 2N + ⌈log(2) N⌉ + 1 and 2N + 3 ⌈log(2) N⌉ + B + 2 cycles, architectures that can compute the DPRT and its inverse in respectively, where B is the number of bits used to represent each input pixel. On the other hand, the scalable DPRT approach requires more 1-b additions than for the systolic implementation and provides a tradeoff between speed and additional 1-b additions. All of the proposed DPRT architectures were implemented in VHSIC Hardware Description Language

Distributed Contour Trees

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morozov, Dmitriy; Weber, Gunther H.

2014-03-31

Topological techniques provide robust tools for data analysis. They are used, for example, for feature extraction, for data de-noising, and for comparison of data sets. This chapter concerns contour trees, a topological descriptor that records the connectivity of the isosurfaces of scalar functions. These trees are fundamental to analysis and visualization of physical phenomena modeled by real-valued measurements. We study the parallel analysis of contour trees. After describing a particular representation of a contour tree, called local{global representation, we illustrate how di erent problems that rely on contour trees can be solved in parallel with minimal communication.

Scalable High Performance Computing: Direct and Large-Eddy Turbulent Flow Simulations Using Massively Parallel Computers

NASA Technical Reports Server (NTRS)

Morgan, Philip E.

2004-01-01

This final report contains reports of research related to the tasks "Scalable High Performance Computing: Direct and Lark-Eddy Turbulent FLow Simulations Using Massively Parallel Computers" and "Devleop High-Performance Time-Domain Computational Electromagnetics Capability for RCS Prediction, Wave Propagation in Dispersive Media, and Dual-Use Applications. The discussion of Scalable High Performance Computing reports on three objectives: validate, access scalability, and apply two parallel flow solvers for three-dimensional Navier-Stokes flows; develop and validate a high-order parallel solver for Direct Numerical Simulations (DNS) and Large Eddy Simulation (LES) problems; and Investigate and develop a high-order Reynolds averaged Navier-Stokes turbulence model. The discussion of High-Performance Time-Domain Computational Electromagnetics reports on five objectives: enhancement of an electromagnetics code (CHARGE) to be able to effectively model antenna problems; utilize lessons learned in high-order/spectral solution of swirling 3D jets to apply to solving electromagnetics project; transition a high-order fluids code, FDL3DI, to be able to solve Maxwell's Equations using compact-differencing; develop and demonstrate improved radiation absorbing boundary conditions for high-order CEM; and extend high-order CEM solver to address variable material properties. The report also contains a review of work done by the systems engineer.

Towards Scalable Entangled Photon Sources with Self-Assembled InAs /GaAs Quantum Dots

NASA Astrophysics Data System (ADS)

Wang, Jianping; Gong, Ming; Guo, G.-C.; He, Lixin

2015-08-01

The biexciton cascade process in self-assembled quantum dots (QDs) provides an ideal system for realizing deterministic entangled photon-pair sources, which are essential to quantum information science. The entangled photon pairs have recently been generated in experiments after eliminating the fine-structure splitting (FSS) of excitons using a number of different methods. Thus far, however, QD-based sources of entangled photons have not been scalable because the wavelengths of QDs differ from dot to dot. Here, we propose a wavelength-tunable entangled photon emitter mounted on a three-dimensional stressor, in which the FSS and exciton energy can be tuned independently, thereby enabling photon entanglement between dissimilar QDs. We confirm these results via atomistic pseudopotential calculations. This provides a first step towards future realization of scalable entangled photon generators for quantum information applications.

Efficient transmission of compressed data for remote volume visualization.

PubMed

Krishnan, Karthik; Marcellin, Michael W; Bilgin, Ali; Nadar, Mariappan S

2006-09-01

One of the goals of telemedicine is to enable remote visualization and browsing of medical volumes. There is a need to employ scalable compression schemes and efficient client-server models to obtain interactivity and an enhanced viewing experience. First, we present a scheme that uses JPEG2000 and JPIP (JPEG2000 Interactive Protocol) to transmit data in a multi-resolution and progressive fashion. The server exploits the spatial locality offered by the wavelet transform and packet indexing information to transmit, in so far as possible, compressed volume data relevant to the clients query. Once the client identifies its volume of interest (VOI), the volume is refined progressively within the VOI from an initial lossy to a final lossless representation. Contextual background information can also be made available having quality fading away from the VOI. Second, we present a prioritization that enables the client to progressively visualize scene content from a compressed file. In our specific example, the client is able to make requests to progressively receive data corresponding to any tissue type. The server is now capable of reordering the same compressed data file on the fly to serve data packets prioritized as per the client's request. Lastly, we describe the effect of compression parameters on compression ratio, decoding times and interactivity. We also present suggestions for optimizing JPEG2000 for remote volume visualization and volume browsing applications. The resulting system is ideally suited for client-server applications with the server maintaining the compressed volume data, to be browsed by a client with a low bandwidth constraint.

Scalable high-precision tuning of photonic resonators by resonant cavity-enhanced photoelectrochemical etching

PubMed Central

Gil-Santos, Eduardo; Baker, Christopher; Lemaître, Aristide; Gomez, Carmen; Leo, Giuseppe; Favero, Ivan

2017-01-01

Photonic lattices of mutually interacting indistinguishable cavities represent a cornerstone of collective phenomena in optics and could become important in advanced sensing or communication devices. The disorder induced by fabrication technologies has so far hindered the development of such resonant cavity architectures, while post-fabrication tuning methods have been limited by complexity and poor scalability. Here we present a new simple and scalable tuning method for ensembles of microphotonic and nanophotonic resonators, which enables their permanent collective spectral alignment. The method introduces an approach of cavity-enhanced photoelectrochemical etching in a fluid, a resonant process triggered by sub-bandgap light that allows for high selectivity and precision. The technique is presented on a gallium arsenide nanophotonic platform and illustrated by finely tuning one, two and up to five resonators. It opens the way to applications requiring large networks of identical resonators and their spectral referencing to external etalons. PMID:28117394

OXC management and control system architecture with scalability, maintenance, and distributed managing environment

NASA Astrophysics Data System (ADS)

Park, Soomyung; Joo, Seong-Soon; Yae, Byung-Ho; Lee, Jong-Hyun

2002-07-01

In this paper, we present the Optical Cross-Connect (OXC) Management Control System Architecture, which has the scalability and robust maintenance and provides the distributed managing environment in the optical transport network. The OXC system we are developing, which is divided into the hardware and the internal and external software for the OXC system, is made up the OXC subsystem with the Optical Transport Network (OTN) sub layers-hardware and the optical switch control system, the signaling control protocol subsystem performing the User-to-Network Interface (UNI) and Network-to-Network Interface (NNI) signaling control, the Operation Administration Maintenance & Provisioning (OAM&P) subsystem, and the network management subsystem. And the OXC management control system has the features that can support the flexible expansion of the optical transport network, provide the connectivity to heterogeneous external network elements, be added or deleted without interrupting OAM&P services, be remotely operated, provide the global view and detail information for network planner and operator, and have Common Object Request Broker Architecture (CORBA) based the open system architecture adding and deleting the intelligent service networking functions easily in future. To meet these considerations, we adopt the object oriented development method in the whole developing steps of the system analysis, design, and implementation to build the OXC management control system with the scalability, the maintenance, and the distributed managing environment. As a consequently, the componentification for the OXC operation management functions of each subsystem makes the robust maintenance, and increases code reusability. Also, the component based OXC management control system architecture will have the flexibility and scalability in nature.

A Scalable Framework to Detect Personal Health Mentions on Twitter

PubMed Central

Fabbri, Daniel; Rosenbloom, S Trent

2015-01-01

Background Biomedical research has traditionally been conducted via surveys and the analysis of medical records. However, these resources are limited in their content, such that non-traditional domains (eg, online forums and social media) have an opportunity to supplement the view of an individual’s health. Objective The objective of this study was to develop a scalable framework to detect personal health status mentions on Twitter and assess the extent to which such information is disclosed. Methods We collected more than 250 million tweets via the Twitter streaming API over a 2-month period in 2014. The corpus was filtered down to approximately 250,000 tweets, stratified across 34 high-impact health issues, based on guidance from the Medical Expenditure Panel Survey. We created a labeled corpus of several thousand tweets via a survey, administered over Amazon Mechanical Turk, that documents when terms correspond to mentions of personal health issues or an alternative (eg, a metaphor). We engineered a scalable classifier for personal health mentions via feature selection and assessed its potential over the health issues. We further investigated the utility of the tweets by determining the extent to which Twitter users disclose personal health status. Results Our investigation yielded several notable findings. First, we find that tweets from a small subset of the health issues can train a scalable classifier to detect health mentions. Specifically, training on 2000 tweets from four health issues (cancer, depression, hypertension, and leukemia) yielded a classifier with precision of 0.77 on all 34 health issues. Second, Twitter users disclosed personal health status for all health issues. Notably, personal health status was disclosed over 50% of the time for 11 out of 34 (33%) investigated health issues. Third, the disclosure rate was dependent on the health issue in a statistically significant manner (P<.001). For instance, more than 80% of the tweets about

Space-Filling Supercapacitor Carpets: Highly scalable fractal architecture for energy storage

NASA Astrophysics Data System (ADS)

Tiliakos, Athanasios; Trefilov, Alexandra M. I.; Tanasǎ, Eugenia; Balan, Adriana; Stamatin, Ioan

2018-04-01

Revamping ground-breaking ideas from fractal geometry, we propose an alternative micro-supercapacitor configuration realized by laser-induced graphene (LIG) foams produced via laser pyrolysis of inexpensive commercial polymers. The Space-Filling Supercapacitor Carpet (SFSC) architecture introduces the concept of nested electrodes based on the pre-fractal Peano space-filling curve, arranged in a symmetrical equilateral setup that incorporates multiple parallel capacitor cells sharing common electrodes for maximum efficiency and optimal length-to-area distribution. We elucidate on the theoretical foundations of the SFSC architecture, and we introduce innovations (high-resolution vector-mode printing) in the LIG method that allow for the realization of flexible and scalable devices based on low iterations of the Peano algorithm. SFSCs exhibit distributed capacitance properties, leading to capacitance, energy, and power ratings proportional to the number of nested electrodes (up to 4.3 mF, 0.4 μWh, and 0.2 mW for the largest tested model of low iteration using aqueous electrolytes), with competitively high energy and power densities. This can pave the road for full scalability in energy storage, reaching beyond the scale of micro-supercapacitors for incorporating into larger and more demanding applications.

Stable scalable control of soliton propagation in broadband nonlinear optical waveguides

NASA Astrophysics Data System (ADS)

Peleg, Avner; Nguyen, Quan M.; Huynh, Toan T.

2017-02-01

We develop a method for achieving scalable transmission stabilization and switching of N colliding soliton sequences in optical waveguides with broadband delayed Raman response and narrowband nonlinear gain-loss. We show that dynamics of soliton amplitudes in N-sequence transmission is described by a generalized N-dimensional predator-prey model. Stability and bifurcation analysis for the predator-prey model are used to obtain simple conditions on the physical parameters for robust transmission stabilization as well as on-off and off-on switching of M out of N soliton sequences. Numerical simulations for single-waveguide transmission with a system of N coupled nonlinear Schrödinger equations with 2 ≤ N ≤ 4 show excellent agreement with the predator-prey model's predictions and stable propagation over significantly larger distances compared with other broadband nonlinear single-waveguide systems. Moreover, stable on-off and off-on switching of multiple soliton sequences and stable multiple transmission switching events are demonstrated by the simulations. We discuss the reasons for the robustness and scalability of transmission stabilization and switching in waveguides with broadband delayed Raman response and narrowband nonlinear gain-loss, and explain their advantages compared with other broadband nonlinear waveguides.

A lightweight scalable agarose-gel-synthesized thermoelectric composite

NASA Astrophysics Data System (ADS)

Kim, Jin Ho; Fernandes, Gustavo E.; Lee, Do-Joong; Hirst, Elizabeth S.; Osgood, Richard M., III; Xu, Jimmy

2018-03-01

Electronic devices are now advancing beyond classical, rigid systems and moving into lighweight flexible regimes, enabling new applications such as body-wearables and ‘e-textiles’. To support this new electronic platform, composite materials that are highly conductive yet scalable, flexible, and wearable are needed. Materials with high electrical conductivity often have poor thermoelectric properties because their thermal transport is made greater by the same factors as their electronic conductivity. We demonstrate, in proof-of-principle experiments, that a novel binary composite can disrupt thermal (phononic) transport, while maintaining high electrical conductivity, thus yielding promising thermoelectric properties. Highly conductive Multi-Wall Carbon Nanotube (MWCNT) composites are combined with a low-band gap semiconductor, PbS. The work functions of the two materials are closely matched, minimizing the electrical contact resistance within the composite. Disparities in the speed of sound in MWCNTs and PbS help to inhibit phonon propagation, and boundary layer scattering at interfaces between these two materials lead to large Seebeck coefficient (> 150 μV/K) (Mott N F and Davis E A 1971 Electronic Processes in Non-crystalline Materials (Oxford: Clarendon), p 47) and a power factor as high as 10 μW/(K2 m). The overall fabrication process is not only scalable but also conformal and compatible with large-area flexible hosts including metal sheets, films, coatings, possibly arrays of fibers, textiles and fabrics. We explain the behavior of this novel thermoelectric material platform in terms of differing length scales for electrical conductivity and phononic heat transfer, and explore new material configurations for potentially lightweight and flexible thermoelectric devices that could be networked in a textile.

fastBMA: scalable network inference and transitive reduction.

PubMed

Hung, Ling-Hong; Shi, Kaiyuan; Wu, Migao; Young, William Chad; Raftery, Adrian E; Yeung, Ka Yee

2017-10-01

Inferring genetic networks from genome-wide expression data is extremely demanding computationally. We have developed fastBMA, a distributed, parallel, and scalable implementation of Bayesian model averaging (BMA) for this purpose. fastBMA also includes a computationally efficient module for eliminating redundant indirect edges in the network by mapping the transitive reduction to an easily solved shortest-path problem. We evaluated the performance of fastBMA on synthetic data and experimental genome-wide time series yeast and human datasets. When using a single CPU core, fastBMA is up to 100 times faster than the next fastest method, LASSO, with increased accuracy. It is a memory-efficient, parallel, and distributed application that scales to human genome-wide expression data. A 10 000-gene regulation network can be obtained in a matter of hours using a 32-core cloud cluster (2 nodes of 16 cores). fastBMA is a significant improvement over its predecessor ScanBMA. It is more accurate and orders of magnitude faster than other fast network inference methods such as the 1 based on LASSO. The improved scalability allows it to calculate networks from genome scale data in a reasonable time frame. The transitive reduction method can improve accuracy in denser networks. fastBMA is available as code (M.I.T. license) from GitHub (https://github.com/lhhunghimself/fastBMA), as part of the updated networkBMA Bioconductor package (https://www.bioconductor.org/packages/release/bioc/html/networkBMA.html) and as ready-to-deploy Docker images (https://hub.docker.com/r/biodepot/fastbma/). © The Authors 2017. Published by Oxford University Press.

Scalability in Distance Education: "Can We Have Our Cake and Eat It Too?"

ERIC Educational Resources Information Center

Laws, R. Dwight; Howell, Scott L.; Lindsay, Nathan K.

2003-01-01

The decision to increase distance education enrollment hinges on the factors of pedagogical effectiveness, interactivity, audience, faculty incentives, retention, program type, and profitability. A complex interplay exists among these scalability concerns (i.e., issues related to meeting the growing enrollment demand), and any program's approach…

A scalable parallel algorithm for multiple objective linear programs

NASA Technical Reports Server (NTRS)

Wiecek, Malgorzata M.; Zhang, Hong

1994-01-01

This paper presents an ADBASE-based parallel algorithm for solving multiple objective linear programs (MOLP's). Job balance, speedup and scalability are of primary interest in evaluating efficiency of the new algorithm. Implementation results on Intel iPSC/2 and Paragon multiprocessors show that the algorithm significantly speeds up the process of solving MOLP's, which is understood as generating all or some efficient extreme points and unbounded efficient edges. The algorithm gives specially good results for large and very large problems. Motivation and justification for solving such large MOLP's are also included.

Integration of information and volume visualization for analysis of cell lineage and gene expression during embryogenesis

NASA Astrophysics Data System (ADS)

Cedilnik, Andrej; Baumes, Jeffrey; Ibanez, Luis; Megason, Sean; Wylie, Brian

2008-01-01

Dramatic technological advances in the field of genomics have made it possible to sequence the complete genomes of many different organisms. With this overwhelming amount of data at hand, biologists are now confronted with the challenge of understanding the function of the many different elements of the genome. One of the best places to start gaining insight on the mechanisms by which the genome controls an organism is the study of embryogenesis. There are multiple and inter-related layers of information that must be established in order to understand how the genome controls the formation of an organism. One is cell lineage which describes how patterns of cell division give rise to different parts of an organism. Another is gene expression which describes when and where different genes are turned on. Both of these data types can now be acquired using fluorescent laser-scanning (confocal or 2-photon) microscopy of embryos tagged with fluorescent proteins to generate 3D movies of developing embryos. However, analyzing the wealth of resulting images requires tools capable of interactively visualizing several different types of information as well as being scalable to terabytes of data. This paper describes how the combination of existing large data volume visualization and the new Titan information visualization framework of the Visualization Toolkit (VTK) can be applied to the problem of studying the cell lineage of an organism. In particular, by linking the visualization of spatial and temporal gene expression data with novel ways of visualizing cell lineage data, users can study how the genome regulates different aspects of embryonic development.

Scalable Architecture for Multihop Wireless ad Hoc Networks

NASA Technical Reports Server (NTRS)

Arabshahi, Payman; Gray, Andrew; Okino, Clayton; Yan, Tsun-Yee

2004-01-01

A scalable architecture for wireless digital data and voice communications via ad hoc networks has been proposed. Although the details of the architecture and of its implementation in hardware and software have yet to be developed, the broad outlines of the architecture are fairly clear: This architecture departs from current commercial wireless communication architectures, which are characterized by low effective bandwidth per user and are not well suited to low-cost, rapid scaling in large metropolitan areas. This architecture is inspired by a vision more akin to that of more than two dozen noncommercial community wireless networking organizations established by volunteers in North America and several European countries.

Shadow-Bitcoin: Scalable Simulation via Direct Execution of Multi-Threaded Applications

DTIC Science & Technology

2015-08-10

Shadow- Bitcoin : Scalable Simulation via Direct Execution of Multi-threaded Applications Andrew Miller University of Maryland amiller@cs.umd.edu Rob...Shadow plug-in that directly executes the Bitcoin reference client software. To demonstrate the usefulness of this tool, we present novel denial-of...service attacks against the Bit- coin software that exploit low-level implementation ar- tifacts in the Bitcoin reference client; our determinis- tic

Large-scale propagation of ultrasound in a 3-D breast model based on high-resolution MRI data.

PubMed

Salahura, Gheorghe; Tillett, Jason C; Metlay, Leon A; Waag, Robert C

2010-06-01

A 40 x 35 x 25-mm(3) specimen of human breast consisting mostly of fat and connective tissue was imaged using a 3-T magnetic resonance scanner. The resolutions in the image plane and in the orthogonal direction were 130 microm and 150 microm, respectively. Initial processing to prepare the data for segmentation consisted of contrast inversion, interpolation, and noise reduction. Noise reduction used a multilevel bidirectional median filter to preserve edges. The volume of data was segmented into regions of fat and connective tissue by using a combination of local and global thresholding. Local thresholding was performed to preserve fine detail, while global thresholding was performed to minimize the interclass variance between voxels classified as background and voxels classified as object. After smoothing the data to avoid aliasing artifacts, the segmented data volume was visualized using isosurfaces. The isosurfaces were enhanced using transparency, lighting, shading, reflectance, and animation. Computations of pulse propagation through the model illustrate its utility for the study of ultrasound aberration. The results show the feasibility of using the described combination of methods to demonstrate tissue morphology in a form that provides insight about the way ultrasound beams are aberrated in three dimensions by tissue.

Large-Scale Propagation of Ultrasound in a 3-D Breast Model Based on High-Resolution MRI Data

PubMed Central

Tillett, Jason C.; Metlay, Leon A.; Waag, Robert C.

2010-01-01

A 40 × 35 × 25-mm3 specimen of human breast consisting mostly of fat and connective tissue was imaged using a 3-T magnetic resonance scanner. The resolutions in the image plane and in the orthogonal direction were 130 μm and 150 μm, respectively. Initial processing to prepare the data for segmentation consisted of contrast inversion, interpolation, and noise reduction. Noise reduction used a multilevel bidirectional median filter to preserve edges. The volume of data was segmented into regions of fat and connective tissue by using a combination of local and global thresholding. Local thresholding was performed to preserve fine detail, while global thresholding was performed to minimize the interclass variance between voxels classified as background and voxels classified as object. After smoothing the data to avoid aliasing artifacts, the segmented data volume was visualized using iso-surfaces. The isosurfaces were enhanced using transparency, lighting, shading, reflectance, and animation. Computations of pulse propagation through the model illustrate its utility for the study of ultrasound aberration. The results show the feasibility of using the described combination of methods to demonstrate tissue morphology in a form that provides insight about the way ultrasound beams are aberrated in three dimensions by tissue. PMID:20172794

Scalable ranked retrieval using document images

NASA Astrophysics Data System (ADS)

Jain, Rajiv; Oard, Douglas W.; Doermann, David

2013-12-01

Despite the explosion of text on the Internet, hard copy documents that have been scanned as images still play a significant role for some tasks. The best method to perform ranked retrieval on a large corpus of document images, however, remains an open research question. The most common approach has been to perform text retrieval using terms generated by optical character recognition. This paper, by contrast, examines whether a scalable segmentation-free image retrieval algorithm, which matches sub-images containing text or graphical objects, can provide additional benefit in satisfying a user's information needs on a large, real world dataset. Results on 7 million scanned pages from the CDIP v1.0 test collection show that content based image retrieval finds a substantial number of documents that text retrieval misses, and that when used as a basis for relevance feedback can yield improvements in retrieval effectiveness.

A versatile scalable PET processing system

DOE Office of Scientific and Technical Information (OSTI.GOV)

H. Dong, A. Weisenberger, J. McKisson, Xi Wenze, C. Cuevas, J. Wilson, L. Zukerman

2011-06-01

Positron Emission Tomography (PET) historically has major clinical and preclinical applications in cancerous oncology, neurology, and cardiovascular diseases. Recently, in a new direction, an application specific PET system is being developed at Thomas Jefferson National Accelerator Facility (Jefferson Lab) in collaboration with Duke University, University of Maryland at Baltimore (UMAB), and West Virginia University (WVU) targeted for plant eco-physiology research. The new plant imaging PET system is versatile and scalable such that it could adapt to several plant imaging needs - imaging many important plant organs including leaves, roots, and stems. The mechanical arrangement of the detectors is designed tomore » accommodate the unpredictable and random distribution in space of the plant organs without requiring the plant be disturbed. Prototyping such a system requires a new data acquisition system (DAQ) and data processing system which are adaptable to the requirements of these unique and versatile detectors.« less

A Scalable Heuristic for Viral Marketing Under the Tipping Model

DTIC Science & Technology

2013-09-01

removal of high-degree nodes. The rest of the paper is organized as follows. In Section 2, we provide formal definitions of the tipping model. This is...that must be activated for it to become activate as well. A Scalable Heuristic for Viral Marketing Under the Tipping Model 3 Definition 1 (Threshold...returns a set of active nodes after one time step. Definition 2 (Activation Function) Given a threshold function, θ, an ac- tivation function Aθ maps

Enhancing Scalability and Efficiency of the TOUGH2_MP for LinuxClusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Keni; Wu, Yu-Shu

2006-04-17

TOUGH2{_}MP, the parallel version TOUGH2 code, has been enhanced by implementing more efficient communication schemes. This enhancement is achieved through reducing the amount of small-size messages and the volume of large messages. The message exchange speed is further improved by using non-blocking communications for both linear and nonlinear iterations. In addition, we have modified the AZTEC parallel linear-equation solver to nonblocking communication. Through the improvement of code structuring and bug fixing, the new version code is now more stable, while demonstrating similar or even better nonlinear iteration converging speed than the original TOUGH2 code. As a result, the new versionmore » of TOUGH2{_}MP is improved significantly in its efficiency. In this paper, the scalability and efficiency of the parallel code are demonstrated by solving two large-scale problems. The testing results indicate that speedup of the code may depend on both problem size and complexity. In general, the code has excellent scalability in memory requirement as well as computing time.« less

Scalability of Several Asynchronous Many-Task Models for In Situ Statistical Analysis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pebay, Philippe Pierre; Bennett, Janine Camille; Kolla, Hemanth

This report is a sequel to [PB16], in which we provided a first progress report on research and development towards a scalable, asynchronous many-task, in situ statistical analysis engine using the Legion runtime system. This earlier work included a prototype implementation of a proposed solution, using a proxy mini-application as a surrogate for a full-scale scientific simulation code. The first scalability studies were conducted with the above on modestly-sized experimental clusters. In contrast, in the current work we have integrated our in situ analysis engines with a full-size scientific application (S3D, using the Legion-SPMD model), and have conducted nu- mericalmore » tests on the largest computational platform currently available for DOE science ap- plications. We also provide details regarding the design and development of a light-weight asynchronous collectives library. We describe how this library is utilized within our SPMD- Legion S3D workflow, and compare the data aggregation technique deployed herein to the approach taken within our previous work.« less

A scalable and continuous-upgradable optical wireless and wired convergent access network.

PubMed

Sung, J Y; Cheng, K T; Chow, C W; Yeh, C H; Pan, C-L

2014-06-02

In this work, a scalable and continuous upgradable convergent optical access network is proposed. By using a multi-wavelength coherent comb source and a programmable waveshaper at the central office (CO), optical millimeter-wave (mm-wave) signals of different frequencies (from baseband to > 100 GHz) can be generated. Hence, it provides a scalable and continuous upgradable solution for end-user who needs 60 GHz wireless services now and > 100 GHz wireless services in the future. During the upgrade, user only needs to upgrade their optical networking unit (ONU). A programmable waveshaper is used to select the suitable optical tones with wavelength separation equals to the desired mm-wave frequency; while the CO remains intact. The centralized characteristics of the proposed system can easily add any new service and end-user. The centralized control of the wavelength makes the system more stable. Wired data rate of 17.45 Gb/s and w-band wireless data rate up to 3.36 Gb/s were demonstrated after transmission over 40 km of single-mode fiber (SMF).

An efficient and scalable deformable model for virtual reality-based medical applications.

PubMed

Choi, Kup-Sze; Sun, Hanqiu; Heng, Pheng-Ann

2004-09-01

Modeling of tissue deformation is of great importance to virtual reality (VR)-based medical simulations. Considerable effort has been dedicated to the development of interactively deformable virtual tissues. In this paper, an efficient and scalable deformable model is presented for virtual-reality-based medical applications. It considers deformation as a localized force transmittal process which is governed by algorithms based on breadth-first search (BFS). The computational speed is scalable to facilitate real-time interaction by adjusting the penetration depth. Simulated annealing (SA) algorithms are developed to optimize the model parameters by using the reference data generated with the linear static finite element method (FEM). The mechanical behavior and timing performance of the model have been evaluated. The model has been applied to simulate the typical behavior of living tissues and anisotropic materials. Integration with a haptic device has also been achieved on a generic personal computer (PC) platform. The proposed technique provides a feasible solution for VR-based medical simulations and has the potential for multi-user collaborative work in virtual environment.

Towards Sustainability and Scalability of Educational Innovations in Hydrology:What is the Value and who is the Customer?

NASA Astrophysics Data System (ADS)

Deshotel, M.; Habib, E. H.

2016-12-01

There is an increasing desire by the water education community to use emerging research resources and technological advances in order to reform current educational practices. Recent years have witnessed some exemplary developments that tap into emerging hydrologic modeling and data sharing resources, innovative digital and visualization technologies, and field experiences. However, such attempts remain largely at the scale of individual efforts and fall short of meeting scalability and sustainability solutions. This can be attributed to number of reasons such as inadequate experience with modeling and data-based educational developments, lack of faculty time to invest in further developments, and lack of resources to further support the project. Another important but often-overlooked reason is the lack of adequate insight on the actual needs of end-users of such developments. Such insight is highly critical to inform how to scale and sustain educational innovations. In this presentation, we share with the hydrologic community experiences gathered from an ongoing experiment where the authors engaged in a hypothesis-driven, customer-discovery process to inform the scalability and sustainability of educational innovations in the field of hydrology and water resources education. The experiment is part of a program called Innovation Corps for Learning (I-Corps L). This program follows a business model approach where a value proposition is initially formulated on the educational innovation. The authors then engaged in a hypothesis-validation process through an intense series of customer interviews with different segments of potential end users, including junior/senior students, student interns, and hydrology professors. The authors also sought insight from engineering firms by interviewing junior engineers and their supervisors to gather feedback on the preparedness of graduating engineers as they enter the workforce in the area of water resources. Exploring the large

Scalable implicit incompressible resistive MHD with stabilized FE and fully-coupled Newton–Krylov-AMG

DOE PAGES

Shadid, J. N.; Pawlowski, R. P.; Cyr, E. C.; ...

2016-02-10

Here, we discuss that the computational solution of the governing balance equations for mass, momentum, heat transfer and magnetic induction for resistive magnetohydrodynamics (MHD) systems can be extremely challenging. These difficulties arise from both the strong nonlinear, nonsymmetric coupling of fluid and electromagnetic phenomena, as well as the significant range of time- and length-scales that the interactions of these physical mechanisms produce. This paper explores the development of a scalable, fully-implicit stabilized unstructured finite element (FE) capability for 3D incompressible resistive MHD. The discussion considers the development of a stabilized FE formulation in context of the variational multiscale (VMS) method,more » and describes the scalable implicit time integration and direct-to-steady-state solution capability. The nonlinear solver strategy employs Newton–Krylov methods, which are preconditioned using fully-coupled algebraic multilevel preconditioners. These preconditioners are shown to enable a robust, scalable and efficient solution approach for the large-scale sparse linear systems generated by the Newton linearization. Verification results demonstrate the expected order-of-accuracy for the stabilized FE discretization. The approach is tested on a variety of prototype problems, that include MHD duct flows, an unstable hydromagnetic Kelvin–Helmholtz shear layer, and a 3D island coalescence problem used to model magnetic reconnection. Initial results that explore the scaling of the solution methods are also presented on up to 128K processors for problems with up to 1.8B unknowns on a CrayXK7.« less

Analysis of scalability of high-performance 3D image processing platform for virtual colonoscopy

NASA Astrophysics Data System (ADS)

Yoshida, Hiroyuki; Wu, Yin; Cai, Wenli

2014-03-01

One of the key challenges in three-dimensional (3D) medical imaging is to enable the fast turn-around time, which is often required for interactive or real-time response. This inevitably requires not only high computational power but also high memory bandwidth due to the massive amount of data that need to be processed. For this purpose, we previously developed a software platform for high-performance 3D medical image processing, called HPC 3D-MIP platform, which employs increasingly available and affordable commodity computing systems such as the multicore, cluster, and cloud computing systems. To achieve scalable high-performance computing, the platform employed size-adaptive, distributable block volumes as a core data structure for efficient parallelization of a wide range of 3D-MIP algorithms, supported task scheduling for efficient load distribution and balancing, and consisted of a layered parallel software libraries that allow image processing applications to share the common functionalities. We evaluated the performance of the HPC 3D-MIP platform by applying it to computationally intensive processes in virtual colonoscopy. Experimental results showed a 12-fold performance improvement on a workstation with 12-core CPUs over the original sequential implementation of the processes, indicating the efficiency of the platform. Analysis of performance scalability based on the Amdahl's law for symmetric multicore chips showed the potential of a high performance scalability of the HPC 3DMIP platform when a larger number of cores is available.

Volumetric Medical Image Coding: An Object-based, Lossy-to-lossless and Fully Scalable Approach

PubMed Central

Danyali, Habibiollah; Mertins, Alfred

2011-01-01

In this article, an object-based, highly scalable, lossy-to-lossless 3D wavelet coding approach for volumetric medical image data (e.g., magnetic resonance (MR) and computed tomography (CT)) is proposed. The new method, called 3DOBHS-SPIHT, is based on the well-known set partitioning in the hierarchical trees (SPIHT) algorithm and supports both quality and resolution scalability. The 3D input data is grouped into groups of slices (GOS) and each GOS is encoded and decoded as a separate unit. The symmetric tree definition of the original 3DSPIHT is improved by introducing a new asymmetric tree structure. While preserving the compression efficiency, the new tree structure allows for a small size of each GOS, which not only reduces memory consumption during the encoding and decoding processes, but also facilitates more efficient random access to certain segments of slices. To achieve more compression efficiency, the algorithm only encodes the main object of interest in each 3D data set, which can have any arbitrary shape, and ignores the unnecessary background. The experimental results on some MR data sets show the good performance of the 3DOBHS-SPIHT algorithm for multi-resolution lossy-to-lossless coding. The compression efficiency, full scalability, and object-based features of the proposed approach, beside its lossy-to-lossless coding support, make it a very attractive candidate for volumetric medical image information archiving and transmission applications. PMID:22606653

The ever-expanding role of asymmetric covalent organocatalysis in scalable, natural product synthesis.

PubMed

Abbasov, Mikail E; Romo, Daniel

2014-10-01

Following the turn of the millennium, the role of asymmetric covalent organocatalysis has developed into a scalable, synthetic paradigm galvanizing the synthetic community toward utilization of these methods toward more practical, metal-free syntheses of natural products. A myriad of reports on asymmetric organocatalytic modes of substrate activation relying on small, exclusively organic molecules are delineating what has now become the multifaceted field of organocatalysis. In covalent catalysis, the catalyst and substrate combine to first form a covalent, activated intermediate that enters the catalytic cycle. Following asymmetric bond formation, the chiral catalyst is recycled through hydrolysis or displacement by a pendant group on the newly formed product. Amine- and phosphine-based organocatalysts are the most common examples that have led to a vast array of reaction types. This Highlight provides a brief overview of covalent modes of organocatalysis and applications of scalable versions of these methods applied to the total synthesis of natural products including examples from our own laboratory.

Scalable hydrothermal synthesis of free-standing VO₂ nanowires in the M1 phase.

PubMed

Horrocks, Gregory A; Singh, Sujay; Likely, Maliek F; Sambandamurthy, G; Banerjee, Sarbajit

2014-09-24

VO2 nanostructures derived from solution-phase methods are often plagued by broadened and relatively diminished metal-insulator transitions and adventitious doping due to imperfect control of stoichiometry. Here, we demonstrate a stepwise scalable hydrothermal and annealing route for obtaining VO2 nanowires exhibiting almost 4 orders of magnitude abrupt (within 1 °C) metal-insulator transitions. The prepared nanowires have been characterized across their structural and electronic phase transitions using single-nanowire Raman microprobe analysis, ensemble differential scanning calorimetry, and single-nanowire electrical transport measurements. The electrical band gap is determined to be 600 meV and is consistent with the optical band gap of VO2, and the narrowness of differential scanning calorimetry profiles indicates homogeneity of stoichiometry. The preparation of high-quality free-standing nanowires exhibiting pronounced metal-insulator transitions by a solution-phase process allows for scalability, further solution-phase processing, incorporation within nanocomposites, and integration onto arbitrary substrates.

Citizen science provides a reliable and scalable tool to track disease-carrying mosquitoes.

PubMed

Palmer, John R B; Oltra, Aitana; Collantes, Francisco; Delgado, Juan Antonio; Lucientes, Javier; Delacour, Sarah; Bengoa, Mikel; Eritja, Roger; Bartumeus, Frederic

2017-10-24

Recent outbreaks of Zika, chikungunya and dengue highlight the importance of better understanding the spread of disease-carrying mosquitoes across multiple spatio-temporal scales. Traditional surveillance tools are limited by jurisdictional boundaries and cost constraints. Here we show how a scalable citizen science system can solve this problem by combining citizen scientists' observations with expert validation and correcting for sampling effort. Our system provides accurate early warning information about the Asian tiger mosquito (Aedes albopictus) invasion in Spain, well beyond that available from traditional methods, and vital for public health services. It also provides estimates of tiger mosquito risk comparable to those from traditional methods but more directly related to the human-mosquito encounters that are relevant for epidemiological modelling and scalable enough to cover the entire country. These results illustrate how powerful public participation in science can be and suggest citizen science is positioned to revolutionize mosquito-borne disease surveillance worldwide.

Scalable real space pseudopotential density functional codes for materials in the exascale regime

NASA Astrophysics Data System (ADS)

Lena, Charles; Chelikowsky, James; Schofield, Grady; Biller, Ariel; Kronik, Leeor; Saad, Yousef; Deslippe, Jack

Real-space pseudopotential density functional theory has proven to be an efficient method for computing the properties of matter in many different states and geometries, including liquids, wires, slabs, and clusters with and without spin polarization. Fully self-consistent solutions using this approach have been routinely obtained for systems with thousands of atoms. Yet, there are many systems of notable larger sizes where quantum mechanical accuracy is desired, but scalability proves to be a hindrance. Such systems include large biological molecules, complex nanostructures, or mismatched interfaces. We will present an overview of our new massively parallel algorithms, which offer improved scalability in preparation for exascale supercomputing. We will illustrate these algorithms by considering the electronic structure of a Si nanocrystal exceeding 104 atoms. Support provided by the SciDAC program, Department of Energy, Office of Science, Advanced Scientific Computing Research and Basic Energy Sciences. Grant Numbers DE-SC0008877 (Austin) and DE-FG02-12ER4 (Berkeley).

Toward Scalable Fabrication of Hierarchical Silica Capsules with Integrated Micro-, Meso-, and Macropores.

PubMed

Zhou, Weizheng; Tong, Gangsheng; Wang, Dali; Zhu, Bangshang; Ren, Yu; Butler, Michael; Pelan, Eddie; Yan, Deyue; Zhu, Xinyuan; Stoyanov, Simeon D

2016-04-06

Hierarchical porous structures are ubiquitous in biological organisms and inorganic systems. Although such structures have been replicated, designed, and fabricated, they are often inferior to naturally occurring analogues. Apart from the complexity and multiple functionalities developed by the biological systems, the controllable and scalable production of hierarchically porous structures and building blocks remains a technological challenge. Herein, a facile and scalable approach is developed to fabricate hierarchical hollow spheres with integrated micro-, meso-, and macropores ranging from 1 nm to 100 μm (spanning five orders of magnitude). (Macro)molecules, micro-rods (which play a key role for the creation of robust capsules), and emulsion droplets have been successfully employed as multiple length scale templates, allowing the creation of hierarchical porous macrospheres. Thanks to their specific mechanical strength, these hierarchical porous spheres could be incorporated and assembled as higher level building blocks in various novel materials. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hydra: a scalable proteomic search engine which utilizes the Hadoop distributed computing framework.

PubMed

Lewis, Steven; Csordas, Attila; Killcoyne, Sarah; Hermjakob, Henning; Hoopmann, Michael R; Moritz, Robert L; Deutsch, Eric W; Boyle, John

2012-12-05

For shotgun mass spectrometry based proteomics the most computationally expensive step is in matching the spectra against an increasingly large database of sequences and their post-translational modifications with known masses. Each mass spectrometer can generate data at an astonishingly high rate, and the scope of what is searched for is continually increasing. Therefore solutions for improving our ability to perform these searches are needed. We present a sequence database search engine that is specifically designed to run efficiently on the Hadoop MapReduce distributed computing framework. The search engine implements the K-score algorithm, generating comparable output for the same input files as the original implementation. The scalability of the system is shown, and the architecture required for the development of such distributed processing is discussed. The software is scalable in its ability to handle a large peptide database, numerous modifications and large numbers of spectra. Performance scales with the number of processors in the cluster, allowing throughput to expand with the available resources.

Ultrahigh-order Maxwell solver with extreme scalability for electromagnetic PIC simulations of plasmas

NASA Astrophysics Data System (ADS)

Vincenti, Henri; Vay, Jean-Luc

2018-07-01

The advent of massively parallel supercomputers, with their distributed-memory technology using many processing units, has favored the development of highly-scalable local low-order solvers at the expense of harder-to-scale global very high-order spectral methods. Indeed, FFT-based methods, which were very popular on shared memory computers, have been largely replaced by finite-difference (FD) methods for the solution of many problems, including plasmas simulations with electromagnetic Particle-In-Cell methods. For some problems, such as the modeling of so-called "plasma mirrors" for the generation of high-energy particles and ultra-short radiations, we have shown that the inaccuracies of standard FD-based PIC methods prevent the modeling on present supercomputers at sufficient accuracy. We demonstrate here that a new method, based on the use of local FFTs, enables ultrahigh-order accuracy with unprecedented scalability, and thus for the first time the accurate modeling of plasma mirrors in 3D.

Design and Implementation of a Scalable Membership Service for Supercomputer Resiliency-Aware Runtime

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tock, Yoav; Mandler, Benjamin; Moreira, Jose

2013-01-01

As HPC systems and applications get bigger and more complex, we are approaching an era in which resiliency and run-time elasticity concerns be- come paramount.We offer a building block for an alternative resiliency approach in which computations will be able to make progress while components fail, in addition to enabling a dynamic set of nodes throughout a computation lifetime. The core of our solution is a hierarchical scalable membership service provid- ing eventual consistency semantics. An attribute replication service is used for hierarchy organization, and is exposed to external applications. Our solution is based on P2P technologies and provides resiliencymore » and elastic runtime support at ultra large scales. Resulting middleware is general purpose while exploiting HPC platform unique features and architecture. We have implemented and tested this system on BlueGene/P with Linux, and using worst-case analysis, evaluated the service scalability as effective for up to 1M nodes.« less

Generation of scalable terahertz radiation from cylindrically focused two-color laser pulses in air

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuk, D.; Yoo, Y. J.; Rosenthal, E. W.

2016-03-21

We demonstrate scalable terahertz (THz) generation by focusing terawatt, two-color laser pulses in air with a cylindrical lens. This focusing geometry creates a two-dimensional air plasma sheet, which yields two diverging THz lobe profiles in the far field. This setup can avoid plasma-induced laser defocusing and subsequent THz saturation, previously observed with spherical lens focusing of high-power laser pulses. By expanding the plasma source into a two-dimensional sheet, cylindrical focusing can lead to scalable THz generation. This scheme provides an energy conversion efficiency of 7 × 10{sup −4}, ∼7 times better than spherical lens focusing. The diverging THz lobes are refocused withmore » a combination of cylindrical and parabolic mirrors to produce strong THz fields (>21 MV/cm) at the focal point.« less

Real-Time Agent-Based Modeling Simulation with in-situ Visualization of Complex Biological Systems: A Case Study on Vocal Fold Inflammation and Healing.

PubMed

Seekhao, Nuttiiya; Shung, Caroline; JaJa, Joseph; Mongeau, Luc; Li-Jessen, Nicole Y K

2016-05-01

We present an efficient and scalable scheme for implementing agent-based modeling (ABM) simulation with In Situ visualization of large complex systems on heterogeneous computing platforms. The scheme is designed to make optimal use of the resources available on a heterogeneous platform consisting of a multicore CPU and a GPU, resulting in minimal to no resource idle time. Furthermore, the scheme was implemented under a client-server paradigm that enables remote users to visualize and analyze simulation data as it is being generated at each time step of the model. Performance of a simulation case study of vocal fold inflammation and wound healing with 3.8 million agents shows 35× and 7× speedup in execution time over single-core and multi-core CPU respectively. Each iteration of the model took less than 200 ms to simulate, visualize and send the results to the client. This enables users to monitor the simulation in real-time and modify its course as needed.

The TOTEM DAQ based on the Scalable Readout System (SRS)

NASA Astrophysics Data System (ADS)

Quinto, Michele; Cafagna, Francesco S.; Fiergolski, Adrian; Radicioni, Emilio

2018-02-01

The TOTEM (TOTal cross section, Elastic scattering and diffraction dissociation Measurement at the LHC) experiment at LHC, has been designed to measure the total proton-proton cross-section and study the elastic and diffractive scattering at the LHC energies. In order to cope with the increased machine luminosity and the higher statistic required by the extension of the TOTEM physics program, approved for the LHC's Run Two phase, the previous VME based data acquisition system has been replaced with a new one based on the Scalable Readout System. The system features an aggregated data throughput of 2GB / s towards the online storage system. This makes it possible to sustain a maximum trigger rate of ˜ 24kHz, to be compared with the 1KHz rate of the previous system. The trigger rate is further improved by implementing zero-suppression and second-level hardware algorithms in the Scalable Readout System. The new system fulfils the requirements for an increased efficiency, providing higher bandwidth, and increasing the purity of the data recorded. Moreover full compatibility has been guaranteed with the legacy front-end hardware, as well as with the DAQ interface of the CMS experiment and with the LHC's Timing, Trigger and Control distribution system. In this contribution we describe in detail the architecture of full system and its performance measured during the commissioning phase at the LHC Interaction Point.

Toward optimized light utilization in nanowire arrays using scalable nanosphere lithography and selected area growth.

PubMed

Madaria, Anuj R; Yao, Maoqing; Chi, Chunyung; Huang, Ningfeng; Lin, Chenxi; Li, Ruijuan; Povinelli, Michelle L; Dapkus, P Daniel; Zhou, Chongwu

2012-06-13

Vertically aligned, catalyst-free semiconducting nanowires hold great potential for photovoltaic applications, in which achieving scalable synthesis and optimized optical absorption simultaneously is critical. Here, we report combining nanosphere lithography (NSL) and selected area metal-organic chemical vapor deposition (SA-MOCVD) for the first time for scalable synthesis of vertically aligned gallium arsenide nanowire arrays, and surprisingly, we show that such nanowire arrays with patterning defects due to NSL can be as good as highly ordered nanowire arrays in terms of optical absorption and reflection. Wafer-scale patterning for nanowire synthesis was done using a polystyrene nanosphere template as a mask. Nanowires grown from substrates patterned by NSL show similar structural features to those patterned using electron beam lithography (EBL). Reflection of photons from the NSL-patterned nanowire array was used as a measure of the effect of defects present in the structure. Experimentally, we show that GaAs nanowires as short as 130 nm show reflection of <10% over the visible range of the solar spectrum. Our results indicate that a highly ordered nanowire structure is not necessary: despite the "defects" present in NSL-patterned nanowire arrays, their optical performance is similar to "defect-free" structures patterned by more costly, time-consuming EBL methods. Our scalable approach for synthesis of vertical semiconducting nanowires can have application in high-throughput and low-cost optoelectronic devices, including solar cells.

The Efficiency and the Scalability of an Explicit Operator on an IBM POWER4 System

NASA Technical Reports Server (NTRS)

Frumkin, Michael; Biegel, Bryan A. (Technical Monitor)

2002-01-01

We present an evaluation of the efficiency and the scalability of an explicit CFD operator on an IBM POWER4 system. The POWER4 architecture exhibits a common trend in HPC architectures: boosting CPU processing power by increasing the number of functional units, while hiding the latency of memory access by increasing the depth of the memory hierarchy. The overall machine performance depends on the ability of the caches-buses-fabric-memory to feed the functional units with the data to be processed. In this study we evaluate the efficiency and scalability of one explicit CFD operator on an IBM POWER4. This operator performs computations at the points of a Cartesian grid and involves a few dozen floating point numbers and on the order of 100 floating point operations per grid point. The computations in all grid points are independent. Specifically, we estimate the efficiency of the RHS operator (SP of NPB) on a single processor as the observed/peak performance ratio. Then we estimate the scalability of the operator on a single chip (2 CPUs), a single MCM (8 CPUs), 16 CPUs, and the whole machine (32 CPUs). Then we perform the same measurements for a chache-optimized version of the RHS operator. For our measurements we use the HPM (Hardware Performance Monitor) counters available on the POWER4. These counters allow us to analyze the obtained performance results.

Web-Based Visual Analytics for Social Media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Best, Daniel M.; Bruce, Joseph R.; Dowson, Scott T.

Social media provides a rich source of data that reflects current trends and public opinion on a multitude of topics. The data can be harvested from Twitter, Facebook, Blogs, and other social applications. The high rate of adoption of social media has created a domain that has an ever expanding volume of data that make it difficult to use the raw data for analysis. Information visual analytics is key in drawing out features of interest in social media. The Scalable Reasoning System is an application that couples a back end server performing analysis algorithms and an intuitive front end visualizationmore » to allow for investigation. We provide a componentized system that can be rapidly adapted to customer needs such that the information they are most interested in is brought to their attention through the application. To this end, we have developed a social media application for use by emergency operations for the city of Seattle to show current weather and traffic trends which is important for their tasks.« less

The Broken Ring: Reduced Aromaticity in Lys-Trp Cations and High pH Tautomer Correlates with Lower Quantum Yield and Shorter Lifetimes

PubMed Central

2015-01-01

Several nonradiative processes compete with tryptophan fluorescence emission. The difficulty in spectral interpretation lies in associating specific molecular environmental features with these processes and thereby utilizing the fluorescence spectral data to identify the local environment of tryptophan. Here, spectroscopic and molecular modeling study of Lys-Trp dipeptide charged species shows that backbone-ring interactions are undistinguished. Instead, quantum mechanical ground state isosurfaces reveal variations in indole π electron distribution and density that parallel charge (as a function of pK1, pK2, and pKR) on the backbone and residues. A pattern of aromaticity-associated quantum yield and fluorescence lifetime changes emerges. Where quantum yield is high, isosurfaces have a charge distribution similar to the highest occupied molecular orbital (HOMO) of indole, which is the dominant fluorescent ground state of the 1La transition dipole moment. Where quantum yield is low, isosurface charge distribution over the ring is uneven, diminished, and even found off ring. At pH 13, the indole amine is deprotonated, and Lys-Trp quantum yield is extremely low due to tautomer structure that concentrates charge on the indole amine; the isosurface charge distribution bears scant resemblance to the indole HOMO. Such greatly diminished fluorescence has been observed for proteins where the indole nitrogen is hydrogen bonded, lending credence to the association of aromaticity changes with diminished quantum yield in proteins as well. Thus tryptophan ground state isosurfaces are an indicator of indole aromaticity, signaling the partition of excitation energy between radiative and nonradiative processes. PMID:24882092

A Transparently-Scalable Metadata Service for the Ursa Minor Storage System

DTIC Science & Technology

2010-06-25

provide application-level guarantees. For example, many document editing programs imple- ment atomic updates by writing the new document ver- sion into a...Transparently-Scalable Metadata Service for the Ursa Minor Storage System 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...operations that could involve multiple servers, how close existing systems come to transparent scala - bility, how systems that handle multi-server

celerite: Scalable 1D Gaussian Processes in C++, Python, and Julia

NASA Astrophysics Data System (ADS)

Foreman-Mackey, Daniel; Agol, Eric; Ambikasaran, Sivaram; Angus, Ruth

2017-09-01

celerite provides fast and scalable Gaussian Process (GP) Regression in one dimension and is implemented in C++, Python, and Julia. The celerite API is designed to be familiar to users of george and, like george, celerite is designed to efficiently evaluate the marginalized likelihood of a dataset under a GP model. This is then be used alongside a non-linear optimization or posterior inference library for the best results.

Highly Scalable Asynchronous Computing Method for Partial Differential Equations: A Path Towards Exascale

NASA Astrophysics Data System (ADS)

Konduri, Aditya

Many natural and engineering systems are governed by nonlinear partial differential equations (PDEs) which result in a multiscale phenomena, e.g. turbulent flows. Numerical simulations of these problems are computationally very expensive and demand for extreme levels of parallelism. At realistic conditions, simulations are being carried out on massively parallel computers with hundreds of thousands of processing elements (PEs). It has been observed that communication between PEs as well as their synchronization at these extreme scales take up a significant portion of the total simulation time and result in poor scalability of codes. This issue is likely to pose a bottleneck in scalability of codes on future Exascale systems. In this work, we propose an asynchronous computing algorithm based on widely used finite difference methods to solve PDEs in which synchronization between PEs due to communication is relaxed at a mathematical level. We show that while stability is conserved when schemes are used asynchronously, accuracy is greatly degraded. Since message arrivals at PEs are random processes, so is the behavior of the error. We propose a new statistical framework in which we show that average errors drop always to first-order regardless of the original scheme. We propose new asynchrony-tolerant schemes that maintain accuracy when synchronization is relaxed. The quality of the solution is shown to depend, not only on the physical phenomena and numerical schemes, but also on the characteristics of the computing machine. A novel algorithm using remote memory access communications has been developed to demonstrate excellent scalability of the method for large-scale computing. Finally, we present a path to extend this method in solving complex multi-scale problems on Exascale machines.

Toward Scalable Benchmarks for Mass Storage Systems

NASA Technical Reports Server (NTRS)

Miller, Ethan L.

1996-01-01

This paper presents guidelines for the design of a mass storage system benchmark suite, along with preliminary suggestions for programs to be included. The benchmarks will measure both peak and sustained performance of the system as well as predicting both short- and long-term behavior. These benchmarks should be both portable and scalable so they may be used on storage systems from tens of gigabytes to petabytes or more. By developing a standard set of benchmarks that reflect real user workload, we hope to encourage system designers and users to publish performance figures that can be compared with those of other systems. This will allow users to choose the system that best meets their needs and give designers a tool with which they can measure the performance effects of improvements to their systems.

Joint-layer encoder optimization for HEVC scalable extensions

NASA Astrophysics Data System (ADS)

Tsai, Chia-Ming; He, Yuwen; Dong, Jie; Ye, Yan; Xiu, Xiaoyu; He, Yong

2014-09-01

Scalable video coding provides an efficient solution to support video playback on heterogeneous devices with various channel conditions in heterogeneous networks. SHVC is the latest scalable video coding standard based on the HEVC standard. To improve enhancement layer coding efficiency, inter-layer prediction including texture and motion information generated from the base layer is used for enhancement layer coding. However, the overall performance of the SHVC reference encoder is not fully optimized because rate-distortion optimization (RDO) processes in the base and enhancement layers are independently considered. It is difficult to directly extend the existing joint-layer optimization methods to SHVC due to the complicated coding tree block splitting decisions and in-loop filtering process (e.g., deblocking and sample adaptive offset (SAO) filtering) in HEVC. To solve those problems, a joint-layer optimization method is proposed by adjusting the quantization parameter (QP) to optimally allocate the bit resource between layers. Furthermore, to make more proper resource allocation, the proposed method also considers the viewing probability of base and enhancement layers according to packet loss rate. Based on the viewing probability, a novel joint-layer RD cost function is proposed for joint-layer RDO encoding. The QP values of those coding tree units (CTUs) belonging to lower layers referenced by higher layers are decreased accordingly, and the QP values of those remaining CTUs are increased to keep total bits unchanged. Finally the QP values with minimal joint-layer RD cost are selected to match the viewing probability. The proposed method was applied to the third temporal level (TL-3) pictures in the Random Access configuration. Simulation results demonstrate that the proposed joint-layer optimization method can improve coding performance by 1.3% for these TL-3 pictures compared to the SHVC reference encoder without joint-layer optimization.

Scalable Faceted Ranking in Tagging Systems

NASA Astrophysics Data System (ADS)

Orlicki, José I.; Alvarez-Hamelin, J. Ignacio; Fierens, Pablo I.

Nowadays, web collaborative tagging systems which allow users to upload, comment on and recommend contents, are growing. Such systems can be represented as graphs where nodes correspond to users and tagged-links to recommendations. In this paper we analyze the problem of computing a ranking of users with respect to a facet described as a set of tags. A straightforward solution is to compute a PageRank-like algorithm on a facet-related graph, but it is not feasible for online computation. We propose an alternative: (i) a ranking for each tag is computed offline on the basis of tag-related subgraphs; (ii) a faceted order is generated online by merging rankings corresponding to all the tags in the facet. Based on the graph analysis of YouTube and Flickr, we show that step (i) is scalable. We also present efficient algorithms for step (ii), which are evaluated by comparing their results with two gold standards.

An Intelligent Cooperative Visual Sensor Network for Urban Mobility

PubMed Central

Leone, Giuseppe Riccardo; Petracca, Matteo; Salvetti, Ovidio; Azzarà, Andrea

2017-01-01

Smart cities are demanding solutions for improved traffic efficiency, in order to guarantee optimal access to mobility resources available in urban areas. Intelligent video analytics deployed directly on board embedded sensors offers great opportunities to gather highly informative data about traffic and transport, allowing reconstruction of a real-time neat picture of urban mobility patterns. In this paper, we present a visual sensor network in which each node embeds computer vision logics for analyzing in real time urban traffic. The nodes in the network share their perceptions and build a global and comprehensive interpretation of the analyzed scenes in a cooperative and adaptive fashion. This is possible thanks to an especially designed Internet of Things (IoT) compliant middleware which encompasses in-network event composition as well as full support of Machine-2-Machine (M2M) communication mechanism. The potential of the proposed cooperative visual sensor network is shown with two sample applications in urban mobility connected to the estimation of vehicular flows and parking management. Besides providing detailed results of each key component of the proposed solution, the validity of the approach is demonstrated by extensive field tests that proved the suitability of the system in providing a scalable, adaptable and extensible data collection layer for managing and understanding mobility in smart cities. PMID:29125535

Scalable web services for the PSIPRED Protein Analysis Workbench.

PubMed

Buchan, Daniel W A; Minneci, Federico; Nugent, Tim C O; Bryson, Kevin; Jones, David T

2013-07-01

Here, we present the new UCL Bioinformatics Group's PSIPRED Protein Analysis Workbench. The Workbench unites all of our previously available analysis methods into a single web-based framework. The new web portal provides a greatly streamlined user interface with a number of new features to allow users to better explore their results. We offer a number of additional services to enable computationally scalable execution of our prediction methods; these include SOAP and XML-RPC web server access and new HADOOP packages. All software and services are available via the UCL Bioinformatics Group website at http://bioinf.cs.ucl.ac.uk/.

Optimal erasure protection for scalably compressed video streams with limited retransmission.

PubMed

Taubman, David; Thie, Johnson

2005-08-01

This paper shows how the priority encoding transmission (PET) framework may be leveraged to exploit both unequal error protection and limited retransmission for RD-optimized delivery of streaming media. Previous work on scalable media protection with PET has largely ignored the possibility of retransmission. Conversely, the PET framework has not been harnessed by the substantial body of previous work on RD optimized hybrid forward error correction/automatic repeat request schemes. We limit our attention to sources which can be modeled as independently compressed frames (e.g., video frames), where each element in the scalable representation of each frame can be transmitted in one or both of two transmission slots. An optimization algorithm determines the level of protection which should be assigned to each element in each slot, subject to transmission bandwidth constraints. To balance the protection assigned to elements which are being transmitted for the first time with those which are being retransmitted, the proposed algorithm formulates a collection of hypotheses concerning its own behavior in future transmission slots. We show how the PET framework allows for a decoupled optimization algorithm with only modest complexity. Experimental results obtained with Motion JPEG2000 compressed video demonstrate that substantial performance benefits can be obtained using the proposed framework.

Scalable creation of gold nanostructures on high performance engineering polymeric substrate

NASA Astrophysics Data System (ADS)

Jia, Kun; Wang, Pan; Wei, Shiliang; Huang, Yumin; Liu, Xiaobo

2017-12-01

The article reveals a facile protocol for scalable production of gold nanostructures on a high performance engineering thermoplastic substrate made of polyarylene ether nitrile (PEN) for the first time. Firstly, gold thin films with different thicknesses of 2 nm, 4 nm and 6 nm were evaporated on a spin-coated PEN substrate on glass slide in vacuum. Next, the as-evaporated samples were thermally annealed around the glass transition temperature of the PEN substrate, on which gold nanostructures with island-like morphology were created. Moreover, it was found that the initial gold evaporation thickness and annealing atmosphere played an important role in determining the morphology and plasmonic properties of the formulated Au NPs. Interestingly, we discovered that isotropic Au NPs can be easily fabricated on the freestanding PEN substrate, which was fabricated by a cost-effective polymer solution casting method. More specifically, monodispersed Au nanospheres with an average size of ∼60 nm were obtained after annealing a 4 nm gold film covered PEN casting substrate at 220 °C for 2 h in oxygen. Therefore, the scalable production of Au NPs with controlled morphology on PEN substrate would open the way for development of robust flexible nanosensors and optical devices using high performance engineering polyarylene ethers.

Scalable Method to Produce Biodegradable Nanoparticles that Rapidly Penetrate Human Mucus

PubMed Central

Xu, Qingguo; Boylan, Nicholas J.; Cai, Shutian; Miao, Bolong; Patel, Himatkumar; Hanes, Justin

2013-01-01

Mucus typically traps and rapidly removes foreign particles from the airways, gastrointestinal tract, nasopharynx, female reproductive tract and the surface of the eye. Nanoparticles capable of rapid penetration through mucus can potentially avoid rapid clearance, and open significant opportunities for controlled drug delivery at mucosal surfaces. Here, we report an industrially scalable emulsification method to produce biodegradable mucus-penetrating particles (MPP). The emulsification of diblock copolymers of poly(lactic-co-glycolic acid) and polyethylene glycol (PLGA-PEG) using low molecular weight (MW) emulsifiers forms dense brush PEG coatings on nanoparticles that allow rapid nanoparticle penetration through fresh undiluted human mucus. In comparison, conventional high MW emulsifiers, such as polyvinyl alcohol (PVA), interrupts the PEG coating on nanoparticles, resulting in their immobilization in mucus owing to adhesive interactions with mucus mesh elements. PLGA-PEG nanoparticles with a wide range of PEG MW (1, 2, 5, and 10 kDa), prepared by the emulsification method using low MW emulsifiers, all rapidly penetrated mucus. A range of drugs, from hydrophobic small molecules to hydrohilic large biologics, can be efficiently loaded into biodegradable MPP using the method described. This readily scalable method should facilitate the production of MPP products for mucosal drug delivery, as well as potentially longer-circulating particles following intravenous administration. PMID:23751567

A Multi-Time Scale Morphable Software Milieu for Polymorphous Computing Architectures (PCA) - Composable, Scalable Systems

DTIC Science & Technology

2004-10-01

MONITORING AGENCY NAME(S) AND ADDRESS(ES) Defense Advanced Research Projects Agency AFRL/IFTC 3701 North Fairfax Drive...Scalable Parallel Libraries for Large-Scale Concurrent Applications," Technical Report UCRL -JC-109251, Lawrence Livermore National Laboratory

Template-Assisted Scalable Nanowire Networks

NASA Astrophysics Data System (ADS)

Friedl, Martin; Cerveny, Kris; Weigele, Pirmin; Tütüncüoglu, Gozde; Martí-Sánchez, Sara; Huang, Chunyi; Patlatiuk, Taras; Potts, Heidi; Sun, Zhiyuan; Hill, Megan O.; Güniat, Lucas; Kim, Wonjong; Zamani, Mahdi; Dubrovskii, Vladimir G.; Arbiol, Jordi; Lauhon, Lincoln J.; Zumbühl, Dominik M.; Fontcuberta i Morral, Anna

2018-04-01

Topological qubits based on Majorana fermions have the potential to revolutionize the emerging field of quantum computing by making information processing significantly more robust to decoherence. Nanowires (NWs) are a promising medium for hosting these kinds of qubits, though branched NWs are needed to perform qubit manipulations. Here we report gold-free templated growth of III-V NWs by molecular beam epitaxy using an approach that enables patternable and highly regular branched NW arrays on a far greater scale than what has been reported thus far. Our approach relies on the lattice-mismatched growth of InAs on top of defect-free GaAs nanomembranes (NMs) yielding laterally-oriented, low-defect InAs and InGaAs NWs whose shapes are determined by surface and strain energy minimization. By controlling NM width and growth time, we demonstrate the formation of compositionally graded NWs with cross-sections less than 50 nm. Scaling the NWs below 20 nm leads to the formation of homogenous InGaAs NWs which exhibit phase-coherent, quasi-1D quantum transport as shown by magnetoconductance measurements. These results are an important advance towards scalable topological quantum computing.

Template-Assisted Scalable Nanowire Networks.

PubMed

Friedl, Martin; Cerveny, Kris; Weigele, Pirmin; Tütüncüoglu, Gozde; Martí-Sánchez, Sara; Huang, Chunyi; Patlatiuk, Taras; Potts, Heidi; Sun, Zhiyuan; Hill, Megan O; Güniat, Lucas; Kim, Wonjong; Zamani, Mahdi; Dubrovskii, Vladimir G; Arbiol, Jordi; Lauhon, Lincoln J; Zumbühl, Dominik M; Fontcuberta I Morral, Anna

2018-04-11

Topological qubits based on Majorana Fermions have the potential to revolutionize the emerging field of quantum computing by making information processing significantly more robust to decoherence. Nanowires are a promising medium for hosting these kinds of qubits, though branched nanowires are needed to perform qubit manipulations. Here we report a gold-free templated growth of III-V nanowires by molecular beam epitaxy using an approach that enables patternable and highly regular branched nanowire arrays on a far greater scale than what has been reported thus far. Our approach relies on the lattice-mismatched growth of InAs on top of defect-free GaAs nanomembranes yielding laterally oriented, low-defect InAs and InGaAs nanowires whose shapes are determined by surface and strain energy minimization. By controlling nanomembrane width and growth time, we demonstrate the formation of compositionally graded nanowires with cross-sections less than 50 nm. Scaling the nanowires below 20 nm leads to the formation of homogeneous InGaAs nanowires, which exhibit phase-coherent, quasi-1D quantum transport as shown by magnetoconductance measurements. These results are an important advance toward scalable topological quantum computing.

Scalable Production Method for Graphene Oxide Water Vapor Separation Membranes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fifield, Leonard S.; Shin, Yongsoon; Liu, Wei

ABSTRACT Membranes for selective water vapor separation were assembled from graphene oxide suspension using techniques compatible with high volume industrial production. The large-diameter graphene oxide flake suspensions were synthesized from graphite materials via relatively efficient chemical oxidation steps with attention paid to maintaining flake size and achieving high graphene oxide concentrations. Graphene oxide membranes produced using scalable casting methods exhibited water vapor flux and water/nitrogen selectivity performance meeting or exceeding that of membranes produced using vacuum-assisted laboratory techniques. (PNNL-SA-117497)

Fast and Exact Fiber Surfaces for Tetrahedral Meshes.

PubMed

Klacansky, Pavol; Tierny, Julien; Carr, Hamish; Zhao Geng

2017-07-01

Isosurfaces are fundamental geometrical objects for the analysis and visualization of volumetric scalar fields. Recent work has generalized them to bivariate volumetric fields with fiber surfaces, the pre-image of polygons in range space. However, the existing algorithm for their computation is approximate, and is limited to closed polygons. Moreover, its runtime performance does not allow instantaneous updates of the fiber surfaces upon user edits of the polygons. Overall, these limitations prevent a reliable and interactive exploration of the space of fiber surfaces. This paper introduces the first algorithm for the exact computation of fiber surfaces in tetrahedral meshes. It assumes no restriction on the topology of the input polygon, handles degenerate cases and better captures sharp features induced by polygon bends. The algorithm also allows visualization of individual fibers on the output surface, better illustrating their relationship with data features in range space. To enable truly interactive exploration sessions, we further improve the runtime performance of this algorithm. In particular, we show that it is trivially parallelizable and that it scales nearly linearly with the number of cores. Further, we study acceleration data-structures both in geometrical domain and range space and we show how to generalize interval trees used in isosurface extraction to fiber surface extraction. Experiments demonstrate the superiority of our algorithm over previous work, both in terms of accuracy and running time, with up to two orders of magnitude speedups. This improvement enables interactive edits of range polygons with instantaneous updates of the fiber surface for exploration purpose. A VTK-based reference implementation is provided as additional material to reproduce our results.

Statistical exchange-coupling errors and the practicality of scalable silicon donor qubits

NASA Astrophysics Data System (ADS)

Song, Yang; Das Sarma, S.

2016-12-01

Recent experimental efforts have led to considerable interest in donor-based localized electron spins in Si as viable qubits for a scalable silicon quantum computer. With the use of isotopically purified 28Si and the realization of extremely long spin coherence time in single-donor electrons, the recent experimental focus is on two-coupled donors with the eventual goal of a scaled-up quantum circuit. Motivated by this development, we simulate the statistical distribution of the exchange coupling J between a pair of donors under realistic donor placement straggles, and quantify the errors relative to the intended J value. With J values in a broad range of donor-pair separation ( 5 <|R |<60 nm), we work out various cases systematically, for a target donor separation R0 along the [001], [110] and [111] Si crystallographic directions, with |R0|=10 ,20 or 30 nm and standard deviation σR=1 ,2 ,5 or 10 nm. Our extensive theoretical results demonstrate the great challenge for a prescribed J gate even with just a donor pair, a first step for any scalable Si-donor-based quantum computer.

Scalable Creation of Long-Lived Multipartite Entanglement

NASA Astrophysics Data System (ADS)

Kaufmann, H.; Ruster, T.; Schmiegelow, C. T.; Luda, M. A.; Kaushal, V.; Schulz, J.; von Lindenfels, D.; Schmidt-Kaler, F.; Poschinger, U. G.

2017-10-01

We demonstrate the deterministic generation of multipartite entanglement based on scalable methods. Four qubits are encoded in 40Ca+, stored in a microstructured segmented Paul trap. These qubits are sequentially entangled by laser-driven pairwise gate operations. Between these, the qubit register is dynamically reconfigured via ion shuttling operations, where ion crystals are separated and merged, and ions are moved in and out of a fixed laser interaction zone. A sequence consisting of three pairwise entangling gates yields a four-ion Greenberger-Horne-Zeilinger state |ψ ⟩=(1 /√{2 })(|0000 ⟩+|1111 ⟩) , and full quantum state tomography reveals a state fidelity of 94.4(3)%. We analyze the decoherence of this state and employ dynamic decoupling on the spatially distributed constituents to maintain 69(5)% coherence at a storage time of 1.1 sec.

Scalable randomized benchmarking of non-Clifford gates

NASA Astrophysics Data System (ADS)

Cross, Andrew; Magesan, Easwar; Bishop, Lev; Smolin, John; Gambetta, Jay

Randomized benchmarking is a widely used experimental technique to characterize the average error of quantum operations. Benchmarking procedures that scale to enable characterization of n-qubit circuits rely on efficient procedures for manipulating those circuits and, as such, have been limited to subgroups of the Clifford group. However, universal quantum computers require additional, non-Clifford gates to approximate arbitrary unitary transformations. We define a scalable randomized benchmarking procedure over n-qubit unitary matrices that correspond to protected non-Clifford gates for a class of stabilizer codes. We present efficient methods for representing and composing group elements, sampling them uniformly, and synthesizing corresponding poly (n) -sized circuits. The procedure provides experimental access to two independent parameters that together characterize the average gate fidelity of a group element. We acknowledge support from ARO under Contract W911NF-14-1-0124.

Scalable Creation of Long-Lived Multipartite Entanglement.

PubMed

Kaufmann, H; Ruster, T; Schmiegelow, C T; Luda, M A; Kaushal, V; Schulz, J; von Lindenfels, D; Schmidt-Kaler, F; Poschinger, U G

2017-10-13

We demonstrate the deterministic generation of multipartite entanglement based on scalable methods. Four qubits are encoded in ^{40}Ca^{+}, stored in a microstructured segmented Paul trap. These qubits are sequentially entangled by laser-driven pairwise gate operations. Between these, the qubit register is dynamically reconfigured via ion shuttling operations, where ion crystals are separated and merged, and ions are moved in and out of a fixed laser interaction zone. A sequence consisting of three pairwise entangling gates yields a four-ion Greenberger-Horne-Zeilinger state |ψ⟩=(1/sqrt[2])(|0000⟩+|1111⟩), and full quantum state tomography reveals a state fidelity of 94.4(3)%. We analyze the decoherence of this state and employ dynamic decoupling on the spatially distributed constituents to maintain 69(5)% coherence at a storage time of 1.1 sec.

Scalable Active Optical Access Network Using Variable High-Speed PLZT Optical Switch/Splitter

NASA Astrophysics Data System (ADS)

Ashizawa, Kunitaka; Sato, Takehiro; Tokuhashi, Kazumasa; Ishii, Daisuke; Okamoto, Satoru; Yamanaka, Naoaki; Oki, Eiji

This paper proposes a scalable active optical access network using high-speed Plumbum Lanthanum Zirconate Titanate (PLZT) optical switch/splitter. The Active Optical Network, called ActiON, using PLZT switching technology has been presented to increase the number of subscribers and the maximum transmission distance, compared to the Passive Optical Network (PON). ActiON supports the multicast slot allocation realized by running the PLZT switch elements in the splitter mode, which forces the switch to behave as an optical splitter. However, the previous ActiON creates a tradeoff between the network scalability and the power loss experienced by the optical signal to each user. It does not use the optical power efficiently because the optical power is simply divided into 0.5 to 0.5 without considering transmission distance from OLT to each ONU. The proposed network adopts PLZT switch elements in the variable splitter mode, which controls the split ratio of the optical power considering the transmission distance from OLT to each ONU, in addition to PLZT switch elements in existing two modes, the switching mode and the splitter mode. The proposed network introduces the flexible multicast slot allocation according to the transmission distance from OLT to each user and the number of required users using three modes, while keeping the advantages of ActiON, which are to support scalable and secure access services. Numerical results show that the proposed network dramatically reduces the required number of slots and supports high bandwidth efficiency services and extends the coverage of access network, compared to the previous ActiON, and the required computation time for selecting multicast users is less than 30msec, which is acceptable for on-demand broadcast services.

Visibiome: an efficient microbiome search engine based on a scalable, distributed architecture.

PubMed

Azman, Syafiq Kamarul; Anwar, Muhammad Zohaib; Henschel, Andreas

2017-07-24

Given the current influx of 16S rRNA profiles of microbiota samples, it is conceivable that large amounts of them eventually are available for search, comparison and contextualization with respect to novel samples. This process facilitates the identification of similar compositional features in microbiota elsewhere and therefore can help to understand driving factors for microbial community assembly. We present Visibiome, a microbiome search engine that can perform exhaustive, phylogeny based similarity search and contextualization of user-provided samples against a comprehensive dataset of 16S rRNA profiles environments, while tackling several computational challenges. In order to scale to high demands, we developed a distributed system that combines web framework technology, task queueing and scheduling, cloud computing and a dedicated database server. To further ensure speed and efficiency, we have deployed Nearest Neighbor search algorithms, capable of sublinear searches in high-dimensional metric spaces in combination with an optimized Earth Mover Distance based implementation of weighted UniFrac. The search also incorporates pairwise (adaptive) rarefaction and optionally, 16S rRNA copy number correction. The result of a query microbiome sample is the contextualization against a comprehensive database of microbiome samples from a diverse range of environments, visualized through a rich set of interactive figures and diagrams, including barchart-based compositional comparisons and ranking of the closest matches in the database. Visibiome is a convenient, scalable and efficient framework to search microbiomes against a comprehensive database of environmental samples. The search engine leverages a popular but computationally expensive, phylogeny based distance metric, while providing numerous advantages over the current state of the art tool.

Scalable, Lightweight, Integrated and Quick-to-Assemble (SLIQ) Hyperdrives for Functional Circuit Dissection.

PubMed

Liang, Li; Oline, Stefan N; Kirk, Justin C; Schmitt, Lukas Ian; Komorowski, Robert W; Remondes, Miguel; Halassa, Michael M

2017-01-01

Independently adjustable multielectrode arrays are routinely used to interrogate neuronal circuit function, enabling chronic in vivo monitoring of neuronal ensembles in freely behaving animals at a single-cell, single spike resolution. Despite the importance of this approach, its widespread use is limited by highly specialized design and fabrication methods. To address this, we have developed a Scalable, Lightweight, Integrated and Quick-to-assemble multielectrode array platform. This platform additionally integrates optical fibers with independently adjustable electrodes to allow simultaneous single unit recordings and circuit-specific optogenetic targeting and/or manipulation. In current designs, the fully assembled platforms are scalable from 2 to 32 microdrives, and yet range 1-3 g, light enough for small animals. Here, we describe the design process starting from intent in computer-aided design, parameter testing through finite element analysis and experimental means, and implementation of various applications across mice and rats. Combined, our methods may expand the utility of multielectrode recordings and their continued integration with other tools enabling functional dissection of intact neural circuits.

Hydra: a scalable proteomic search engine which utilizes the Hadoop distributed computing framework

PubMed Central

2012-01-01

Background For shotgun mass spectrometry based proteomics the most computationally expensive step is in matching the spectra against an increasingly large database of sequences and their post-translational modifications with known masses. Each mass spectrometer can generate data at an astonishingly high rate, and the scope of what is searched for is continually increasing. Therefore solutions for improving our ability to perform these searches are needed. Results We present a sequence database search engine that is specifically designed to run efficiently on the Hadoop MapReduce distributed computing framework. The search engine implements the K-score algorithm, generating comparable output for the same input files as the original implementation. The scalability of the system is shown, and the architecture required for the development of such distributed processing is discussed. Conclusion The software is scalable in its ability to handle a large peptide database, numerous modifications and large numbers of spectra. Performance scales with the number of processors in the cluster, allowing throughput to expand with the available resources. PMID:23216909

A Bit Stream Scalable Speech/Audio Coder Combining Enhanced Regular Pulse Excitation and Parametric Coding

NASA Astrophysics Data System (ADS)

Riera-Palou, Felip; den Brinker, Albertus C.

2007-12-01

This paper introduces a new audio and speech broadband coding technique based on the combination of a pulse excitation coder and a standardized parametric coder, namely, MPEG-4 high-quality parametric coder. After presenting a series of enhancements to regular pulse excitation (RPE) to make it suitable for the modeling of broadband signals, it is shown how pulse and parametric codings complement each other and how they can be merged to yield a layered bit stream scalable coder able to operate at different points in the quality bit rate plane. The performance of the proposed coder is evaluated in a listening test. The major result is that the extra functionality of the bit stream scalability does not come at the price of a reduced performance since the coder is competitive with standardized coders (MP3, AAC, SSC).

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience.

PubMed

Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R; Bock, Davi D; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R Clay; Smith, Stephen J; Szalay, Alexander S; Vogelstein, Joshua T; Vogelstein, R Jacob

2013-01-01

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes - neural connectivity maps of the brain-using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems-reads to parallel disk arrays and writes to solid-state storage-to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization.

The Open Connectome Project Data Cluster: Scalable Analysis and Vision for High-Throughput Neuroscience

PubMed Central

Burns, Randal; Roncal, William Gray; Kleissas, Dean; Lillaney, Kunal; Manavalan, Priya; Perlman, Eric; Berger, Daniel R.; Bock, Davi D.; Chung, Kwanghun; Grosenick, Logan; Kasthuri, Narayanan; Weiler, Nicholas C.; Deisseroth, Karl; Kazhdan, Michael; Lichtman, Jeff; Reid, R. Clay; Smith, Stephen J.; Szalay, Alexander S.; Vogelstein, Joshua T.; Vogelstein, R. Jacob

2013-01-01

We describe a scalable database cluster for the spatial analysis and annotation of high-throughput brain imaging data, initially for 3-d electron microscopy image stacks, but for time-series and multi-channel data as well. The system was designed primarily for workloads that build connectomes— neural connectivity maps of the brain—using the parallel execution of computer vision algorithms on high-performance compute clusters. These services and open-science data sets are publicly available at openconnecto.me. The system design inherits much from NoSQL scale-out and data-intensive computing architectures. We distribute data to cluster nodes by partitioning a spatial index. We direct I/O to different systems—reads to parallel disk arrays and writes to solid-state storage—to avoid I/O interference and maximize throughput. All programming interfaces are RESTful Web services, which are simple and stateless, improving scalability and usability. We include a performance evaluation of the production system, highlighting the effec-tiveness of spatial data organization. PMID:24401992

Efficient and Scalable Cross-Matching of (Very) Large Catalogs

NASA Astrophysics Data System (ADS)

Pineau, F.-X.; Boch, T.; Derriere, S.

2011-07-01

Whether it be for building multi-wavelength datasets from independent surveys, studying changes in objects luminosities, or detecting moving objects (stellar proper motions, asteroids), cross-catalog matching is a technique widely used in astronomy. The need for efficient, reliable and scalable cross-catalog matching is becoming even more pressing with forthcoming projects which will produce huge catalogs in which astronomers will dig for rare objects, perform statistical analysis and classification, or real-time transients detection. We have developed a formalism and the corresponding technical framework to address the challenge of fast cross-catalog matching. Our formalism supports more than simple nearest-neighbor search, and handles elliptical positional errors. Scalability is improved by partitioning the sky using the HEALPix scheme, and processing independently each sky cell. The use of multi-threaded two-dimensional kd-trees adapted to managing equatorial coordinates enables efficient neighbor search. The whole process can run on a single computer, but could also use clusters of machines to cross-match future very large surveys such as GAIA or LSST in reasonable times. We already achieve performances where the 2MASS (˜470M sources) and SDSS DR7 (˜350M sources) can be matched on a single machine in less than 10 minutes. We aim at providing astronomers with a catalog cross-matching service, available on-line and leveraging on the catalogs present in the VizieR database. This service will allow users both to access pre-computed cross-matches across some very large catalogs, and to run customized cross-matching operations. It will also support VO protocols for synchronous or asynchronous queries.

Bringing the CMS distributed computing system into scalable operations

NASA Astrophysics Data System (ADS)

Belforte, S.; Fanfani, A.; Fisk, I.; Flix, J.; Hernández, J. M.; Kress, T.; Letts, J.; Magini, N.; Miccio, V.; Sciabà, A.

2010-04-01

Establishing efficient and scalable operations of the CMS distributed computing system critically relies on the proper integration, commissioning and scale testing of the data and workload management tools, the various computing workflows and the underlying computing infrastructure, located at more than 50 computing centres worldwide and interconnected by the Worldwide LHC Computing Grid. Computing challenges periodically undertaken by CMS in the past years with increasing scale and complexity have revealed the need for a sustained effort on computing integration and commissioning activities. The Processing and Data Access (PADA) Task Force was established at the beginning of 2008 within the CMS Computing Program with the mandate of validating the infrastructure for organized processing and user analysis including the sites and the workload and data management tools, validating the distributed production system by performing functionality, reliability and scale tests, helping sites to commission, configure and optimize the networking and storage through scale testing data transfers and data processing, and improving the efficiency of accessing data across the CMS computing system from global transfers to local access. This contribution reports on the tools and procedures developed by CMS for computing commissioning and scale testing as well as the improvements accomplished towards efficient, reliable and scalable computing operations. The activities include the development and operation of load generators for job submission and data transfers with the aim of stressing the experiment and Grid data management and workload management systems, site commissioning procedures and tools to monitor and improve site availability and reliability, as well as activities targeted to the commissioning of the distributed production, user analysis and monitoring systems.

Final Report. Center for Scalable Application Development Software

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mellor-Crummey, John

2014-10-26

The Center for Scalable Application Development Software (CScADS) was established as a part- nership between Rice University, Argonne National Laboratory, University of California Berkeley, University of Tennessee – Knoxville, and University of Wisconsin – Madison. CScADS pursued an integrated set of activities with the aim of increasing the productivity of DOE computational scientists by catalyzing the development of systems software, libraries, compilers, and tools for leadership computing platforms. Principal Center activities were workshops to engage the research community in the challenges of leadership computing, research and development of open-source software, and work with computational scientists to help them develop codesmore » for leadership computing platforms. This final report summarizes CScADS activities at Rice University in these areas.« less

Scalable sensing electronics towards a motion capture suit

NASA Astrophysics Data System (ADS)

Xu, Daniel; Gisby, Todd A.; Xie, Shane; Anderson, Iain A.

2013-04-01

Being able to accurately record body motion allows complex movements to be characterised and studied. This is especially important in the film or sport coaching industry. Unfortunately, the human body has over 600 skeletal muscles, giving rise to multiple degrees of freedom. In order to accurately capture motion such as hand gestures, elbow or knee flexion and extension, vast numbers of sensors are required. Dielectric elastomer (DE) sensors are an emerging class of electroactive polymer (EAP) that is soft, lightweight and compliant. These characteristics are ideal for a motion capture suit. One challenge is to design sensing electronics that can simultaneously measure multiple sensors. This paper describes a scalable capacitive sensing device that can measure up to 8 different sensors with an update rate of 20Hz.

Scalable uniform construction of highly conditional quantum gates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ivanov, Svetoslav S.; Vitanov, Nikolay V.

2011-08-15

We present a scalable uniform technique for the construction of highly conditional multiply-controlled-not quantum gates of trapped ion qubits, such as the Toffoli gate, without using ancilla states and circuits of an exorbitant number of concatenated one- and two-qubit gates. Apart from the initial dressing of the internal qubit states with vibrational phonons and the final restoration of the phonon ground state, our technique requires the application of just a single composite pulse on the target qubit and is applicable both in and outside the Lamb-Dicke regime. We design special narrowband composite pulses, which suppress all transitions but the conditionalmore » transition of the target qubit; moreover, these composite pulses significantly improve the spatial addressing selectivity.« less

Scalable Database Design of End-Game Model with Decoupled Countermeasure and Threat Information

DTIC Science & Technology

2017-11-01

Threat Information by Decetria Akole and Michael Chen Approved for public release; distribution is unlimited...Scalable Database Design of End-Game Model with Decoupled Countermeasure and Threat Information by Decetria Akole The Thurgood Marshall...for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data

On the scalability of the Albany/FELIX first-order Stokes approximation ice sheet solver for large-scale simulations of the Greenland and Antarctic ice sheets

DOE PAGES

Tezaur, Irina K.; Tuminaro, Raymond S.; Perego, Mauro; ...

2015-01-01

We examine the scalability of the recently developed Albany/FELIX finite-element based code for the first-order Stokes momentum balance equations for ice flow. We focus our analysis on the performance of two possible preconditioners for the iterative solution of the sparse linear systems that arise from the discretization of the governing equations: (1) a preconditioner based on the incomplete LU (ILU) factorization, and (2) a recently-developed algebraic multigrid (AMG) preconditioner, constructed using the idea of semi-coarsening. A strong scalability study on a realistic, high resolution Greenland ice sheet problem reveals that, for a given number of processor cores, the AMG preconditionermore » results in faster linear solve times but the ILU preconditioner exhibits better scalability. In addition, a weak scalability study is performed on a realistic, moderate resolution Antarctic ice sheet problem, a substantial fraction of which contains floating ice shelves, making it fundamentally different from the Greenland ice sheet problem. We show that as the problem size increases, the performance of the ILU preconditioner deteriorates whereas the AMG preconditioner maintains scalability. This is because the linear systems are extremely ill-conditioned in the presence of floating ice shelves, and the ill-conditioning has a greater negative effect on the ILU preconditioner than on the AMG preconditioner.« less

The scalable implementation of quantum walks using classical light

NASA Astrophysics Data System (ADS)

Goyal, Sandeep K.; Roux, F. S.; Forbes, Andrew; Konrad, Thomas

2014-02-01

A quantum walk is the quantum analog of the classical random walks. Despite their simple structure they form a universal platform to implement any algorithm of quantum computation. However, it is very hard to realize quantum walks with a sufficient number of iterations in quantum systems due to their sensitivity to environmental influences and subsequent loss of coherence. Here we present a scalable implementation scheme for one-dimensional quantum walks for arbitrary number of steps using the orbital angular momentum modes of classical light beams. Furthermore, we show that using the same setup with a minor adjustment we can also realize electric quantum walks.

Scalable nuclear density functional theory with Sky3D

NASA Astrophysics Data System (ADS)

Afibuzzaman, Md; Schuetrumpf, Bastian; Aktulga, Hasan Metin

2018-02-01

In nuclear astrophysics, quantum simulations of large inhomogeneous dense systems as they appear in the crusts of neutron stars present big challenges. The number of particles in a simulation with periodic boundary conditions is strongly limited due to the immense computational cost of the quantum methods. In this paper, we describe techniques for an efficient and scalable parallel implementation of Sky3D, a nuclear density functional theory solver that operates on an equidistant grid. Presented techniques allow Sky3D to achieve good scaling and high performance on a large number of cores, as demonstrated through detailed performance analysis on a Cray XC40 supercomputer.

A Scalable Implementation of Van der Waals Density Functionals

NASA Astrophysics Data System (ADS)

Wu, Jun; Gygi, Francois

2010-03-01

Recently developed Van der Waals density functionals[1] offer the promise to account for weak intermolecular interactions that are not described accurately by local exchange-correlation density functionals. In spite of recent progress [2], the computational cost of such calculations remains high. We present a scalable parallel implementation of the functional proposed by Dion et al.[1]. The method is implemented in the Qbox first-principles simulation code (http://eslab.ucdavis.edu/software/qbox). Application to large molecular systems will be presented. [4pt] [1] M. Dion et al. Phys. Rev. Lett. 92, 246401 (2004).[0pt] [2] G. Roman-Perez and J. M. Soler, Phys. Rev. Lett. 103, 096102 (2009).

The Digital Learning Transition MOOC for Educators: Exploring a Scalable Approach to Professional Development

ERIC Educational Resources Information Center

Kleiman, Glenn M.; Wolf, Mary Ann; Frye, David

2013-01-01

In conjunction with the relaunch of the Digital Learning Transition (DLT) Massive Open Online Course for Educatos (MOOC-Ed) in September 2013, the Alliance and the Friday Institute released "The Digital Learning Transition MOOC for Educators: Exploring a Scalable Approach to Professional Development", a new paper that describes the…

paraGSEA: a scalable approach for large-scale gene expression profiling

PubMed Central

Peng, Shaoliang; Yang, Shunyun

2017-01-01

Abstract More studies have been conducted using gene expression similarity to identify functional connections among genes, diseases and drugs. Gene Set Enrichment Analysis (GSEA) is a powerful analytical method for interpreting gene expression data. However, due to its enormous computational overhead in the estimation of significance level step and multiple hypothesis testing step, the computation scalability and efficiency are poor on large-scale datasets. We proposed paraGSEA for efficient large-scale transcriptome data analysis. By optimization, the overall time complexity of paraGSEA is reduced from O(mn) to O(m+n), where m is the length of the gene sets and n is the length of the gene expression profiles, which contributes more than 100-fold increase in performance compared with other popular GSEA implementations such as GSEA-P, SAM-GS and GSEA2. By further parallelization, a near-linear speed-up is gained on both workstations and clusters in an efficient manner with high scalability and performance on large-scale datasets. The analysis time of whole LINCS phase I dataset (GSE92742) was reduced to nearly half hour on a 1000 node cluster on Tianhe-2, or within 120 hours on a 96-core workstation. The source code of paraGSEA is licensed under the GPLv3 and available at http://github.com/ysycloud/paraGSEA. PMID:28973463

A scalable quantum computer with ions in an array of microtraps

PubMed

Cirac; Zoller

2000-04-06

Quantum computers require the storage of quantum information in a set of two-level systems (called qubits), the processing of this information using quantum gates and a means of final readout. So far, only a few systems have been identified as potentially viable quantum computer models--accurate quantum control of the coherent evolution is required in order to realize gate operations, while at the same time decoherence must be avoided. Examples include quantum optical systems (such as those utilizing trapped ions or neutral atoms, cavity quantum electrodynamics and nuclear magnetic resonance) and solid state systems (using nuclear spins, quantum dots and Josephson junctions). The most advanced candidates are the quantum optical and nuclear magnetic resonance systems, and we expect that they will allow quantum computing with about ten qubits within the next few years. This is still far from the numbers required for useful applications: for example, the factorization of a 200-digit number requires about 3,500 qubits, rising to 100,000 if error correction is implemented. Scalability of proposed quantum computer architectures to many qubits is thus of central importance. Here we propose a model for an ion trap quantum computer that combines scalability (a feature usually associated with solid state proposals) with the advantages of quantum optical systems (in particular, quantum control and long decoherence times).

Scalable 3D bicontinuous fluid networks: polymer heat exchangers toward artificial organs.

PubMed

Roper, Christopher S; Schubert, Randall C; Maloney, Kevin J; Page, David; Ro, Christopher J; Yang, Sophia S; Jacobsen, Alan J

2015-04-17

A scalable method for fabricating architected materials well-suited for heat and mass exchange is presented. These materials exhibit unprecedented combinations of small hydraulic diameters (13.0-0.09 mm) and large hydraulic-diameter-to-thickness ratios (5.0-30,100). This process expands the range of material architectures achievable starting from photopolymer waveguide lattices or additive manufacturing. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Architectural Considerations for Highly Scalable Computing to Support On-demand Video Analytics

DTIC Science & Technology

2017-04-19

enforcement . The system was tested in the wild using video files as well as a commercial Video Management System supporting more than 100 surveillance...research were used to implement a distributed on-demand video analytics system that was prototyped for the use of forensics investigators in law...cameras as video sources. The architectural considerations of this system are presented. Issues to be reckoned with in implementing a scalable

Block-based scalable wavelet image codec

NASA Astrophysics Data System (ADS)

Bao, Yiliang; Kuo, C.-C. Jay

1999-10-01

This paper presents a high performance block-based wavelet image coder which is designed to be of very low implementational complexity yet with rich features. In this image coder, the Dual-Sliding Wavelet Transform (DSWT) is first applied to image data to generate wavelet coefficients in fixed-size blocks. Here, a block only consists of wavelet coefficients from a single subband. The coefficient blocks are directly coded with the Low Complexity Binary Description (LCBiD) coefficient coding algorithm. Each block is encoded using binary context-based bitplane coding. No parent-child correlation is exploited in the coding process. There is also no intermediate buffering needed in between DSWT and LCBiD. The compressed bit stream generated by the proposed coder is both SNR and resolution scalable, as well as highly resilient to transmission errors. Both DSWT and LCBiD process the data in blocks whose size is independent of the size of the original image. This gives more flexibility in the implementation. The codec has a very good coding performance even the block size is (16,16).

SCTP as scalable video coding transport

NASA Astrophysics Data System (ADS)

Ortiz, Jordi; Graciá, Eduardo Martínez; Skarmeta, Antonio F.

2013-12-01

This study presents an evaluation of the Stream Transmission Control Protocol (SCTP) for the transport of the scalable video codec (SVC), proposed by MPEG as an extension to H.264/AVC. Both technologies fit together properly. On the one hand, SVC permits to split easily the bitstream into substreams carrying different video layers, each with different importance for the reconstruction of the complete video sequence at the receiver end. On the other hand, SCTP includes features, such as the multi-streaming and multi-homing capabilities, that permit to transport robustly and efficiently the SVC layers. Several transmission strategies supported on baseline SCTP and its concurrent multipath transfer (CMT) extension are compared with the classical solutions based on the Transmission Control Protocol (TCP) and the Realtime Transmission Protocol (RTP). Using ns-2 simulations, it is shown that CMT-SCTP outperforms TCP and RTP in error-prone networking environments. The comparison is established according to several performance measurements, including delay, throughput, packet loss, and peak signal-to-noise ratio of the received video.

On implementing clinical decision support: achieving scalability and maintainability by combining business rules and ontologies.

PubMed

Kashyap, Vipul; Morales, Alfredo; Hongsermeier, Tonya

2006-01-01

We present an approach and architecture for implementing scalable and maintainable clinical decision support at the Partners HealthCare System. The architecture integrates a business rules engine that executes declarative if-then rules stored in a rule-base referencing objects and methods in a business object model. The rules engine executes object methods by invoking services implemented on the clinical data repository. Specialized inferences that support classification of data and instances into classes are identified and an approach to implement these inferences using an OWL based ontology engine is presented. Alternative representations of these specialized inferences as if-then rules or OWL axioms are explored and their impact on the scalability and maintenance of the system is presented. Architectural alternatives for integration of clinical decision support functionality with the invoking application and the underlying clinical data repository; and their associated trade-offs are discussed and presented.

Fully programmable and scalable optical switching fabric for petabyte data center.

PubMed

Zhu, Zhonghua; Zhong, Shan; Chen, Li; Chen, Kai

2015-02-09

We present a converged EPS and OCS switching fabric for data center networks (DCNs) based on a distributed optical switching architecture leveraging both WDM & SDM technologies. The architecture is topology adaptive, well suited to dynamic and diverse *-cast traffic patterns. Compared to a typical folded-Clos network, the new architecture is more readily scalable to future multi-Petabyte data centers with 1000 + racks while providing a higher link bandwidth, reducing transceiver count by 50%, and improving cabling efficiency by more than 90%.

Scalable, Stereocontrolled Total Syntheses of (±)–Axinellamines A and B

PubMed Central

Su, Shun; Rodriguez, Rodrigo A.; Baran, Phil S.

2011-01-01

The development of a simple, efficient, scalable, and stereocontrolled synthesis of a common intermediate en route to the axinellamines, massadines, and palau’amine is reported. This completely new route was utilized to prepare the axinellamines on a gram scale. In a more general sense, three distinct and enabling methodological advances were made during these studies: 1. ethylene glycol-assisted Pauson-Khand cycloaddition reaction, 2. a Zn/In-mediated Barbier type reaction, and 3. a TfNH2-assisted chlorination-spirocyclization. PMID:21846138

In Situ Distribution Guided Analysis and Visualization of Transonic Jet Engine Simulations.

PubMed

Dutta, Soumya; Chen, Chun-Ming; Heinlein, Gregory; Shen, Han-Wei; Chen, Jen-Ping

2017-01-01

Study of flow instability in turbine engine compressors is crucial to understand the inception and evolution of engine stall. Aerodynamics experts have been working on detecting the early signs of stall in order to devise novel stall suppression technologies. A state-of-the-art Navier-Stokes based, time-accurate computational fluid dynamics simulator, TURBO, has been developed in NASA to enhance the understanding of flow phenomena undergoing rotating stall. Despite the proven high modeling accuracy of TURBO, the excessive simulation data prohibits post-hoc analysis in both storage and I/O time. To address these issues and allow the expert to perform scalable stall analysis, we have designed an in situ distribution guided stall analysis technique. Our method summarizes statistics of important properties of the simulation data in situ using a probabilistic data modeling scheme. This data summarization enables statistical anomaly detection for flow instability in post analysis, which reveals the spatiotemporal trends of rotating stall for the expert to conceive new hypotheses. Furthermore, the verification of the hypotheses and exploratory visualization using the summarized data are realized using probabilistic visualization techniques such as uncertain isocontouring. Positive feedback from the domain scientist has indicated the efficacy of our system in exploratory stall analysis.

Factors influencing the implementation, adoption, use, sustainability and scalability of eLearning for family medicine specialty training: a systematic review protocol.

PubMed

Cotič, Živa; Rees, Rebecca; Wark, Petra A; Car, Josip

2016-10-19

In 2013, there was a shortage of approximately 7.2 million health workers worldwide, which is larger among family physicians than among specialists. eLearning could provide a potential solution to some of these global workforce challenges. However, there is little evidence on factors facilitating or hindering implementation, adoption, use, scalability and sustainability of eLearning. This review aims to synthesise results from qualitative and mixed methods studies to provide insight on factors influencing implementation of eLearning for family medicine specialty education and training. Additionally, this review aims to identify the actions needed to increase effectiveness of eLearning and identify the strategies required to improve eLearning implementation, adoption, use, sustainability and scalability for family medicine speciality education and training. A systematic search will be conducted across a range of databases for qualitative studies focusing on experiences, barriers, facilitators, and other factors related to the implementation, adoption, use, sustainability and scalability of eLearning for family medicine specialty education and training. Studies will be synthesised by using the framework analysis approach. This study will contribute to the evaluation of eLearning implementation, adoption, use, sustainability and scalability for family medicine specialty training and education and the development of eLearning guidelines for postgraduate medical education. PROSPERO http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42016036449.

Scalable Conjunction Processing using Spatiotemporally Indexed Ephemeris Data

NASA Astrophysics Data System (ADS)

Budianto-Ho, I.; Johnson, S.; Sivilli, R.; Alberty, C.; Scarberry, R.

2014-09-01

The collision warnings produced by the Joint Space Operations Center (JSpOC) are of critical importance in protecting U.S. and allied spacecraft against destructive collisions and protecting the lives of astronauts during space flight. As the Space Surveillance Network (SSN) improves its sensor capabilities for tracking small and dim space objects, the number of tracked objects increases from thousands to hundreds of thousands of objects, while the number of potential conjunctions increases with the square of the number of tracked objects. Classical filtering techniques such as apogee and perigee filters have proven insufficient. Novel and orders of magnitude faster conjunction analysis algorithms are required to find conjunctions in a timely manner. Stellar Science has developed innovative filtering techniques for satellite conjunction processing using spatiotemporally indexed ephemeris data that efficiently and accurately reduces the number of objects requiring high-fidelity and computationally-intensive conjunction analysis. Two such algorithms, one based on the k-d Tree pioneered in robotics applications and the other based on Spatial Hash Tables used in computer gaming and animation, use, at worst, an initial O(N log N) preprocessing pass (where N is the number of tracked objects) to build large O(N) spatial data structures that substantially reduce the required number of O(N^2) computations, substituting linear memory usage for quadratic processing time. The filters have been implemented as Open Services Gateway initiative (OSGi) plug-ins for the Continuous Anomalous Orbital Situation Discriminator (CAOS-D) conjunction analysis architecture. We have demonstrated the effectiveness, efficiency, and scalability of the techniques using a catalog of 100,000 objects, an analysis window of one day, on a 64-core computer with 1TB shared memory. Each algorithm can process the full catalog in 6 minutes or less, almost a twenty-fold performance improvement over the

Recent advances in scalable non-Gaussian geostatistics: The generalized sub-Gaussian model

NASA Astrophysics Data System (ADS)

Guadagnini, Alberto; Riva, Monica; Neuman, Shlomo P.

2018-07-01

Geostatistical analysis has been introduced over half a century ago to allow quantifying seemingly random spatial variations in earth quantities such as rock mineral content or permeability. The traditional approach has been to view such quantities as multivariate Gaussian random functions characterized by one or a few well-defined spatial correlation scales. There is, however, mounting evidence that many spatially varying quantities exhibit non-Gaussian behavior over a multiplicity of scales. The purpose of this minireview is not to paint a broad picture of the subject and its treatment in the literature. Instead, we focus on very recent advances in the recognition and analysis of this ubiquitous phenomenon, which transcends hydrology and the Earth sciences, brought about largely by our own work. In particular, we use porosity data from a deep borehole to illustrate typical aspects of such scalable non-Gaussian behavior, describe a very recent theoretical model that (for the first time) captures all these behavioral aspects in a comprehensive manner, show how this allows generating random realizations of the quantity conditional on sampled values, point toward ways of incorporating scalable non-Gaussian behavior in hydrologic analysis, highlight the significance of doing so, and list open questions requiring further research.

Comparison of three methods for registration of abdominal/pelvic volume data sets from functional-anatomic scans

NASA Astrophysics Data System (ADS)

Mahmoud, Faaiza; Ton, Anthony; Crafoord, Joakim; Kramer, Elissa L.; Maguire, Gerald Q., Jr.; Noz, Marilyn E.; Zeleznik, Michael P.

2000-06-01

The purpose of this work was to evaluate three volumetric registration methods in terms of technique, user-friendliness and time requirements. CT and SPECT data from 11 patients were interactively registered using: a 3D method involving only affine transformation; a mixed 3D - 2D non-affine (warping) method; and a 3D non-affine (warping) method. In the first method representative isosurfaces are generated from the anatomical images. Registration proceeds through translation, rotation, and scaling in all three space variables. Resulting isosurfaces are fused and quantitative measurements are possible. In the second method, the 3D volumes are rendered co-planar by performing an oblique projection. Corresponding landmark pairs are chosen on matching axial slice sets. A polynomial warp is then applied. This method has undergone extensive validation and was used to evaluate the results. The third method employs visualization tools. The data model allows images to be localized within two separate volumes. Landmarks are chosen on separate slices. Polynomial warping coefficients are generated and data points from one volume are moved to the corresponding new positions. The two landmark methods were the least time consuming (10 to 30 minutes from start to finish), but did demand a good knowledge of anatomy. The affine method was tedious and required a fair understanding of 3D geometry.

A scalable method for computing quadruplet wave-wave interactions

NASA Astrophysics Data System (ADS)

Van Vledder, Gerbrant

2017-04-01

Non-linear four-wave interactions are a key physical process in the evolution of wind generated ocean waves. The present generation operational wave models use the Discrete Interaction Approximation (DIA), but it accuracy is poor. It is now generally acknowledged that the DIA should be replaced with a more accurate method to improve predicted spectral shapes and derived parameters. The search for such a method is challenging as one should find a balance between accuracy and computational requirements. Such a method is presented here in the form of a scalable and adaptive method that can mimic both the time consuming exact Snl4 approach and the fast but inaccurate DIA, and everything in between. The method provides an elegant approach to improve the DIA, not by including more arbitrarily shaped wave number configurations, but by a mathematically consistent reduction of an exact method, viz. the WRT method. The adaptiveness is to adapt the abscissa of the locus integrand in relation to the magnitude of the known terms. The adaptiveness is extended to the highest level of the WRT method to select interacting wavenumber configurations in a hierarchical way in relation to their importance. This adaptiveness results in a speed-up of one to three orders of magnitude depending on the measure of accuracy. This definition of accuracy should not be expressed in terms of the quality of the transfer integral for academic spectra but rather in terms of wave model performance in a dynamic run. This has consequences for the balance between the required accuracy and the computational workload for evaluating these interactions. The performance of the scalable method on different scales is illustrated with results from academic spectra, simple growth curves to more complicated field cases using a 3G-wave model.

A scalable correlator for multichannel diffuse correlation spectroscopy.

PubMed

Stapels, Christopher J; Kolodziejski, Noah J; McAdams, Daniel; Podolsky, Matthew J; Fernandez, Daniel E; Farkas, Dana; Christian, James F

2016-02-01

Diffuse correlation spectroscopy (DCS) is a technique which enables powerful and robust non-invasive optical studies of tissue micro-circulation and vascular blood flow. The technique amounts to autocorrelation analysis of coherent photons after their migration through moving scatterers and subsequent collection by single-mode optical fibers. A primary cost driver of DCS instruments are the commercial hardware-based correlators, limiting the proliferation of multi-channel instruments for validation of perfusion analysis as a clinical diagnostic metric. We present the development of a low-cost scalable correlator enabled by microchip-based time-tagging, and a software-based multi-tau data analysis method. We will discuss the capabilities of the instrument as well as the implementation and validation of 2- and 8-channel systems built for live animal and pre-clinical settings.