Beowulf Cluster Computing is offered as a fully comprehensive discussion of the foundations and practices for the operation and application of commodity clusters with an emphasis on those derived from mass-market hardware components and readily available software. The book is divided into three broad topic areas. Part I describes the hardware components that make up a Beowulf system and shows how to assemble such a system as well as take it out for an initial spin using some readily available parallel benchmarks. Part II discusses the concepts and techniques for writing parallel application programs to run on a Beowulf using the two dominant communitywide standards, PVM and MPI. Part III explains how to manage the resources of Beowulf systems, including system administration and task scheduling. Each part is standalone; any one or pair of parts can be used without the need of the others. In this way, you can just jump into the middle to get to the necessary information fast. To help in this, Chapter 2 (the next chapter) provides an overview and summary of all of the material in the book. A quick perusal of that chapter should give enough context for any single chapter to make sense without your having to have read the rest of the book.
The Beowulf book presents three kinds of information to best meet the requirements of the broad and varied cluster computing community. It includes foundation material for students and people new to the field. It also includes reference material in each topic area, such as the major library calls to MPI and PVM or the basic controls for PBS. And, it gives explicit step-by-step guidance on how to accomplish specific tasks such as assembling a processor node from basic components or installing the Maui scheduler.
This book can be used in many different ways. We recommend just sitting down and perusing it for an hour or so to get a good feel for where the information is that you would find most useful. Take a walk through Chapter 2 to get a solid overview. Then, if you're trying to get a job done, go after that material germane to your immediate needs. Or if you are a first-time Beowulf user and just learning about cluster computing, use this as your guide through the field. Every section is designed both to be interesting and to teach you how to do something new and useful.
One major challenge was how to satisfy the needs of the majority of the commodity cluster community when a major division exists across the lines of the operating system used. In fact, at least a dozen different operating systems have been used for cluster systems. But the majority of the community use either Linux or Windows. The choice of which of the two to use depends on many factors, some of them purely subjective. We therefore have taken the unprecedented action of offering a choice: we've crafted two books, mostly the same, but differing between the two operating systems. So, you are holding either Beowulf Cluster Computing with Windows or Beowulf Cluster Computing with Linux. Whichever works best for you, we hope you find it the single most valuable book on your shelf for making clusters and for making clusters work for you.
I ENABLING TECHNOLOGIES
md 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. By incorporating only components already developed for wider markets, they exploit the economy of scale not possible in the high-end computing market alone and circumvent significant development costs and lead times typical of earlier classes of high-end systems resulting in a price/performance advantage that may exceed an order of magnitude for many user workloads. In addition, users have greater flexibility of configuration, upgrade, and supplier, ensuring longevity of this class of distributed system and user confidence in their software investment. Beowulf-class systems exploit mass-market components such as PCs to deliver exceptional cost advantage with the widest space of choice for building systems. 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:
2. resource administration and management environment,
3. distributed programming libraries and tools, and
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. 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. 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. Finally, 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.
This chapter provides a brief and top-level overview of these four main domains that constitute Beowulf cluster computing. The objective is to provide sufficient context for you to understand any single part of the remaining book and how its contribution fits in to the broader form and function of commodity clusters.
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