Title: High-Performance Computing
Description: 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.
Subjects: Computer Technology, Nonfiction, Electronic data processing, distributed processing, Engineering, data processing, High performance computing, Parallel processing (electronic computers), Science, data processing