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This book constitutes the refereed proceedings of the 10th International Conference on High-Performance Computing, HiPC 2003, held in Hyderabad, India in December 2003. The 48 revised full papers presented together with 5 keynote abstracts were carefully reviewed and selected from 164 submissions. The papers are organized in topical sections on performance issues and power-aware systems; distributed and network algorithms; routing in wireless, mobile, and cut-through networks; scientific and engineering applications; overlay networks, clusters, and grids; scheduling and software algorithms; network design and performance; grid applications and architecture support; performance analysis; scheduling and migration.
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.
This book constitutes the refereed proceedings of the 13th International Conference on High-Performance Computing, HiPC 2006, held in Bangalore, India, December 2006. Coverage in this volume includes scheduling and load balancing, network and distributed algorithms, application software, network services, ad-hoc networks, systems software, sensor networks and performance evaluation, as well as routing and data management algorithms.
This book constitutes the refereed proceedings of the Second International Conference on High Performance Computing and Communications, HPCC 2006. The book presents 95 revised full papers, addressing all current issues of parallel and distributed systems and high performance computing and communication. Coverage includes networking protocols, routing, and algorithms, languages and compilers for HPC, parallel and distributed architectures and algorithms, wireless, mobile and pervasive computing, Web services, peer-to-peer computing, and more.
Provides a collection of authoritative articles from distinguished international researchers in information technology and Web engineering.
Programming multi-core and many-core computing systems Sabri Pllana, Linnaeus University, Sweden Fatos Xhafa, Technical University of Catalonia, Spain Provides state-of-the-art methods for programming multi-core and many-core systems The book comprises a selection of twenty two chapters covering: fundamental techniques and algorithms; programming approaches; methodologies and frameworks; scheduling and management; testing and evaluation methodologies; and case studies for programming multi-core and many-core systems. Program development for multi-core processors, especially for heterogeneous multi-core processors, is significantly more complex than for single-core processors. However, programmers have been traditionally trained for the development of sequential programs, and only a small percentage of them have experience with parallel programming. In the past, only a relatively small group of programmers interested in High Performance Computing (HPC) was concerned with the parallel programming issues, but the situation has changed dramatically with the appearance of multi-core processors on commonly used computing systems. It is expected that with the pervasiveness of multi-core processors, parallel programming will become mainstream. The pervasiveness of multi-core processors affects a large spectrum of systems, from embedded and general-purpose, to high-end computing systems. This book assists programmers in mastering the efficient programming of multi-core systems, which is of paramount importance for the software-intensive industry towards a more effective product-development cycle. Key features: Lessons, challenges, and roadmaps ahead. Contains real world examples and case studies. Helps programmers in mastering the efficient programming of multi-core and many-core systems. The book serves as a reference for a larger audience of practitioners, young researchers and graduate level students. A basic level of programming knowledge is required to use this book.
Parallel processing has been an enabling technology in scientific computing for more than 20 years. This book is the first in-depth discussion of parallel computing in 10 years; it reflects the mix of topics that mathematicians, computer scientists, and computational scientists focus on to make parallel processing effective for scientific problems. Presently, the impact of parallel processing on scientific computing varies greatly across disciplines, but it plays a vital role in most problem domains and is absolutely essential in many of them. Parallel Processing for Scientific Computing is divided into four parts: The first concerns performance modeling, analysis, and optimization; the second focuses on parallel algorithms and software for an array of problems common to many modeling and simulation applications; the third emphasizes tools and environments that can ease and enhance the process of application development; and the fourth provides a sampling of applications that require parallel computing for scaling to solve larger and realistic models that can advance science and engineering.
This book constitutes the refereed proceedings of the 34th International Conference on High Performance Computing, ISC High Performance 2019, held in Frankfurt/Main, Germany, in June 2019. The 17 revised full papers presented were carefully reviewed and selected from 70 submissions. The papers cover a broad range of topics such as next-generation high performance components; exascale systems; extreme-scale applications; HPC and advanced environmental engineering projects; parallel ray tracing - visualization at its best; blockchain technology and cryptocurrency; parallel processing in life science; quantum computers/computing; what's new with cloud computing for HPC; parallel programming models for extreme-scale computing; workflow management; machine learning and big data analytics; and deep learning and HPC.
Unconventional approaches to programming have long been developed, in various niches and out of curiosity, and they constitute a reservoir of alternative avenues to deal with unknown programming challenges. New paradigms of programming are currently experiencing a renewed period of interest and growth to cope with problems from specific application domains. This book constitutes the thoroughly refereed post-proceedings of the International Workshop on Unconventional Programming Paradigms, UPP 2004, held at Le Mont Saint Michel, France, in September 2004. The 26 revised full papers presented together with an invited paper on quantum computing were carefully reviewed for presentation in the book. The papers are organized in topical sections on chemical computing, amorphous computing, bio-inspired computing, autonomic computing, and generative programming.