High-Performance Computing

This book presents the most recent advances in parallel and distributed computing from experts in the field. Serves as a unique format for professionals to present, discuss, and exchange their recent advances, new ideas, results, works-in-progress, and experiences in the areas of parallel and distributed computing for science and engineering applications. All chapters written with introduction, detailed background, and in-depth discussion.

Informationen zum Autor LAURENCE T. YANG is a Professor of Computer Science, St. Francis Xavier University, Canada. Dr. Yang served as the vice chair of IEEE Technical Committee of Supercomputing Applications (TCSA) until 2004 and as an executive committee member of the IEEE Technical Committee of Scalable Computing (TCSC) since 2004. Dr. Yang has also received many awards, including the Distinguished Contribution Award, 2004; Technical Achievement Award, 2004; Outstanding Achievement Award, 2002, University Research/Publication/Teaching Award, 2000?2001/2002?2003/2003?2004, and Canada Foundation for Innovation (CFI) Award, 2003. MINYI GUO received his PhD from the University of Tsukuba, Japan. He is currently an Associate Professor in the Department of Computer Software at the University of Aizu, Japan. In addition, Dr. Guo is Editor in Chief of the International Journal of Embedded Systems, and has written and edited books in the area of parallel and distributed computing, as well as embedded and ubiquitous computing. Klappentext The state of the art of high-performance computingProminent researchers from around the world have gathered to present the state-of-the-art techniques and innovations in high-performance computing (HPC), including: 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 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 Scheduling and resource management issues with heterogeneous systems, bus saturation effects on SMPs, genetic algorithms for distributed computing, and novel task-scheduling algorithms Clusters and grid computing: design requirements, grid middleware, distributed virtual machines, data grid services and performance-boosting techniques, security issues, and open issues Peer-to-peer computing (P2P) including the proposed search mechanism of hybrid periodical flooding (HPF) and routing protocols for improved routing performance 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 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 protocolsHigh-Performance Computing: Paradigm and Infrastructure is an invaluable compendium for engineers, IT professionals, and researchers and students of computer science and applied mathematics. Zusammenfassung The state of the art of high-performance computingProminent researchers from around the world have gathered to present the state-of-the-art techniques and innovations in high-performance computing (HPC), including: 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 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 Scheduling and resource management issues with heterogeneous systems, bus saturation effects on SMPs, genetic algorithms for distributed computing, and novel task-scheduling algorithms* Clusters and grid computing: design requiremen...

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The state of the art of high-performance computing Prominent researchers from around the world have gathered to present the state-of-the-art techniques and innovations in high-performance computing (HPC), including: 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 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 Scheduling and resource management issues with heterogeneous systems, bus saturation effects on SMPs, genetic algorithms for distributed computing, and novel task-scheduling algorithms Clusters and grid computing: design requirements, grid middleware, distributed virtual machines, data grid services and performance-boosting techniques, security issues, and open issues Peer-to-peer computing (P2P) including the proposed search mechanism of hybrid periodical flooding (HPF) and routing protocols for improved routing performance 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 * 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 High-Performance Computing: Paradigm and Infrastructure is an invaluable compendium for engineers, IT professionals, and researchers and students of computer science and applied mathematics.

Contenu

Preface. Contributors. PART 1. PROGRAMMING MODEL. 1. ClusterGOP: A High-Level Programming Environment for Clusters (Fan Chan, Jiannong Cao and Minyi Guo). 1.1 Introduction. 1.2 GOP Model and ClusterGOP Architecture. 1.3 VisualGOP. 1.4 The ClusterGOP Library. 1.5 MPMD Programming Support. 1.6 Programming Using ClusterGOP. 1.7 Summary. 2. The Challenge of Providing A High-Level Programming Model for High-Performance Computing (Barbara Chapman). 2.1 Introduction. 2.2 HPC Architectures. 2.3 HPC Programming Models: The First Generation. 2.4 The Second generation of HPC Programming Models. 2.5 OpenMP for DMPs. 2.6 Experiments with OpenMP on DMPs. 2.7 Conclusions. 3. SAT: Toward Structured Parallelism Using Skeletons (Sergei Gorlatch). 3.1 Introduction. 3.2 SAT: A Methodology Outline. 3.3 Skeletons and Collective Operations. 3.4 Case Study: Maximum Segment SUM (MSS). 3.5 Performance Aspect in SAT. 3.6 Conclusions and Related Work. 4. Bulk-Synchronous Parallelism: An Emerging Paradigm of High-Performance Computing (Alexander Tiskin). 4.1 The BSP Model. 4.2 BSP Programming. 4.3 Conclusions. 5. Cilk Versus MPI: Comparing Two Parallel Programming Styles on Heterogenous Systems (John Morris, KyuHo Lee and JunSeong Kim). 5.1 Introduction. 5.2 Experiments. 5.3 Results. 5.4 Conclusion. 6. Nested Parallelism and Pipelining in OpenMP (Marc Gonzalez, E. Ayguade, X. Martorell and J. Labarta). 6.1 Introduction. 6.2 OpenMP Extensions for Nested Parallelism. 6.3 OpenMP Extensions for Thread Synchronization. 6.4 Summary. **7. OpenMP for Chip Multiprocessors (Feng L…