{"product_id":"high-performance-computing-paradigm-and-infrastructure-hardback-9780471654711","title":"High-Performance Computing; Paradigm and Infrastructure (Hardback) 9780471654711","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eHigh-Performance Computing\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eParadigm and Infrastructure\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eLaurence T. Yang (Author), Minyi Guo (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780471654711, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 2 December 2005\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e816 pages, Drawings: 100 B\u0026amp;W, 0 Color\u003cbr\u003e23.8 x 16.2 x 4.2 cm, 1.214 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cem\u003e\u003cfont size=\"3\"\u003e\"In this book, the reader will obtain a bird's-eye view on the diversity of problems and approaches in the field of HPC.\" (\u003ci\u003eComputing Reviews.com\u003c\/i\u003e, August 24, 2006)\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eThe state of the art of high-performance computing\u003cbr\u003e \u003cbr\u003e Prominent researchers from around the world have gathered to present the state-of-the-art techniques and innovations in high-performance computing (HPC), including:\u003cbr\u003e * Programming models for parallel computing: graph-oriented programming (GOP), OpenMP, the stages and transformation (SAT) approach, the bulk-synchronous parallel (BSP) model, Message Passing Interface (MPI), and Cilk\u003cbr\u003e * Architectural and system support, featuring the code tiling compiler technique, the MigThread application-level migration and checkpointing package, the new prefetching scheme of atomicity, a new \"receiver makes right\" data conversion method, and lessons learned from applying reconfigurable computing to HPC\u003cbr\u003e * Scheduling and resource management issues with heterogeneous systems, bus saturation effects on SMPs, genetic algorithms for distributed computing, and novel task-scheduling algorithms\u003cbr\u003e * Clusters and grid computing: design requirements, grid middleware, distributed virtual machines, data grid services and performance-boosting techniques, security issues, and open issues\u003cbr\u003e * Peer-to-peer computing (P2P) including the proposed search mechanism of hybrid periodical flooding (HPF) and routing protocols for improved routing performance\u003cbr\u003e * Wireless and mobile computing, featuring discussions of implementing the Gateway Location Register (GLR) concept in 3G cellular networks, maximizing network longevity, and comparisons of QoS-aware scatternet scheduling algorithms\u003cbr\u003e * High-performance applications including partitioners, running Bag-of-Tasks applications on grids, using low-cost clusters to meet high-demand applications, and advanced convergent architectures and protocols\u003cbr\u003e \u003cbr\u003e High-Performance Computing: Paradigm and Infrastructure is an invaluable compendium for engineers, IT professionals, and researchers and students of computer science and applied mathematics.\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003ePreface.  \u003cp\u003e\u003c\/p\u003e Contributors.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003ePART 1. PROGRAMMING MODEL.\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e1. ClusterGOP: A High-Level Programming Environment for Clusters (Fan Chan, Jiannong Cao and Minyi Guo).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 1.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 1.2 GOP Model and ClusterGOP Architecture.  \u003cp\u003e\u003c\/p\u003e 1.3 VisualGOP.  \u003cp\u003e\u003c\/p\u003e 1.4 The ClusterGOP Library.  \u003cp\u003e\u003c\/p\u003e 1.5 MPMD Programming Support.  \u003cp\u003e\u003c\/p\u003e 1.6 Programming Using ClusterGOP.  \u003cp\u003e\u003c\/p\u003e 1.7 Summary.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e2. The Challenge of Providing A High-Level Programming Model for High-Performance Computing (Barbara Chapman).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 2.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 2.2 HPC Architectures.  \u003cp\u003e\u003c\/p\u003e 2.3 HPC Programming Models: The First Generation.  \u003cp\u003e\u003c\/p\u003e 2.4 The Second generation of HPC Programming Models.  \u003cp\u003e\u003c\/p\u003e 2.5 OpenMP for DMPs.  \u003cp\u003e\u003c\/p\u003e 2.6 Experiments with OpenMP on DMPs.  \u003cp\u003e\u003c\/p\u003e 2.7 Conclusions.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e3. SAT: Toward Structured Parallelism Using Skeletons (Sergei Gorlatch).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 3.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 3.2 SAT: A Methodology Outline.  \u003cp\u003e\u003c\/p\u003e 3.3 Skeletons and Collective Operations.  \u003cp\u003e\u003c\/p\u003e 3.4 Case Study: Maximum Segment SUM (MSS).  \u003cp\u003e\u003c\/p\u003e 3.5 Performance Aspect in SAT.  \u003cp\u003e\u003c\/p\u003e 3.6 Conclusions and Related Work.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e4. Bulk-Synchronous Parallelism: An Emerging Paradigm of High-Performance Computing (Alexander Tiskin).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 4.1 The BSP Model.  \u003cp\u003e\u003c\/p\u003e 4.2 BSP Programming.  \u003cp\u003e\u003c\/p\u003e 4.3 Conclusions.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e5. Cilk Versus MPI: Comparing Two Parallel Programming Styles on Heterogenous Systems (John Morris, KyuHo Lee and JunSeong Kim).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 5.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 5.2 Experiments.  \u003cp\u003e\u003c\/p\u003e 5.3 Results.  \u003cp\u003e\u003c\/p\u003e 5.4 Conclusion.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e6. Nested Parallelism and Pipelining in OpenMP (Marc Gonzalez, E. Ayguade, X. Martorell and J. Labarta).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 6.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 6.2 OpenMP Extensions for Nested Parallelism.  \u003cp\u003e\u003c\/p\u003e 6.3 OpenMP Extensions for Thread Synchronization.  \u003cp\u003e\u003c\/p\u003e 6.4 Summary.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e7. OpenMP for Chip Multiprocessors (Feng Liu and Vipin Chaudhary).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 7.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 7.2 3SoC Architecture Overview.  \u003cp\u003e\u003c\/p\u003e 7.3 The OpenMP Conpiler\/Translator.  \u003cp\u003e\u003c\/p\u003e 7.4 Extensions to OpenMP for DSEs.  \u003cp\u003e\u003c\/p\u003e 7.5 Optimization for OpenMP.  \u003cp\u003e\u003c\/p\u003e 7.6 Implementation.  \u003cp\u003e\u003c\/p\u003e 7.7 Performance Evaluation.  \u003cp\u003e\u003c\/p\u003e 7.8 Conclusions.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003ePART 2. ARCHITECTURAL AND SYSTEM SUPPORT.\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e8. Compiler and Run-Time Parallelization Techniques for Scientific Computations on Distributed-Memory Parallel Computers (PeiZong Lee, Cheien-Min Wang and Jan-Jan Wu).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 8.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 8.2 Background Material.  \u003cp\u003e\u003c\/p\u003e 8.3 Compiling Regular Programs on DMPCs.  \u003cp\u003e\u003c\/p\u003e 8.4 Compiler and Run-Time Support for Irregular Programs.  \u003cp\u003e\u003c\/p\u003e 8.5 Library Support for Irregular Applications.  \u003cp\u003e\u003c\/p\u003e 8.6 Related Works.  \u003cp\u003e\u003c\/p\u003e 8.7 Concluding Remarks.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e9. Enabling Partial-Cache Line Prefetching Through Data Compression (Youtao Zhang and Rajiv Gupta).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 9.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 9.2 Motivation of Partial Cache-Line Perfetching.  \u003cp\u003e\u003c\/p\u003e 9.3 Cache Design Details.  \u003cp\u003e\u003c\/p\u003e 9.4 Experimental Results.  \u003cp\u003e\u003c\/p\u003e 9.5 Related Work.  \u003cp\u003e\u003c\/p\u003e 9.6 Conclusion.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e10. MPI Atomicity and Concurrent Overlapping I\/O (Wei-Keng Liao, Alok Choudhary, Kenin Coloma, Lee Ward, Eric Russell and Neil Pundit).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 10.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 10.2 Concurrent Overlapping I\/O.  \u003cp\u003e\u003c\/p\u003e 10.3 Implementation Strategies.  \u003cp\u003e\u003c\/p\u003e 10.4 Experiment Results.  \u003cp\u003e\u003c\/p\u003e 10.5 Summary.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e11. Code Tiling: One Size Fits All (Jingling Xue and Qingguang Huang).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 11.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 11.2 Cache Model.  \u003cp\u003e\u003c\/p\u003e 11.3 Code Tiling.  \u003cp\u003e\u003c\/p\u003e 11.4 Data Tiling.  \u003cp\u003e\u003c\/p\u003e 11.5 Finding Optimal Tile Sizes.  \u003cp\u003e\u003c\/p\u003e 11.6 Experimental Results.  \u003cp\u003e\u003c\/p\u003e 11.7 Related Work.  \u003cp\u003e\u003c\/p\u003e 11.8 Conclusion.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e12. Data Conversion for Heterogeneous Migration\/Checkpointing (Hai Jiang, Vipin Chaudhary and John Paul Walters).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 12.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 12.2 Migration and Checkpointing.  \u003cp\u003e\u003c\/p\u003e 12.3 Data Conversion.  \u003cp\u003e\u003c\/p\u003e 12.4 Coarse-Grain Tagged RMR in MigThread.  \u003cp\u003e\u003c\/p\u003e 12.5 Microbenchmarks and Experiments.  \u003cp\u003e\u003c\/p\u003e 12.6 Related Work.  \u003cp\u003e\u003c\/p\u003e 12.7 Conclusions and Future Work.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e13. Receiving-Message Prediction and Its Speculative Execution (Takanobu Baba, Takashi Yokota, Kamemitsu Ootsu, Fumihitto Furukawa and Yoshiyuki Iwamoto).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 13.1 Background.  \u003cp\u003e\u003c\/p\u003e 13.2 Receiving-Message Prediction Method.  \u003cp\u003e\u003c\/p\u003e 13.3 Implementation of the Method in the MIPI Libraries.  \u003cp\u003e\u003c\/p\u003e 13.4 Experimental Results.  \u003cp\u003e\u003c\/p\u003e 13.5 Conclusing Remarks.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e14. An Investigation of the Applicability of Distributed FPGAs to High-Performance Computing (John P. Morrison, Padraig O’Dowd and Philip D. Healy).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 14.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 14.2 High Performance Computing with Cluster Computing.  \u003cp\u003e\u003c\/p\u003e 14.3 Reconfigurable Computing with EPGAs.  \u003cp\u003e\u003c\/p\u003e 14.4 DRMC: A Distributed Reconfigurable Metacomputer.  \u003cp\u003e\u003c\/p\u003e 14.5 Algorithms Suited to the Implementation on FPGAs\/DRMC.  \u003cp\u003e\u003c\/p\u003e 14.6 Algorithms Not Suited to the Implementation on FPGAs\/DRMC.  \u003cp\u003e\u003c\/p\u003e 14.7 Summary.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003ePART 3. SCHEDULING AND RESOURCE MANAGEMENT.\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e15. Bandwidth-Aware Resource Allocation for Heterogeneous Computing Systems to Maximize Throughput (Bo Hong and Viktor K. Prasanna).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 15.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 15.2 Related Work.  \u003cp\u003e\u003c\/p\u003e 15.3 Systems Model and Problem Statement.  \u003cp\u003e\u003c\/p\u003e 15.4 Resource Allocation to Maximize System Throughput.  \u003cp\u003e\u003c\/p\u003e 15.5 Experimental Results.  \u003cp\u003e\u003c\/p\u003e 15.6 Conclusion.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e16. Scheduling Algorithms with Bus Bandwidth Considerations for SMPs (Christos D. Antonopoulos, Dimitrios S., Nikolopoulos and Theeodore S. Papatheodorou).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 16.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 16.2 Related Work.  \u003cp\u003e\u003c\/p\u003e 16.3 The Implications of Bus Bandwidth for Application Performance.  \u003cp\u003e\u003c\/p\u003e 16.4 Scheduling Policies for Preserving Bus Bandwidth.  \u003cp\u003e\u003c\/p\u003e 16.5 Experimental Evaluation.  \u003cp\u003e\u003c\/p\u003e 16.6 Conclusions.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e17. Toward Performance Guarantee of Dynamic Task Scheduling of a Parameter-Sweep Application onto a Computational Grid (Noriyuki Fujimoto and Kenichi Hagihara).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 17.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 17.2 A Grid Scheduling Model.  \u003cp\u003e\u003c\/p\u003e 17.3 Related Works.  \u003cp\u003e\u003c\/p\u003e 17.4 The Proposed Algorithm RR.  \u003cp\u003e\u003c\/p\u003e 17.5 The Performance Guarantee of the Proposed Algorithm.  \u003cp\u003e\u003c\/p\u003e 17.6 Conclusion.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e18. Performance Study of Reliability Maximization and Turnaround Minimization with GA-based Task Allocation in DCS (Deo Prakash Vidyarthi, Anil Kumar Tripathi, Biplab Kumer Sarker, Kirti Rani and Laurence T. Yang).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 18.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 18.2 GA for Task Allocation.  \u003cp\u003e\u003c\/p\u003e 18.3 The Algorithm.  \u003cp\u003e\u003c\/p\u003e 18.4 Illustrative Examples.  \u003cp\u003e\u003c\/p\u003e 18.5 Discussions and Conclusion.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e19. Toward Fast and Efficient Compile-Time Task Scheduling in Heterogeneous Computing Systems (Tarek Hagras and Jan Janecek).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 19.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 19.2 Problem Definition.  \u003cp\u003e\u003c\/p\u003e 19.3 The Suggested Algorithm.  \u003cp\u003e\u003c\/p\u003e 19.4 Heterogeneous Systems Scheduling Heuristics.  \u003cp\u003e\u003c\/p\u003e 19.5 Experimental Results and Discussion.  \u003cp\u003e\u003c\/p\u003e 19.6 Conclusion.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e20. An On-Line Approach for Classifying and Extracting Application Behavior on Linux (Luciano José Senger, Rodrigo Fernandes de Mello, Marcos José Santana, Regina Helena Carlucci Santana and Laurence Tianruo Yang).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 20.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 20.2 Related Work.  \u003cp\u003e\u003c\/p\u003e 20.3 Information Acquisition.  \u003cp\u003e\u003c\/p\u003e 20.4 Linux Process Classification Model.  \u003cp\u003e\u003c\/p\u003e 20.5 Results.  \u003cp\u003e\u003c\/p\u003e 20.6 Evaluation of The Model Intrusion on the System Performance.  \u003cp\u003e\u003c\/p\u003e 20.7 Conclusions.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003ePART 4. CLUSTERS AND GRID COMPUTING.\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e21. Peer-to-Peer Grid Computing and a .NET-Based Alchemi Framework (Akshay Luther, Rajkumar Buyya, Rajiv Ranjan and Srikumar Venugopal).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 21.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 21.2 Background.  \u003cp\u003e\u003c\/p\u003e 21.3 Desktop Grid Middleware Considerations.  \u003cp\u003e\u003c\/p\u003e 21.4 Representation Desktop Grid Systems.  \u003cp\u003e\u003c\/p\u003e 21.5 Alchemi Desktop Grid Framework.  \u003cp\u003e\u003c\/p\u003e 21.6 Alchemi Design and Implementation.  \u003cp\u003e\u003c\/p\u003e 21.7 Alchemi Performance Evaluation.  \u003cp\u003e\u003c\/p\u003e 21.8 Summary and Future Work.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e22. Global Grids and Software Toolkits: A Study of Four Grid Middleware Technologies (Parvin Asadzadeh, Rajkumar Buyya, Chun Ling Kei, Deepa Nayar and Srikumar Venugopal).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 22.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 22.2 Overview of Grid Middleware Systems.  \u003cp\u003e\u003c\/p\u003e 22.3 Unicore.  \u003cp\u003e\u003c\/p\u003e 22.4 Globus.  \u003cp\u003e\u003c\/p\u003e 22.5 Legion.  \u003cp\u003e\u003c\/p\u003e 22.6 Gridbus.  \u003cp\u003e\u003c\/p\u003e 22.7 Implementation of UNICORE Adaptor for Gridbus Broker.  \u003cp\u003e\u003c\/p\u003e 22.8 Comparison of Middleware Systems.  \u003cp\u003e\u003c\/p\u003e 22.9 Summary.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e23. High-Performance Computing on Clusters: The Distributed JVM Approach (Wenzhang Zhu, Weijian Fang, Cho-Li Wang and Francis C. M. Lau).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 23.1 Background.  \u003cp\u003e\u003c\/p\u003e 23.2 Distributed JVM.  \u003cp\u003e\u003c\/p\u003e 23.3 JESSICA2 Distributed JVM.  \u003cp\u003e\u003c\/p\u003e 23.4 Performance Analysis.  \u003cp\u003e\u003c\/p\u003e 23.5 Related Work.  \u003cp\u003e\u003c\/p\u003e 23.6 Summary.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e24. Data Grids: Supporting Data-Intensive Applications in Wide-Area Networks (Xiao Qin and Hong Jiang).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 24.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 24.2 Data Grid Services.  \u003cp\u003e\u003c\/p\u003e 24.3 High-Performance Data Grid.  \u003cp\u003e\u003c\/p\u003e 24.4 Security Issues.  \u003cp\u003e\u003c\/p\u003e 24.5 Open Issues.  \u003cp\u003e\u003c\/p\u003e 24.6 Conclusions.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e25. Application I\/O on a Parallel File System for Linux Clusters (Dheeraj Bhaardwaj).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 25.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 25.2 Application I\/O.  \u003cp\u003e\u003c\/p\u003e 25.3 Parallel I\/O System Software.  \u003cp\u003e\u003c\/p\u003e 25.4 Standard Unix \u0026amp; Parallel I\/O.  \u003cp\u003e\u003c\/p\u003e 25.5 Example: Seismic Imaging.  \u003cp\u003e\u003c\/p\u003e 25.6 Discussion and Conclusion.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e26. One Teraflop Achieved with a Geographically Distributed Linux Cluster (Peng Wang, George Turner, Steven Simms, Dave Hart, Mary Papakhiam and Craig Stewart).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 26.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 26.2 Hardware and Software Setup.  \u003cp\u003e\u003c\/p\u003e 26.3 System Tuning and Benchmark Results.  \u003cp\u003e\u003c\/p\u003e 26.4 Performance Costs and Benefits.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e27. A Grid-Based Distributed Simulation of Plasma Turbulence (Beniamino Di Martino, Salvatore Venticinque, Sergio Criguglio, Giulana Fogaccia and Gregorio Vlad).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 27.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 27.2 MPI Implementation of The Internode Domain Decomposition.  \u003cp\u003e\u003c\/p\u003e 27.3 Integration of The Internode Domain Decomposition with Intranode Particle Decomposition Strategies.  \u003cp\u003e\u003c\/p\u003e 27.4 The MPICH-G2 Implementation.  \u003cp\u003e\u003c\/p\u003e 27.5 Conclusions.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e28. Evidence-Aware Trust Model for Dynamic Services (Ali Shaikh Ali, Omer F. Rana and Rashid J. Al-Ali).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 28.1 Motivation For Evaluating Trust.  \u003cp\u003e\u003c\/p\u003e 28.2 Service Trust—What Is It?  \u003cp\u003e\u003c\/p\u003e 28.3 Evidence-Aware Trust Model.  \u003cp\u003e\u003c\/p\u003e 28.4 The System Life Cycle.  \u003cp\u003e\u003c\/p\u003e 28.5 Conclusion.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003ePART 5. PEER-TO-PEER COMPUTING.\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e29. Resource Discovery in Peer-to-Peer Infrastructures (Huang-Chang Hsiao and Chung-Ta King).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 29.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 29.2 Design Requirements.  \u003cp\u003e\u003c\/p\u003e 29.3 Unstructured P2P Systems 4.  \u003cp\u003e\u003c\/p\u003e 29.4 Structured P2P Systems.  \u003cp\u003e\u003c\/p\u003e 29.5 Advanced Resource Discovery for Structured P2P Systems.  \u003cp\u003e\u003c\/p\u003e 29.6 Summary.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e30. Hybrid Periodical Flooding in Unstructured Peer-to-Peer Networks (Yunhao Liu, Li Xiao, Lionel M. Ni and Zhenyun Zhuang).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 30.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 30.2 Serarch Mechanisms.  \u003cp\u003e\u003c\/p\u003e 30.3 Hybrid Periodical Flooding.  \u003cp\u003e\u003c\/p\u003e 30.4 Simulation Methodology.  \u003cp\u003e\u003c\/p\u003e 30.5 Performance Evaluation.  \u003cp\u003e\u003c\/p\u003e 30.6 Conclusion.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e31. HIERAS: A DHT-Based Hierarchical P2P Routing Algorithm (Zhiyong Xu, Yiming Hu and Laxmi Bhuyan).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 31.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 31.2 Hierarchical P2P Architecture.  \u003cp\u003e\u003c\/p\u003e 31.3 System Design.  \u003cp\u003e\u003c\/p\u003e 31.4 Performance Evaluation.  \u003cp\u003e\u003c\/p\u003e 31.5 Related Works.  \u003cp\u003e\u003c\/p\u003e 31.6 Summary.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e32. Flexible and Scalable Group Communication Model for Peer-to-Peer Systems (Tomoya Enokido and Makoto Takizawa).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 32.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 32.2 Group of Agents.  \u003cp\u003e\u003c\/p\u003e 32.3 Functions of Group Protocol.  \u003cp\u003e\u003c\/p\u003e 32.4 Autonomic Group Protocol.  \u003cp\u003e\u003c\/p\u003e 32.5 Retransmission.  \u003cp\u003e\u003c\/p\u003e 32.6 Conclusion.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003ePART 6. WIRELESS AND \u003cst1:place w:st=\"on\"\u003eMOBILE\u003c\/st1:place\u003e COMPUTING.\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e33. Study of Cache-Enhanced Dynamic Movement-Based Location Management Schemes for 3G Cellular Networks (Krishna Priya Patury, Yi Pan, Xiaola Lin, Yang Xiao and Jie Li).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 33. 1 Introduction.  \u003cp\u003e\u003c\/p\u003e 33.2 Location Management with and without Cache.  \u003cp\u003e\u003c\/p\u003e 33.3 The Cache-Enhanced Location Management Scheme.  \u003cp\u003e\u003c\/p\u003e 33.4 Simulation Results and Analysis.  \u003cp\u003e\u003c\/p\u003e 33.5 Conclusion.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e34. Maximizing Multicast Lifetime in Wireless Ad Hoc Networks (Guofeng Deng and Sandeep K. S. Gupta).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 34.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 34.2 Energy Consumption Model In WANETs.  \u003cp\u003e\u003c\/p\u003e 34.3 Definitions of Maximum Multicast Lifetime.  \u003cp\u003e\u003c\/p\u003e 34.4 Maximum Multicast Lifetime of The Network Using Single Tree (MMLM).  \u003cp\u003e\u003c\/p\u003e 34.5 Maximum Multicast Lifetime of The Network Using Multiple Trees (MMLM).  \u003cp\u003e\u003c\/p\u003e 34.6 Summary.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e35. A QoS-Aware Scheduling Algorithm for Bluetooth Scatternets (Young Man Kim, Ten H. Lai and Anish Arora).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 35.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 35.2 Perfect Scheduling Problem for Bipartite Scatternet.  \u003cp\u003e\u003c\/p\u003e 35.3 Perfect Assignment Scheduling Algorithm for Bipartite Scatternets.  \u003cp\u003e\u003c\/p\u003e 35.4 Distributed, Local, and Incremental Scheduling Algorithms.  \u003cp\u003e\u003c\/p\u003e 35.5 Performance and QOS Analysis.  \u003cp\u003e\u003c\/p\u003e 35.6 Conclusion.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003ePART 7. HIGH PERFORMANCE APPLICATIONS.\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e36. A Workload Partitioner for Heterogeneous Grids (Daniel J. Harvey, Sajal K. Das and Rupak Biswas).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 36.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 36.2 Preliminaries.  \u003cp\u003e\u003c\/p\u003e 36.3 The MinEX Partitioner.  \u003cp\u003e\u003c\/p\u003e 36.4 N-Body Application.  \u003cp\u003e\u003c\/p\u003e 36.5 Experimental Study.  \u003cp\u003e\u003c\/p\u003e 36.6 Conclusion.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e37. Building a User-Level Grid for Bag-of-Tasks Applications (Walfredo Cirne, Francisco Brasileiro, Daniel Paranhos, Lauro Costa, Elizeu Santos-Neto and Carla Osthoff).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 37.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 37.2 Design Goals.  \u003cp\u003e\u003c\/p\u003e 37.3 Architecture.  \u003cp\u003e\u003c\/p\u003e 37.4 Working Environment.  \u003cp\u003e\u003c\/p\u003e 37.5 Scheduling.  \u003cp\u003e\u003c\/p\u003e 37.6 Implementation.  \u003cp\u003e\u003c\/p\u003e 37.7 Performance Evaluation.  \u003cp\u003e\u003c\/p\u003e 37.8 Conclusions and Future Work.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e38. An Efficient Parallel Method for Calculating the Smarandache Function (Sabin Tabirca, Tatiana Tabirca, Kieran Reynolds and Laurence T. Yang).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 38.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 38.2 Computing in Parallel.  \u003cp\u003e\u003c\/p\u003e 38.3 Experimental Results.  \u003cp\u003e\u003c\/p\u003e 38.4 Conclusion.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e39. Design, Implementation and Deployment of a Commodity Cluster for Peirodic Comparison of Gene Sequences (Anita M. Orendt, Brian Haymore, David Richardson, Sofia Robb, Alejandro Sanchez Alvarado and Julio C. Facelli).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 39.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 39.2 System Requirements and Design.  \u003cp\u003e\u003c\/p\u003e 39.3 Performance.  \u003cp\u003e\u003c\/p\u003e 39.4 Conclusions.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e40. A Hierarchical Distributed Shared-Memory Parallel Branch \u0026amp; Bound Application with PVM and OpenMP on Multiprocessor Clusters (Rocco Aversa, Beniamino Di Martino, Nicola Mazzocca and Salvatore Venticinque).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 40.1 Introduction.  \u003cp\u003e\u003c\/p\u003e 40.2 The B\u0026amp;B Parallel Application.  \u003cp\u003e\u003c\/p\u003e 40.3 The OpenMP Extension.  \u003cp\u003e\u003c\/p\u003e 40.4 Experimental Results.  \u003cp\u003e\u003c\/p\u003e 40.5 Conclusions.  \u003cp\u003e\u003c\/p\u003e \u003cb\u003e41. IP Based Telecommunication Services (Anna Bonifacio and G. Spinillo).\u003c\/b\u003e  \u003cp\u003e\u003c\/p\u003e 41.1 Introduction.  \u003cp\u003e\u003c\/p\u003e Index.\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Electronics \u0026amp; communications engineering [\u003ca title=\"See our other books on Electronics \u0026amp; communications engineering\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Electronics%20\u0026amp;%20communications%20engineering%20%5BTJ%5D%22\"\u003eTJ\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Interscience","offers":[{"title":"Brand New","offer_id":52298022912280,"sku":"9780471654711","price":146.39,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9780471654711.jpg?v=1781731292","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/high-performance-computing-paradigm-and-infrastructure-hardback-9780471654711","provider":"Freshly Printed Books","version":"1.0","type":"link"}