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An Overview of Cluster Computing

Commodity cluster systems offer an alternative to the technical and commercial computing market for scalable computing systems for medium - and high-end computing capability. For many applications they replace previous-generation monolithic vector supercomputers and MPPs. Users have greater flexibility of configuration, upgrade, and supplier, ensuring longevity of this class of distributed system and user confidence in their software investment. Beowulfs integrate widely available and easily accessible low-cost or no-cost system software to provide many of the capabilities required by a system environment. As a result of these attributes and the opportunities they imply, Beowulf-class clusters have penetrated almost every aspect of computing and are rapidly coming to dominate the medium to high end. Computing with a Beowulf cluster engages four distinct but interrelated areas of consideration:
  1. hardware system structure Hardware system structure encompasses all aspects of the hardware node components and their capabilities, the dedicated network controllers and switches, and the interconnection topology that determines the system's global organization.
  2. resource administration and management environment The resource management environment is the battery of system software and tools that govern all phases of system operation from installation, configuration, and initialization, through administration and task management, to system status monitoring, fault diagnosis, and maintenance.
  3. distributed programming libraries and tools The distributed programming libraries and tools determine the paradigm by which the end user coordinates the distributed computing resources to execute simultaneously and cooperatively the many concurrent logical components constituting the parallel application program.
  4. parallel algorithms The domain of parallel algorithms provides the models and approaches for organizing a user's application to exploit the intrinsic parallelism of the problem while operating within the practical constraints of effective performance.


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next up previous contents
Next: A Taxonomy of Parallel Up: Cluster Computing Previous: Elements of a Cluster   Contents
Cem Ozdogan 2009-01-05