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JOURNAL OF GRID COMPUTING 2010年第2期8卷 159-179页

作者： Fanfani, Alessandra Afaq, Anzar Sanches, Jose Afonso Andreeva, Julia Bagliesi, Giusepppe Bauerdick, Lothar Belforte, Stefano Sampaio, Patricia Bittencourt Bloom, Ken Blumenfeld, Barry Bonacorsi, Daniele Brew, Chris Calloni, Marco Cesini, Daniele Cinquilli, Mattia Codispoti, Giuseppe D'Hondt, Jorgen Dong, Liang Dongiovanni, Danilo Donvito, Giacinto Dykstra, David Edelmann, Erik Egeland, Ricky Elmer, Peter Eulisse, Giulio Evans, Dave Fanzago, Federica Farina, Fabio Feichtinger, Derek Fisk, Ian Flix, Josep Grandi, Claudio Guo, Yuyi Happonen, Kalle Hernandez, Jose M. Huang, Chih-Hao Kang, Kejing Karavakis, Edward Kasemann, Matthias Kavka, Carlos Khan, Akram Kim, Bockjoo Klem, Jukka Koivumaki, Jesper Kress, Thomas Kreuzer, Peter Kurca, Tibor Kuznetsov, Valentin Lacaprara, Stefano Lassila-Perini, Kati Letts, James Linden, Tomas Lueking, Lee Maes, Joris Magini, Nicolo Maier, Gerhild Mcbride, Patricia Metson, Simon Miccio, Vincenzo Padhi, Sanjay Pi, Haifeng Riahi, Hassen Riley, Daniel Rossman, Paul Saiz, Pablo Sartirana, Andrea Sciaba, Andrea Sekhri, Vijay Spiga, Daniele Tuura, Lassi Vaandering, Eric Vanelderen, Lukas Van Mulders, Petra Vedaee, Aresh Villella, Ilaria Wicklund, Eric Wildish, Tony Wissing, Christoph Wuerthwein, Frank Ist Nazl Fis Nucl I-40127 Bologna Italy Univ Bologna I-40127 Bologna Italy Fermilab Natl Accelerator Lab Batavia IL USA Univ Rio De Janeiro UERJ Rio De Janeiro Brazil CERN CH-1211 Geneva 23 Switzerland Pisa INFN Pisa Italy Trieste INFN Trieste Italy Univ Nebraska Lincoln NE USA Johns Hopkins Univ Baltimore MD USA Rutherford Appleton Lab Didcot OX11 0QX Oxon England INFN CNAF Bologna Italy Perugia INFN Perugia Italy Brussel Univ Brussels Belgium Chinese Acad Sci Inst High Energy Phys Acad Sinica Beijing Peoples R China Ist Nazl Fis Nucl I-70126 Bari Italy Univ Bari Bari Italy Helsinki Inst Phys Helsinki Finland Univ Minnesota St Paul MN USA Princeton Univ Princeton NJ 08544 USA Northeastern Univ Boston MA 02115 USA Padova INFN Padua Italy Milano Bicocca INFN Milan Italy Paul Scherrer Inst Villigen Switzerland CIEMAT E-28040 Madrid Spain PIC Barcelona Spain Peking Univ Beijing Peoples R China Brunel Univ London England DESY D-2000 Hamburg Germany Univ Florida Gainesville FL USA Rhein Westfal TH Aachen Aachen Germany Inst Phys Nucl Villeurbanne France Cornell Univ Ithaca NY USA Legnaro INFN Legnaro Italy Univ Calif San Diego La Jolla CA 92093 USA Univ Linz A-4040 Linz Austria Univ Bristol Bristol Avon England Ecole Polytech F-75230 Paris France Univ Ghent B-9000 Ghent Belgium

The CMS experiment expects to manage several Pbytes of data each year during the LHC programme, distributing them over many computing sites around the world and enabling data access at those centers for analysis. CMS has identified the distributed sites as the primary location for physics analysis to support a wide community with thousands potential users. This represents an unprecedented experimental challenge in terms of the scale of distributed computing resources and number of user. An overview of the computing architecture, the software tools and the distributed infrastructure is reported. Summaries of the experience in establishing efficient and scalable operations to get prepared for CMS distributed analysis are presented, followed by the user experience in their current analysis activities.

关键词： LHC CMS distributed analysis Grid

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distributed analysis jobs with the ATLAS production system

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IEEE TRANSACTIONS ON NUCLEAR SCIENCE 2006年第6期53卷 3803-3807页

作者： Gonzalez, Santiago Liko, Dietrich Nairz, Armin Mair, Gregor Orellana, Frederik Goossens, Luc Resconi, Silvia de Salvo, Alessandro CERN European Org Nucl Res CH-1211 Geneva Switzerland Sez Milano Ist Nazl Fis Nucl Milan Italy Sez Roma Ist Nazl Fis Nucl Rome Italy

The Large Hadron Collider at CERN will start data acquisition in 2007. The A Torioidal LHC ApparatuS (ATLAS) experiment is preparing for the data handling and analysis via a series of data challenges and production exercises to validate its computing model to provide useful samples of data for detector and physics studies. The ATLAS production system has been successfully used to run production of simulation data at an unprecedented scale. Up to 10 000 jobs were processed by the system on about 100 sites in one day. In this paper, we discuss the experience of performing analysis jobs using this system on the LCG infrastructure.

关键词： ATLAS distributed analysis grid high energy physics

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Fully distributed analysis of MOS Transistor at Millimeter-Wave Band, Based on Matrix-Functions of the Three Line Active Transmission Lines Model

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APPLIED COMPUTATIONAL ELECTROMAGNETICS SOCIETY JOURNAL 2016年第11期31卷 1330-1336页

作者： Khoshniyat, H. Abdipour, A. Moradi, G. Amirkabir Univ Technol Inst Commun Technol & Appl Elect Dept Elect Engn Tehran 15914 Iran

In this paper, distributed model of MOS transistor is presented that is based on active multi-conductor transmission line model. The analysis is done in frequency domain by considering frequency dependence of primary parameters such as series resistance caused by skin effect. The analysis is performed based on matrix function that is calculated by eigenvalue approach in the frequency domain. The scattering parameters are computed by using transmission matrix and applying boundary conditions. To investigate the analysis, the scattering parameters of a 0.13 mu m transistor are calculated by proposed approach over the 1-100 GHz frequency band. They compared with the results obtained from the available lumped and distributed models and a commercial simulator that have a good agreement with each other.

关键词： Active multi transmission lines distributed analysis matrix function MOS transistor skin effect

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ASAP distributed analysis

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IEEE TRANSACTIONS ON NUCLEAR SCIENCE 2007年第5期54卷 1753-1757页

作者： Munro, Craig Andreeva, Julia Khan, Akram Brunel Univ Uxbridge UB8 3PH Middx England CERN CH-1211 Geneva 23 Switzerland

The Grid offers physicists far more resources than have previously been available by combining elements in computing centers around the world into a globally accessible resource. However, in order to harness this computing power many steps need to be performed for job creation and management and data discovery. ASAP (ARDA Support for CMS analysis Process) was developed to make this step as simple and straightforward as possible for physicists working on the Compact Moon Solenoid (CMS) experiment at CERN. ASAP transfers a local application to the Grid by packaging the application, discovering the location of input data then creating, submitting and monitoring jobs. One of the main components of the system is that users can delegate responsibility for their tasks to the ASAP server which can take actions on behalf of the user to ensure that tasks are completed successfully. The system can operate in the traditional push model but can also be used by agents executing on the Grid to pull jobs to the worker node for execution.

关键词： distributed analysis grid computing high energy physics software

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Watchdog - a workflow management system for the distributed analysis of large-scale experimental data

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BMC BIOINFORMATICS 2018年第20180327期19卷 97-97页

作者： Kluge, Michael Friedel, Caroline C. Ludwig Maximilians Univ Munchen Inst Informat Amalienstr 17 D-80333 Munich Germany

Background: The development of high-throughput experimental technologies, such as next-generation sequencing, have led to new challenges for handling, analyzing and integrating the resulting large and diverse datasets. Bioinformatical analysis of these data commonly requires a number of mutually dependent steps applied to numerous samples for multiple conditions and replicates. To support these analyses, a number of workflow management systems (WMSs) have been developed to allow automated execution of corresponding analysis workflows. Major advantages of WMSs are the easy reproducibility of results as well as the reusability of workflows or their components. Results: In this article, we present Watchdog, a WMS for the automated analysis of large-scale experimental data. Main features include straightforward processing of replicate data, support for distributed computer systems, customizable error detection and manual intervention into workflow execution. Watchdog is implemented in Java and thus platform-independent and allows easy sharing of workflows and corresponding program modules. It provides a graphical user interface (GUI) for workflow construction using pre-defined modules as well as a helper script for creating new module definitions. Execution of workflows is possible using either the GUI or a command-line interface and a web-interface is provided for monitoring the execution status and intervening in case of errors. To illustrate its potentials on a real-life example, a comprehensive workflow and modules for the analysis of RNA-seq experiments were implemented and are provided with the software in addition to simple test examples. Conclusions: Watchdog is a powerful and flexible WMS for the analysis of large-scale high-throughput experiments. We believe it will greatly benefit both users with and without programming skills who want to develop and apply bioinformatical workflows with reasonable overhead. The software, example workflows and a comprehensive

关键词： Workflow management system High-throughput experiments Large-scale datasets Automated execution distributed analysis Reusability Reproducibility RNA-seq

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Workflow-Driven Programming Paradigms for distributed analysis of Biological Big Data

Workflow-Driven Programming Paradigms for Distributed Analys...

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IEEE International Conference on Computational Advances in Bio and Medical Sciences

作者： Ilkay Altintas San Diego Supercomputer Center University of California San Diego La Jolla CA 92093-0505 USA

ISBN: (纸本)9781479907151

Scientific workflows have been used as a programming model to automate scientific tasks ranging from short pipelines to complex workflows that span across heterogeneous data and computing resources. While utilization of scientific workflow technologies varies slightly across different scientific disciplines, all informatics and computational science disciplines provide a common set of attributes to facilitate and accelerate workflow-driven research. Scientific workflows provide assembly of complex processing easily in local or distributed environments via rich and expressive programming models. Scientific workflows enable transparent access to diverse resources ranging from local clusters and traditional supercomputers to elastic and heterogeneous Cloud resources. Scientific workflows support incorporation of multiple software tools including domain specific tools for standard processing to custom generalized workflows and middleware tools that can be reused in various contexts. Scientific workflows often collect provenance information on workflow entities, e.g., workflow definitions, their executions and run time parameters, and, in turn, assure a level of reproducibility while enabling referencing and replicating results. While doing all these, scientific workflows often foster an open-source, open-access and standards-driven community development model based on sharing and collaborations. Cyberinfrastructure platforms and gateways commonly employ scientific workflows to bridge the gap between the infrastructure and users needs. While capturing and communicating the scientific process formally, workflows ensure flexibility, synergy between users, provide optimized usage of resources, increase reuse and ensure compliance with system specific data models and community-driven standards. Currently, scientific workflows are used widely in life sciences at different stages of end-to-end 'data lifecycle from generation to analysis and publication of biological data. The

关键词： Workflow-Driven Programming Paradigms distributed analysis

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Overcoming Limited Collaboration Channels in distributed Intelligence analysis: Visualization Tools and Design Seeds

Overcoming Limited Collaboration Channels in Distributed Int...

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IEEE Joint Intelligence and Security Informatics Conference (JISIC 2014)

作者： Prue, Brian Jenkins, Michael Stern, Lauren D. Pfautz, Jonathan Charles River Analyt Cambridge MA 02138 USA

ISBN: (纸本)9781479963645

Military intelligence analysis (IA) support tools are often developed using generalized models of IA that fail to take into consideration the real-world constraints put on analysts by factors such as organizational structures and cultures. IA in domains where distributed collaboration is required because direct communication and coordination is infeasible represents a challenge for generalized models of IA. This paper provides our analysis of distributed IA, which we conducted to support the design of software. We present a resulting set of capabilities that have been developed and deployed in an operational community. Our analysis approach and design focuses on extracting requirements and translating them into "design seeds," or guidelines for implementation, which are later used to verify that the resulting system meets the expressed requirements.

关键词： Intelligence analysis Visual Analytics Network Visualization Collaboration distributed analysis

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A Visual Analytics Framework for distributed Data analysis Systems

A Visual Analytics Framework for Distributed Data Analysis S...

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9th IEEE International Conference on Big Data (IEEE BigData)

作者： Nayeem, Abdullah-Al-Raihan Elshambakey, Mohammed Dobbs, Todd Lee, Huikyo Crichton, Daniel Zhu, Yimin Chokwitthaya, Chanachok Tolone, William J. Cho, Isaac Univ North Carolina Charlotte Coll Comp & Informat Charlotte NC 28223 USA Univ North Carolina Greensboro Comp Sci Greensboro NC USA City Sci Res & Technol Applicat Alexandria Egypt CALTECH Jet Prop Lab Pasadena CA USA Louisiana State Univ Construct Management Baton Rouge LA 70803 USA Utah State Univ Comp Sci Logan UT 84322 USA

ISBN: (纸本)9781665439022

This paper proposes a visual analytics framework that addresses the complex user interactions required through a command-line interface to run analyses in distributed data analysis systems. The visual analytics framework facilitates the user to manage access to the distributed servers, incorporate data from the source, run data-driven analysis, monitor the progress, and explore the result using interactive visualizations. We provide a user interface embedded with generalized functionalities and access protocols and integrate it with a distributed analysis system. To demonstrate our proof of concept, we present two use cases from the earth science and Sustainable Human Building Ecosystem research domain.

关键词： visual analytics distributed analysis data-driven analysis

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A high-throughput distributed DNA sequence analysis and database system

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IBM SYSTEMS JOURNAL 2001年第2期40卷 464-486页

作者： Inman, JT Flores, HR May, GD Weller, JW Bell, CJ Natl Ctr Genome Resources Santa Fe NM 87505 USA Netvoice Technol Corp Irving TX 75063 USA Samuel Roberts Noble Fdn Inc Ardmore OK 73402 USA Virginia Polytech Inst & State Univ Virginia Bioinformat Inst Blacksburg VA 24136 USA

The National Center for Genome Resources (NCGR) has developed a high-throughput DNA (deoxyribonucleic acid) sequence analysis pipeline, which allows researchers at remote sites to submit biological sequence information for rapid analysis, the results of which can be queried through a Web interface. Behind the browser interface is a relational database used to manage both the raw data and the results of the different analyses performed, and a server, which performs those analyses. The system allows multiple contributors to submit data and also allows the data to be marked as "private" or as available to the general public. The CPU-intensive part of the processing is done on a 40-processor domain of a Sun Enterprise 10000 computer, which is represented by a distributed system of software objects, implemented in CORBA (TM) (Common Object Request Broker Architecture (TM)). In this paper we discuss the architecture of the pipeline, the database support, types of DNA sequence analysis used, the distributed analysis system, and the capabilities of the Web interface. As a case study, we present data from an ongoing collaborative project in which expressed sequence tags (ESTs) from Medicago truncatula are being processed. M. truncatula is a plant that is used as a research model for crops in the legume family, an economically important group of food and forage plants.

关键词： .Sequencing acid processor ESTs DNA Sequence Genome Resources NCGR analysis pipeline distributed analysis Medicago

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Object oriented implementation of distributed finite element analysis in .NET

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ADVANCES IN ENGINEERING SOFTWARE 2007年第11-12期38卷 726-737页

作者： Mackie, Robert Ian Univ Dundee Fac Engn & Phys Sci Dundee DD1 4HN Scotland

The paper describes a detailed study into the object-oriented implementation of distributed finite element analysis on desktop computers using the NET framework. The software design aspects are described in some detail for both direct and iterative solution algorithms. The use of interfaces played an important role in the software design. This, together with the NET framework, enabled remote objects to be implemented in a relatively seamless fashion. The solution routines were "blind" to whether the objects were local or remote. Numerical tests were carried out and reasonable speed-up was achieved, particularly for direct solution methods. It is concluded that NET provides a viable framework for implementing distributed computing on networks of personal computers. (c) 2006 Elsevier Ltd. and Civil-Comp Ltd. All rights reserved.

关键词： object-oriented programming finite element analysis distributed analysis parallel computing .NET

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