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      Large-Scale Computing Techniques for Complex System Simulations

      AvWerner Dubitzky,Krzysztof Kurowski

      Inbunden, Engelska, 2011

      Del 80 i serien Wiley Series on Parallel and Distributed Computing

      1 362 kr

      Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

      Beskrivning

      Complex systems modeling and simulation approaches are being adopted in a growing number of sectors, including finance, economics, biology, astronomy, and many more. Technologies ranging from distributed computing to specialized hardware are explored and developed to address the computational requirements arising in complex systems simulations. The aim of this book is to present a representative overview of contemporary large-scale computing technologies in the context of complex systems simulations applications. The intention is to identify new research directions in this field and to provide a communications platform facilitating an exchange of concepts, ideas and needs between the scientists and technologist and complex system modelers. On the application side, the book focuses on modeling and simulation of natural and man-made complex systems. On the computing technology side, emphasis is placed on the distributed computing approaches, but supercomputing and other novel technologies are also considered.

      Produktinformation

      • Utgivningsdatum:2011-12-23
      • Mått:163 x 243 x 17 mm
      • Vikt:458 g
      • Format:Inbunden
      • Språk:Engelska
      • Serie:Wiley Series on Parallel and Distributed Computing
      • Antal sidor:220
      • Förlag:John Wiley & Sons Inc
      • ISBN:9780470592441

      Utforska kategorier

      • Elektronik och kommunikationer inom Naturvetenskap och teknik

      Mer om författaren

      Werner Dubitzky, PhD, is Chair of Bioinformatics at the Biomedical Sciences Research Institute in the Faculty of Life and Health Sciences at the University of Ulster. His research investigates systems biology, knowledge management in biology, grid computing, and data mining. Krzysztof Kurowski, PhD, leads the Applications Department at Poznan Supercomputing and Networking Center in Poland. His research is focused on the modeling of advanced applications, scheduling, and resource management in networked environments.Bernhard Schott, Dipl. Phys., is the EU-Research Program Manager for Platform Computing GmbH.

      Innehållsförteckning

      • Foreword xi Preface xvContributors xix1. State-of-the-Art Technologies for Large-Scale Computing 1Florian Feldhaus, Stefan Freitag, and Chaker El Amrani1.1 Introduction 11.2 Grid Computing 21.3 Virtualization 61.4 Cloud Computing 81.5 Grid and Cloud: Two Complementary Technologies 121.6 Modeling and Simulation of Grid and Cloud Computing 131.7 Summary and Outlook 15References 162. The e-Infrastructure Ecosystems: Providing Local Support to Global Science 19Erwin Laure and Åke Edlund2.1 The Worldwide e-Infrastructure Landscape 192.2 BalticGrid: A Regional e-Infrastructure, Leveraging on the Global “Mothership” EGEE 212.3 The EGEE Infrastructure 252.4 Industry and e-Infrastructures: The Baltic Example 292.5 The Future of European e-Infrastructures: The European Grid Initiative (EGI) and the Partnership for Advanced Computing in Europe (PRACE) Infrastructures 312.6 Summary 33Acknowledgments 34References 343. Accelerated Many-Core GPU Computing for Physics and Astrophysics on Three Continents 35Rainer Spurzem, Peter Berczik, Ingo Berentzen, Wei Ge, Xiaowei Wang, Hsi-Yu Schive, Keigo Nitadori, Tsuyoshi Hamada, and José Fiestas3.1 Introduction 363.2 Astrophysical Application for Star Clusters and Galactic Nuclei 383.3 Hardware 403.4 Software 413.5 Results of Benchmarks 423.6 Adaptive Mesh Refinement Hydrosimulations 493.7 Physical Multiscale Discrete Simulation at IPE 493.8 Discussion and Conclusions 53Acknowledgments 54References 544. An Overview of the SimWorld Agent-Based Grid Experimentation Systems 59Matthew Scheutz and Jack J. Harris4.1 Introduction 594.2 System Architecture 624.3 System Implementation 674.4 A SWAGES Case Study 714.5 Discussion 744.6 Conclusions 78References 785. Repast HPC: A Platform for Large-Scale Agent-Based Modeling 81Nicholson Collier and Michael North5.1 Introduction 815.2 Agent Simulation 825.3 Motivation and Related Work 825.4 From Repast S to Repast HPC 905.5 Parallelism 925.6 Implementation 945.7 Example Application: Rumor Spreading 1015.8 Summary and Future Work 107References 1076. Building and Running Collaborative Distributed Multiscale Applications 111Katarzyna Rycerz and Marian Bubak6.1 Introduction 1116.2 Requirements of Multiscale Simulations 1126.3 Available Technologies 1166.4 An Environment Supporting the HLA Component Model 1196.5 Case Study with the MUSE Application 1246.6 Summary and Future Work 127Acknowledgments 128References 1297. Large-Scale Data-Intensive Computing 131Mark Parsons7.1 Digital Data: Challenge and Opportunity 1317.2 Data-Intensive Computers 1327.3 Advanced Software Tools and Techniques 1347.4 Conclusion 139Acknowledgments 139References 1398. A Topolpgy-Aware Evolutionary Algorithm for Reverse-Engineering Gene Regulatory Networks 141Martin Swain, Camille Coti, Johannes Mandel, and Werner Dubitzky8.1 Introduction 1418.2 Methodology 1438.3 Results and Discussion 1558.4 Conclusions 160Acknowledgments 161References 1619. QosCosGrid e-Science Infrastructure for Large-Scale Complex System Simulations 163Krzysztof Kurowski, Bartosz Bosak, Piotr Grabowski, Mariusz Mamonski, Tomasz Piontek, George Kampis, László Gulyás, Camille Coti, Thomas Herault, and Franck Cappello9.1 Introduction 1639.2 Distributed and Parallel Simulations 1659.3 Programming and Execution Environments 1689.4 QCG Middleware 1749.5 Additional QCG Tools 1799.6 QosCosGrid Science Gateways 1809.7 Discussion and Related Work 182References 184Glossary 187Index 195
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