In Search of Clusters

In Search of Clusters

          
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About the Book

This text explains an increasingly popular form of parallel or distributed computing that is frequently misunderstood. A leading expert on microprocessing, Pfister demonstrates that clusters are a distinct form of parallel computing with extraordinary potential and highlights the critical role clusters can play in downsizing. The book covers the underlying hardware and software technologies and shows how clusters of small computers can match the performance of the most powerful supercomputers. It provides the background needed to understand the real issues involved in implementing parallel and distributed systems, and also includes an analysis of the various forms of clusters and how they differ from the competitive symmetric multiprocessor (SMP) architectures.

Table of Contents:
I. WHAT IS A CLUSTER, AND WHY USE THEM? 1. Introduction. Working Harder. Working Smarter. Getting Help. A Neglected Paradigm. What Is To Come. 2. Examples. The Farm. Fermilab. Many Others. Cluster System Products. Cluster Software Products. Availability Clusters. Not the End. 3. Why Clusters? The Standard Litany. Why Now? Why Not Now? Cluster Enablers. 4. Definition, Distinctions, and Initial Comparisons. Definition. Distinction From Parallel Systems. Distinctions from Distributed Systems. Concerning "Single System Image". Other Comparisons. Reactions. II. HARDWARE. 5. A Cluster Bestiary. Exposed vs. Enclosed. "Glass-House" vs. "Campus-Wide" Cluster. Cluster Hardware Structures. Communication Requirements. 6. Symmetric Multiprocessors. What Is an SMP? What Is a Cache, and Why Is It Necessary? Memory Contention. Cache Coherence. Sequential and Other Consistencies. Input/Output. Summary. III. SOFTWARE. 7. Workloads. Why Discuss Workloads? Serial: Throughput. Parallel. Amdahl's Law. The Point of All This. 8. Basic Programming Models and Issues. What Is a Programming Model? The Sample Problem. Uniprocessor. Shared Memory. Message-Passing. Both at Once. SIMD and All That. Importance. 9. Commercial Programming Models. Small N vs. Large N. Small-N Programming Models. Large-N I/O Programming Models. Large-N Processor-Memory Models. Shared Disk or not Shared Disk? Small N vs. Large N in Commercial Subsystems. 10. Single System Image. Single-System-Image Boundaries. Single-System-Image Levels. The Application and Subsystem Levels. The Operating System Kernel Levels. Hardware Levels. SSI and System Management. IV. SYSTEMS. 11. Symmetric Multiprocessors vs. Clusters. What's Being Compared? Conventional Wisdom. SMP and Other Scaling. SMP-Cluster Performance Comparisons. Other Comparisons. Conclusions? 12. Why We Need the Concept of "Cluster". Benchmarks. Development Directions. Confusion of Issues. The Lure of Large Numbers. 13. Conclusion. Cluster Operating Systems. Communication Overhead. Standards. Software Pricing. Coda: The End of Parallel Computer Architecture. Annotated Bibliography. Index. About the Author.


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Product Details
  • ISBN-13: 9780134376257
  • Publisher: Pearson Education (US)
  • Publisher Imprint: Prentice Hall
  • Height: 230 mm
  • No of Pages: 444
  • Weight: 570 gr
  • ISBN-10: 0134376250
  • Publisher Date: 11 Aug 1995
  • Binding: Paperback
  • Language: English
  • Spine Width: 20 mm
  • Width: 152 mm


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