Beowulf Cluster Computing with Linux (Scientific and Engineering Computation)

This second edition covers a large range of cluster topics. Firstly, in terms of why you might need a Beowulf. Then, how to assemble the hardware. And how to install linux on the nodes. The book is valuable not least because it encapsulates decades of knowledge about running clusters, not just of the Beowulf type. The chapters' authors hail from places like Argonne and Oak Ridge National Labs, where there have been research groups using many different types of clusters for years.Aside from linux, the book describes the special purpose parallel language called MPI. It can be accessed from a C, C++ or Fortran program. Note this choice of languages. Typically the cluster is meant for intensive computational use, with UI issues a low priority. So the book focuses on those languages, and not how to hook Java or C# to MPI.Of course, with each chapter written by a different author, there is somewhat of a discontinuity between chapters. Think of the book as more akin to a conference proceedings writeup. Comprehensive guides to the latest Beowulf tools and methodologies.Beowulf clusters, which exploit mass-market PC hardware and software in conjunction with cost-effective commercial network technology, are becoming the platform for many scientific, engineering, and commercial applications. With growing popularity has come growing complexity. Addressing that complexity, Beowulf Cluster Computing with Linux and Beowulf Cluster Computing with Windows provide system users and administrators with the tools they need to run the most advanced Beowulf clusters. The book is appearing in both Linux and Windows versions in order to reach the entire PC cluster community, which is divided into two distinct camps according to the node operating system. Each book consists of three stand-alone parts. The first provides an introduction to the underlying hardware technology, assembly, and configuration. The second part offers a detailed presentation of the major parallel programming librairies. The third, and largest, part describes software infrastructures and tools for managing cluster resources. This includes some of the most popular of the software packages available for distributed task scheduling, as well as tools for monitoring and administering system resources and user accounts. Approximately 75% of the material in the two books is shared, with the other 25% pertaining to the specific operating system. Most of the chapters include text specific to the operating system. The Linux volume includes a discussion of parallel file systems.