Quality indexing with computer-aided lexicography

NASA Technical Reports Server (NTRS)

Buchan, Ronald L.

1992-01-01

Indexing with computers is a far cry from indexing with the first indexing tool, the manual card sorter. With the aid of computer-aided lexicography, both indexing and indexing tools can provide standardization, consistency, and accuracy, resulting in greater quality control than ever before. A brief survey of computer activity in indexing is presented with detailed illustrations from NASA activity. Applications from techniques mentioned, such as Retrospective Indexing (RI), can be made to many indexing systems. In addition to improving the quality of indexing with computers, the improved efficiency with which certain tasks can be done is demonstrated.

Tools for Administration of a UNIX-Based Network

NASA Technical Reports Server (NTRS)

LeClaire, Stephen; Farrar, Edward

2004-01-01

Several computer programs have been developed to enable efficient administration of a large, heterogeneous, UNIX-based computing and communication network that includes a variety of computers connected to a variety of subnetworks. One program provides secure software tools for administrators to create, modify, lock, and delete accounts of specific users. This program also provides tools for users to change their UNIX passwords and log-in shells. These tools check for errors. Another program comprises a client and a server component that, together, provide a secure mechanism to create, modify, and query quota levels on a network file system (NFS) mounted by use of the VERITAS File SystemJ software. The client software resides on an internal secure computer with a secure Web interface; one can gain access to the client software from any authorized computer capable of running web-browser software. The server software resides on a UNIX computer configured with the VERITAS software system. Directories where VERITAS quotas are applied are NFS-mounted. Another program is a Web-based, client/server Internet Protocol (IP) address tool that facilitates maintenance lookup of information about IP addresses for a network of computers.

Center for Efficient Exascale Discretizations Software Suite

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

Kolev, Tzanio; Dobrev, Veselin; Tomov, Vladimir

The CEED Software suite is a collection of generally applicable software tools focusing on the following computational motives: PDE discretizations on unstructured meshes, high-order finite element and spectral element methods and unstructured adaptive mesh refinement. All of this software is being developed as part of CEED, a co-design Center for Efficient Exascale Discretizations, within DOE's Exascale Computing Project (ECP) program.

IMAT (Integrated Multidisciplinary Analysis Tool) user's guide for the VAX/VMS computer

NASA Technical Reports Server (NTRS)

Meissner, Frances T. (Editor)

1988-01-01

The Integrated Multidisciplinary Analysis Tool (IMAT) is a computer software system for the VAX/VMS computer developed at the Langley Research Center. IMAT provides researchers and analysts with an efficient capability to analyze satellite control systems influenced by structural dynamics. Using a menu-driven executive system, IMAT leads the user through the program options. IMAT links a relational database manager to commercial and in-house structural and controls analysis codes. This paper describes the IMAT software system and how to use it.

Some Observations on the Current Status of Performing Finite Element Analyses

NASA Technical Reports Server (NTRS)

Raju, Ivatury S.; Knight, Norman F., Jr; Shivakumar, Kunigal N.

2015-01-01

Aerospace structures are complex high-performance structures. Advances in reliable and efficient computing and modeling tools are enabling analysts to consider complex configurations, build complex finite element models, and perform analysis rapidly. Many of the early career engineers of today are very proficient in the usage of modern computers, computing engines, complex software systems, and visualization tools. These young engineers are becoming increasingly efficient in building complex 3D models of complicated aerospace components. However, the current trends demonstrate blind acceptance of the results of the finite element analysis results. This paper is aimed at raising an awareness of this situation. Examples of the common encounters are presented. To overcome the current trends, some guidelines and suggestions for analysts, senior engineers, and educators are offered.

Plant Aquaporins: Genome-Wide Identification, Transcriptomics, Proteomics, and Advanced Analytical Tools.

PubMed

Deshmukh, Rupesh K; Sonah, Humira; Bélanger, Richard R

2016-01-01

Aquaporins (AQPs) are channel-forming integral membrane proteins that facilitate the movement of water and many other small molecules. Compared to animals, plants contain a much higher number of AQPs in their genome. Homology-based identification of AQPs in sequenced species is feasible because of the high level of conservation of protein sequences across plant species. Genome-wide characterization of AQPs has highlighted several important aspects such as distribution, genetic organization, evolution and conserved features governing solute specificity. From a functional point of view, the understanding of AQP transport system has expanded rapidly with the help of transcriptomics and proteomics data. The efficient analysis of enormous amounts of data generated through omic scale studies has been facilitated through computational advancements. Prediction of protein tertiary structures, pore architecture, cavities, phosphorylation sites, heterodimerization, and co-expression networks has become more sophisticated and accurate with increasing computational tools and pipelines. However, the effectiveness of computational approaches is based on the understanding of physiological and biochemical properties, transport kinetics, solute specificity, molecular interactions, sequence variations, phylogeny and evolution of aquaporins. For this purpose, tools like Xenopus oocyte assays, yeast expression systems, artificial proteoliposomes, and lipid membranes have been efficiently exploited to study the many facets that influence solute transport by AQPs. In the present review, we discuss genome-wide identification of AQPs in plants in relation with recent advancements in analytical tools, and their availability and technological challenges as they apply to AQPs. An exhaustive review of omics resources available for AQP research is also provided in order to optimize their efficient utilization. Finally, a detailed catalog of computational tools and analytical pipelines is offered as a resource for AQP research.

Plant Aquaporins: Genome-Wide Identification, Transcriptomics, Proteomics, and Advanced Analytical Tools

PubMed Central

Deshmukh, Rupesh K.; Sonah, Humira; Bélanger, Richard R.

2016-01-01

Aquaporins (AQPs) are channel-forming integral membrane proteins that facilitate the movement of water and many other small molecules. Compared to animals, plants contain a much higher number of AQPs in their genome. Homology-based identification of AQPs in sequenced species is feasible because of the high level of conservation of protein sequences across plant species. Genome-wide characterization of AQPs has highlighted several important aspects such as distribution, genetic organization, evolution and conserved features governing solute specificity. From a functional point of view, the understanding of AQP transport system has expanded rapidly with the help of transcriptomics and proteomics data. The efficient analysis of enormous amounts of data generated through omic scale studies has been facilitated through computational advancements. Prediction of protein tertiary structures, pore architecture, cavities, phosphorylation sites, heterodimerization, and co-expression networks has become more sophisticated and accurate with increasing computational tools and pipelines. However, the effectiveness of computational approaches is based on the understanding of physiological and biochemical properties, transport kinetics, solute specificity, molecular interactions, sequence variations, phylogeny and evolution of aquaporins. For this purpose, tools like Xenopus oocyte assays, yeast expression systems, artificial proteoliposomes, and lipid membranes have been efficiently exploited to study the many facets that influence solute transport by AQPs. In the present review, we discuss genome-wide identification of AQPs in plants in relation with recent advancements in analytical tools, and their availability and technological challenges as they apply to AQPs. An exhaustive review of omics resources available for AQP research is also provided in order to optimize their efficient utilization. Finally, a detailed catalog of computational tools and analytical pipelines is offered as a resource for AQP research. PMID:28066459

A Foothold for Handhelds.

ERIC Educational Resources Information Center

Joyner, Amy

2003-01-01

Handheld computers provide students tremendous computing and learning power at about a 10th the cost of a regular computer. Describes the evolution of handhelds; provides some examples of their uses; and cites research indicating they are effective classroom tools that can improve efficiency and instruction. A sidebar lists handheld resources.…

Tools for Atmospheric Radiative Transfer: Streamer and FluxNet. Revised

NASA Technical Reports Server (NTRS)

Key, Jeffrey R.; Schweiger, Axel J.

1998-01-01

Two tools for the solution of radiative transfer problems are presented. Streamer is a highly flexible medium spectral resolution radiative transfer model based on the plane-parallel theory of radiative transfer. Capable of computing either fluxes or radiances, it is suitable for studying radiative processes at the surface or within the atmosphere and for the development of remote-sensing algorithms. FluxNet is a fast neural network-based implementation of Streamer for computing surface fluxes. It allows for a sophisticated treatment of radiative processes in the analysis of large data sets and potential integration into geophysical models where computational efficiency is an issue. Documentation and tools for the development of alternative versions of Fluxnet are available. Collectively, Streamer and FluxNet solve a wide variety of problems related to radiative transfer: Streamer provides the detail and sophistication needed to perform basic research on most aspects of complex radiative processes while the efficiency and simplicity of FluxNet make it ideal for operational use.

Factors Influencing Computer Anxiety and Its Impact on E-Learning Effectiveness: A Review of Literature

ERIC Educational Resources Information Center

Chien, Tien-Chen

2008-01-01

Computer is not only a powerful technology for managing information and enhancing productivity, but also an efficient tool for education and training. Computer anxiety can be one of the major problems that affect the effectiveness of learning. Through analyzing related literature, this study describes the phenomenon of computer anxiety,…

Introduction to the Use of Computers in Libraries: A Textbook for the Non-Technical Student.

ERIC Educational Resources Information Center

Ogg, Harold C.

This book outlines computing and information science from the perspective of what librarians and educators need to do with computer technology and how it can help them perform their jobs more efficiently. It provides practical explanations and library applications for non-technical users of desktop computers and other library automation tools.…

3D TRUMP - A GBI launch window tool

NASA Astrophysics Data System (ADS)

Karels, Steven N.; Hancock, John; Matchett, Gary

3D TRUMP is a novel GPS and communicatons-link software analysis tool developed for the SDIO's Ground-Based Interceptor (GBI) program. 3D TRUMP uses a computationally efficient analysis tool which provides key GPS-based performance measures for an entire GBI mission's reentry vehicle and interceptor trajectories. Algorithms and sample outputs are presented.

Shield system

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

Finch, D.R.; Chandler, J.R.; Church, J.P.

1979-01-01

The SHIELD system is a powerful new computational tool for calculation of isotopic inventory, radiation sources, decay heat, and shielding assessment in part of the nuclear fuel cycle. The integrated approach used in this system permitss the communication and management of large fields of numbers efficiently thus permitting the user to address the technical rather than computer aspects of a problem. Emphasis on graphical outputs permits large fields of resulting numbers to be efficiently displayed.

ADAM: analysis of discrete models of biological systems using computer algebra.

PubMed

Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

2011-07-20

Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics.

Managing Laboratory Data Using Cloud Computing as an Organizational Tool

ERIC Educational Resources Information Center

Bennett, Jacqueline; Pence, Harry E.

2011-01-01

One of the most significant difficulties encountered when directing undergraduate research and developing new laboratory experiments is how to efficiently manage the data generated by a number of students. Cloud computing, where both software and computer files reside online, offers a solution to this data-management problem and allows researchers…

Semi-autonomous parking for enhanced safety and efficiency.

DOT National Transportation Integrated Search

2017-06-01

This project focuses on the use of tools from a combination of computer vision and localization based navigation schemes to aid the process of efficient and safe parking of vehicles in high density parking spaces. The principles of collision avoidanc...

Tools for Analyzing Computing Resource Management Strategies and Algorithms for SDR Clouds

NASA Astrophysics Data System (ADS)

Marojevic, Vuk; Gomez-Miguelez, Ismael; Gelonch, Antoni

2012-09-01

Software defined radio (SDR) clouds centralize the computing resources of base stations. The computing resource pool is shared between radio operators and dynamically loads and unloads digital signal processing chains for providing wireless communications services on demand. Each new user session request particularly requires the allocation of computing resources for executing the corresponding SDR transceivers. The huge amount of computing resources of SDR cloud data centers and the numerous session requests at certain hours of a day require an efficient computing resource management. We propose a hierarchical approach, where the data center is divided in clusters that are managed in a distributed way. This paper presents a set of computing resource management tools for analyzing computing resource management strategies and algorithms for SDR clouds. We use the tools for evaluating a different strategies and algorithms. The results show that more sophisticated algorithms can achieve higher resource occupations and that a tradeoff exists between cluster size and algorithm complexity.

GAPIT version 2: an enhanced integrated tool for genomic association and prediction

USDA-ARS?s Scientific Manuscript database

Most human diseases and agriculturally important traits are complex. Dissecting their genetic architecture requires continued development of innovative and powerful statistical methods. Corresponding advances in computing tools are critical to efficiently use these statistical innovations and to enh...

Applications of the pipeline environment for visual informatics and genomics computations

PubMed Central

2011-01-01

Background Contemporary informatics and genomics research require efficient, flexible and robust management of large heterogeneous data, advanced computational tools, powerful visualization, reliable hardware infrastructure, interoperability of computational resources, and detailed data and analysis-protocol provenance. The Pipeline is a client-server distributed computational environment that facilitates the visual graphical construction, execution, monitoring, validation and dissemination of advanced data analysis protocols. Results This paper reports on the applications of the LONI Pipeline environment to address two informatics challenges - graphical management of diverse genomics tools, and the interoperability of informatics software. Specifically, this manuscript presents the concrete details of deploying general informatics suites and individual software tools to new hardware infrastructures, the design, validation and execution of new visual analysis protocols via the Pipeline graphical interface, and integration of diverse informatics tools via the Pipeline eXtensible Markup Language syntax. We demonstrate each of these processes using several established informatics packages (e.g., miBLAST, EMBOSS, mrFAST, GWASS, MAQ, SAMtools, Bowtie) for basic local sequence alignment and search, molecular biology data analysis, and genome-wide association studies. These examples demonstrate the power of the Pipeline graphical workflow environment to enable integration of bioinformatics resources which provide a well-defined syntax for dynamic specification of the input/output parameters and the run-time execution controls. Conclusions The LONI Pipeline environment http://pipeline.loni.ucla.edu provides a flexible graphical infrastructure for efficient biomedical computing and distributed informatics research. The interactive Pipeline resource manager enables the utilization and interoperability of diverse types of informatics resources. The Pipeline client-server model provides computational power to a broad spectrum of informatics investigators - experienced developers and novice users, user with or without access to advanced computational-resources (e.g., Grid, data), as well as basic and translational scientists. The open development, validation and dissemination of computational networks (pipeline workflows) facilitates the sharing of knowledge, tools, protocols and best practices, and enables the unbiased validation and replication of scientific findings by the entire community. PMID:21791102

Google-Earth Based Visualizations for Environmental Flows and Pollutant Dispersion in Urban Areas

PubMed Central

Liu, Daoming; Kenjeres, Sasa

2017-01-01

In the present study, we address the development and application of an efficient tool for conversion of results obtained by an integrated computational fluid dynamics (CFD) and computational reaction dynamics (CRD) approach and their visualization in the Google Earth. We focus on results typical for environmental fluid mechanics studies at a city scale that include characteristic wind flow patterns and dispersion of reactive scalars. This is achieved by developing a code based on the Java language, which converts the typical four-dimensional structure (spatial and temporal dependency) of data results in the Keyhole Markup Language (KML) format. The visualization techniques most often used are revisited and implemented into the conversion tool. The potential of the tool is demonstrated in a case study of smog formation due to an intense traffic emission in Rotterdam (The Netherlands). It is shown that the Google Earth can provide a computationally efficient and user-friendly means of data representation. This feature can be very useful for visualization of pollution at street levels, which is of great importance for the city residents. Various meteorological and traffic emissions can be easily visualized and analyzed, providing a powerful, user-friendly tool for traffic regulations and urban climate adaptations. PMID:28257078

Projected role of advanced computational aerodynamic methods at the Lockheed-Georgia company

NASA Technical Reports Server (NTRS)

Lores, M. E.

1978-01-01

Experience with advanced computational methods being used at the Lockheed-Georgia Company to aid in the evaluation and design of new and modified aircraft indicates that large and specialized computers will be needed to make advanced three-dimensional viscous aerodynamic computations practical. The Numerical Aerodynamic Simulation Facility should be used to provide a tool for designing better aerospace vehicles while at the same time reducing development costs by performing computations using Navier-Stokes equations solution algorithms and permitting less sophisticated but nevertheless complex calculations to be made efficiently. Configuration definition procedures and data output formats can probably best be defined in cooperation with industry, therefore, the computer should handle many remote terminals efficiently. The capability of transferring data to and from other computers needs to be provided. Because of the significant amount of input and output associated with 3-D viscous flow calculations and because of the exceedingly fast computation speed envisioned for the computer, special attention should be paid to providing rapid, diversified, and efficient input and output.

A non-linear programming approach to the computer-aided design of regulators using a linear-quadratic formulation

NASA Technical Reports Server (NTRS)

Fleming, P.

1985-01-01

A design technique is proposed for linear regulators in which a feedback controller of fixed structure is chosen to minimize an integral quadratic objective function subject to the satisfaction of integral quadratic constraint functions. Application of a non-linear programming algorithm to this mathematically tractable formulation results in an efficient and useful computer-aided design tool. Particular attention is paid to computational efficiency and various recommendations are made. Two design examples illustrate the flexibility of the approach and highlight the special insight afforded to the designer.

Visualizing Matrix Multiplication

ERIC Educational Resources Information Center

Daugulis, Peteris; Sondore, Anita

2018-01-01

Efficient visualizations of computational algorithms are important tools for students, educators, and researchers. In this article, we point out an innovative visualization technique for matrix multiplication. This method differs from the standard, formal approach by using block matrices to make computations more visual. We find this method a…

Fermilab computing at the Intensity Frontier

DOE PAGES

Group, Craig; Fuess, S.; Gutsche, O.; ...

2015-12-23

The Intensity Frontier refers to a diverse set of particle physics experiments using high- intensity beams. In this paper I will focus the discussion on the computing requirements and solutions of a set of neutrino and muon experiments in progress or planned to take place at the Fermi National Accelerator Laboratory located near Chicago, Illinois. In addition, the experiments face unique challenges, but also have overlapping computational needs. In principle, by exploiting the commonality and utilizing centralized computing tools and resources, requirements can be satisfied efficiently and scientists of individual experiments can focus more on the science and less onmore » the development of tools and infrastructure.« less

De-quantisation

NASA Astrophysics Data System (ADS)

Gruska, Jozef

2012-06-01

One of the most basic tasks in quantum information processing, communication and security (QIPCC) research, theoretically deep and practically important, is to find bounds on how really important are inherently quantum resources for speeding up computations. This area of research is bringing a variety of results that imply, often in a very unexpected and counter-intuitive way, that: (a) surprisingly large classes of quantum circuits and algorithms can be efficiently simulated on classical computers; (b) the border line between quantum processes that can and cannot be efficiently simulated on classical computers is often surprisingly thin; (c) the addition of a seemingly very simple resource or a tool often enormously increases the power of available quantum tools. These discoveries have put also a new light on our understanding of quantum phenomena and quantum physics and on the potential of its inherently quantum and often mysteriously looking phenomena. The paper motivates and surveys research and its outcomes in the area of de-quantisation, especially presents various approaches and their outcomes concerning efficient classical simulations of various families of quantum circuits and algorithms. To motivate this area of research some outcomes in the area of de-randomization of classical randomized computations.

Advanced Scientific Computing Research Exascale Requirements Review. An Office of Science review sponsored by Advanced Scientific Computing Research, September 27-29, 2016, Rockville, Maryland

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

Almgren, Ann; DeMar, Phil; Vetter, Jeffrey

The widespread use of computing in the American economy would not be possible without a thoughtful, exploratory research and development (R&D) community pushing the performance edge of operating systems, computer languages, and software libraries. These are the tools and building blocks — the hammers, chisels, bricks, and mortar — of the smartphone, the cloud, and the computing services on which we rely. Engineers and scientists need ever-more specialized computing tools to discover new material properties for manufacturing, make energy generation safer and more efficient, and provide insight into the fundamentals of the universe, for example. The research division of themore » U.S. Department of Energy’s (DOE’s) Office of Advanced Scientific Computing and Research (ASCR Research) ensures that these tools and building blocks are being developed and honed to meet the extreme needs of modern science. See also http://exascaleage.org/ascr/ for additional information.« less

A Computational Framework for Efficient Low Temperature Plasma Simulations

NASA Astrophysics Data System (ADS)

Verma, Abhishek Kumar; Venkattraman, Ayyaswamy

2016-10-01

Over the past years, scientific computing has emerged as an essential tool for the investigation and prediction of low temperature plasmas (LTP) applications which includes electronics, nanomaterial synthesis, metamaterials etc. To further explore the LTP behavior with greater fidelity, we present a computational toolbox developed to perform LTP simulations. This framework will allow us to enhance our understanding of multiscale plasma phenomenon using high performance computing tools mainly based on OpenFOAM FVM distribution. Although aimed at microplasma simulations, the modular framework is able to perform multiscale, multiphysics simulations of physical systems comprises of LTP. Some salient introductory features are capability to perform parallel, 3D simulations of LTP applications on unstructured meshes. Performance of the solver is tested based on numerical results assessing accuracy and efficiency of benchmarks for problems in microdischarge devices. Numerical simulation of microplasma reactor at atmospheric pressure with hemispherical dielectric coated electrodes will be discussed and hence, provide an overview of applicability and future scope of this framework.

Modeling Methodologies for Design and Control of Solid Oxide Fuel Cell APUs

NASA Astrophysics Data System (ADS)

Pianese, C.; Sorrentino, M.

2009-08-01

Among the existing fuel cell technologies, Solid Oxide Fuel Cells (SOFC) are particularly suitable for both stationary and mobile applications, due to their high energy conversion efficiencies, modularity, high fuel flexibility, low emissions and noise. Moreover, the high working temperatures enable their use for efficient cogeneration applications. SOFCs are entering in a pre-industrial era and a strong interest for designing tools has growth in the last years. Optimal system configuration, components sizing, control and diagnostic system design require computational tools that meet the conflicting needs of accuracy, affordable computational time, limited experimental efforts and flexibility. The paper gives an overview on control-oriented modeling of SOFC at both single cell and stack level. Such an approach provides useful simulation tools for designing and controlling SOFC-APUs destined to a wide application area, ranging from automotive to marine and airplane APUs.

Parallelization of ARC3D with Computer-Aided Tools

NASA Technical Reports Server (NTRS)

Jin, Haoqiang; Hribar, Michelle; Yan, Jerry; Saini, Subhash (Technical Monitor)

1998-01-01

A series of efforts have been devoted to investigating methods of porting and parallelizing applications quickly and efficiently for new architectures, such as the SCSI Origin 2000 and Cray T3E. This report presents the parallelization of a CFD application, ARC3D, using the computer-aided tools, Cesspools. Steps of parallelizing this code and requirements of achieving better performance are discussed. The generated parallel version has achieved reasonably well performance, for example, having a speedup of 30 for 36 Cray T3E processors. However, this performance could not be obtained without modification of the original serial code. It is suggested that in many cases improving serial code and performing necessary code transformations are important parts for the automated parallelization process although user intervention in many of these parts are still necessary. Nevertheless, development and improvement of useful software tools, such as Cesspools, can help trim down many tedious parallelization details and improve the processing efficiency.

Adjoint-Based Aerodynamic Design of Complex Aerospace Configurations

NASA Technical Reports Server (NTRS)

Nielsen, Eric J.

2016-01-01

An overview of twenty years of adjoint-based aerodynamic design research at NASA Langley Research Center is presented. Adjoint-based algorithms provide a powerful tool for efficient sensitivity analysis of complex large-scale computational fluid dynamics (CFD) simulations. Unlike alternative approaches for which computational expense generally scales with the number of design parameters, adjoint techniques yield sensitivity derivatives of a simulation output with respect to all input parameters at the cost of a single additional simulation. With modern large-scale CFD applications often requiring millions of compute hours for a single analysis, the efficiency afforded by adjoint methods is critical in realizing a computationally tractable design optimization capability for such applications.

Prediction of miRNA targets.

PubMed

Oulas, Anastasis; Karathanasis, Nestoras; Louloupi, Annita; Pavlopoulos, Georgios A; Poirazi, Panayiota; Kalantidis, Kriton; Iliopoulos, Ioannis

2015-01-01

Computational methods for miRNA target prediction are currently undergoing extensive review and evaluation. There is still a great need for improvement of these tools and bioinformatics approaches are looking towards high-throughput experiments in order to validate predictions. The combination of large-scale techniques with computational tools will not only provide greater credence to computational predictions but also lead to the better understanding of specific biological questions. Current miRNA target prediction tools utilize probabilistic learning algorithms, machine learning methods and even empirical biologically defined rules in order to build models based on experimentally verified miRNA targets. Large-scale protein downregulation assays and next-generation sequencing (NGS) are now being used to validate methodologies and compare the performance of existing tools. Tools that exhibit greater correlation between computational predictions and protein downregulation or RNA downregulation are considered the state of the art. Moreover, efficiency in prediction of miRNA targets that are concurrently verified experimentally provides additional validity to computational predictions and further highlights the competitive advantage of specific tools and their efficacy in extracting biologically significant results. In this review paper, we discuss the computational methods for miRNA target prediction and provide a detailed comparison of methodologies and features utilized by each specific tool. Moreover, we provide an overview of current state-of-the-art high-throughput methods used in miRNA target prediction.

SUNREL Related Links | Buildings | NREL

Science.gov Websites

SUNREL Related Links SUNREL Related Links DOE Simulation Software Tools Directory a directory of 301 building software tools for evaluation of energy efficiency, renewable energy, and sustainability in buildings. TREAT Software Program a computer program that uses SUNREL and is designed to provide

Management on the Go

ERIC Educational Resources Information Center

Technology & Learning, 2005

2005-01-01

The employment of administrative tools for effective management is evaluated in this article. Using an administrative tool like a Palm[R] handheld computer and appropriate software can make the difference. For anyone running a single school or an entire district, managing data is the key to maintaining an efficient organization. Many…

Integrated design, execution, and analysis of arrayed and pooled CRISPR genome-editing experiments.

PubMed

Canver, Matthew C; Haeussler, Maximilian; Bauer, Daniel E; Orkin, Stuart H; Sanjana, Neville E; Shalem, Ophir; Yuan, Guo-Cheng; Zhang, Feng; Concordet, Jean-Paul; Pinello, Luca

2018-05-01

CRISPR (clustered regularly interspaced short palindromic repeats) genome-editing experiments offer enormous potential for the evaluation of genomic loci using arrayed single guide RNAs (sgRNAs) or pooled sgRNA libraries. Numerous computational tools are available to help design sgRNAs with optimal on-target efficiency and minimal off-target potential. In addition, computational tools have been developed to analyze deep-sequencing data resulting from genome-editing experiments. However, these tools are typically developed in isolation and oftentimes are not readily translatable into laboratory-based experiments. Here, we present a protocol that describes in detail both the computational and benchtop implementation of an arrayed and/or pooled CRISPR genome-editing experiment. This protocol provides instructions for sgRNA design with CRISPOR (computational tool for the design, evaluation, and cloning of sgRNA sequences), experimental implementation, and analysis of the resulting high-throughput sequencing data with CRISPResso (computational tool for analysis of genome-editing outcomes from deep-sequencing data). This protocol allows for design and execution of arrayed and pooled CRISPR experiments in 4-5 weeks by non-experts, as well as computational data analysis that can be performed in 1-2 d by both computational and noncomputational biologists alike using web-based and/or command-line versions.

Anatomical medial surfaces with efficient resolution of branches singularities.

PubMed

Gil, Debora; Vera, Sergio; Borràs, Agnés; Andaluz, Albert; González Ballester, Miguel A

2017-01-01

Medial surfaces are powerful tools for shape description, but their use has been limited due to the sensibility of existing methods to branching artifacts. Medial branching artifacts are associated to perturbations of the object boundary rather than to geometric features. Such instability is a main obstacle for a confident application in shape recognition and description. Medial branches correspond to singularities of the medial surface and, thus, they are problematic for existing morphological and energy-based algorithms. In this paper, we use algebraic geometry concepts in an energy-based approach to compute a medial surface presenting a stable branching topology. We also present an efficient GPU-CPU implementation using standard image processing tools. We show the method computational efficiency and quality on a custom made synthetic database. Finally, we present some results on a medical imaging application for localization of abdominal pathologies. Copyright © 2016 Elsevier B.V. All rights reserved.

Harnessing the power of emerging petascale platforms

NASA Astrophysics Data System (ADS)

Mellor-Crummey, John

2007-07-01

As part of the US Department of Energy's Scientific Discovery through Advanced Computing (SciDAC-2) program, science teams are tackling problems that require computational simulation and modeling at the petascale. A grand challenge for computer science is to develop software technology that makes it easier to harness the power of these systems to aid scientific discovery. As part of its activities, the SciDAC-2 Center for Scalable Application Development Software (CScADS) is building open source software tools to support efficient scientific computing on the emerging leadership-class platforms. In this paper, we describe two tools for performance analysis and tuning that are being developed as part of CScADS: a tool for analyzing scalability and performance, and a tool for optimizing loop nests for better node performance. We motivate these tools by showing how they apply to S3D, a turbulent combustion code under development at Sandia National Laboratory. For S3D, our node performance analysis tool helped uncover several performance bottlenecks. Using our loop nest optimization tool, we transformed S3D's most costly loop nest to reduce execution time by a factor of 2.94 for a processor working on a 503 domain.

Parallel Computation of Unsteady Flows on a Network of Workstations

NASA Technical Reports Server (NTRS)

1997-01-01

Parallel computation of unsteady flows requires significant computational resources. The utilization of a network of workstations seems an efficient solution to the problem where large problems can be treated at a reasonable cost. This approach requires the solution of several problems: 1) the partitioning and distribution of the problem over a network of workstation, 2) efficient communication tools, 3) managing the system efficiently for a given problem. Of course, there is the question of the efficiency of any given numerical algorithm to such a computing system. NPARC code was chosen as a sample for the application. For the explicit version of the NPARC code both two- and three-dimensional problems were studied. Again both steady and unsteady problems were investigated. The issues studied as a part of the research program were: 1) how to distribute the data between the workstations, 2) how to compute and how to communicate at each node efficiently, 3) how to balance the load distribution. In the following, a summary of these activities is presented. Details of the work have been presented and published as referenced.

Northwest Trajectory Analysis Capability: A Platform for Enhancing Computational Biophysics Analysis

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

Peterson, Elena S.; Stephan, Eric G.; Corrigan, Abigail L.

2008-07-30

As computational resources continue to increase, the ability of computational simulations to effectively complement, and in some cases replace, experimentation in scientific exploration also increases. Today, large-scale simulations are recognized as an effective tool for scientific exploration in many disciplines including chemistry and biology. A natural side effect of this trend has been the need for an increasingly complex analytical environment. In this paper, we describe Northwest Trajectory Analysis Capability (NTRAC), an analytical software suite developed to enhance the efficiency of computational biophysics analyses. Our strategy is to layer higher-level services and introduce improved tools within the user’s familiar environmentmore » without preventing researchers from using traditional tools and methods. Our desire is to share these experiences to serve as an example for effectively analyzing data intensive large scale simulation data.« less

The future challenge for aeropropulsion

NASA Technical Reports Server (NTRS)

Rosen, Robert; Bowditch, David N.

1992-01-01

NASA's research in aeropropulsion is focused on improving the efficiency, capability, and environmental compatibility for all classes of future aircraft. The development of innovative concepts, and theoretical, experimental, and computational tools provide the knowledge base for continued propulsion system advances. Key enabling technologies include advances in internal fluid mechanics, structures, light-weight high-strength composite materials, and advanced sensors and controls. Recent emphasis has been on the development of advanced computational tools in internal fluid mechanics, structural mechanics, reacting flows, and computational chemistry. For subsonic transport applications, very high bypass ratio turbofans with increased engine pressure ratio are being investigated to increase fuel efficiency and reduce airport noise levels. In a joint supersonic cruise propulsion program with industry, the critical environmental concerns of emissions and community noise are being addressed. NASA is also providing key technologies for the National Aerospaceplane, and is studying propulsion systems that provide the capability for aircraft to accelerate to and cruise in the Mach 4-6 speed range. The combination of fundamental, component, and focused technology development underway at NASA will make possible dramatic advances in aeropropulsion efficiency and environmental compatibility for future aeronautical vehicles.

Computer-assisted coding and clinical documentation: first things first.

PubMed

Tully, Melinda; Carmichael, Angela

2012-10-01

Computer-assisted coding tools have the potential to drive improvements in seven areas: Transparency of coding. Productivity (generally by 20 to 25 percent for inpatient claims). Accuracy (by improving specificity of documentation). Cost containment (by reducing overtime expenses, audit fees, and denials). Compliance. Efficiency. Consistency.

Development of Advanced Light-Duty Powertrain and Hybrid Analysis Tool (SAE 2013-01-0808)

EPA Science Inventory

The Advanced Light-Duty Powertrain and Hybrid Analysis tool was created by Environmental Protection Agency to evaluate the Greenhouse gas emissions and fuel efficiency from light-duty vehicles. It is a physics-based, forward-looking, full vehicle computer simulator, which is cap...

Network-Centric Data Mining for Medical Applications

ERIC Educational Resources Information Center

Davis, Darcy A.

2012-01-01

Faced with unsustainable costs and enormous amounts of under-utilized data, health care needs more efficient practices, research, and tools to harness the benefits of data. These methods create a feedback loop where computational tools guide and facilitate research, leading to improved biological knowledge and clinical standards, which will in…

DEVELOPING A CAPE-OPEN COMPLIANT METAL FINISHING FACILITY POLLUTION PREVENTION TOOL (CO-MFFP2T)

EPA Science Inventory

The USEPA is developing a Computer Aided Process Engineering (CAPE) software tool for the metal finishing industry that helps users design efficient metal finishing processes that are less polluting to the environment. Metal finishing process lines can be simulated and evaluated...

Efficient hybrid-symbolic methods for quantum mechanical calculations

NASA Astrophysics Data System (ADS)

Scott, T. C.; Zhang, Wenxing

2015-06-01

We present hybrid symbolic-numerical tools to generate optimized numerical code for rapid prototyping and fast numerical computation starting from a computer algebra system (CAS) and tailored to any given quantum mechanical problem. Although a major focus concerns the quantum chemistry methods of H. Nakatsuji which has yielded successful and very accurate eigensolutions for small atoms and molecules, the tools are general and may be applied to any basis set calculation with a variational principle applied to its linear and non-linear parameters.

Topology and boundary shape optimization as an integrated design tool

NASA Technical Reports Server (NTRS)

Bendsoe, Martin Philip; Rodrigues, Helder Carrico

1990-01-01

The optimal topology of a two dimensional linear elastic body can be computed by regarding the body as a domain of the plane with a high density of material. Such an optimal topology can then be used as the basis for a shape optimization method that computes the optimal form of the boundary curves of the body. This results in an efficient and reliable design tool, which can be implemented via common FEM mesh generator and CAD type input-output facilities.

Software For Computer-Security Audits

NASA Technical Reports Server (NTRS)

Arndt, Kate; Lonsford, Emily

1994-01-01

Information relevant to potential breaches of security gathered efficiently. Automated Auditing Tools for VAX/VMS program includes following automated software tools performing noted tasks: Privileged ID Identification, program identifies users and their privileges to circumvent existing computer security measures; Critical File Protection, critical files not properly protected identified; Inactive ID Identification, identifications of users no longer in use found; Password Lifetime Review, maximum lifetimes of passwords of all identifications determined; and Password Length Review, minimum allowed length of passwords of all identifications determined. Written in DEC VAX DCL language.

Memory management in genome-wide association studies

PubMed Central

2009-01-01

Genome-wide association is a powerful tool for the identification of genes that underlie common diseases. Genome-wide association studies generate billions of genotypes and pose significant computational challenges for most users including limited computer memory. We applied a recently developed memory management tool to two analyses of North American Rheumatoid Arthritis Consortium studies and measured the performance in terms of central processing unit and memory usage. We conclude that our memory management approach is simple, efficient, and effective for genome-wide association studies. PMID:20018047

SURE reliability analysis: Program and mathematics

NASA Technical Reports Server (NTRS)

Butler, Ricky W.; White, Allan L.

1988-01-01

The SURE program is a new reliability analysis tool for ultrareliable computer system architectures. The computational methods on which the program is based provide an efficient means for computing accurate upper and lower bounds for the death state probabilities of a large class of semi-Markov models. Once a semi-Markov model is described using a simple input language, the SURE program automatically computes the upper and lower bounds on the probability of system failure. A parameter of the model can be specified as a variable over a range of values directing the SURE program to perform a sensitivity analysis automatically. This feature, along with the speed of the program, makes it especially useful as a design tool.

The Ethics of Technology

ERIC Educational Resources Information Center

Olson, Gary A.

2007-01-01

Many professors, staff members, and even administrators see campus computers and e-mail accounts as their own private property--a type of employment benefit provided with no constraints on use. The fact is, universities "assign" computer equipment to personnel as tools to help them perform their jobs more effectively and efficiently, in the same…

Final-Approach-Spacing Subsystem For Air Traffic

NASA Technical Reports Server (NTRS)

Davis, Thomas J.; Erzberger, Heinz; Bergeron, Hugh

1992-01-01

Automation subsystem of computers, computer workstations, communication equipment, and radar helps air-traffic controllers in terminal radar approach-control (TRACON) facility manage sequence and spacing of arriving aircraft for both efficiency and safety. Called FAST (Final Approach Spacing Tool), subsystem enables controllers to choose among various levels of automation.

APPLICATION OF 3D COMPUTER-AIDED TOMOGRAPHY TO THE QUANTIFICATION OF MARINE SEDIMENT COMMUNITIES IN POLLUTION GRADIENTS

EPA Science Inventory

Computer-Aided Tomography (CT) has been demonstrated to be a cost efficient tool for the qualitative and quantitative study of estuarine benthic communities along pollution gradients.
Now we have advanced this technology to successfully visualize and discriminate three dimen...

ICCE/ICCAI 2000 Full & Short Papers (Teaching and Learning Processes).

ERIC Educational Resources Information Center

2000

This document contains the full and short papers on teaching and learning processes from ICCE/ICCAI 2000 (International Conference on Computers in Education/International Conference on Computer-Assisted Instruction) covering the following topics: a code restructuring tool to help scaffold novice programmers; efficient study of Kanji using…

GTZ: a fast compression and cloud transmission tool optimized for FASTQ files.

PubMed

Xing, Yuting; Li, Gen; Wang, Zhenguo; Feng, Bolun; Song, Zhuo; Wu, Chengkun

2017-12-28

The dramatic development of DNA sequencing technology is generating real big data, craving for more storage and bandwidth. To speed up data sharing and bring data to computing resource faster and cheaper, it is necessary to develop a compression tool than can support efficient compression and transmission of sequencing data onto the cloud storage. This paper presents GTZ, a compression and transmission tool, optimized for FASTQ files. As a reference-free lossless FASTQ compressor, GTZ treats different lines of FASTQ separately, utilizes adaptive context modelling to estimate their characteristic probabilities, and compresses data blocks with arithmetic coding. GTZ can also be used to compress multiple files or directories at once. Furthermore, as a tool to be used in the cloud computing era, it is capable of saving compressed data locally or transmitting data directly into cloud by choice. We evaluated the performance of GTZ on some diverse FASTQ benchmarks. Results show that in most cases, it outperforms many other tools in terms of the compression ratio, speed and stability. GTZ is a tool that enables efficient lossless FASTQ data compression and simultaneous data transmission onto to cloud. It emerges as a useful tool for NGS data storage and transmission in the cloud environment. GTZ is freely available online at: https://github.com/Genetalks/gtz .

Programming the Navier-Stokes computer: An abstract machine model and a visual editor

NASA Technical Reports Server (NTRS)

Middleton, David; Crockett, Tom; Tomboulian, Sherry

1988-01-01

The Navier-Stokes computer is a parallel computer designed to solve Computational Fluid Dynamics problems. Each processor contains several floating point units which can be configured under program control to implement a vector pipeline with several inputs and outputs. Since the development of an effective compiler for this computer appears to be very difficult, machine level programming seems necessary and support tools for this process have been studied. These support tools are organized into a graphical program editor. A programming process is described by which appropriate computations may be efficiently implemented on the Navier-Stokes computer. The graphical editor would support this programming process, verifying various programmer choices for correctness and deducing values such as pipeline delays and network configurations. Step by step details are provided and demonstrated with two example programs.

Current And Future Directions Of Lens Design Software

NASA Astrophysics Data System (ADS)

Gustafson, Darryl E.

1983-10-01

The most effective environment for doing lens design continues to evolve as new computer hardware and software tools become available. Important recent hardware developments include: Low-cost but powerful interactive multi-user 32 bit computers with virtual memory that are totally software-compatible with prior larger and more expensive members of the family. A rapidly growing variety of graphics devices for both hard-copy and screen graphics, including many with color capability. In addition, with optical design software readily accessible in many forms, optical design has become a part-time activity for a large number of engineers instead of being restricted to a small number of full-time specialists. A designer interface that is friendly for the part-time user while remaining efficient for the full-time designer is thus becoming more important as well as more practical. Along with these developments, software tools in other scientific and engineering disciplines are proliferating. Thus, the optical designer is less and less unique in his use of computer-aided techniques and faces the challenge and opportunity of efficiently communicating his designs to other computer-aided-design (CAD), computer-aided-manufacturing (CAM), structural, thermal, and mechanical software tools. This paper will address the impact of these developments on the current and future directions of the CODE VTM optical design software package, its implementation, and the resulting lens design environment.

Computer assisted audit techniques for UNIX (UNIX-CAATS)

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

Polk, W.T.

1991-12-31

Federal and DOE regulations impose specific requirements for internal controls of computer systems. These controls include adequate separation of duties and sufficient controls for access of system and data. The DOE Inspector General`s Office has the responsibility to examine internal controls, as well as efficient use of computer system resources. As a result, DOE supported NIST development of computer assisted audit techniques to examine BSD UNIX computers (UNIX-CAATS). These systems were selected due to the increasing number of UNIX workstations in use within DOE. This paper describes the design and development of these techniques, as well as the results ofmore » testing at NIST and the first audit at a DOE site. UNIX-CAATS consists of tools which examine security of passwords, file systems, and network access. In addition, a tool was developed to examine efficiency of disk utilization. Test results at NIST indicated inadequate password management, as well as weak network resource controls. File system security was considered adequate. Audit results at a DOE site indicated weak password management and inefficient disk utilization. During the audit, we also found improvements to UNIX-CAATS were needed when applied to large systems. NIST plans to enhance the techniques developed for DOE/IG in future work. This future work would leverage currently available tools, along with needed enhancements. These enhancements would enable DOE/IG to audit large systems, such as supercomputers.« less

Computer assisted audit techniques for UNIX (UNIX-CAATS)

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

Polk, W.T.

1991-01-01

Federal and DOE regulations impose specific requirements for internal controls of computer systems. These controls include adequate separation of duties and sufficient controls for access of system and data. The DOE Inspector General's Office has the responsibility to examine internal controls, as well as efficient use of computer system resources. As a result, DOE supported NIST development of computer assisted audit techniques to examine BSD UNIX computers (UNIX-CAATS). These systems were selected due to the increasing number of UNIX workstations in use within DOE. This paper describes the design and development of these techniques, as well as the results ofmore » testing at NIST and the first audit at a DOE site. UNIX-CAATS consists of tools which examine security of passwords, file systems, and network access. In addition, a tool was developed to examine efficiency of disk utilization. Test results at NIST indicated inadequate password management, as well as weak network resource controls. File system security was considered adequate. Audit results at a DOE site indicated weak password management and inefficient disk utilization. During the audit, we also found improvements to UNIX-CAATS were needed when applied to large systems. NIST plans to enhance the techniques developed for DOE/IG in future work. This future work would leverage currently available tools, along with needed enhancements. These enhancements would enable DOE/IG to audit large systems, such as supercomputers.« less

Developing eThread pipeline using SAGA-pilot abstraction for large-scale structural bioinformatics.

PubMed

Ragothaman, Anjani; Boddu, Sairam Chowdary; Kim, Nayong; Feinstein, Wei; Brylinski, Michal; Jha, Shantenu; Kim, Joohyun

2014-01-01

While most of computational annotation approaches are sequence-based, threading methods are becoming increasingly attractive because of predicted structural information that could uncover the underlying function. However, threading tools are generally compute-intensive and the number of protein sequences from even small genomes such as prokaryotes is large typically containing many thousands, prohibiting their application as a genome-wide structural systems biology tool. To leverage its utility, we have developed a pipeline for eThread--a meta-threading protein structure modeling tool, that can use computational resources efficiently and effectively. We employ a pilot-based approach that supports seamless data and task-level parallelism and manages large variation in workload and computational requirements. Our scalable pipeline is deployed on Amazon EC2 and can efficiently select resources based upon task requirements. We present runtime analysis to characterize computational complexity of eThread and EC2 infrastructure. Based on results, we suggest a pathway to an optimized solution with respect to metrics such as time-to-solution or cost-to-solution. Our eThread pipeline can scale to support a large number of sequences and is expected to be a viable solution for genome-scale structural bioinformatics and structure-based annotation, particularly, amenable for small genomes such as prokaryotes. The developed pipeline is easily extensible to other types of distributed cyberinfrastructure.

Developing eThread Pipeline Using SAGA-Pilot Abstraction for Large-Scale Structural Bioinformatics

PubMed Central

Ragothaman, Anjani; Feinstein, Wei; Jha, Shantenu; Kim, Joohyun

2014-01-01

While most of computational annotation approaches are sequence-based, threading methods are becoming increasingly attractive because of predicted structural information that could uncover the underlying function. However, threading tools are generally compute-intensive and the number of protein sequences from even small genomes such as prokaryotes is large typically containing many thousands, prohibiting their application as a genome-wide structural systems biology tool. To leverage its utility, we have developed a pipeline for eThread—a meta-threading protein structure modeling tool, that can use computational resources efficiently and effectively. We employ a pilot-based approach that supports seamless data and task-level parallelism and manages large variation in workload and computational requirements. Our scalable pipeline is deployed on Amazon EC2 and can efficiently select resources based upon task requirements. We present runtime analysis to characterize computational complexity of eThread and EC2 infrastructure. Based on results, we suggest a pathway to an optimized solution with respect to metrics such as time-to-solution or cost-to-solution. Our eThread pipeline can scale to support a large number of sequences and is expected to be a viable solution for genome-scale structural bioinformatics and structure-based annotation, particularly, amenable for small genomes such as prokaryotes. The developed pipeline is easily extensible to other types of distributed cyberinfrastructure. PMID:24995285

A Computationally Efficient Method for Polyphonic Pitch Estimation

NASA Astrophysics Data System (ADS)

Zhou, Ruohua; Reiss, Joshua D.; Mattavelli, Marco; Zoia, Giorgio

2009-12-01

This paper presents a computationally efficient method for polyphonic pitch estimation. The method employs the Fast Resonator Time-Frequency Image (RTFI) as the basic time-frequency analysis tool. The approach is composed of two main stages. First, a preliminary pitch estimation is obtained by means of a simple peak-picking procedure in the pitch energy spectrum. Such spectrum is calculated from the original RTFI energy spectrum according to harmonic grouping principles. Then the incorrect estimations are removed according to spectral irregularity and knowledge of the harmonic structures of the music notes played on commonly used music instruments. The new approach is compared with a variety of other frame-based polyphonic pitch estimation methods, and results demonstrate the high performance and computational efficiency of the approach.

A high performance scientific cloud computing environment for materials simulations

NASA Astrophysics Data System (ADS)

Jorissen, K.; Vila, F. D.; Rehr, J. J.

2012-09-01

We describe the development of a scientific cloud computing (SCC) platform that offers high performance computation capability. The platform consists of a scientific virtual machine prototype containing a UNIX operating system and several materials science codes, together with essential interface tools (an SCC toolset) that offers functionality comparable to local compute clusters. In particular, our SCC toolset provides automatic creation of virtual clusters for parallel computing, including tools for execution and monitoring performance, as well as efficient I/O utilities that enable seamless connections to and from the cloud. Our SCC platform is optimized for the Amazon Elastic Compute Cloud (EC2). We present benchmarks for prototypical scientific applications and demonstrate performance comparable to local compute clusters. To facilitate code execution and provide user-friendly access, we have also integrated cloud computing capability in a JAVA-based GUI. Our SCC platform may be an alternative to traditional HPC resources for materials science or quantum chemistry applications.

ADAM: Analysis of Discrete Models of Biological Systems Using Computer Algebra

PubMed Central

2011-01-01

Background Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. Results We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Conclusions Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics. PMID:21774817

NREL's Building-Integrated Supercomputer Provides Heating and Efficient Computing (Fact Sheet)

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

Not Available

2014-09-01

NREL's Energy Systems Integration Facility (ESIF) is meant to investigate new ways to integrate energy sources so they work together efficiently, and one of the key tools to that investigation, a new supercomputer, is itself a prime example of energy systems integration. NREL teamed with Hewlett-Packard (HP) and Intel to develop the innovative warm-water, liquid-cooled Peregrine supercomputer, which not only operates efficiently but also serves as the primary source of building heat for ESIF offices and laboratories. This innovative high-performance computer (HPC) can perform more than a quadrillion calculations per second as part of the world's most energy-efficient HPC datamore » center.« less

Efficient Use of Distributed Systems for Scientific Applications

NASA Technical Reports Server (NTRS)

Taylor, Valerie; Chen, Jian; Canfield, Thomas; Richard, Jacques

2000-01-01

Distributed computing has been regarded as the future of high performance computing. Nationwide high speed networks such as vBNS are becoming widely available to interconnect high-speed computers, virtual environments, scientific instruments and large data sets. One of the major issues to be addressed with distributed systems is the development of computational tools that facilitate the efficient execution of parallel applications on such systems. These tools must exploit the heterogeneous resources (networks and compute nodes) in distributed systems. This paper presents a tool, called PART, which addresses this issue for mesh partitioning. PART takes advantage of the following heterogeneous system features: (1) processor speed; (2) number of processors; (3) local network performance; and (4) wide area network performance. Further, different finite element applications under consideration may have different computational complexities, different communication patterns, and different element types, which also must be taken into consideration when partitioning. PART uses parallel simulated annealing to partition the domain, taking into consideration network and processor heterogeneity. The results of using PART for an explicit finite element application executing on two IBM SPs (located at Argonne National Laboratory and the San Diego Supercomputer Center) indicate an increase in efficiency by up to 36% as compared to METIS, a widely used mesh partitioning tool. The input to METIS was modified to take into consideration heterogeneous processor performance; METIS does not take into consideration heterogeneous networks. The execution times for these applications were reduced by up to 30% as compared to METIS. These results are given in Figure 1 for four irregular meshes with number of elements ranging from 30,269 elements for the Barth5 mesh to 11,451 elements for the Barth4 mesh. Future work with PART entails using the tool with an integrated application requiring distributed systems. In particular this application, illustrated in the document entails an integration of finite element and fluid dynamic simulations to address the cooling of turbine blades of a gas turbine engine design. It is not uncommon to encounter high-temperature, film-cooled turbine airfoils with 1,000,000s of degrees of freedom. This results because of the complexity of the various components of the airfoils, requiring fine-grain meshing for accuracy. Additional information is contained in the original.

Citizens unite for computational immunology!

PubMed

Belden, Orrin S; Baker, Sarah Catherine; Baker, Brian M

2015-07-01

Recruiting volunteers who can provide computational time, programming expertise, or puzzle-solving talent has emerged as a powerful tool for biomedical research. Recent projects demonstrate the potential for such 'crowdsourcing' efforts in immunology. Tools for developing applications, new funding opportunities, and an eager public make crowdsourcing a serious option for creative solutions for computationally-challenging problems. Expanded uses of crowdsourcing in immunology will allow for more efficient large-scale data collection and analysis. It will also involve, inspire, educate, and engage the public in a variety of meaningful ways. The benefits are real - it is time to jump in! Copyright © 2015 Elsevier Ltd. All rights reserved.

Computer Grading As an Instructional Tool.

ERIC Educational Resources Information Center

Rottmann, Ray M.; Hudson, H. T.

1983-01-01

Describes computer grading system providing/storing scores and giving feedback to instructors on how students are performing on a day-to-day basis and how they are handling course concepts. Focuses on the hardware and software of this efficient computerized grading package, which can be used with classes of 250 students (or larger). (Author/JN)

Two reduced form air quality modeling techniques for rapidly calculating pollutant mitigation potential across many sources, locations and precursor emission types

EPA Science Inventory

Due to the computational cost of running regional-scale numerical air quality models, reduced form models (RFM) have been proposed as computationally efficient simulation tools for characterizing the pollutant response to many different types of emission reductions. The U.S. Envi...

Cost-effective cloud computing: a case study using the comparative genomics tool, roundup.

PubMed

Kudtarkar, Parul; Deluca, Todd F; Fusaro, Vincent A; Tonellato, Peter J; Wall, Dennis P

2010-12-22

Comparative genomics resources, such as ortholog detection tools and repositories are rapidly increasing in scale and complexity. Cloud computing is an emerging technological paradigm that enables researchers to dynamically build a dedicated virtual cluster and may represent a valuable alternative for large computational tools in bioinformatics. In the present manuscript, we optimize the computation of a large-scale comparative genomics resource-Roundup-using cloud computing, describe the proper operating principles required to achieve computational efficiency on the cloud, and detail important procedures for improving cost-effectiveness to ensure maximal computation at minimal costs. Utilizing the comparative genomics tool, Roundup, as a case study, we computed orthologs among 902 fully sequenced genomes on Amazon's Elastic Compute Cloud. For managing the ortholog processes, we designed a strategy to deploy the web service, Elastic MapReduce, and maximize the use of the cloud while simultaneously minimizing costs. Specifically, we created a model to estimate cloud runtime based on the size and complexity of the genomes being compared that determines in advance the optimal order of the jobs to be submitted. We computed orthologous relationships for 245,323 genome-to-genome comparisons on Amazon's computing cloud, a computation that required just over 200 hours and cost $8,000 USD, at least 40% less than expected under a strategy in which genome comparisons were submitted to the cloud randomly with respect to runtime. Our cost savings projections were based on a model that not only demonstrates the optimal strategy for deploying RSD to the cloud, but also finds the optimal cluster size to minimize waste and maximize usage. Our cost-reduction model is readily adaptable for other comparative genomics tools and potentially of significant benefit to labs seeking to take advantage of the cloud as an alternative to local computing infrastructure.

Methodological Foundations for Designing Intelligent Computer-Based Training

DTIC Science & Technology

1991-09-03

student models, graphic forms, version control data structures, flowcharts , etc. Circuit simulations are an obvious case. A circuit, after all, can... flowcharts as a basic data structure, and we were able to generalize our tools to create a flowchart drawing tool for inputting both the appearance and...the meaning of flowcharts efficiently. For the Sherlock work, we built a tool that permitted inputting of information about front panels and

VirusDetect: An automated pipeline for efficient virus discovery using deep sequencing of small RNAs

USDA-ARS?s Scientific Manuscript database

Accurate detection of viruses in plants and animals is critical for agriculture production and human health. Deep sequencing and assembly of virus-derived siRNAs has proven to be a highly efficient approach for virus discovery. However, to date no computational tools specifically designed for both k...

Development of efficient and cost-effective distributed hydrological modeling tool MWEasyDHM based on open-source MapWindow GIS

NASA Astrophysics Data System (ADS)

Lei, Xiaohui; Wang, Yuhui; Liao, Weihong; Jiang, Yunzhong; Tian, Yu; Wang, Hao

2011-09-01

Many regions are still threatened with frequent floods and water resource shortage problems in China. Consequently, the task of reproducing and predicting the hydrological process in watersheds is hard and unavoidable for reducing the risks of damage and loss. Thus, it is necessary to develop an efficient and cost-effective hydrological tool in China as many areas should be modeled. Currently, developed hydrological tools such as Mike SHE and ArcSWAT (soil and water assessment tool based on ArcGIS) show significant power in improving the precision of hydrological modeling in China by considering spatial variability both in land cover and in soil type. However, adopting developed commercial tools in such a large developing country comes at a high cost. Commercial modeling tools usually contain large numbers of formulas, complicated data formats, and many preprocessing or postprocessing steps that may make it difficult for the user to carry out simulation, thus lowering the efficiency of the modeling process. Besides, commercial hydrological models usually cannot be modified or improved to be suitable for some special hydrological conditions in China. Some other hydrological models are open source, but integrated into commercial GIS systems. Therefore, by integrating hydrological simulation code EasyDHM, a hydrological simulation tool named MWEasyDHM was developed based on open-source MapWindow GIS, the purpose of which is to establish the first open-source GIS-based distributed hydrological model tool in China by integrating modules of preprocessing, model computation, parameter estimation, result display, and analysis. MWEasyDHM provides users with a friendly manipulating MapWindow GIS interface, selectable multifunctional hydrological processing modules, and, more importantly, an efficient and cost-effective hydrological simulation tool. The general construction of MWEasyDHM consists of four major parts: (1) a general GIS module for hydrological analysis, (2) a preprocessing module for modeling inputs, (3) a model calibration module, and (4) a postprocessing module. The general GIS module for hydrological analysis is developed on the basis of totally open-source GIS software, MapWindow, which contains basic GIS functions. The preprocessing module is made up of three submodules including a DEM-based submodule for hydrological analysis, a submodule for default parameter calculation, and a submodule for the spatial interpolation of meteorological data. The calibration module contains parallel computation, real-time computation, and visualization. The postprocessing module includes model calibration and model results spatial visualization using tabular form and spatial grids. MWEasyDHM makes it possible for efficient modeling and calibration of EasyDHM, and promises further development of cost-effective applications in various watersheds.

The SURE reliability analysis program

NASA Technical Reports Server (NTRS)

Butler, R. W.

1986-01-01

The SURE program is a new reliability tool for ultrareliable computer system architectures. The program is based on computational methods recently developed for the NASA Langley Research Center. These methods provide an efficient means for computing accurate upper and lower bounds for the death state probabilities of a large class of semi-Markov models. Once a semi-Markov model is described using a simple input language, the SURE program automatically computes the upper and lower bounds on the probability of system failure. A parameter of the model can be specified as a variable over a range of values directing the SURE program to perform a sensitivity analysis automatically. This feature, along with the speed of the program, makes it especially useful as a design tool.

The SURE Reliability Analysis Program

NASA Technical Reports Server (NTRS)

Butler, R. W.

1986-01-01

The SURE program is a new reliability analysis tool for ultrareliable computer system architectures. The program is based on computational methods recently developed for the NASA Langley Research Center. These methods provide an efficient means for computing accurate upper and lower bounds for the death state probabilities of a large class of semi-Markov models. Once a semi-Markov model is described using a simple input language, the SURE program automatically computes the upper and lower bounds on the probability of system failure. A parameter of the model can be specified as a variable over a range of values directing the SURE program to perform a sensitivity analysis automatically. This feature, along with the speed of the program, makes it especially useful as a design tool.

Desktop microsimulation: a tool to improve efficiency in the medical office practice.

PubMed

Montgomery, James B; Linville, Beth A; Slonim, Anthony D

2013-01-01

Because the economic crisis in the United States continues to have an impact on healthcare organizations, industry leaders must optimize their decision making. Discrete-event computer simulation is a quality tool with a demonstrated track record of improving the precision of analysis for process redesign. However, the use of simulation to consolidate practices and design efficiencies into an unfinished medical office building was a unique task. A discrete-event computer simulation package was used to model the operations and forecast future results for four orthopedic surgery practices. The scenarios were created to allow an evaluation of the impact of process change on the output variables of exam room utilization, patient queue size, and staff utilization. The model helped with decisions regarding space allocation and efficient exam room use by demonstrating the impact of process changes in patient queues at check-in/out, x-ray, and cast room locations when compared to the status quo model. The analysis impacted decisions on facility layout, patient flow, and staff functions in this newly consolidated practice. Simulation was found to be a useful tool for process redesign and decision making even prior to building occupancy. © 2011 National Association for Healthcare Quality.

Efficient utilization of graphics technology for space animation

NASA Technical Reports Server (NTRS)

Panos, Gregory Peter

1989-01-01

Efficient utilization of computer graphics technology has become a major investment in the work of aerospace engineers and mission designers. These new tools are having a significant impact in the development and analysis of complex tasks and procedures which must be prepared prior to actual space flight. Design and implementation of useful methods in applying these tools has evolved into a complex interaction of hardware, software, network, video and various user interfaces. Because few people can understand every aspect of this broad mix of technology, many specialists are required to build, train, maintain and adapt these tools to changing user needs. Researchers have set out to create systems where an engineering designer can easily work to achieve goals with a minimum of technological distraction. This was accomplished with high-performance flight simulation visual systems and supercomputer computational horsepower. Control throughout the creative process is judiciously applied while maintaining generality and ease of use to accommodate a wide variety of engineering needs.

The ChIP-Seq tools and web server: a resource for analyzing ChIP-seq and other types of genomic data.

PubMed

Ambrosini, Giovanna; Dreos, René; Kumar, Sunil; Bucher, Philipp

2016-11-18

ChIP-seq and related high-throughput chromatin profilig assays generate ever increasing volumes of highly valuable biological data. To make sense out of it, biologists need versatile, efficient and user-friendly tools for access, visualization and itegrative analysis of such data. Here we present the ChIP-Seq command line tools and web server, implementing basic algorithms for ChIP-seq data analysis starting with a read alignment file. The tools are optimized for memory-efficiency and speed thus allowing for processing of large data volumes on inexpensive hardware. The web interface provides access to a large database of public data. The ChIP-Seq tools have a modular and interoperable design in that the output from one application can serve as input to another one. Complex and innovative tasks can thus be achieved by running several tools in a cascade. The various ChIP-Seq command line tools and web services either complement or compare favorably to related bioinformatics resources in terms of computational efficiency, ease of access to public data and interoperability with other web-based tools. The ChIP-Seq server is accessible at http://ccg.vital-it.ch/chipseq/ .

BCM: toolkit for Bayesian analysis of Computational Models using samplers.

PubMed

Thijssen, Bram; Dijkstra, Tjeerd M H; Heskes, Tom; Wessels, Lodewyk F A

2016-10-21

Computational models in biology are characterized by a large degree of uncertainty. This uncertainty can be analyzed with Bayesian statistics, however, the sampling algorithms that are frequently used for calculating Bayesian statistical estimates are computationally demanding, and each algorithm has unique advantages and disadvantages. It is typically unclear, before starting an analysis, which algorithm will perform well on a given computational model. We present BCM, a toolkit for the Bayesian analysis of Computational Models using samplers. It provides efficient, multithreaded implementations of eleven algorithms for sampling from posterior probability distributions and for calculating marginal likelihoods. BCM includes tools to simplify the process of model specification and scripts for visualizing the results. The flexible architecture allows it to be used on diverse types of biological computational models. In an example inference task using a model of the cell cycle based on ordinary differential equations, BCM is significantly more efficient than existing software packages, allowing more challenging inference problems to be solved. BCM represents an efficient one-stop-shop for computational modelers wishing to use sampler-based Bayesian statistics.

Current trends for customized biomedical software tools.

PubMed

Khan, Haseeb Ahmad

2017-01-01

In the past, biomedical scientists were solely dependent on expensive commercial software packages for various applications. However, the advent of user-friendly programming languages and open source platforms has revolutionized the development of simple and efficient customized software tools for solving specific biomedical problems. Many of these tools are designed and developed by biomedical scientists independently or with the support of computer experts and often made freely available for the benefit of scientific community. The current trends for customized biomedical software tools are highlighted in this short review.

Informed public choices for low-carbon electricity portfolios using a computer decision tool.

PubMed

Mayer, Lauren A Fleishman; Bruine de Bruin, Wändi; Morgan, M Granger

2014-04-01

Reducing CO2 emissions from the electricity sector will likely require policies that encourage the widespread deployment of a diverse mix of low-carbon electricity generation technologies. Public discourse informs such policies. To make informed decisions and to productively engage in public discourse, citizens need to understand the trade-offs between electricity technologies proposed for widespread deployment. Building on previous paper-and-pencil studies, we developed a computer tool that aimed to help nonexperts make informed decisions about the challenges faced in achieving a low-carbon energy future. We report on an initial usability study of this interactive computer tool. After providing participants with comparative and balanced information about 10 electricity technologies, we asked them to design a low-carbon electricity portfolio. Participants used the interactive computer tool, which constrained portfolio designs to be realistic and yield low CO2 emissions. As they changed their portfolios, the tool updated information about projected CO2 emissions, electricity costs, and specific environmental impacts. As in the previous paper-and-pencil studies, most participants designed diverse portfolios that included energy efficiency, nuclear, coal with carbon capture and sequestration, natural gas, and wind. Our results suggest that participants understood the tool and used it consistently. The tool may be downloaded from http://cedmcenter.org/tools-for-cedm/informing-the-public-about-low-carbon-technologies/ .

Computational Tools for Metabolic Engineering

PubMed Central

Copeland, Wilbert B.; Bartley, Bryan A.; Chandran, Deepak; Galdzicki, Michal; Kim, Kyung H.; Sleight, Sean C.; Maranas, Costas D.; Sauro, Herbert M.

2012-01-01

A great variety of software applications are now employed in the metabolic engineering field. These applications have been created to support a wide range of experimental and analysis techniques. Computational tools are utilized throughout the metabolic engineering workflow to extract and interpret relevant information from large data sets, to present complex models in a more manageable form, and to propose efficient network design strategies. In this review, we present a number of tools that can assist in modifying and understanding cellular metabolic networks. The review covers seven areas of relevance to metabolic engineers. These include metabolic reconstruction efforts, network visualization, nucleic acid and protein engineering, metabolic flux analysis, pathway prospecting, post-structural network analysis and culture optimization. The list of available tools is extensive and we can only highlight a small, representative portion of the tools from each area. PMID:22629572

Optimizing Engineering Tools Using Modern Ground Architectures

DTIC Science & Technology

2017-12-01

Considerations,” International Journal of Computer Science & Engineering Survey , vol. 5, no. 4, 2014. [10] R. Bell. (n.d). A beginner’s guide to big O notation...scientific community. Traditional computing architectures were not capable of processing the data efficiently, or in some cases, could not process the...thesis investigates how these modern computing architectures could be leveraged by industry and academia to improve the performance and capabilities of

CFD - Mature Technology?

NASA Technical Reports Server (NTRS)

Kwak, Dochan

2005-01-01

Over the past 30 years, numerical methods and simulation tools for fluid dynamic problems have advanced as a new discipline, namely, computational fluid dynamics (CFD). Although a wide spectrum of flow regimes are encountered in many areas of science and engineering, simulation of compressible flow has been the major driver for developing computational algorithms and tools. This is probably due to a large demand for predicting the aerodynamic performance characteristics of flight vehicles, such as commercial, military, and space vehicles. As flow analysis is required to be more accurate and computationally efficient for both commercial and mission-oriented applications (such as those encountered in meteorology, aerospace vehicle development, general fluid engineering and biofluid analysis) CFD tools for engineering become increasingly important for predicting safety, performance and cost. This paper presents the author's perspective on the maturity of CFD, especially from an aerospace engineering point of view.

Analytical prediction with multidimensional computer programs and experimental verification of the performance, at a variety of operating conditions, of two traveling wave tubes with depressed collectors

NASA Technical Reports Server (NTRS)

Dayton, J. A., Jr.; Kosmahl, H. G.; Ramins, P.; Stankiewicz, N.

1979-01-01

Experimental and analytical results are compared for two high performance, octave bandwidth TWT's that use depressed collectors (MDC's) to improve the efficiency. The computations were carried out with advanced, multidimensional computer programs that are described here in detail. These programs model the electron beam as a series of either disks or rings of charge and follow their multidimensional trajectories from the RF input of the ideal TWT, through the slow wave structure, through the magnetic refocusing system, to their points of impact in the depressed collector. Traveling wave tube performance, collector efficiency, and collector current distribution were computed and the results compared with measurements for a number of TWT-MDC systems. Power conservation and correct accounting of TWT and collector losses were observed. For the TWT's operating at saturation, very good agreement was obtained between the computed and measured collector efficiencies. For a TWT operating 3 and 6 dB below saturation, excellent agreement between computed and measured collector efficiencies was obtained in some cases but only fair agreement in others. However, deviations can largely be explained by small differences in the computed and actual spent beam energy distributions. The analytical tools used here appear to be sufficiently refined to design efficient collectors for this class of TWT. However, for maximum efficiency, some experimental optimization (e.g., collector voltages and aperture sizes) will most likely be required.

Aligator: A computational tool for optimizing total chemical synthesis of large proteins.

PubMed

Jacobsen, Michael T; Erickson, Patrick W; Kay, Michael S

2017-09-15

The scope of chemical protein synthesis (CPS) continues to expand, driven primarily by advances in chemical ligation tools (e.g., reversible solubilizing groups and novel ligation chemistries). However, the design of an optimal synthesis route can be an arduous and fickle task due to the large number of theoretically possible, and in many cases problematic, synthetic strategies. In this perspective, we highlight recent CPS tool advances and then introduce a new and easy-to-use program, Aligator (Automated Ligator), for analyzing and designing the most efficient strategies for constructing large targets using CPS. As a model set, we selected the E. coli ribosomal proteins and associated factors for computational analysis. Aligator systematically scores and ranks all feasible synthetic strategies for a particular CPS target. The Aligator script methodically evaluates potential peptide segments for a target using a scoring function that includes solubility, ligation site quality, segment lengths, and number of ligations to provide a ranked list of potential synthetic strategies. We demonstrate the utility of Aligator by analyzing three recent CPS projects from our lab: TNFα (157 aa), GroES (97 aa), and DapA (312 aa). As the limits of CPS are extended, we expect that computational tools will play an increasingly important role in the efficient execution of ambitious CPS projects such as production of a mirror-image ribosome. Copyright © 2017 Elsevier Ltd. All rights reserved.

Geometric modeling for computer aided design

NASA Technical Reports Server (NTRS)

Schwing, James L.

1992-01-01

The goal was the design and implementation of software to be used in the conceptual design of aerospace vehicles. Several packages and design studies were completed, including two software tools currently used in the conceptual level design of aerospace vehicles. These tools are the Solid Modeling Aerospace Research Tool (SMART) and the Environment for Software Integration and Execution (EASIE). SMART provides conceptual designers with a rapid prototyping capability and additionally provides initial mass property analysis. EASIE provides a set of interactive utilities that simplify the task of building and executing computer aided design systems consisting of diverse, stand alone analysis codes that result in the streamlining of the exchange of data between programs, reducing errors and improving efficiency.

Computational Challenges of Viscous Incompressible Flows

NASA Technical Reports Server (NTRS)

Kwak, Dochan; Kiris, Cetin; Kim, Chang Sung

2004-01-01

Over the past thirty years, numerical methods and simulation tools for incompressible flows have been advanced as a subset of the computational fluid dynamics (CFD) discipline. Although incompressible flows are encountered in many areas of engineering, simulation of compressible flow has been the major driver for developing computational algorithms and tools. This is probably due to the rather stringent requirements for predicting aerodynamic performance characteristics of flight vehicles, while flow devices involving low-speed or incompressible flow could be reasonably well designed without resorting to accurate numerical simulations. As flow devices are required to be more sophisticated and highly efficient CFD took become increasingly important in fluid engineering for incompressible and low-speed flow. This paper reviews some of the successes made possible by advances in computational technologies during the same period, and discusses some of the current challenges faced in computing incompressible flows.

EXTENDING THE REALM OF OPTIMIZATION FOR COMPLEX SYSTEMS: UNCERTAINTY, COMPETITION, AND DYNAMICS

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

Shanbhag, Uday V; Basar, Tamer; Meyn, Sean

Research reported addressed these topics: the development of analytical and algorithmic tools for distributed computation of Nash equilibria; synchronization in mean-field oscillator games, with an emphasis on learning and efficiency analysis; questions that combine learning and computation; questions including stochastic and mean-field games; modeling and control in the context of power markets.

Implementation of a parallel unstructured Euler solver on shared and distributed memory architectures

NASA Technical Reports Server (NTRS)

Mavriplis, D. J.; Das, Raja; Saltz, Joel; Vermeland, R. E.

1992-01-01

An efficient three dimensional unstructured Euler solver is parallelized on a Cray Y-MP C90 shared memory computer and on an Intel Touchstone Delta distributed memory computer. This paper relates the experiences gained and describes the software tools and hardware used in this study. Performance comparisons between two differing architectures are made.

Final Report: Correctness Tools for Petascale Computing

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

Mellor-Crummey, John

2014-10-27

In the course of developing parallel programs for leadership computing systems, subtle programming errors often arise that are extremely difficult to diagnose without tools. To meet this challenge, University of Maryland, the University of Wisconsin—Madison, and Rice University worked to develop lightweight tools to help code developers pinpoint a variety of program correctness errors that plague parallel scientific codes. The aim of this project was to develop software tools that help diagnose program errors including memory leaks, memory access errors, round-off errors, and data races. Research at Rice University focused on developing algorithms and data structures to support efficient monitoringmore » of multithreaded programs for memory access errors and data races. This is a final report about research and development work at Rice University as part of this project.« less

Towards Individualized Instruction with Technology-Enabled Tools and Methods: An Exploratory Study. CRESST Report 854

ERIC Educational Resources Information Center

Chung, Gregory K. W. K.; Delacruz, Girlie C.; Dionne, Gary B.; Baker, Eva L.; Lee, John J.; Osmundson, Ellen

2016-01-01

This report addresses a renewed interest in individualized instruction, driven in part by advances in technology and assessment as well as a persistent desire to increase the access, efficiency, and cost effectiveness of training and education. Using computer-based instruction we delivered extremely efficient instruction targeted to low knowledge…

Research in Computational Astrobiology

NASA Technical Reports Server (NTRS)

Chaban, Galina; Colombano, Silvano; Scargle, Jeff; New, Michael H.; Pohorille, Andrew; Wilson, Michael A.

2003-01-01

We report on several projects in the field of computational astrobiology, which is devoted to advancing our understanding of the origin, evolution and distribution of life in the Universe using theoretical and computational tools. Research projects included modifying existing computer simulation codes to use efficient, multiple time step algorithms, statistical methods for analysis of astrophysical data via optimal partitioning methods, electronic structure calculations on water-nuclei acid complexes, incorporation of structural information into genomic sequence analysis methods and calculations of shock-induced formation of polycylic aromatic hydrocarbon compounds.

Near-Infrared Neuroimaging with NinPy

PubMed Central

Strangman, Gary E.; Zhang, Quan; Zeffiro, Thomas

2009-01-01

There has been substantial recent growth in the use of non-invasive optical brain imaging in studies of human brain function in health and disease. Near-infrared neuroimaging (NIN) is one of the most promising of these techniques and, although NIN hardware continues to evolve at a rapid pace, software tools supporting optical data acquisition, image processing, statistical modeling, and visualization remain less refined. Python, a modular and computationally efficient development language, can support functional neuroimaging studies of diverse design and implementation. In particular, Python's easily readable syntax and modular architecture allow swift prototyping followed by efficient transition to stable production systems. As an introduction to our ongoing efforts to develop Python software tools for structural and functional neuroimaging, we discuss: (i) the role of non-invasive diffuse optical imaging in measuring brain function, (ii) the key computational requirements to support NIN experiments, (iii) our collection of software tools to support NIN, called NinPy, and (iv) future extensions of these tools that will allow integration of optical with other structural and functional neuroimaging data sources. Source code for the software discussed here will be made available at www.nmr.mgh.harvard.edu/Neural_SystemsGroup/software.html. PMID:19543449

An efficient framework for Java data processing systems in HPC environments

NASA Astrophysics Data System (ADS)

Fries, Aidan; Castañeda, Javier; Isasi, Yago; Taboada, Guillermo L.; Portell de Mora, Jordi; Sirvent, Raül

2011-11-01

Java is a commonly used programming language, although its use in High Performance Computing (HPC) remains relatively low. One of the reasons is a lack of libraries offering specific HPC functions to Java applications. In this paper we present a Java-based framework, called DpcbTools, designed to provide a set of functions that fill this gap. It includes a set of efficient data communication functions based on message-passing, thus providing, when a low latency network such as Myrinet is available, higher throughputs and lower latencies than standard solutions used by Java. DpcbTools also includes routines for the launching, monitoring and management of Java applications on several computing nodes by making use of JMX to communicate with remote Java VMs. The Gaia Data Processing and Analysis Consortium (DPAC) is a real case where scientific data from the ESA Gaia astrometric satellite will be entirely processed using Java. In this paper we describe the main elements of DPAC and its usage of the DpcbTools framework. We also assess the usefulness and performance of DpcbTools through its performance evaluation and the analysis of its impact on some DPAC systems deployed in the MareNostrum supercomputer (Barcelona Supercomputing Center).

ParCAT: A Parallel Climate Analysis Toolkit

NASA Astrophysics Data System (ADS)

Haugen, B.; Smith, B.; Steed, C.; Ricciuto, D. M.; Thornton, P. E.; Shipman, G.

2012-12-01

Climate science has employed increasingly complex models and simulations to analyze the past and predict the future of our climate. The size and dimensionality of climate simulation data has been growing with the complexity of the models. This growth in data is creating a widening gap between the data being produced and the tools necessary to analyze large, high dimensional data sets. With single run data sets increasing into 10's, 100's and even 1000's of gigabytes, parallel computing tools are becoming a necessity in order to analyze and compare climate simulation data. The Parallel Climate Analysis Toolkit (ParCAT) provides basic tools that efficiently use parallel computing techniques to narrow the gap between data set size and analysis tools. ParCAT was created as a collaborative effort between climate scientists and computer scientists in order to provide efficient parallel implementations of the computing tools that are of use to climate scientists. Some of the basic functionalities included in the toolkit are the ability to compute spatio-temporal means and variances, differences between two runs and histograms of the values in a data set. ParCAT is designed to facilitate the "heavy lifting" that is required for large, multidimensional data sets. The toolkit does not focus on performing the final visualizations and presentation of results but rather, reducing large data sets to smaller, more manageable summaries. The output from ParCAT is provided in commonly used file formats (NetCDF, CSV, ASCII) to allow for simple integration with other tools. The toolkit is currently implemented as a command line utility, but will likely also provide a C library for developers interested in tighter software integration. Elements of the toolkit are already being incorporated into projects such as UV-CDAT and CMDX. There is also an effort underway to implement portions of the CCSM Land Model Diagnostics package using ParCAT in conjunction with Python and gnuplot. ParCAT is implemented in C to provide efficient file IO. The file IO operations in the toolkit use the parallel-netcdf library; this enables the code to use the parallel IO capabilities of modern HPC systems. Analysis that currently requires an estimated 12+ hours with the traditional CCSM Land Model Diagnostics Package can now be performed in as little as 30 minutes on a single desktop workstation and a few minutes for relatively small jobs completed on modern HPC systems such as ORNL's Jaguar.

Effective Energy Simulation and Optimal Design of Side-lit Buildings with Venetian Blinds

NASA Astrophysics Data System (ADS)

Cheng, Tian

Venetian blinds are popularly used in buildings to control the amount of incoming daylight for improving visual comfort and reducing heat gains in air-conditioning systems. Studies have shown that the proper design and operation of window systems could result in significant energy savings in both lighting and cooling. However, there is no convenient computer tool that allows effective and efficient optimization of the envelope of side-lit buildings with blinds now. Three computer tools, Adeline, DOE2 and EnergyPlus widely used for the above-mentioned purpose have been experimentally examined in this study. Results indicate that the two former tools give unacceptable accuracy due to unrealistic assumptions adopted while the last one may generate large errors in certain conditions. Moreover, current computer tools have to conduct hourly energy simulations, which are not necessary for life-cycle energy analysis and optimal design, to provide annual cooling loads. This is not computationally efficient, particularly not suitable for optimal designing a building at initial stage because the impacts of many design variations and optional features have to be evaluated. A methodology is therefore developed for efficient and effective thermal and daylighting simulations and optimal design of buildings with blinds. Based on geometric optics and radiosity method, a mathematical model is developed to reasonably simulate the daylighting behaviors of venetian blinds. Indoor illuminance at any reference point can be directly and efficiently computed. They have been validated with both experiments and simulations with Radiance. Validation results show that indoor illuminances computed by the new models agree well with the measured data, and the accuracy provided by them is equivalent to that of Radiance. The computational efficiency of the new models is much higher than that of Radiance as well as EnergyPlus. Two new methods are developed for the thermal simulation of buildings. A fast Fourier transform (FFT) method is presented to avoid the root-searching process in the inverse Laplace transform of multilayered walls. Generalized explicit FFT formulae for calculating the discrete Fourier transform (DFT) are developed for the first time. They can largely facilitate the implementation of FFT. The new method also provides a basis for generating the symbolic response factors. Validation simulations show that it can generate the response factors as accurate as the analytical solutions. The second method is for direct estimation of annual or seasonal cooling loads without the need for tedious hourly energy simulations. It is validated by hourly simulation results with DOE2. Then symbolic long-term cooling load can be created by combining the two methods with thermal network analysis. The symbolic long-term cooling load can keep the design parameters of interest as symbols, which is particularly useful for the optimal design and sensitivity analysis. The methodology is applied to an office building in Hong Kong for the optimal design of building envelope. Design variables such as window-to-wall ratio, building orientation, and glazing optical and thermal properties are included in the study. Results show that the selected design values could significantly impact the energy performance of windows, and the optimal design of side-lit buildings could greatly enhance energy savings. The application example also demonstrates that the developed methodology significantly facilitates the optimal building design and sensitivity analysis, and leads to high computational efficiency.

Changing computing paradigms towards power efficiency

PubMed Central

Klavík, Pavel; Malossi, A. Cristiano I.; Bekas, Costas; Curioni, Alessandro

2014-01-01

Power awareness is fast becoming immensely important in computing, ranging from the traditional high-performance computing applications to the new generation of data centric workloads. In this work, we describe our efforts towards a power-efficient computing paradigm that combines low- and high-precision arithmetic. We showcase our ideas for the widely used kernel of solving systems of linear equations that finds numerous applications in scientific and engineering disciplines as well as in large-scale data analytics, statistics and machine learning. Towards this goal, we developed tools for the seamless power profiling of applications at a fine-grain level. In addition, we verify here previous work on post-FLOPS/W metrics and show that these can shed much more light in the power/energy profile of important applications. PMID:24842033

Optimum spaceborne computer system design by simulation

NASA Technical Reports Server (NTRS)

Williams, T.; Kerner, H.; Weatherbee, J. E.; Taylor, D. S.; Hodges, B.

1973-01-01

A deterministic simulator is described which models the Automatically Reconfigurable Modular Multiprocessor System (ARMMS), a candidate computer system for future manned and unmanned space missions. Its use as a tool to study and determine the minimum computer system configuration necessary to satisfy the on-board computational requirements of a typical mission is presented. The paper describes how the computer system configuration is determined in order to satisfy the data processing demand of the various shuttle booster subsytems. The configuration which is developed as a result of studies with the simulator is optimal with respect to the efficient use of computer system resources.

Target Identification Using Harmonic Wavelet Based ISAR Imaging

NASA Astrophysics Data System (ADS)

Shreyamsha Kumar, B. K.; Prabhakar, B.; Suryanarayana, K.; Thilagavathi, V.; Rajagopal, R.

2006-12-01

A new approach has been proposed to reduce the computations involved in the ISAR imaging, which uses harmonic wavelet-(HW) based time-frequency representation (TFR). Since the HW-based TFR falls into a category of nonparametric time-frequency (T-F) analysis tool, it is computationally efficient compared to parametric T-F analysis tools such as adaptive joint time-frequency transform (AJTFT), adaptive wavelet transform (AWT), and evolutionary AWT (EAWT). Further, the performance of the proposed method of ISAR imaging is compared with the ISAR imaging by other nonparametric T-F analysis tools such as short-time Fourier transform (STFT) and Choi-Williams distribution (CWD). In the ISAR imaging, the use of HW-based TFR provides similar/better results with significant (92%) computational advantage compared to that obtained by CWD. The ISAR images thus obtained are identified using a neural network-based classification scheme with feature set invariant to translation, rotation, and scaling.

Do Computers Improve the Drawing of a Geometrical Figure for 10 Year-Old Children?

ERIC Educational Resources Information Center

Martin, Perrine; Velay, Jean-Luc

2012-01-01

Nowadays, computer aided design (CAD) is widely used by designers. Would children learn to draw more easily and more efficiently if they were taught with computerised tools? To answer this question, we made an experiment designed to compare two methods for children to do the same drawing: the classical "pen and paper" method and a CAD…

Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

NASA Technical Reports Server (NTRS)

Liu, Yi; Anusonti-Inthra, Phuriwat; Diskin, Boris

2011-01-01

A physics-based, systematically coupled, multidisciplinary prediction tool (MUTE) for rotorcraft noise was developed and validated with a wide range of flight configurations and conditions. MUTE is an aggregation of multidisciplinary computational tools that accurately and efficiently model the physics of the source of rotorcraft noise, and predict the noise at far-field observer locations. It uses systematic coupling approaches among multiple disciplines including Computational Fluid Dynamics (CFD), Computational Structural Dynamics (CSD), and high fidelity acoustics. Within MUTE, advanced high-order CFD tools are used around the rotor blade to predict the transonic flow (shock wave) effects, which generate the high-speed impulsive noise. Predictions of the blade-vortex interaction noise in low speed flight are also improved by using the Particle Vortex Transport Method (PVTM), which preserves the wake flow details required for blade/wake and fuselage/wake interactions. The accuracy of the source noise prediction is further improved by utilizing a coupling approach between CFD and CSD, so that the effects of key structural dynamics, elastic blade deformations, and trim solutions are correctly represented in the analysis. The blade loading information and/or the flow field parameters around the rotor blade predicted by the CFD/CSD coupling approach are used to predict the acoustic signatures at far-field observer locations with a high-fidelity noise propagation code (WOPWOP3). The predicted results from the MUTE tool for rotor blade aerodynamic loading and far-field acoustic signatures are compared and validated with a variation of experimental data sets, such as UH60-A data, DNW test data and HART II test data.

Enhancements in medicine by integrating content based image retrieval in computer-aided diagnosis

NASA Astrophysics Data System (ADS)

Aggarwal, Preeti; Sardana, H. K.

2010-02-01

Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging and diagnostic radiology. With cad, radiologists use the computer output as a "second opinion" and make the final decisions. Retrieving images is a useful tool to help radiologist to check medical image and diagnosis. The impact of contentbased access to medical images is frequently reported but existing systems are designed for only a particular context of diagnosis. The challenge in medical informatics is to develop tools for analyzing the content of medical images and to represent them in a way that can be efficiently searched and compared by the physicians. CAD is a concept established by taking into account equally the roles of physicians and computers. To build a successful computer aided diagnostic system, all the relevant technologies, especially retrieval need to be integrated in such a manner that should provide effective and efficient pre-diagnosed cases with proven pathology for the current case at the right time. In this paper, it is suggested that integration of content-based image retrieval (CBIR) in cad can bring enormous results in medicine especially in diagnosis. This approach is also compared with other approaches by highlighting its advantages over those approaches.

Efficiently modeling neural networks on massively parallel computers

NASA Technical Reports Server (NTRS)

Farber, Robert M.

1993-01-01

Neural networks are a very useful tool for analyzing and modeling complex real world systems. Applying neural network simulations to real world problems generally involves large amounts of data and massive amounts of computation. To efficiently handle the computational requirements of large problems, we have implemented at Los Alamos a highly efficient neural network compiler for serial computers, vector computers, vector parallel computers, and fine grain SIMD computers such as the CM-2 connection machine. This paper describes the mapping used by the compiler to implement feed-forward backpropagation neural networks for a SIMD (Single Instruction Multiple Data) architecture parallel computer. Thinking Machines Corporation has benchmarked our code at 1.3 billion interconnects per second (approximately 3 gigaflops) on a 64,000 processor CM-2 connection machine (Singer 1990). This mapping is applicable to other SIMD computers and can be implemented on MIMD computers such as the CM-5 connection machine. Our mapping has virtually no communications overhead with the exception of the communications required for a global summation across the processors (which has a sub-linear runtime growth on the order of O(log(number of processors)). We can efficiently model very large neural networks which have many neurons and interconnects and our mapping can extend to arbitrarily large networks (within memory limitations) by merging the memory space of separate processors with fast adjacent processor interprocessor communications. This paper will consider the simulation of only feed forward neural network although this method is extendable to recurrent networks.

Information Power Grid (IPG) Tutorial 2003

NASA Technical Reports Server (NTRS)

Meyers, George

2003-01-01

For NASA and the general community today Grid middleware: a) provides tools to access/use data sources (databases, instruments, ...); b) provides tools to access computing (unique and generic); c) Is an enabler of large scale collaboration. Dynamically responding to needs is a key selling point of a grid. Independent resources can be joined as appropriate to solve a problem. Provide tools to enable the building of a frameworks for application. Provide value added service to the NASA user base for utilizing resources on the grid in new and more efficient ways. Provides tools for development of Frameworks.

Computational Screening of 2D Materials for Photocatalysis.

PubMed

Singh, Arunima K; Mathew, Kiran; Zhuang, Houlong L; Hennig, Richard G

2015-03-19

Two-dimensional (2D) materials exhibit a range of extraordinary electronic, optical, and mechanical properties different from their bulk counterparts with potential applications for 2D materials emerging in energy storage and conversion technologies. In this Perspective, we summarize the recent developments in the field of solar water splitting using 2D materials and review a computational screening approach to rapidly and efficiently discover more 2D materials that possess properties suitable for solar water splitting. Computational tools based on density-functional theory can predict the intrinsic properties of potential photocatalyst such as their electronic properties, optical absorbance, and solubility in aqueous solutions. Computational tools enable the exploration of possible routes to enhance the photocatalytic activity of 2D materials by use of mechanical strain, bias potential, doping, and pH. We discuss future research directions and needed method developments for the computational design and optimization of 2D materials for photocatalysis.

High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis.

PubMed

Simonyan, Vahan; Mazumder, Raja

2014-09-30

The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis.

High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis

PubMed Central

Simonyan, Vahan; Mazumder, Raja

2014-01-01

The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis. PMID:25271953

Improving Cognitive Abilities and e-Inclusion in Children with Cerebral Palsy

NASA Astrophysics Data System (ADS)

Martinengo, Chiara; Curatelli, Francesco

Besides overcoming the motor barriers for accessing to computers and Internet, ICT tools can provide a very useful, and often necessary, support for the cognitive development of motor-impaired children with cerebral palsy. In fact, software tools for computation and communication allow teachers to put into effect, in a more complete and efficient way, the learning methods and the educational plans studied for the child. In the present article, after a brief analysis of the general objectives to be pursued for favouring the learning for children with cerebral palsy, we take account of some specific difficulties in the logical-linguistic and logical-mathematical fields, and we show how they can be overcome using general ICT tools and specifically implemented software programs.

Visualization and Interaction in Research, Teaching, and Scientific Communication

NASA Astrophysics Data System (ADS)

Ammon, C. J.

2017-12-01

Modern computing provides many tools for exploring observations, numerical calculations, and theoretical relationships. The number of options is, in fact, almost overwhelming. But the choices provide those with modest programming skills opportunities to create unique views of scientific information and to develop deeper insights into their data, their computations, and the underlying theoretical data-model relationships. I present simple examples of using animation and human-computer interaction to explore scientific data and scientific-analysis approaches. I illustrate how valuable a little programming ability can free scientists from the constraints of existing tools and can facilitate the development of deeper appreciation data and models. I present examples from a suite of programming languages ranging from C to JavaScript including the Wolfram Language. JavaScript is valuable for sharing tools and insight (hopefully) with others because it is integrated into one of the most powerful communication tools in human history, the web browser. Although too much of that power is often spent on distracting advertisements, the underlying computation and graphics engines are efficient, flexible, and almost universally available in desktop and mobile computing platforms. Many are working to fulfill the browser's potential to become the most effective tool for interactive study. Open-source frameworks for visualizing everything from algorithms to data are available, but advance rapidly. One strategy for dealing with swiftly changing tools is to adopt common, open data formats that are easily adapted (often by framework or tool developers). I illustrate the use of animation and interaction in research and teaching with examples from earthquake seismology.

Cost-Effective Cloud Computing: A Case Study Using the Comparative Genomics Tool, Roundup

PubMed Central

Kudtarkar, Parul; DeLuca, Todd F.; Fusaro, Vincent A.; Tonellato, Peter J.; Wall, Dennis P.

2010-01-01

Background Comparative genomics resources, such as ortholog detection tools and repositories are rapidly increasing in scale and complexity. Cloud computing is an emerging technological paradigm that enables researchers to dynamically build a dedicated virtual cluster and may represent a valuable alternative for large computational tools in bioinformatics. In the present manuscript, we optimize the computation of a large-scale comparative genomics resource—Roundup—using cloud computing, describe the proper operating principles required to achieve computational efficiency on the cloud, and detail important procedures for improving cost-effectiveness to ensure maximal computation at minimal costs. Methods Utilizing the comparative genomics tool, Roundup, as a case study, we computed orthologs among 902 fully sequenced genomes on Amazon’s Elastic Compute Cloud. For managing the ortholog processes, we designed a strategy to deploy the web service, Elastic MapReduce, and maximize the use of the cloud while simultaneously minimizing costs. Specifically, we created a model to estimate cloud runtime based on the size and complexity of the genomes being compared that determines in advance the optimal order of the jobs to be submitted. Results We computed orthologous relationships for 245,323 genome-to-genome comparisons on Amazon’s computing cloud, a computation that required just over 200 hours and cost $8,000 USD, at least 40% less than expected under a strategy in which genome comparisons were submitted to the cloud randomly with respect to runtime. Our cost savings projections were based on a model that not only demonstrates the optimal strategy for deploying RSD to the cloud, but also finds the optimal cluster size to minimize waste and maximize usage. Our cost-reduction model is readily adaptable for other comparative genomics tools and potentially of significant benefit to labs seeking to take advantage of the cloud as an alternative to local computing infrastructure. PMID:21258651

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

Kitanidis, Peter

As large-scale, commercial storage projects become operational, the problem of utilizing information from diverse sources becomes more critically important. In this project, we developed, tested, and applied an advanced joint data inversion system for CO 2 storage modeling with large data sets for use in site characterization and real-time monitoring. Emphasis was on the development of advanced and efficient computational algorithms for joint inversion of hydro-geophysical data, coupled with state-of-the-art forward process simulations. The developed system consists of (1) inversion tools using characterization data, such as 3D seismic survey (amplitude images), borehole log and core data, as well as hydraulic,more » tracer and thermal tests before CO 2 injection, (2) joint inversion tools for updating the geologic model with the distribution of rock properties, thus reducing uncertainty, using hydro-geophysical monitoring data, and (3) highly efficient algorithms for directly solving the dense or sparse linear algebra systems derived from the joint inversion. The system combines methods from stochastic analysis, fast linear algebra, and high performance computing. The developed joint inversion tools have been tested through synthetic CO 2 storage examples.« less

IDEAL: Images Across Domains, Experiments, Algorithms and Learning

NASA Astrophysics Data System (ADS)

Ushizima, Daniela M.; Bale, Hrishikesh A.; Bethel, E. Wes; Ercius, Peter; Helms, Brett A.; Krishnan, Harinarayan; Grinberg, Lea T.; Haranczyk, Maciej; Macdowell, Alastair A.; Odziomek, Katarzyna; Parkinson, Dilworth Y.; Perciano, Talita; Ritchie, Robert O.; Yang, Chao

2016-11-01

Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this paper, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds.

Exponential Methods for the Time Integration of Schroedinger Equation

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

Cano, B.; Gonzalez-Pachon, A.

2010-09-30

We consider exponential methods of second order in time in order to integrate the cubic nonlinear Schroedinger equation. We are interested in taking profit of the special structure of this equation. Therefore, we look at symmetry, symplecticity and approximation of invariants of the proposed methods. That will allow to integrate till long times with reasonable accuracy. Computational efficiency is also our aim. Therefore, we make numerical computations in order to compare the methods considered and so as to conclude that explicit Lawson schemes projected on the norm of the solution are an efficient tool to integrate this equation.

Using NERSC High-Performance Computing (HPC) systems for high-energy nuclear physics applications with ALICE

NASA Astrophysics Data System (ADS)

Fasel, Markus

2016-10-01

High-Performance Computing Systems are powerful tools tailored to support large- scale applications that rely on low-latency inter-process communications to run efficiently. By design, these systems often impose constraints on application workflows, such as limited external network connectivity and whole node scheduling, that make more general-purpose computing tasks, such as those commonly found in high-energy nuclear physics applications, more difficult to carry out. In this work, we present a tool designed to simplify access to such complicated environments by handling the common tasks of job submission, software management, and local data management, in a framework that is easily adaptable to the specific requirements of various computing systems. The tool, initially constructed to process stand-alone ALICE simulations for detector and software development, was successfully deployed on the NERSC computing systems, Carver, Hopper and Edison, and is being configured to provide access to the next generation NERSC system, Cori. In this report, we describe the tool and discuss our experience running ALICE applications on NERSC HPC systems. The discussion will include our initial benchmarks of Cori compared to other systems and our attempts to leverage the new capabilities offered with Cori to support data-intensive applications, with a future goal of full integration of such systems into ALICE grid operations.

The challenge of big data in public health: an opportunity for visual analytics.

PubMed

Ola, Oluwakemi; Sedig, Kamran

2014-01-01

Public health (PH) data can generally be characterized as big data. The efficient and effective use of this data determines the extent to which PH stakeholders can sufficiently address societal health concerns as they engage in a variety of work activities. As stakeholders interact with data, they engage in various cognitive activities such as analytical reasoning, decision-making, interpreting, and problem solving. Performing these activities with big data is a challenge for the unaided mind as stakeholders encounter obstacles relating to the data's volume, variety, velocity, and veracity. Such being the case, computer-based information tools are needed to support PH stakeholders. Unfortunately, while existing computational tools are beneficial in addressing certain work activities, they fall short in supporting cognitive activities that involve working with large, heterogeneous, and complex bodies of data. This paper presents visual analytics (VA) tools, a nascent category of computational tools that integrate data analytics with interactive visualizations, to facilitate the performance of cognitive activities involving big data. Historically, PH has lagged behind other sectors in embracing new computational technology. In this paper, we discuss the role that VA tools can play in addressing the challenges presented by big data. In doing so, we demonstrate the potential benefit of incorporating VA tools into PH practice, in addition to highlighting the need for further systematic and focused research.

The Challenge of Big Data in Public Health: An Opportunity for Visual Analytics

PubMed Central

Ola, Oluwakemi; Sedig, Kamran

2014-01-01

Public health (PH) data can generally be characterized as big data. The efficient and effective use of this data determines the extent to which PH stakeholders can sufficiently address societal health concerns as they engage in a variety of work activities. As stakeholders interact with data, they engage in various cognitive activities such as analytical reasoning, decision-making, interpreting, and problem solving. Performing these activities with big data is a challenge for the unaided mind as stakeholders encounter obstacles relating to the data’s volume, variety, velocity, and veracity. Such being the case, computer-based information tools are needed to support PH stakeholders. Unfortunately, while existing computational tools are beneficial in addressing certain work activities, they fall short in supporting cognitive activities that involve working with large, heterogeneous, and complex bodies of data. This paper presents visual analytics (VA) tools, a nascent category of computational tools that integrate data analytics with interactive visualizations, to facilitate the performance of cognitive activities involving big data. Historically, PH has lagged behind other sectors in embracing new computational technology. In this paper, we discuss the role that VA tools can play in addressing the challenges presented by big data. In doing so, we demonstrate the potential benefit of incorporating VA tools into PH practice, in addition to highlighting the need for further systematic and focused research. PMID:24678376

Data-driven Applications for the Sun-Earth System

NASA Astrophysics Data System (ADS)

Kondrashov, D. A.

2016-12-01

Advances in observational and data mining techniques allow extracting information from the large volume of Sun-Earth observational data that can be assimilated into first principles physical models. However, equations governing Sun-Earth phenomena are typically nonlinear, complex, and high-dimensional. The high computational demand of solving the full governing equations over a large range of scales precludes the use of a variety of useful assimilative tools that rely on applied mathematical and statistical techniques for quantifying uncertainty and predictability. Effective use of such tools requires the development of computationally efficient methods to facilitate fusion of data with models. This presentation will provide an overview of various existing as well as newly developed data-driven techniques adopted from atmospheric and oceanic sciences that proved to be useful for space physics applications, such as computationally efficient implementation of Kalman Filter in radiation belts modeling, solar wind gap-filling by Singular Spectrum Analysis, and low-rank procedure for assimilation of low-altitude ionospheric magnetic perturbations into the Lyon-Fedder-Mobarry (LFM) global magnetospheric model. Reduced-order non-Markovian inverse modeling and novel data-adaptive decompositions of Sun-Earth datasets will be also demonstrated.

Using computer graphics to enhance astronaut and systems safety

NASA Technical Reports Server (NTRS)

Brown, J. W.

1985-01-01

Computer graphics is being employed at the NASA Johnson Space Center as a tool to perform rapid, efficient and economical analyses for man-machine integration, flight operations development and systems engineering. The Operator Station Design System (OSDS), a computer-based facility featuring a highly flexible and versatile interactive software package, PLAID, is described. This unique evaluation tool, with its expanding data base of Space Shuttle elements, various payloads, experiments, crew equipment and man models, supports a multitude of technical evaluations, including spacecraft and workstation layout, definition of astronaut visual access, flight techniques development, cargo integration and crew training. As OSDS is being applied to the Space Shuttle, Orbiter payloads (including the European Space Agency's Spacelab) and future space vehicles and stations, astronaut and systems safety are being enhanced. Typical OSDS examples are presented. By performing physical and operational evaluations during early conceptual phases. supporting systems verification for flight readiness, and applying its capabilities to real-time mission support, the OSDS provides the wherewithal to satisfy a growing need of the current and future space programs for efficient, economical analyses.

EggLib: processing, analysis and simulation tools for population genetics and genomics

PubMed Central

2012-01-01

Background With the considerable growth of available nucleotide sequence data over the last decade, integrated and flexible analytical tools have become a necessity. In particular, in the field of population genetics, there is a strong need for automated and reliable procedures to conduct repeatable and rapid polymorphism analyses, coalescent simulations, data manipulation and estimation of demographic parameters under a variety of scenarios. Results In this context, we present EggLib (Evolutionary Genetics and Genomics Library), a flexible and powerful C++/Python software package providing efficient and easy to use computational tools for sequence data management and extensive population genetic analyses on nucleotide sequence data. EggLib is a multifaceted project involving several integrated modules: an underlying computationally efficient C++ library (which can be used independently in pure C++ applications); two C++ programs; a Python package providing, among other features, a high level Python interface to the C++ library; and the egglib script which provides direct access to pre-programmed Python applications. Conclusions EggLib has been designed aiming to be both efficient and easy to use. A wide array of methods are implemented, including file format conversion, sequence alignment edition, coalescent simulations, neutrality tests and estimation of demographic parameters by Approximate Bayesian Computation (ABC). Classes implementing different demographic scenarios for ABC analyses can easily be developed by the user and included to the package. EggLib source code is distributed freely under the GNU General Public License (GPL) from its website http://egglib.sourceforge.net/ where a full documentation and a manual can also be found and downloaded. PMID:22494792

EggLib: processing, analysis and simulation tools for population genetics and genomics.

PubMed

De Mita, Stéphane; Siol, Mathieu

2012-04-11

With the considerable growth of available nucleotide sequence data over the last decade, integrated and flexible analytical tools have become a necessity. In particular, in the field of population genetics, there is a strong need for automated and reliable procedures to conduct repeatable and rapid polymorphism analyses, coalescent simulations, data manipulation and estimation of demographic parameters under a variety of scenarios. In this context, we present EggLib (Evolutionary Genetics and Genomics Library), a flexible and powerful C++/Python software package providing efficient and easy to use computational tools for sequence data management and extensive population genetic analyses on nucleotide sequence data. EggLib is a multifaceted project involving several integrated modules: an underlying computationally efficient C++ library (which can be used independently in pure C++ applications); two C++ programs; a Python package providing, among other features, a high level Python interface to the C++ library; and the egglib script which provides direct access to pre-programmed Python applications. EggLib has been designed aiming to be both efficient and easy to use. A wide array of methods are implemented, including file format conversion, sequence alignment edition, coalescent simulations, neutrality tests and estimation of demographic parameters by Approximate Bayesian Computation (ABC). Classes implementing different demographic scenarios for ABC analyses can easily be developed by the user and included to the package. EggLib source code is distributed freely under the GNU General Public License (GPL) from its website http://egglib.sourceforge.net/ where a full documentation and a manual can also be found and downloaded.

A Guide to Computational Tools and Design Strategies for Genome Editing Experiments in Zebrafish Using CRISPR/Cas9.

PubMed

Prykhozhij, Sergey V; Rajan, Vinothkumar; Berman, Jason N

2016-02-01

The development of clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 technology for mainstream biotechnological use based on its discovery as an adaptive immune mechanism in bacteria has dramatically improved the ability of molecular biologists to modify genomes of model organisms. The zebrafish is highly amenable to applications of CRISPR/Cas9 for mutation generation and a variety of DNA insertions. Cas9 protein in complex with a guide RNA molecule recognizes where to cut the homologous DNA based on a short stretch of DNA termed the protospacer-adjacent motif (PAM). Rapid and efficient identification of target sites immediately preceding PAM sites, quantification of genomic occurrences of similar (off target) sites and predictions of cutting efficiency are some of the features where computational tools play critical roles in CRISPR/Cas9 applications. Given the rapid advent and development of this technology, it can be a challenge for researchers to remain up to date with all of the important technological developments in this field. We have contributed to the armamentarium of CRISPR/Cas9 bioinformatics tools and trained other researchers in the use of appropriate computational programs to develop suitable experimental strategies. Here we provide an in-depth guide on how to use CRISPR/Cas9 and other relevant computational tools at each step of a host of genome editing experimental strategies. We also provide detailed conceptual outlines of the steps involved in the design and execution of CRISPR/Cas9-based experimental strategies, such as generation of frameshift mutations, larger chromosomal deletions and inversions, homology-independent insertion of gene cassettes and homology-based knock-in of defined point mutations and larger gene constructs.

AMAS: a fast tool for alignment manipulation and computing of summary statistics.

PubMed

Borowiec, Marek L

2016-01-01

The amount of data used in phylogenetics has grown explosively in the recent years and many phylogenies are inferred with hundreds or even thousands of loci and many taxa. These modern phylogenomic studies often entail separate analyses of each of the loci in addition to multiple analyses of subsets of genes or concatenated sequences. Computationally efficient tools for handling and computing properties of thousands of single-locus or large concatenated alignments are needed. Here I present AMAS (Alignment Manipulation And Summary), a tool that can be used either as a stand-alone command-line utility or as a Python package. AMAS works on amino acid and nucleotide alignments and combines capabilities of sequence manipulation with a function that calculates basic statistics. The manipulation functions include conversions among popular formats, concatenation, extracting sites and splitting according to a pre-defined partitioning scheme, creation of replicate data sets, and removal of taxa. The statistics calculated include the number of taxa, alignment length, total count of matrix cells, overall number of undetermined characters, percent of missing data, AT and GC contents (for DNA alignments), count and proportion of variable sites, count and proportion of parsimony informative sites, and counts of all characters relevant for a nucleotide or amino acid alphabet. AMAS is particularly suitable for very large alignments with hundreds of taxa and thousands of loci. It is computationally efficient, utilizes parallel processing, and performs better at concatenation than other popular tools. AMAS is a Python 3 program that relies solely on Python's core modules and needs no additional dependencies. AMAS source code and manual can be downloaded from http://github.com/marekborowiec/AMAS/ under GNU General Public License.

Massively parallel multicanonical simulations

NASA Astrophysics Data System (ADS)

Gross, Jonathan; Zierenberg, Johannes; Weigel, Martin; Janke, Wolfhard

2018-03-01

Generalized-ensemble Monte Carlo simulations such as the multicanonical method and similar techniques are among the most efficient approaches for simulations of systems undergoing discontinuous phase transitions or with rugged free-energy landscapes. As Markov chain methods, they are inherently serial computationally. It was demonstrated recently, however, that a combination of independent simulations that communicate weight updates at variable intervals allows for the efficient utilization of parallel computational resources for multicanonical simulations. Implementing this approach for the many-thread architecture provided by current generations of graphics processing units (GPUs), we show how it can be efficiently employed with of the order of 104 parallel walkers and beyond, thus constituting a versatile tool for Monte Carlo simulations in the era of massively parallel computing. We provide the fully documented source code for the approach applied to the paradigmatic example of the two-dimensional Ising model as starting point and reference for practitioners in the field.

LIVING SHORES GALLERY MX964015

EPA Science Inventory

An interactive computer kiosk will allow the Texas State Aquarium to deliver a considerable amount of information in an efficient and highly effective manner. Touch screen interactives have proven to be excellent teaching tools in the Aquarium's Jellies: Floating Phantoms galler...

Computer Aided Design of Computer Generated Holograms for electron beam fabrication

NASA Technical Reports Server (NTRS)

Urquhart, Kristopher S.; Lee, Sing H.; Guest, Clark C.; Feldman, Michael R.; Farhoosh, Hamid

1989-01-01

Computer Aided Design (CAD) systems that have been developed for electrical and mechanical design tasks are also effective tools for the process of designing Computer Generated Holograms (CGHs), particularly when these holograms are to be fabricated using electron beam lithography. CAD workstations provide efficient and convenient means of computing, storing, displaying, and preparing for fabrication many of the features that are common to CGH designs. Experience gained in the process of designing CGHs with various types of encoding methods is presented. Suggestions are made so that future workstations may further accommodate the CGH design process.

Advanced Dynamically Adaptive Algorithms for Stochastic Simulations on Extreme Scales

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

Xiu, Dongbin

2017-03-03

The focus of the project is the development of mathematical methods and high-performance computational tools for stochastic simulations, with a particular emphasis on computations on extreme scales. The core of the project revolves around the design of highly efficient and scalable numerical algorithms that can adaptively and accurately, in high dimensional spaces, resolve stochastic problems with limited smoothness, even containing discontinuities.

Efficient computation of electrograms and ECGs in human whole heart simulations using a reaction-eikonal model.

PubMed

Neic, Aurel; Campos, Fernando O; Prassl, Anton J; Niederer, Steven A; Bishop, Martin J; Vigmond, Edward J; Plank, Gernot

2017-10-01

Anatomically accurate and biophysically detailed bidomain models of the human heart have proven a powerful tool for gaining quantitative insight into the links between electrical sources in the myocardium and the concomitant current flow in the surrounding medium as they represent their relationship mechanistically based on first principles. Such models are increasingly considered as a clinical research tool with the perspective of being used, ultimately, as a complementary diagnostic modality. An important prerequisite in many clinical modeling applications is the ability of models to faithfully replicate potential maps and electrograms recorded from a given patient. However, while the personalization of electrophysiology models based on the gold standard bidomain formulation is in principle feasible, the associated computational expenses are significant, rendering their use incompatible with clinical time frames. In this study we report on the development of a novel computationally efficient reaction-eikonal (R-E) model for modeling extracellular potential maps and electrograms. Using a biventricular human electrophysiology model, which incorporates a topologically realistic His-Purkinje system (HPS), we demonstrate by comparing against a high-resolution reaction-diffusion (R-D) bidomain model that the R-E model predicts extracellular potential fields, electrograms as well as ECGs at the body surface with high fidelity and offers vast computational savings greater than three orders of magnitude. Due to their efficiency R-E models are ideally suitable for forward simulations in clinical modeling studies which attempt to personalize electrophysiological model features.

Electromagnetomechanical elastodynamic model for Lamb wave damage quantification in composites

NASA Astrophysics Data System (ADS)

Borkowski, Luke; Chattopadhyay, Aditi

2014-03-01

Physics-based wave propagation computational models play a key role in structural health monitoring (SHM) and the development of improved damage quantification methodologies. Guided waves (GWs), such as Lamb waves, provide the capability to monitor large plate-like aerospace structures with limited actuators and sensors and are sensitive to small scale damage; however due to the complex nature of GWs, accurate and efficient computation tools are necessary to investigate the mechanisms responsible for dispersion, coupling, and interaction with damage. In this paper, the local interaction simulation approach (LISA) coupled with the sharp interface model (SIM) solution methodology is used to solve the fully coupled electro-magneto-mechanical elastodynamic equations for the piezoelectric and piezomagnetic actuation and sensing of GWs in fiber reinforced composite material systems. The final framework provides the full three-dimensional displacement as well as electrical and magnetic potential fields for arbitrary plate and transducer geometries and excitation waveform and frequency. The model is validated experimentally and proven computationally efficient for a laminated composite plate. Studies are performed with surface bonded piezoelectric and embedded piezomagnetic sensors to gain insight into the physics of experimental techniques used for SHM. The symmetric collocation of piezoelectric actuators is modeled to demonstrate mode suppression in laminated composites for the purpose of damage detection. The effect of delamination and damage (i.e., matrix cracking) on the GW propagation is demonstrated and quantified. The developed model provides a valuable tool for the improvement of SHM techniques due to its proven accuracy and computational efficiency.

Efficient computation of electrograms and ECGs in human whole heart simulations using a reaction-eikonal model

NASA Astrophysics Data System (ADS)

Neic, Aurel; Campos, Fernando O.; Prassl, Anton J.; Niederer, Steven A.; Bishop, Martin J.; Vigmond, Edward J.; Plank, Gernot

2017-10-01

Anatomically accurate and biophysically detailed bidomain models of the human heart have proven a powerful tool for gaining quantitative insight into the links between electrical sources in the myocardium and the concomitant current flow in the surrounding medium as they represent their relationship mechanistically based on first principles. Such models are increasingly considered as a clinical research tool with the perspective of being used, ultimately, as a complementary diagnostic modality. An important prerequisite in many clinical modeling applications is the ability of models to faithfully replicate potential maps and electrograms recorded from a given patient. However, while the personalization of electrophysiology models based on the gold standard bidomain formulation is in principle feasible, the associated computational expenses are significant, rendering their use incompatible with clinical time frames. In this study we report on the development of a novel computationally efficient reaction-eikonal (R-E) model for modeling extracellular potential maps and electrograms. Using a biventricular human electrophysiology model, which incorporates a topologically realistic His-Purkinje system (HPS), we demonstrate by comparing against a high-resolution reaction-diffusion (R-D) bidomain model that the R-E model predicts extracellular potential fields, electrograms as well as ECGs at the body surface with high fidelity and offers vast computational savings greater than three orders of magnitude. Due to their efficiency R-E models are ideally suitable for forward simulations in clinical modeling studies which attempt to personalize electrophysiological model features.

Efficient matrix approach to optical wave propagation and Linear Canonical Transforms.

PubMed

Shakir, Sami A; Fried, David L; Pease, Edwin A; Brennan, Terry J; Dolash, Thomas M

2015-10-05

The Fresnel diffraction integral form of optical wave propagation and the more general Linear Canonical Transforms (LCT) are cast into a matrix transformation form. Taking advantage of recent efficient matrix multiply algorithms, this approach promises an efficient computational and analytical tool that is competitive with FFT based methods but offers better behavior in terms of aliasing, transparent boundary condition, and flexibility in number of sampling points and computational window sizes of the input and output planes being independent. This flexibility makes the method significantly faster than FFT based propagators when only a single point, as in Strehl metrics, or a limited number of points, as in power-in-the-bucket metrics, are needed in the output observation plane.

Changing computing paradigms towards power efficiency.

PubMed

Klavík, Pavel; Malossi, A Cristiano I; Bekas, Costas; Curioni, Alessandro

2014-06-28

Power awareness is fast becoming immensely important in computing, ranging from the traditional high-performance computing applications to the new generation of data centric workloads. In this work, we describe our efforts towards a power-efficient computing paradigm that combines low- and high-precision arithmetic. We showcase our ideas for the widely used kernel of solving systems of linear equations that finds numerous applications in scientific and engineering disciplines as well as in large-scale data analytics, statistics and machine learning. Towards this goal, we developed tools for the seamless power profiling of applications at a fine-grain level. In addition, we verify here previous work on post-FLOPS/W metrics and show that these can shed much more light in the power/energy profile of important applications. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

A meta-analysis of pedagogical tools used in introductory programming courses

NASA Astrophysics Data System (ADS)

Trees, Frances P.

Programming is recognized as being challenging for teachers to teach and difficult for students to learn. For decades, computer science educators have looked at innovative approaches by creating pedagogical software tools that attempt to facilitate both the teaching of and the learning of programming. This dissertation investigates the motivations for the integration of pedagogical tools in introductory programming courses and the characteristics that are perceived to contribute to the effectiveness of these tools. The study employs three research stages that examine the tool characteristics and their use. The first stage surveys teachers who use pedagogical tools in an introductory programming course. The second interviews teachers to explore the survey results in more detail and to add greater depth into the choice and use of pedagogical tools in the introductory programming class. The third interviews tool developers to provide an explanatory insight of the tool and the motivation for its creation. The results indicate that the pedagogical tools perceived to be effective share common characteristics: They provide an environment that is manageable, flexible and visual; they provide for active engagement in learning activities and support programming in small pieces; they allow for an easy transition to subsequent courses and more robust environments; they provide technical support and resource materials. The results of this study also indicate that recommendations from other computer science educators have a strong impact on a teacher's initial tool choice for an introductory programming course. This study informs present and future tool developers of the characteristics that the teachers perceive to contribute to the effectiveness of a pedagogical tool and how to present their tools to encourage a more efficient and more effective widespread adoption of the tool into the teacher's curriculum. The teachers involved in this study are actively involved in the computer science education community. The results of this study, based on the perceptions of these computer science educators, provide guidance to those educators choosing to introduce a new pedagogical tool into their programming course.

A General-purpose Framework for Parallel Processing of Large-scale LiDAR Data

NASA Astrophysics Data System (ADS)

Li, Z.; Hodgson, M.; Li, W.

2016-12-01

Light detection and ranging (LiDAR) technologies have proven efficiency to quickly obtain very detailed Earth surface data for a large spatial extent. Such data is important for scientific discoveries such as Earth and ecological sciences and natural disasters and environmental applications. However, handling LiDAR data poses grand geoprocessing challenges due to data intensity and computational intensity. Previous studies received notable success on parallel processing of LiDAR data to these challenges. However, these studies either relied on high performance computers and specialized hardware (GPUs) or focused mostly on finding customized solutions for some specific algorithms. We developed a general-purpose scalable framework coupled with sophisticated data decomposition and parallelization strategy to efficiently handle big LiDAR data. Specifically, 1) a tile-based spatial index is proposed to manage big LiDAR data in the scalable and fault-tolerable Hadoop distributed file system, 2) two spatial decomposition techniques are developed to enable efficient parallelization of different types of LiDAR processing tasks, and 3) by coupling existing LiDAR processing tools with Hadoop, this framework is able to conduct a variety of LiDAR data processing tasks in parallel in a highly scalable distributed computing environment. The performance and scalability of the framework is evaluated with a series of experiments conducted on a real LiDAR dataset using a proof-of-concept prototype system. The results show that the proposed framework 1) is able to handle massive LiDAR data more efficiently than standalone tools; and 2) provides almost linear scalability in terms of either increased workload (data volume) or increased computing nodes with both spatial decomposition strategies. We believe that the proposed framework provides valuable references on developing a collaborative cyberinfrastructure for processing big earth science data in a highly scalable environment.

Acceleration of FDTD mode solver by high-performance computing techniques.

PubMed

Han, Lin; Xi, Yanping; Huang, Wei-Ping

2010-06-21

A two-dimensional (2D) compact finite-difference time-domain (FDTD) mode solver is developed based on wave equation formalism in combination with the matrix pencil method (MPM). The method is validated for calculation of both real guided and complex leaky modes of typical optical waveguides against the bench-mark finite-difference (FD) eigen mode solver. By taking advantage of the inherent parallel nature of the FDTD algorithm, the mode solver is implemented on graphics processing units (GPUs) using the compute unified device architecture (CUDA). It is demonstrated that the high-performance computing technique leads to significant acceleration of the FDTD mode solver with more than 30 times improvement in computational efficiency in comparison with the conventional FDTD mode solver running on CPU of a standard desktop computer. The computational efficiency of the accelerated FDTD method is in the same order of magnitude of the standard finite-difference eigen mode solver and yet require much less memory (e.g., less than 10%). Therefore, the new method may serve as an efficient, accurate and robust tool for mode calculation of optical waveguides even when the conventional eigen value mode solvers are no longer applicable due to memory limitation.

Computer literacy for life sciences: helping the digital-era biology undergraduates face today's research.

PubMed

Smolinski, Tomasz G

2010-01-01

Computer literacy plays a critical role in today's life sciences research. Without the ability to use computers to efficiently manipulate and analyze large amounts of data resulting from biological experiments and simulations, many of the pressing questions in the life sciences could not be answered. Today's undergraduates, despite the ubiquity of computers in their lives, seem to be largely unfamiliar with how computers are being used to pursue and answer such questions. This article describes an innovative undergraduate-level course, titled Computer Literacy for Life Sciences, that aims to teach students the basics of a computerized scientific research pursuit. The purpose of the course is for students to develop a hands-on working experience in using standard computer software tools as well as computer techniques and methodologies used in life sciences research. This paper provides a detailed description of the didactical tools and assessment methods used in and outside of the classroom as well as a discussion of the lessons learned during the first installment of the course taught at Emory University in fall semester 2009.

Better informed in clinical practice - a brief overview of dental informatics.

PubMed

Reynolds, P A; Harper, J; Dunne, S

2008-03-22

Uptake of dental informatics has been hampered by technical and user issues. Innovative systems have been developed, but usability issues have affected many. Advances in technology and artificial intelligence are now producing clinically useful systems, although issues still remain with adapting computer interfaces to the dental practice working environment. A dental electronic health record has become a priority in many countries, including the UK. However, experience shows that any dental electronic health record (EHR) system cannot be subordinate to, or a subset of, a medical record. Such a future dental EHR is likely to incorporate integrated care pathways. Future best dental practice will increasingly depend on computer-based support tools, although disagreement remains about the effectiveness of current support tools. Over the longer term, future dental informatics tools will incorporate dynamic, online evidence-based medicine (EBM) tools, and promise more adaptive, patient-focused and efficient dental care with educational advantages in training.

A Format for Phylogenetic Placements

PubMed Central

Matsen, Frederick A.; Hoffman, Noah G.; Gallagher, Aaron; Stamatakis, Alexandros

2012-01-01

We have developed a unified format for phylogenetic placements, that is, mappings of environmental sequence data (e.g., short reads) into a phylogenetic tree. We are motivated to do so by the growing number of tools for computing and post-processing phylogenetic placements, and the lack of an established standard for storing them. The format is lightweight, versatile, extensible, and is based on the JSON format, which can be parsed by most modern programming languages. Our format is already implemented in several tools for computing and post-processing parsimony- and likelihood-based phylogenetic placements and has worked well in practice. We believe that establishing a standard format for analyzing read placements at this early stage will lead to a more efficient development of powerful and portable post-analysis tools for the growing applications of phylogenetic placement. PMID:22383988

A format for phylogenetic placements.

PubMed

Matsen, Frederick A; Hoffman, Noah G; Gallagher, Aaron; Stamatakis, Alexandros

2012-01-01

We have developed a unified format for phylogenetic placements, that is, mappings of environmental sequence data (e.g., short reads) into a phylogenetic tree. We are motivated to do so by the growing number of tools for computing and post-processing phylogenetic placements, and the lack of an established standard for storing them. The format is lightweight, versatile, extensible, and is based on the JSON format, which can be parsed by most modern programming languages. Our format is already implemented in several tools for computing and post-processing parsimony- and likelihood-based phylogenetic placements and has worked well in practice. We believe that establishing a standard format for analyzing read placements at this early stage will lead to a more efficient development of powerful and portable post-analysis tools for the growing applications of phylogenetic placement.

Development and Demonstration of a Computational Tool for the Analysis of Particle Vitiation Effects in Hypersonic Propulsion Test Facilities

NASA Technical Reports Server (NTRS)

Perkins, Hugh Douglas

2010-01-01

In order to improve the understanding of particle vitiation effects in hypersonic propulsion test facilities, a quasi-one dimensional numerical tool was developed to efficiently model reacting particle-gas flows over a wide range of conditions. Features of this code include gas-phase finite-rate kinetics, a global porous-particle combustion model, mass, momentum and energy interactions between phases, and subsonic and supersonic particle drag and heat transfer models. The basic capabilities of this tool were validated against available data or other validated codes. To demonstrate the capabilities of the code a series of computations were performed for a model hypersonic propulsion test facility and scramjet. Parameters studied were simulated flight Mach number, particle size, particle mass fraction and particle material.

CASE tools and UML: state of the ART.

PubMed

Agarwal, S

2001-05-01

With increasing need for automated tools to assist complex systems development, software design methods are becoming popular. This article analyzes the state of art in computer-aided software engineering (CASE) tools and unified modeling language (UML), focusing on their evolution, merits, and industry usage. It identifies managerial issues for the tools' adoption and recommends an action plan to select and implement them. While CASE and UML offer inherent advantages like cheaper, shorter, and efficient development cycles, they suffer from poor user satisfaction. The critical success factors for their implementation include, among others, management and staff commitment, proper corporate infrastructure, and user training.

Proteinortho: detection of (co-)orthologs in large-scale analysis.

PubMed

Lechner, Marcus; Findeiss, Sven; Steiner, Lydia; Marz, Manja; Stadler, Peter F; Prohaska, Sonja J

2011-04-28

Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes it desirable to compute genome-wide orthology relations for a given dataset rather than relying on relations listed in databases. The program Proteinortho described here is a stand-alone tool that is geared towards large datasets and makes use of distributed computing techniques when run on multi-core hardware. It implements an extended version of the reciprocal best alignment heuristic. We apply Proteinortho to compute orthologous proteins in the complete set of all 717 eubacterial genomes available at NCBI at the beginning of 2009. We identified thirty proteins present in 99% of all bacterial proteomes. Proteinortho significantly reduces the required amount of memory for orthology analysis compared to existing tools, allowing such computations to be performed on off-the-shelf hardware.

An Efficient Computational Framework for the Analysis of Whole Slide Images: Application to Follicular Lymphoma Immunohistochemistry

PubMed Central

Samsi, Siddharth; Krishnamurthy, Ashok K.; Gurcan, Metin N.

2012-01-01

Follicular Lymphoma (FL) is one of the most common non-Hodgkin Lymphoma in the United States. Diagnosis and grading of FL is based on the review of histopathological tissue sections under a microscope and is influenced by human factors such as fatigue and reader bias. Computer-aided image analysis tools can help improve the accuracy of diagnosis and grading and act as another tool at the pathologist’s disposal. Our group has been developing algorithms for identifying follicles in immunohistochemical images. These algorithms have been tested and validated on small images extracted from whole slide images. However, the use of these algorithms for analyzing the entire whole slide image requires significant changes to the processing methodology since the images are relatively large (on the order of 100k × 100k pixels). In this paper we discuss the challenges involved in analyzing whole slide images and propose potential computational methodologies for addressing these challenges. We discuss the use of parallel computing tools on commodity clusters and compare performance of the serial and parallel implementations of our approach. PMID:22962572

Materials Genome Initiative

NASA Technical Reports Server (NTRS)

Vickers, John

2015-01-01

The Materials Genome Initiative (MGI) project element is a cross-Center effort that is focused on the integration of computational tools to simulate manufacturing processes and materials behavior. These computational simulations will be utilized to gain understanding of processes and materials behavior to accelerate process development and certification to more efficiently integrate new materials in existing NASA projects and to lead to the design of new materials for improved performance. This NASA effort looks to collaborate with efforts at other government agencies and universities working under the national MGI. MGI plans to develop integrated computational/experimental/ processing methodologies for accelerating discovery and insertion of materials to satisfy NASA's unique mission demands. The challenges include validated design tools that incorporate materials properties, processes, and design requirements; and materials process control to rapidly mature emerging manufacturing methods and develop certified manufacturing processes

Rational, computer-enabled peptide drug design: principles, methods, applications and future directions.

PubMed

Diller, David J; Swanson, Jon; Bayden, Alexander S; Jarosinski, Mark; Audie, Joseph

2015-01-01

Peptides provide promising templates for developing drugs to occupy a middle space between small molecules and antibodies and for targeting 'undruggable' intracellular protein-protein interactions. Importantly, rational or in cerebro design, especially when coupled with validated in silico tools, can be used to efficiently explore chemical space and identify islands of 'drug-like' peptides to satisfy diverse drug discovery program objectives. Here, we consider the underlying principles of and recent advances in rational, computer-enabled peptide drug design. In particular, we consider the impact of basic physicochemical properties, potency and ADME/Tox opportunities and challenges, and recently developed computational tools for enabling rational peptide drug design. Key principles and practices are spotlighted by recent case studies. We close with a hypothetical future case study.

Higher-order ice-sheet modelling accelerated by multigrid on graphics cards

NASA Astrophysics Data System (ADS)

Brædstrup, Christian; Egholm, David

2013-04-01

Higher-order ice flow modelling is a very computer intensive process owing primarily to the nonlinear influence of the horizontal stress coupling. When applied for simulating long-term glacial landscape evolution, the ice-sheet models must consider very long time series, while both high temporal and spatial resolution is needed to resolve small effects. The use of higher-order and full stokes models have therefore seen very limited usage in this field. However, recent advances in graphics card (GPU) technology for high performance computing have proven extremely efficient in accelerating many large-scale scientific computations. The general purpose GPU (GPGPU) technology is cheap, has a low power consumption and fits into a normal desktop computer. It could therefore provide a powerful tool for many glaciologists working on ice flow models. Our current research focuses on utilising the GPU as a tool in ice-sheet and glacier modelling. To this extent we have implemented the Integrated Second-Order Shallow Ice Approximation (iSOSIA) equations on the device using the finite difference method. To accelerate the computations, the GPU solver uses a non-linear Red-Black Gauss-Seidel iterator coupled with a Full Approximation Scheme (FAS) multigrid setup to further aid convergence. The GPU finite difference implementation provides the inherent parallelization that scales from hundreds to several thousands of cores on newer cards. We demonstrate the efficiency of the GPU multigrid solver using benchmark experiments.

Petascale Many Body Methods for Complex Correlated Systems

NASA Astrophysics Data System (ADS)

Pruschke, Thomas

2012-02-01

Correlated systems constitute an important class of materials in modern condensed matter physics. Correlation among electrons are at the heart of all ordering phenomena and many intriguing novel aspects, such as quantum phase transitions or topological insulators, observed in a variety of compounds. Yet, theoretically describing these phenomena is still a formidable task, even if one restricts the models used to the smallest possible set of degrees of freedom. Here, modern computer architectures play an essential role, and the joint effort to devise efficient algorithms and implement them on state-of-the art hardware has become an extremely active field in condensed-matter research. To tackle this task single-handed is quite obviously not possible. The NSF-OISE funded PIRE collaboration ``Graduate Education and Research in Petascale Many Body Methods for Complex Correlated Systems'' is a successful initiative to bring together leading experts around the world to form a virtual international organization for addressing these emerging challenges and educate the next generation of computational condensed matter physicists. The collaboration includes research groups developing novel theoretical tools to reliably and systematically study correlated solids, experts in efficient computational algorithms needed to solve the emerging equations, and those able to use modern heterogeneous computer architectures to make then working tools for the growing community.

G-LoSA: An efficient computational tool for local structure-centric biological studies and drug design.

PubMed

Lee, Hui Sun; Im, Wonpil

2016-04-01

Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G-LoSA. G-LoSA aligns protein local structures in a sequence order independent way and provides a GA-score, a chemical feature-based and size-independent structure similarity score. Our benchmark validation shows the robust performance of G-LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure-centric comparative biology studies. In particular, G-LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G-LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer-aided drug design. We hope that G-LoSA can be a useful computational method for exploring interesting biological problems through large-scale comparison of protein local structures and facilitating drug discovery research and development. G-LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. © 2016 The Protein Society.

An application of nonlinear programming to the design of regulators of a linear-quadratic formulation

NASA Technical Reports Server (NTRS)

Fleming, P.

1983-01-01

A design technique is proposed for linear regulators in which a feedback controller of fixed structure is chosen to minimize an integral quadratic objective function subject to the satisfaction of integral quadratic constraint functions. Application of a nonlinear programming algorithm to this mathematically tractable formulation results in an efficient and useful computer aided design tool. Particular attention is paid to computational efficiency and various recommendations are made. Two design examples illustrate the flexibility of the approach and highlight the special insight afforded to the designer. One concerns helicopter longitudinal dynamics and the other the flight dynamics of an aerodynamically unstable aircraft.

Fragment informatics and computational fragment-based drug design: an overview and update.

PubMed

Sheng, Chunquan; Zhang, Wannian

2013-05-01

Fragment-based drug design (FBDD) is a promising approach for the discovery and optimization of lead compounds. Despite its successes, FBDD also faces some internal limitations and challenges. FBDD requires a high quality of target protein and good solubility of fragments. Biophysical techniques for fragment screening necessitate expensive detection equipment and the strategies for evolving fragment hits to leads remain to be improved. Regardless, FBDD is necessary for investigating larger chemical space and can be applied to challenging biological targets. In this scenario, cheminformatics and computational chemistry can be used as alternative approaches that can significantly improve the efficiency and success rate of lead discovery and optimization. Cheminformatics and computational tools assist FBDD in a very flexible manner. Computational FBDD can be used independently or in parallel with experimental FBDD for efficiently generating and optimizing leads. Computational FBDD can also be integrated into each step of experimental FBDD and help to play a synergistic role by maximizing its performance. This review will provide critical analysis of the complementarity between computational and experimental FBDD and highlight recent advances in new algorithms and successful examples of their applications. In particular, fragment-based cheminformatics tools, high-throughput fragment docking, and fragment-based de novo drug design will provide the focus of this review. We will also discuss the advantages and limitations of different methods and the trends in new developments that should inspire future research. © 2012 Wiley Periodicals, Inc.

Progress Toward an Efficient and General CFD Tool for Propulsion Design/Analysis

NASA Technical Reports Server (NTRS)

Cox, C. F.; Cinnella, P.; Westmoreland, S.

1996-01-01

The simulation of propulsive flows inherently involves chemical activity. Recent years have seen substantial strides made in the development of numerical schemes for reacting flowfields, in particular those involving finite-rate chemistry. However, finite-rate calculations are computationally intensive and require knowledge of the actual kinetics, which are not always known with sufficient accuracy. Alternatively, flow simulations based on the assumption of local chemical equilibrium are capable of obtaining physically reasonable results at far less computational cost. The present study summarizes the development of efficient numerical techniques for the simulation of flows in local chemical equilibrium, whereby a 'Black Box' chemical equilibrium solver is coupled to the usual gasdynamic equations. The generalization of the methods enables the modelling of any arbitrary mixture of thermally perfect gases, including air, combustion mixtures and plasmas. As demonstration of the potential of the methodologies, several solutions, involving reacting and perfect gas flows, will be presented. Included is a preliminary simulation of the SSME startup transient. Future enhancements to the proposed techniques will be discussed, including more efficient finite-rate and hybrid (partial equilibrium) schemes. The algorithms that have been developed and are being optimized provide for an efficient and general tool for the design and analysis of propulsion systems.

Design of a high altitude long endurance flying-wing solar-powered unmanned air vehicle

NASA Astrophysics Data System (ADS)

Alsahlani, A. A.; Johnston, L. J.; Atcliffe, P. A.

2017-06-01

The low-Reynolds number environment of high-altitude §ight places severe demands on the aerodynamic design and stability and control of a high altitude, long endurance (HALE) unmanned air vehicle (UAV). The aerodynamic efficiency of a §ying-wing configuration makes it an attractive design option for such an application and is investigated in the present work. The proposed configuration has a high-aspect ratio, swept-wing planform, the wing sweep being necessary to provide an adequate moment arm for outboard longitudinal and lateral control surfaces. A design optimization framework is developed under a MATLAB environment, combining aerodynamic, structural, and stability analysis. Low-order analysis tools are employed to facilitate efficient computations, which is important when there are multiple optimization loops for the various engineering analyses. In particular, a vortex-lattice method is used to compute the wing planform aerodynamics, coupled to a twodimensional (2D) panel method to derive aerofoil sectional characteristics. Integral boundary-layer methods are coupled to the panel method in order to predict §ow separation boundaries during the design iterations. A quasi-analytical method is adapted for application to flyingwing con¦gurations to predict the wing weight and a linear finite-beam element approach is used for structural analysis of the wing-box. Stability is a particular concern in the low-density environment of high-altitude flight for flying-wing aircraft and so provision of adequate directional stability and control power forms part of the optimization process. At present, a modified Genetic Algorithm is used in all of the optimization loops. Each of the low-order engineering analysis tools is validated using higher-order methods to provide con¦dence in the use of these computationally-efficient tools in the present design-optimization framework. This paper includes the results of employing the present optimization tools in the design of a HALE, flying-wing UAV to indicate that this is a viable design configuration option.

Manufacturing Technology Support (MATES). Delivery Order 0002: Business Practices Assessment (BPA) Development

DTIC Science & Technology

2008-03-01

order fulfillment visibility, Kanban deployment, inventory count can be made visually, machines and tool labeling, costs, preventive maintenance...order fulfillment, computer scheduling versus Kanban , pull versus push systems, flow time efficiencies, back room costs of scheduling, MRP costs

Growth and yield models for central hardwoods

Treesearch

Martin E. Dale; Donald E. Hilt

1989-01-01

Over the last 20 years computers have become an efficient tool to estimate growth and yield. Computerized yield estimates vary from simple approximation or interpolation of traditional normal yield tables to highly sophisticated programs that simulate the growth and yield of each individual tree.

An Accurate and Computationally Efficient Model for Membrane-Type Circular-Symmetric Micro-Hotplates

PubMed Central

Khan, Usman; Falconi, Christian

2014-01-01

Ideally, the design of high-performance micro-hotplates would require a large number of simulations because of the existence of many important design parameters as well as the possibly crucial effects of both spread and drift. However, the computational cost of FEM simulations, which are the only available tool for accurately predicting the temperature in micro-hotplates, is very high. As a result, micro-hotplate designers generally have no effective simulation-tools for the optimization. In order to circumvent these issues, here, we propose a model for practical circular-symmetric micro-hot-plates which takes advantage of modified Bessel functions, computationally efficient matrix-approach for considering the relevant boundary conditions, Taylor linearization for modeling the Joule heating and radiation losses, and external-region-segmentation strategy in order to accurately take into account radiation losses in the entire micro-hotplate. The proposed model is almost as accurate as FEM simulations and two to three orders of magnitude more computationally efficient (e.g., 45 s versus more than 8 h). The residual errors, which are mainly associated to the undesired heating in the electrical contacts, are small (e.g., few degrees Celsius for an 800 °C operating temperature) and, for important analyses, almost constant. Therefore, we also introduce a computationally-easy single-FEM-compensation strategy in order to reduce the residual errors to about 1 °C. As illustrative examples of the power of our approach, we report the systematic investigation of a spread in the membrane thermal conductivity and of combined variations of both ambient and bulk temperatures. Our model enables a much faster characterization of micro-hotplates and, thus, a much more effective optimization prior to fabrication. PMID:24763214

MRUniNovo: an efficient tool for de novo peptide sequencing utilizing the hadoop distributed computing framework.

PubMed

Li, Chuang; Chen, Tao; He, Qiang; Zhu, Yunping; Li, Kenli

2017-03-15

Tandem mass spectrometry-based de novo peptide sequencing is a complex and time-consuming process. The current algorithms for de novo peptide sequencing cannot rapidly and thoroughly process large mass spectrometry datasets. In this paper, we propose MRUniNovo, a novel tool for parallel de novo peptide sequencing. MRUniNovo parallelizes UniNovo based on the Hadoop compute platform. Our experimental results demonstrate that MRUniNovo significantly reduces the computation time of de novo peptide sequencing without sacrificing the correctness and accuracy of the results, and thus can process very large datasets that UniNovo cannot. MRUniNovo is an open source software tool implemented in java. The source code and the parameter settings are available at http://bioinfo.hupo.org.cn/MRUniNovo/index.php. s131020002@hnu.edu.cn ; taochen1019@163.com. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Using computer-aided drug design and medicinal chemistry strategies in the fight against diabetes.

PubMed

Semighini, Evandro P; Resende, Jonathan A; de Andrade, Peterson; Morais, Pedro A B; Carvalho, Ivone; Taft, Carlton A; Silva, Carlos H T P

2011-04-01

The aim of this work is to present a simple, practical and efficient protocol for drug design, in particular Diabetes, which includes selection of the illness, good choice of a target as well as a bioactive ligand and then usage of various computer aided drug design and medicinal chemistry tools to design novel potential drug candidates in different diseases. We have selected the validated target dipeptidyl peptidase IV (DPP-IV), whose inhibition contributes to reduce glucose levels in type 2 diabetes patients. The most active inhibitor with complex X-ray structure reported was initially extracted from the BindingDB database. By using molecular modification strategies widely used in medicinal chemistry, besides current state-of-the-art tools in drug design (including flexible docking, virtual screening, molecular interaction fields, molecular dynamics, ADME and toxicity predictions), we have proposed 4 novel potential DPP-IV inhibitors with drug properties for Diabetes control, which have been supported and validated by all the computational tools used herewith.

SAGE: The Self-Adaptive Grid Code. 3

NASA Technical Reports Server (NTRS)

Davies, Carol B.; Venkatapathy, Ethiraj

1999-01-01

The multi-dimensional self-adaptive grid code, SAGE, is an important tool in the field of computational fluid dynamics (CFD). It provides an efficient method to improve the accuracy of flow solutions while simultaneously reducing computer processing time. Briefly, SAGE enhances an initial computational grid by redistributing the mesh points into more appropriate locations. The movement of these points is driven by an equal-error-distribution algorithm that utilizes the relationship between high flow gradients and excessive solution errors. The method also provides a balance between clustering points in the high gradient regions and maintaining the smoothness and continuity of the adapted grid, The latest version, Version 3, includes the ability to change the boundaries of a given grid to more efficiently enclose flow structures and provides alternative redistribution algorithms.

Quantum machine learning.

PubMed

Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

2017-09-13

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

Quantum machine learning

NASA Astrophysics Data System (ADS)

Biamonte, Jacob; Wittek, Peter; Pancotti, Nicola; Rebentrost, Patrick; Wiebe, Nathan; Lloyd, Seth

2017-09-01

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Quantum systems produce atypical patterns that classical systems are thought not to produce efficiently, so it is reasonable to postulate that quantum computers may outperform classical computers on machine learning tasks. The field of quantum machine learning explores how to devise and implement quantum software that could enable machine learning that is faster than that of classical computers. Recent work has produced quantum algorithms that could act as the building blocks of machine learning programs, but the hardware and software challenges are still considerable.

A 3D staggered-grid finite difference scheme for poroelastic wave equation

NASA Astrophysics Data System (ADS)

Zhang, Yijie; Gao, Jinghuai

2014-10-01

Three dimensional numerical modeling has been a viable tool for understanding wave propagation in real media. The poroelastic media can better describe the phenomena of hydrocarbon reservoirs than acoustic and elastic media. However, the numerical modeling in 3D poroelastic media demands significantly more computational capacity, including both computational time and memory. In this paper, we present a 3D poroelastic staggered-grid finite difference (SFD) scheme. During the procedure, parallel computing is implemented to reduce the computational time. Parallelization is based on domain decomposition, and communication between processors is performed using message passing interface (MPI). Parallel analysis shows that the parallelized SFD scheme significantly improves the simulation efficiency and 3D decomposition in domain is the most efficient. We also analyze the numerical dispersion and stability condition of the 3D poroelastic SFD method. Numerical results show that the 3D numerical simulation can provide a real description of wave propagation.

The expanded role of computers in Space Station Freedom real-time operations

NASA Technical Reports Server (NTRS)

Crawford, R. Paul; Cannon, Kathleen V.

1990-01-01

The challenges that NASA and its international partners face in their real-time operation of the Space Station Freedom necessitate an increased role on the part of computers. In building the operational concepts concerning the role of the computer, the Space Station program is using lessons learned experience from past programs, knowledge of the needs of future space programs, and technical advances in the computer industry. The computer is expected to contribute most significantly in real-time operations by forming a versatile operating architecture, a responsive operations tool set, and an environment that promotes effective and efficient utilization of Space Station Freedom resources.

The Java Image Science Toolkit (JIST) for rapid prototyping and publishing of neuroimaging software.

PubMed

Lucas, Blake C; Bogovic, John A; Carass, Aaron; Bazin, Pierre-Louis; Prince, Jerry L; Pham, Dzung L; Landman, Bennett A

2010-03-01

Non-invasive neuroimaging techniques enable extraordinarily sensitive and specific in vivo study of the structure, functional response and connectivity of biological mechanisms. With these advanced methods comes a heavy reliance on computer-based processing, analysis and interpretation. While the neuroimaging community has produced many excellent academic and commercial tool packages, new tools are often required to interpret new modalities and paradigms. Developing custom tools and ensuring interoperability with existing tools is a significant hurdle. To address these limitations, we present a new framework for algorithm development that implicitly ensures tool interoperability, generates graphical user interfaces, provides advanced batch processing tools, and, most importantly, requires minimal additional programming or computational overhead. Java-based rapid prototyping with this system is an efficient and practical approach to evaluate new algorithms since the proposed system ensures that rapidly constructed prototypes are actually fully-functional processing modules with support for multiple GUI's, a broad range of file formats, and distributed computation. Herein, we demonstrate MRI image processing with the proposed system for cortical surface extraction in large cross-sectional cohorts, provide a system for fully automated diffusion tensor image analysis, and illustrate how the system can be used as a simulation framework for the development of a new image analysis method. The system is released as open source under the Lesser GNU Public License (LGPL) through the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC).

The Java Image Science Toolkit (JIST) for Rapid Prototyping and Publishing of Neuroimaging Software

PubMed Central

Lucas, Blake C.; Bogovic, John A.; Carass, Aaron; Bazin, Pierre-Louis; Prince, Jerry L.; Pham, Dzung

2010-01-01

Non-invasive neuroimaging techniques enable extraordinarily sensitive and specific in vivo study of the structure, functional response and connectivity of biological mechanisms. With these advanced methods comes a heavy reliance on computer-based processing, analysis and interpretation. While the neuroimaging community has produced many excellent academic and commercial tool packages, new tools are often required to interpret new modalities and paradigms. Developing custom tools and ensuring interoperability with existing tools is a significant hurdle. To address these limitations, we present a new framework for algorithm development that implicitly ensures tool interoperability, generates graphical user interfaces, provides advanced batch processing tools, and, most importantly, requires minimal additional programming or computational overhead. Java-based rapid prototyping with this system is an efficient and practical approach to evaluate new algorithms since the proposed system ensures that rapidly constructed prototypes are actually fully-functional processing modules with support for multiple GUI's, a broad range of file formats, and distributed computation. Herein, we demonstrate MRI image processing with the proposed system for cortical surface extraction in large cross-sectional cohorts, provide a system for fully automated diffusion tensor image analysis, and illustrate how the system can be used as a simulation framework for the development of a new image analysis method. The system is released as open source under the Lesser GNU Public License (LGPL) through the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC). PMID:20077162

Integrated multidisciplinary analysis tool IMAT users' guide

NASA Technical Reports Server (NTRS)

Meissner, Frances T. (Editor)

1988-01-01

The Integrated Multidisciplinary Analysis Tool (IMAT) is a computer software system developed at Langley Research Center. IMAT provides researchers and analysts with an efficient capability to analyze satellite controls systems influenced by structural dynamics. Using a menu-driven executive system, IMAT leads the user through the program options. IMAT links a relational database manager to commercial and in-house structural and controls analysis codes. This paper describes the IMAT software system and how to use it.

From design to manufacturing of asymmetric teeth gears using computer application

NASA Astrophysics Data System (ADS)

Suciu, F.; Dascalescu, A.; Ungureanu, M.

2017-05-01

The asymmetric cylindrical gears, with involutes teeth profiles having different base circle diameters, are nonstandard gears, used with the aim to obtain better function parameters for the active profile. We will expect that the manufacturing of these gears became possible only after the design and realization of some specific tools. The paper present how the computer aided design and applications developed in MATLAB, for obtain the geometrical parameters, in the same time for calculation some functional parameters like stress and displacements, transmission error, efficiency of the gears and the 2D models, generated with AUTOLISP applications, are used for computer aided manufacturing of asymmetric gears with standard tools. So the specific tools considered one of the disadvantages of these gears are not necessary and implicitly the expected supplementary costs are reduced. The calculus algorithm established for the asymmetric gear design application use the „direct design“ of the spur gears. This method offers the possibility of determining first the parameters of the gears, followed by the determination of the asymmetric gear rack’s parameters, based on those of the gears. Using original design method and computer applications have been determined the geometrical parameters, the 2D and 3D models of the asymmetric gears and on the base of these models have been manufacturing on CNC machine tool asymmetric gears.

On the study of control effectiveness and computational efficiency of reduced Saint-Venant model in model predictive control of open channel flow

NASA Astrophysics Data System (ADS)

Xu, M.; van Overloop, P. J.; van de Giesen, N. C.

2011-02-01

Model predictive control (MPC) of open channel flow is becoming an important tool in water management. The complexity of the prediction model has a large influence on the MPC application in terms of control effectiveness and computational efficiency. The Saint-Venant equations, called SV model in this paper, and the Integrator Delay (ID) model are either accurate but computationally costly, or simple but restricted to allowed flow changes. In this paper, a reduced Saint-Venant (RSV) model is developed through a model reduction technique, Proper Orthogonal Decomposition (POD), on the SV equations. The RSV model keeps the main flow dynamics and functions over a large flow range but is easier to implement in MPC. In the test case of a modeled canal reach, the number of states and disturbances in the RSV model is about 45 and 16 times less than the SV model, respectively. The computational time of MPC with the RSV model is significantly reduced, while the controller remains effective. Thus, the RSV model is a promising means to balance the control effectiveness and computational efficiency.

Swellix: a computational tool to explore RNA conformational space.

PubMed

Sloat, Nathan; Liu, Jui-Wen; Schroeder, Susan J

2017-11-21

The sequence of nucleotides in an RNA determines the possible base pairs for an RNA fold and thus also determines the overall shape and function of an RNA. The Swellix program presented here combines a helix abstraction with a combinatorial approach to the RNA folding problem in order to compute all possible non-pseudoknotted RNA structures for RNA sequences. The Swellix program builds on the Crumple program and can include experimental constraints on global RNA structures such as the minimum number and lengths of helices from crystallography, cryoelectron microscopy, or in vivo crosslinking and chemical probing methods. The conceptual advance in Swellix is to count helices and generate all possible combinations of helices rather than counting and combining base pairs. Swellix bundles similar helices and includes improvements in memory use and efficient parallelization. Biological applications of Swellix are demonstrated by computing the reduction in conformational space and entropy due to naturally modified nucleotides in tRNA sequences and by motif searches in Human Endogenous Retroviral (HERV) RNA sequences. The Swellix motif search reveals occurrences of protein and drug binding motifs in the HERV RNA ensemble that do not occur in minimum free energy or centroid predicted structures. Swellix presents significant improvements over Crumple in terms of efficiency and memory use. The efficient parallelization of Swellix enables the computation of sequences as long as 418 nucleotides with sufficient experimental constraints. Thus, Swellix provides a practical alternative to free energy minimization tools when multiple structures, kinetically determined structures, or complex RNA-RNA and RNA-protein interactions are present in an RNA folding problem.

Distributions of Cognates in Europe as Based on Levenshtein Distance

ERIC Educational Resources Information Center

Schepens, Job; Dijkstra, Ton; Grootjen, Franc

2012-01-01

Researchers on bilingual processing can benefit from computational tools developed in artificial intelligence. We show that a normalized Levenshtein distance function can efficiently and reliably simulate bilingual orthographic similarity ratings. Orthographic similarity distributions of cognates and non-cognates were identified across pairs of…

SGFSC: speeding the gene functional similarity calculation based on hash tables.

PubMed

Tian, Zhen; Wang, Chunyu; Guo, Maozu; Liu, Xiaoyan; Teng, Zhixia

2016-11-04

In recent years, many measures of gene functional similarity have been proposed and widely used in all kinds of essential research. These methods are mainly divided into two categories: pairwise approaches and group-wise approaches. However, a common problem with these methods is their time consumption, especially when measuring the gene functional similarities of a large number of gene pairs. The problem of computational efficiency for pairwise approaches is even more prominent because they are dependent on the combination of semantic similarity. Therefore, the efficient measurement of gene functional similarity remains a challenging problem. To speed current gene functional similarity calculation methods, a novel two-step computing strategy is proposed: (1) establish a hash table for each method to store essential information obtained from the Gene Ontology (GO) graph and (2) measure gene functional similarity based on the corresponding hash table. There is no need to traverse the GO graph repeatedly for each method with the help of the hash table. The analysis of time complexity shows that the computational efficiency of these methods is significantly improved. We also implement a novel Speeding Gene Functional Similarity Calculation tool, namely SGFSC, which is bundled with seven typical measures using our proposed strategy. Further experiments show the great advantage of SGFSC in measuring gene functional similarity on the whole genomic scale. The proposed strategy is successful in speeding current gene functional similarity calculation methods. SGFSC is an efficient tool that is freely available at http://nclab.hit.edu.cn/SGFSC . The source code of SGFSC can be downloaded from http://pan.baidu.com/s/1dFFmvpZ .

Evaluation of the efficiency and fault density of software generated by code generators

NASA Technical Reports Server (NTRS)

Schreur, Barbara

1993-01-01

Flight computers and flight software are used for GN&C (guidance, navigation, and control), engine controllers, and avionics during missions. The software development requires the generation of a considerable amount of code. The engineers who generate the code make mistakes and the generation of a large body of code with high reliability requires considerable time. Computer-aided software engineering (CASE) tools are available which generates code automatically with inputs through graphical interfaces. These tools are referred to as code generators. In theory, code generators could write highly reliable code quickly and inexpensively. The various code generators offer different levels of reliability checking. Some check only the finished product while some allow checking of individual modules and combined sets of modules as well. Considering NASA's requirement for reliability, an in house manually generated code is needed. Furthermore, automatically generated code is reputed to be as efficient as the best manually generated code when executed. In house verification is warranted.

Addressing Curse of Dimensionality in Sensitivity Analysis: How Can We Handle High-Dimensional Problems?

NASA Astrophysics Data System (ADS)

Safaei, S.; Haghnegahdar, A.; Razavi, S.

2016-12-01

Complex environmental models are now the primary tool to inform decision makers for the current or future management of environmental resources under the climate and environmental changes. These complex models often contain a large number of parameters that need to be determined by a computationally intensive calibration procedure. Sensitivity analysis (SA) is a very useful tool that not only allows for understanding the model behavior, but also helps in reducing the number of calibration parameters by identifying unimportant ones. The issue is that most global sensitivity techniques are highly computationally demanding themselves for generating robust and stable sensitivity metrics over the entire model response surface. Recently, a novel global sensitivity analysis method, Variogram Analysis of Response Surfaces (VARS), is introduced that can efficiently provide a comprehensive assessment of global sensitivity using the Variogram concept. In this work, we aim to evaluate the effectiveness of this highly efficient GSA method in saving computational burden, when applied to systems with extra-large number of input factors ( 100). We use a test function and a hydrological modelling case study to demonstrate the capability of VARS method in reducing problem dimensionality by identifying important vs unimportant input factors.

AREVA Developments for an Efficient and Reliable use of Monte Carlo codes for Radiation Transport Applications

NASA Astrophysics Data System (ADS)

Chapoutier, Nicolas; Mollier, François; Nolin, Guillaume; Culioli, Matthieu; Mace, Jean-Reynald

2017-09-01

In the context of the rising of Monte Carlo transport calculations for any kind of application, AREVA recently improved its suite of engineering tools in order to produce efficient Monte Carlo workflow. Monte Carlo codes, such as MCNP or TRIPOLI, are recognized as reference codes to deal with a large range of radiation transport problems. However the inherent drawbacks of theses codes - laboring input file creation and long computation time - contrast with the maturity of the treatment of the physical phenomena. The goals of the recent AREVA developments were to reach similar efficiency as other mature engineering sciences such as finite elements analyses (e.g. structural or fluid dynamics). Among the main objectives, the creation of a graphical user interface offering CAD tools for geometry creation and other graphical features dedicated to the radiation field (source definition, tally definition) has been reached. The computations times are drastically reduced compared to few years ago thanks to the use of massive parallel runs, and above all, the implementation of hybrid variance reduction technics. From now engineering teams are capable to deliver much more prompt support to any nuclear projects dealing with reactors or fuel cycle facilities from conceptual phase to decommissioning.

RNAmutants: a web server to explore the mutational landscape of RNA secondary structures

PubMed Central

Waldispühl, Jerome; Devadas, Srinivas; Berger, Bonnie; Clote, Peter

2009-01-01

The history and mechanism of molecular evolution in DNA have been greatly elucidated by contributions from genetics, probability theory and bioinformatics—indeed, mathematical developments such as Kimura's neutral theory, Kingman's coalescent theory and efficient software such as BLAST, ClustalW, Phylip, etc., provide the foundation for modern population genetics. In contrast to DNA, the function of most noncoding RNA depends on tertiary structure, experimentally known to be largely determined by secondary structure, for which dynamic programming can efficiently compute the minimum free energy secondary structure. For this reason, understanding the effect of pointwise mutations in RNA secondary structure could reveal fundamental properties of structural RNA molecules and improve our understanding of molecular evolution of RNA. The web server RNAmutants provides several efficient tools to compute the ensemble of low-energy secondary structures for all k-mutants of a given RNA sequence, where k is bounded by a user-specified upper bound. As we have previously shown, these tools can be used to predict putative deleterious mutations and to analyze regulatory sequences from the hepatitis C and human immunodeficiency genomes. Web server is available at http://bioinformatics.bc.edu/clotelab/RNAmutants/, and downloadable binaries at http://rnamutants.csail.mit.edu/. PMID:19531740

Implementing WebGL and HTML5 in Macromolecular Visualization and Modern Computer-Aided Drug Design.

PubMed

Yuan, Shuguang; Chan, H C Stephen; Hu, Zhenquan

2017-06-01

Web browsers have long been recognized as potential platforms for remote macromolecule visualization. However, the difficulty in transferring large-scale data to clients and the lack of native support for hardware-accelerated applications in the local browser undermine the feasibility of such utilities. With the introduction of WebGL and HTML5 technologies in recent years, it is now possible to exploit the power of a graphics-processing unit (GPU) from a browser without any third-party plugin. Many new tools have been developed for biological molecule visualization and modern drug discovery. In contrast to traditional offline tools, real-time computing, interactive data analysis, and cross-platform analyses feature WebGL- and HTML5-based tools, facilitating biological research in a more efficient and user-friendly way. Copyright © 2017 Elsevier Ltd. All rights reserved.

Successes and Challenges of Incompressible Flow Simulation

NASA Technical Reports Server (NTRS)

Kwak, Dochan; Kiris, Cetin

2003-01-01

During the past thirty years, numerical methods and simulation tools for incompressible flows have been advanced as a subset of CFD discipline. Even though incompressible flows are encountered in many areas of engineering, simulation of compressible flow has been the major driver for developing computational algorithms and tools. This is probably due to rather stringent requirements for predicting aerodynamic performance characteristics of flight vehicles, while flow devices involving low speed or incompressible flow could be reasonably well designed without resorting to accurate numerical simulations. As flow devices are required to be more sophisticated and highly efficient, CFD tools become indispensable in fluid engineering for incompressible and low speed flow. This paper is intended to review some of the successes made possible by advances in computational technologies during the same period, and discuss some of the current challenges.

SoftLab: A Soft-Computing Software for Experimental Research with Commercialization Aspects

NASA Technical Reports Server (NTRS)

Akbarzadeh-T, M.-R.; Shaikh, T. S.; Ren, J.; Hubbell, Rob; Kumbla, K. K.; Jamshidi, M

1998-01-01

SoftLab is a software environment for research and development in intelligent modeling/control using soft-computing paradigms such as fuzzy logic, neural networks, genetic algorithms, and genetic programs. SoftLab addresses the inadequacies of the existing soft-computing software by supporting comprehensive multidisciplinary functionalities from management tools to engineering systems. Furthermore, the built-in features help the user process/analyze information more efficiently by a friendly yet powerful interface, and will allow the user to specify user-specific processing modules, hence adding to the standard configuration of the software environment.

A SCILAB Program for Computing General-Relativistic Models of Rotating Neutron Stars by Implementing Hartle's Perturbation Method

NASA Astrophysics Data System (ADS)

Papasotiriou, P. J.; Geroyannis, V. S.

We implement Hartle's perturbation method to the computation of relativistic rigidly rotating neutron star models. The program has been written in SCILAB (© INRIA ENPC), a matrix-oriented high-level programming language. The numerical method is described in very detail and is applied to many models in slow or fast rotation. We show that, although the method is perturbative, it gives accurate results for all practical purposes and it should prove an efficient tool for computing rapidly rotating pulsars.

Parallelization of Nullspace Algorithm for the computation of metabolic pathways

PubMed Central

Jevremović, Dimitrije; Trinh, Cong T.; Srienc, Friedrich; Sosa, Carlos P.; Boley, Daniel

2011-01-01

Elementary mode analysis is a useful metabolic pathway analysis tool in understanding and analyzing cellular metabolism, since elementary modes can represent metabolic pathways with unique and minimal sets of enzyme-catalyzed reactions of a metabolic network under steady state conditions. However, computation of the elementary modes of a genome- scale metabolic network with 100–1000 reactions is very expensive and sometimes not feasible with the commonly used serial Nullspace Algorithm. In this work, we develop a distributed memory parallelization of the Nullspace Algorithm to handle efficiently the computation of the elementary modes of a large metabolic network. We give an implementation in C++ language with the support of MPI library functions for the parallel communication. Our proposed algorithm is accompanied with an analysis of the complexity and identification of major bottlenecks during computation of all possible pathways of a large metabolic network. The algorithm includes methods to achieve load balancing among the compute-nodes and specific communication patterns to reduce the communication overhead and improve efficiency. PMID:22058581

PVT: An Efficient Computational Procedure to Speed up Next-generation Sequence Analysis

PubMed Central

2014-01-01

Background High-throughput Next-Generation Sequencing (NGS) techniques are advancing genomics and molecular biology research. This technology generates substantially large data which puts up a major challenge to the scientists for an efficient, cost and time effective solution to analyse such data. Further, for the different types of NGS data, there are certain common challenging steps involved in analysing those data. Spliced alignment is one such fundamental step in NGS data analysis which is extremely computational intensive as well as time consuming. There exists serious problem even with the most widely used spliced alignment tools. TopHat is one such widely used spliced alignment tools which although supports multithreading, does not efficiently utilize computational resources in terms of CPU utilization and memory. Here we have introduced PVT (Pipelined Version of TopHat) where we take up a modular approach by breaking TopHat’s serial execution into a pipeline of multiple stages, thereby increasing the degree of parallelization and computational resource utilization. Thus we address the discrepancies in TopHat so as to analyze large NGS data efficiently. Results We analysed the SRA dataset (SRX026839 and SRX026838) consisting of single end reads and SRA data SRR1027730 consisting of paired-end reads. We used TopHat v2.0.8 to analyse these datasets and noted the CPU usage, memory footprint and execution time during spliced alignment. With this basic information, we designed PVT, a pipelined version of TopHat that removes the redundant computational steps during ‘spliced alignment’ and breaks the job into a pipeline of multiple stages (each comprising of different step(s)) to improve its resource utilization, thus reducing the execution time. Conclusions PVT provides an improvement over TopHat for spliced alignment of NGS data analysis. PVT thus resulted in the reduction of the execution time to ~23% for the single end read dataset. Further, PVT designed for paired end reads showed an improved performance of ~41% over TopHat (for the chosen data) with respect to execution time. Moreover we propose PVT-Cloud which implements PVT pipeline in cloud computing system. PMID:24894600

PVT: an efficient computational procedure to speed up next-generation sequence analysis.

PubMed

Maji, Ranjan Kumar; Sarkar, Arijita; Khatua, Sunirmal; Dasgupta, Subhasis; Ghosh, Zhumur

2014-06-04

High-throughput Next-Generation Sequencing (NGS) techniques are advancing genomics and molecular biology research. This technology generates substantially large data which puts up a major challenge to the scientists for an efficient, cost and time effective solution to analyse such data. Further, for the different types of NGS data, there are certain common challenging steps involved in analysing those data. Spliced alignment is one such fundamental step in NGS data analysis which is extremely computational intensive as well as time consuming. There exists serious problem even with the most widely used spliced alignment tools. TopHat is one such widely used spliced alignment tools which although supports multithreading, does not efficiently utilize computational resources in terms of CPU utilization and memory. Here we have introduced PVT (Pipelined Version of TopHat) where we take up a modular approach by breaking TopHat's serial execution into a pipeline of multiple stages, thereby increasing the degree of parallelization and computational resource utilization. Thus we address the discrepancies in TopHat so as to analyze large NGS data efficiently. We analysed the SRA dataset (SRX026839 and SRX026838) consisting of single end reads and SRA data SRR1027730 consisting of paired-end reads. We used TopHat v2.0.8 to analyse these datasets and noted the CPU usage, memory footprint and execution time during spliced alignment. With this basic information, we designed PVT, a pipelined version of TopHat that removes the redundant computational steps during 'spliced alignment' and breaks the job into a pipeline of multiple stages (each comprising of different step(s)) to improve its resource utilization, thus reducing the execution time. PVT provides an improvement over TopHat for spliced alignment of NGS data analysis. PVT thus resulted in the reduction of the execution time to ~23% for the single end read dataset. Further, PVT designed for paired end reads showed an improved performance of ~41% over TopHat (for the chosen data) with respect to execution time. Moreover we propose PVT-Cloud which implements PVT pipeline in cloud computing system.

GAPIT: genome association and prediction integrated tool.

PubMed

Lipka, Alexander E; Tian, Feng; Wang, Qishan; Peiffer, Jason; Li, Meng; Bradbury, Peter J; Gore, Michael A; Buckler, Edward S; Zhang, Zhiwu

2012-09-15

Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results. http://www.maizegenetics.net/GAPIT. zhiwu.zhang@cornell.edu Supplementary data are available at Bioinformatics online.

Atomdroid: a computational chemistry tool for mobile platforms.

PubMed

Feldt, Jonas; Mata, Ricardo A; Dieterich, Johannes M

2012-04-23

We present the implementation of a new molecular mechanics program designed for use in mobile platforms, the first specifically built for these devices. The software is designed to run on Android operating systems and is compatible with several modern tablet-PCs and smartphones available in the market. It includes molecular viewer/builder capabilities with integrated routines for geometry optimizations and Monte Carlo simulations. These functionalities allow it to work as a stand-alone tool. We discuss some particular development aspects, as well as the overall feasibility of using computational chemistry software packages in mobile platforms. Benchmark calculations show that through efficient implementation techniques even hand-held devices can be used to simulate midsized systems using force fields.

Systems Engineering Building Advances Power Grid Research

ScienceCinema

Virden, Jud; Huang, Henry; Skare, Paul; Dagle, Jeff; Imhoff, Carl; Stoustrup, Jakob; Melton, Ron; Stiles, Dennis; Pratt, Rob

2018-01-16

Researchers and industry are now better equipped to tackle the nation’s most pressing energy challenges through PNNL’s new Systems Engineering Building – including challenges in grid modernization, buildings efficiency and renewable energy integration. This lab links real-time grid data, software platforms, specialized laboratories and advanced computing resources for the design and demonstration of new tools to modernize the grid and increase buildings energy efficiency.

Hybrid computational and experimental approach for the study and optimization of mechanical components

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Pryputniewicz, Ryszard J.

1998-05-01

Increased demands on the performance and efficiency of mechanical components impose challenges on their engineering design and optimization, especially when new and more demanding applications must be developed in relatively short periods of time while satisfying design objectives, as well as cost and manufacturability. In addition, reliability and durability must be taken into consideration. As a consequence, effective quantitative methodologies, computational and experimental, should be applied in the study and optimization of mechanical components. Computational investigations enable parametric studies and the determination of critical engineering design conditions, while experimental investigations, especially those using optical techniques, provide qualitative and quantitative information on the actual response of the structure of interest to the applied load and boundary conditions. We discuss a hybrid experimental and computational approach for investigation and optimization of mechanical components. The approach is based on analytical, computational, and experimental resolutions methodologies in the form of computational, noninvasive optical techniques, and fringe prediction analysis tools. Practical application of the hybrid approach is illustrated with representative examples that demonstrate the viability of the approach as an effective engineering tool for analysis and optimization.

Language-Agnostic Reproducible Data Analysis Using Literate Programming.

PubMed

Vassilev, Boris; Louhimo, Riku; Ikonen, Elina; Hautaniemi, Sampsa

2016-01-01

A modern biomedical research project can easily contain hundreds of analysis steps and lack of reproducibility of the analyses has been recognized as a severe issue. While thorough documentation enables reproducibility, the number of analysis programs used can be so large that in reality reproducibility cannot be easily achieved. Literate programming is an approach to present computer programs to human readers. The code is rearranged to follow the logic of the program, and to explain that logic in a natural language. The code executed by the computer is extracted from the literate source code. As such, literate programming is an ideal formalism for systematizing analysis steps in biomedical research. We have developed the reproducible computing tool Lir (literate, reproducible computing) that allows a tool-agnostic approach to biomedical data analysis. We demonstrate the utility of Lir by applying it to a case study. Our aim was to investigate the role of endosomal trafficking regulators to the progression of breast cancer. In this analysis, a variety of tools were combined to interpret the available data: a relational database, standard command-line tools, and a statistical computing environment. The analysis revealed that the lipid transport related genes LAPTM4B and NDRG1 are coamplified in breast cancer patients, and identified genes potentially cooperating with LAPTM4B in breast cancer progression. Our case study demonstrates that with Lir, an array of tools can be combined in the same data analysis to improve efficiency, reproducibility, and ease of understanding. Lir is an open-source software available at github.com/borisvassilev/lir.

Language-Agnostic Reproducible Data Analysis Using Literate Programming

PubMed Central

Vassilev, Boris; Louhimo, Riku; Ikonen, Elina; Hautaniemi, Sampsa

2016-01-01

A modern biomedical research project can easily contain hundreds of analysis steps and lack of reproducibility of the analyses has been recognized as a severe issue. While thorough documentation enables reproducibility, the number of analysis programs used can be so large that in reality reproducibility cannot be easily achieved. Literate programming is an approach to present computer programs to human readers. The code is rearranged to follow the logic of the program, and to explain that logic in a natural language. The code executed by the computer is extracted from the literate source code. As such, literate programming is an ideal formalism for systematizing analysis steps in biomedical research. We have developed the reproducible computing tool Lir (literate, reproducible computing) that allows a tool-agnostic approach to biomedical data analysis. We demonstrate the utility of Lir by applying it to a case study. Our aim was to investigate the role of endosomal trafficking regulators to the progression of breast cancer. In this analysis, a variety of tools were combined to interpret the available data: a relational database, standard command-line tools, and a statistical computing environment. The analysis revealed that the lipid transport related genes LAPTM4B and NDRG1 are coamplified in breast cancer patients, and identified genes potentially cooperating with LAPTM4B in breast cancer progression. Our case study demonstrates that with Lir, an array of tools can be combined in the same data analysis to improve efficiency, reproducibility, and ease of understanding. Lir is an open-source software available at github.com/borisvassilev/lir. PMID:27711123

48 CFR 23.705 - Electronic products environmental assessment tool.

Code of Federal Regulations, 2010 CFR

2010-10-01

... REGULATION SOCIOECONOMIC PROGRAMS ENVIRONMENT, ENERGY AND WATER EFFICIENCY, RENEWABLE ENERGY TECHNOLOGIES... standard for personal computer products— (i) Was issued by the Institute of Electrical and Electronics.... 104-113, the “National Technology Transfer and Advancement Act of 1995”, (see 11.102(c)); (iii) Meets...

48 CFR 23.704 - Electronic products environmental assessment tool.

Code of Federal Regulations, 2011 CFR

2011-10-01

... REGULATION SOCIOECONOMIC PROGRAMS ENVIRONMENT, ENERGY AND WATER EFFICIENCY, RENEWABLE ENERGY TECHNOLOGIES... standard for personal computer products— (i) Was issued by the Institute of Electrical and Electronics.... 104-113, the “National Technology Transfer and Advancement Act of 1995”, (see 11.102(c)); (iii) Meets...

48 CFR 23.704 - Electronic products environmental assessment tool.

Code of Federal Regulations, 2012 CFR

2012-10-01

... REGULATION SOCIOECONOMIC PROGRAMS ENVIRONMENT, ENERGY AND WATER EFFICIENCY, RENEWABLE ENERGY TECHNOLOGIES... standard for personal computer products— (i) Was issued by the Institute of Electrical and Electronics.... 104-113, the “National Technology Transfer and Advancement Act of 1995”, (see 11.102(c)); (iii) Meets...

Evaluation of a stepwise, multi-objective, multi-variable parameter optimization method for the APEX model

USDA-ARS?s Scientific Manuscript database

Hydrologic models are essential tools for environmental assessment of agricultural non-point source pollution. The automatic calibration of hydrologic models, though efficient, demands significant computational power, which can limit its application. The study objective was to investigate a cost e...

Productivity, part 2: cloud storage, remote meeting tools, screencasting, speech recognition software, password managers, and online data backup.

PubMed

Lackey, Amanda E; Pandey, Tarun; Moshiri, Mariam; Lalwani, Neeraj; Lall, Chandana; Bhargava, Puneet

2014-06-01

It is an opportune time for radiologists to focus on personal productivity. The ever increasing reliance on computers and the Internet has significantly changed the way we work. Myriad software applications are available to help us improve our personal efficiency. In this article, the authors discuss some tools that help improve collaboration and personal productivity, maximize e-learning, and protect valuable digital data. Published by Elsevier Inc.

Geometric modeling for computer aided design

NASA Technical Reports Server (NTRS)

Schwing, James L.; Olariu, Stephen

1995-01-01

The primary goal of this grant has been the design and implementation of software to be used in the conceptual design of aerospace vehicles particularly focused on the elements of geometric design, graphical user interfaces, and the interaction of the multitude of software typically used in this engineering environment. This has resulted in the development of several analysis packages and design studies. These include two major software systems currently used in the conceptual level design of aerospace vehicles. These tools are SMART, the Solid Modeling Aerospace Research Tool, and EASIE, the Environment for Software Integration and Execution. Additional software tools were designed and implemented to address the needs of the engineer working in the conceptual design environment. SMART provides conceptual designers with a rapid prototyping capability and several engineering analysis capabilities. In addition, SMART has a carefully engineered user interface that makes it easy to learn and use. Finally, a number of specialty characteristics have been built into SMART which allow it to be used efficiently as a front end geometry processor for other analysis packages. EASIE provides a set of interactive utilities that simplify the task of building and executing computer aided design systems consisting of diverse, stand-alone, analysis codes. Resulting in a streamlining of the exchange of data between programs reducing errors and improving the efficiency. EASIE provides both a methodology and a collection of software tools to ease the task of coordinating engineering design and analysis codes.

Knowledge-acquisition tools for medical knowledge-based systems.

PubMed

Lanzola, G; Quaglini, S; Stefanelli, M

1995-03-01

Knowledge-based systems (KBS) have been proposed to solve a large variety of medical problems. A strategic issue for KBS development and maintenance are the efforts required for both knowledge engineers and domain experts. The proposed solution is building efficient knowledge acquisition (KA) tools. This paper presents a set of KA tools we are developing within a European Project called GAMES II. They have been designed after the formulation of an epistemological model of medical reasoning. The main goal is that of developing a computational framework which allows knowledge engineers and domain experts to interact cooperatively in developing a medical KBS. To this aim, a set of reusable software components is highly recommended. Their design was facilitated by the development of a methodology for KBS construction. It views this process as comprising two activities: the tailoring of the epistemological model to the specific medical task to be executed and the subsequent translation of this model into a computational architecture so that the connections between computational structures and their knowledge level counterparts are maintained. The KA tools we developed are illustrated taking examples from the behavior of a KBS we are building for the management of children with acute myeloid leukemia.

On modelling three-dimensional piezoelectric smart structures with boundary spectral element method

NASA Astrophysics Data System (ADS)

Zou, Fangxin; Aliabadi, M. H.

2017-05-01

The computational efficiency of the boundary element method in elastodynamic analysis can be significantly improved by employing high-order spectral elements for boundary discretisation. In this work, for the first time, the so-called boundary spectral element method is utilised to formulate the piezoelectric smart structures that are widely used in structural health monitoring (SHM) applications. The resultant boundary spectral element formulation has been validated by the finite element method (FEM) and physical experiments. The new formulation has demonstrated a lower demand on computational resources and a higher numerical stability than commercial FEM packages. Comparing to the conventional boundary element formulation, a significant reduction in computational expenses has been achieved. In summary, the boundary spectral element formulation presented in this paper provides a highly efficient and stable mathematical tool for the development of SHM applications.

TRIM—3D: a three-dimensional model for accurate simulation of shallow water flow

USGS Publications Warehouse

Casulli, Vincenzo; Bertolazzi, Enrico; Cheng, Ralph T.

1993-01-01

A semi-implicit finite difference formulation for the numerical solution of three-dimensional tidal circulation is discussed. The governing equations are the three-dimensional Reynolds equations in which the pressure is assumed to be hydrostatic. A minimal degree of implicitness has been introduced in the finite difference formula so that the resulting algorithm permits the use of large time steps at a minimal computational cost. This formulation includes the simulation of flooding and drying of tidal flats, and is fully vectorizable for an efficient implementation on modern vector computers. The high computational efficiency of this method has made it possible to provide the fine details of circulation structure in complex regions that previous studies were unable to obtain. For proper interpretation of the model results suitable interactive graphics is also an essential tool.

Towards a flexible middleware for context-aware pervasive and wearable systems.

PubMed

Muro, Marco; Amoretti, Michele; Zanichelli, Francesco; Conte, Gianni

2012-11-01

Ambient intelligence and wearable computing call for innovative hardware and software technologies, including a highly capable, flexible and efficient middleware, allowing for the reuse of existing pervasive applications when developing new ones. In the considered application domain, middleware should also support self-management, interoperability among different platforms, efficient communications, and context awareness. In the on-going "everything is networked" scenario scalability appears as a very important issue, for which the peer-to-peer (P2P) paradigm emerges as an appealing solution for connecting software components in an overlay network, allowing for efficient and balanced data distribution mechanisms. In this paper, we illustrate how all these concepts can be placed into a theoretical tool, called networked autonomic machine (NAM), implemented into a NAM-based middleware, and evaluated against practical problems of pervasive computing.

Centralized Monitoring of the Microsoft Windows-based computers of the LHC Experiment Control Systems

NASA Astrophysics Data System (ADS)

Varela Rodriguez, F.

2011-12-01

The control system of each of the four major Experiments at the CERN Large Hadron Collider (LHC) is distributed over up to 160 computers running either Linux or Microsoft Windows. A quick response to abnormal situations of the computer infrastructure is crucial to maximize the physics usage. For this reason, a tool was developed to supervise, identify errors and troubleshoot such a large system. Although the monitoring of the performance of the Linux computers and their processes was available since the first versions of the tool, it is only recently that the software package has been extended to provide similar functionality for the nodes running Microsoft Windows as this platform is the most commonly used in the LHC detector control systems. In this paper, the architecture and the functionality of the Windows Management Instrumentation (WMI) client developed to provide centralized monitoring of the nodes running different flavour of the Microsoft platform, as well as the interface to the SCADA software of the control systems are presented. The tool is currently being commissioned by the Experiments and it has already proven to be very efficient optimize the running systems and to detect misbehaving processes or nodes.

Proteinortho: Detection of (Co-)orthologs in large-scale analysis

PubMed Central

2011-01-01

Background Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes it desirable to compute genome-wide orthology relations for a given dataset rather than relying on relations listed in databases. Results The program Proteinortho described here is a stand-alone tool that is geared towards large datasets and makes use of distributed computing techniques when run on multi-core hardware. It implements an extended version of the reciprocal best alignment heuristic. We apply Proteinortho to compute orthologous proteins in the complete set of all 717 eubacterial genomes available at NCBI at the beginning of 2009. We identified thirty proteins present in 99% of all bacterial proteomes. Conclusions Proteinortho significantly reduces the required amount of memory for orthology analysis compared to existing tools, allowing such computations to be performed on off-the-shelf hardware. PMID:21526987

Visual analysis of fluid dynamics at NASA's numerical aerodynamic simulation facility

NASA Technical Reports Server (NTRS)

Watson, Velvin R.

1991-01-01

A study aimed at describing and illustrating visualization tools used in Computational Fluid Dynamics (CFD) and indicating how these tools are likely to change by showing a projected resolution of the human computer interface is presented. The following are outlined using a graphically based test format: the revolution of human computer environments for CFD research; comparison of current environments; current environments with the ideal; predictions for the future CFD environments; what can be done to accelerate the improvements. The following comments are given: when acquiring visualization tools, potential rapid changes must be considered; environmental changes over the next ten years due to human computer interface cannot be fathomed; data flow packages such as AVS, apE, Explorer and Data Explorer are easy to learn and use for small problems, excellent for prototyping, but not so efficient for large problems; the approximation techniques used in visualization software must be appropriate for the data; it has become more cost effective to move jobs that fit on workstations and run only memory intensive jobs on the supercomputer; use of three dimensional skills will be maximized when the three dimensional environment is built in from the start.

Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations

NASA Technical Reports Server (NTRS)

Sharma, Shivanjli; Fergus, John

2017-01-01

A real time dashboard was developed in order to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users across a number of roles benefit from a real time system that enables common situational awareness. In addition to shared situational awareness the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial set of metrics computed on operational data. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017; Charlotte-Douglas International Airport. Analysis and metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of metrics across delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

CoCoNUT: an efficient system for the comparison and analysis of genomes

PubMed Central

2008-01-01

Background Comparative genomics is the analysis and comparison of genomes from different species. This area of research is driven by the large number of sequenced genomes and heavily relies on efficient algorithms and software to perform pairwise and multiple genome comparisons. Results Most of the software tools available are tailored for one specific task. In contrast, we have developed a novel system CoCoNUT (Computational Comparative geNomics Utility Toolkit) that allows solving several different tasks in a unified framework: (1) finding regions of high similarity among multiple genomic sequences and aligning them, (2) comparing two draft or multi-chromosomal genomes, (3) locating large segmental duplications in large genomic sequences, and (4) mapping cDNA/EST to genomic sequences. Conclusion CoCoNUT is competitive with other software tools w.r.t. the quality of the results. The use of state of the art algorithms and data structures allows CoCoNUT to solve comparative genomics tasks more efficiently than previous tools. With the improved user interface (including an interactive visualization component), CoCoNUT provides a unified, versatile, and easy-to-use software tool for large scale studies in comparative genomics. PMID:19014477

Visualizing a silicon quantum computer

NASA Astrophysics Data System (ADS)

Sanders, Barry C.; Hollenberg, Lloyd C. L.; Edmundson, Darran; Edmundson, Andrew

2008-12-01

Quantum computation is a fast-growing, multi-disciplinary research field. The purpose of a quantum computer is to execute quantum algorithms that efficiently solve computational problems intractable within the existing paradigm of 'classical' computing built on bits and Boolean gates. While collaboration between computer scientists, physicists, chemists, engineers, mathematicians and others is essential to the project's success, traditional disciplinary boundaries can hinder progress and make communicating the aims of quantum computing and future technologies difficult. We have developed a four minute animation as a tool for representing, understanding and communicating a silicon-based solid-state quantum computer to a variety of audiences, either as a stand-alone animation to be used by expert presenters or embedded into a longer movie as short animated sequences. The paper includes a generally applicable recipe for successful scientific animation production.

Java Tool Framework for Automation of Hardware Commissioning and Maintenance Procedures

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

Ho, J C; Fisher, J M; Gordon, J B

2007-10-02

The National Ignition Facility (NIF) is a 192-beam laser system designed to study high energy density physics. Each beam line contains a variety of line replaceable units (LRUs) that contain optics, stepping motors, sensors and other devices to control and diagnose the laser. During commissioning and subsequent maintenance of the laser, LRUs undergo a qualification process using the Integrated Computer Control System (ICCS) to verify and calibrate the equipment. The commissioning processes are both repetitive and tedious when we use remote manual computer controls, making them ideal candidates for software automation. Maintenance and Commissioning Tool (MCT) software was developed tomore » improve the efficiency of the qualification process. The tools are implemented in Java, leveraging ICCS services and CORBA to communicate with the control devices. The framework provides easy-to-use mechanisms for handling configuration data, task execution, task progress reporting, and generation of commissioning test reports. The tool framework design and application examples will be discussed.« less

Automated Reporting of DXA Studies Using a Custom-Built Computer Program.

PubMed

England, Joseph R; Colletti, Patrick M

2018-06-01

Dual-energy x-ray absorptiometry (DXA) scans are a critical population health tool and relatively simple to interpret but can be time consuming to report, often requiring manual transfer of bone mineral density and associated statistics into commercially available dictation systems. We describe here a custom-built computer program for automated reporting of DXA scans using Pydicom, an open-source package built in the Python computer language, and regular expressions to mine DICOM tags for patient information and bone mineral density statistics. This program, easy to emulate by any novice computer programmer, has doubled our efficiency at reporting DXA scans and has eliminated dictation errors.

Optimum spaceborne computer system design by simulation

NASA Technical Reports Server (NTRS)

Williams, T.; Weatherbee, J. E.; Taylor, D. S.

1972-01-01

A deterministic digital simulation model is described which models the Automatically Reconfigurable Modular Multiprocessor System (ARMMS), a candidate computer system for future manned and unmanned space missions. Use of the model as a tool in configuring a minimum computer system for a typical mission is demonstrated. The configuration which is developed as a result of studies with the simulator is optimal with respect to the efficient use of computer system resources, i.e., the configuration derived is a minimal one. Other considerations such as increased reliability through the use of standby spares would be taken into account in the definition of a practical system for a given mission.

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

Grote, D. P.

Forthon generates links between Fortran and Python. Python is a high level, object oriented, interactive and scripting language that allows a flexible and versatile interface to computational tools. The Forthon package generates the necessary wrapping code which allows access to the Fortran database and to the Fortran subroutines and functions. This provides a development package where the computationally intensive parts of a code can be written in efficient Fortran, and the high level controlling code can be written in the much more versatile Python language.

National Fusion Collaboratory: Grid Computing for Simulations and Experiments

NASA Astrophysics Data System (ADS)

Greenwald, Martin

2004-05-01

The National Fusion Collaboratory Project is creating a computational grid designed to advance scientific understanding and innovation in magnetic fusion research by facilitating collaborations, enabling more effective integration of experiments, theory and modeling and allowing more efficient use of experimental facilities. The philosophy of FusionGrid is that data, codes, analysis routines, visualization tools, and communication tools should be thought of as network available services, easily used by the fusion scientist. In such an environment, access to services is stressed rather than portability. By building on a foundation of established computer science toolkits, deployment time can be minimized. These services all share the same basic infrastructure that allows for secure authentication and resource authorization which allows stakeholders to control their own resources such as computers, data and experiments. Code developers can control intellectual property, and fair use of shared resources can be demonstrated and controlled. A key goal is to shield scientific users from the implementation details such that transparency and ease-of-use are maximized. The first FusionGrid service deployed was the TRANSP code, a widely used tool for transport analysis. Tools for run preparation, submission, monitoring and management have been developed and shared among a wide user base. This approach saves user sites from the laborious effort of maintaining such a large and complex code while at the same time reducing the burden on the development team by avoiding the need to support a large number of heterogeneous installations. Shared visualization and A/V tools are being developed and deployed to enhance long-distance collaborations. These include desktop versions of the Access Grid, a highly capable multi-point remote conferencing tool and capabilities for sharing displays and analysis tools over local and wide-area networks.

A climate responsive urban design tool: a platform to improve energy efficiency in a dry hot climate

NASA Astrophysics Data System (ADS)

El Dallal, Norhan; Visser, Florentine

2017-09-01

In the Middle East and North Africa (MENA) region, new urban developments should address the climatic conditions to improve outdoor comfort and to reduce the energy consumption of buildings. This article describes a design tool that supports climate responsive design for a dry hot climate. The approach takes the climate as an initiator for the conceptual urban form with a more energy-efficient urban morphology. The methodology relates the different passive strategies suitable for major climate conditions in MENA region (dry-hot) to design parameters that create the urban form. This parametric design approach is the basis for a tool that generates conceptual climate responsive urban forms so as to assist the urban designer early in the design process. Various conceptual scenarios, generated by a computational model, are the results of the proposed platform. A practical application of the approach is conducted on a New Urban Community in Aswan (Egypt), showing the economic feasibility of the resulting urban form and morphology, and the proposed tool.

Economic Modeling as a Component of Academic Strategic Planning.

ERIC Educational Resources Information Center

MacKinnon, Joyce; Sothmann, Mark; Johnson, James

2001-01-01

Computer-based economic modeling was used to enable a school of allied health to define outcomes, identify associated costs, develop cost and revenue models, and create a financial planning system. As a strategic planning tool, it assisted realistic budgeting and improved efficiency and effectiveness. (Contains 18 references.) (SK)

From Web 2.0 to Teacher 2.0

ERIC Educational Resources Information Center

Thomas, David A.; Li, Qing

2008-01-01

The World Wide Web is evolving in response to users who demand faster and more efficient access to information, portability, and reusability of digital objects between Web-based and computer-based applications and powerful communication, publication, collaboration, and teaching and learning tools. This article reviews current uses of Web-based…

Artificial Intelligence Applications in Special Education: How Feasible? Final Report.

ERIC Educational Resources Information Center

Hofmeister, Alan M.; Ferrara, Joseph M.

The research project investigated whether expert system tools have become sophisticated enough to be applied efficiently to problems in special education. (Expert systems are a development of artificial intelligence that combines the computer's capacity for storing specialized knowledge with a general set of rules intended to replicate the…

Adaptable Interactive CBL Design Tools for Education.

ERIC Educational Resources Information Center

Chandra, Peter

The design team approach to the development of computer based learning (CBL) courseware relies heavily on the effective communication between different members of the team, including up-to-date paperwork and documentation. This is important for the accurate and efficient overall coordination of the courseware design, and for future maintenance of…

IMPLEMENTATION OF A CAPE-OPEN COMPLIANT PROCESS SIMULATOR USING MICROSOFT'S VISUAL STUDIO.NET AND THE .NET FRAMEWORK

EPA Science Inventory

The United States Environmental Protection Agency is developing a Computer
Aided Process Engineering (CAPE) software tool for the metal finishing
industry that helps users design efficient metal finishing processes that
are less polluting to the environment. Metal finish...

The microcomputer scientific software series 4: testing prediction accuracy.

Treesearch

H. Michael Rauscher

1986-01-01

A computer program, ATEST, is described in this combination user's guide / programmer's manual. ATEST provides users with an efficient and convenient tool to test the accuracy of predictors. As input ATEST requires observed-predicted data pairs. The output reports the two components of accuracy, bias and precision.

Active Control Technology at NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Antcliff, Richard R.; McGowan, Anna-Marie R.

2000-01-01

NASA Langley has a long history of attacking important technical opportunities from a broad base of supporting disciplines. The research and development at Langley in this subject area range from the test tube to the test flight. The information covered here will range from the development of innovative new materials, sensors and actuators, to the incorporation of smart sensors and actuators in practical devices, to the optimization of the location of these devices, to, finally, a wide variety of applications of these devices utilizing Langley's facilities and expertise. Advanced materials are being developed for sensors and actuators, as well as polymers for integrating smart devices into composite structures. Contributions reside in three key areas: computational materials; advanced piezoelectric materials; and integrated composite structures. The computational materials effort is focused on developing predictive tools for the efficient design of new materials with the appropriate combination of properties for next generation smart airframe systems. Research in the area of advanced piezoelectrics includes optimizing the efficiency, force output, use temperature, and energy transfer between the structure and device for both ceramic and polymeric materials. For structural health monitoring, advanced non-destructive techniques including fiber optics are being developed for detection of delaminations, cracks and environmental deterioration in aircraft structures. The computational materials effort is focused on developing predictive tools for the efficient design of new materials with the appropriate combination of properties for next generation smart airframe system. Innovative fabrication techniques processing structural composites with sensor and actuator integration are being developed.

Development of a computer code for calculating the steady super/hypersonic inviscid flow around real configurations. Volume 1: Computational technique

NASA Technical Reports Server (NTRS)

Marconi, F.; Salas, M.; Yaeger, L.

1976-01-01

A numerical procedure has been developed to compute the inviscid super/hypersonic flow field about complex vehicle geometries accurately and efficiently. A second order accurate finite difference scheme is used to integrate the three dimensional Euler equations in regions of continuous flow, while all shock waves are computed as discontinuities via the Rankine Hugoniot jump conditions. Conformal mappings are used to develop a computational grid. The effects of blunt nose entropy layers are computed in detail. Real gas effects for equilibrium air are included using curve fits of Mollier charts. Typical calculated results for shuttle orbiter, hypersonic transport, and supersonic aircraft configurations are included to demonstrate the usefulness of this tool.

Computer modeling in the practice of acoustical consulting: An evolving variety of uses from marketing and diagnosis through design to eventually research

NASA Astrophysics Data System (ADS)

Madaras, Gary S.

2002-05-01

The use of computer modeling as a marketing, diagnosis, design, and research tool in the practice of acoustical consulting is discussed. From the time it is obtained, the software can be used as an effective marketing tool. It is not until the software basics are learned and some amount of testing and verification occurs that the software can be used as a tool for diagnosing the acoustics of existing rooms. A greater understanding of the output types and formats as well as experience in interpreting the results is required before the software can be used as an efficient design tool. Lastly, it is only after repetitive use as a design tool that the software can be used as a cost-effective means of conducting research in practice. The discussion is supplemented with specific examples of actual projects provided by various consultants within multiple firms. Focus is placed on the use of CATT-Acoustic software and predicting the room acoustics of large performing arts halls as well as other public assembly spaces.

C 3, A Command-line Catalog Cross-match Tool for Large Astrophysical Catalogs

NASA Astrophysics Data System (ADS)

Riccio, Giuseppe; Brescia, Massimo; Cavuoti, Stefano; Mercurio, Amata; di Giorgio, Anna Maria; Molinari, Sergio

2017-02-01

Modern Astrophysics is based on multi-wavelength data organized into large and heterogeneous catalogs. Hence, the need for efficient, reliable and scalable catalog cross-matching methods plays a crucial role in the era of the petabyte scale. Furthermore, multi-band data have often very different angular resolution, requiring the highest generality of cross-matching features, mainly in terms of region shape and resolution. In this work we present C 3 (Command-line Catalog Cross-match), a multi-platform application designed to efficiently cross-match massive catalogs. It is based on a multi-core parallel processing paradigm and conceived to be executed as a stand-alone command-line process or integrated within any generic data reduction/analysis pipeline, providing the maximum flexibility to the end-user, in terms of portability, parameter configuration, catalog formats, angular resolution, region shapes, coordinate units and cross-matching types. Using real data, extracted from public surveys, we discuss the cross-matching capabilities and computing time efficiency also through a direct comparison with some publicly available tools, chosen among the most used within the community, and representative of different interface paradigms. We verified that the C 3 tool has excellent capabilities to perform an efficient and reliable cross-matching between large data sets. Although the elliptical cross-match and the parametric handling of angular orientation and offset are known concepts in the astrophysical context, their availability in the presented command-line tool makes C 3 competitive in the context of public astronomical tools.

DOVIS 2.0: an efficient and easy to use parallel virtual screening tool based on AutoDock 4.0.

PubMed

Jiang, Xiaohui; Kumar, Kamal; Hu, Xin; Wallqvist, Anders; Reifman, Jaques

2008-09-08

Small-molecule docking is an important tool in studying receptor-ligand interactions and in identifying potential drug candidates. Previously, we developed a software tool (DOVIS) to perform large-scale virtual screening of small molecules in parallel on Linux clusters, using AutoDock 3.05 as the docking engine. DOVIS enables the seamless screening of millions of compounds on high-performance computing platforms. In this paper, we report significant advances in the software implementation of DOVIS 2.0, including enhanced screening capability, improved file system efficiency, and extended usability. To keep DOVIS up-to-date, we upgraded the software's docking engine to the more accurate AutoDock 4.0 code. We developed a new parallelization scheme to improve runtime efficiency and modified the AutoDock code to reduce excessive file operations during large-scale virtual screening jobs. We also implemented an algorithm to output docked ligands in an industry standard format, sd-file format, which can be easily interfaced with other modeling programs. Finally, we constructed a wrapper-script interface to enable automatic rescoring of docked ligands by arbitrarily selected third-party scoring programs. The significance of the new DOVIS 2.0 software compared with the previous version lies in its improved performance and usability. The new version makes the computation highly efficient by automating load balancing, significantly reducing excessive file operations by more than 95%, providing outputs that conform to industry standard sd-file format, and providing a general wrapper-script interface for rescoring of docked ligands. The new DOVIS 2.0 package is freely available to the public under the GNU General Public License.

OSLay: optimal syntenic layout of unfinished assemblies.

PubMed

Richter, Daniel C; Schuster, Stephan C; Huson, Daniel H

2007-07-01

The whole genome shotgun approach to genome sequencing results in a collection of contigs that must be ordered and oriented to facilitate efficient gap closure. We present a new tool OSLay that uses synteny between matching sequences in a target assembly and a reference assembly to layout the contigs (or scaffolds) in the target assembly. The underlying algorithm is based on maximum weight matching. The tool provides an interactive visualization of the computed layout and the result can be imported into the assembly editing tool Consed to support the design of primer pairs for gap closure. To enhance efficiency in the gap closure phase of a genome project it is crucial to know which contigs are adjacent in the target genome. Related genome sequences can be used to layout contigs in an assembly. OSLay is freely available from: http://www-ab.informatik.unituebingen.de/software/oslay.

Building a Data Science capability for USGS water research and communication

NASA Astrophysics Data System (ADS)

Appling, A.; Read, E. K.

2015-12-01

Interpreting and communicating water issues in an era of exponentially increasing information requires a blend of domain expertise, computational proficiency, and communication skills. The USGS Office of Water Information has established a Data Science team to meet these needs, providing challenging careers for diverse domain scientists and innovators in the fields of information technology and data visualization. Here, we detail the experience of building a Data Science capability as a bridging element between traditional water resources analyses and modern computing tools and data management techniques. This approach includes four major components: 1) building reusable research tools, 2) documenting data-intensive research approaches in peer reviewed journals, 3) communicating complex water resources issues with interactive web visualizations, and 4) offering training programs for our peers in scientific computing. These components collectively improve the efficiency, transparency, and reproducibility of USGS data analyses and scientific workflows.

Increasingly mobile: How new technologies can enhance qualitative research

PubMed Central

Moylan, Carrie Ann; Derr, Amelia Seraphia; Lindhorst, Taryn

2015-01-01

Advances in technology, such as the growth of smart phones, tablet computing, and improved access to the internet have resulted in many new tools and applications designed to increase efficiency and improve workflow. Some of these tools will assist scholars using qualitative methods with their research processes. We describe emerging technologies for use in data collection, analysis, and dissemination that each offer enhancements to existing research processes. Suggestions for keeping pace with the ever-evolving technological landscape are also offered. PMID:25798072

DOVIS 2.0: An Efficient and Easy to Use Parallel Virtual Screening Tool Based on AutoDock 4.0

DTIC Science & Technology

2008-09-08

under the GNU General Public License. Background Molecular docking is a computational method that pre- dicts how a ligand interacts with a receptor...Hence, it is an important tool in studying receptor-ligand interactions and plays an essential role in drug design. Particularly, molecular docking has...libraries from OpenBabel and setup a molecular data structure as a C++ object in our program. This makes handling of molecular structures (e.g., atoms

extrap: Software to assist the selection of extrapolation methods for moving-boat ADCP streamflow measurements

NASA Astrophysics Data System (ADS)

Mueller, David S.

2013-04-01

Selection of the appropriate extrapolation methods for computing the discharge in the unmeasured top and bottom parts of a moving-boat acoustic Doppler current profiler (ADCP) streamflow measurement is critical to the total discharge computation. The software tool, extrap, combines normalized velocity profiles from the entire cross section and multiple transects to determine a mean profile for the measurement. The use of an exponent derived from normalized data from the entire cross section is shown to be valid for application of the power velocity distribution law in the computation of the unmeasured discharge in a cross section. Selected statistics are combined with empirically derived criteria to automatically select the appropriate extrapolation methods. A graphical user interface (GUI) provides the user tools to visually evaluate the automatically selected extrapolation methods and manually change them, as necessary. The sensitivity of the total discharge to available extrapolation methods is presented in the GUI. Use of extrap by field hydrographers has demonstrated that extrap is a more accurate and efficient method of determining the appropriate extrapolation methods compared with tools currently (2012) provided in the ADCP manufacturers' software.

LittleQuickWarp: an ultrafast image warping tool.

PubMed

Qu, Lei; Peng, Hanchuan

2015-02-01

Warping images into a standard coordinate space is critical for many image computing related tasks. However, for multi-dimensional and high-resolution images, an accurate warping operation itself is often very expensive in terms of computer memory and computational time. For high-throughput image analysis studies such as brain mapping projects, it is desirable to have high performance image warping tools that are compatible with common image analysis pipelines. In this article, we present LittleQuickWarp, a swift and memory efficient tool that boosts 3D image warping performance dramatically and at the same time has high warping quality similar to the widely used thin plate spline (TPS) warping. Compared to the TPS, LittleQuickWarp can improve the warping speed 2-5 times and reduce the memory consumption 6-20 times. We have implemented LittleQuickWarp as an Open Source plug-in program on top of the Vaa3D system (http://vaa3d.org). The source code and a brief tutorial can be found in the Vaa3D plugin source code repository. Copyright © 2014 Elsevier Inc. All rights reserved.

Savant Genome Browser 2: visualization and analysis for population-scale genomics.

PubMed

Fiume, Marc; Smith, Eric J M; Brook, Andrew; Strbenac, Dario; Turner, Brian; Mezlini, Aziz M; Robinson, Mark D; Wodak, Shoshana J; Brudno, Michael

2012-07-01

High-throughput sequencing (HTS) technologies are providing an unprecedented capacity for data generation, and there is a corresponding need for efficient data exploration and analysis capabilities. Although most existing tools for HTS data analysis are developed for either automated (e.g. genotyping) or visualization (e.g. genome browsing) purposes, such tools are most powerful when combined. For example, integration of visualization and computation allows users to iteratively refine their analyses by updating computational parameters within the visual framework in real-time. Here we introduce the second version of the Savant Genome Browser, a standalone program for visual and computational analysis of HTS data. Savant substantially improves upon its predecessor and existing tools by introducing innovative visualization modes and navigation interfaces for several genomic datatypes, and synergizing visual and automated analyses in a way that is powerful yet easy even for non-expert users. We also present a number of plugins that were developed by the Savant Community, which demonstrate the power of integrating visual and automated analyses using Savant. The Savant Genome Browser is freely available (open source) at www.savantbrowser.com.

Savant Genome Browser 2: visualization and analysis for population-scale genomics

PubMed Central

Smith, Eric J. M.; Brook, Andrew; Strbenac, Dario; Turner, Brian; Mezlini, Aziz M.; Robinson, Mark D.; Wodak, Shoshana J.; Brudno, Michael

2012-01-01

High-throughput sequencing (HTS) technologies are providing an unprecedented capacity for data generation, and there is a corresponding need for efficient data exploration and analysis capabilities. Although most existing tools for HTS data analysis are developed for either automated (e.g. genotyping) or visualization (e.g. genome browsing) purposes, such tools are most powerful when combined. For example, integration of visualization and computation allows users to iteratively refine their analyses by updating computational parameters within the visual framework in real-time. Here we introduce the second version of the Savant Genome Browser, a standalone program for visual and computational analysis of HTS data. Savant substantially improves upon its predecessor and existing tools by introducing innovative visualization modes and navigation interfaces for several genomic datatypes, and synergizing visual and automated analyses in a way that is powerful yet easy even for non-expert users. We also present a number of plugins that were developed by the Savant Community, which demonstrate the power of integrating visual and automated analyses using Savant. The Savant Genome Browser is freely available (open source) at www.savantbrowser.com. PMID:22638571

Aeroelastic Model Structure Computation for Envelope Expansion

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2007-01-01

Structure detection is a procedure for selecting a subset of candidate terms, from a full model description, that best describes the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modelling may be of critical importance in the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion which may save significant development time and costs. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of nonlinear aeroelastic systems. The LASSO minimises the residual sum of squares by the addition of an l(sub 1) penalty term on the parameter vector of the traditional 2 minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudolinear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. Applicability of this technique for model structure computation for the F/A-18 Active Aeroelastic Wing using flight test data is shown for several flight conditions (Mach numbers) by identifying a parsimonious system description with a high percent fit for cross-validated data.

An interactive computer code for calculation of gas-phase chemical equilibrium (EQLBRM)

NASA Technical Reports Server (NTRS)

Pratt, B. S.; Pratt, D. T.

1984-01-01

A user friendly, menu driven, interactive computer program known as EQLBRM which calculates the adiabatic equilibrium temperature and product composition resulting from the combustion of hydrocarbon fuels with air, at specified constant pressure and enthalpy is discussed. The program is developed primarily as an instructional tool to be run on small computers to allow the user to economically and efficiency explore the effects of varying fuel type, air/fuel ratio, inlet air and/or fuel temperature, and operating pressure on the performance of continuous combustion devices such as gas turbine combustors, Stirling engine burners, and power generation furnaces.

Quantum Monte Carlo for large chemical systems: implementing efficient strategies for petascale platforms and beyond.

PubMed

Scemama, Anthony; Caffarel, Michel; Oseret, Emmanuel; Jalby, William

2013-04-30

Various strategies to implement efficiently quantum Monte Carlo (QMC) simulations for large chemical systems are presented. These include: (i) the introduction of an efficient algorithm to calculate the computationally expensive Slater matrices. This novel scheme is based on the use of the highly localized character of atomic Gaussian basis functions (not the molecular orbitals as usually done), (ii) the possibility of keeping the memory footprint minimal, (iii) the important enhancement of single-core performance when efficient optimization tools are used, and (iv) the definition of a universal, dynamic, fault-tolerant, and load-balanced framework adapted to all kinds of computational platforms (massively parallel machines, clusters, or distributed grids). These strategies have been implemented in the QMC=Chem code developed at Toulouse and illustrated with numerical applications on small peptides of increasing sizes (158, 434, 1056, and 1731 electrons). Using 10-80 k computing cores of the Curie machine (GENCI-TGCC-CEA, France), QMC=Chem has been shown to be capable of running at the petascale level, thus demonstrating that for this machine a large part of the peak performance can be achieved. Implementation of large-scale QMC simulations for future exascale platforms with a comparable level of efficiency is expected to be feasible. Copyright © 2013 Wiley Periodicals, Inc.

DEVELOPMENTS IN GRworkbench

NASA Astrophysics Data System (ADS)

Moylan, Andrew; Scott, Susan M.; Searle, Anthony C.

2006-02-01

The software tool GRworkbench is an ongoing project in visual, numerical General Relativity at The Australian National University. Recently, GRworkbench has been significantly extended to facilitate numerical experimentation in analytically-defined space-times. The numerical differential geometric engine has been rewritten using functional programming techniques, enabling objects which are normally defined as functions in the formalism of differential geometry and General Relativity to be directly represented as function variables in the C++ code of GRworkbench. The new functional differential geometric engine allows for more accurate and efficient visualisation of objects in space-times and makes new, efficient computational techniques available. Motivated by the desire to investigate a recent scientific claim using GRworkbench, new tools for numerical experimentation have been implemented, allowing for the simulation of complex physical situations.

Edge control in a computer controlled optical surfacing process using a heterocercal tool influence function.

PubMed

Hu, Haixiang; Zhang, Xin; Ford, Virginia; Luo, Xiao; Qi, Erhui; Zeng, Xuefeng; Zhang, Xuejun

2016-11-14

Edge effect is regarded as one of the most difficult technical issues in a computer controlled optical surfacing (CCOS) process. Traditional opticians have to even up the consequences of the two following cases. Operating CCOS in a large overhang condition affects the accuracy of material removal, while in a small overhang condition, it achieves a more accurate performance, but leaves a narrow rolled-up edge, which takes time and effort to remove. In order to control the edge residuals in the latter case, we present a new concept of the 'heterocercal' tool influence function (TIF). Generated from compound motion equipment, this type of TIF can 'transfer' the material removal from the inner place to the edge, meanwhile maintaining the high accuracy and efficiency of CCOS. We call it the 'heterocercal' TIF, because of the inspiration from the heterocercal tails of sharks, whose upper lobe provides most of the explosive power. The heterocercal TIF was theoretically analyzed, and physically realized in CCOS facilities. Experimental and simulation results showed good agreement. It enables significant control of the edge effect and convergence of entire surface errors in large tool-to-mirror size-ratio conditions. This improvement will largely help manufacturing efficiency in some extremely large optical system projects, like the tertiary mirror of the Thirty Meter Telescope.

Computational Tools and Algorithms for Designing Customized Synthetic Genes

PubMed Central

Gould, Nathan; Hendy, Oliver; Papamichail, Dimitris

2014-01-01

Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein-coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review, we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations. PMID:25340050

Intelligent control system based on ARM for lithography tool

NASA Astrophysics Data System (ADS)

Chen, Changlong; Tang, Xiaoping; Hu, Song; Wang, Nan

2014-08-01

The control system of traditional lithography tool is based on PC and MCU. The PC handles the complex algorithm, human-computer interaction, and communicates with MCU via serial port; The MCU controls motors and electromagnetic valves, etc. This mode has shortcomings like big volume, high power consumption, and wasting of PC resource. In this paper, an embedded intelligent control system of lithography tool, based on ARM, is provided. The control system used S5PV210 as processor, completing the functions of PC in traditional lithography tool, and provided a good human-computer interaction by using LCD and capacitive touch screen. Using Android4.0.3 as operating system, the equipment provided a cool and easy UI which made the control more user-friendly, and implemented remote control and debug, pushing video information of product by network programming. As a result, it's convenient for equipment vendor to provide technical support for users. Finally, compared with traditional lithography tool, this design reduced the PC part, making the hardware resources efficiently used and reducing the cost and volume. Introducing embedded OS and the concepts in "The Internet of things" into the design of lithography tool can be a development trend.

CMOST: an open-source framework for the microsimulation of colorectal cancer screening strategies.

PubMed

Prakash, Meher K; Lang, Brian; Heinrich, Henriette; Valli, Piero V; Bauerfeind, Peter; Sonnenberg, Amnon; Beerenwinkel, Niko; Misselwitz, Benjamin

2017-06-05

Colorectal cancer (CRC) is a leading cause of cancer-related mortality. CRC incidence and mortality can be reduced by several screening strategies, including colonoscopy, but randomized CRC prevention trials face significant obstacles such as the need for large study populations with long follow-up. Therefore, CRC screening strategies will likely be designed and optimized based on computer simulations. Several computational microsimulation tools have been reported for estimating efficiency and cost-effectiveness of CRC prevention. However, none of these tools is publicly available. There is a need for an open source framework to answer practical questions including testing of new screening interventions and adapting findings to local conditions. We developed and implemented a new microsimulation model, Colon Modeling Open Source Tool (CMOST), for modeling the natural history of CRC, simulating the effects of CRC screening interventions, and calculating the resulting costs. CMOST facilitates automated parameter calibration against epidemiological adenoma prevalence and CRC incidence data. Predictions of CMOST were highly similar compared to a large endoscopic CRC prevention study as well as predictions of existing microsimulation models. We applied CMOST to calculate the optimal timing of a screening colonoscopy. CRC incidence and mortality are reduced most efficiently by a colonoscopy between the ages of 56 and 59; while discounted life years gained (LYG) is maximal at 49-50 years. With a dwell time of 13 years, the most cost-effective screening is at 59 years, at $17,211 discounted USD per LYG. While cost-efficiency varied according to dwell time it did not influence the optimal time point of screening interventions within the tested range. Predictions of CMOST are highly similar compared to a randomized CRC prevention trial as well as those of other microsimulation tools. This open source tool will enable health-economics analyses in for various countries, health-care scenarios and CRC prevention strategies. CMOST is freely available under the GNU General Public License at https://gitlab.com/misselwb/CMOST.

Online System for Faster Multipoint Linkage Analysis via Parallel Execution on Thousands of Personal Computers

PubMed Central

Silberstein, M.; Tzemach, A.; Dovgolevsky, N.; Fishelson, M.; Schuster, A.; Geiger, D.

2006-01-01

Computation of LOD scores is a valuable tool for mapping disease-susceptibility genes in the study of Mendelian and complex diseases. However, computation of exact multipoint likelihoods of large inbred pedigrees with extensive missing data is often beyond the capabilities of a single computer. We present a distributed system called “SUPERLINK-ONLINE,” for the computation of multipoint LOD scores of large inbred pedigrees. It achieves high performance via the efficient parallelization of the algorithms in SUPERLINK, a state-of-the-art serial program for these tasks, and through the use of the idle cycles of thousands of personal computers. The main algorithmic challenge has been to efficiently split a large task for distributed execution in a highly dynamic, nondedicated running environment. Notably, the system is available online, which allows computationally intensive analyses to be performed with no need for either the installation of software or the maintenance of a complicated distributed environment. As the system was being developed, it was extensively tested by collaborating medical centers worldwide on a variety of real data sets, some of which are presented in this article. PMID:16685644

Non-intrusive uncertainty quantification of computational fluid dynamics simulations: notes on the accuracy and efficiency

NASA Astrophysics Data System (ADS)

Zimoń, Małgorzata; Sawko, Robert; Emerson, David; Thompson, Christopher

2017-11-01

Uncertainty quantification (UQ) is increasingly becoming an indispensable tool for assessing the reliability of computational modelling. Efficient handling of stochastic inputs, such as boundary conditions, physical properties or geometry, increases the utility of model results significantly. We discuss the application of non-intrusive generalised polynomial chaos techniques in the context of fluid engineering simulations. Deterministic and Monte Carlo integration rules are applied to a set of problems, including ordinary differential equations and the computation of aerodynamic parameters subject to random perturbations. In particular, we analyse acoustic wave propagation in a heterogeneous medium to study the effects of mesh resolution, transients, number and variability of stochastic inputs. We consider variants of multi-level Monte Carlo and perform a novel comparison of the methods with respect to numerical and parametric errors, as well as computational cost. The results provide a comprehensive view of the necessary steps in UQ analysis and demonstrate some key features of stochastic fluid flow systems.

VOFTools - A software package of calculation tools for volume of fluid methods using general convex grids

NASA Astrophysics Data System (ADS)

López, J.; Hernández, J.; Gómez, P.; Faura, F.

2018-02-01

The VOFTools library includes efficient analytical and geometrical routines for (1) area/volume computation, (2) truncation operations that typically arise in VOF (volume of fluid) methods, (3) area/volume conservation enforcement (VCE) in PLIC (piecewise linear interface calculation) reconstruction and(4) computation of the distance from a given point to the reconstructed interface. The computation of a polyhedron volume uses an efficient formula based on a quadrilateral decomposition and a 2D projection of each polyhedron face. The analytical VCE method is based on coupling an interpolation procedure to bracket the solution with an improved final calculation step based on the above volume computation formula. Although the library was originally created to help develop highly accurate advection and reconstruction schemes in the context of VOF methods, it may have more general applications. To assess the performance of the supplied routines, different tests, which are provided in FORTRAN and C, were implemented for several 2D and 3D geometries.

Development and Validation of a Monte Carlo Simulation Tool for Multi-Pinhole SPECT

PubMed Central

Mok, Greta S. P.; Du, Yong; Wang, Yuchuan; Frey, Eric C.; Tsui, Benjamin M. W.

2011-01-01

Purpose In this work, we developed and validated a Monte Carlo simulation (MCS) tool for investigation and evaluation of multi-pinhole (MPH) SPECT imaging. Procedures This tool was based on a combination of the SimSET and MCNP codes. Photon attenuation and scatter in the object, as well as penetration and scatter through the collimator detector, are modeled in this tool. It allows accurate and efficient simulation of MPH SPECT with focused pinhole apertures and user-specified photon energy, aperture material, and imaging geometry. The MCS method was validated by comparing the point response function (PRF), detection efficiency (DE), and image profiles obtained from point sources and phantom experiments. A prototype single-pinhole collimator and focused four- and five-pinhole collimators fitted on a small animal imager were used for the experimental validations. We have also compared computational speed among various simulation tools for MPH SPECT, including SimSET-MCNP, MCNP, SimSET-GATE, and GATE for simulating projections of a hot sphere phantom. Results We found good agreement between the MCS and experimental results for PRF, DE, and image profiles, indicating the validity of the simulation method. The relative computational speeds for SimSET-MCNP, MCNP, SimSET-GATE, and GATE are 1: 2.73: 3.54: 7.34, respectively, for 120-view simulations. We also demonstrated the application of this MCS tool in small animal imaging by generating a set of low-noise MPH projection data of a 3D digital mouse whole body phantom. Conclusions The new method is useful for studying MPH collimator designs, data acquisition protocols, image reconstructions, and compensation techniques. It also has great potential to be applied for modeling the collimator-detector response with penetration and scatter effects for MPH in the quantitative reconstruction method. PMID:19779896

Electronic tools for infectious diseases and microbiology

PubMed Central

Burdette, Steven D

2007-01-01

Electronic tools for infectious diseases and medical microbiology have the ability to change the way the diagnosis and treatment of infectious diseases are approached. Medical information today has the ability to be dynamic, keeping up with the latest research or clinical issues, instead of being static and years behind, as many textbooks are. The ability to rapidly disseminate information around the world opens up the possibility of communicating with people thousands of miles away to quickly and efficiently learn about emerging infections. Electronic tools have expanded beyond the desktop computer and the Internet, and now include personal digital assistants and other portable devices such as cellular phones. These pocket-sized devices have the ability to provide access to clinical information at the point of care. New electronic tools include e-mail listservs, electronic drug databases and search engines that allow focused clinical questions. The goal of the present article is to provide an overview of how electronic tools can impact infectious diseases and microbiology, while providing links and resources to allow users to maximize their efficiency in accessing this information. Links to the mentioned Web sites and programs are provided along with other useful electronic tools. PMID:18978984

Managing Information On Technical Requirements

NASA Technical Reports Server (NTRS)

Mauldin, Lemuel E., III; Hammond, Dana P.

1993-01-01

Technical Requirements Analysis and Control Systems/Initial Operating Capability (TRACS/IOC) computer program provides supplemental software tools for analysis, control, and interchange of project requirements so qualified project members have access to pertinent project information, even if in different locations. Enables users to analyze and control requirements, serves as focal point for project requirements, and integrates system supporting efficient and consistent operations. TRACS/IOC is HyperCard stack for use on Macintosh computers running HyperCard 1.2 or later and Oracle 1.2 or later.

Combinatorial-topological framework for the analysis of global dynamics.

PubMed

Bush, Justin; Gameiro, Marcio; Harker, Shaun; Kokubu, Hiroshi; Mischaikow, Konstantin; Obayashi, Ippei; Pilarczyk, Paweł

2012-12-01

We discuss an algorithmic framework based on efficient graph algorithms and algebraic-topological computational tools. The framework is aimed at automatic computation of a database of global dynamics of a given m-parameter semidynamical system with discrete time on a bounded subset of the n-dimensional phase space. We introduce the mathematical background, which is based upon Conley's topological approach to dynamics, describe the algorithms for the analysis of the dynamics using rectangular grids both in phase space and parameter space, and show two sample applications.

Combinatorial-topological framework for the analysis of global dynamics

NASA Astrophysics Data System (ADS)

Bush, Justin; Gameiro, Marcio; Harker, Shaun; Kokubu, Hiroshi; Mischaikow, Konstantin; Obayashi, Ippei; Pilarczyk, Paweł

2012-12-01

We discuss an algorithmic framework based on efficient graph algorithms and algebraic-topological computational tools. The framework is aimed at automatic computation of a database of global dynamics of a given m-parameter semidynamical system with discrete time on a bounded subset of the n-dimensional phase space. We introduce the mathematical background, which is based upon Conley's topological approach to dynamics, describe the algorithms for the analysis of the dynamics using rectangular grids both in phase space and parameter space, and show two sample applications.

Organization and use of a Software/Hardware Avionics Research Program (SHARP)

NASA Technical Reports Server (NTRS)

Karmarkar, J. S.; Kareemi, M. N.

1975-01-01

The organization and use is described of the software/hardware avionics research program (SHARP) developed to duplicate the automatic portion of the STOLAND simulator system, on a general-purpose computer system (i.e., IBM 360). The program's uses are: (1) to conduct comparative evaluation studies of current and proposed airborne and ground system concepts via single run or Monte Carlo simulation techniques, and (2) to provide a software tool for efficient algorithm evaluation and development for the STOLAND avionics computer.

A Computationally Efficient Parallel Levenberg-Marquardt Algorithm for Large-Scale Big-Data Inversion

NASA Astrophysics Data System (ADS)

Lin, Y.; O'Malley, D.; Vesselinov, V. V.

2015-12-01

Inverse modeling seeks model parameters given a set of observed state variables. However, for many practical problems due to the facts that the observed data sets are often large and model parameters are often numerous, conventional methods for solving the inverse modeling can be computationally expensive. We have developed a new, computationally-efficient Levenberg-Marquardt method for solving large-scale inverse modeling. Levenberg-Marquardt methods require the solution of a dense linear system of equations which can be prohibitively expensive to compute for large-scale inverse problems. Our novel method projects the original large-scale linear problem down to a Krylov subspace, such that the dimensionality of the measurements can be significantly reduced. Furthermore, instead of solving the linear system for every Levenberg-Marquardt damping parameter, we store the Krylov subspace computed when solving the first damping parameter and recycle it for all the following damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved by using these computational techniques. We apply this new inverse modeling method to invert for a random transitivity field. Our algorithm is fast enough to solve for the distributed model parameters (transitivity) at each computational node in the model domain. The inversion is also aided by the use regularization techniques. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). Julia is an advanced high-level scientific programing language that allows for efficient memory management and utilization of high-performance computational resources. By comparing with a Levenberg-Marquardt method using standard linear inversion techniques, our Levenberg-Marquardt method yields speed-up ratio of 15 in a multi-core computational environment and a speed-up ratio of 45 in a single-core computational environment. Therefore, our new inverse modeling method is a powerful tool for large-scale applications.

Computation of Reacting Flows in Combustion Processes

NASA Technical Reports Server (NTRS)

Keith, Theo G., Jr.; Chen, Kuo-Huey

1997-01-01

The main objective of this research was to develop an efficient three-dimensional computer code for chemically reacting flows. The main computer code developed is ALLSPD-3D. The ALLSPD-3D computer program is developed for the calculation of three-dimensional, chemically reacting flows with sprays. The ALL-SPD code employs a coupled, strongly implicit solution procedure for turbulent spray combustion flows. A stochastic droplet model and an efficient method for treatment of the spray source terms in the gas-phase equations are used to calculate the evaporating liquid sprays. The chemistry treatment in the code is general enough that an arbitrary number of reaction and species can be defined by the users. Also, it is written in generalized curvilinear coordinates with both multi-block and flexible internal blockage capabilities to handle complex geometries. In addition, for general industrial combustion applications, the code provides both dilution and transpiration cooling capabilities. The ALLSPD algorithm, which employs the preconditioning and eigenvalue rescaling techniques, is capable of providing efficient solution for flows with a wide range of Mach numbers. Although written for three-dimensional flows in general, the code can be used for two-dimensional and axisymmetric flow computations as well. The code is written in such a way that it can be run in various computer platforms (supercomputers, workstations and parallel processors) and the GUI (Graphical User Interface) should provide a user-friendly tool in setting up and running the code.

G‐LoSA: An efficient computational tool for local structure‐centric biological studies and drug design

PubMed Central

2016-01-01

Abstract Molecular recognition by protein mostly occurs in a local region on the protein surface. Thus, an efficient computational method for accurate characterization of protein local structural conservation is necessary to better understand biology and drug design. We present a novel local structure alignment tool, G‐LoSA. G‐LoSA aligns protein local structures in a sequence order independent way and provides a GA‐score, a chemical feature‐based and size‐independent structure similarity score. Our benchmark validation shows the robust performance of G‐LoSA to the local structures of diverse sizes and characteristics, demonstrating its universal applicability to local structure‐centric comparative biology studies. In particular, G‐LoSA is highly effective in detecting conserved local regions on the entire surface of a given protein. In addition, the applications of G‐LoSA to identifying template ligands and predicting ligand and protein binding sites illustrate its strong potential for computer‐aided drug design. We hope that G‐LoSA can be a useful computational method for exploring interesting biological problems through large‐scale comparison of protein local structures and facilitating drug discovery research and development. G‐LoSA is freely available to academic users at http://im.compbio.ku.edu/GLoSA/. PMID:26813336

A supportive architecture for CFD-based design optimisation

NASA Astrophysics Data System (ADS)

Li, Ni; Su, Zeya; Bi, Zhuming; Tian, Chao; Ren, Zhiming; Gong, Guanghong

2014-03-01

Multi-disciplinary design optimisation (MDO) is one of critical methodologies to the implementation of enterprise systems (ES). MDO requiring the analysis of fluid dynamics raises a special challenge due to its extremely intensive computation. The rapid development of computational fluid dynamic (CFD) technique has caused a rise of its applications in various fields. Especially for the exterior designs of vehicles, CFD has become one of the three main design tools comparable to analytical approaches and wind tunnel experiments. CFD-based design optimisation is an effective way to achieve the desired performance under the given constraints. However, due to the complexity of CFD, integrating with CFD analysis in an intelligent optimisation algorithm is not straightforward. It is a challenge to solve a CFD-based design problem, which is usually with high dimensions, and multiple objectives and constraints. It is desirable to have an integrated architecture for CFD-based design optimisation. However, our review on existing works has found that very few researchers have studied on the assistive tools to facilitate CFD-based design optimisation. In the paper, a multi-layer architecture and a general procedure are proposed to integrate different CFD toolsets with intelligent optimisation algorithms, parallel computing technique and other techniques for efficient computation. In the proposed architecture, the integration is performed either at the code level or data level to fully utilise the capabilities of different assistive tools. Two intelligent algorithms are developed and embedded with parallel computing. These algorithms, together with the supportive architecture, lay a solid foundation for various applications of CFD-based design optimisation. To illustrate the effectiveness of the proposed architecture and algorithms, the case studies on aerodynamic shape design of a hypersonic cruising vehicle are provided, and the result has shown that the proposed architecture and developed algorithms have performed successfully and efficiently in dealing with the design optimisation with over 200 design variables.

Perspectives in astrophysical databases

NASA Astrophysics Data System (ADS)

Frailis, Marco; de Angelis, Alessandro; Roberto, Vito

2004-07-01

Astrophysics has become a domain extremely rich of scientific data. Data mining tools are needed for information extraction from such large data sets. This asks for an approach to data management emphasizing the efficiency and simplicity of data access; efficiency is obtained using multidimensional access methods and simplicity is achieved by properly handling metadata. Moreover, clustering and classification techniques on large data sets pose additional requirements in terms of computation and memory scalability and interpretability of results. In this study we review some possible solutions.

Design and Development of ChemInfoCloud: An Integrated Cloud Enabled Platform for Virtual Screening.

PubMed

Karthikeyan, Muthukumarasamy; Pandit, Deepak; Bhavasar, Arvind; Vyas, Renu

2015-01-01

The power of cloud computing and distributed computing has been harnessed to handle vast and heterogeneous data required to be processed in any virtual screening protocol. A cloud computing platorm ChemInfoCloud was built and integrated with several chemoinformatics and bioinformatics tools. The robust engine performs the core chemoinformatics tasks of lead generation, lead optimisation and property prediction in a fast and efficient manner. It has also been provided with some of the bioinformatics functionalities including sequence alignment, active site pose prediction and protein ligand docking. Text mining, NMR chemical shift (1H, 13C) prediction and reaction fingerprint generation modules for efficient lead discovery are also implemented in this platform. We have developed an integrated problem solving cloud environment for virtual screening studies that also provides workflow management, better usability and interaction with end users using container based virtualization, OpenVz.

A computationally efficient description of heterogeneous freezing: A simplified version of the Soccer ball model

NASA Astrophysics Data System (ADS)

Niedermeier, Dennis; Ervens, Barbara; Clauss, Tina; Voigtländer, Jens; Wex, Heike; Hartmann, Susan; Stratmann, Frank

2014-01-01

In a recent study, the Soccer ball model (SBM) was introduced for modeling and/or parameterizing heterogeneous ice nucleation processes. The model applies classical nucleation theory. It allows for a consistent description of both apparently singular and stochastic ice nucleation behavior, by distributing contact angles over the nucleation sites of a particle population assuming a Gaussian probability density function. The original SBM utilizes the Monte Carlo technique, which hampers its usage in atmospheric models, as fairly time-consuming calculations must be performed to obtain statistically significant results. Thus, we have developed a simplified and computationally more efficient version of the SBM. We successfully used the new SBM to parameterize experimental nucleation data of, e.g., bacterial ice nucleation. Both SBMs give identical results; however, the new model is computationally less expensive as confirmed by cloud parcel simulations. Therefore, it is a suitable tool for describing heterogeneous ice nucleation processes in atmospheric models.

An accurate and efficient reliability-based design optimization using the second order reliability method and improved stability transformation method

NASA Astrophysics Data System (ADS)

Meng, Zeng; Yang, Dixiong; Zhou, Huanlin; Yu, Bo

2018-05-01

The first order reliability method has been extensively adopted for reliability-based design optimization (RBDO), but it shows inaccuracy in calculating the failure probability with highly nonlinear performance functions. Thus, the second order reliability method is required to evaluate the reliability accurately. However, its application for RBDO is quite challenge owing to the expensive computational cost incurred by the repeated reliability evaluation and Hessian calculation of probabilistic constraints. In this article, a new improved stability transformation method is proposed to search the most probable point efficiently, and the Hessian matrix is calculated by the symmetric rank-one update. The computational capability of the proposed method is illustrated and compared to the existing RBDO approaches through three mathematical and two engineering examples. The comparison results indicate that the proposed method is very efficient and accurate, providing an alternative tool for RBDO of engineering structures.

An efficient algorithm for computing fixed length attractors based on bounded model checking in synchronous Boolean networks with biochemical applications.

PubMed

Li, X Y; Yang, G W; Zheng, D S; Guo, W S; Hung, W N N

2015-04-28

Genetic regulatory networks are the key to understanding biochemical systems. One condition of the genetic regulatory network under different living environments can be modeled as a synchronous Boolean network. The attractors of these Boolean networks will help biologists to identify determinant and stable factors. Existing methods identify attractors based on a random initial state or the entire state simultaneously. They cannot identify the fixed length attractors directly. The complexity of including time increases exponentially with respect to the attractor number and length of attractors. This study used the bounded model checking to quickly locate fixed length attractors. Based on the SAT solver, we propose a new algorithm for efficiently computing the fixed length attractors, which is more suitable for large Boolean networks and numerous attractors' networks. After comparison using the tool BooleNet, empirical experiments involving biochemical systems demonstrated the feasibility and efficiency of our approach.

Energy efficiency analysis and optimization for mobile platforms

NASA Astrophysics Data System (ADS)

Metri, Grace Camille

The introduction of mobile devices changed the landscape of computing. Gradually, these devices are replacing traditional personal computer (PCs) to become the devices of choice for entertainment, connectivity, and productivity. There are currently at least 45.5 million people in the United States who own a mobile device, and that number is expected to increase to 1.5 billion by 2015. Users of mobile devices expect and mandate that their mobile devices have maximized performance while consuming minimal possible power. However, due to the battery size constraints, the amount of energy stored in these devices is limited and is only growing by 5% annually. As a result, we focused in this dissertation on energy efficiency analysis and optimization for mobile platforms. We specifically developed SoftPowerMon, a tool that can power profile Android platforms in order to expose the power consumption behavior of the CPU. We also performed an extensive set of case studies in order to determine energy inefficiencies of mobile applications. Through our case studies, we were able to propose optimization techniques in order to increase the energy efficiency of mobile devices and proposed guidelines for energy-efficient application development. In addition, we developed BatteryExtender, an adaptive user-guided tool for power management of mobile devices. The tool enables users to extend battery life on demand for a specific duration until a particular task is completed. Moreover, we examined the power consumption of System-on-Chips (SoCs) and observed the impact on the energy efficiency in the event of offloading tasks from the CPU to the specialized custom engines. Based on our case studies, we were able to demonstrate that current software-based power profiling techniques for SoCs can have an error rate close to 12%, which needs to be addressed in order to be able to optimize the energy consumption of the SoC. Finally, we summarize our contributions and outline possible direction for future research in this field.

Supporting Blended-Learning: Tool Requirements and Solutions with OWLish

ERIC Educational Resources Information Center

Álvarez, Ainhoa; Martín, Maite; Fernández-Castro, Isabel; Urretavizcaya, Maite

2016-01-01

Currently, most of the educational approaches applied to higher education combine face-to-face (F2F) and computer-mediated instruction in a Blended-Learning (B-Learning) approach. One of the main challenges of these approaches is fully integrating the traditional brick-and-mortar classes with online learning environments in an efficient and…

Domain-Specific QSAR Models for Identifying Potential Estrogenic Activity of Phenols (FutureTox III)

EPA Science Inventory

Computational tools can be used for efficient evaluation of untested chemicals for their ability to disrupt the endocrine system. We have employed previously developed global QSAR models that were trained and validated on the ToxCast/Tox21 ER assay data for virtual screening of a...

Information Communication Technology Policy and Public Primary Schools' Efficiency in Rwanda

ERIC Educational Resources Information Center

Munyengabe, Sylvestre; Haiyan, He; Yiyi, Zhao

2018-01-01

Teaching and learning processes have been developed through different methods and materials; nowadays the introduction of computers and other ICT tools in different forms and levels of education have been found to be highly influential in education system of different countries. The main objective of this study was to correlate Information…

Isolated Open Rotor Noise Prediction Assessment Using the F31A31 Historical Blade Set

NASA Technical Reports Server (NTRS)

Nark, Douglas M.; Jones, William T.; Boyd, D. Douglas, Jr.; Zawodny, Nikolas S.

2016-01-01

In an effort to mitigate next-generation fuel efficiency and environmental impact concerns for aviation, open rotor propulsion systems have received renewed interest. However, maintaining the high propulsive efficiency while simultaneously meeting noise goals has been one of the challenges in making open rotor propulsion a viable option. Improvements in prediction tools and design methodologies have opened the design space for next generation open rotor designs that satisfy these challenging objectives. As such, validation of aerodynamic and acoustic prediction tools has been an important aspect of open rotor research efforts. This paper describes validation efforts of a combined computational fluid dynamics and Ffowcs Williams and Hawkings equation methodology for open rotor aeroacoustic modeling. Performance and acoustic predictions were made for a benchmark open rotor blade set and compared with measurements over a range of rotor speeds and observer angles. Overall, the results indicate that the computational approach is acceptable for assessing low-noise open rotor designs. Additionally, this approach may be used to provide realistic incident source fields for acoustic shielding/scattering studies on various aircraft configurations.

Comparison of Implicit Schemes for the Incompressible Navier-Stokes Equations

NASA Technical Reports Server (NTRS)

Rogers, Stuart E.

1995-01-01

For a computational flow simulation tool to be useful in a design environment, it must be very robust and efficient. To develop such a tool for incompressible flow applications, a number of different implicit schemes are compared for several two-dimensional flow problems in the current study. The schemes include Point-Jacobi relaxation, Gauss-Seidel line relaxation, incomplete lower-upper decomposition, and the generalized minimum residual method preconditioned with each of the three other schemes. The efficiency of the schemes is measured in terms of the computing time required to obtain a steady-state solution for the laminar flow over a backward-facing step, the flow over a NACA 4412 airfoil, and the flow over a three-element airfoil using overset grids. The flow solver used in the study is the INS2D code that solves the incompressible Navier-Stokes equations using the method of artificial compressibility and upwind differencing of the convective terms. The results show that the generalized minimum residual method preconditioned with the incomplete lower-upper factorization outperforms all other methods by at least a factor of 2.

An efficient implementation of 3D high-resolution imaging for large-scale seismic data with GPU/CPU heterogeneous parallel computing

NASA Astrophysics Data System (ADS)

Xu, Jincheng; Liu, Wei; Wang, Jin; Liu, Linong; Zhang, Jianfeng

2018-02-01

De-absorption pre-stack time migration (QPSTM) compensates for the absorption and dispersion of seismic waves by introducing an effective Q parameter, thereby making it an effective tool for 3D, high-resolution imaging of seismic data. Although the optimal aperture obtained via stationary-phase migration reduces the computational cost of 3D QPSTM and yields 3D stationary-phase QPSTM, the associated computational efficiency is still the main problem in the processing of 3D, high-resolution images for real large-scale seismic data. In the current paper, we proposed a division method for large-scale, 3D seismic data to optimize the performance of stationary-phase QPSTM on clusters of graphics processing units (GPU). Then, we designed an imaging point parallel strategy to achieve an optimal parallel computing performance. Afterward, we adopted an asynchronous double buffering scheme for multi-stream to perform the GPU/CPU parallel computing. Moreover, several key optimization strategies of computation and storage based on the compute unified device architecture (CUDA) were adopted to accelerate the 3D stationary-phase QPSTM algorithm. Compared with the initial GPU code, the implementation of the key optimization steps, including thread optimization, shared memory optimization, register optimization and special function units (SFU), greatly improved the efficiency. A numerical example employing real large-scale, 3D seismic data showed that our scheme is nearly 80 times faster than the CPU-QPSTM algorithm. Our GPU/CPU heterogeneous parallel computing framework significant reduces the computational cost and facilitates 3D high-resolution imaging for large-scale seismic data.

Development of a computer code for calculating the steady super/hypersonic inviscid flow around real configurations. Volume 2: Code description

NASA Technical Reports Server (NTRS)

Marconi, F.; Yaeger, L.

1976-01-01

A numerical procedure was developed to compute the inviscid super/hypersonic flow field about complex vehicle geometries accurately and efficiently. A second-order accurate finite difference scheme is used to integrate the three-dimensional Euler equations in regions of continuous flow, while all shock waves are computed as discontinuities via the Rankine-Hugoniot jump conditions. Conformal mappings are used to develop a computational grid. The effects of blunt nose entropy layers are computed in detail. Real gas effects for equilibrium air are included using curve fits of Mollier charts. Typical calculated results for shuttle orbiter, hypersonic transport, and supersonic aircraft configurations are included to demonstrate the usefulness of this tool.

Interoperability of GADU in using heterogeneous Grid resources for bioinformatics applications.

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

Sulakhe, D.; Rodriguez, A.; Wilde, M.

2008-03-01

Bioinformatics tools used for efficient and computationally intensive analysis of genetic sequences require large-scale computational resources to accommodate the growing data. Grid computational resources such as the Open Science Grid and TeraGrid have proved useful for scientific discovery. The genome analysis and database update system (GADU) is a high-throughput computational system developed to automate the steps involved in accessing the Grid resources for running bioinformatics applications. This paper describes the requirements for building an automated scalable system such as GADU that can run jobs on different Grids. The paper describes the resource-independent configuration of GADU using the Pegasus-based virtual datamore » system that makes high-throughput computational tools interoperable on heterogeneous Grid resources. The paper also highlights the features implemented to make GADU a gateway to computationally intensive bioinformatics applications on the Grid. The paper will not go into the details of problems involved or the lessons learned in using individual Grid resources as it has already been published in our paper on genome analysis research environment (GNARE) and will focus primarily on the architecture that makes GADU resource independent and interoperable across heterogeneous Grid resources.« less

Tablet computers in assessing performance in a high stakes exam: opinion matters.

PubMed

Currie, G P; Sinha, S; Thomson, F; Cleland, J; Denison, A R

2017-06-01

Background Tablet computers have emerged as a tool to capture, process and store data in examinations, yet evidence relating to their acceptability and usefulness in assessment is limited. Methods We performed an observational study to explore opinions and attitudes relating to tablet computer use in recording performance in a final year objective structured clinical examination at a single UK medical school. Examiners completed a short questionnaire encompassing background, forced-choice and open questions. Forced choice questions were analysed using descriptive statistics and open questions by framework analysis. Results Ninety-two (97% response rate) examiners completed the questionnaire of whom 85% had previous use of tablet computers. Ninety per cent felt checklist mark allocation was 'very/quite easy', while approximately half considered recording 'free-type' comments was 'easy/very easy'. Greater overall efficiency of marking and resource savings were considered the main advantages of tablet computers, while concerns relating to technological failure and ability to record free type comments were raised. Discussion In a context where examiners were familiar with tablet computers, they were preferred to paper checklists, although concerns were raised. This study adds to the limited literature underpinning the use of electronic devices as acceptable tools in objective structured clinical examinations.

Designing overall stoichiometric conversions and intervening metabolic reactions

DOE PAGES

Chowdhury, Anupam; Maranas, Costas D.

2015-11-04

Existing computational tools for de novo metabolic pathway assembly, either based on mixed integer linear programming techniques or graph-search applications, generally only find linear pathways connecting the source to the target metabolite. The overall stoichiometry of conversion along with alternate co-reactant (or co-product) combinations is not part of the pathway design. Therefore, global carbon and energy efficiency is in essence fixed with no opportunities to identify more efficient routes for recycling carbon flux closer to the thermodynamic limit. Here, we introduce a two-stage computational procedure that both identifies the optimum overall stoichiometry (i.e., optStoic) and selects for (non-)native reactions (i.e.,more » minRxn/minFlux) that maximize carbon, energy or price efficiency while satisfying thermodynamic feasibility requirements. Implementation for recent pathway design studies identified non-intuitive designs with improved efficiencies. Specifically, multiple alternatives for non-oxidative glycolysis are generated and non-intuitive ways of co-utilizing carbon dioxide with methanol are revealed for the production of C 2+ metabolites with higher carbon efficiency.« less

Light-weight Parallel Python Tools for Earth System Modeling Workflows

NASA Astrophysics Data System (ADS)

Mickelson, S. A.; Paul, K.; Xu, H.; Dennis, J.; Brown, D. I.

2015-12-01

With the growth in computing power over the last 30 years, earth system modeling codes have become increasingly data-intensive. As an example, it is expected that the data required for the next Intergovernmental Panel on Climate Change (IPCC) Assessment Report (AR6) will increase by more than 10x to an expected 25PB per climate model. Faced with this daunting challenge, developers of the Community Earth System Model (CESM) have chosen to change the format of their data for long-term storage from time-slice to time-series, in order to reduce the required download bandwidth needed for later analysis and post-processing by climate scientists. Hence, efficient tools are required to (1) perform the transformation of the data from time-slice to time-series format and to (2) compute climatology statistics, needed for many diagnostic computations, on the resulting time-series data. To address the first of these two challenges, we have developed a parallel Python tool for converting time-slice model output to time-series format. To address the second of these challenges, we have developed a parallel Python tool to perform fast time-averaging of time-series data. These tools are designed to be light-weight, be easy to install, have very few dependencies, and can be easily inserted into the Earth system modeling workflow with negligible disruption. In this work, we present the motivation, approach, and testing results of these two light-weight parallel Python tools, as well as our plans for future research and development.

Approximate, computationally efficient online learning in Bayesian spiking neurons.

PubMed

Kuhlmann, Levin; Hauser-Raspe, Michael; Manton, Jonathan H; Grayden, David B; Tapson, Jonathan; van Schaik, André

2014-03-01

Bayesian spiking neurons (BSNs) provide a probabilistic interpretation of how neurons perform inference and learning. Online learning in BSNs typically involves parameter estimation based on maximum-likelihood expectation-maximization (ML-EM) which is computationally slow and limits the potential of studying networks of BSNs. An online learning algorithm, fast learning (FL), is presented that is more computationally efficient than the benchmark ML-EM for a fixed number of time steps as the number of inputs to a BSN increases (e.g., 16.5 times faster run times for 20 inputs). Although ML-EM appears to converge 2.0 to 3.6 times faster than FL, the computational cost of ML-EM means that ML-EM takes longer to simulate to convergence than FL. FL also provides reasonable convergence performance that is robust to initialization of parameter estimates that are far from the true parameter values. However, parameter estimation depends on the range of true parameter values. Nevertheless, for a physiologically meaningful range of parameter values, FL gives very good average estimation accuracy, despite its approximate nature. The FL algorithm therefore provides an efficient tool, complementary to ML-EM, for exploring BSN networks in more detail in order to better understand their biological relevance. Moreover, the simplicity of the FL algorithm means it can be easily implemented in neuromorphic VLSI such that one can take advantage of the energy-efficient spike coding of BSNs.

Neuroimaging Study Designs, Computational Analyses and Data Provenance Using the LONI Pipeline

PubMed Central

Dinov, Ivo; Lozev, Kamen; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Pierce, Jonathan; Zamanyan, Alen; Chakrapani, Shruthi; Van Horn, John; Parker, D. Stott; Magsipoc, Rico; Leung, Kelvin; Gutman, Boris; Woods, Roger; Toga, Arthur

2010-01-01

Modern computational neuroscience employs diverse software tools and multidisciplinary expertise to analyze heterogeneous brain data. The classical problems of gathering meaningful data, fitting specific models, and discovering appropriate analysis and visualization tools give way to a new class of computational challenges—management of large and incongruous data, integration and interoperability of computational resources, and data provenance. We designed, implemented and validated a new paradigm for addressing these challenges in the neuroimaging field. Our solution is based on the LONI Pipeline environment [3], [4], a graphical workflow environment for constructing and executing complex data processing protocols. We developed study-design, database and visual language programming functionalities within the LONI Pipeline that enable the construction of complete, elaborate and robust graphical workflows for analyzing neuroimaging and other data. These workflows facilitate open sharing and communication of data and metadata, concrete processing protocols, result validation, and study replication among different investigators and research groups. The LONI Pipeline features include distributed grid-enabled infrastructure, virtualized execution environment, efficient integration, data provenance, validation and distribution of new computational tools, automated data format conversion, and an intuitive graphical user interface. We demonstrate the new LONI Pipeline features using large scale neuroimaging studies based on data from the International Consortium for Brain Mapping [5] and the Alzheimer's Disease Neuroimaging Initiative [6]. User guides, forums, instructions and downloads of the LONI Pipeline environment are available at http://pipeline.loni.ucla.edu. PMID:20927408

Computational Design and Discovery of Ni-Based Alloys and Coatings: Thermodynamic Approaches Validated by Experiments

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

Liu, Zi-Kui; Gleeson, Brian; Shang, Shunli

This project developed computational tools that can complement and support experimental efforts in order to enable discovery and more efficient development of Ni-base structural materials and coatings. The project goal was reached through an integrated computation-predictive and experimental-validation approach, including first-principles calculations, thermodynamic CALPHAD (CALculation of PHAse Diagram), and experimental investigations on compositions relevant to Ni-base superalloys and coatings in terms of oxide layer growth and microstructure stabilities. The developed description included composition ranges typical for coating alloys and, hence, allow for prediction of thermodynamic properties for these material systems. The calculation of phase compositions, phase fraction, and phase stabilities,more » which are directly related to properties such as ductility and strength, was a valuable contribution, along with the collection of computational tools that are required to meet the increasing demands for strong, ductile and environmentally-protective coatings. Specifically, a suitable thermodynamic description for the Ni-Al-Cr-Co-Si-Hf-Y system was developed for bulk alloy and coating compositions. Experiments were performed to validate and refine the thermodynamics from the CALPHAD modeling approach. Additionally, alloys produced using predictions from the current computational models were studied in terms of their oxidation performance. Finally, results obtained from experiments aided in the development of a thermodynamic modeling automation tool called ESPEI/pycalphad - for more rapid discovery and development of new materials.« less

Computer-aided design for metabolic engineering.

PubMed

Fernández-Castané, Alfred; Fehér, Tamás; Carbonell, Pablo; Pauthenier, Cyrille; Faulon, Jean-Loup

2014-12-20

The development and application of biotechnology-based strategies has had a great socio-economical impact and is likely to play a crucial role in the foundation of more sustainable and efficient industrial processes. Within biotechnology, metabolic engineering aims at the directed improvement of cellular properties, often with the goal of synthesizing a target chemical compound. The use of computer-aided design (CAD) tools, along with the continuously emerging advanced genetic engineering techniques have allowed metabolic engineering to broaden and streamline the process of heterologous compound-production. In this work, we review the CAD tools available for metabolic engineering with an emphasis, on retrosynthesis methodologies. Recent advances in genetic engineering strategies for pathway implementation and optimization are also reviewed as well as a range of bionalytical tools to validate in silico predictions. A case study applying retrosynthesis is presented as an experimental verification of the output from Retropath, the first complete automated computational pipeline applicable to metabolic engineering. Applying this CAD pipeline, together with genetic reassembly and optimization of culture conditions led to improved production of the plant flavonoid pinocembrin. Coupling CAD tools with advanced genetic engineering strategies and bioprocess optimization is crucial for enhanced product yields and will be of great value for the development of non-natural products through sustainable biotechnological processes. Copyright © 2014 Elsevier B.V. All rights reserved.

SCALING AN URBAN EMERGENCY EVACUATION FRAMEWORK: CHALLENGES AND PRACTICES

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

Karthik, Rajasekar; Lu, Wei

2014-01-01

Critical infrastructure disruption, caused by severe weather events, natural disasters, terrorist attacks, etc., has significant impacts on urban transportation systems. We built a computational framework to simulate urban transportation systems under critical infrastructure disruption in order to aid real-time emergency evacuation. This framework will use large scale datasets to provide a scalable tool for emergency planning and management. Our framework, World-Wide Emergency Evacuation (WWEE), integrates population distribution and urban infrastructure networks to model travel demand in emergency situations at global level. Also, a computational model of agent-based traffic simulation is used to provide an optimal evacuation plan for traffic operationmore » purpose [1]. In addition, our framework provides a web-based high resolution visualization tool for emergency evacuation modelers and practitioners. We have successfully tested our framework with scenarios in both United States (Alexandria, VA) and Europe (Berlin, Germany) [2]. However, there are still some major drawbacks for scaling this framework to handle big data workloads in real time. On our back-end, lack of proper infrastructure limits us in ability to process large amounts of data, run the simulation efficiently and quickly, and provide fast retrieval and serving of data. On the front-end, the visualization performance of microscopic evacuation results is still not efficient enough due to high volume data communication between server and client. We are addressing these drawbacks by using cloud computing and next-generation web technologies, namely Node.js, NoSQL, WebGL, Open Layers 3 and HTML5 technologies. We will describe briefly about each one and how we are using and leveraging these technologies to provide an efficient tool for emergency management organizations. Our early experimentation demonstrates that using above technologies is a promising approach to build a scalable and high performance urban emergency evacuation framework that can improve traffic mobility and safety under critical infrastructure disruption in today s socially connected world.« less

Application of modern tools and techniques to maximize engineering productivity in the development of orbital operations plans for the space station progrm

NASA Technical Reports Server (NTRS)

Manford, J. S.; Bennett, G. R.

1985-01-01

The Space Station Program will incorporate analysis of operations constraints and considerations in the early design phases to avoid the need for later modifications to the Space Station for operations. The application of modern tools and administrative techniques to minimize the cost of performing effective orbital operations planning and design analysis in the preliminary design phase of the Space Station Program is discussed. Tools and techniques discussed include: approach for rigorous analysis of operations functions, use of the resources of a large computer network, and providing for efficient research and access to information.

An evolutionary computation based algorithm for calculating solar differential rotation by automatic tracking of coronal bright points

NASA Astrophysics Data System (ADS)

Shahamatnia, Ehsan; Dorotovič, Ivan; Fonseca, Jose M.; Ribeiro, Rita A.

2016-03-01

Developing specialized software tools is essential to support studies of solar activity evolution. With new space missions such as Solar Dynamics Observatory (SDO), solar images are being produced in unprecedented volumes. To capitalize on that huge data availability, the scientific community needs a new generation of software tools for automatic and efficient data processing. In this paper a prototype of a modular framework for solar feature detection, characterization, and tracking is presented. To develop an efficient system capable of automatic solar feature tracking and measuring, a hybrid approach combining specialized image processing, evolutionary optimization, and soft computing algorithms is being followed. The specialized hybrid algorithm for tracking solar features allows automatic feature tracking while gathering characterization details about the tracked features. The hybrid algorithm takes advantages of the snake model, a specialized image processing algorithm widely used in applications such as boundary delineation, image segmentation, and object tracking. Further, it exploits the flexibility and efficiency of Particle Swarm Optimization (PSO), a stochastic population based optimization algorithm. PSO has been used successfully in a wide range of applications including combinatorial optimization, control, clustering, robotics, scheduling, and image processing and video analysis applications. The proposed tool, denoted PSO-Snake model, was already successfully tested in other works for tracking sunspots and coronal bright points. In this work, we discuss the application of the PSO-Snake algorithm for calculating the sidereal rotational angular velocity of the solar corona. To validate the results we compare them with published manual results performed by an expert.

Computer Aided Battery Engineering Consortium

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

Pesaran, Ahmad

A multi-national lab collaborative team was assembled that includes experts from academia and industry to enhance recently developed Computer-Aided Battery Engineering for Electric Drive Vehicles (CAEBAT)-II battery crush modeling tools and to develop microstructure models for electrode design - both computationally efficient. Task 1. The new Multi-Scale Multi-Domain model framework (GH-MSMD) provides 100x to 1,000x computation speed-up in battery electrochemical/thermal simulation while retaining modularity of particles and electrode-, cell-, and pack-level domains. The increased speed enables direct use of the full model in parameter identification. Task 2. Mechanical-electrochemical-thermal (MECT) models for mechanical abuse simulation were simultaneously coupled, enabling simultaneous modelingmore » of electrochemical reactions during the short circuit, when necessary. The interactions between mechanical failure and battery cell performance were studied, and the flexibility of the model for various batteries structures and loading conditions was improved. Model validation is ongoing to compare with test data from Sandia National Laboratories. The ABDT tool was established in ANSYS. Task 3. Microstructural modeling was conducted to enhance next-generation electrode designs. This 3- year project will validate models for a variety of electrodes, complementing Advanced Battery Research programs. Prototype tools have been developed for electrochemical simulation and geometric reconstruction.« less

Time-efficient simulations of tight-binding electronic structures with Intel Xeon PhiTM many-core processors

NASA Astrophysics Data System (ADS)

Ryu, Hoon; Jeong, Yosang; Kang, Ji-Hoon; Cho, Kyu Nam

2016-12-01

Modelling of multi-million atomic semiconductor structures is important as it not only predicts properties of physically realizable novel materials, but can accelerate advanced device designs. This work elaborates a new Technology-Computer-Aided-Design (TCAD) tool for nanoelectronics modelling, which uses a sp3d5s∗ tight-binding approach to describe multi-million atomic structures, and simulate electronic structures with high performance computing (HPC), including atomic effects such as alloy and dopant disorders. Being named as Quantum simulation tool for Advanced Nanoscale Devices (Q-AND), the tool shows nice scalability on traditional multi-core HPC clusters implying the strong capability of large-scale electronic structure simulations, particularly with remarkable performance enhancement on latest clusters of Intel Xeon PhiTM coprocessors. A review of the recent modelling study conducted to understand an experimental work of highly phosphorus-doped silicon nanowires, is presented to demonstrate the utility of Q-AND. Having been developed via Intel Parallel Computing Center project, Q-AND will be open to public to establish a sound framework of nanoelectronics modelling with advanced HPC clusters of a many-core base. With details of the development methodology and exemplary study of dopant electronics, this work will present a practical guideline for TCAD development to researchers in the field of computational nanoelectronics.

H-BLAST: a fast protein sequence alignment toolkit on heterogeneous computers with GPUs.

PubMed

Ye, Weicai; Chen, Ying; Zhang, Yongdong; Xu, Yuesheng

2017-04-15

The sequence alignment is a fundamental problem in bioinformatics. BLAST is a routinely used tool for this purpose with over 118 000 citations in the past two decades. As the size of bio-sequence databases grows exponentially, the computational speed of alignment softwares must be improved. We develop the heterogeneous BLAST (H-BLAST), a fast parallel search tool for a heterogeneous computer that couples CPUs and GPUs, to accelerate BLASTX and BLASTP-basic tools of NCBI-BLAST. H-BLAST employs a locally decoupled seed-extension algorithm for better performance on GPUs, and offers a performance tuning mechanism for better efficiency among various CPUs and GPUs combinations. H-BLAST produces identical alignment results as NCBI-BLAST and its computational speed is much faster than that of NCBI-BLAST. Speedups achieved by H-BLAST over sequential NCBI-BLASTP (resp. NCBI-BLASTX) range mostly from 4 to 10 (resp. 5 to 7.2). With 2 CPU threads and 2 GPUs, H-BLAST can be faster than 16-threaded NCBI-BLASTX. Furthermore, H-BLAST is 1.5-4 times faster than GPU-BLAST. https://github.com/Yeyke/H-BLAST.git. yux06@syr.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Discovering Synergistic Drug Combination from a Computational Perspective.

PubMed

Ding, Pingjian; Luo, Jiawei; Liang, Cheng; Xiao, Qiu; Cao, Buwen; Li, Guanghui

2018-03-30

Synergistic drug combinations play an important role in the treatment of complex diseases. The identification of effective drug combination is vital to further reduce the side effects and improve therapeutic efficiency. In previous years, in vitro method has been the main route to discover synergistic drug combinations. However, many limitations of time and resource consumption lie within the in vitro method. Therefore, with the rapid development of computational models and the explosive growth of large and phenotypic data, computational methods for discovering synergistic drug combinations are an efficient and promising tool and contribute to precision medicine. It is the key of computational methods how to construct the computational model. Different computational strategies generate different performance. In this review, the recent advancements in computational methods for predicting effective drug combination are concluded from multiple aspects. First, various datasets utilized to discover synergistic drug combinations are summarized. Second, we discussed feature-based approaches and partitioned these methods into two classes including feature-based methods in terms of similarity measure, and feature-based methods in terms of machine learning. Third, we discussed network-based approaches for uncovering synergistic drug combinations. Finally, we analyzed and prospected computational methods for predicting effective drug combinations. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A service-based BLAST command tool supported by cloud infrastructures.

PubMed

Carrión, Abel; Blanquer, Ignacio; Hernández, Vicente

2012-01-01

Notwithstanding the benefits of distributed-computing infrastructures for empowering bioinformatics analysis tools with the needed computing and storage capability, the actual use of these infrastructures is still low. Learning curves and deployment difficulties have reduced the impact on the wide research community. This article presents a porting strategy of BLAST based on a multiplatform client and a service that provides the same interface as sequential BLAST, thus reducing learning curve and with minimal impact on their integration on existing workflows. The porting has been done using the execution and data access components from the EC project Venus-C and the Windows Azure infrastructure provided in this project. The results obtained demonstrate a low overhead on the global execution framework and reasonable speed-up and cost-efficiency with respect to a sequential version.

Advancements in RNASeqGUI towards a Reproducible Analysis of RNA-Seq Experiments

PubMed Central

Russo, Francesco; Righelli, Dario

2016-01-01

We present the advancements and novelties recently introduced in RNASeqGUI, a graphical user interface that helps biologists to handle and analyse large data collected in RNA-Seq experiments. This work focuses on the concept of reproducible research and shows how it has been incorporated in RNASeqGUI to provide reproducible (computational) results. The novel version of RNASeqGUI combines graphical interfaces with tools for reproducible research, such as literate statistical programming, human readable report, parallel executions, caching, and interactive and web-explorable tables of results. These features allow the user to analyse big datasets in a fast, efficient, and reproducible way. Moreover, this paper represents a proof of concept, showing a simple way to develop computational tools for Life Science in the spirit of reproducible research. PMID:26977414

A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses

NASA Astrophysics Data System (ADS)

Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.

2016-09-01

Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace such that the dimensionality of the problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2-D and a random hydraulic conductivity field in 3-D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ˜101 to ˜102 in a multicore computational environment. Therefore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate to large-scale problems.

An efficient parallel termination detection algorithm

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

Baker, A. H.; Crivelli, S.; Jessup, E. R.

2004-05-27

Information local to any one processor is insufficient to monitor the overall progress of most distributed computations. Typically, a second distributed computation for detecting termination of the main computation is necessary. In order to be a useful computational tool, the termination detection routine must operate concurrently with the main computation, adding minimal overhead, and it must promptly and correctly detect termination when it occurs. In this paper, we present a new algorithm for detecting the termination of a parallel computation on distributed-memory MIMD computers that satisfies all of those criteria. A variety of termination detection algorithms have been devised. Ofmore » these, the algorithm presented by Sinha, Kale, and Ramkumar (henceforth, the SKR algorithm) is unique in its ability to adapt to the load conditions of the system on which it runs, thereby minimizing the impact of termination detection on performance. Because their algorithm also detects termination quickly, we consider it to be the most efficient practical algorithm presently available. The termination detection algorithm presented here was developed for use in the PMESC programming library for distributed-memory MIMD computers. Like the SKR algorithm, our algorithm adapts to system loads and imposes little overhead. Also like the SKR algorithm, ours is tree-based, and it does not depend on any assumptions about the physical interconnection topology of the processors or the specifics of the distributed computation. In addition, our algorithm is easier to implement and requires only half as many tree traverses as does the SKR algorithm. This paper is organized as follows. In section 2, we define our computational model. In section 3, we review the SKR algorithm. We introduce our new algorithm in section 4, and prove its correctness in section 5. We discuss its efficiency and present experimental results in section 6.« less

Quantum Monte Carlo Endstation for Petascale Computing

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

Lubos Mitas

2011-01-26

NCSU research group has been focused on accomplising the key goals of this initiative: establishing new generation of quantum Monte Carlo (QMC) computational tools as a part of Endstation petaflop initiative for use at the DOE ORNL computational facilities and for use by computational electronic structure community at large; carrying out high accuracy quantum Monte Carlo demonstration projects in application of these tools to the forefront electronic structure problems in molecular and solid systems; expanding the impact of QMC methods and approaches; explaining and enhancing the impact of these advanced computational approaches. In particular, we have developed quantum Monte Carlomore » code (QWalk, www.qwalk.org) which was significantly expanded and optimized using funds from this support and at present became an actively used tool in the petascale regime by ORNL researchers and beyond. These developments have been built upon efforts undertaken by the PI's group and collaborators over the period of the last decade. The code was optimized and tested extensively on a number of parallel architectures including petaflop ORNL Jaguar machine. We have developed and redesigned a number of code modules such as evaluation of wave functions and orbitals, calculations of pfaffians and introduction of backflow coordinates together with overall organization of the code and random walker distribution over multicore architectures. We have addressed several bottlenecks such as load balancing and verified efficiency and accuracy of the calculations with the other groups of the Endstation team. The QWalk package contains about 50,000 lines of high quality object-oriented C++ and includes also interfaces to data files from other conventional electronic structure codes such as Gamess, Gaussian, Crystal and others. This grant supported PI for one month during summers, a full-time postdoc and partially three graduate students over the period of the grant duration, it has resulted in 13 published papers, 15 invited talks and lectures nationally and internationally. My former graduate student and postdoc Dr. Michal Bajdich, who was supported byt this grant, is currently a postdoc with ORNL in the group of Dr. F. Reboredo and Dr. P. Kent and is using the developed tools in a number of DOE projects. The QWalk package has become a truly important research tool used by the electronic structure community and has attracted several new developers in other research groups. Our tools use several types of correlated wavefunction approaches, variational, diffusion and reptation methods, large-scale optimization methods for wavefunctions and enables to calculate energy differences such as cohesion, electronic gaps, but also densities and other properties, using multiple runs one can obtain equations of state for given structures and beyond. Our codes use efficient numerical and Monte Carlo strategies (high accuracy numerical orbitals, multi-reference wave functions, highly accurate correlation factors, pairing orbitals, force biased and correlated sampling Monte Carlo), are robustly parallelized and enable to run on tens of thousands cores very efficiently. Our demonstration applications were focused on the challenging research problems in several fields of materials science such as transition metal solids. We note that our study of FeO solid was the first QMC calculation of transition metal oxides at high pressures.« less

Cloud computing for energy management in smart grid - an application survey

NASA Astrophysics Data System (ADS)

Naveen, P.; Kiing Ing, Wong; Kobina Danquah, Michael; Sidhu, Amandeep S.; Abu-Siada, Ahmed

2016-03-01

The smart grid is the emerging energy system wherein the application of information technology, tools and techniques that make the grid run more efficiently. It possesses demand response capacity to help balance electrical consumption with supply. The challenges and opportunities of emerging and future smart grids can be addressed by cloud computing. To focus on these requirements, we provide an in-depth survey on different cloud computing applications for energy management in the smart grid architecture. In this survey, we present an outline of the current state of research on smart grid development. We also propose a model of cloud based economic power dispatch for smart grid.

Developing an eLearning tool formalizing in YAWL the guidelines used in a transfusion medicine service.

PubMed

Russo, Paola; Piazza, Miriam; Leonardi, Giorgio; Roncoroni, Layla; Russo, Carlo; Spadaro, Salvatore; Quaglini, Silvana

2012-01-01

The blood transfusion is a complex activity subject to a high risk of eventually fatal errors. The development and application of computer-based systems could help reducing the error rate, playing a fundamental role in the improvement of the quality of care. This poster presents an under development eLearning tool formalizing the guidelines of the transfusion process. This system, implemented in YAWL (Yet Another Workflow Language), will be used to train the personnel in order to improve the efficiency of care and to reduce errors.

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses

PubMed Central

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-01-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. PMID:24462600

Computational tool for simulation of power and refrigeration cycles

NASA Astrophysics Data System (ADS)

Córdoba Tuta, E.; Reyes Orozco, M.

2016-07-01

Small improvement in thermal efficiency of power cycles brings huge cost savings in the production of electricity, for that reason have a tool for simulation of power cycles allows modeling the optimal changes for a best performance. There is also a big boom in research Organic Rankine Cycle (ORC), which aims to get electricity at low power through cogeneration, in which the working fluid is usually a refrigerant. A tool to design the elements of an ORC cycle and the selection of the working fluid would be helpful, because sources of heat from cogeneration are very different and in each case would be a custom design. In this work the development of a multiplatform software for the simulation of power cycles and refrigeration, which was implemented in the C ++ language and includes a graphical interface which was developed using multiplatform environment Qt and runs on operating systems Windows and Linux. The tool allows the design of custom power cycles, selection the type of fluid (thermodynamic properties are calculated through CoolProp library), calculate the plant efficiency, identify the fractions of flow in each branch and finally generates a report very educational in pdf format via the LaTeX tool.

Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses.

PubMed

Liu, Bo; Madduri, Ravi K; Sotomayor, Borja; Chard, Kyle; Lacinski, Lukasz; Dave, Utpal J; Li, Jianqiang; Liu, Chunchen; Foster, Ian T

2014-06-01

Due to the upcoming data deluge of genome data, the need for storing and processing large-scale genome data, easy access to biomedical analyses tools, efficient data sharing and retrieval has presented significant challenges. The variability in data volume results in variable computing and storage requirements, therefore biomedical researchers are pursuing more reliable, dynamic and convenient methods for conducting sequencing analyses. This paper proposes a Cloud-based bioinformatics workflow platform for large-scale next-generation sequencing analyses, which enables reliable and highly scalable execution of sequencing analyses workflows in a fully automated manner. Our platform extends the existing Galaxy workflow system by adding data management capabilities for transferring large quantities of data efficiently and reliably (via Globus Transfer), domain-specific analyses tools preconfigured for immediate use by researchers (via user-specific tools integration), automatic deployment on Cloud for on-demand resource allocation and pay-as-you-go pricing (via Globus Provision), a Cloud provisioning tool for auto-scaling (via HTCondor scheduler), and the support for validating the correctness of workflows (via semantic verification tools). Two bioinformatics workflow use cases as well as performance evaluation are presented to validate the feasibility of the proposed approach. Copyright © 2014 Elsevier Inc. All rights reserved.

2015 Army Science Planning and Strategy Meeting Series: Outcomes and Conclusions

DTIC Science & Technology

2017-12-21

modeling and nanoscale characterization tools to enable efficient design of hybridized manufacturing ; realtime, multiscale computational capability...to enable predictive analytics for expeditionary on-demand manufacturing • Discovery of design principles to enable programming advanced genetic...goals, significant research is needed to mature the fundamental materials science, processing and manufacturing sciences, design methodologies, data

Structural-Vibration-Response Data Analysis

NASA Technical Reports Server (NTRS)

Smith, W. R.; Hechenlaible, R. N.; Perez, R. C.

1983-01-01

Computer program developed as structural-vibration-response data analysis tool for use in dynamic testing of Space Shuttle. Program provides fast and efficient time-domain least-squares curve-fitting procedure for reducing transient response data to obtain structural model frequencies and dampings from free-decay records. Procedure simultaneously identifies frequencies, damping values, and participation factors for noisy multiple-response records.

Design Aids for Real-Time Systems (DARTS)

NASA Technical Reports Server (NTRS)

Szulewski, P. A.

1982-01-01

Design-Aids for Real-Time Systems (DARTS) is a tool that assists in defining embedded computer systems through tree structured graphics, military standard documentation support, and various analyses including automated Software Science parameter counting and metrics calculation. These analyses provide both static and dynamic design quality feedback which can potentially aid in producing efficient, high quality software systems.

Hardwood sawyer trainer

Treesearch

Luis G. Occeña; Eknarin Santitrakul; Daniel L. Schmoldt

2000-01-01

It is well understood by now that the initial breakdown of hardwood logs into lumber has a tremendous impact on the total lumber value and conversion efficiency. The focus of this research project is the development of a computer-aided sawing trainer tool for the primary breakdown of hardwood logs. Maximum lumber recovery is dependent on the proper log orientation as...

Health Literacy Assessment of the STOFHLA: Paper versus Electronic Administration Continuation Study

ERIC Educational Resources Information Center

Chesser, Amy K.; Keene Woods, Nikki; Wipperman, Jennifer; Wilson, Rachel; Dong, Frank

2014-01-01

Low health literacy is associated with poor health outcomes. Research is needed to understand the mechanisms and pathways of its effects. Computer-based assessment tools may improve efficiency and cost-effectiveness of health literacy research. The objective of this preliminary study was to assess if administration of the Short Test of Functional…

Simulated sawing of squares: a tool to improve wood utilization

Treesearch

R. Bruce Anderson; Hugh W. Reynolds

1981-01-01

Manufacturers of turning squares have had difficulty finding the best combination of bolt and square sizes for producing squares most efficiently. A computer simulation technique has been developed for inexpensively detemining the best combination of bolt and square size. Ranges of bolt dimeters to achieve a stated level of yield are given. The manufacturer can choose...

Aeroelastic Model Structure Computation for Envelope Expansion

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2007-01-01

Structure detection is a procedure for selecting a subset of candidate terms, from a full model description, that best describes the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modeling may be of critical importance in the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion that may save significant development time and costs. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of non-linear aeroelastic systems. The LASSO minimises the residual sum of squares with the addition of an l(Sub 1) penalty term on the parameter vector of the traditional l(sub 2) minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudo-linear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. Applicability of this technique for model structure computation for the F/A-18 (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) Active Aeroelastic Wing project using flight test data is shown for several flight conditions (Mach numbers) by identifying a parsimonious system description with a high percent fit for cross-validated data.

A novel concept for smart trepanation.

PubMed

Follmann, Axel; Korff, Alexander; Fuertjes, Tobias; Kunze, Sandra C; Schmieder, Kirsten; Radermacher, Klaus

2012-01-01

Trepanation of the skull is a common procedure in craniofacial and neurosurgical interventions, allowing access to the innermost cranial structures. Despite a careful advancement, injury of the dura mater represents a frequent complication during these cranial openings. The technology of computer-assisted surgery offers different support systems such as navigated tools and surgical robots. This article presents a novel technical approach toward an image- and sensor-based synergistic control of the cutting depth of a manually guided soft-tissue-preserving saw. Feasibility studies in a laboratory setup modeling relevant skull tissue parameters demonstrate that errors due to computed tomography or magnetic resonance image segmentation and registration, optical tracking, and mechanical tolerances of up to 2.5 mm, imminent to many computer-assisted surgery systems, can be compensated for by the cutting tool characteristics without damaging the dura. In conclusion, the feasibility of a computer-controlled trepanation system providing a safer and efficient trepanation has been demonstrated. Injuries of the dura mater can be avoided, and the bone cutting gap can be reduced to 0.5 mm with potential benefits for the reintegration of the bone flap.

A programming language for composable DNA circuits

PubMed Central

Phillips, Andrew; Cardelli, Luca

2009-01-01

Recently, a range of information-processing circuits have been implemented in DNA by using strand displacement as their main computational mechanism. Examples include digital logic circuits and catalytic signal amplification circuits that function as efficient molecular detectors. As new paradigms for DNA computation emerge, the development of corresponding languages and tools for these paradigms will help to facilitate the design of DNA circuits and their automatic compilation to nucleotide sequences. We present a programming language for designing and simulating DNA circuits in which strand displacement is the main computational mechanism. The language includes basic elements of sequence domains, toeholds and branch migration, and assumes that strands do not possess any secondary structure. The language is used to model and simulate a variety of circuits, including an entropy-driven catalytic gate, a simple gate motif for synthesizing large-scale circuits and a scheme for implementing an arbitrary system of chemical reactions. The language is a first step towards the design of modelling and simulation tools for DNA strand displacement, which complements the emergence of novel implementation strategies for DNA computing. PMID:19535415

A programming language for composable DNA circuits.

PubMed

Phillips, Andrew; Cardelli, Luca

2009-08-06

Recently, a range of information-processing circuits have been implemented in DNA by using strand displacement as their main computational mechanism. Examples include digital logic circuits and catalytic signal amplification circuits that function as efficient molecular detectors. As new paradigms for DNA computation emerge, the development of corresponding languages and tools for these paradigms will help to facilitate the design of DNA circuits and their automatic compilation to nucleotide sequences. We present a programming language for designing and simulating DNA circuits in which strand displacement is the main computational mechanism. The language includes basic elements of sequence domains, toeholds and branch migration, and assumes that strands do not possess any secondary structure. The language is used to model and simulate a variety of circuits, including an entropy-driven catalytic gate, a simple gate motif for synthesizing large-scale circuits and a scheme for implementing an arbitrary system of chemical reactions. The language is a first step towards the design of modelling and simulation tools for DNA strand displacement, which complements the emergence of novel implementation strategies for DNA computing.

A computer method for schedule processing and quick-time updating.

NASA Technical Reports Server (NTRS)

Mccoy, W. H.

1972-01-01

A schedule analysis program is presented which can be used to process any schedule with continuous flow and with no loops. Although generally thought of as a management tool, it has applicability to such extremes as music composition and computer program efficiency analysis. Other possibilities for its use include the determination of electrical power usage during some operation such as spacecraft checkout, and the determination of impact envelopes for the purpose of scheduling payloads in launch processing. At the core of the described computer method is an algorithm which computes the position of each activity bar on the output waterfall chart. The algorithm is basically a maximal-path computation which gives to each node in the schedule network the maximal path from the initial node to the given node.

RF Models for Plasma-Surface Interactions in VSim

NASA Astrophysics Data System (ADS)

Jenkins, Thomas G.; Smithe, D. N.; Pankin, A. Y.; Roark, C. M.; Zhou, C. D.; Stoltz, P. H.; Kruger, S. E.

2014-10-01

An overview of ongoing enhancements to the Plasma Discharge (PD) module of Tech-X's VSim software tool is presented. A sub-grid kinetic sheath model, developed for the accurate computation of sheath potentials near metal and dielectric-coated walls, enables the physical effects of DC and RF sheath physics to be included in macroscopic-scale plasma simulations that need not explicitly resolve sheath scale lengths. Sheath potential evolution, together with particle behavior near the sheath, can thus be simulated in complex geometries. Generalizations of the model to include sputtering, secondary electron emission, and effects from multiple ion species and background magnetic fields are summarized; related numerical results are also presented. In addition, improved tools for plasma chemistry and IEDF/EEDF visualization and modeling are discussed, as well as our initial efforts toward the development of hybrid fluid/kinetic transition capabilities within VSim. Ultimately, we aim to establish VSimPD as a robust, efficient computational tool for modeling industrial plasma processes. Supported by US DoE SBIR-I/II Award DE-SC0009501.

Application of linear regression analysis in accuracy assessment of rolling force calculations

NASA Astrophysics Data System (ADS)

Poliak, E. I.; Shim, M. K.; Kim, G. S.; Choo, W. Y.

1998-10-01

Efficient operation of the computational models employed in process control systems require periodical assessment of the accuracy of their predictions. Linear regression is proposed as a tool which allows separate systematic and random prediction errors from those related to measurements. A quantitative characteristic of the model predictive ability is introduced in addition to standard statistical tests for model adequacy. Rolling force calculations are considered as an example for the application. However, the outlined approach can be used to assess the performance of any computational model.

GenIce: Hydrogen-Disordered Ice Generator.

PubMed

Matsumoto, Masakazu; Yagasaki, Takuma; Tanaka, Hideki

2018-01-05

GenIce is an efficient and user-friendly tool to generate hydrogen-disordered ice structures. It makes ice and clathrate hydrate structures in various file formats. More than 100 kinds of structures are preset. Users can install their own crystal structures, guest molecules, and file formats as plugins. The algorithm certifies that the generated structures are completely randomized hydrogen-disordered networks obeying the ice rule with zero net polarization. © 2017 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. © 2017 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Rapid Geometry Creation for Computer-Aided Engineering Parametric Analyses: A Case Study Using ComGeom2 for Launch Abort System Design

NASA Technical Reports Server (NTRS)

Hawke, Veronica; Gage, Peter; Manning, Ted

2007-01-01

ComGeom2, a tool developed to generate Common Geometry representation for multidisciplinary analysis, has been used to create a large set of geometries for use in a design study requiring analysis by two computational codes. This paper describes the process used to generate the large number of configurations and suggests ways to further automate the process and make it more efficient for future studies. The design geometry for this study is the launch abort system of the NASA Crew Launch Vehicle.

BLESS 2: accurate, memory-efficient and fast error correction method.

PubMed

Heo, Yun; Ramachandran, Anand; Hwu, Wen-Mei; Ma, Jian; Chen, Deming

2016-08-01

The most important features of error correction tools for sequencing data are accuracy, memory efficiency and fast runtime. The previous version of BLESS was highly memory-efficient and accurate, but it was too slow to handle reads from large genomes. We have developed a new version of BLESS to improve runtime and accuracy while maintaining a small memory usage. The new version, called BLESS 2, has an error correction algorithm that is more accurate than BLESS, and the algorithm has been parallelized using hybrid MPI and OpenMP programming. BLESS 2 was compared with five top-performing tools, and it was found to be the fastest when it was executed on two computing nodes using MPI, with each node containing twelve cores. Also, BLESS 2 showed at least 11% higher gain while retaining the memory efficiency of the previous version for large genomes. Freely available at https://sourceforge.net/projects/bless-ec dchen@illinois.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A smarter way to search, share and utilize open-spatial online data for energy R&D - Custom machine learning and GIS tools in U.S. DOE's virtual data library & laboratory, EDX

NASA Astrophysics Data System (ADS)

Rose, K.; Bauer, J.; Baker, D.; Barkhurst, A.; Bean, A.; DiGiulio, J.; Jones, K.; Jones, T.; Justman, D.; Miller, R., III; Romeo, L.; Sabbatino, M.; Tong, A.

2017-12-01

As spatial datasets are increasingly accessible through open, online systems, the opportunity to use these resources to address a range of Earth system questions grows. Simultaneously, there is a need for better infrastructure and tools to find and utilize these resources. We will present examples of advanced online computing capabilities, hosted in the U.S. DOE's Energy Data eXchange (EDX), that address these needs for earth-energy research and development. In one study the computing team developed a custom, machine learning, big data computing tool designed to parse the web and return priority datasets to appropriate servers to develop an open-source global oil and gas infrastructure database. The results of this spatial smart search approach were validated against expert-driven, manual search results which required a team of seven spatial scientists three months to produce. The custom machine learning tool parsed online, open systems, including zip files, ftp sites and other web-hosted resources, in a matter of days. The resulting resources were integrated into a geodatabase now hosted for open access via EDX. Beyond identifying and accessing authoritative, open spatial data resources, there is also a need for more efficient tools to ingest, perform, and visualize multi-variate, spatial data analyses. Within the EDX framework, there is a growing suite of processing, analytical and visualization capabilities that allow multi-user teams to work more efficiently in private, virtual workspaces. An example of these capabilities are a set of 5 custom spatio-temporal models and data tools that form NETL's Offshore Risk Modeling suite that can be used to quantify oil spill risks and impacts. Coupling the data and advanced functions from EDX with these advanced spatio-temporal models has culminated with an integrated web-based decision-support tool. This platform has capabilities to identify and combine data across scales and disciplines, evaluate potential environmental, social, and economic impacts, highlight knowledge or technology gaps, and reduce uncertainty for a range of `what if' scenarios relevant to oil spill prevention efforts. These examples illustrate EDX's growing capabilities for advanced spatial data search and analysis to support geo-data science needs.

NASA transmission research and its probable effects on helicopter transmission design

NASA Technical Reports Server (NTRS)

Zaretsky, E. V.; Coy, J. J.; Townsend, D. P.

1983-01-01

Transmissions studied for application to helicopters in addition to the more conventional geared transmissions include hybrid (traction/gear), bearingless planetary, and split torque transmissions. Research is being performed to establish the validity of analysis and computer codes developed to predict the performance, efficiency, life, and reliability of these transmissions. Results of this research should provide the transmission designer with analytical tools to design for minimum weight and noise with maximum life and efficiency. In addition, the advantages and limitations of drive systems as well as the more conventional systems will be defined.

Planar Inlet Design and Analysis Process (PINDAP)

NASA Technical Reports Server (NTRS)

Slater, John W.; Gruber, Christopher R.

2005-01-01

The Planar Inlet Design and Analysis Process (PINDAP) is a collection of software tools that allow the efficient aerodynamic design and analysis of planar (two-dimensional and axisymmetric) inlets. The aerodynamic analysis is performed using the Wind-US computational fluid dynamics (CFD) program. A major element in PINDAP is a Fortran 90 code named PINDAP that can establish the parametric design of the inlet and efficiently model the geometry and generate the grid for CFD analysis with design changes to those parameters. The use of PINDAP is demonstrated for subsonic, supersonic, and hypersonic inlets.

NASA transmission research and its probable effects on helicopter transmission design

NASA Technical Reports Server (NTRS)

Zaretsky, E. V.; Coy, J. J.; Townsend, D. P.

1984-01-01

Transmissions studied for application to helicopters in addition to the more conventional geared transmissions include hybrid (traction/gear), bearingless planetary, and split torque transmissions. Research is being performed to establish the validity of analysis and computer codes developed to predict the performance, efficiency, life, and reliability of these transmissions. Results of this research should provide the transmission designer with analytical tools to design for minimum weight and noise with maximum life and efficiency. In addition, the advantages and limitations of drive systems as well as the more conventional systems will be defined.

PHYSICO2: an UNIX based standalone procedure for computation of physicochemical, window-dependent and substitution based evolutionary properties of protein sequences along with automated block preparation tool, version 2.

PubMed

Banerjee, Shyamashree; Gupta, Parth Sarthi Sen; Nayek, Arnab; Das, Sunit; Sur, Vishma Pratap; Seth, Pratyay; Islam, Rifat Nawaz Ul; Bandyopadhyay, Amal K

2015-01-01

Automated genome sequencing procedure is enriching the sequence database very fast. To achieve a balance between the entry of sequences in the database and their analyses, efficient software is required. In this end PHYSICO2, compare to earlier PHYSICO and other public domain tools, is most efficient in that it i] extracts physicochemical, window-dependent and homologousposition-based-substitution (PWS) properties including positional and BLOCK-specific diversity and conservation, ii] provides users with optional-flexibility in setting relevant input-parameters, iii] helps users to prepare BLOCK-FASTA-file by the use of Automated Block Preparation Tool of the program, iv] performs fast, accurate and user-friendly analyses and v] redirects itemized outputs in excel format along with detailed methodology. The program package contains documentation describing application of methods. Overall the program acts as efficient PWS-analyzer and finds application in sequence-bioinformatics. PHYSICO2: is freely available at http://sourceforge.net/projects/physico2/ along with its documentation at https://sourceforge.net/projects/physico2/files/Documentation.pdf/download for all users.

PHYSICO2: an UNIX based standalone procedure for computation of physicochemical, window-dependent and substitution based evolutionary properties of protein sequences along with automated block preparation tool, version 2

PubMed Central

Banerjee, Shyamashree; Gupta, Parth Sarthi Sen; Nayek, Arnab; Das, Sunit; Sur, Vishma Pratap; Seth, Pratyay; Islam, Rifat Nawaz Ul; Bandyopadhyay, Amal K

2015-01-01

Automated genome sequencing procedure is enriching the sequence database very fast. To achieve a balance between the entry of sequences in the database and their analyses, efficient software is required. In this end PHYSICO2, compare to earlier PHYSICO and other public domain tools, is most efficient in that it i] extracts physicochemical, window-dependent and homologousposition-based-substitution (PWS) properties including positional and BLOCK-specific diversity and conservation, ii] provides users with optional-flexibility in setting relevant input-parameters, iii] helps users to prepare BLOCK-FASTA-file by the use of Automated Block Preparation Tool of the program, iv] performs fast, accurate and user-friendly analyses and v] redirects itemized outputs in excel format along with detailed methodology. The program package contains documentation describing application of methods. Overall the program acts as efficient PWS-analyzer and finds application in sequence-bioinformatics. Availability PHYSICO2: is freely available at http://sourceforge.net/projects/physico2/ along with its documentation at https://sourceforge.net/projects/physico2/files/Documentation.pdf/download for all users. PMID:26339154

Design and evaluation of a software prototype for participatory planning of environmental adaptations.

PubMed

Eriksson, J; Ek, A; Johansson, G

2000-03-01

A software prototype to support the planning process for adapting home and work environments for people with physical disabilities was designed and later evaluated. The prototype exploits low-cost three-dimensional (3-D) graphics products in the home computer market. The essential features of the prototype are: interactive rendering with optional hardware acceleration, interactive walk-throughs, direct manipulation tools for moving objects and measuring distances, and import of 3-D-objects from a library. A usability study was conducted, consisting of two test sessions (three weeks apart) and a final interview. The prototype was then tested and evaluated by representatives of future users: five occupational therapist students, and four persons with physical disability, with no previous experience of the prototype. Emphasis in the usability study was placed on the prototype's efficiency and learnability. We found that it is possible to realise a planning tool for environmental adaptations, both regarding usability and technical efficiency. The usability evaluation confirms our findings from previous case studies, regarding the relevance and positive attitude towards this kind of planning tool. Although the prototype was found to be satisfactorily efficient for the basic tasks, the paper presents several suggestions for improvement of future prototype versions.

Fast and Epsilon-Optimal Discretized Pursuit Learning Automata.

PubMed

Zhang, JunQi; Wang, Cheng; Zhou, MengChu

2015-10-01

Learning automata (LA) are powerful tools for reinforcement learning. A discretized pursuit LA is the most popular one among them. During an iteration its operation consists of three basic phases: 1) selecting the next action; 2) finding the optimal estimated action; and 3) updating the state probability. However, when the number of actions is large, the learning becomes extremely slow because there are too many updates to be made at each iteration. The increased updates are mostly from phases 1 and 3. A new fast discretized pursuit LA with assured ε -optimality is proposed to perform both phases 1 and 3 with the computational complexity independent of the number of actions. Apart from its low computational complexity, it achieves faster convergence speed than the classical one when operating in stationary environments. This paper can promote the applications of LA toward the large-scale-action oriented area that requires efficient reinforcement learning tools with assured ε -optimality, fast convergence speed, and low computational complexity for each iteration.

A comparison of homogeneous equilibrium and relaxation model for CO2 expansion inside the two-phase ejector

NASA Astrophysics Data System (ADS)

Palacz, M.; Haida, M.; Smolka, J.; Nowak, A. J.; Hafner, A.

2016-09-01

In this study, the comparison of the accuracy of the homogeneous equilibrium model (HEM) and homogeneous relaxation model (HRM) is presented. Both models were applied to simulate the CO2 expansion inside the two-phase ejectors. Moreover, the mentioned models were implemented in the robust and efficient computational tool ejectorPL. That tool guarantees the fully automated computational process and the repeatable computations for the various ejector shapes and operating conditions. The simulated motive nozzle mass flow rates were compared to the experimentally measured mass flow rates. That comparison was made for both, HEM and HRM. The results showed the unsatisfying fidelity of the HEM for the operating regimes far from the carbon dioxide critical point. On the other hand, the HRM accuracy for such conditions was slightly higher. The approach presented in this paper, showed the limitation of applicability of both two-phase models for the expansion phenomena inside the ejectors.

Static tool influence function for fabrication simulation of hexagonal mirror segments for extremely large telescopes.

PubMed

Kim, Dae Wook; Kim, Sug-Whan

2005-02-07

We present a novel simulation technique that offers efficient mass fabrication strategies for 2m class hexagonal mirror segments of extremely large telescopes. As the first of two studies in series, we establish the theoretical basis of the tool influence function (TIF) for precessing tool polishing simulation for non-rotating workpieces. These theoretical TIFs were then used to confirm the reproducibility of the material removal foot-prints (measured TIFs) of the bulged precessing tooling reported elsewhere. This is followed by the reverse-computation technique that traces, employing the simplex search method, the real polishing pressure from the empirical TIF. The technical details, together with the results and implications described here, provide the theoretical tool for material removal essential to the successful polishing simulation which will be reported in the second study.

PC Software graphics tool for conceptual design of space/planetary electrical power systems

NASA Technical Reports Server (NTRS)

Truong, Long V.

1995-01-01

This paper describes the Decision Support System (DSS), a personal computer software graphics tool for designing conceptual space and/or planetary electrical power systems. By using the DSS, users can obtain desirable system design and operating parameters, such as system weight, electrical distribution efficiency, and bus power. With this tool, a large-scale specific power system was designed in a matter of days. It is an excellent tool to help designers make tradeoffs between system components, hardware architectures, and operation parameters in the early stages of the design cycle. The DSS is a user-friendly, menu-driven tool with online help and a custom graphical user interface. An example design and results are illustrated for a typical space power system with multiple types of power sources, frequencies, energy storage systems, and loads.

Langley Ground Facilities and Testing in the 21st Century

NASA Technical Reports Server (NTRS)

Ambur, Damodar R.; Kegelman, Jerome T.; Kilgore, William A.

2010-01-01

A strategic approach for retaining and more efficiently operating the essential Langley Ground Testing Facilities in the 21st Century is presented. This effort takes advantage of the previously completed and ongoing studies at the Agency and National levels. This integrated approach takes into consideration the overall decline in test business base within the nation and reduced utilization in each of the Langley facilities with capabilities to test in the subsonic, transonic, supersonic, and hypersonic speed regimes. The strategy accounts for capability needs to meet the Agency programmatic requirements and strategic goals and to execute test activities in the most efficient and flexible facility operating structure. The structure currently being implemented at Langley offers agility to right-size our capability and capacity from a national perspective, to accommodate the dynamic nature of the testing needs, and will address the influence of existing and emerging analytical tools for design. The paradigm for testing in the retained facilities is to efficiently and reliably provide more accurate and high-quality test results at an affordable cost to support design information needs for flight regimes where the computational capability is not adequate and to verify and validate the existing and emerging computational tools. Each of the above goals are planned to be achieved, keeping in mind the increasing small industry customer base engaged in developing unpiloted aerial vehicles and commercial space transportation systems.

Recurrence time statistics: versatile tools for genomic DNA sequence analysis.

PubMed

Cao, Yinhe; Tung, Wen-Wen; Gao, J B

2004-01-01

With the completion of the human and a few model organisms' genomes, and the genomes of many other organisms waiting to be sequenced, it has become increasingly important to develop faster computational tools which are capable of easily identifying the structures and extracting features from DNA sequences. One of the more important structures in a DNA sequence is repeat-related. Often they have to be masked before protein coding regions along a DNA sequence are to be identified or redundant expressed sequence tags (ESTs) are to be sequenced. Here we report a novel recurrence time based method for sequence analysis. The method can conveniently study all kinds of periodicity and exhaustively find all repeat-related features from a genomic DNA sequence. An efficient codon index is also derived from the recurrence time statistics, which has the salient features of being largely species-independent and working well on very short sequences. Efficient codon indices are key elements of successful gene finding algorithms, and are particularly useful for determining whether a suspected EST belongs to a coding or non-coding region. We illustrate the power of the method by studying the genomes of E. coli, the yeast S. cervisivae, the nematode worm C. elegans, and the human, Homo sapiens. Computationally, our method is very efficient. It allows us to carry out analysis of genomes on the whole genomic scale by a PC.

Test-bench system for a borehole azimuthal acoustic reflection imaging logging tool

NASA Astrophysics Data System (ADS)

Liu, Xianping; Ju, Xiaodong; Qiao, Wenxiao; Lu, Junqiang; Men, Baiyong; Liu, Dong

2016-06-01

The borehole azimuthal acoustic reflection imaging logging tool (BAAR) is a new generation of imaging logging tool, which is able to investigate stratums in a relatively larger range of space around the borehole. The BAAR is designed based on the idea of modularization with a very complex structure, so it has become urgent for us to develop a dedicated test-bench system to debug each module of the BAAR. With the help of a test-bench system introduced in this paper, test and calibration of BAAR can be easily achieved. The test-bench system is designed based on the client/server model. The hardware system mainly consists of a host computer, an embedded controlling board, a bus interface board, a data acquisition board and a telemetry communication board. The host computer serves as the human machine interface and processes the uploaded data. The software running on the host computer is designed based on VC++. The embedded controlling board uses Advanced Reduced Instruction Set Machines 7 (ARM7) as the micro controller and communicates with the host computer via Ethernet. The software for the embedded controlling board is developed based on the operating system uClinux. The bus interface board, data acquisition board and telemetry communication board are designed based on a field programmable gate array (FPGA) and provide test interfaces for the logging tool. To examine the feasibility of the test-bench system, it was set up to perform a test on BAAR. By analyzing the test results, an unqualified channel of the electronic receiving cabin was discovered. It is suggested that the test-bench system can be used to quickly determine the working condition of sub modules of BAAR and it is of great significance in improving production efficiency and accelerating industrial production of the logging tool.

DVS-SOFTWARE: An Effective Tool for Applying Highly Parallelized Hardware To Computational Geophysics

NASA Astrophysics Data System (ADS)

Herrera, I.; Herrera, G. S.

2015-12-01

Most geophysical systems are macroscopic physical systems. The behavior prediction of such systems is carried out by means of computational models whose basic models are partial differential equations (PDEs) [1]. Due to the enormous size of the discretized version of such PDEs it is necessary to apply highly parallelized super-computers. For them, at present, the most efficient software is based on non-overlapping domain decomposition methods (DDM). However, a limiting feature of the present state-of-the-art techniques is due to the kind of discretizations used in them. Recently, I. Herrera and co-workers using 'non-overlapping discretizations' have produced the DVS-Software which overcomes this limitation [2]. The DVS-software can be applied to a great variety of geophysical problems and achieves very high parallel efficiencies (90%, or so [3]). It is therefore very suitable for effectively applying the most advanced parallel supercomputers available at present. In a parallel talk, in this AGU Fall Meeting, Graciela Herrera Z. will present how this software is being applied to advance MOD-FLOW. Key Words: Parallel Software for Geophysics, High Performance Computing, HPC, Parallel Computing, Domain Decomposition Methods (DDM)REFERENCES [1]. Herrera Ismael and George F. Pinder, Mathematical Modelling in Science and Engineering: An axiomatic approach", John Wiley, 243p., 2012. [2]. Herrera, I., de la Cruz L.M. and Rosas-Medina A. "Non Overlapping Discretization Methods for Partial, Differential Equations". NUMER METH PART D E, 30: 1427-1454, 2014, DOI 10.1002/num 21852. (Open source) [3]. Herrera, I., & Contreras Iván "An Innovative Tool for Effectively Applying Highly Parallelized Software To Problems of Elasticity". Geofísica Internacional, 2015 (In press)

Knowledge management in a waste based biorefinery in the QbD paradigm.

PubMed

Rathore, Anurag S; Chopda, Viki R; Gomes, James

2016-09-01

Shifting resource base from fossil feedstock to renewable raw materials for production of chemical products has opened up an area of novel applications of industrial biotechnology-based process tools. This review aims to provide a concise and focused discussion on recent advances in knowledge management to facilitate efficient and optimal operation of a biorefinery. Application of quality by design (QbD) and process analytical technology (PAT) as tools for knowledge creation and management at different levels has been highlighted. Role of process integration, government policies, knowledge exchange through collaboration, and use of databases and computational tools have also been touched upon. Copyright © 2016 Elsevier Ltd. All rights reserved.

TLD efficiency calculations for heavy ions: an analytical approach

DOE PAGES

Boscolo, Daria; Scifoni, Emanuele; Carlino, Antonio; ...

2015-12-18

The use of thermoluminescent dosimeters (TLDs) in heavy charged particles’ dosimetry is limited by their non-linear dose response curve and by their response dependence on the radiation quality. Thus, in order to use TLDs with particle beams, a model that can reproduce the behavior of these detectors under different conditions is needed. Here a new, simple and completely analytical algorithm for the calculation of the relative TL-efficiency depending on the ion charge Z and energy E is presented. In addition, the detector response is evaluated starting from the single ion case, where the computed effectiveness values have been compared withmore » experimental data as well as with predictions from a different method. The main advantage of this approach is that, being fully analytical, it is computationally fast and can be efficiently integrated into treatment planning verification tools. In conclusion, the calculated efficiency values have been then implemented in the treatment planning code TRiP98 and dose calculations on a macroscopic target irradiated with an extended carbon ion field have been performed and verified against experimental data.« less

Health Literacy Assessment of the STOFHLA: Paper versus electronic administration continuation study.

PubMed

Chesser, Amy K; Keene Woods, Nikki; Wipperman, Jennifer; Wilson, Rachel; Dong, Frank

2014-02-01

Low health literacy is associated with poor health outcomes. Research is needed to understand the mechanisms and pathways of its effects. Computer-based assessment tools may improve efficiency and cost-effectiveness of health literacy research. The objective of this preliminary study was to assess if administration of the Short Test of Functional Health Literacy in Adults (STOFHLA) through a computer-based medium was comparable to the paper-based test in terms of accuracy and time to completion. A randomized, crossover design was used to compare computer versus paper format of the STOFHLA at a Midwestern family medicine residency program. Eighty participants were initially randomized to either computer (n = 42) or paper (n = 38) format of the STOFHLA. After a 30-day washout period, participants returned to complete the other version of the STOFHLA. Data analysis revealed no significant difference between paper- and computer-based surveys (p = .9401; N = 57). The majority of participants showed "adequate" health literacy via paper- and computer-based surveys (100% and 97% of participants, respectively). Electronic administration of STOFHLA results were equivalent to the paper administration results for evaluation of adult health literacy. Future investigations should focus on expanded populations in multiple health care settings and validation of other health literacy screening tools in a clinical setting.

Design synthesis and optimization of permanent magnet synchronous machines based on computationally-efficient finite element analysis

NASA Astrophysics Data System (ADS)

Sizov, Gennadi Y.

In this dissertation, a model-based multi-objective optimal design of permanent magnet ac machines, supplied by sine-wave current regulated drives, is developed and implemented. The design procedure uses an efficient electromagnetic finite element-based solver to accurately model nonlinear material properties and complex geometric shapes associated with magnetic circuit design. Application of an electromagnetic finite element-based solver allows for accurate computation of intricate performance parameters and characteristics. The first contribution of this dissertation is the development of a rapid computational method that allows accurate and efficient exploration of large multi-dimensional design spaces in search of optimum design(s). The computationally efficient finite element-based approach developed in this work provides a framework of tools that allow rapid analysis of synchronous electric machines operating under steady-state conditions. In the developed modeling approach, major steady-state performance parameters such as, winding flux linkages and voltages, average, cogging and ripple torques, stator core flux densities, core losses, efficiencies and saturated machine winding inductances, are calculated with minimum computational effort. In addition, the method includes means for rapid estimation of distributed stator forces and three-dimensional effects of stator and/or rotor skew on the performance of the machine. The second contribution of this dissertation is the development of the design synthesis and optimization method based on a differential evolution algorithm. The approach relies on the developed finite element-based modeling method for electromagnetic analysis and is able to tackle large-scale multi-objective design problems using modest computational resources. Overall, computational time savings of up to two orders of magnitude are achievable, when compared to current and prevalent state-of-the-art methods. These computational savings allow one to expand the optimization problem to achieve more complex and comprehensive design objectives. The method is used in the design process of several interior permanent magnet industrial motors. The presented case studies demonstrate that the developed finite element-based approach practically eliminates the need for using less accurate analytical and lumped parameter equivalent circuit models for electric machine design optimization. The design process and experimental validation of the case-study machines are detailed in the dissertation.

Structural alignment of protein descriptors - a combinatorial model.

PubMed

Antczak, Maciej; Kasprzak, Marta; Lukasiak, Piotr; Blazewicz, Jacek

2016-09-17

Structural alignment of proteins is one of the most challenging problems in molecular biology. The tertiary structure of a protein strictly correlates with its function and computationally predicted structures are nowadays a main premise for understanding the latter. However, computationally derived 3D models often exhibit deviations from the native structure. A way to confirm a model is a comparison with other structures. The structural alignment of a pair of proteins can be defined with the use of a concept of protein descriptors. The protein descriptors are local substructures of protein molecules, which allow us to divide the original problem into a set of subproblems and, consequently, to propose a more efficient algorithmic solution. In the literature, one can find many applications of the descriptors concept that prove its usefulness for insight into protein 3D structures, but the proposed approaches are presented rather from the biological perspective than from the computational or algorithmic point of view. Efficient algorithms for identification and structural comparison of descriptors can become crucial components of methods for structural quality assessment as well as tertiary structure prediction. In this paper, we propose a new combinatorial model and new polynomial-time algorithms for the structural alignment of descriptors. The model is based on the maximum-size assignment problem, which we define here and prove that it can be solved in polynomial time. We demonstrate suitability of this approach by comparison with an exact backtracking algorithm. Besides a simplification coming from the combinatorial modeling, both on the conceptual and complexity level, we gain with this approach high quality of obtained results, in terms of 3D alignment accuracy and processing efficiency. All the proposed algorithms were developed and integrated in a computationally efficient tool descs-standalone, which allows the user to identify and structurally compare descriptors of biological molecules, such as proteins and RNAs. Both PDB (Protein Data Bank) and mmCIF (macromolecular Crystallographic Information File) formats are supported. The proposed tool is available as an open source project stored on GitHub ( https://github.com/mantczak/descs-standalone ).

Parallel Implementation of Triangular Cellular Automata for Computing Two-Dimensional Elastodynamic Response on Arbitrary Domains

NASA Astrophysics Data System (ADS)

Leamy, Michael J.; Springer, Adam C.

In this research we report parallel implementation of a Cellular Automata-based simulation tool for computing elastodynamic response on complex, two-dimensional domains. Elastodynamic simulation using Cellular Automata (CA) has recently been presented as an alternative, inherently object-oriented technique for accurately and efficiently computing linear and nonlinear wave propagation in arbitrarily-shaped geometries. The local, autonomous nature of the method should lead to straight-forward and efficient parallelization. We address this notion on symmetric multiprocessor (SMP) hardware using a Java-based object-oriented CA code implementing triangular state machines (i.e., automata) and the MPI bindings written in Java (MPJ Express). We use MPJ Express to reconfigure our existing CA code to distribute a domain's automata to cores present on a dual quad-core shared-memory system (eight total processors). We note that this message passing parallelization strategy is directly applicable to computer clustered computing, which will be the focus of follow-on research. Results on the shared memory platform indicate nearly-ideal, linear speed-up. We conclude that the CA-based elastodynamic simulator is easily configured to run in parallel, and yields excellent speed-up on SMP hardware.

Automatic detection and analysis of cell motility in phase-contrast time-lapse images using a combination of maximally stable extremal regions and Kalman filter approaches.

PubMed

Kaakinen, M; Huttunen, S; Paavolainen, L; Marjomäki, V; Heikkilä, J; Eklund, L

2014-01-01

Phase-contrast illumination is simple and most commonly used microscopic method to observe nonstained living cells. Automatic cell segmentation and motion analysis provide tools to analyze single cell motility in large cell populations. However, the challenge is to find a sophisticated method that is sufficiently accurate to generate reliable results, robust to function under the wide range of illumination conditions encountered in phase-contrast microscopy, and also computationally light for efficient analysis of large number of cells and image frames. To develop better automatic tools for analysis of low magnification phase-contrast images in time-lapse cell migration movies, we investigated the performance of cell segmentation method that is based on the intrinsic properties of maximally stable extremal regions (MSER). MSER was found to be reliable and effective in a wide range of experimental conditions. When compared to the commonly used segmentation approaches, MSER required negligible preoptimization steps thus dramatically reducing the computation time. To analyze cell migration characteristics in time-lapse movies, the MSER-based automatic cell detection was accompanied by a Kalman filter multiobject tracker that efficiently tracked individual cells even in confluent cell populations. This allowed quantitative cell motion analysis resulting in accurate measurements of the migration magnitude and direction of individual cells, as well as characteristics of collective migration of cell groups. Our results demonstrate that MSER accompanied by temporal data association is a powerful tool for accurate and reliable analysis of the dynamic behaviour of cells in phase-contrast image sequences. These techniques tolerate varying and nonoptimal imaging conditions and due to their relatively light computational requirements they should help to resolve problems in computationally demanding and often time-consuming large-scale dynamical analysis of cultured cells. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Structure Computation of Quiet Spike[Trademark] Flight-Test Data During Envelope Expansion

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.

2008-01-01

System identification or mathematical modeling is used in the aerospace community for development of simulation models for robust control law design. These models are often described as linear time-invariant processes. Nevertheless, it is well known that the underlying process is often nonlinear. The reason for using a linear approach has been due to the lack of a proper set of tools for the identification of nonlinear systems. Over the past several decades, the controls and biomedical communities have made great advances in developing tools for the identification of nonlinear systems. These approaches are robust and readily applicable to aerospace systems. In this paper, we show the application of one such nonlinear system identification technique, structure detection, for the analysis of F-15B Quiet Spike(TradeMark) aeroservoelastic flight-test data. Structure detection is concerned with the selection of a subset of candidate terms that best describe the observed output. This is a necessary procedure to compute an efficient system description that may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modeling may be of critical importance for the development of robust parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion, which may save significant development time and costs. The objectives of this study are to demonstrate via analysis of F-15B Quiet Spike aeroservoelastic flight-test data for several flight conditions that 1) linear models are inefficient for modeling aeroservoelastic data, 2) nonlinear identification provides a parsimonious model description while providing a high percent fit for cross-validated data, and 3) the model structure and parameters vary as the flight condition is altered.

Air traffic surveillance and control using hybrid estimation and protocol-based conflict resolution

NASA Astrophysics Data System (ADS)

Hwang, Inseok

The continued growth of air travel and recent advances in new technologies for navigation, surveillance, and communication have led to proposals by the Federal Aviation Administration (FAA) to provide reliable and efficient tools to aid Air Traffic Control (ATC) in performing their tasks. In this dissertation, we address four problems frequently encountered in air traffic surveillance and control; multiple target tracking and identity management, conflict detection, conflict resolution, and safety verification. We develop a set of algorithms and tools to aid ATC; These algorithms have the provable properties of safety, computational efficiency, and convergence. Firstly, we develop a multiple-maneuvering-target tracking and identity management algorithm which can keep track of maneuvering aircraft in noisy environments and of their identities. Secondly, we propose a hybrid probabilistic conflict detection algorithm between multiple aircraft which uses flight mode estimates as well as aircraft current state estimates. Our algorithm is based on hybrid models of aircraft, which incorporate both continuous dynamics and discrete mode switching. Thirdly, we develop an algorithm for multiple (greater than two) aircraft conflict avoidance that is based on a closed-form analytic solution and thus provides guarantees of safety. Finally, we consider the problem of safety verification of control laws for safety critical systems, with application to air traffic control systems. We approach safety verification through reachability analysis, which is a computationally expensive problem. We develop an over-approximate method for reachable set computation using polytopic approximation methods and dynamic optimization. These algorithms may be used either in a fully autonomous way, or as supporting tools to increase controllers' situational awareness and to reduce their work load.

PET-Tool: a software suite for comprehensive processing and managing of Paired-End diTag (PET) sequence data.

PubMed

Chiu, Kuo Ping; Wong, Chee-Hong; Chen, Qiongyu; Ariyaratne, Pramila; Ooi, Hong Sain; Wei, Chia-Lin; Sung, Wing-Kin Ken; Ruan, Yijun

2006-08-25

We recently developed the Paired End diTag (PET) strategy for efficient characterization of mammalian transcriptomes and genomes. The paired end nature of short PET sequences derived from long DNA fragments raised a new set of bioinformatics challenges, including how to extract PETs from raw sequence reads, and correctly yet efficiently map PETs to reference genome sequences. To accommodate and streamline data analysis of the large volume PET sequences generated from each PET experiment, an automated PET data process pipeline is desirable. We designed an integrated computation program package, PET-Tool, to automatically process PET sequences and map them to the genome sequences. The Tool was implemented as a web-based application composed of four modules: the Extractor module for PET extraction; the Examiner module for analytic evaluation of PET sequence quality; the Mapper module for locating PET sequences in the genome sequences; and the Project Manager module for data organization. The performance of PET-Tool was evaluated through the analyses of 2.7 million PET sequences. It was demonstrated that PET-Tool is accurate and efficient in extracting PET sequences and removing artifacts from large volume dataset. Using optimized mapping criteria, over 70% of quality PET sequences were mapped specifically to the genome sequences. With a 2.4 GHz LINUX machine, it takes approximately six hours to process one million PETs from extraction to mapping. The speed, accuracy, and comprehensiveness have proved that PET-Tool is an important and useful component in PET experiments, and can be extended to accommodate other related analyses of paired-end sequences. The Tool also provides user-friendly functions for data quality check and system for multi-layer data management.

A comprehensive overview of computational resources to aid in precision genome editing with engineered nucleases.

PubMed

Periwal, Vinita

2017-07-01

Genome editing with engineered nucleases (zinc finger nucleases, TAL effector nucleases s and Clustered regularly inter-spaced short palindromic repeats/CRISPR-associated) has recently been shown to have great promise in a variety of therapeutic and biotechnological applications. However, their exploitation in genetic analysis and clinical settings largely depends on their specificity for the intended genomic target. Large and complex genomes often contain highly homologous/repetitive sequences, which limits the specificity of genome editing tools and could result in off-target activity. Over the past few years, various computational approaches have been developed to assist the design process and predict/reduce the off-target activity of these nucleases. These tools could be efficiently used to guide the design of constructs for engineered nucleases and evaluate results after genome editing. This review provides a comprehensive overview of various databases, tools, web servers and resources for genome editing and compares their features and functionalities. Additionally, it also describes tools that have been developed to analyse post-genome editing results. The article also discusses important design parameters that could be considered while designing these nucleases. This review is intended to be a quick reference guide for experimentalists as well as computational biologists working in the field of genome editing with engineered nucleases. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Computing Advances Enable More Efficient Buildings - Continuum Magazine |

Science.gov Websites

-and to visualize and react to the data that's available to them," says Brackney. One example of to tell occupants when to open and close their windows. A screen shot of the Building Agent, showing it has been launched. One of the visualization tools is a floor plan that shows which parts of the

Recent Advances in Source Localisation Using Range Measurements

DTIC Science & Technology

2015-10-01

Range Weighted SR- LS ............................................................................................ 5 GEOLOCATION USING SEMIDEFINITE... LS ) and the squared range least squares (SR- LS ) [3]. The R- LS -based formulation is of great interest and has been known for its optimal performance...to efficiently compute an R- LS position estimate. A number of optimization tools may be applied to globally solve the R- LS problem and are usually

Educational Games as Stand-Alone Learning Tools and Their Motivational Effect on L2 Vocabulary Acquisition and Perceived Learning Gains

ERIC Educational Resources Information Center

Calvo-Ferrer, José Ramón

2017-01-01

According to different authors, computer games not only teach contents and skills, but also do so in a more efficient manner, allowing long-lasting learning. However, there is still little consensus on this matter as different studies put their educational benefits into question, especially when used without instructional support. An empirical…

PuLP/XtraPuLP : Partitioning Tools for Extreme-Scale Graphs

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

Slota, George M; Rajamanickam, Sivasankaran; Madduri, Kamesh

2017-09-21

PuLP/XtraPulp is software for partitioning graphs from several real-world problems. Graphs occur in several places in real world from road networks, social networks and scientific simulations. For efficient parallel processing these graphs have to be partitioned (split) with respect to metrics such as computation and communication costs. Our software allows such partitioning for massive graphs.

Seeing Red? The Agency of Computer Software in the Production and Management of Students' School Absences

ERIC Educational Resources Information Center

Bodén, Linnea

2013-01-01

An increasing number of Swedish municipalities use digital software to manage the registration of students' school absences. The software is regarded as a problem-solving tool to make registration more efficient, but its effects on the educational setting have been largely neglected. Focusing on an event with two students from a class of…

Use of the parameterised finite element method to robustly and efficiently evolve the edge of a moving cell.

PubMed

Neilson, Matthew P; Mackenzie, John A; Webb, Steven D; Insall, Robert H

2010-11-01

In this paper we present a computational tool that enables the simulation of mathematical models of cell migration and chemotaxis on an evolving cell membrane. Recent models require the numerical solution of systems of reaction-diffusion equations on the evolving cell membrane and then the solution state is used to drive the evolution of the cell edge. Previous work involved moving the cell edge using a level set method (LSM). However, the LSM is computationally very expensive, which severely limits the practical usefulness of the algorithm. To address this issue, we have employed the parameterised finite element method (PFEM) as an alternative method for evolving a cell boundary. We show that the PFEM is far more efficient and robust than the LSM. We therefore suggest that the PFEM potentially has an essential role to play in computational modelling efforts towards the understanding of many of the complex issues related to chemotaxis.

Automated Software Acceleration in Programmable Logic for an Efficient NFFT Algorithm Implementation: A Case Study.

PubMed

Rodríguez, Manuel; Magdaleno, Eduardo; Pérez, Fernando; García, Cristhian

2017-03-28

Non-equispaced Fast Fourier transform (NFFT) is a very important algorithm in several technological and scientific areas such as synthetic aperture radar, computational photography, medical imaging, telecommunications, seismic analysis and so on. However, its computation complexity is high. In this paper, we describe an efficient NFFT implementation with a hardware coprocessor using an All-Programmable System-on-Chip (APSoC). This is a hybrid device that employs an Advanced RISC Machine (ARM) as Processing System with Programmable Logic for high-performance digital signal processing through parallelism and pipeline techniques. The algorithm has been coded in C language with pragma directives to optimize the architecture of the system. We have used the very novel Software Develop System-on-Chip (SDSoC) evelopment tool that simplifies the interface and partitioning between hardware and software. This provides shorter development cycles and iterative improvements by exploring several architectures of the global system. The computational results shows that hardware acceleration significantly outperformed the software based implementation.

Automated Software Acceleration in Programmable Logic for an Efficient NFFT Algorithm Implementation: A Case Study

PubMed Central

Rodríguez, Manuel; Magdaleno, Eduardo; Pérez, Fernando; García, Cristhian

2017-01-01

Non-equispaced Fast Fourier transform (NFFT) is a very important algorithm in several technological and scientific areas such as synthetic aperture radar, computational photography, medical imaging, telecommunications, seismic analysis and so on. However, its computation complexity is high. In this paper, we describe an efficient NFFT implementation with a hardware coprocessor using an All-Programmable System-on-Chip (APSoC). This is a hybrid device that employs an Advanced RISC Machine (ARM) as Processing System with Programmable Logic for high-performance digital signal processing through parallelism and pipeline techniques. The algorithm has been coded in C language with pragma directives to optimize the architecture of the system. We have used the very novel Software Develop System-on-Chip (SDSoC) evelopment tool that simplifies the interface and partitioning between hardware and software. This provides shorter development cycles and iterative improvements by exploring several architectures of the global system. The computational results shows that hardware acceleration significantly outperformed the software based implementation. PMID:28350358

A versatile model for soft patchy particles with various patch arrangements.

PubMed

Li, Zhan-Wei; Zhu, You-Liang; Lu, Zhong-Yuan; Sun, Zhao-Yan

2016-01-21

We propose a simple and general mesoscale soft patchy particle model, which can felicitously describe the deformable and surface-anisotropic characteristics of soft patchy particles. This model can be used in dynamics simulations to investigate the aggregation behavior and mechanism of various types of soft patchy particles with tunable number, size, direction, and geometrical arrangement of the patches. To improve the computational efficiency of this mesoscale model in dynamics simulations, we give the simulation algorithm that fits the compute unified device architecture (CUDA) framework of NVIDIA graphics processing units (GPUs). The validation of the model and the performance of the simulations using GPUs are demonstrated by simulating several benchmark systems of soft patchy particles with 1 to 4 patches in a regular geometrical arrangement. Because of its simplicity and computational efficiency, the soft patchy particle model will provide a powerful tool to investigate the aggregation behavior of soft patchy particles, such as patchy micelles, patchy microgels, and patchy dendrimers, over larger spatial and temporal scales.

Echo™ User Manual

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

Harvey, Dustin Yewell

Echo™ is a MATLAB-based software package designed for robust and scalable analysis of complex data workflows. An alternative to tedious, error-prone conventional processes, Echo is based on three transformative principles for data analysis: self-describing data, name-based indexing, and dynamic resource allocation. The software takes an object-oriented approach to data analysis, intimately connecting measurement data with associated metadata. Echo operations in an analysis workflow automatically track and merge metadata and computation parameters to provide a complete history of the process used to generate final results, while automated figure and report generation tools eliminate the potential to mislabel those results. History reportingmore » and visualization methods provide straightforward auditability of analysis processes. Furthermore, name-based indexing on metadata greatly improves code readability for analyst collaboration and reduces opportunities for errors to occur. Echo efficiently manages large data sets using a framework that seamlessly allocates resources such that only the necessary computations to produce a given result are executed. Echo provides a versatile and extensible framework, allowing advanced users to add their own tools and data classes tailored to their own specific needs. Applying these transformative principles and powerful features, Echo greatly improves analyst efficiency and quality of results in many application areas.« less

Kernel methods and flexible inference for complex stochastic dynamics

NASA Astrophysics Data System (ADS)

Capobianco, Enrico

2008-07-01

Approximation theory suggests that series expansions and projections represent standard tools for random process applications from both numerical and statistical standpoints. Such instruments emphasize the role of both sparsity and smoothness for compression purposes, the decorrelation power achieved in the expansion coefficients space compared to the signal space, and the reproducing kernel property when some special conditions are met. We consider these three aspects central to the discussion in this paper, and attempt to analyze the characteristics of some known approximation instruments employed in a complex application domain such as financial market time series. Volatility models are often built ad hoc, parametrically and through very sophisticated methodologies. But they can hardly deal with stochastic processes with regard to non-Gaussianity, covariance non-stationarity or complex dependence without paying a big price in terms of either model mis-specification or computational efficiency. It is thus a good idea to look at other more flexible inference tools; hence the strategy of combining greedy approximation and space dimensionality reduction techniques, which are less dependent on distributional assumptions and more targeted to achieve computationally efficient performances. Advantages and limitations of their use will be evaluated by looking at algorithmic and model building strategies, and by reporting statistical diagnostics.

Minimalist Design of Allosterically Regulated Protein Catalysts.

PubMed

Makhlynets, O V; Korendovych, I V

2016-01-01

Nature facilitates chemical transformations with exceptional selectivity and efficiency. Despite a tremendous progress in understanding and predicting protein function, the overall problem of designing a protein catalyst for a given chemical transformation is far from solved. Over the years, many design techniques with various degrees of complexity and rational input have been developed. Minimalist approach to protein design that focuses on the bare minimum requirements to achieve activity presents several important advantages. By focusing on basic physicochemical properties and strategic placing of only few highly active residues one can feasibly evaluate in silico a very large variety of possible catalysts. In more general terms minimalist approach looks for the mere possibility of catalysis, rather than trying to identify the most active catalyst possible. Even very basic designs that utilize a single residue introduced into nonenzymatic proteins or peptide bundles are surprisingly active. Because of the inherent simplicity of the minimalist approach computational tools greatly enhance its efficiency. No complex calculations need to be set up and even a beginner can master this technique in a very short time. Here, we present a step-by-step protocol for minimalist design of functional proteins using basic, easily available, and free computational tools. © 2016 Elsevier Inc. All rights reserved.

A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses

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

Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.

Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally-efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace, such that the dimensionality of themore » problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2D and a random hydraulic conductivity field in 3D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ~10 1 to ~10 2 in a multi-core computational environment. Furthermore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate- to large-scale problems.« less

A computationally efficient parallel Levenberg-Marquardt algorithm for highly parameterized inverse model analyses

DOE PAGES

Lin, Youzuo; O'Malley, Daniel; Vesselinov, Velimir V.

2016-09-01

Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally-efficient parallel Levenberg-Marquardt method for solving inverse modeling problems with a highly parameterized model space. Levenberg-Marquardt methods require the solution of a linear system of equations which can be prohibitively expensive to compute for moderate to large-scale problems. Our novel method projects the original linear problem down to a Krylov subspace, such that the dimensionality of themore » problem can be significantly reduced. Furthermore, we store the Krylov subspace computed when using the first damping parameter and recycle the subspace for the subsequent damping parameters. The efficiency of our new inverse modeling algorithm is significantly improved using these computational techniques. We apply this new inverse modeling method to invert for random transmissivity fields in 2D and a random hydraulic conductivity field in 3D. Our algorithm is fast enough to solve for the distributed model parameters (transmissivity) in the model domain. The algorithm is coded in Julia and implemented in the MADS computational framework (http://mads.lanl.gov). By comparing with Levenberg-Marquardt methods using standard linear inversion techniques such as QR or SVD methods, our Levenberg-Marquardt method yields a speed-up ratio on the order of ~10 1 to ~10 2 in a multi-core computational environment. Furthermore, our new inverse modeling method is a powerful tool for characterizing subsurface heterogeneity for moderate- to large-scale problems.« less

Vehicle trajectory linearisation to enable efficient optimisation of the constant speed racing line

NASA Astrophysics Data System (ADS)

Timings, Julian P.; Cole, David J.

2012-06-01

A driver model is presented capable of optimising the trajectory of a simple dynamic nonlinear vehicle, at constant forward speed, so that progression along a predefined track is maximised as a function of time. In doing so, the model is able to continually operate a vehicle at its lateral-handling limit, maximising vehicle performance. The technique used forms a part of the solution to the motor racing objective of minimising lap time. A new approach of formulating the minimum lap time problem is motivated by the need for a more computationally efficient and robust tool-set for understanding on-the-limit driving behaviour. This has been achieved through set point-dependent linearisation of the vehicle model and coupling the vehicle-track system using an intrinsic coordinate description. Through this, the geometric vehicle trajectory had been linearised relative to the track reference, leading to new path optimisation algorithm which can be formed as a computationally efficient convex quadratic programming problem.

Enabling smart personalized healthcare: a hybrid mobile-cloud approach for ECG telemonitoring.

PubMed

Wang, Xiaoliang; Gui, Qiong; Liu, Bingwei; Jin, Zhanpeng; Chen, Yu

2014-05-01

The severe challenges of the skyrocketing healthcare expenditure and the fast aging population highlight the needs for innovative solutions supporting more accurate, affordable, flexible, and personalized medical diagnosis and treatment. Recent advances of mobile technologies have made mobile devices a promising tool to manage patients' own health status through services like telemedicine. However, the inherent limitations of mobile devices make them less effective in computation- or data-intensive tasks such as medical monitoring. In this study, we propose a new hybrid mobile-cloud computational solution to enable more effective personalized medical monitoring. To demonstrate the efficacy and efficiency of the proposed approach, we present a case study of mobile-cloud based electrocardiograph monitoring and analysis and develop a mobile-cloud prototype. The experimental results show that the proposed approach can significantly enhance the conventional mobile-based medical monitoring in terms of diagnostic accuracy, execution efficiency, and energy efficiency, and holds the potential in addressing future large-scale data analysis in personalized healthcare.

Improved Ant Colony Clustering Algorithm and Its Performance Study

PubMed Central

Gao, Wei

2016-01-01

Clustering analysis is used in many disciplines and applications; it is an important tool that descriptively identifies homogeneous groups of objects based on attribute values. The ant colony clustering algorithm is a swarm-intelligent method used for clustering problems that is inspired by the behavior of ant colonies that cluster their corpses and sort their larvae. A new abstraction ant colony clustering algorithm using a data combination mechanism is proposed to improve the computational efficiency and accuracy of the ant colony clustering algorithm. The abstraction ant colony clustering algorithm is used to cluster benchmark problems, and its performance is compared with the ant colony clustering algorithm and other methods used in existing literature. Based on similar computational difficulties and complexities, the results show that the abstraction ant colony clustering algorithm produces results that are not only more accurate but also more efficiently determined than the ant colony clustering algorithm and the other methods. Thus, the abstraction ant colony clustering algorithm can be used for efficient multivariate data clustering. PMID:26839533

a Hadoop-Based Distributed Framework for Efficient Managing and Processing Big Remote Sensing Images

NASA Astrophysics Data System (ADS)

Wang, C.; Hu, F.; Hu, X.; Zhao, S.; Wen, W.; Yang, C.

2015-07-01

Various sensors from airborne and satellite platforms are producing large volumes of remote sensing images for mapping, environmental monitoring, disaster management, military intelligence, and others. However, it is challenging to efficiently storage, query and process such big data due to the data- and computing- intensive issues. In this paper, a Hadoop-based framework is proposed to manage and process the big remote sensing data in a distributed and parallel manner. Especially, remote sensing data can be directly fetched from other data platforms into the Hadoop Distributed File System (HDFS). The Orfeo toolbox, a ready-to-use tool for large image processing, is integrated into MapReduce to provide affluent image processing operations. With the integration of HDFS, Orfeo toolbox and MapReduce, these remote sensing images can be directly processed in parallel in a scalable computing environment. The experiment results show that the proposed framework can efficiently manage and process such big remote sensing data.

Synthesizing parallel imaging applications using the CAP (computer-aided parallelization) tool

NASA Astrophysics Data System (ADS)

Gennart, Benoit A.; Mazzariol, Marc; Messerli, Vincent; Hersch, Roger D.

1997-12-01

Imaging applications such as filtering, image transforms and compression/decompression require vast amounts of computing power when applied to large data sets. These applications would potentially benefit from the use of parallel processing. However, dedicated parallel computers are expensive and their processing power per node lags behind that of the most recent commodity components. Furthermore, developing parallel applications remains a difficult task: writing and debugging the application is difficult (deadlocks), programs may not be portable from one parallel architecture to the other, and performance often comes short of expectations. In order to facilitate the development of parallel applications, we propose the CAP computer-aided parallelization tool which enables application programmers to specify at a high-level of abstraction the flow of data between pipelined-parallel operations. In addition, the CAP tool supports the programmer in developing parallel imaging and storage operations. CAP enables combining efficiently parallel storage access routines and image processing sequential operations. This paper shows how processing and I/O intensive imaging applications must be implemented to take advantage of parallelism and pipelining between data access and processing. This paper's contribution is (1) to show how such implementations can be compactly specified in CAP, and (2) to demonstrate that CAP specified applications achieve the performance of custom parallel code. The paper analyzes theoretically the performance of CAP specified applications and demonstrates the accuracy of the theoretical analysis through experimental measurements.

TU-AB-BRC-12: Optimized Parallel MonteCarlo Dose Calculations for Secondary MU Checks

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

French, S; Nazareth, D; Bellor, M

Purpose: Secondary MU checks are an important tool used during a physics review of a treatment plan. Commercial software packages offer varying degrees of theoretical dose calculation accuracy, depending on the modality involved. Dose calculations of VMAT plans are especially prone to error due to the large approximations involved. Monte Carlo (MC) methods are not commonly used due to their long run times. We investigated two methods to increase the computational efficiency of MC dose simulations with the BEAMnrc code. Distributed computing resources, along with optimized code compilation, will allow for accurate and efficient VMAT dose calculations. Methods: The BEAMnrcmore » package was installed on a high performance computing cluster accessible to our clinic. MATLAB and PYTHON scripts were developed to convert a clinical VMAT DICOM plan into BEAMnrc input files. The BEAMnrc installation was optimized by running the VMAT simulations through profiling tools which indicated the behavior of the constituent routines in the code, e.g. the bremsstrahlung splitting routine, and the specified random number generator. This information aided in determining the most efficient compiling parallel configuration for the specific CPU’s available on our cluster, resulting in the fastest VMAT simulation times. Our method was evaluated with calculations involving 10{sup 8} – 10{sup 9} particle histories which are sufficient to verify patient dose using VMAT. Results: Parallelization allowed the calculation of patient dose on the order of 10 – 15 hours with 100 parallel jobs. Due to the compiler optimization process, further speed increases of 23% were achieved when compared with the open-source compiler BEAMnrc packages. Conclusion: Analysis of the BEAMnrc code allowed us to optimize the compiler configuration for VMAT dose calculations. In future work, the optimized MC code, in conjunction with the parallel processing capabilities of BEAMnrc, will be applied to provide accurate and efficient secondary MU checks.« less

Computational fluid dynamics uses in fluid dynamics/aerodynamics education

NASA Technical Reports Server (NTRS)

Holst, Terry L.

1994-01-01

The field of computational fluid dynamics (CFD) has advanced to the point where it can now be used for the purpose of fluid dynamics physics education. Because of the tremendous wealth of information available from numerical simulation, certain fundamental concepts can be efficiently communicated using an interactive graphical interrogation of the appropriate numerical simulation data base. In other situations, a large amount of aerodynamic information can be communicated to the student by interactive use of simple CFD tools on a workstation or even in a personal computer environment. The emphasis in this presentation is to discuss ideas for how this process might be implemented. Specific examples, taken from previous publications, will be used to highlight the presentation.

Computer Graphics-aided systems analysis: application to well completion design

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

Detamore, J.E.; Sarma, M.P.

1985-03-01

The development of an engineering tool (in the form of a computer model) for solving design and analysis problems related with oil and gas well production operations is discussed. The development of the method is based on integrating the concepts of ''Systems Analysis'' with the techniques of ''Computer Graphics''. The concepts behind the method are very general in nature. This paper, however, illustrates the application of the method in solving gas well completion design problems. The use of the method will save time and improve the efficiency of such design and analysis problems. The method can be extended to othermore » design and analysis aspects of oil and gas wells.« less

OpenTopography: Addressing Big Data Challenges Using Cloud Computing, HPC, and Data Analytics

NASA Astrophysics Data System (ADS)

Crosby, C. J.; Nandigam, V.; Phan, M.; Youn, C.; Baru, C.; Arrowsmith, R.

2014-12-01

OpenTopography (OT) is a geoinformatics-based data facility initiated in 2009 for democratizing access to high-resolution topographic data, derived products, and tools. Hosted at the San Diego Supercomputer Center (SDSC), OT utilizes cyberinfrastructure, including large-scale data management, high-performance computing, and service-oriented architectures to provide efficient Web based access to large, high-resolution topographic datasets. OT collocates data with processing tools to enable users to quickly access custom data and derived products for their application. OT's ongoing R&D efforts aim to solve emerging technical challenges associated with exponential growth in data, higher order data products, as well as user base. Optimization of data management strategies can be informed by a comprehensive set of OT user access metrics that allows us to better understand usage patterns with respect to the data. By analyzing the spatiotemporal access patterns within the datasets, we can map areas of the data archive that are highly active (hot) versus the ones that are rarely accessed (cold). This enables us to architect a tiered storage environment consisting of high performance disk storage (SSD) for the hot areas and less expensive slower disk for the cold ones, thereby optimizing price to performance. From a compute perspective, OT is looking at cloud based solutions such as the Microsoft Azure platform to handle sudden increases in load. An OT virtual machine image in Microsoft's VM Depot can be invoked and deployed quickly in response to increased system demand. OT has also integrated SDSC HPC systems like the Gordon supercomputer into our infrastructure tier to enable compute intensive workloads like parallel computation of hydrologic routing on high resolution topography. This capability also allows OT to scale to HPC resources during high loads to meet user demand and provide more efficient processing. With a growing user base and maturing scientific user community comes new requests for algorithms and processing capabilities. To address this demand, OT is developing an extensible service based architecture for integrating community-developed software. This "plugable" approach to Web service deployment will enable new processing and analysis tools to run collocated with OT hosted data.

Faster Aerodynamic Simulation With Cart3D

NASA Technical Reports Server (NTRS)

2003-01-01

A NASA-developed aerodynamic simulation tool is ensuring the safety of future space operations while providing designers and engineers with an automated, highly accurate computer simulation suite. Cart3D, co-winner of NASA's 2002 Software of the Year award, is the result of over 10 years of research and software development conducted by Michael Aftosmis and Dr. John Melton of Ames Research Center and Professor Marsha Berger of the Courant Institute at New York University. Cart3D offers a revolutionary approach to computational fluid dynamics (CFD), the computer simulation of how fluids and gases flow around an object of a particular design. By fusing technological advancements in diverse fields such as mineralogy, computer graphics, computational geometry, and fluid dynamics, the software provides a new industrial geometry processing and fluid analysis capability with unsurpassed automation and efficiency.

Parametric bicubic spline and CAD tools for complex targets shape modelling in physical optics radar cross section prediction

NASA Astrophysics Data System (ADS)

Delogu, A.; Furini, F.

1991-09-01

Increasing interest in radar cross section (RCS) reduction is placing new demands on theoretical, computation, and graphic techniques for calculating scattering properties of complex targets. In particular, computer codes capable of predicting the RCS of an entire aircraft at high frequency and of achieving RCS control with modest structural changes, are becoming of paramount importance in stealth design. A computer code, evaluating the RCS of arbitrary shaped metallic objects that are computer aided design (CAD) generated, and its validation with measurements carried out using ALENIA RCS test facilities are presented. The code, based on the physical optics method, is characterized by an efficient integration algorithm with error control, in order to contain the computer time within acceptable limits, and by an accurate parametric representation of the target surface in terms of bicubic splines.

Quantum computing on encrypted data

NASA Astrophysics Data System (ADS)

Fisher, K. A. G.; Broadbent, A.; Shalm, L. K.; Yan, Z.; Lavoie, J.; Prevedel, R.; Jennewein, T.; Resch, K. J.

2014-01-01

The ability to perform computations on encrypted data is a powerful tool for protecting privacy. Recently, protocols to achieve this on classical computing systems have been found. Here, we present an efficient solution to the quantum analogue of this problem that enables arbitrary quantum computations to be carried out on encrypted quantum data. We prove that an untrusted server can implement a universal set of quantum gates on encrypted quantum bits (qubits) without learning any information about the inputs, while the client, knowing the decryption key, can easily decrypt the results of the computation. We experimentally demonstrate, using single photons and linear optics, the encryption and decryption scheme on a set of gates sufficient for arbitrary quantum computations. As our protocol requires few extra resources compared with other schemes it can be easily incorporated into the design of future quantum servers. These results will play a key role in enabling the development of secure distributed quantum systems.

Quantum computing on encrypted data.

PubMed

Fisher, K A G; Broadbent, A; Shalm, L K; Yan, Z; Lavoie, J; Prevedel, R; Jennewein, T; Resch, K J

2014-01-01

The ability to perform computations on encrypted data is a powerful tool for protecting privacy. Recently, protocols to achieve this on classical computing systems have been found. Here, we present an efficient solution to the quantum analogue of this problem that enables arbitrary quantum computations to be carried out on encrypted quantum data. We prove that an untrusted server can implement a universal set of quantum gates on encrypted quantum bits (qubits) without learning any information about the inputs, while the client, knowing the decryption key, can easily decrypt the results of the computation. We experimentally demonstrate, using single photons and linear optics, the encryption and decryption scheme on a set of gates sufficient for arbitrary quantum computations. As our protocol requires few extra resources compared with other schemes it can be easily incorporated into the design of future quantum servers. These results will play a key role in enabling the development of secure distributed quantum systems.

A computer vision for animal ecology.

PubMed

Weinstein, Ben G

2018-05-01

A central goal of animal ecology is to observe species in the natural world. The cost and challenge of data collection often limit the breadth and scope of ecological study. Ecologists often use image capture to bolster data collection in time and space. However, the ability to process these images remains a bottleneck. Computer vision can greatly increase the efficiency, repeatability and accuracy of image review. Computer vision uses image features, such as colour, shape and texture to infer image content. I provide a brief primer on ecological computer vision to outline its goals, tools and applications to animal ecology. I reviewed 187 existing applications of computer vision and divided articles into ecological description, counting and identity tasks. I discuss recommendations for enhancing the collaboration between ecologists and computer scientists and highlight areas for future growth of automated image analysis. © 2017 The Author. Journal of Animal Ecology © 2017 British Ecological Society.

G-CNV: A GPU-Based Tool for Preparing Data to Detect CNVs with Read-Depth Methods.

PubMed

Manconi, Andrea; Manca, Emanuele; Moscatelli, Marco; Gnocchi, Matteo; Orro, Alessandro; Armano, Giuliano; Milanesi, Luciano

2015-01-01

Copy number variations (CNVs) are the most prevalent types of structural variations (SVs) in the human genome and are involved in a wide range of common human diseases. Different computational methods have been devised to detect this type of SVs and to study how they are implicated in human diseases. Recently, computational methods based on high-throughput sequencing (HTS) are increasingly used. The majority of these methods focus on mapping short-read sequences generated from a donor against a reference genome to detect signatures distinctive of CNVs. In particular, read-depth based methods detect CNVs by analyzing genomic regions with significantly different read-depth from the other ones. The pipeline analysis of these methods consists of four main stages: (i) data preparation, (ii) data normalization, (iii) CNV regions identification, and (iv) copy number estimation. However, available tools do not support most of the operations required at the first two stages of this pipeline. Typically, they start the analysis by building the read-depth signal from pre-processed alignments. Therefore, third-party tools must be used to perform most of the preliminary operations required to build the read-depth signal. These data-intensive operations can be efficiently parallelized on graphics processing units (GPUs). In this article, we present G-CNV, a GPU-based tool devised to perform the common operations required at the first two stages of the analysis pipeline. G-CNV is able to filter low-quality read sequences, to mask low-quality nucleotides, to remove adapter sequences, to remove duplicated read sequences, to map the short-reads, to resolve multiple mapping ambiguities, to build the read-depth signal, and to normalize it. G-CNV can be efficiently used as a third-party tool able to prepare data for the subsequent read-depth signal generation and analysis. Moreover, it can also be integrated in CNV detection tools to generate read-depth signals.

Computer-aided resource planning and scheduling for radiological services

NASA Astrophysics Data System (ADS)

Garcia, Hong-Mei C.; Yun, David Y.; Ge, Yiqun; Khan, Javed I.

1996-05-01

There exists tremendous opportunity in hospital-wide resource optimization based on system integration. This paper defines the resource planning and scheduling requirements integral to PACS, RIS and HIS integration. An multi-site case study is conducted to define the requirements. A well-tested planning and scheduling methodology, called Constrained Resource Planning model, has been applied to the chosen problem of radiological service optimization. This investigation focuses on resource optimization issues for minimizing the turnaround time to increase clinical efficiency and customer satisfaction, particularly in cases where the scheduling of multiple exams are required for a patient. How best to combine the information system efficiency and human intelligence in improving radiological services is described. Finally, an architecture for interfacing a computer-aided resource planning and scheduling tool with the existing PACS, HIS and RIS implementation is presented.

Automated Development of Accurate Algorithms and Efficient Codes for Computational Aeroacoustics

NASA Technical Reports Server (NTRS)

Goodrich, John W.; Dyson, Rodger W.

1999-01-01

The simulation of sound generation and propagation in three space dimensions with realistic aircraft components is a very large time dependent computation with fine details. Simulations in open domains with embedded objects require accurate and robust algorithms for propagation, for artificial inflow and outflow boundaries, and for the definition of geometrically complex objects. The development, implementation, and validation of methods for solving these demanding problems is being done to support the NASA pillar goals for reducing aircraft noise levels. Our goal is to provide algorithms which are sufficiently accurate and efficient to produce usable results rapidly enough to allow design engineers to study the effects on sound levels of design changes in propulsion systems, and in the integration of propulsion systems with airframes. There is a lack of design tools for these purposes at this time. Our technical approach to this problem combines the development of new, algorithms with the use of Mathematica and Unix utilities to automate the algorithm development, code implementation, and validation. We use explicit methods to ensure effective implementation by domain decomposition for SPMD parallel computing. There are several orders of magnitude difference in the computational efficiencies of the algorithms which we have considered. We currently have new artificial inflow and outflow boundary conditions that are stable, accurate, and unobtrusive, with implementations that match the accuracy and efficiency of the propagation methods. The artificial numerical boundary treatments have been proven to have solutions which converge to the full open domain problems, so that the error from the boundary treatments can be driven as low as is required. The purpose of this paper is to briefly present a method for developing highly accurate algorithms for computational aeroacoustics, the use of computer automation in this process, and a brief survey of the algorithms that have resulted from this work. A review of computational aeroacoustics has recently been given by Lele.

Large-scale inverse model analyses employing fast randomized data reduction

NASA Astrophysics Data System (ADS)

Lin, Youzuo; Le, Ellen B.; O'Malley, Daniel; Vesselinov, Velimir V.; Bui-Thanh, Tan

2017-08-01

When the number of observations is large, it is computationally challenging to apply classical inverse modeling techniques. We have developed a new computationally efficient technique for solving inverse problems with a large number of observations (e.g., on the order of 107 or greater). Our method, which we call the randomized geostatistical approach (RGA), is built upon the principal component geostatistical approach (PCGA). We employ a data reduction technique combined with the PCGA to improve the computational efficiency and reduce the memory usage. Specifically, we employ a randomized numerical linear algebra technique based on a so-called "sketching" matrix to effectively reduce the dimension of the observations without losing the information content needed for the inverse analysis. In this way, the computational and memory costs for RGA scale with the information content rather than the size of the calibration data. Our algorithm is coded in Julia and implemented in the MADS open-source high-performance computational framework (http://mads.lanl.gov). We apply our new inverse modeling method to invert for a synthetic transmissivity field. Compared to a standard geostatistical approach (GA), our method is more efficient when the number of observations is large. Most importantly, our method is capable of solving larger inverse problems than the standard GA and PCGA approaches. Therefore, our new model inversion method is a powerful tool for solving large-scale inverse problems. The method can be applied in any field and is not limited to hydrogeological applications such as the characterization of aquifer heterogeneity.

Benchmarking the efficiency of the Chilean water and sewerage companies: a double-bootstrap approach.

PubMed

Molinos-Senante, María; Donoso, Guillermo; Sala-Garrido, Ramon; Villegas, Andrés

2018-03-01

Benchmarking the efficiency of water companies is essential to set water tariffs and to promote their sustainability. In doing so, most of the previous studies have applied conventional data envelopment analysis (DEA) models. However, it is a deterministic method that does not allow to identify environmental factors influencing efficiency scores. To overcome this limitation, this paper evaluates the efficiency of a sample of Chilean water and sewerage companies applying a double-bootstrap DEA model. Results evidenced that the ranking of water and sewerage companies changes notably whether efficiency scores are computed applying conventional or double-bootstrap DEA models. Moreover, it was found that the percentage of non-revenue water and customer density are factors influencing the efficiency of Chilean water and sewerage companies. This paper illustrates the importance of using a robust and reliable method to increase the relevance of benchmarking tools.

An implicit higher-order spatially accurate scheme for solving time dependent flows on unstructured meshes

NASA Astrophysics Data System (ADS)

Tomaro, Robert F.

1998-07-01

The present research is aimed at developing a higher-order, spatially accurate scheme for both steady and unsteady flow simulations using unstructured meshes. The resulting scheme must work on a variety of general problems to ensure the creation of a flexible, reliable and accurate aerodynamic analysis tool. To calculate the flow around complex configurations, unstructured grids and the associated flow solvers have been developed. Efficient simulations require the minimum use of computer memory and computational times. Unstructured flow solvers typically require more computer memory than a structured flow solver due to the indirect addressing of the cells. The approach taken in the present research was to modify an existing three-dimensional unstructured flow solver to first decrease the computational time required for a solution and then to increase the spatial accuracy. The terms required to simulate flow involving non-stationary grids were also implemented. First, an implicit solution algorithm was implemented to replace the existing explicit procedure. Several test cases, including internal and external, inviscid and viscous, two-dimensional, three-dimensional and axi-symmetric problems, were simulated for comparison between the explicit and implicit solution procedures. The increased efficiency and robustness of modified code due to the implicit algorithm was demonstrated. Two unsteady test cases, a plunging airfoil and a wing undergoing bending and torsion, were simulated using the implicit algorithm modified to include the terms required for a moving and/or deforming grid. Secondly, a higher than second-order spatially accurate scheme was developed and implemented into the baseline code. Third- and fourth-order spatially accurate schemes were implemented and tested. The original dissipation was modified to include higher-order terms and modified near shock waves to limit pre- and post-shock oscillations. The unsteady cases were repeated using the higher-order spatially accurate code. The new solutions were compared with those obtained using the second-order spatially accurate scheme. Finally, the increased efficiency of using an implicit solution algorithm in a production Computational Fluid Dynamics flow solver was demonstrated for steady and unsteady flows. A third- and fourth-order spatially accurate scheme has been implemented creating a basis for a state-of-the-art aerodynamic analysis tool.

The Hematopoietic Expression Viewer: expanding mobile apps as a scientific tool.

PubMed

James, Regis A; Rao, Mitchell M; Chen, Edward S; Goodell, Margaret A; Shaw, Chad A

2012-07-15

Many important data in current biological science comprise hundreds, thousands or more individual results. These massive data require computational tools to navigate results and effectively interact with the content. Mobile device apps are an increasingly important tool in the everyday lives of scientists and non-scientists alike. These software present individuals with compact and efficient tools to interact with complex data at meetings or other locations remote from their main computing environment. We believe that apps will be important tools for biologists, geneticists and physicians to review content while participating in biomedical research or practicing medicine. We have developed a prototype app for displaying gene expression data using the iOS platform. To present the software engineering requirements, we review the model-view-controller schema for Apple's iOS. We apply this schema to a simple app for querying locally developed microarray gene expression data. The challenge of this application is to balance between storing content locally within the app versus obtaining it dynamically via a network connection. The Hematopoietic Expression Viewer is available at http://www.shawlab.org/he_viewer. The source code for this project and any future information on how to obtain the app can be accessed at http://www.shawlab.org/he_viewer.

The reduced basis method for the electric field integral equation

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

Fares, M., E-mail: fares@cerfacs.f; Hesthaven, J.S., E-mail: Jan_Hesthaven@Brown.ed; Maday, Y., E-mail: maday@ann.jussieu.f

We introduce the reduced basis method (RBM) as an efficient tool for parametrized scattering problems in computational electromagnetics for problems where field solutions are computed using a standard Boundary Element Method (BEM) for the parametrized electric field integral equation (EFIE). This combination enables an algorithmic cooperation which results in a two step procedure. The first step consists of a computationally intense assembling of the reduced basis, that needs to be effected only once. In the second step, we compute output functionals of the solution, such as the Radar Cross Section (RCS), independently of the dimension of the discretization space, formore » many different parameter values in a many-query context at very little cost. Parameters include the wavenumber, the angle of the incident plane wave and its polarization.« less

Multiple shooting shadowing for sensitivity analysis of chaotic dynamical systems

NASA Astrophysics Data System (ADS)

Blonigan, Patrick J.; Wang, Qiqi

2018-02-01

Sensitivity analysis methods are important tools for research and design with simulations. Many important simulations exhibit chaotic dynamics, including scale-resolving turbulent fluid flow simulations. Unfortunately, conventional sensitivity analysis methods are unable to compute useful gradient information for long-time-averaged quantities in chaotic dynamical systems. Sensitivity analysis with least squares shadowing (LSS) can compute useful gradient information for a number of chaotic systems, including simulations of chaotic vortex shedding and homogeneous isotropic turbulence. However, this gradient information comes at a very high computational cost. This paper presents multiple shooting shadowing (MSS), a more computationally efficient shadowing approach than the original LSS approach. Through an analysis of the convergence rate of MSS, it is shown that MSS can have lower memory usage and run time than LSS.

XS: a FASTQ read simulator.

PubMed

Pratas, Diogo; Pinho, Armando J; Rodrigues, João M O S

2014-01-16

The emerging next-generation sequencing (NGS) is bringing, besides the natural huge amounts of data, an avalanche of new specialized tools (for analysis, compression, alignment, among others) and large public and private network infrastructures. Therefore, a direct necessity of specific simulation tools for testing and benchmarking is rising, such as a flexible and portable FASTQ read simulator, without the need of a reference sequence, yet correctly prepared for producing approximately the same characteristics as real data. We present XS, a skilled FASTQ read simulation tool, flexible, portable (does not need a reference sequence) and tunable in terms of sequence complexity. It has several running modes, depending on the time and memory available, and is aimed at testing computing infrastructures, namely cloud computing of large-scale projects, and testing FASTQ compression algorithms. Moreover, XS offers the possibility of simulating the three main FASTQ components individually (headers, DNA sequences and quality-scores). XS provides an efficient and convenient method for fast simulation of FASTQ files, such as those from Ion Torrent (currently uncovered by other simulators), Roche-454, Illumina and ABI-SOLiD sequencing machines. This tool is publicly available at http://bioinformatics.ua.pt/software/xs/.

ReSeqTools: an integrated toolkit for large-scale next-generation sequencing based resequencing analysis.

PubMed

He, W; Zhao, S; Liu, X; Dong, S; Lv, J; Liu, D; Wang, J; Meng, Z

2013-12-04

Large-scale next-generation sequencing (NGS)-based resequencing detects sequence variations, constructs evolutionary histories, and identifies phenotype-related genotypes. However, NGS-based resequencing studies generate extraordinarily large amounts of data, making computations difficult. Effective use and analysis of these data for NGS-based resequencing studies remains a difficult task for individual researchers. Here, we introduce ReSeqTools, a full-featured toolkit for NGS (Illumina sequencing)-based resequencing analysis, which processes raw data, interprets mapping results, and identifies and annotates sequence variations. ReSeqTools provides abundant scalable functions for routine resequencing analysis in different modules to facilitate customization of the analysis pipeline. ReSeqTools is designed to use compressed data files as input or output to save storage space and facilitates faster and more computationally efficient large-scale resequencing studies in a user-friendly manner. It offers abundant practical functions and generates useful statistics during the analysis pipeline, which significantly simplifies resequencing analysis. Its integrated algorithms and abundant sub-functions provide a solid foundation for special demands in resequencing projects. Users can combine these functions to construct their own pipelines for other purposes.

Modeling RF-induced Plasma-Surface Interactions with VSim

NASA Astrophysics Data System (ADS)

Jenkins, Thomas G.; Smithe, David N.; Pankin, Alexei Y.; Roark, Christine M.; Stoltz, Peter H.; Zhou, Sean C.-D.; Kruger, Scott E.

2014-10-01

An overview of ongoing enhancements to the Plasma Discharge (PD) module of Tech-X's VSim software tool is presented. A sub-grid kinetic sheath model, developed for the accurate computation of sheath potentials near metal and dielectric-coated walls, enables the physical effects of DC and RF sheath dynamics to be included in macroscopic-scale plasma simulations that need not explicitly resolve sheath scale lengths. Sheath potential evolution, together with particle behavior near the sheath (e.g. sputtering), can thus be simulated in complex, experimentally relevant geometries. Simulations of RF sheath-enhanced impurity production near surfaces of the C-Mod field-aligned ICRF antenna are presented to illustrate the model; impurity mitigation techniques are also explored. Model extensions to capture the physics of secondary electron emission and of multispecies plasmas are summarized, together with a discussion of improved tools for plasma chemistry and IEDF/EEDF visualization and modeling. The latter tools are also highly relevant for commercial plasma processing applications. Ultimately, we aim to establish VSimPD as a robust, efficient computational tool for modeling fusion and industrial plasma processes. Supported by U.S. DoE SBIR Phase I/II Award DE-SC0009501.

Secure and Efficient Regression Analysis Using a Hybrid Cryptographic Framework: Development and Evaluation

PubMed Central

Jiang, Xiaoqian; Aziz, Md Momin Al; Wang, Shuang; Mohammed, Noman

2018-01-01

Background Machine learning is an effective data-driven tool that is being widely used to extract valuable patterns and insights from data. Specifically, predictive machine learning models are very important in health care for clinical data analysis. The machine learning algorithms that generate predictive models often require pooling data from different sources to discover statistical patterns or correlations among different attributes of the input data. The primary challenge is to fulfill one major objective: preserving the privacy of individuals while discovering knowledge from data. Objective Our objective was to develop a hybrid cryptographic framework for performing regression analysis over distributed data in a secure and efficient way. Methods Existing secure computation schemes are not suitable for processing the large-scale data that are used in cutting-edge machine learning applications. We designed, developed, and evaluated a hybrid cryptographic framework, which can securely perform regression analysis, a fundamental machine learning algorithm using somewhat homomorphic encryption and a newly introduced secure hardware component of Intel Software Guard Extensions (Intel SGX) to ensure both privacy and efficiency at the same time. Results Experimental results demonstrate that our proposed method provides a better trade-off in terms of security and efficiency than solely secure hardware-based methods. Besides, there is no approximation error. Computed model parameters are exactly similar to plaintext results. Conclusions To the best of our knowledge, this kind of secure computation model using a hybrid cryptographic framework, which leverages both somewhat homomorphic encryption and Intel SGX, is not proposed or evaluated to this date. Our proposed framework ensures data security and computational efficiency at the same time. PMID:29506966

Secure and Efficient Regression Analysis Using a Hybrid Cryptographic Framework: Development and Evaluation.

PubMed

Sadat, Md Nazmus; Jiang, Xiaoqian; Aziz, Md Momin Al; Wang, Shuang; Mohammed, Noman

2018-03-05

Machine learning is an effective data-driven tool that is being widely used to extract valuable patterns and insights from data. Specifically, predictive machine learning models are very important in health care for clinical data analysis. The machine learning algorithms that generate predictive models often require pooling data from different sources to discover statistical patterns or correlations among different attributes of the input data. The primary challenge is to fulfill one major objective: preserving the privacy of individuals while discovering knowledge from data. Our objective was to develop a hybrid cryptographic framework for performing regression analysis over distributed data in a secure and efficient way. Existing secure computation schemes are not suitable for processing the large-scale data that are used in cutting-edge machine learning applications. We designed, developed, and evaluated a hybrid cryptographic framework, which can securely perform regression analysis, a fundamental machine learning algorithm using somewhat homomorphic encryption and a newly introduced secure hardware component of Intel Software Guard Extensions (Intel SGX) to ensure both privacy and efficiency at the same time. Experimental results demonstrate that our proposed method provides a better trade-off in terms of security and efficiency than solely secure hardware-based methods. Besides, there is no approximation error. Computed model parameters are exactly similar to plaintext results. To the best of our knowledge, this kind of secure computation model using a hybrid cryptographic framework, which leverages both somewhat homomorphic encryption and Intel SGX, is not proposed or evaluated to this date. Our proposed framework ensures data security and computational efficiency at the same time. ©Md Nazmus Sadat, Xiaoqian Jiang, Md Momin Al Aziz, Shuang Wang, Noman Mohammed. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 05.03.2018.

Modeling methods of MEMS micro-speaker with electrostatic working principle

NASA Astrophysics Data System (ADS)

Tumpold, D.; Kaltenbacher, M.; Glacer, C.; Nawaz, M.; Dehé, A.

2013-05-01

The market for mobile devices like tablets, laptops or mobile phones is increasing rapidly. Device housings get thinner and energy efficiency is more and more important. Micro-Electro-Mechanical-System (MEMS) loudspeakers, fabricated in complementary metal oxide semiconductor (CMOS) compatible technology merge energy efficient driving technology with cost economical fabrication processes. In most cases, the fabrication of such devices within the design process is a lengthy and costly task. Therefore, the need for computer modeling tools capable of precisely simulating the multi-field interactions is increasing. The accurate modeling of such MEMS devices results in a system of coupled partial differential equations (PDEs) describing the interaction between the electric, mechanical and acoustic field. For the efficient and accurate solution we apply the Finite Element (FE) method. Thereby, we fully take the nonlinear effects into account: electrostatic force, charged moving body (loaded membrane) in an electric field, geometric nonlinearities and mechanical contact during the snap-in case between loaded membrane and stator. To efficiently handle the coupling between the mechanical and acoustic fields, we apply Mortar FE techniques, which allow different grid sizes along the coupling interface. Furthermore, we present a recently developed PML (Perfectly Matched Layer) technique, which allows limiting the acoustic computational domain even in the near field without getting spurious reflections. For computations towards the acoustic far field we us a Kirchhoff Helmholtz integral (e.g, to compute the directivity pattern). We will present simulations of a MEMS speaker system based on a single sided driving mechanism as well as an outlook on MEMS speakers using double stator systems (pull-pull-system), and discuss their efficiency (SPL) and quality (THD) towards the generated acoustic sound.

On the evaluation of segmentation editing tools

PubMed Central

Heckel, Frank; Moltz, Jan H.; Meine, Hans; Geisler, Benjamin; Kießling, Andreas; D’Anastasi, Melvin; dos Santos, Daniel Pinto; Theruvath, Ashok Joseph; Hahn, Horst K.

2014-01-01

Abstract. Efficient segmentation editing tools are important components in the segmentation process, as no automatic methods exist that always generate sufficient results. Evaluating segmentation editing algorithms is challenging, because their quality depends on the user’s subjective impression. So far, no established methods for an objective, comprehensive evaluation of such tools exist and, particularly, intermediate segmentation results are not taken into account. We discuss the evaluation of editing algorithms in the context of tumor segmentation in computed tomography. We propose a rating scheme to qualitatively measure the accuracy and efficiency of editing tools in user studies. In order to objectively summarize the overall quality, we propose two scores based on the subjective rating and the quantified segmentation quality over time. Finally, a simulation-based evaluation approach is discussed, which allows a more reproducible evaluation without the need for human input. This automated evaluation complements user studies, allowing a more convincing evaluation, particularly during development, where frequent user studies are not possible. The proposed methods have been used to evaluate two dedicated editing algorithms on 131 representative tumor segmentations. We show how the comparison of editing algorithms benefits from the proposed methods. Our results also show the correlation of the suggested quality score with the qualitative ratings. PMID:26158063

OLTARIS: An Efficient Web-Based Tool for Analyzing Materials Exposed to Space Radiation

NASA Technical Reports Server (NTRS)

Slaba, Tony; McMullen, Amelia M.; Thibeault, Sheila A.; Sandridge, Chris A.; Clowdsley, Martha S.; Blatting, Steve R.

2011-01-01

The near-Earth space radiation environment includes energetic galactic cosmic rays (GCR), high intensity proton and electron belts, and the potential for solar particle events (SPE). These sources may penetrate shielding materials and deposit significant energy in sensitive electronic devices on board spacecraft and satellites. Material and design optimization methods may be used to reduce the exposure and extend the operational lifetime of individual components and systems. Since laboratory experiments are expensive and may not cover the range of particles and energies relevant for space applications, such optimization may be done computationally with efficient algorithms that include the various constraints placed on the component, system, or mission. In the present work, the web-based tool OLTARIS (On-Line Tool for the Assessment of Radiation in Space) is presented, and the applicability of the tool for rapidly analyzing exposure levels within either complicated shielding geometries or user-defined material slabs exposed to space radiation is demonstrated. An example approach for material optimization is also presented. Slabs of various advanced multifunctional materials are defined and exposed to several space radiation environments. The materials and thicknesses defining each layer in the slab are then systematically adjusted to arrive at an optimal slab configuration.

A new approach to road accident rescue.

PubMed

Morales, Alejandro; González-Aguilera, Diego; López, Alfonso I; Gutiérrez, Miguel A

2016-01-01

This article develops and validates a new methodology and tool for rescue assistance in traffic accidents, with the aim of improving its efficiency and safety in the evacuation of people, reducing the number of victims in road accidents. Different tests supported by professionals and experts have been designed under different circumstances and with different categories of damaged vehicles coming from real accidents and simulated trapped victims in order to calibrate and refine the proposed methodology and tool. To validate this new approach, a tool called App_Rescue has been developed. This tool is based on the use of a computer system that allows an efficient access to the technical information of the vehicle and sanitary information of the common passengers. The time spent during rescue using the standard protocol and the proposed method was compared. This rescue assistance system allows us to make vital information accessible in posttrauma care services, improving the effectiveness of interventions by the emergency services, reducing the rescue time and therefore minimizing the consequences involved and the number of victims. This could often mean saving lives. In the different simulated rescue operations, the rescue time has been reduced an average of 14%.

Morphogenic designer--an efficient tool to digitally design tooth forms.

PubMed

Hajtó, J; Marinescu, C; Silva, N R F A

2014-01-01

Different digital software tools are available today for the purpose of designing anatomically correct anterior and posterior restorations. The current concepts present weaknesses, which can be potentially addressed by more advanced modeling tools, such as the ones already available in professional CAD (Computer Aided Design) graphical software. This study describes the morphogenic designer (MGD) as an efficient and easy method for digitally designing tooth forms for the anterior and posterior dentition. Anterior and posterior tooth forms were selected from a collection of digitalized natural teeth and subjectively assessed as "average". The models in the form of STL files were filtered, cleaned, idealized, and re-meshed to match the specifications of the software used. The shapes were then imported as wavefront ".obj" model into Modo 701, software built for modeling, texturing, visualization, and animation. In order to create a parametric design system, intentional interactive deformations were performed on the average tooth shapes and then further defined as morph targets. By combining various such parameters, several tooth shapes were formed virtually and their images presented. MGD proved to be a versatile and powerful tool for the purpose of esthetic and functional digital crown designs.

MITHRA 1.0: A full-wave simulation tool for free electron lasers

NASA Astrophysics Data System (ADS)

Fallahi, Arya; Yahaghi, Alireza; Kärtner, Franz X.

2018-07-01

Free Electron Lasers (FELs) are a solution for providing intense, coherent and bright radiation in the hard X-ray regime. Due to the low wall-plug efficiency of FEL facilities, it is crucial and additionally very useful to develop complete and accurate simulation tools for better optimizing a FEL interaction. The highly sophisticated dynamics involved in a FEL process was the main obstacle hindering the development of general simulation tools for this problem. We present a numerical algorithm based on finite difference time domain/Particle in cell (FDTD/PIC) in a Lorentz boosted coordinate system which is able to fulfill a full-wave simulation of a FEL process. The developed software offers a suitable tool for the analysis of FEL interactions without considering any of the usual approximations. A coordinate transformation to bunch rest frame makes the very different length scales of bunch size, optical wavelengths and the undulator period transform to values with the same order. Consequently, FDTD/PIC simulations in conjunction with efficient parallelization techniques make the full-wave simulation feasible using the available computational resources. Several examples of free electron lasers are analyzed using the developed software, the results are benchmarked based on standard FEL codes and discussed in detail.

Electron-Ion Dynamics with Time-Dependent Density Functional Theory: Towards Predictive Solar Cell Modeling: Final Technical Report

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

Maitra, Neepa

2016-07-14

This project investigates the accuracy of currently-used functionals in time-dependent density functional theory, which is today routinely used to predict and design materials and computationally model processes in solar energy conversion. The rigorously-based electron-ion dynamics method developed here sheds light on traditional methods and overcomes challenges those methods have. The fundamental research undertaken here is important for building reliable and practical methods for materials discovery. The ultimate goal is to use these tools for the computational design of new materials for solar cell devices of high efficiency.

An Introduction to the BFS Method and Its Use to Model Binary NiAl Alloys

NASA Technical Reports Server (NTRS)

Bozzolo, Guillermo; Noebe, Ronald D.; Ferrante, J.; Amador, C.

1998-01-01

We introduce the Bozzolo-Ferrante-Smith (BFS) method for alloys as a computationally efficient tool for aiding in the process of alloy design. An intuitive description of the BFS method is provided, followed by a formal discussion of its implementation. The method is applied to the study of the defect structure of NiAl binary alloys. The groundwork is laid for a detailed progression to higher order NiAl-based alloys linking theoretical calculations and computer simulations based on the BFS method and experimental work validating each step of the alloy design process.

Cloud-Based Tools to Support High-Resolution Modeling (Invited)

NASA Astrophysics Data System (ADS)

Jones, N.; Nelson, J.; Swain, N.; Christensen, S.

2013-12-01

The majority of watershed models developed to support decision-making by water management agencies are simple, lumped-parameter models. Maturity in research codes and advances in the computational power from multi-core processors on desktop machines, commercial cloud-computing resources, and supercomputers with thousands of cores have created new opportunities for employing more accurate, high-resolution distributed models for routine use in decision support. The barriers for using such models on a more routine basis include massive amounts of spatial data that must be processed for each new scenario and lack of efficient visualization tools. In this presentation we will review a current NSF-funded project called CI-WATER that is intended to overcome many of these roadblocks associated with high-resolution modeling. We are developing a suite of tools that will make it possible to deploy customized web-based apps for running custom scenarios for high-resolution models with minimal effort. These tools are based on a software stack that includes 52 North, MapServer, PostGIS, HT Condor, CKAN, and Python. This open source stack provides a simple scripting environment for quickly configuring new custom applications for running high-resolution models as geoprocessing workflows. The HT Condor component facilitates simple access to local distributed computers or commercial cloud resources when necessary for stochastic simulations. The CKAN framework provides a powerful suite of tools for hosting such workflows in a web-based environment that includes visualization tools and storage of model simulations in a database to archival, querying, and sharing of model results. Prototype applications including land use change, snow melt, and burned area analysis will be presented. This material is based upon work supported by the National Science Foundation under Grant No. 1135482

Blazing Signature Filter: a library for fast pairwise similarity comparisons

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

Lee, Joon-Yong; Fujimoto, Grant M.; Wilson, Ryan

Identifying similarities between datasets is a fundamental task in data mining and has become an integral part of modern scientific investigation. Whether the task is to identify co-expressed genes in large-scale expression surveys or to predict combinations of gene knockouts which would elicit a similar phenotype, the underlying computational task is often a multi-dimensional similarity test. As datasets continue to grow, improvements to the efficiency, sensitivity or specificity of such computation will have broad impacts as it allows scientists to more completely explore the wealth of scientific data. A significant practical drawback of large-scale data mining is the vast majoritymore » of pairwise comparisons are unlikely to be relevant, meaning that they do not share a signature of interest. It is therefore essential to efficiently identify these unproductive comparisons as rapidly as possible and exclude them from more time-intensive similarity calculations. The Blazing Signature Filter (BSF) is a highly efficient pairwise similarity algorithm which enables extensive data mining within a reasonable amount of time. The algorithm transforms datasets into binary metrics, allowing it to utilize the computationally efficient bit operators and provide a coarse measure of similarity. As a result, the BSF can scale to high dimensionality and rapidly filter unproductive pairwise comparison. Two bioinformatics applications of the tool are presented to demonstrate the ability to scale to billions of pairwise comparisons and the usefulness of this approach.« less

Natural language processing and the Now-or-Never bottleneck.

PubMed

Gómez-Rodríguez, Carlos

2016-01-01

Researchers, motivated by the need to improve the efficiency of natural language processing tools to handle web-scale data, have recently arrived at models that remarkably match the expected features of human language processing under the Now-or-Never bottleneck framework. This provides additional support for said framework and highlights the research potential in the interaction between applied computational linguistics and cognitive science.

Crux: Rapid Open Source Protein Tandem Mass Spectrometry Analysis

PubMed Central

2015-01-01

Efficiently and accurately analyzing big protein tandem mass spectrometry data sets requires robust software that incorporates state-of-the-art computational, machine learning, and statistical methods. The Crux mass spectrometry analysis software toolkit (http://cruxtoolkit.sourceforge.net) is an open source project that aims to provide users with a cross-platform suite of analysis tools for interpreting protein mass spectrometry data. PMID:25182276

The Integrated Waste Tracking System - A Flexible Waste Management Tool

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

Anderson, Robert Stephen

2001-02-01

The US Department of Energy (DOE) Idaho National Engineering and Environmental Laboratory (INEEL) has fully embraced a flexible, computer-based tool to help increase waste management efficiency and integrate multiple operational functions from waste generation through waste disposition while reducing cost. The Integrated Waste Tracking System (IWTS)provides comprehensive information management for containerized waste during generation,storage, treatment, transport, and disposal. The IWTS provides all information necessary for facilities to properly manage and demonstrate regulatory compliance. As a platformindependent, client-server and Web-based inventory and compliance system, the IWTS has proven to be a successful tracking, characterization, compliance, and reporting tool that meets themore » needs of both operations and management while providing a high level of management flexibility.« less

Efficient computation of the joint probability of multiple inherited risk alleles from pedigree data.

PubMed

Madsen, Thomas; Braun, Danielle; Peng, Gang; Parmigiani, Giovanni; Trippa, Lorenzo

2018-06-25

The Elston-Stewart peeling algorithm enables estimation of an individual's probability of harboring germline risk alleles based on pedigree data, and serves as the computational backbone of important genetic counseling tools. However, it remains limited to the analysis of risk alleles at a small number of genetic loci because its computing time grows exponentially with the number of loci considered. We propose a novel, approximate version of this algorithm, dubbed the peeling and paring algorithm, which scales polynomially in the number of loci. This allows extending peeling-based models to include many genetic loci. The algorithm creates a trade-off between accuracy and speed, and allows the user to control this trade-off. We provide exact bounds on the approximation error and evaluate it in realistic simulations. Results show that the loss of accuracy due to the approximation is negligible in important applications. This algorithm will improve genetic counseling tools by increasing the number of pathogenic risk alleles that can be addressed. To illustrate we create an extended five genes version of BRCAPRO, a widely used model for estimating the carrier probabilities of BRCA1 and BRCA2 risk alleles and assess its computational properties. © 2018 WILEY PERIODICALS, INC.

LEMON - LHC Era Monitoring for Large-Scale Infrastructures

NASA Astrophysics Data System (ADS)

Marian, Babik; Ivan, Fedorko; Nicholas, Hook; Hector, Lansdale Thomas; Daniel, Lenkes; Miroslav, Siket; Denis, Waldron

2011-12-01

At the present time computer centres are facing a massive rise in virtualization and cloud computing as these solutions bring advantages to service providers and consolidate the computer centre resources. However, as a result the monitoring complexity is increasing. Computer centre management requires not only to monitor servers, network equipment and associated software but also to collect additional environment and facilities data (e.g. temperature, power consumption, cooling efficiency, etc.) to have also a good overview of the infrastructure performance. The LHC Era Monitoring (Lemon) system is addressing these requirements for a very large scale infrastructure. The Lemon agent that collects data on every client and forwards the samples to the central measurement repository provides a flexible interface that allows rapid development of new sensors. The system allows also to report on behalf of remote devices such as switches and power supplies. Online and historical data can be visualized via a web-based interface or retrieved via command-line tools. The Lemon Alarm System component can be used for notifying the operator about error situations. In this article, an overview of the Lemon monitoring is provided together with a description of the CERN LEMON production instance. No direct comparison is made with other monitoring tool.

HammerCloud: A Stress Testing System for Distributed Analysis

NASA Astrophysics Data System (ADS)

van der Ster, Daniel C.; Elmsheuser, Johannes; Úbeda García, Mario; Paladin, Massimo

2011-12-01

Distributed analysis of LHC data is an I/O-intensive activity which places large demands on the internal network, storage, and local disks at remote computing facilities. Commissioning and maintaining a site to provide an efficient distributed analysis service is therefore a challenge which can be aided by tools to help evaluate a variety of infrastructure designs and configurations. HammerCloud is one such tool; it is a stress testing service which is used by central operations teams, regional coordinators, and local site admins to (a) submit arbitrary number of analysis jobs to a number of sites, (b) maintain at a steady-state a predefined number of jobs running at the sites under test, (c) produce web-based reports summarizing the efficiency and performance of the sites under test, and (d) present a web-interface for historical test results to both evaluate progress and compare sites. HammerCloud was built around the distributed analysis framework Ganga, exploiting its API for grid job management. HammerCloud has been employed by the ATLAS experiment for continuous testing of many sites worldwide, and also during large scale computing challenges such as STEP'09 and UAT'09, where the scale of the tests exceeded 10,000 concurrently running and 1,000,000 total jobs over multi-day periods. In addition, HammerCloud is being adopted by the CMS experiment; the plugin structure of HammerCloud allows the execution of CMS jobs using their official tool (CRAB).

SCNS: a graphical tool for reconstructing executable regulatory networks from single-cell genomic data.

PubMed

Woodhouse, Steven; Piterman, Nir; Wintersteiger, Christoph M; Göttgens, Berthold; Fisher, Jasmin

2018-05-25

Reconstruction of executable mechanistic models from single-cell gene expression data represents a powerful approach to understanding developmental and disease processes. New ambitious efforts like the Human Cell Atlas will soon lead to an explosion of data with potential for uncovering and understanding the regulatory networks which underlie the behaviour of all human cells. In order to take advantage of this data, however, there is a need for general-purpose, user-friendly and efficient computational tools that can be readily used by biologists who do not have specialist computer science knowledge. The Single Cell Network Synthesis toolkit (SCNS) is a general-purpose computational tool for the reconstruction and analysis of executable models from single-cell gene expression data. Through a graphical user interface, SCNS takes single-cell qPCR or RNA-sequencing data taken across a time course, and searches for logical rules that drive transitions from early cell states towards late cell states. Because the resulting reconstructed models are executable, they can be used to make predictions about the effect of specific gene perturbations on the generation of specific lineages. SCNS should be of broad interest to the growing number of researchers working in single-cell genomics and will help further facilitate the generation of valuable mechanistic insights into developmental, homeostatic and disease processes.

OVERSMART Reporting Tool for Flow Computations Over Large Grid Systems

NASA Technical Reports Server (NTRS)

Kao, David L.; Chan, William M.

2012-01-01

Structured grid solvers such as NASA's OVERFLOW compressible Navier-Stokes flow solver can generate large data files that contain convergence histories for flow equation residuals, turbulence model equation residuals, component forces and moments, and component relative motion dynamics variables. Most of today's large-scale problems can extend to hundreds of grids, and over 100 million grid points. However, due to the lack of efficient tools, only a small fraction of information contained in these files is analyzed. OVERSMART (OVERFLOW Solution Monitoring And Reporting Tool) provides a comprehensive report of solution convergence of flow computations over large, complex grid systems. It produces a one-page executive summary of the behavior of flow equation residuals, turbulence model equation residuals, and component forces and moments. Under the automatic option, a matrix of commonly viewed plots such as residual histograms, composite residuals, sub-iteration bar graphs, and component forces and moments is automatically generated. Specific plots required by the user can also be prescribed via a command file or a graphical user interface. Output is directed to the user s computer screen and/or to an html file for archival purposes. The current implementation has been targeted for the OVERFLOW flow solver, which is used to obtain a flow solution on structured overset grids. The OVERSMART framework allows easy extension to other flow solvers.

Assessment of Near-Field Sonic Boom Simulation Tools

NASA Technical Reports Server (NTRS)

Casper, J. H.; Cliff, S. E.; Thomas, S. D.; Park, M. A.; McMullen, M. S.; Melton, J. E.; Durston, D. A.

2008-01-01

A recent study for the Supersonics Project, within the National Aeronautics and Space Administration, has been conducted to assess current in-house capabilities for the prediction of near-field sonic boom. Such capabilities are required to simulate the highly nonlinear flow near an aircraft, wherein a sonic-boom signature is generated. There are many available computational fluid dynamics codes that could be used to provide the near-field flow for a sonic boom calculation. However, such codes have typically been developed for applications involving aerodynamic configuration, for which an efficiently generated computational mesh is usually not optimum for a sonic boom prediction. Preliminary guidelines are suggested to characterize a state-of-the-art sonic boom prediction methodology. The available simulation tools that are best suited to incorporate into that methodology are identified; preliminary test cases are presented in support of the selection. During this phase of process definition and tool selection, parallel research was conducted in an attempt to establish criteria that link the properties of a computational mesh to the accuracy of a sonic boom prediction. Such properties include sufficient grid density near shocks and within the zone of influence, which are achieved by adaptation and mesh refinement strategies. Prediction accuracy is validated by comparison with wind tunnel data.

Object-oriented design and implementation of CFDLab: a computer-assisted learning tool for fluid dynamics using dual reciprocity boundary element methodology

NASA Astrophysics Data System (ADS)

Friedrich, J.

1999-08-01

As lecturers, our main concern and goal is to develop more attractive and efficient ways of communicating up-to-date scientific knowledge to our students and facilitate an in-depth understanding of physical phenomena. Computer-based instruction is very promising to help both teachers and learners in their difficult task, which involves complex cognitive psychological processes. This complexity is reflected in high demands on the design and implementation methods used to create computer-assisted learning (CAL) programs. Due to their concepts, flexibility, maintainability and extended library resources, object-oriented modeling techniques are very suitable to produce this type of pedagogical tool. Computational fluid dynamics (CFD) enjoys not only a growing importance in today's research, but is also very powerful for teaching and learning fluid dynamics. For this purpose, an educational PC program for university level called 'CFDLab 1.1' for Windows™ was developed with an interactive graphical user interface (GUI) for multitasking and point-and-click operations. It uses the dual reciprocity boundary element method as a versatile numerical scheme, allowing to handle a variety of relevant governing equations in two dimensions on personal computers due to its simple pre- and postprocessing including 2D Laplace, Poisson, diffusion, transient convection-diffusion.

Distributed geospatial model sharing based on open interoperability standards

USGS Publications Warehouse

Feng, Min; Liu, Shuguang; Euliss, Ned H.; Fang, Yin

2009-01-01

Numerous geospatial computational models have been developed based on sound principles and published in journals or presented in conferences. However modelers have made few advances in the development of computable modules that facilitate sharing during model development or utilization. Constraints hampering development of model sharing technology includes limitations on computing, storage, and connectivity; traditional stand-alone and closed network systems cannot fully support sharing and integrating geospatial models. To address this need, we have identified methods for sharing geospatial computational models using Service Oriented Architecture (SOA) techniques and open geospatial standards. The service-oriented model sharing service is accessible using any tools or systems compliant with open geospatial standards, making it possible to utilize vast scientific resources available from around the world to solve highly sophisticated application problems. The methods also allow model services to be empowered by diverse computational devices and technologies, such as portable devices and GRID computing infrastructures. Based on the generic and abstract operations and data structures required for Web Processing Service (WPS) standards, we developed an interactive interface for model sharing to help reduce interoperability problems for model use. Geospatial computational models are shared on model services, where the computational processes provided by models can be accessed through tools and systems compliant with WPS. We developed a platform to help modelers publish individual models in a simplified and efficient way. Finally, we illustrate our technique using wetland hydrological models we developed for the prairie pothole region of North America.

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

Karp, Peter D.

Pathway Tools is a systems-biology software package written by SRI International (SRI) that produces Pathway/Genome Databases (PGDBs) for organisms with a sequenced genome. Pathway Tools also provides a wide range of capabilities for analyzing predicted metabolic networks and user-generated omics data. More than 5,000 academic, industrial, and government groups have licensed Pathway Tools. This user community includes researchers at all three DOE bioenergy centers, as well as academic and industrial metabolic engineering (ME) groups. An integral part of the Pathway Tools software is MetaCyc, a large, multiorganism database of metabolic pathways and enzymes that SRI and its academic collaborators manuallymore » curate. This project included two main goals: I. Enhance the MetaCyc content of bioenergy-related enzymes and pathways. II. Develop computational tools for engineering metabolic pathways that satisfy specified design goals, in particular for bioenergy-related pathways. In part I, SRI proposed to significantly expand the coverage of bioenergy-related metabolic information in MetaCyc, followed by the generation of organism-specific PGDBs for all energy-relevant organisms sequenced at the DOE Joint Genome Institute (JGI). Part I objectives included: 1: Expand the content of MetaCyc to include bioenergy-related enzymes and pathways. 2: Enhance the Pathway Tools software to enable display of complex polymer degradation processes. 3: Create new PGDBs for the energy-related organisms sequenced by JGI, update existing PGDBs with new MetaCyc content, and make these data available to JBEI via the BioCyc website. In part II, SRI proposed to develop an efficient computational tool for the engineering of metabolic pathways. Part II objectives included: 4: Develop computational tools for generating metabolic pathways that satisfy specified design goals, enabling users to specify parameters such as starting and ending compounds, and preferred or disallowed intermediate compounds. The pathways were to be generated using metabolic reactions from a reference database (DB). 5: Develop computational tools for ranking the pathways generated in objective (4) according to their optimality. The ranking criteria include stoichiometric yield, the number and cost of additional inputs and the cofactor compounds required by the pathway, pathway length, and pathway energetics. 6: Develop tools for visualizing generated pathways to facilitate the evaluation of a large space of generated pathways.« less

Tolerant (parallel) Programming

NASA Technical Reports Server (NTRS)

DiNucci, David C.; Bailey, David H. (Technical Monitor)

1997-01-01

In order to be truly portable, a program must be tolerant of a wide range of development and execution environments, and a parallel program is just one which must be tolerant of a very wide range. This paper first defines the term "tolerant programming", then describes many layers of tools to accomplish it. The primary focus is on F-Nets, a formal model for expressing computation as a folded partial-ordering of operations, thereby providing an architecture-independent expression of tolerant parallel algorithms. For implementing F-Nets, Cooperative Data Sharing (CDS) is a subroutine package for implementing communication efficiently in a large number of environments (e.g. shared memory and message passing). Software Cabling (SC), a very-high-level graphical programming language for building large F-Nets, possesses many of the features normally expected from today's computer languages (e.g. data abstraction, array operations). Finally, L2(sup 3) is a CASE tool which facilitates the construction, compilation, execution, and debugging of SC programs.

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

Hasan, Iftekhar; Husain, Tausif; Sozer, Yilmaz

This paper proposes an analytical machine design tool using magnetic equivalent circuit (MEC)-based particle swarm optimization (PSO) for a double-sided, flux-concentrating transverse flux machine (TFM). The magnetic equivalent circuit method is applied to analytically establish the relationship between the design objective and the input variables of prospective TFM designs. This is computationally less intensive and more time efficient than finite element solvers. A PSO algorithm is then used to design a machine with the highest torque density within the specified power range along with some geometric design constraints. The stator pole length, magnet length, and rotor thickness are the variablesmore » that define the optimization search space. Finite element analysis (FEA) was carried out to verify the performance of the MEC-PSO optimized machine. The proposed analytical design tool helps save computation time by at least 50% when compared to commercial FEA-based optimization programs, with results found to be in agreement with less than 5% error.« less

Psi4NumPy: An Interactive Quantum Chemistry Programming Environment for Reference Implementations and Rapid Development.

PubMed

Smith, Daniel G A; Burns, Lori A; Sirianni, Dominic A; Nascimento, Daniel R; Kumar, Ashutosh; James, Andrew M; Schriber, Jeffrey B; Zhang, Tianyuan; Zhang, Boyi; Abbott, Adam S; Berquist, Eric J; Lechner, Marvin H; Cunha, Leonardo A; Heide, Alexander G; Waldrop, Jonathan M; Takeshita, Tyler Y; Alenaizan, Asem; Neuhauser, Daniel; King, Rollin A; Simmonett, Andrew C; Turney, Justin M; Schaefer, Henry F; Evangelista, Francesco A; DePrince, A Eugene; Crawford, T Daniel; Patkowski, Konrad; Sherrill, C David

2018-06-11

Psi4NumPy demonstrates the use of efficient computational kernels from the open-source Psi4 program through the popular NumPy library for linear algebra in Python to facilitate the rapid development of clear, understandable Python computer code for new quantum chemical methods, while maintaining a relatively low execution time. Using these tools, reference implementations have been created for a number of methods, including self-consistent field (SCF), SCF response, many-body perturbation theory, coupled-cluster theory, configuration interaction, and symmetry-adapted perturbation theory. Furthermore, several reference codes have been integrated into Jupyter notebooks, allowing background, underlying theory, and formula information to be associated with the implementation. Psi4NumPy tools and associated reference implementations can lower the barrier for future development of quantum chemistry methods. These implementations also demonstrate the power of the hybrid C++/Python programming approach employed by the Psi4 program.

T7 lytic phage-displayed peptide libraries: construction and diversity characterization.

PubMed

Krumpe, Lauren R H; Mori, Toshiyuki

2014-01-01

In this chapter, we describe the construction of T7 bacteriophage (phage)-displayed peptide libraries and the diversity analyses of random amino acid sequences obtained from the libraries. We used commercially available reagents, Novagen's T7Select system, to construct the libraries. Using a combination of biotinylated extension primer and streptavidin-coupled magnetic beads, we were able to prepare library DNA without applying gel purification, resulting in extremely high ligation efficiencies. Further, we describe the use of bioinformatics tools to characterize library diversity. Amino acid frequency and positional amino acid diversity and hydropathy are estimated using the REceptor LIgand Contacts website http://relic.bio.anl.gov. Peptide net charge analysis and peptide hydropathy analysis are conducted using the Genetics Computer Group Wisconsin Package computational tools. A comprehensive collection of the estimated number of recombinants and titers of T7 phage-displayed peptide libraries constructed in our lab is included.

JAtlasView: a Java atlas-viewer for browsing biomedical 3D images and atlases.

PubMed

Feng, Guangjie; Burton, Nick; Hill, Bill; Davidson, Duncan; Kerwin, Janet; Scott, Mark; Lindsay, Susan; Baldock, Richard

2005-03-09

Many three-dimensional (3D) images are routinely collected in biomedical research and a number of digital atlases with associated anatomical and other information have been published. A number of tools are available for viewing this data ranging from commercial visualization packages to freely available, typically system architecture dependent, solutions. Here we discuss an atlas viewer implemented to run on any workstation using the architecture neutral Java programming language. We report the development of a freely available Java based viewer for 3D image data, descibe the structure and functionality of the viewer and how automated tools can be developed to manage the Java Native Interface code. The viewer allows arbitrary re-sectioning of the data and interactive browsing through the volume. With appropriately formatted data, for example as provided for the Electronic Atlas of the Developing Human Brain, a 3D surface view and anatomical browsing is available. The interface is developed in Java with Java3D providing the 3D rendering. For efficiency the image data is manipulated using the Woolz image-processing library provided as a dynamically linked module for each machine architecture. We conclude that Java provides an appropriate environment for efficient development of these tools and techniques exist to allow computationally efficient image-processing libraries to be integrated relatively easily.

A tool for simulating parallel branch-and-bound methods

NASA Astrophysics Data System (ADS)

Golubeva, Yana; Orlov, Yury; Posypkin, Mikhail

2016-01-01

The Branch-and-Bound method is known as one of the most powerful but very resource consuming global optimization methods. Parallel and distributed computing can efficiently cope with this issue. The major difficulty in parallel B&B method is the need for dynamic load redistribution. Therefore design and study of load balancing algorithms is a separate and very important research topic. This paper presents a tool for simulating parallel Branchand-Bound method. The simulator allows one to run load balancing algorithms with various numbers of processors, sizes of the search tree, the characteristics of the supercomputer's interconnect thereby fostering deep study of load distribution strategies. The process of resolution of the optimization problem by B&B method is replaced by a stochastic branching process. Data exchanges are modeled using the concept of logical time. The user friendly graphical interface to the simulator provides efficient visualization and convenient performance analysis.

DNAPrint Genomics, Inc.: better drugs for segmented markets.

PubMed

Frudakis, Tony

2008-02-01

The postgenome era promises more efficient drug-development cycles and medications targeted to compatible populations, resulting in improved outcomes, fewer drug-company failures, less litigation, fewer recalls and a refurbished image of 'pharma' in the mind of the customer. DNAPrint was founded to help precipitate these changes. Since 1999, we have developed and optimized novel methods for assessing patient response proclivities as individuals but also as constituents of populations, and we have introduced a computational platform for modeling drug biology. We expect these tools will allow us to maximize the efficiency of our clinical trials and, more importantly, ensure better postmarket performance parameters. With these tools, we are now carefully engineering select drug-development projects in an attempt to illustrate the viability of a novel drug-development model - one based on the application of intelligence and new technologies for superior drug performance in segmented markets.

MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities

DOE PAGES

Kang, Dongwan D.; Froula, Jeff; Egan, Rob; ...

2015-01-01

Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. Because of the complex nature of these communities, existing metagenome binning methods often miss a large number of microbial species. In addition, most of the tools are not scalable to large datasets. Here we introduce automated software called MetaBAT that integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency for accurate metagenome binning. MetaBAT outperforms alternative methods in accuracy and computational efficiency on both synthetic and real metagenome datasets. Lastly, it automatically formsmore » hundreds of high quality genome bins on a very large assembly consisting millions of contigs in a matter of hours on a single node. MetaBAT is open source software and available at https://bitbucket.org/berkeleylab/metabat.« less

Efficient volumetric estimation from plenoptic data

NASA Astrophysics Data System (ADS)

Anglin, Paul; Reeves, Stanley J.; Thurow, Brian S.

2013-03-01

The commercial release of the Lytro camera, and greater availability of plenoptic imaging systems in general, have given the image processing community cost-effective tools for light-field imaging. While this data is most commonly used to generate planar images at arbitrary focal depths, reconstruction of volumetric fields is also possible. Similarly, deconvolution is a technique that is conventionally used in planar image reconstruction, or deblurring, algorithms. However, when leveraged with the ability of a light-field camera to quickly reproduce multiple focal planes within an imaged volume, deconvolution offers a computationally efficient method of volumetric reconstruction. Related research has shown than light-field imaging systems in conjunction with tomographic reconstruction techniques are also capable of estimating the imaged volume and have been successfully applied to particle image velocimetry (PIV). However, while tomographic volumetric estimation through algorithms such as multiplicative algebraic reconstruction techniques (MART) have proven to be highly accurate, they are computationally intensive. In this paper, the reconstruction problem is shown to be solvable by deconvolution. Deconvolution offers significant improvement in computational efficiency through the use of fast Fourier transforms (FFTs) when compared to other tomographic methods. This work describes a deconvolution algorithm designed to reconstruct a 3-D particle field from simulated plenoptic data. A 3-D extension of existing 2-D FFT-based refocusing techniques is presented to further improve efficiency when computing object focal stacks and system point spread functions (PSF). Reconstruction artifacts are identified; their underlying source and methods of mitigation are explored where possible, and reconstructions of simulated particle fields are provided.

Computer-based Learning of Neuroanatomy: A Longitudinal Study of Learning, Transfer, and Retention

PubMed Central

Chariker, Julia H.; Naaz, Farah; Pani, John R.

2013-01-01

A longitudinal experiment was conducted to evaluate the effectiveness of new methods for learning neuroanatomy with computer-based instruction. Using a 3D graphical model of the human brain, and sections derived from the model, tools for exploring neuroanatomy were developed to encourage adaptive exploration. This is an instructional method which incorporates graphical exploration in the context of repeated testing and feedback. With this approach, 72 participants learned either sectional anatomy alone or whole anatomy followed by sectional anatomy. Sectional anatomy was explored either with perceptually continuous navigation through the sections or with discrete navigation (as in the use of an anatomical atlas). Learning was measured longitudinally to a high performance criterion. Subsequent tests examined transfer of learning to the interpretation of biomedical images and long-term retention. There were several clear results of this study. On initial exposure to neuroanatomy, whole anatomy was learned more efficiently than sectional anatomy. After whole anatomy was mastered, learners demonstrated high levels of transfer of learning to sectional anatomy and from sectional anatomy to the interpretation of complex biomedical images. Learning whole anatomy prior to learning sectional anatomy led to substantially fewer errors overall than learning sectional anatomy alone. Use of continuous or discrete navigation through sectional anatomy made little difference to measured outcomes. Efficient learning, good long-term retention, and successful transfer to the interpretation of biomedical images indicated that computer-based learning using adaptive exploration can be a valuable tool in instruction of neuroanatomy and similar disciplines. PMID:23349552

The effect of influent temperature variations in a sedimentation tank for potable water treatment--a computational fluid dynamics study.

PubMed

Goula, Athanasia M; Kostoglou, Margaritis; Karapantsios, Thodoris D; Zouboulis, Anastasios I

2008-07-01

A computational fluid dynamics (CFD) model is used to assess the effect of influent temperature variation on solids settling in a sedimentation tank for potable water treatment. The model is based on the CFD code Fluent and exploits several specific aspects of the potable water application to derive a computational tool much more efficient than the corresponding tools employed to simulate primary and secondary wastewater settling tanks. The linearity of the particle conservation equations allows separate calculations for each particle size class, leading to the uncoupling of the CFD problem from a particular inlet particle size distribution. The usually unknown and difficult to be measured particle density is determined by matching the theoretical to the easily measured experimental total settling efficiency. The present model is adjusted against data from a real sedimentation tank and then it is used to assess the significance of influent temperature variation. It is found that a temperature difference of only 1 degrees C between influent and tank content is enough to induce a density current. When the influent temperature rises, the tank exhibits a rising buoyant plume that changes the direction of the main circular current. This process keeps the particles in suspension and leads to a higher effluent suspended solids concentration, thus, worse settling. As the warmer water keeps coming in, the temperature differential decreases, the current starts going back to its original position, and, thus, the suspended solids concentration decreases.

System analysis tools for an ELT at ESO

NASA Astrophysics Data System (ADS)

Mueller, Michael; Koch, Franz

2006-06-01

Engineering of complex, large scale systems like the ELT designs currently investigated and developed in Europe and Northern America require powerful and sophisticated tools within specific technical disciplines such as mechanics, optics and control engineering. However, even analyzing a certain component of the telescope like the telescope structure necessitates a system approach to evaluate the structural effects onto the optical performance. This paper shows several software tools developed by the European Southern Observatory (ESO) which focus onto the system approach in the analyses: Using modal results of a finite element analysis the SMI-toolbox allows an easy generation of structural models with different sizes and levels of accuracy for the control design and closed-loop simulations. The optical modeling code BeamWarrior was developed by ESO and Astrium GmbH, Germany) especially for integrated modeling and interfering with a structural model. Within BeamWarrior displacements and deformations can be applied in an arbitrary coordinate system, and hence also in the global coordinates of the FE model avoiding error prone transformations. In addition to this, a sparse state space model object was developed for Matlab to gain in computational efficiency and reduced memory requirements due to the sparsity pattern of both the structural models and the control architecture. As one result these tools allow building an integrated model in order to reliably simulate interactions, cross-coupling effects, system responses, and to evaluate global performance. In order to evaluate disturbance effects on the optical performance in openloop more efficiently, an optical evaluation toolbox was built in the FE software ANSYS which performs Zernike decomposition and best-fit computation of the deformations directly in the FE analysis.

Grid Computing and Collaboration Technology in Support of Fusion Energy Sciences

NASA Astrophysics Data System (ADS)

Schissel, D. P.

2004-11-01

The SciDAC Initiative is creating a computational grid designed to advance scientific understanding in fusion research by facilitating collaborations, enabling more effective integration of experiments, theory and modeling, and allowing more efficient use of experimental facilities. The philosophy is that data, codes, analysis routines, visualization tools, and communication tools should be thought of as easy to use network available services. Access to services is stressed rather than portability. Services share the same basic security infrastructure so that stakeholders can control their own resources and helps ensure fair use of resources. The collaborative control room is being developed using the open-source Access Grid software that enables secure group-to-group collaboration with capabilities beyond teleconferencing including application sharing and control. The ability to effectively integrate off-site scientists into a dynamic control room will be critical to the success of future international projects like ITER. Grid computing, the secure integration of computer systems over high-speed networks to provide on-demand access to data analysis capabilities and related functions, is being deployed as an alternative to traditional resource sharing among institutions. The first grid computational service deployed was the transport code TRANSP and included tools for run preparation, submission, monitoring and management. This approach saves user sites from the laborious effort of maintaining a complex code while at the same time reducing the burden on developers by avoiding the support of a large number of heterogeneous installations. This tutorial will present the philosophy behind an advanced collaborative environment, give specific examples, and discuss its usage beyond FES.

Moose: An Open-Source Framework to Enable Rapid Development of Collaborative, Multi-Scale, Multi-Physics Simulation Tools

NASA Astrophysics Data System (ADS)

Slaughter, A. E.; Permann, C.; Peterson, J. W.; Gaston, D.; Andrs, D.; Miller, J.

2014-12-01

The Idaho National Laboratory (INL)-developed Multiphysics Object Oriented Simulation Environment (MOOSE; www.mooseframework.org), is an open-source, parallel computational framework for enabling the solution of complex, fully implicit multiphysics systems. MOOSE provides a set of computational tools that scientists and engineers can use to create sophisticated multiphysics simulations. Applications built using MOOSE have computed solutions for chemical reaction and transport equations, computational fluid dynamics, solid mechanics, heat conduction, mesoscale materials modeling, geomechanics, and others. To facilitate the coupling of diverse and highly-coupled physical systems, MOOSE employs the Jacobian-free Newton-Krylov (JFNK) method when solving the coupled nonlinear systems of equations arising in multiphysics applications. The MOOSE framework is written in C++, and leverages other high-quality, open-source scientific software packages such as LibMesh, Hypre, and PETSc. MOOSE uses a "hybrid parallel" model which combines both shared memory (thread-based) and distributed memory (MPI-based) parallelism to ensure efficient resource utilization on a wide range of computational hardware. MOOSE-based applications are inherently modular, which allows for simulation expansion (via coupling of additional physics modules) and the creation of multi-scale simulations. Any application developed with MOOSE supports running (in parallel) any other MOOSE-based application. Each application can be developed independently, yet easily communicate with other applications (e.g., conductivity in a slope-scale model could be a constant input, or a complete phase-field micro-structure simulation) without additional code being written. This method of development has proven effective at INL and expedites the development of sophisticated, sustainable, and collaborative simulation tools.

Atropos: specific, sensitive, and speedy trimming of sequencing reads.

PubMed

Didion, John P; Martin, Marcel; Collins, Francis S

2017-01-01

A key step in the transformation of raw sequencing reads into biological insights is the trimming of adapter sequences and low-quality bases. Read trimming has been shown to increase the quality and reliability while decreasing the computational requirements of downstream analyses. Many read trimming software tools are available; however, no tool simultaneously provides the accuracy, computational efficiency, and feature set required to handle the types and volumes of data generated in modern sequencing-based experiments. Here we introduce Atropos and show that it trims reads with high sensitivity and specificity while maintaining leading-edge speed. Compared to other state-of-the-art read trimming tools, Atropos achieves significant increases in trimming accuracy while remaining competitive in execution times. Furthermore, Atropos maintains high accuracy even when trimming data with elevated rates of sequencing errors. The accuracy, high performance, and broad feature set offered by Atropos makes it an appropriate choice for the pre-processing of Illumina, ABI SOLiD, and other current-generation short-read sequencing datasets. Atropos is open source and free software written in Python (3.3+) and available at https://github.com/jdidion/atropos.

FITSManager: Management of Personal Astronomical Data

NASA Astrophysics Data System (ADS)

Cui, Chenzhou; Fan, Dongwei; Zhao, Yongheng; Kembhavi, Ajit; He, Boliang; Cao, Zihuang; Li, Jian; Nandrekar, Deoyani

2011-07-01

With the increase of personal storage capacity, it is easy to find hundreds to thousands of FITS files in the personal computer of an astrophysicist. Because Flexible Image Transport System (FITS) is a professional data format initiated by astronomers and used mainly in the small community, data management toolkits for FITS files are very few. Astronomers need a powerful tool to help them manage their local astronomical data. Although Virtual Observatory (VO) is a network oriented astronomical research environment, its applications and related technologies provide useful solutions to enhance the management and utilization of astronomical data hosted in an astronomer's personal computer. FITSManager is such a tool to provide astronomers an efficient management and utilization of their local data, bringing VO to astronomers in a seamless and transparent way. FITSManager provides fruitful functions for FITS file management, like thumbnail, preview, type dependent icons, header keyword indexing and search, collaborated working with other tools and online services, and so on. The development of the FITSManager is an effort to fill the gap between management and analysis of astronomical data.

Atropos: specific, sensitive, and speedy trimming of sequencing reads

PubMed Central

Collins, Francis S.

2017-01-01

A key step in the transformation of raw sequencing reads into biological insights is the trimming of adapter sequences and low-quality bases. Read trimming has been shown to increase the quality and reliability while decreasing the computational requirements of downstream analyses. Many read trimming software tools are available; however, no tool simultaneously provides the accuracy, computational efficiency, and feature set required to handle the types and volumes of data generated in modern sequencing-based experiments. Here we introduce Atropos and show that it trims reads with high sensitivity and specificity while maintaining leading-edge speed. Compared to other state-of-the-art read trimming tools, Atropos achieves significant increases in trimming accuracy while remaining competitive in execution times. Furthermore, Atropos maintains high accuracy even when trimming data with elevated rates of sequencing errors. The accuracy, high performance, and broad feature set offered by Atropos makes it an appropriate choice for the pre-processing of Illumina, ABI SOLiD, and other current-generation short-read sequencing datasets. Atropos is open source and free software written in Python (3.3+) and available at https://github.com/jdidion/atropos. PMID:28875074

Big Data Approaches for the Analysis of Large-Scale fMRI Data Using Apache Spark and GPU Processing: A Demonstration on Resting-State fMRI Data from the Human Connectome Project

PubMed Central

Boubela, Roland N.; Kalcher, Klaudius; Huf, Wolfgang; Našel, Christian; Moser, Ewald

2016-01-01

Technologies for scalable analysis of very large datasets have emerged in the domain of internet computing, but are still rarely used in neuroimaging despite the existence of data and research questions in need of efficient computation tools especially in fMRI. In this work, we present software tools for the application of Apache Spark and Graphics Processing Units (GPUs) to neuroimaging datasets, in particular providing distributed file input for 4D NIfTI fMRI datasets in Scala for use in an Apache Spark environment. Examples for using this Big Data platform in graph analysis of fMRI datasets are shown to illustrate how processing pipelines employing it can be developed. With more tools for the convenient integration of neuroimaging file formats and typical processing steps, big data technologies could find wider endorsement in the community, leading to a range of potentially useful applications especially in view of the current collaborative creation of a wealth of large data repositories including thousands of individual fMRI datasets. PMID:26778951

Rational protein design: developing next-generation biological therapeutics and nanobiotechnological tools.

PubMed

Wilson, Corey J

2015-01-01

Proteins are the most functionally diverse macromolecules observed in nature, participating in a broad array of catalytic, biosensing, transport, scaffolding, and regulatory functions. Fittingly, proteins have become one of the most promising nanobiotechnological tools to date, and through the use of recombinant DNA and other laboratory methods we have produced a vast number of biological therapeutics derived from human genes. Our emerging ability to rationally design proteins (e.g., via computational methods) holds the promise of significantly expanding the number and diversity of protein therapies and has opened the gateway to realizing true and uncompromised personalized medicine. In the last decade computational protein design has been transformed from a set of fundamental strategies to stringently test our understanding of the protein structure-function relationship, to practical tools for developing useful biological processes, nano-devices, and novel therapeutics. As protein design strategies improve (i.e., in terms of accuracy and efficiency) clinicians will be able to leverage individual genetic data and biological metrics to develop and deliver personalized protein therapeutics with minimal delay. © 2014 Wiley Periodicals, Inc.

Extensible Computational Chemistry Environment

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

2012-08-09

ECCE provides a sophisticated graphical user interface, scientific visualization tools, and the underlying data management framework enabling scientists to efficiently set up calculations and store, retrieve, and analyze the rapidly growing volumes of data produced by computational chemistry studies. ECCE was conceived as part of the Environmental Molecular Sciences Laboratory construction to solve the problem of researchers being able to effectively utilize complex computational chemistry codes and massively parallel high performance compute resources. Bringing the power of these codes and resources to the desktops of researcher and thus enabling world class research without users needing a detailed understanding of themore » inner workings of either the theoretical codes or the supercomputers needed to run them was a grand challenge problem in the original version of the EMSL. ECCE allows collaboration among researchers using a web-based data repository where the inputs and results for all calculations done within ECCE are organized. ECCE is a first of kind end-to-end problem solving environment for all phases of computational chemistry research: setting up calculations with sophisticated GUI and direct manipulation visualization tools, submitting and monitoring calculations on remote high performance supercomputers without having to be familiar with the details of using these compute resources, and performing results visualization and analysis including creating publication quality images. ECCE is a suite of tightly integrated applications that are employed as the user moves through the modeling process.« less

Data mining in soft computing framework: a survey.

PubMed

Mitra, S; Pal, S K; Mitra, P

2002-01-01

The present article provides a survey of the available literature on data mining using soft computing. A categorization has been provided based on the different soft computing tools and their hybridizations used, the data mining function implemented, and the preference criterion selected by the model. The utility of the different soft computing methodologies is highlighted. Generally fuzzy sets are suitable for handling the issues related to understandability of patterns, incomplete/noisy data, mixed media information and human interaction, and can provide approximate solutions faster. Neural networks are nonparametric, robust, and exhibit good learning and generalization capabilities in data-rich environments. Genetic algorithms provide efficient search algorithms to select a model, from mixed media data, based on some preference criterion/objective function. Rough sets are suitable for handling different types of uncertainty in data. Some challenges to data mining and the application of soft computing methodologies are indicated. An extensive bibliography is also included.

Experimental scattershot boson sampling

PubMed Central

Bentivegna, Marco; Spagnolo, Nicolò; Vitelli, Chiara; Flamini, Fulvio; Viggianiello, Niko; Latmiral, Ludovico; Mataloni, Paolo; Brod, Daniel J.; Galvão, Ernesto F.; Crespi, Andrea; Ramponi, Roberta; Osellame, Roberto; Sciarrino, Fabio

2015-01-01

Boson sampling is a computational task strongly believed to be hard for classical computers, but efficiently solvable by orchestrated bosonic interference in a specialized quantum computer. Current experimental schemes, however, are still insufficient for a convincing demonstration of the advantage of quantum over classical computation. A new variation of this task, scattershot boson sampling, leads to an exponential increase in speed of the quantum device, using a larger number of photon sources based on parametric down-conversion. This is achieved by having multiple heralded single photons being sent, shot by shot, into different random input ports of the interferometer. We report the first scattershot boson sampling experiments, where six different photon-pair sources are coupled to integrated photonic circuits. We use recently proposed statistical tools to analyze our experimental data, providing strong evidence that our photonic quantum simulator works as expected. This approach represents an important leap toward a convincing experimental demonstration of the quantum computational supremacy. PMID:26601164

Experimental scattershot boson sampling.

PubMed

Bentivegna, Marco; Spagnolo, Nicolò; Vitelli, Chiara; Flamini, Fulvio; Viggianiello, Niko; Latmiral, Ludovico; Mataloni, Paolo; Brod, Daniel J; Galvão, Ernesto F; Crespi, Andrea; Ramponi, Roberta; Osellame, Roberto; Sciarrino, Fabio

2015-04-01

Boson sampling is a computational task strongly believed to be hard for classical computers, but efficiently solvable by orchestrated bosonic interference in a specialized quantum computer. Current experimental schemes, however, are still insufficient for a convincing demonstration of the advantage of quantum over classical computation. A new variation of this task, scattershot boson sampling, leads to an exponential increase in speed of the quantum device, using a larger number of photon sources based on parametric down-conversion. This is achieved by having multiple heralded single photons being sent, shot by shot, into different random input ports of the interferometer. We report the first scattershot boson sampling experiments, where six different photon-pair sources are coupled to integrated photonic circuits. We use recently proposed statistical tools to analyze our experimental data, providing strong evidence that our photonic quantum simulator works as expected. This approach represents an important leap toward a convincing experimental demonstration of the quantum computational supremacy.

Computational modelling of cellular level metabolism

NASA Astrophysics Data System (ADS)

Calvetti, D.; Heino, J.; Somersalo, E.

2008-07-01

The steady and stationary state inverse problems consist of estimating the reaction and transport fluxes, blood concentrations and possibly the rates of change of some of the concentrations based on data which are often scarce noisy and sampled over a population. The Bayesian framework provides a natural setting for the solution of this inverse problem, because a priori knowledge about the system itself and the unknown reaction fluxes and transport rates can compensate for the insufficiency of measured data, provided that the computational costs do not become prohibitive. This article identifies the computational challenges which have to be met when analyzing the steady and stationary states of multicompartment model for cellular metabolism and suggest stable and efficient ways to handle the computations. The outline of a computational tool based on the Bayesian paradigm for the simulation and analysis of complex cellular metabolic systems is also presented.

Control Synthesis of Discrete-Time T-S Fuzzy Systems: Reducing the Conservatism Whilst Alleviating the Computational Burden.

PubMed

Xie, Xiangpeng; Yue, Dong; Zhang, Huaguang; Peng, Chen

2017-09-01

The augmented multi-indexed matrix approach acts as a powerful tool in reducing the conservatism of control synthesis of discrete-time Takagi-Sugeno fuzzy systems. However, its computational burden is sometimes too heavy as a tradeoff. Nowadays, reducing the conservatism whilst alleviating the computational burden becomes an ideal but very challenging problem. This paper is toward finding an efficient way to achieve one of satisfactory answers. Different from the augmented multi-indexed matrix approach in the literature, we aim to design a more efficient slack variable approach under a general framework of homogenous matrix polynomials. Thanks to the introduction of a new extended representation for homogeneous matrix polynomials, related matrices with the same coefficient are collected together into one sole set and thus those redundant terms of the augmented multi-indexed matrix approach can be removed, i.e., the computational burden can be alleviated in this paper. More importantly, due to the fact that more useful information is involved into control design, the conservatism of the proposed approach as well is less than the counterpart of the augmented multi-indexed matrix approach. Finally, numerical experiments are given to show the effectiveness of the proposed approach.

An interactive tool for visualization of spike train synchronization.

PubMed

Terry, Kevin

2010-08-15

A number of studies have examined the synchronization of central and peripheral spike trains by applying signal analysis techniques in the time and frequency domains. These analyses can reveal the presence of one or more common neural inputs that produce synchronization. However, synchronization measurements can fluctuate significantly due to the inherent variability of neural discharges and a finite data record length. Moreover, the effect of these natural variations is further compounded by the number of parameters available for calculating coherence in the frequency domain and the number of indices used to quantify short-term synchronization (STS) in the time domain. The computational tool presented here provides the user with an interactive environment that dynamically calculates and displays spike train properties along with STS and coherence indices to show how these factors interact. It is intended for a broad range of users, from those who are new to synchronization to experienced researchers who want to develop more meaningful and effective computational and experimental studies. To ensure this freely available tool meets the needs of all users, there are two versions. The first is a stand-alone version for educational use that can run on any computer. The second version can be modified and expanded by researchers who want to explore more in-depth questions about synchronization. Therefore, the distribution and use of this tool should both improve the understanding of fundamental spike train synchronization dynamics and produce more efficient and meaningful synchronization studies. (c) 2010 Elsevier B.V. All rights reserved.

Efficiency analysis of numerical integrations for finite element substructure in real-time hybrid simulation

NASA Astrophysics Data System (ADS)

Wang, Jinting; Lu, Liqiao; Zhu, Fei

2018-01-01

Finite element (FE) is a powerful tool and has been applied by investigators to real-time hybrid simulations (RTHSs). This study focuses on the computational efficiency, including the computational time and accuracy, of numerical integrations in solving FE numerical substructure in RTHSs. First, sparse matrix storage schemes are adopted to decrease the computational time of FE numerical substructure. In this way, the task execution time (TET) decreases such that the scale of the numerical substructure model increases. Subsequently, several commonly used explicit numerical integration algorithms, including the central difference method (CDM), the Newmark explicit method, the Chang method and the Gui-λ method, are comprehensively compared to evaluate their computational time in solving FE numerical substructure. CDM is better than the other explicit integration algorithms when the damping matrix is diagonal, while the Gui-λ (λ = 4) method is advantageous when the damping matrix is non-diagonal. Finally, the effect of time delay on the computational accuracy of RTHSs is investigated by simulating structure-foundation systems. Simulation results show that the influences of time delay on the displacement response become obvious with the mass ratio increasing, and delay compensation methods may reduce the relative error of the displacement peak value to less than 5% even under the large time-step and large time delay.

Optimization of Angular-Momentum Biases of Reaction Wheels

NASA Technical Reports Server (NTRS)

Lee, Clifford; Lee, Allan

2008-01-01

RBOT [RWA Bias Optimization Tool (wherein RWA signifies Reaction Wheel Assembly )] is a computer program designed for computing angular momentum biases for reaction wheels used for providing spacecraft pointing in various directions as required for scientific observations. RBOT is currently deployed to support the Cassini mission to prevent operation of reaction wheels at unsafely high speeds while minimizing time in undesirable low-speed range, where elasto-hydrodynamic lubrication films in bearings become ineffective, leading to premature bearing failure. The problem is formulated as a constrained optimization problem in which maximum wheel speed limit is a hard constraint and a cost functional that increases as speed decreases below a low-speed threshold. The optimization problem is solved using a parametric search routine known as the Nelder-Mead simplex algorithm. To increase computational efficiency for extended operation involving large quantity of data, the algorithm is designed to (1) use large time increments during intervals when spacecraft attitudes or rates of rotation are nearly stationary, (2) use sinusoidal-approximation sampling to model repeated long periods of Earth-point rolling maneuvers to reduce computational loads, and (3) utilize an efficient equation to obtain wheel-rate profiles as functions of initial wheel biases based on conservation of angular momentum (in an inertial frame) using pre-computed terms.

Monitoring techniques and alarm procedures for CMS services and sites in WLCG

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

Molina-Perez, J.; Bonacorsi, D.; Gutsche, O.

2012-01-01

The CMS offline computing system is composed of roughly 80 sites (including most experienced T3s) and a number of central services to distribute, process and analyze data worldwide. A high level of stability and reliability is required from the underlying infrastructure and services, partially covered by local or automated monitoring and alarming systems such as Lemon and SLS, the former collects metrics from sensors installed on computing nodes and triggers alarms when values are out of range, the latter measures the quality of service and warns managers when service is affected. CMS has established computing shift procedures with personnel operatingmore » worldwide from remote Computing Centers, under the supervision of the Computing Run Coordinator at CERN. This dedicated 24/7 computing shift personnel is contributing to detect and react timely on any unexpected error and hence ensure that CMS workflows are carried out efficiently and in a sustained manner. Synergy among all the involved actors is exploited to ensure the 24/7 monitoring, alarming and troubleshooting of the CMS computing sites and services. We review the deployment of the monitoring and alarming procedures, and report on the experience gained throughout the first two years of LHC operation. We describe the efficiency of the communication tools employed, the coherent monitoring framework, the proactive alarming systems and the proficient troubleshooting procedures that helped the CMS Computing facilities and infrastructure to operate at high reliability levels.« less

Computation of multi-dimensional viscous supersonic jet flow

NASA Technical Reports Server (NTRS)

Kim, Y. N.; Buggeln, R. C.; Mcdonald, H.

1986-01-01

A new method has been developed for two- and three-dimensional computations of viscous supersonic flows with embedded subsonic regions adjacent to solid boundaries. The approach employs a reduced form of the Navier-Stokes equations which allows solution as an initial-boundary value problem in space, using an efficient noniterative forward marching algorithm. Numerical instability associated with forward marching algorithms for flows with embedded subsonic regions is avoided by approximation of the reduced form of the Navier-Stokes equations in the subsonic regions of the boundary layers. Supersonic and subsonic portions of the flow field are simultaneously calculated by a consistently split linearized block implicit computational algorithm. The results of computations for a series of test cases relevant to internal supersonic flow is presented and compared with data. Comparison between data and computation are in general excellent thus indicating that the computational technique has great promise as a tool for calculating supersonic flow with embedded subsonic regions. Finally, a User's Manual is presented for the computer code used to perform the calculations.

Control mechanism of double-rotator-structure ternary optical computer

NASA Astrophysics Data System (ADS)

Kai, SONG; Liping, YAN

2017-03-01

Double-rotator-structure ternary optical processor (DRSTOP) has two characteristics, namely, giant data-bits parallel computing and reconfigurable processor, which can handle thousands of data bits in parallel, and can run much faster than computers and other optical computer systems so far. In order to put DRSTOP into practical application, this paper established a series of methods, namely, task classification method, data-bits allocation method, control information generation method, control information formatting and sending method, and decoded results obtaining method and so on. These methods form the control mechanism of DRSTOP. This control mechanism makes DRSTOP become an automated computing platform. Compared with the traditional calculation tools, DRSTOP computing platform can ease the contradiction between high energy consumption and big data computing due to greatly reducing the cost of communications and I/O. Finally, the paper designed a set of experiments for DRSTOP control mechanism to verify its feasibility and correctness. Experimental results showed that the control mechanism is correct, feasible and efficient.

Structural Analysis Methods for Structural Health Management of Future Aerospace Vehicles

NASA Technical Reports Server (NTRS)

Tessler, Alexander

2007-01-01

Two finite element based computational methods, Smoothing Element Analysis (SEA) and the inverse Finite Element Method (iFEM), are reviewed, and examples of their use for structural health monitoring are discussed. Due to their versatility, robustness, and computational efficiency, the methods are well suited for real-time structural health monitoring of future space vehicles, large space structures, and habitats. The methods may be effectively employed to enable real-time processing of sensing information, specifically for identifying three-dimensional deformed structural shapes as well as the internal loads. In addition, they may be used in conjunction with evolutionary algorithms to design optimally distributed sensors. These computational tools have demonstrated substantial promise for utilization in future Structural Health Management (SHM) systems.

Application of desktop computers in nuclear engineering education

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

Graves, H.W. Jr.

1990-01-01

Utilization of desktop computers in the academic environment is based on the same objectives as in the industrial environment - increased quality and efficiency. Desktop computers can be extremely useful teaching tools in two general areas: classroom demonstrations and homework assignments. Although differences in emphasis exist, tutorial programs share many characteristics with interactive software developed for the industrial environment. In the Reactor Design and Fuel Management course at the University of Maryland, several interactive tutorial programs provided by Energy analysis Software Service have been utilized. These programs have been designed to be sufficiently structured to permit an orderly, disciplined solutionmore » to the problem being solved, and yet be flexible enough to accommodate most problem solution options.« less

Survey of MapReduce frame operation in bioinformatics.

PubMed

Zou, Quan; Li, Xu-Bin; Jiang, Wen-Rui; Lin, Zi-Yu; Li, Gui-Lin; Chen, Ke

2014-07-01

Bioinformatics is challenged by the fact that traditional analysis tools have difficulty in processing large-scale data from high-throughput sequencing. The open source Apache Hadoop project, which adopts the MapReduce framework and a distributed file system, has recently given bioinformatics researchers an opportunity to achieve scalable, efficient and reliable computing performance on Linux clusters and on cloud computing services. In this article, we present MapReduce frame-based applications that can be employed in the next-generation sequencing and other biological domains. In addition, we discuss the challenges faced by this field as well as the future works on parallel computing in bioinformatics. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Research in Computational Astrobiology

NASA Technical Reports Server (NTRS)

Chaban, Galina; Jaffe, Richard; Liang, Shoudan; New, Michael H.; Pohorille, Andrew; Wilson, Michael A.

2002-01-01

We present results from several projects in the new field of computational astrobiology, which is devoted to advancing our understanding of the origin, evolution and distribution of life in the Universe using theoretical and computational tools. We have developed a procedure for calculating long-range effects in molecular dynamics using a plane wave expansion of the electrostatic potential. This method is expected to be highly efficient for simulating biological systems on massively parallel supercomputers. We have perform genomics analysis on a family of actin binding proteins. We have performed quantum mechanical calculations on carbon nanotubes and nucleic acids, which simulations will allow us to investigate possible sources of organic material on the early earth. Finally, we have developed a model of protobiological chemistry using neural networks.

pyNS: an open-source framework for 0D haemodynamic modelling.

PubMed

Manini, Simone; Antiga, Luca; Botti, Lorenzo; Remuzzi, Andrea

2015-06-01

A number of computational approaches have been proposed for the simulation of haemodynamics and vascular wall dynamics in complex vascular networks. Among them, 0D pulse wave propagation methods allow to efficiently model flow and pressure distributions and wall displacements throughout vascular networks at low computational costs. Although several techniques are documented in literature, the availability of open-source computational tools is still limited. We here present python Network Solver, a modular solver framework for 0D problems released under a BSD license as part of the archToolkit ( http://archtk.github.com ). As an application, we describe patient-specific models of the systemic circulation and detailed upper extremity for use in the prediction of maturation after surgical creation of vascular access for haemodialysis.

Computer-Aided Discovery Tools for Volcano Deformation Studies with InSAR and GPS

NASA Astrophysics Data System (ADS)

Pankratius, V.; Pilewskie, J.; Rude, C. M.; Li, J. D.; Gowanlock, M.; Bechor, N.; Herring, T.; Wauthier, C.

2016-12-01

We present a Computer-Aided Discovery approach that facilitates the cloud-scalable fusion of different data sources, such as GPS time series and Interferometric Synthetic Aperture Radar (InSAR), for the purpose of identifying the expansion centers and deformation styles of volcanoes. The tools currently developed at MIT allow the definition of alternatives for data processing pipelines that use various analysis algorithms. The Computer-Aided Discovery system automatically generates algorithmic and parameter variants to help researchers explore multidimensional data processing search spaces efficiently. We present first application examples of this technique using GPS data on volcanoes on the Aleutian Islands and work in progress on combined GPS and InSAR data in Hawaii. In the model search context, we also illustrate work in progress combining time series Principal Component Analysis with InSAR augmentation to constrain the space of possible model explanations on current empirical data sets and achieve a better identification of deformation patterns. This work is supported by NASA AIST-NNX15AG84G and NSF ACI-1442997 (PI: V. Pankratius).

A Multiphysics and Multiscale Software Environment for Modeling Astrophysical Systems

NASA Astrophysics Data System (ADS)

Portegies Zwart, Simon; McMillan, Steve; O'Nualláin, Breanndán; Heggie, Douglas; Lombardi, James; Hut, Piet; Banerjee, Sambaran; Belkus, Houria; Fragos, Tassos; Fregeau, John; Fuji, Michiko; Gaburov, Evghenii; Glebbeek, Evert; Groen, Derek; Harfst, Stefan; Izzard, Rob; Jurić, Mario; Justham, Stephen; Teuben, Peter; van Bever, Joris; Yaron, Ofer; Zemp, Marcel

We present MUSE, a software framework for tying together existing computational tools for different astrophysical domains into a single multiphysics, multiscale workload. MUSE facilitates the coupling of existing codes written in different languages by providing inter-language tools and by specifying an interface between each module and the framework that represents a balance between generality and computational efficiency. This approach allows scientists to use combinations of codes to solve highly-coupled problems without the need to write new codes for other domains or significantly alter their existing codes. MUSE currently incorporates the domains of stellar dynamics, stellar evolution and stellar hydrodynamics for a generalized stellar systems workload. MUSE has now reached a "Noah's Ark" milestone, with two available numerical solvers for each domain. MUSE can treat small stellar associations, galaxies and everything in between, including planetary systems, dense stellar clusters and galactic nuclei. Here we demonstrate an examples calculated with MUSE: the merger of two galaxies. In addition we demonstrate the working of MUSE on a distributed computer. The current MUSE code base is publicly available as open source at http://muse.li.

Advanced Doubling Adding Method for Radiative Transfer in Planetary Atmospheres

NASA Astrophysics Data System (ADS)

Liu, Quanhua; Weng, Fuzhong

2006-12-01

The doubling adding method (DA) is one of the most accurate tools for detailed multiple-scattering calculations. The principle of the method goes back to the nineteenth century in a problem dealing with reflection and transmission by glass plates. Since then the doubling adding method has been widely used as a reference tool for other radiative transfer models. The method has never been used in operational applications owing to tremendous demand on computational resources from the model. This study derives an analytical expression replacing the most complicated thermal source terms in the doubling adding method. The new development is called the advanced doubling adding (ADA) method. Thanks also to the efficiency of matrix and vector manipulations in FORTRAN 90/95, the advanced doubling adding method is about 60 times faster than the doubling adding method. The radiance (i.e., forward) computation code of ADA is easily translated into tangent linear and adjoint codes for radiance gradient calculations. The simplicity in forward and Jacobian computation codes is very useful for operational applications and for the consistency between the forward and adjoint calculations in satellite data assimilation.

Numerical methods on some structured matrix algebra problems

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

Jessup, E.R.

1996-06-01

This proposal concerned the design, analysis, and implementation of serial and parallel algorithms for certain structured matrix algebra problems. It emphasized large order problems and so focused on methods that can be implemented efficiently on distributed-memory MIMD multiprocessors. Such machines supply the computing power and extensive memory demanded by the large order problems. We proposed to examine three classes of matrix algebra problems: the symmetric and nonsymmetric eigenvalue problems (especially the tridiagonal cases) and the solution of linear systems with specially structured coefficient matrices. As all of these are of practical interest, a major goal of this work was tomore » translate our research in linear algebra into useful tools for use by the computational scientists interested in these and related applications. Thus, in addition to software specific to the linear algebra problems, we proposed to produce a programming paradigm and library to aid in the design and implementation of programs for distributed-memory MIMD computers. We now report on our progress on each of the problems and on the programming tools.« less

Hybrid MPI/OpenMP Implementation of the ORAC Molecular Dynamics Program for Generalized Ensemble and Fast Switching Alchemical Simulations.

PubMed

Procacci, Piero

2016-06-27

We present a new release (6.0β) of the ORAC program [Marsili et al. J. Comput. Chem. 2010, 31, 1106-1116] with a hybrid OpenMP/MPI (open multiprocessing message passing interface) multilevel parallelism tailored for generalized ensemble (GE) and fast switching double annihilation (FS-DAM) nonequilibrium technology aimed at evaluating the binding free energy in drug-receptor system on high performance computing platforms. The production of the GE or FS-DAM trajectories is handled using a weak scaling parallel approach on the MPI level only, while a strong scaling force decomposition scheme is implemented for intranode computations with shared memory access at the OpenMP level. The efficiency, simplicity, and inherent parallel nature of the ORAC implementation of the FS-DAM algorithm, project the code as a possible effective tool for a second generation high throughput virtual screening in drug discovery and design. The code, along with documentation, testing, and ancillary tools, is distributed under the provisions of the General Public License and can be freely downloaded at www.chim.unifi.it/orac .

New paradigms in internal architecture design and freeform fabrication of tissue engineering porous scaffolds.

PubMed

Yoo, Dongjin

2012-07-01

Advanced additive manufacture (AM) techniques are now being developed to fabricate scaffolds with controlled internal pore architectures in the field of tissue engineering. In general, these techniques use a hybrid method which combines computer-aided design (CAD) with computer-aided manufacturing (CAM) tools to design and fabricate complicated three-dimensional (3D) scaffold models. The mathematical descriptions of micro-architectures along with the macro-structures of the 3D scaffold models are limited by current CAD technologies as well as by the difficulty of transferring the designed digital models to standard formats for fabrication. To overcome these difficulties, we have developed an efficient internal pore architecture design system based on triply periodic minimal surface (TPMS) unit cell libraries and associated computational methods to assemble TPMS unit cells into an entire scaffold model. In addition, we have developed a process planning technique based on TPMS internal architecture pattern of unit cells to generate tool paths for freeform fabrication of tissue engineering porous scaffolds. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.

PLUM: Parallel Load Balancing for Unstructured Adaptive Meshes. Degree awarded by Colorado Univ.

NASA Technical Reports Server (NTRS)

Oliker, Leonid

1998-01-01

Dynamic mesh adaption on unstructured grids is a powerful tool for computing large-scale problems that require grid modifications to efficiently resolve solution features. By locally refining and coarsening the mesh to capture physical phenomena of interest, such procedures make standard computational methods more cost effective. Unfortunately, an efficient parallel implementation of these adaptive methods is rather difficult to achieve, primarily due to the load imbalance created by the dynamically-changing nonuniform grid. This requires significant communication at runtime, leading to idle processors and adversely affecting the total execution time. Nonetheless, it is generally thought that unstructured adaptive- grid techniques will constitute a significant fraction of future high-performance supercomputing. Various dynamic load balancing methods have been reported to date; however, most of them either lack a global view of loads across processors or do not apply their techniques to realistic large-scale applications.

Probabilistic power flow using improved Monte Carlo simulation method with correlated wind sources

NASA Astrophysics Data System (ADS)

Bie, Pei; Zhang, Buhan; Li, Hang; Deng, Weisi; Wu, Jiasi

2017-01-01

Probabilistic Power Flow (PPF) is a very useful tool for power system steady-state analysis. However, the correlation among different random injection power (like wind power) brings great difficulties to calculate PPF. Monte Carlo simulation (MCS) and analytical methods are two commonly used methods to solve PPF. MCS has high accuracy but is very time consuming. Analytical method like cumulants method (CM) has high computing efficiency but the cumulants calculating is not convenient when wind power output does not obey any typical distribution, especially when correlated wind sources are considered. In this paper, an Improved Monte Carlo simulation method (IMCS) is proposed. The joint empirical distribution is applied to model different wind power output. This method combines the advantages of both MCS and analytical method. It not only has high computing efficiency, but also can provide solutions with enough accuracy, which is very suitable for on-line analysis.

Structural efficiency study of composite wing rib structures

NASA Technical Reports Server (NTRS)

Swanson, Gary D.; Gurdal, Zafer; Starnes, James H., Jr.

1988-01-01

A series of short stiffened panel designs which may be applied to a preliminary design assessment of an aircraft wing rib is presented. The computer program PASCO is used as the primary design and analysis tool to assess the structural efficiency and geometry of a tailored corrugated panel, a corrugated panel with a continuous laminate, a hat stiffened panel, a blade stiffened panel, and an unstiffened flat plate. To correct some of the shortcomings in the PASCO analysis when shear is present, a two step iterative process using the computer program VICON is used. The loadings considered include combinations of axial compression, shear, and lateral pressure. The loading ranges considered are broad enough such that the designs presented may be applied to other stiffened panel applications. An assessment is made of laminate variations, increased spacing, and nonoptimum geometric variations, including a beaded panel, on the design of the panels.

Efficient computation paths for the systematic analysis of sensitivities

NASA Astrophysics Data System (ADS)

Greppi, Paolo; Arato, Elisabetta

2013-01-01

A systematic sensitivity analysis requires computing the model on all points of a multi-dimensional grid covering the domain of interest, defined by the ranges of variability of the inputs. The issues to efficiently perform such analyses on algebraic models are handling solution failures within and close to the feasible region and minimizing the total iteration count. Scanning the domain in the obvious order is sub-optimal in terms of total iterations and is likely to cause many solution failures. The problem of choosing a better order can be translated geometrically into finding Hamiltonian paths on certain grid graphs. This work proposes two paths, one based on a mixed-radix Gray code and the other, a quasi-spiral path, produced by a novel heuristic algorithm. Some simple, easy-to-visualize examples are presented, followed by performance results for the quasi-spiral algorithm and the practical application of the different paths in a process simulation tool.

Computer-aided design of biological circuits using TinkerCell

PubMed Central

Bergmann, Frank T; Sauro, Herbert M

2010-01-01

Synthetic biology is an engineering discipline that builds on modeling practices from systems biology and wet-lab techniques from genetic engineering. As synthetic biology advances, efficient procedures will be developed that will allow a synthetic biologist to design, analyze and build biological networks. In this idealized pipeline, computer-aided design (CAD) is a necessary component. The role of a CAD application would be to allow efficient transition from a general design to a final product. TinkerCell is a design tool for serving this purpose in synthetic biology. In TinkerCell, users build biological networks using biological parts and modules. The network can be analyzed using one of several functions provided by TinkerCell or custom programs from third-party sources. Since best practices for modeling and constructing synthetic biology networks have not yet been established, TinkerCell is designed as a flexible and extensible application that can adjust itself to changes in the field. PMID:21327060

Rapid Parallel Calculation of shell Element Based On GPU

NASA Astrophysics Data System (ADS)

Wanga, Jian Hua; Lia, Guang Yao; Lib, Sheng; Li, Guang Yao

2010-06-01

Long computing time bottlenecked the application of finite element. In this paper, an effective method to speed up the FEM calculation by using the existing modern graphic processing unit and programmable colored rendering tool was put forward, which devised the representation of unit information in accordance with the features of GPU, converted all the unit calculation into film rendering process, solved the simulation work of all the unit calculation of the internal force, and overcame the shortcomings of lowly parallel level appeared ever before when it run in a single computer. Studies shown that this method could improve efficiency and shorten calculating hours greatly. The results of emulation calculation about the elasticity problem of large number cells in the sheet metal proved that using the GPU parallel simulation calculation was faster than using the CPU's. It is useful and efficient to solve the project problems in this way.

The Brain as an Efficient and Robust Adaptive Learner.

PubMed

Denève, Sophie; Alemi, Alireza; Bourdoukan, Ralph

2017-06-07

Understanding how the brain learns to compute functions reliably, efficiently, and robustly with noisy spiking activity is a fundamental challenge in neuroscience. Most sensory and motor tasks can be described as dynamical systems and could presumably be learned by adjusting connection weights in a recurrent biological neural network. However, this is greatly complicated by the credit assignment problem for learning in recurrent networks, e.g., the contribution of each connection to the global output error cannot be determined based only on locally accessible quantities to the synapse. Combining tools from adaptive control theory and efficient coding theories, we propose that neural circuits can indeed learn complex dynamic tasks with local synaptic plasticity rules as long as they associate two experimentally established neural mechanisms. First, they should receive top-down feedbacks driving both their activity and their synaptic plasticity. Second, inhibitory interneurons should maintain a tight balance between excitation and inhibition in the circuit. The resulting networks could learn arbitrary dynamical systems and produce irregular spike trains as variable as those observed experimentally. Yet, this variability in single neurons may hide an extremely efficient and robust computation at the population level. Copyright © 2017 Elsevier Inc. All rights reserved.

CAESY - COMPUTER AIDED ENGINEERING SYSTEM

NASA Technical Reports Server (NTRS)

Wette, M. R.

1994-01-01

Many developers of software and algorithms for control system design have recognized that current tools have limits in both flexibility and efficiency. Many forces drive the development of new tools including the desire to make complex system modeling design and analysis easier and the need for quicker turnaround time in analysis and design. Other considerations include the desire to make use of advanced computer architectures to help in control system design, adopt new methodologies in control, and integrate design processes (e.g., structure, control, optics). CAESY was developed to provide a means to evaluate methods for dealing with user needs in computer-aided control system design. It is an interpreter for performing engineering calculations and incorporates features of both Ada and MATLAB. It is designed to be reasonably flexible and powerful. CAESY includes internally defined functions and procedures, as well as user defined ones. Support for matrix calculations is provided in the same manner as MATLAB. However, the development of CAESY is a research project, and while it provides some features which are not found in commercially sold tools, it does not exhibit the robustness that many commercially developed tools provide. CAESY is written in C-language for use on Sun4 series computers running SunOS 4.1.1 and later. The program is designed to optionally use the LAPACK math library. The LAPACK math routines are available through anonymous ftp from research.att.com. CAESY requires 4Mb of RAM for execution. The standard distribution medium is a .25 inch streaming magnetic tape cartridge (QIC-24) in UNIX tar format. CAESY was developed in 1993 and is a copyrighted work with all copyright vested in NASA.

Computational modeling of brain tumors: discrete, continuum or hybrid?

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Deisboeck, Thomas S.

In spite of all efforts, patients diagnosed with highly malignant brain tumors (gliomas), continue to face a grim prognosis. Achieving significant therapeutic advances will also require a more detailed quantitative understanding of the dynamic interactions among tumor cells, and between these cells and their biological microenvironment. Data-driven computational brain tumor models have the potential to provide experimental tumor biologists with such quantitative and cost-efficient tools to generate and test hypotheses on tumor progression, and to infer fundamental operating principles governing bidirectional signal propagation in multicellular cancer systems. This review highlights the modeling objectives of and challenges with developing such in silico brain tumor models by outlining two distinct computational approaches: discrete and continuum, each with representative examples. Future directions of this integrative computational neuro-oncology field, such as hybrid multiscale multiresolution modeling are discussed.

Computational modeling of brain tumors: discrete, continuum or hybrid?

NASA Astrophysics Data System (ADS)

Wang, Zhihui; Deisboeck, Thomas S.

2008-04-01

In spite of all efforts, patients diagnosed with highly malignant brain tumors (gliomas), continue to face a grim prognosis. Achieving significant therapeutic advances will also require a more detailed quantitative understanding of the dynamic interactions among tumor cells, and between these cells and their biological microenvironment. Data-driven computational brain tumor models have the potential to provide experimental tumor biologists with such quantitative and cost-efficient tools to generate and test hypotheses on tumor progression, and to infer fundamental operating principles governing bidirectional signal propagation in multicellular cancer systems. This review highlights the modeling objectives of and challenges with developing such in silicobrain tumor models by outlining two distinct computational approaches: discrete and continuum, each with representative examples. Future directions of this integrative computational neuro-oncology field, such as hybrid multiscale multiresolution modeling are discussed.

Computational analysis of water entry of a circular section at constant velocity based on Reynold's averaged Navier-Stokes method

NASA Astrophysics Data System (ADS)

Uddin, M. Maruf; Fuad, Muzaddid-E.-Zaman; Rahaman, Md. Mashiur; Islam, M. Rabiul

2017-12-01

With the rapid decrease in the cost of computational infrastructure with more efficient algorithm for solving non-linear problems, Reynold's averaged Navier-Stokes (RaNS) based Computational Fluid Dynamics (CFD) has been used widely now-a-days. As a preliminary evaluation tool, CFD is used to calculate the hydrodynamic loads on offshore installations, ships, and other structures in the ocean at initial design stages. Traditionally, wedges have been studied more than circular cylinders because cylinder section has zero deadrise angle at the instant of water impact, which increases with increase of submergence. In Present study, RaNS based commercial code ANSYS Fluent is used to simulate the water entry of a circular section at constant velocity. It is seen that present computational results were compared with experiment and other numerical method.

Visual Analysis of Cloud Computing Performance Using Behavioral Lines.

PubMed

Muelder, Chris; Zhu, Biao; Chen, Wei; Zhang, Hongxin; Ma, Kwan-Liu

2016-02-29

Cloud computing is an essential technology to Big Data analytics and services. A cloud computing system is often comprised of a large number of parallel computing and storage devices. Monitoring the usage and performance of such a system is important for efficient operations, maintenance, and security. Tracing every application on a large cloud system is untenable due to scale and privacy issues. But profile data can be collected relatively efficiently by regularly sampling the state of the system, including properties such as CPU load, memory usage, network usage, and others, creating a set of multivariate time series for each system. Adequate tools for studying such large-scale, multidimensional data are lacking. In this paper, we present a visual based analysis approach to understanding and analyzing the performance and behavior of cloud computing systems. Our design is based on similarity measures and a layout method to portray the behavior of each compute node over time. When visualizing a large number of behavioral lines together, distinct patterns often appear suggesting particular types of performance bottleneck. The resulting system provides multiple linked views, which allow the user to interactively explore the data by examining the data or a selected subset at different levels of detail. Our case studies, which use datasets collected from two different cloud systems, show that this visual based approach is effective in identifying trends and anomalies of the systems.

Rough mill simulator version 3.0: an analysis tool for refining rough mill operations

Treesearch

Edward Thomas; Joel Weiss

2006-01-01

ROMI-3 is a rough mill computer simulation package designed to be used by both rip-first and chop-first rough mill operators and researchers. ROMI-3 allows users to model and examine the complex relationships among cutting bill, lumber grade mix, processing options, and their impact on rough mill yield and efficiency. Integrated into the ROMI-3 software is a new least-...

Decision Support Tool for Deep Energy Efficiency Retrofits in DoD Installations

DTIC Science & Technology

2014-01-01

representations (HDMR). Chemical Engineering Science, 57, 4445–4460. 2. Sobol ’, I., 2001. Global sensitivity indices for nonlinear mathematical...models and their Monte Carlo estimates. Mathematics and computers in simulation, 55, 271–280. 3. Sobol , I. and Kucherenko, S., 2009. Derivative based...representations (HDMR). Chemical Engineering Science, 57, 4445–4460. 16. Sobol ’, I., 2001. Global sensitivity indices for nonlinear mathematical models and

Contingency Analysis Post-Processing With Advanced Computing and Visualization

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

Chen, Yousu; Glaesemann, Kurt; Fitzhenry, Erin

Contingency analysis is a critical function widely used in energy management systems to assess the impact of power system component failures. Its outputs are important for power system operation for improved situational awareness, power system planning studies, and power market operations. With the increased complexity of power system modeling and simulation caused by increased energy production and demand, the penetration of renewable energy and fast deployment of smart grid devices, and the trend of operating grids closer to their capacity for better efficiency, more and more contingencies must be executed and analyzed quickly in order to ensure grid reliability andmore » accuracy for the power market. Currently, many researchers have proposed different techniques to accelerate the computational speed of contingency analysis, but not much work has been published on how to post-process the large amount of contingency outputs quickly. This paper proposes a parallel post-processing function that can analyze contingency analysis outputs faster and display them in a web-based visualization tool to help power engineers improve their work efficiency by fast information digestion. Case studies using an ESCA-60 bus system and a WECC planning system are presented to demonstrate the functionality of the parallel post-processing technique and the web-based visualization tool.« less

Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations

NASA Technical Reports Server (NTRS)

Sharma, Shivanjli; Fergus, John

2017-01-01

To address the Integrated Arrival, Departure, and Surface (IADS) challenge, NASA is developing and demonstrating trajectory-based departure automation under a collaborative effort with the FAA and industry known Airspace Technology Demonstration 2 (ATD-2). ATD-2 builds upon and integrates previous NASA research capabilities that include the Spot and Runway Departure Advisor (SARDA), the Precision Departure Release Capability (PDRC), and the Terminal Sequencing and Spacing (TSAS) capability. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users of the tools across a number of roles benefit from a real time system that enables common situational awareness. A real time dashboard was developed to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. In addition to shared situational awareness, the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial proposed set of metrics. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017: Charlotte-Douglas International Airport (CLT). The architecture of implementing such a tool as well as potential uses are presented for operations at CLT. Metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of system delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform users of the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

AZTEC. Parallel Iterative method Software for Solving Linear Systems

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

Hutchinson, S.; Shadid, J.; Tuminaro, R.

1995-07-01

AZTEC is an interactive library that greatly simplifies the parrallelization process when solving the linear systems of equations Ax=b where A is a user supplied n X n sparse matrix, b is a user supplied vector of length n and x is a vector of length n to be computed. AZTEC is intended as a software tool for users who want to avoid cumbersome parallel programming details but who have large sparse linear systems which require an efficiently utilized parallel processing system. A collection of data transformation tools are provided that allow for easy creation of distributed sparse unstructured matricesmore » for parallel solutions.« less

Collaborative Software Development in Support of Fast Adaptive AeroSpace Tools (FAAST)

NASA Technical Reports Server (NTRS)

Kleb, William L.; Nielsen, Eric J.; Gnoffo, Peter A.; Park, Michael A.; Wood, William A.

2003-01-01

A collaborative software development approach is described. The software product is an adaptation of proven computational capabilities combined with new capabilities to form the Agency's next generation aerothermodynamic and aerodynamic analysis and design tools. To efficiently produce a cohesive, robust, and extensible software suite, the approach uses agile software development techniques; specifically, project retrospectives, the Scrum status meeting format, and a subset of Extreme Programming's coding practices are employed. Examples are provided which demonstrate the substantial benefits derived from employing these practices. Also included is a discussion of issues encountered when porting legacy Fortran 77 code to Fortran 95 and a Fortran 95 coding standard.

Two Simple and Efficient Algorithms to Compute the SP-Score Objective Function of a Multiple Sequence Alignment.

PubMed

Ranwez, Vincent

2016-01-01

Multiple sequence alignment (MSA) is a crucial step in many molecular analyses and many MSA tools have been developed. Most of them use a greedy approach to construct a first alignment that is then refined by optimizing the sum of pair score (SP-score). The SP-score estimation is thus a bottleneck for most MSA tools since it is repeatedly required and is time consuming. Given an alignment of n sequences and L sites, I introduce here optimized solutions reaching O(nL) time complexity for affine gap cost, instead of O(n2L), which are easy to implement.

NEMOTAM: tangent and adjoint models for the ocean modelling platform NEMO

NASA Astrophysics Data System (ADS)

Vidard, A.; Bouttier, P.-A.; Vigilant, F.

2015-04-01

Tangent linear and adjoint models (TAMs) are efficient tools to analyse and to control dynamical systems such as NEMO. They can be involved in a large range of applications such as sensitivity analysis, parameter estimation or the computation of characteristic vectors. A TAM is also required by the 4D-Var algorithm, which is one of the major methods in data assimilation. This paper describes the development and the validation of the tangent linear and adjoint model for the NEMO ocean modelling platform (NEMOTAM). The diagnostic tools that are available alongside NEMOTAM are detailed and discussed, and several applications are also presented.

NEMOTAM: tangent and adjoint models for the ocean modelling platform NEMO

NASA Astrophysics Data System (ADS)

Vidard, A.; Bouttier, P.-A.; Vigilant, F.

2014-10-01

The tangent linear and adjoint model (TAM) are efficient tools to analyse and to control dynamical systems such as NEMO. They can be involved in a large range of applications such as sensitivity analysis, parameter estimation or the computation of characteristics vectors. TAM is also required by the 4-D-VAR algorithm which is one of the major method in Data Assimilation. This paper describes the development and the validation of the Tangent linear and Adjoint Model for the NEMO ocean modelling platform (NEMOTAM). The diagnostic tools that are available alongside NEMOTAM are detailed and discussed and several applications are also presented.

S3D: An interactive surface grid generation tool

NASA Technical Reports Server (NTRS)

Luh, Raymond Ching-Chung; Pierce, Lawrence E.; Yip, David

1992-01-01

S3D, an interactive software tool for surface grid generation, is described. S3D provides the means with which a geometry definition based either on a discretized curve set or a rectangular set can be quickly processed towards the generation of a surface grid for computational fluid dynamics (CFD) applications. This is made possible as a result of implementing commonly encountered surface gridding tasks in an environment with a highly efficient and user friendly graphical interface. Some of the more advanced features of S3D include surface-surface intersections, optimized surface domain decomposition and recomposition, and automated propagation of edge distributions to surrounding grids.

Tracking the NGS revolution: managing life science research on shared high-performance computing clusters.

PubMed

Dahlö, Martin; Scofield, Douglas G; Schaal, Wesley; Spjuth, Ola

2018-05-01

Next-generation sequencing (NGS) has transformed the life sciences, and many research groups are newly dependent upon computer clusters to store and analyze large datasets. This creates challenges for e-infrastructures accustomed to hosting computationally mature research in other sciences. Using data gathered from our own clusters at UPPMAX computing center at Uppsala University, Sweden, where core hour usage of ∼800 NGS and ∼200 non-NGS projects is now similar, we compare and contrast the growth, administrative burden, and cluster usage of NGS projects with projects from other sciences. The number of NGS projects has grown rapidly since 2010, with growth driven by entry of new research groups. Storage used by NGS projects has grown more rapidly since 2013 and is now limited by disk capacity. NGS users submit nearly twice as many support tickets per user, and 11 more tools are installed each month for NGS projects than for non-NGS projects. We developed usage and efficiency metrics and show that computing jobs for NGS projects use more RAM than non-NGS projects, are more variable in core usage, and rarely span multiple nodes. NGS jobs use booked resources less efficiently for a variety of reasons. Active monitoring can improve this somewhat. Hosting NGS projects imposes a large administrative burden at UPPMAX due to large numbers of inexperienced users and diverse and rapidly evolving research areas. We provide a set of recommendations for e-infrastructures that host NGS research projects. We provide anonymized versions of our storage, job, and efficiency databases.

Tracking the NGS revolution: managing life science research on shared high-performance computing clusters

PubMed Central

2018-01-01

Abstract Background Next-generation sequencing (NGS) has transformed the life sciences, and many research groups are newly dependent upon computer clusters to store and analyze large datasets. This creates challenges for e-infrastructures accustomed to hosting computationally mature research in other sciences. Using data gathered from our own clusters at UPPMAX computing center at Uppsala University, Sweden, where core hour usage of ∼800 NGS and ∼200 non-NGS projects is now similar, we compare and contrast the growth, administrative burden, and cluster usage of NGS projects with projects from other sciences. Results The number of NGS projects has grown rapidly since 2010, with growth driven by entry of new research groups. Storage used by NGS projects has grown more rapidly since 2013 and is now limited by disk capacity. NGS users submit nearly twice as many support tickets per user, and 11 more tools are installed each month for NGS projects than for non-NGS projects. We developed usage and efficiency metrics and show that computing jobs for NGS projects use more RAM than non-NGS projects, are more variable in core usage, and rarely span multiple nodes. NGS jobs use booked resources less efficiently for a variety of reasons. Active monitoring can improve this somewhat. Conclusions Hosting NGS projects imposes a large administrative burden at UPPMAX due to large numbers of inexperienced users and diverse and rapidly evolving research areas. We provide a set of recommendations for e-infrastructures that host NGS research projects. We provide anonymized versions of our storage, job, and efficiency databases. PMID:29659792

Arterial waveguide model for shear wave elastography: implementation and in vitro validation

NASA Astrophysics Data System (ADS)

Vaziri Astaneh, Ali; Urban, Matthew W.; Aquino, Wilkins; Greenleaf, James F.; Guddati, Murthy N.

2017-07-01

Arterial stiffness is found to be an early indicator of many cardiovascular diseases. Among various techniques, shear wave elastography has emerged as a promising tool for estimating local arterial stiffness through the observed dispersion of guided waves. In this paper, we develop efficient models for the computational simulation of guided wave dispersion in arterial walls. The models are capable of considering fluid-loaded tubes, immersed in fluid or embedded in a solid, which are encountered in in vitro/ex vivo, and in vivo experiments. The proposed methods are based on judiciously combining Fourier transformation and finite element discretization, leading to a significant reduction in computational cost while fully capturing complex 3D wave propagation. The developed methods are implemented in open-source code, and verified by comparing them with significantly more expensive, fully 3D finite element models. We also validate the models using the shear wave elastography of tissue-mimicking phantoms. The computational efficiency of the developed methods indicates the possibility of being able to estimate arterial stiffness in real time, which would be beneficial in clinical settings.

Neptune: a bioinformatics tool for rapid discovery of genomic variation in bacterial populations

PubMed Central

Marinier, Eric; Zaheer, Rahat; Berry, Chrystal; Weedmark, Kelly A.; Domaratzki, Michael; Mabon, Philip; Knox, Natalie C.; Reimer, Aleisha R.; Graham, Morag R.; Chui, Linda; Patterson-Fortin, Laura; Zhang, Jian; Pagotto, Franco; Farber, Jeff; Mahony, Jim; Seyer, Karine; Bekal, Sadjia; Tremblay, Cécile; Isaac-Renton, Judy; Prystajecky, Natalie; Chen, Jessica; Slade, Peter

2017-01-01

Abstract The ready availability of vast amounts of genomic sequence data has created the need to rethink comparative genomics algorithms using ‘big data’ approaches. Neptune is an efficient system for rapidly locating differentially abundant genomic content in bacterial populations using an exact k-mer matching strategy, while accommodating k-mer mismatches. Neptune’s loci discovery process identifies sequences that are sufficiently common to a group of target sequences and sufficiently absent from non-targets using probabilistic models. Neptune uses parallel computing to efficiently identify and extract these loci from draft genome assemblies without requiring multiple sequence alignments or other computationally expensive comparative sequence analyses. Tests on simulated and real datasets showed that Neptune rapidly identifies regions that are both sensitive and specific. We demonstrate that this system can identify trait-specific loci from different bacterial lineages. Neptune is broadly applicable for comparative bacterial analyses, yet will particularly benefit pathogenomic applications, owing to efficient and sensitive discovery of differentially abundant genomic loci. The software is available for download at: http://github.com/phac-nml/neptune. PMID:29048594

Efficient and Robust Optimization for Building Energy Simulation

PubMed Central

Pourarian, Shokouh; Kearsley, Anthony; Wen, Jin; Pertzborn, Amanda

2016-01-01

Efficiently, robustly and accurately solving large sets of structured, non-linear algebraic and differential equations is one of the most computationally expensive steps in the dynamic simulation of building energy systems. Here, the efficiency, robustness and accuracy of two commonly employed solution methods are compared. The comparison is conducted using the HVACSIM+ software package, a component based building system simulation tool. The HVACSIM+ software presently employs Powell’s Hybrid method to solve systems of nonlinear algebraic equations that model the dynamics of energy states and interactions within buildings. It is shown here that the Powell’s method does not always converge to a solution. Since a myriad of other numerical methods are available, the question arises as to which method is most appropriate for building energy simulation. This paper finds considerable computational benefits result from replacing the Powell’s Hybrid method solver in HVACSIM+ with a solver more appropriate for the challenges particular to numerical simulations of buildings. Evidence is provided that a variant of the Levenberg-Marquardt solver has superior accuracy and robustness compared to the Powell’s Hybrid method presently used in HVACSIM+. PMID:27325907

Efficient and Robust Optimization for Building Energy Simulation.

PubMed

Pourarian, Shokouh; Kearsley, Anthony; Wen, Jin; Pertzborn, Amanda

2016-06-15

Efficiently, robustly and accurately solving large sets of structured, non-linear algebraic and differential equations is one of the most computationally expensive steps in the dynamic simulation of building energy systems. Here, the efficiency, robustness and accuracy of two commonly employed solution methods are compared. The comparison is conducted using the HVACSIM+ software package, a component based building system simulation tool. The HVACSIM+ software presently employs Powell's Hybrid method to solve systems of nonlinear algebraic equations that model the dynamics of energy states and interactions within buildings. It is shown here that the Powell's method does not always converge to a solution. Since a myriad of other numerical methods are available, the question arises as to which method is most appropriate for building energy simulation. This paper finds considerable computational benefits result from replacing the Powell's Hybrid method solver in HVACSIM+ with a solver more appropriate for the challenges particular to numerical simulations of buildings. Evidence is provided that a variant of the Levenberg-Marquardt solver has superior accuracy and robustness compared to the Powell's Hybrid method presently used in HVACSIM+.

Using Simulation to Examine the Effect of Physician Heterogeneity on the Operational Efficiency of an Overcrowded Hospital Emergency Department

NASA Astrophysics Data System (ADS)

Kuo, Y.-H.; Leung, J. M. Y.; Graham, C. A.

2015-05-01

In this paper, we present a case study of modelling and analyzing the patient flow of a hospital emergency department in Hong Kong. The emergency department is facing the challenge of overcrowding and the patients there usually experience a long waiting time. Our project team was requested by a senior consultant of the emergency department to analyze the patient flow and provide a decision support tool to help improve their operations. We adopt a simulation approach to mimic their daily operations. With the simulation model, we conduct a computational study to examine the effect of physician heterogeneity on the emergency department performance. We found that physician heterogeneity has a great impact on the operational efficiency and thus should be considered when developing simulation models. Our computational results show that, with the same average of service rates among the physicians, variation in the rates can improve overcrowding situation. This suggests that emergency departments may consider having some efficient physicians to speed up the overall service rate in return for more time for patients who need extra medical care.

Bio-jETI: a service integration, design, and provisioning platform for orchestrated bioinformatics processes.

PubMed

Margaria, Tiziana; Kubczak, Christian; Steffen, Bernhard

2008-04-25

With Bio-jETI, we introduce a service platform for interdisciplinary work on biological application domains and illustrate its use in a concrete application concerning statistical data processing in R and xcms for an LC/MS analysis of FAAH gene knockout. Bio-jETI uses the jABC environment for service-oriented modeling and design as a graphical process modeling tool and the jETI service integration technology for remote tool execution. As a service definition and provisioning platform, Bio-jETI has the potential to become a core technology in interdisciplinary service orchestration and technology transfer. Domain experts, like biologists not trained in computer science, directly define complex service orchestrations as process models and use efficient and complex bioinformatics tools in a simple and intuitive way.

Online machining error estimation method of numerical control gear grinding machine tool based on data analysis of internal sensors

NASA Astrophysics Data System (ADS)

Zhao, Fei; Zhang, Chi; Yang, Guilin; Chen, Chinyin

2016-12-01

This paper presents an online estimation method of cutting error by analyzing of internal sensor readings. The internal sensors of numerical control (NC) machine tool are selected to avoid installation problem. The estimation mathematic model of cutting error was proposed to compute the relative position of cutting point and tool center point (TCP) from internal sensor readings based on cutting theory of gear. In order to verify the effectiveness of the proposed model, it was simulated and experimented in gear generating grinding process. The cutting error of gear was estimated and the factors which induce cutting error were analyzed. The simulation and experiments verify that the proposed approach is an efficient way to estimate the cutting error of work-piece during machining process.

Virtual Tool Mark Generation for Efficient Striation Analysis

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

Ekstrand, Laura; Zhang, Song; Grieve, Taylor

2014-02-16

This study introduces a tool mark analysis approach based upon 3D scans of screwdriver tip and marked plate surfaces at the micrometer scale from an optical microscope. An open-source 3D graphics software package is utilized to simulate the marking process as the projection of the tip's geometry in the direction of tool travel. The edge of this projection becomes a virtual tool mark that is compared to cross-sections of the marked plate geometry using the statistical likelihood algorithm introduced by Chumbley et al. In a study with both sides of six screwdriver tips and 34 corresponding marks, the method distinguishedmore » known matches from known nonmatches with zero false-positive matches and two false-negative matches. For matches, it could predict the correct marking angle within ±5–10°. Individual comparisons could be made in seconds on a desktop computer, suggesting that the method could save time for examiners.« less

EasyModeller: A graphical interface to MODELLER

PubMed Central

2010-01-01

Background MODELLER is a program for automated protein Homology Modeling. It is one of the most widely used tool for homology or comparative modeling of protein three-dimensional structures, but most users find it a bit difficult to start with MODELLER as it is command line based and requires knowledge of basic Python scripting to use it efficiently. Findings The study was designed with an aim to develop of "EasyModeller" tool as a frontend graphical interface to MODELLER using Perl/Tk, which can be used as a standalone tool in windows platform with MODELLER and Python preinstalled. It helps inexperienced users to perform modeling, assessment, visualization, and optimization of protein models in a simple and straightforward way. Conclusion EasyModeller provides a graphical straight forward interface and functions as a stand-alone tool which can be used in a standard personal computer with Microsoft Windows as the operating system. PMID:20712861

FY17 Status Report on NEAMS Neutronics Activities

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

Lee, C. H.; Jung, Y. S.; Smith, M. A.

2017-09-30

Under the U.S. DOE NEAMS program, the high-fidelity neutronics code system has been developed to support the multiphysics modeling and simulation capability named SHARP. The neutronics code system includes the high-fidelity neutronics code PROTEUS, the cross section library and preprocessing tools, the multigroup cross section generation code MC2-3, the in-house meshing generation tool, the perturbation and sensitivity analysis code PERSENT, and post-processing tools. The main objectives of the NEAMS neutronics activities in FY17 are to continue development of an advanced nodal solver in PROTEUS for use in nuclear reactor design and analysis projects, implement a simplified sub-channel based thermal-hydraulic (T/H)more » capability into PROTEUS to efficiently compute the thermal feedback, improve the performance of PROTEUS-MOCEX using numerical acceleration and code optimization, improve the cross section generation tools including MC2-3, and continue to perform verification and validation tests for PROTEUS.« less

iTools: a framework for classification, categorization and integration of computational biology resources.

PubMed

Dinov, Ivo D; Rubin, Daniel; Lorensen, William; Dugan, Jonathan; Ma, Jeff; Murphy, Shawn; Kirschner, Beth; Bug, William; Sherman, Michael; Floratos, Aris; Kennedy, David; Jagadish, H V; Schmidt, Jeanette; Athey, Brian; Califano, Andrea; Musen, Mark; Altman, Russ; Kikinis, Ron; Kohane, Isaac; Delp, Scott; Parker, D Stott; Toga, Arthur W

2008-05-28

The advancement of the computational biology field hinges on progress in three fundamental directions--the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources--data, software tools and web-services. The iTools design, implementation and resource meta-data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu.

iTools: A Framework for Classification, Categorization and Integration of Computational Biology Resources

PubMed Central

Dinov, Ivo D.; Rubin, Daniel; Lorensen, William; Dugan, Jonathan; Ma, Jeff; Murphy, Shawn; Kirschner, Beth; Bug, William; Sherman, Michael; Floratos, Aris; Kennedy, David; Jagadish, H. V.; Schmidt, Jeanette; Athey, Brian; Califano, Andrea; Musen, Mark; Altman, Russ; Kikinis, Ron; Kohane, Isaac; Delp, Scott; Parker, D. Stott; Toga, Arthur W.

2008-01-01

The advancement of the computational biology field hinges on progress in three fundamental directions – the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources–data, software tools and web-services. The iTools design, implementation and resource meta - data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu. PMID:18509477

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

Zitney, S.E.

Emerging fossil energy power generation systems must operate with unprecedented efficiency and near-zero emissions, while optimizing profitably amid cost fluctuations for raw materials, finished products, and energy. To help address these challenges, the fossil energy industry will have to rely increasingly on the use advanced computational tools for modeling and simulating complex process systems. In this paper, we present the computational research challenges and opportunities for the optimization of fossil energy power generation systems across the plant lifecycle from process synthesis and design to plant operations. We also look beyond the plant gates to discuss research challenges and opportunities formore » enterprise-wide optimization, including planning, scheduling, and supply chain technologies.« less

Trends in Programming Languages for Neuroscience Simulations

PubMed Central

Davison, Andrew P.; Hines, Michael L.; Muller, Eilif

2009-01-01

Neuroscience simulators allow scientists to express models in terms of biological concepts, without having to concern themselves with low-level computational details of their implementation. The expressiveness, power and ease-of-use of the simulator interface is critical in efficiently and accurately translating ideas into a working simulation. We review long-term trends in the development of programmable simulator interfaces, and examine the benefits of moving from proprietary, domain-specific languages to modern dynamic general-purpose languages, in particular Python, which provide neuroscientists with an interactive and expressive simulation development environment and easy access to state-of-the-art general-purpose tools for scientific computing. PMID:20198154

Recent advances in fluidized bed drying

NASA Astrophysics Data System (ADS)

Haron, N. S.; Zakaria, J. H.; Mohideen Batcha, M. F.

2017-09-01

Fluidized bed drying are very well known to yield high heat and mass transfer and hence adopted to many industrial drying processes particularly agricultural products. In this paper, recent advances in fluidized bed drying were reviewed and focus is given to the drying related to the usage of Computational Fluid Dynamics (CFD). It can be seen that usage of modern computational tools such as CFD helps to optimize the fluidized bed dryer design and operation for lower energy consumption and thus better thermal efficiency. Among agricultural products that were reviewed in this paper were oil palm frond, wheat grains, olive pomace, coconut, pepper corn and millet.

Learning of embodied interaction dynamics with recurrent neural networks: some exploratory experiments.

PubMed

Oubbati, Mohamed; Kord, Bahram; Koprinkova-Hristova, Petia; Palm, Günther

2014-04-01

The new tendency of artificial intelligence suggests that intelligence must be seen as a result of the interaction between brains, bodies and environments. This view implies that designing sophisticated behaviour requires a primary focus on how agents are functionally coupled to their environments. Under this perspective, we present early results with the application of reservoir computing as an efficient tool to understand how behaviour emerges from interaction. Specifically, we present reservoir computing models, that are inspired by imitation learning designs, to extract the essential components of behaviour that results from agent-environment interaction dynamics. Experimental results using a mobile robot are reported to validate the learning architectures.

Learning of embodied interaction dynamics with recurrent neural networks: some exploratory experiments

NASA Astrophysics Data System (ADS)

Oubbati, Mohamed; Kord, Bahram; Koprinkova-Hristova, Petia; Palm, Günther

2014-04-01

The new tendency of artificial intelligence suggests that intelligence must be seen as a result of the interaction between brains, bodies and environments. This view implies that designing sophisticated behaviour requires a primary focus on how agents are functionally coupled to their environments. Under this perspective, we present early results with the application of reservoir computing as an efficient tool to understand how behaviour emerges from interaction. Specifically, we present reservoir computing models, that are inspired by imitation learning designs, to extract the essential components of behaviour that results from agent-environment interaction dynamics. Experimental results using a mobile robot are reported to validate the learning architectures.

Trends in programming languages for neuroscience simulations.

PubMed

Davison, Andrew P; Hines, Michael L; Muller, Eilif

2009-01-01

Neuroscience simulators allow scientists to express models in terms of biological concepts, without having to concern themselves with low-level computational details of their implementation. The expressiveness, power and ease-of-use of the simulator interface is critical in efficiently and accurately translating ideas into a working simulation. We review long-term trends in the development of programmable simulator interfaces, and examine the benefits of moving from proprietary, domain-specific languages to modern dynamic general-purpose languages, in particular Python, which provide neuroscientists with an interactive and expressive simulation development environment and easy access to state-of-the-art general-purpose tools for scientific computing.

VIPER: Visualization Pipeline for RNA-seq, a Snakemake workflow for efficient and complete RNA-seq analysis.

PubMed

Cornwell, MacIntosh; Vangala, Mahesh; Taing, Len; Herbert, Zachary; Köster, Johannes; Li, Bo; Sun, Hanfei; Li, Taiwen; Zhang, Jian; Qiu, Xintao; Pun, Matthew; Jeselsohn, Rinath; Brown, Myles; Liu, X Shirley; Long, Henry W

2018-04-12

RNA sequencing has become a ubiquitous technology used throughout life sciences as an effective method of measuring RNA abundance quantitatively in tissues and cells. The increase in use of RNA-seq technology has led to the continuous development of new tools for every step of analysis from alignment to downstream pathway analysis. However, effectively using these analysis tools in a scalable and reproducible way can be challenging, especially for non-experts. Using the workflow management system Snakemake we have developed a user friendly, fast, efficient, and comprehensive pipeline for RNA-seq analysis. VIPER (Visualization Pipeline for RNA-seq analysis) is an analysis workflow that combines some of the most popular tools to take RNA-seq analysis from raw sequencing data, through alignment and quality control, into downstream differential expression and pathway analysis. VIPER has been created in a modular fashion to allow for the rapid incorporation of new tools to expand the capabilities. This capacity has already been exploited to include very recently developed tools that explore immune infiltrate and T-cell CDR (Complementarity-Determining Regions) reconstruction abilities. The pipeline has been conveniently packaged such that minimal computational skills are required to download and install the dozens of software packages that VIPER uses. VIPER is a comprehensive solution that performs most standard RNA-seq analyses quickly and effectively with a built-in capacity for customization and expansion.

A Novel Shape Parameterization Approach

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.

1999-01-01

This paper presents a novel parameterization approach for complex shapes suitable for a multidisciplinary design optimization application. The approach consists of two basic concepts: (1) parameterizing the shape perturbations rather than the geometry itself and (2) performing the shape deformation by means of the soft objects animation algorithms used in computer graphics. Because the formulation presented in this paper is independent of grid topology, we can treat computational fluid dynamics and finite element grids in a similar manner. The proposed approach is simple, compact, and efficient. Also, the analytical sensitivity derivatives are easily computed for use in a gradient-based optimization. This algorithm is suitable for low-fidelity (e.g., linear aerodynamics and equivalent laminated plate structures) and high-fidelity analysis tools (e.g., nonlinear computational fluid dynamics and detailed finite element modeling). This paper contains the implementation details of parameterizing for planform, twist, dihedral, thickness, and camber. The results are presented for a multidisciplinary design optimization application consisting of nonlinear computational fluid dynamics, detailed computational structural mechanics, performance, and a simple propulsion module.

Multidisciplinary Aerodynamic-Structural Shape Optimization Using Deformation (MASSOUD)

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.

2000-01-01

This paper presents a multidisciplinary shape parameterization approach. The approach consists of two basic concepts: (1) parameterizing the shape perturbations rather than the geometry itself and (2) performing the shape deformation by means of the soft object animation algorithms used in computer graphics. Because the formulation presented in this paper is independent of grid topology, we can treat computational fluid dynamics and finite element grids in the same manner. The proposed approach is simple, compact, and efficient. Also, the analytical sensitivity derivatives are easily computed for use in a gradient-based optimization. This algorithm is suitable for low-fidelity (e.g., linear aerodynamics and equivalent laminate plate structures) and high-fidelity (e.g., nonlinear computational fluid dynamics and detailed finite element modeling) analysis tools. This paper contains the implementation details of parameterizing for planform, twist, dihedral, thickness, camber, and free-form surface. Results are presented for a multidisciplinary application consisting of nonlinear computational fluid dynamics, detailed computational structural mechanics, and a simple performance module.

Multidisciplinary Aerodynamic-Structural Shape Optimization Using Deformation (MASSOUD)

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.

2000-01-01

This paper presents a multidisciplinary shape parameterization approach. The approach consists of two basic concepts: (1) parameterizing the shape perturbations rather than the geometry itself and (2) performing the shape deformation by means of the soft object animation algorithms used in computer graphics. Because the formulation presented in this paper is independent of grid topology, we can treat computational fluid dynamics and finite element grids in a similar manner. The proposed approach is simple, compact, and efficient. Also, the analytical sensitivity derivatives are easily computed for use in a gradient-based optimization. This algorithm is suitable for low-fidelity (e.g., linear aerodynamics and equivalent laminated plate structures) and high-fidelity (e.g., nonlinear computational fluid dynamics and detailed finite element modeling analysis tools. This paper contains the implementation details of parameterizing for planform, twist, dihedral, thickness, camber, and free-form surface. Results are presented for a multidisciplinary design optimization application consisting of nonlinear computational fluid dynamics, detailed computational structural mechanics, and a simple performance module.

Computation of multi-dimensional viscous supersonic flow

NASA Technical Reports Server (NTRS)

Buggeln, R. C.; Kim, Y. N.; Mcdonald, H.

1986-01-01

A method has been developed for two- and three-dimensional computations of viscous supersonic jet flows interacting with an external flow. The approach employs a reduced form of the Navier-Stokes equations which allows solution as an initial-boundary value problem in space, using an efficient noniterative forward marching algorithm. Numerical instability associated with forward marching algorithms for flows with embedded subsonic regions is avoided by approximation of the reduced form of the Navier-Stokes equations in the subsonic regions of the boundary layers. Supersonic and subsonic portions of the flow field are simultaneously calculated by a consistently split linearized block implicit computational algorithm. The results of computations for a series of test cases associated with supersonic jet flow is presented and compared with other calculations for axisymmetric cases. Demonstration calculations indicate that the computational technique has great promise as a tool for calculating a wide range of supersonic flow problems including jet flow. Finally, a User's Manual is presented for the computer code used to perform the calculations.