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Cluster Computing
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Editors: Buyya, Rajkumar . ; Szyperski, Clemens
Book Description:
At first thought, one may not realize the need for a special book on "Cluster Computing" when our community has already invested years of research and spent a wealth of resources on traditional "Big Iron" supercomputers, for instance, the SGI/Cray Origin and IBM SP. Academia, industry, and national laboratories are still using, and for the foreseeable future, will continue to use, supercomputers to solve both grand-challenge scale and high-throughput applications. Then why the interest and new popularity of research into clusters for high-performance parallel and distributed applications? Clusters incorporate the tremendous successes that are attributable to our parallel and distributed processing community.
Over the next decade, clusters will span the entire range of high-performance computing platforms. Instead of being restricted solely to supercomputers for achieving high-performance computing, the spectrum of available platforms will spread out to Beowulf-class clusters, to superclusters, and on to supercomputers. Moving along this continuum represents increasing computational resources, which in turn allows the capability for solving larger classes of applications or instances of problems. Compute-bound applications on workstations often may take advantage of the extra horsepower provided by symmetric multiprocessors. Applications with even larger computational requirements and a high-degree of concurrency may use Beowulf clusters, that is, clusters that are home-built from mass-market, commercial off-the-shelf workstations and networks, for instance, PC's interconnected by Fast Ethernet. A supercluster may contain commodity SMP nodes interconnected with scalable, low-latency, high-bandwidth networks, and is integrated by a system vendor rather than the computational scientist. Applications with greater complexity, for example, grand challenges from the sciences, demand scalable systems with high-performance, interconnects, perhaps coupled with terascale I/O subsystems, and thus, are appropriate for these superclusters. Finally, supercomputers, the largest of the clusters, may provide the ultimate platform for the highest-fidelity models and simulations and data-intensive applications. At each step up this ladder of cluster architectures, the system cost increases approximately by an order of magnitude, but having the high-performance capability to solve the problem of interest may require an entry point at any of these levels, the Beowulf, or supercluster, or even supercomputer platform.

Table of Contents:
Guest Editors' Introduction: Facilitating Parallel and Distributed Computing (Rajkumar Buyya and Clemens Szyperski); Experiences with Windows NT as a Cluster Computing Platform for Parallel Computing (Markus Fischer and Jack Dongarra); Distributed Processing of Remotely Sensed Landsat-TM Imagery Using MPI (J. A. Gallud, J. García-Consuegra, and A. Martínez); The DOGMA Approach to Parallel and Distributed Computing (Anup K. Bhattacharjee, K. Ravindranath, A. Pal and R. Mall); Overlap of Computation and Communication on Shared-Memory Networks-of-Workstations (Tarek S. Abdelrahman and Gary Liu); Aggressive Communication Optimizations for Clusters of Workstations (Gagan Agrawal); Experiences with the SEMPA Resource Manager for Real World Scientific Computing in Networks of Workstations (Ursula Maier, Peter Luksch and Arndt Bode); Task Scheduling on Bus-based Networks of Workstations (Wei-Ming Lin and Qiuyan Gu); High-Performance Thread Migration on Clusters of SMPs (Boris Weissman and Benedict Gomes); Multiple-Writer Entry Consistency (H. Sandhu, T. Brecht and D. Moscoso); On Using Reliable Network RAM in Networks of Workstations (S. Ioannidis, A.E. Papathanasiou, G.I. Magklis, E.P. Markatos, D.N. Pnevmatikatos and J. Sevaslidou); File Declustering for Efficient Parallel I/O on Networks of Workstations (Hau-Yang Cheng and Chung-Ta King); A Survey of Messaging Software Issues and Systems for Myrinet-Based Clusters (R.W. dos Santos, R. Bianchini and C.L. Amorim); Index

   Binding: Hardcover
   Pub. Date: 2001
   ISBN: 1-59033-113-3
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Cluster Computing