Beowulf Cluster Computing with Windows


Book Description

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.




Beowulf Cluster Computing with Linux


Book Description

Enabling technologies - An overview of cluster computing / Thomas Sterling / - Node Hardware / Thomas Sterling / - Linux / Peter H. Beckman / - Network Hardware / Thomas Sterling / - Network Software / Thomas Sterling / - Setting Up clusters : installation and configuration - How fast is my beowulf? / David Bailey / - Parallel programming / - Parallel programming with MPI / William Gropp / - Advanced topics in MPI programming / William Gropp / - Parallel programming with PVM / Al Geist / - Fault-tolerant and adaptive programs with PVM / Al Geist / - Managing clusters / - Cluster workload management / James Patton Jones / - Condor : a distributed job scheduler / - Maui scheduler : A multifunction cluster scheduler / David B. Jackson / - PBS : portable batch system / James Patton Jones / - PVFS : parallel virtual file system / Walt Ligon / - Chiba city : the Argonne scalable cluster.




How to Build a Beowulf


Book Description

This how-to guide provides step-by-step instructions for building aBeowulf-type computer, including the physical elements that make up aclustered PC computing system, the software required (most of which isfreely available), and insights on how to organize the code to exploitparallelism. Supercomputing research—the goal of which is to make computers that are ever faster and more powerful—has been at the cutting edge of computer technology since the early 1960s. Until recently, research cost in the millions of dollars, and many of the companies that originally made supercomputers are now out of business.The early supercomputers used distributed computing and parallel processing to link processors together in a single machine, often called a mainframe. Exploiting the same technology, researchers are now using off-the-shelf PCs to produce computers with supercomputer performance. It is now possible to make a supercomputer for less than $40,000. Given this new affordability, a number of universities and research laboratories are experimenting with installing such Beowulf-type systems in their facilities.This how-to guide provides step-by-step instructions for building a Beowulf-type computer, including the physical elements that make up a clustered PC computing system, the software required (most of which is freely available), and insights on how to organize the code to exploit parallelism. The book also includes a list of potential pitfalls.




Scientific Programming and Computer Architecture


Book Description

A variety of programming models relevant to scientists explained, with an emphasis on how programming constructs map to parts of the computer. What makes computer programs fast or slow? To answer this question, we have to get behind the abstractions of programming languages and look at how a computer really works. This book examines and explains a variety of scientific programming models (programming models relevant to scientists) with an emphasis on how programming constructs map to different parts of the computer's architecture. Two themes emerge: program speed and program modularity. Throughout this book, the premise is to "get under the hood," and the discussion is tied to specific programs. The book digs into linkers, compilers, operating systems, and computer architecture to understand how the different parts of the computer interact with programs. It begins with a review of C/C++ and explanations of how libraries, linkers, and Makefiles work. Programming models covered include Pthreads, OpenMP, MPI, TCP/IP, and CUDA.The emphasis on how computers work leads the reader into computer architecture and occasionally into the operating system kernel. The operating system studied is Linux, the preferred platform for scientific computing. Linux is also open source, which allows users to peer into its inner workings. A brief appendix provides a useful table of machines used to time programs. The book's website (https://github.com/divakarvi/bk-spca) has all the programs described in the book as well as a link to the html text.




Linux Clustering


Book Description

"Linux Clustering" is the premier resource for system administrators wishing to implement clustering solutions on the many types of Linux systems. It guides Linux Administrators through difficult tasks while offering helpful tips and tricks.




Cloud Computing for Science and Engineering


Book Description

A guide to cloud computing for students, scientists, and engineers, with advice and many hands-on examples. The emergence of powerful, always-on cloud utilities has transformed how consumers interact with information technology, enabling video streaming, intelligent personal assistants, and the sharing of content. Businesses, too, have benefited from the cloud, outsourcing much of their information technology to cloud services. Science, however, has not fully exploited the advantages of the cloud. Could scientific discovery be accelerated if mundane chores were automated and outsourced to the cloud? Leading computer scientists Ian Foster and Dennis Gannon argue that it can, and in this book offer a guide to cloud computing for students, scientists, and engineers, with advice and many hands-on examples. The book surveys the technology that underpins the cloud, new approaches to technical problems enabled by the cloud, and the concepts required to integrate cloud services into scientific work. It covers managing data in the cloud, and how to program these services; computing in the cloud, from deploying single virtual machines or containers to supporting basic interactive science experiments to gathering clusters of machines to do data analytics; using the cloud as a platform for automating analysis procedures, machine learning, and analyzing streaming data; building your own cloud with open source software; and cloud security. The book is accompanied by a website, Cloud4SciEng.org, that provides a variety of supplementary material, including exercises, lecture slides, and other resources helpful to readers and instructors.




Delivery and Adoption of Cloud Computing Services in Contemporary Organizations


Book Description

The ubiquity of technology has not only brought the need for computer knowledge to every aspect of the modern business world; it has also increased our need to safely store the data we are now creating at a rate never experienced before. Delivery and Adoption of Cloud Computing Services in Contemporary Organizations brings together the best practices for storing massive amounts of data. Highlighting ways cloud services can work effectively in production and in real time, this book is an essential reference source for professionals and academics of various disciplines, such as computer science, consulting, information technology, information and communication sciences, healthcare, and finance.




Grid Computing


Book Description

Unter "Grid Computing" versteht man die gleichzeitige Nutzung vieler Computer in einem Netzwerk für die Lösung eines einzelnen Problems. Grundsätzliche Aspekte und anwendungsbezogene Details zu diesem Gebiet finden Sie in diesem Band. - Grid Computing ist ein viel versprechender Trend, denn man kann damit (1) vorhandene Computer-Ressourcen kosteneffizient nutzen, (2) Probleme lösen, für die enorme Rechenleistungen erforderlich sind, und (3) Synergieeffekte erzielen, auch im globalen Maßstab - Ansatz ist in Forschung und Industrie (IBM, Sun, HP und andere) zunehmend populär (aktuelles Beispiel: Genomforschung) - Buch deckt Motivationen zur Einführung von Grids ebenso ab wie technologische Grundlagen und ausgewählte Beispiele für moderne Anwendungen




Programming Models for Parallel Computing


Book Description

An overview of the most prominent contemporary parallel processing programming models, written in a unique tutorial style. With the coming of the parallel computing era, computer scientists have turned their attention to designing programming models that are suited for high-performance parallel computing and supercomputing systems. Programming parallel systems is complicated by the fact that multiple processing units are simultaneously computing and moving data. This book offers an overview of some of the most prominent parallel programming models used in high-performance computing and supercomputing systems today. The chapters describe the programming models in a unique tutorial style rather than using the formal approach taken in the research literature. The aim is to cover a wide range of parallel programming models, enabling the reader to understand what each has to offer. The book begins with a description of the Message Passing Interface (MPI), the most common parallel programming model for distributed memory computing. It goes on to cover one-sided communication models, ranging from low-level runtime libraries (GASNet, OpenSHMEM) to high-level programming models (UPC, GA, Chapel); task-oriented programming models (Charm++, ADLB, Scioto, Swift, CnC) that allow users to describe their computation and data units as tasks so that the runtime system can manage computation and data movement as necessary; and parallel programming models intended for on-node parallelism in the context of multicore architecture or attached accelerators (OpenMP, Cilk Plus, TBB, CUDA, OpenCL). The book will be a valuable resource for graduate students, researchers, and any scientist who works with data sets and large computations. Contributors Timothy Armstrong, Michael G. Burke, Ralph Butler, Bradford L. Chamberlain, Sunita Chandrasekaran, Barbara Chapman, Jeff Daily, James Dinan, Deepak Eachempati, Ian T. Foster, William D. Gropp, Paul Hargrove, Wen-mei Hwu, Nikhil Jain, Laxmikant Kale, David Kirk, Kath Knobe, Ariram Krishnamoorthy, Jeffery A. Kuehn, Alexey Kukanov, Charles E. Leiserson, Jonathan Lifflander, Ewing Lusk, Tim Mattson, Bruce Palmer, Steven C. Pieper, Stephen W. Poole, Arch D. Robison, Frank Schlimbach, Rajeev Thakur, Abhinav Vishnu, Justin M. Wozniak, Michael Wilde, Kathy Yelick, Yili Zheng




Quantum Computing Without Magic


Book Description

How quantum computing is really done: a primer for future quantum device engineers. This text offers an introduction to quantum computing, with a special emphasis on basic quantum physics, experiment, and quantum devices. Unlike many other texts, which tend to emphasize algorithms, Quantum Computing Without Magic explains the requisite quantum physics in some depth, and then explains the devices themselves. It is a book for readers who, having already encountered quantum algorithms, may ask, “Yes, I can see how the algebra does the trick, but how can we actually do it?” By explaining the details in the context of the topics covered, this book strips the subject of the “magic” with which it is so often cloaked. Quantum Computing Without Magic covers the essential probability calculus; the qubit, its physics, manipulation and measurement, and how it can be implemented using superconducting electronics; quaternions and density operator formalism; unitary formalism and its application to Berry phase manipulation; the biqubit, the mysteries of entanglement, nonlocality, separability, biqubit classification, and the Schroedinger's Cat paradox; the controlled-NOT gate, its applications and implementations; and classical analogs of quantum devices and quantum processes. Quantum Computing Without Magic can be used as a complementary text for physics and electronic engineering undergraduates studying quantum computing and basic quantum mechanics, or as an introduction and guide for electronic engineers, mathematicians, computer scientists, or scholars in these fields who are interested in quantum computing and how it might fit into their research programs.