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2013 IEEE 37th Annual computer Software and Applications Conference, COMPSAC 2013

作者： Gahvari, Hormozd Gropp, William Jordan, Kirk E. Schulz, Martin Yang, Ulrike Meier Department of Computer Science University of Illinois at Urbana-Champaign Urbana IL 61801 United States Computational Science Center IBM TJ Watson Research Center Cambridge MA 02142 United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore CA 94551 United States

ISBN: (纸本)9780769549798

Algebraic Multigrid (AMG) solvers find wide use in scientific simulation codes. Their ideal computational complexity makes them especially attractive for solving large problems on parallel machines. However, they also involve a substantial amount of data movement, posing challenges to performance and scalability. In this paper, we present an algorithm that provides a systematic means of reducing data movement in AMG. The algorithm operates by gathering and redistributing the problem data to reduce the need to move it on the communication-intensive coarse grid portion of AMG. The data is gathered in a way that ensures data locality by keeping data movement confined to specific regions of the machine. Any decision to gather data is made systematically through the means of a performance model. This approach results in substantial speedups on a multicore cluster when using AMG to solve a variety of test problems. © 2013 IEEE.

关键词： Algebra

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11th German Conference on Chemoinformatics (GCC 2015) Abstracts

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JOURNAL OF CHEMINFORMATICS 2016年第SUPPL 1期8卷 1-27页

作者： [Anonymous] GDCh-CIC Division Associated Board Member Beilstein-Institut zur Förderung der Chemischen Wissenschaften Trakehner Str. 7-9 60487 Frankfurt Germany. ufechner@beilstein-institut.de. Division Medicinal Chemistry Amsterdam Institute for Molecules Medicines and Systems (AIMMS) VU University Amsterdam The Netherlands. Centre for Bioinformatics Uni Hamburg Bundesstr. 43 20146 Hamburg Germany. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. stefan.guessregen@***. Sanofi-Aventis Deutschland GmbH 65926 Frankfurt am Main Germany. GlaxoSmithKline Stevenage SG1 2NY UK. nicola.j.richmond@***. Discngine Paris 75011 France. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. marwin.segler@wwu.de. Organisch-Chemisches Institut Westfälische Wilhelms-Universität Münster Germany. Bundeskriminalamt Wiesbaden Central Analytics II 65173 Wiesbaden Germany. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. shea@chem.ucsb.edu. Department of Chemistry and Biochemistry University of California Santa Barbara CA 93111 USA. Chemistry Department Ludwig-Maximilians-Universität München Butenandtstr. 7 81377 Munich Germany. Inorganic Chemistry and Center for Nanointegration University of Duisburg-Essen Essen Germany. CAM-D Technologies Essen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. Institute for Bioinformatics and Chemoinformatics Westphalian University of Applied Sciences Recklinghausen Germany. achim.zielesny@w-hs.de. Leiden University Leiden Netherlands. j.fraaije@chem.leidenuniv.nl. Culgi BV Berlin Germany. Physikalische Chemie III TU Dortmund 44227 Dortmund Germany. stefan.kast@tu-dortmund.de. Centre for Molecular Informatics Department of Chemistry University of Cambridge Lensfield Road Cambridge CB2 1EW United Kingdom. kcb27@cam.ac.uk. Centre for Molecular Informatics Department of Chemistry

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From the desktop to the grid: Conversion of KNIME Workflows to gUSE 5

From the desktop to the grid: Conversion of KNIME Workflows ...

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5th International Workshop on science Gateways, IWSG 2013

作者： De La Garza, Luis Krüger, Jens Schärfe, Charlotta Röttig, Marc Aiche, Stephan Reinert, Knut Kohlbacher, Oliver Applied Bioinformatics Group University of Tübingen Germany Department of Mathematics and Computer Science Freie Universität Berlin Berlin Germany International Max Planck Research School Computational Biology and Scientific Computing Berlin Germany Algorithms in Bioinformatics Freie Universität Berlin Berlin Germany

The Konstanz Information Miner is a user-friendly graphical workflow designer with a broad user base in industry and academia. Its broad range of embedded tools and its powerful data mining and visualization tools render it ideal for scientific workflows. It is thus used more and more in a broad range of applications. However, the free version typically runs on a desktop computer, restricting users if they want to tap into computing power. The grid and cloud User Support Environment is a free and open source project created for parallelized and distributed systems, but the creation of workflows with the included components has a steeper learning curve. In this work we suggest an easy to implement solution combining the ease-of-use of the Konstanz Information Miner with the computational power of distributed computing infrastructures. We present a solution permitting the conversion of workflows between the two platforms. This enables a convenient development, debugging, and maintenance of scientific workflows on the desktop. These workflows can then be deployed on a cloud or grid, thus permitting large-scale computation. To achieve our goals, we relied on a Common Tool Description XML file format which describes the execution of arbitrary programs in a structured and easily readable and parseable way. In order to integrate external programs into we employed the Generic KNIME Nodes extension.

关键词： Miners

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Interactive Visualization of Large Scale Atomistic and Cosmological Particle Simulations

Interactive Visualization of Large Scale Atomistic and Cosmo...

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IEEE Aerospace Conference

作者： Jason Kimball Mark Duchaineau Falko Kuester Department of Computer Science and Engineering University of California Center for Applied Scientific Computing Lawrence Livermore National Laboratory Department of Structural Engineering University of California

ISBN: (纸本)9781467318129

In this paper we present a method for interactive high-quality visualization of large and time-varying 3D unstructured data from particle simulations. To help design next-generation materials for aerospace systems, understanding the physics of material structures at the atomic scale is achieved through molecular dynamics simulations run on tens to hundreds of millions of atoms. Similarly, to understand the formation of the cosmos, galaxy formation simulations are run using tens to hundreds of millions of particles. From the atomically small to the astronomically large, these simulations produce immense amounts of data. While these simulations have been shown to produce excellent results matching real-world observations, the daunting Big Data that they produce can be difficult to work with. Numerical analysis is useful for processing this large quantity of data, but visual analysis is also important in the search for identifying interesting results and formulating new hypotheses to explore. Though many level-of-detail techniques exist for structured and geometric data, allowing scalable interactive visualization, unstructured particle data is not suitable for these techniques. Therefore, we have developed a new technique for scalable visualization of massive particle datasets. The technique is different from previous level-of-detail techniques which create progressive approximations of the data itself. Instead, the technique creates a volumetric representation of the data first and then creates a hierarchy of progressive approximations of the volumetric representation. An adaptive volume rendering technique is also presented that progressively refines the volume hierarchy depending on the view of the data and the time available to load data. The technique provides a scalable framework, allowing various levels of detail to be loaded while maintaining interactivity. This paper describes the rendering techniques used to produce the 3D volume hierarchy as well as the ada

关键词： Visualization Interactive simulating Social Hierarchy Particle scattering aerospace systems Molecular Dynamics Simulation particles Scalability Information retrieval systems-Teletext and videotex

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Big Data: Prospects and Challenges

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Vikalpa 2015年第1期40卷 74 - 96页

作者： Janakiraman Moorthy Rangin Lahiri Neelanjan Biswas Dipyaman Sanyal Jayanthi Ranjan Krishnadas Nanath Pulak Ghosh (Coordinator) Director and Professor of Marketing at the Institute of Management Technology Dubai. Earlier he was Professor of Marketing at the IIM Calcutta and IIM Lucknow. He received his PhD from IIM Ahmedabad. His recent research papers were published in the leading scholarly ournals such as Marketing Science British Food Journal Journal of Information Technology Case and Application Research Journal of Database Marketing & Customer Strategy Management. He has wide experience in the banking and investment industry. He was earlier the Global Research and Project Director of the Institute for Customer Relationship Management Atlanta USA. He was the Convener of the prestigious CAT Exam 2011. e-mail: Practice Director leading Atos India's CRM practice while supporting Strategic Business Development for North American Market. With an experience of more than 15 years Rangin has worked extensively as a Business Consultant in Information Technology (Sales Automation Marketing & Service Management area) Customer Data Management and CRM Analytics. e-mail: Business Consultant at Atos with extensive experience in Business Analysis Risk Management Analytics Business Development Presales Solution Ideation on Enterprise Data Management Enterprise Reference Data and Master Data Management area. e-mail: founder and CEO of dono consulting a boutique quantitative analytics and investment research firm. He has worked for leading financial firms in New York and India including Dow Jones Blackstone Sorin Capital (VP Quantitative Modeling) and Thomson Reuters (Head of Real Estate Analytics). A CFA charter holder and Commonwealth Scholar Deep has an MS (Applied Economics) from University of Texas Dallas and an MA (Economics) from Jadavpur University e-mail: Professor in the Information Systems Group of the Institute of Management Technology Ghaziabad. Her PhD is in the field of data mining from Jamia Millia Islamia Central University India. She has published five edited books. She is serving on the editorial b

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Systematic Reduction of Data Movement in Algebraic Multigrid Solvers

Systematic Reduction of Data Movement in Algebraic Multigrid...

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IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Hormozd Gahvari William Gropp Kirk E. Jordan Martin Schulz Ulrike Meier Yang Department of Computer Science University of Illinois at Urbana-Champaign Urbana IL Computational Science Center IBM TJ Watson Research Center Cambridge MA Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore CA

ISBN: (纸本)9781479913725

关键词： Switches Interpolation Computational modeling Data models Bandwidth Multicore processing Heuristic algorithms

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Towards a high productivity automatic analysis framework for classification: An initial study

Towards a high productivity automatic analysis framework for...

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13th Industrial Conference on Advances in Data Mining, ICDM 2013

作者： Ludescher, Thomas Feilhauer, Thomas Amann, Anton Brezany, Peter Fachhochschule Vorarlberg University of Applied Sciences Hochschulstrasse 1 6850 Dornbirn Austria Breath Research Institute Austrian Academy of Sciences Rathausplatz 4 A-6080 Dornbirn Austria Univ.-Clinic for Anesthesia Innsbruck Medical University Anichstr 35 A-6020 Innsbruck Austria Research Group Scientific Computing Faculty of Computer Science University of Vienna Währinger Strasse 29 A-1090 Vienna Austria

ISBN: (纸本)9783642397356

Due to the recent explosion of research data based on novel scientific instruments and corresponding experiments, automatic features, in particular in data analysis, has become more essential than ever. In this paper we present a new Automatic Analysis Framework (AAF) that is able to increase the productivity of data analysis. The AAF can be used for classifications, predictions and clustering. It is built upon the workflow engine Taverna, which is widely used in different domains and there exists a large number of Taverna activities for various kinds of analytical methods. The AAF enables scientists to modify our predefined Taverna workflow and to extend it with other available activities. For the execution of the analytical methods, in particular for the computation of the results, we use our own cloud-based Code Execution Framework (CEF). It provides web services to execute problem solving environment code, such as MATLAB, Octave, and R scripts, in parallel in the cloud. This combination of the AAF and CEF enables scientists to easily conduct time-consuming calculations without the need to manually combine potential combinations of independent variables. It furthermore automatically evaluates all identified models and provides service for the scientists conducting the analysis. The framework has been tested and evaluated with real breath gas data. © 2013 Springer-Verlag.

关键词： Web services

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Design and rationale of a quality assurance process for a scientific framework

Design and rationale of a quality assurance process for a sc...

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ICSE Workshop on Software Engineering for Computational science and Engineering, SECSE

作者： Hanna Remmel Barbara Paech Christian Engwer Peter Bastian Institute for Computer Science University of Heidelberg Heidelberg Germany Institute for Computational and Applied Mathematics University of Münster Münster Germany Interdisciplinary Centre for Scientific Computing (IWR) University of Heidelberg Heidelberg Germany

ISBN: (纸本)9781467362603

The testing of scientific frameworks is a challenging task. The special characteristics of scientific software e.g. missing test oracle, the need for high performance parallel computing, and high priority of non-functional requirements, need to be accounted for as well as the large variability in a framework. In our previous research, we have shown how software product line engineering can be applied to support the testing of scientific frameworks. We developed a process for handling the variability of a framework using software product line (SPL) variability modeling. From the variability models, we derive test applications and use them for system tests for the framework. In this paper we examine the overall quality assurance for a scientific framework. First, we propose a SPL test strategy for scientific frameworks called Variable test Application strategy for Frameworks (VAF). This test strategy tests both, commonality and variability, of the framework and supports the framework's users in testing their applications by creating reusable test artifacts. We operationalize VAF with test activities that are combined with other quality assurance activities to form the design of a quality assurance process for scientific frameworks. We introduce a list of special characteristics for scientific software that we use as rationale for the design of this process.

关键词： Testing Software Quality assurance Mathematical model Software algorithms Software engineering Parallel processing

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Abstracts from the 3rd International Genomic Medicine Conference (3rd IGMC 2015) : Jeddah, Kingdom of Saudi Arabia. 30 November - 3 December 2015

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BMC genomics 2016年第6期17 Suppl 6卷 487页

作者： Jerry W. Shay Noriko Homma Ruyun Zhou Muhammad Imran Naseer Adeel G. Chaudhary Mohammed Al-Qahtani Nobutaka Hirokawa Maryam Goudarzi Albert J. Fornace Saleh Baeesa Deema Hussain Mohammed Bangash Fahad Alghamdi Hans-Juergen Schulten Angel Carracedo Ishaq Khan Hanadi Qashqari Nawal Madkhali Mohamad Saka Kulvinder S. Saini Awatif Jamal Jaudah Al-Maghrabi Adel Abuzenadah Adeel Chaudhary Mohammed Al Qahtani Ghazi Damanhouri Heba Alkhatabi Anne Goodeve Laura Crookes Nikolas Niksic Nicholas Beauchamp Adel M. Abuzenadah Jim Vaught Bruce Budowle Mourad Assidi Abdelbaset Buhmeida Leena Merdad Sudhir Kumar Sayaka Miura Karen Gomez Mahmood Rasool Ahmed Rebai Sajjad Karim Hend F. Nour Eldin Heba Abusamra Elham M. Alhathli Nada Salem Mohammed H. Al-Qahtani Hossam Faheem Ashok Agarwa Eberhard Nieschlag Joachim Wistuba Oliver S. Damm Mohd A. Beg Taha A. Abdel-Meguid Hisham A. Mosli Osama S. Bajouh Serdar Coskun Muhammad Abu-Elmagd Ashraf Dallol Sahar Hakamy Wejdan Al-Qahtani Asia Al-Harbi Shireen Hussain Burak Ozkosem Rick DuBois Safia S. Messaoudi Maryam T. Dandana Touhami Mahjoub Wassim Y. Almawi S. Abdalla M. Nabil Al-Aama Asmaa Elzawahry Tsuyoshi Takahashi Sachiyo Mimaki Eisaku Furukawa Rie Nakatsuka Isao Kurosaka Takahiko Nishigaki Hiromi Nakamura Satoshi Serada Tetsuji Naka Seiichi Hirota Tatsuhiro Shibata Katsuya Tsuchihara Toshirou Nishida Mamoru Kato Sajid Mehmood Naeem Mahmood Ashraf Awais Asif Muhammad Bilal Malik Siddique Mehmood Aadil Hussain Qazi Mohammad Sajid Jamal Mughees Uddin Siddiqui Mohammad A. Alzohairy Mohammad A. Al Karaawi Taoufik Nedjadi Heba Al-Khattabi Adel Al-Ammari Ahmed Al-Sayyad Hédia Zitouni Nozha Raguema Marwa Ben Ali Wided Malah Raja Lfalah Wassim Almawi Mohammed Elanbari Andrey Ptitsyn Sana Mahjoub Rabeb El Ghali Bechir Achour Nidhal Ben Amor Brahim N’siri Hamid Morjani Esam Azhar Vera Chayeb Maryam Dendena Hedia Zitouni Khedija Zouari-Limayem Bassem Refaat Ahmed M. Ashshi Sarah A. Batwa Hazem Ramadan Amal Awad Ahmed Ateya Adel Galal Ahmed El-Shemi Ahmad Ashshi Mohammed Basalamah Youjin Na Cha University of Texas Southwestern Medical Center Dallas USA Department of Cell Biology and Anatomy Graduate School of Medicine the University of Tokyo Tokyo Japan Center of Excellence in Genomic Medicine Research King Abdulaziz University Jeddah Saudi Arabia Department of Biochemistry and Molecular & Cellular Biology Lombardi Comprehensive Cancer Center Georgetown University Washington USA Department of Oncology Lombardi Comprehensive Cancer Center Georgetown University Washington USA Department of Radiation Medicine Lombardi Comprehensive Cancer Center Georgetown University Washington USA Center of Excellence in Genomic Medicine Research (CEGMR) King Abdulaziz University Jeddah Kingdom of Saudi Arabia King Fahd Medical Research Centre King Abdulaziz University Jeddah Saudi Arabia Centre of Excellence in Genomic Medicine Research King Abdulaziz University Jeddah Saudi Arabia Sheffield Diagnostic Genetic Service Sheffield Children’s NHS Foundation Trust Western Bank Sheffield UK Center of Innovations in Personalized Medicine King Abdulaziz University Jeddah Saudi Arabia President ISBER Editor-in-Chief Biopreservation & Biobanking ᅟ USA Institute of Applied Genetics Department of Molecular and Medical Genetics University of North Texas Health Science Center Fort Worth USA Department of Dental Public Health Faculty of Dentistry King Abdulaziz University Jeddah Saudi Arabia Institute for Genomics and Evolutionary Medicine Temple University Philadelphia USA Center of Excellence in Genomic Medicine King Abdulaziz University Jeddah Kingdom of Saudi Arabia Laboratory of Molecular and Cellular Screening Processes (Bioinformatics Group) Centre of Biotechnology of Sfax Sfax Tunisia Fujitsu Technology Solutions International ᅟ ᅟ Case Western Reserve University School of Medicine and Lerner College of Medicine Cleveland Clinic Foundation Cleveland USA American Center for Reproductive Medicine Andrology Center Cleveland USA Center for Reproductive Medicine and

O1 Regulation of genes by telomere length over long distances Jerry W. Shay O2 The microtubule destabilizer KIF2A regulates the postnatal establishment of neuronal circuits in addition to prenatal cell survival, cell migration, and axon elongation, and its loss leading to malformation of cortical development and severe epilepsy Noriko Homma, Ruyun Zhou, Muhammad Imran Naseer, Adeel G. Chaudhary, Mohammed Al-Qahtani, Nobutaka Hirokawa O3 Integration of metagenomics and metabolomics in gut microbiome research Maryam Goudarzi, Albert J. Fornace Jr. O4 A unique integrated system to discern pathogenesis of central nervous system tumors Saleh Baeesa, Deema Hussain, Mohammed Bangash, Fahad Alghamdi, Hans-Juergen Schulten, Angel Carracedo, Ishaq Khan, Hanadi Qashqari, Nawal Madkhali, Mohamad Saka, Kulvinder S. Saini, Awatif Jamal, Jaudah Al-Maghrabi, Adel Abuzenadah, Adeel Chaudhary, Mohammed Al Qahtani, Ghazi Damanhouri O5 RPL27A is a target of miR-595 and deficiency contributes to ribosomal dysgenesis Heba Alkhatabi O6 Next generation DNA sequencing panels for haemostatic and platelet disorders and for Fanconi anaemia in routine diagnostic service Anne Goodeve, Laura Crookes, Nikolas Niksic, Nicholas Beauchamp O7 Targeted sequencing panels and their utilization in personalized medicine Adel M. Abuzenadah O8 International biobanking in the era of precision medicine Jim Vaught O9 Biobank and biodata for clinical and forensic applications Bruce Budowle, Mourad Assidi, Abdelbaset Buhmeida O10 Tissue microarray technique: a powerful adjunct tool for molecular profiling of solid tumors Jaudah Al-Maghrabi O11 The CEGMR biobanking unit: achievements, challenges and future plans Abdelbaset Buhmeida, Mourad Assidi, Leena Merdad O12 Phylomedicine of tumors Sudhir Kumar, Sayaka Miura, Karen Gomez O13 Clinical implementation of pharmacogenomics for colorectal cancer treatment Angel Carracedo, Mahmood Rasool O14 From association to causality: translation of GWAS findings for genomic me

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Scaling Techniques for Massive Scale-Free Graphs in Distributed (External) Memory

Scaling Techniques for Massive Scale-Free Graphs in Distribu...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Roger Pearce Maya Gokhale Nancy M. Amato Texas A&M University College Station College Station TX US Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore CA USA Parasol Laboratory Department of Computer Science and Engineering Texas A&M University College Station TX USA

ISBN: (纸本)9781467360661

We present techniques to process large scale-free graphs in distributed memory. Our aim is to scale to trillions of edges, and our research is targeted at leadership class supercomputers and clusters with local non-volatile memory, e.g., NAND Flash. We apply an edge list partitioning technique, designed to accommodate high-degree vertices (hubs) that create scaling challenges when processing scale-free graphs. In addition to partitioning hubs, we use ghost vertices to represent the hubs to reduce communication hotspots. We present a scaling study with three important graph algorithms: Breadth-First Search (BFS), K-Core decomposition, and Triangle Counting. We also demonstrate scalability on BG/P Intrepid by comparing to best known Graph500 results [1]. We show results on two clusters with local NVRAM storage that are capable of traversing trillion-edge scale-free graphs. By leveraging node-local NAND Flash, our approach can process thirty-two times larger datasets with only a 39% performance degradation in Traversed Edges Per Second (TEPS).

关键词： Nonvolatile memory Random access memory Partitioning algorithms Algorithm design and analysis Routing Heuristic algorithms Topology

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