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Introduction to Parallel Computing by Ananth Grama Pdf
A complete source of information on almost all aspects of parallel computing from introduction, to architectures, to programming paradigms, to algorithms, to programming standards. It covers traditional Computer Science algorithms, scientific computing algorithms and data intensive algorithms.
Introduction to Parallel Programming by Subodh Kumar Pdf
In modern computer science, there exists no truly sequential computing system; and most advanced programming is parallel programming. This is particularly evident in modern application domains like scientific computation, data science, machine intelligence, etc. This lucid introductory textbook will be invaluable to students of computer science and technology, acting as a self-contained primer to parallel programming. It takes the reader from introduction to expertise, addressing a broad gamut of issues. It covers different parallel programming styles, describes parallel architecture, includes parallel programming frameworks and techniques, presents algorithmic and analysis techniques and discusses parallel design and performance issues. With its broad coverage, the book can be useful in a wide range of courses; and can also prove useful as a ready reckoner for professionals in the field.
Introduction to Parallel Computing by Roman Trobec,Boštjan Slivnik,Patricio Bulić,Borut Robič Pdf
Advancements in microprocessor architecture, interconnection technology, and software development have fueled rapid growth in parallel and distributed computing. However, this development is only of practical benefit if it is accompanied by progress in the design, analysis and programming of parallel algorithms. This concise textbook provides, in one place, three mainstream parallelization approaches, Open MPP, MPI and OpenCL, for multicore computers, interconnected computers and graphical processing units. An overview of practical parallel computing and principles will enable the reader to design efficient parallel programs for solving various computational problems on state-of-the-art personal computers and computing clusters. Topics covered range from parallel algorithms, programming tools, OpenMP, MPI and OpenCL, followed by experimental measurements of parallel programs’ run-times, and by engineering analysis of obtained results for improved parallel execution performances. Many examples and exercises support the exposition.
Introduction to Parallel Processing by Behrooz Parhami Pdf
THE CONTEXT OF PARALLEL PROCESSING The field of digital computer architecture has grown explosively in the past two decades. Through a steady stream of experimental research, tool-building efforts, and theoretical studies, the design of an instruction-set architecture, once considered an art, has been transformed into one of the most quantitative branches of computer technology. At the same time, better understanding of various forms of concurrency, from standard pipelining to massive parallelism, and invention of architectural structures to support a reasonably efficient and user-friendly programming model for such systems, has allowed hardware performance to continue its exponential growth. This trend is expected to continue in the near future. This explosive growth, linked with the expectation that performance will continue its exponential rise with each new generation of hardware and that (in stark contrast to software) computer hardware will function correctly as soon as it comes off the assembly line, has its down side. It has led to unprecedented hardware complexity and almost intolerable dev- opment costs. The challenge facing current and future computer designers is to institute simplicity where we now have complexity; to use fundamental theories being developed in this area to gain performance and ease-of-use benefits from simpler circuits; to understand the interplay between technological capabilities and limitations, on the one hand, and design decisions based on user and application requirements on the other.
Embedded Computing by Joseph A. Fisher,Paolo Faraboschi,Cliff Young Pdf
"Embedded Computing is enthralling in its clarity and exhilarating in its scope. If the technology you are working on is associated with VLIWs or "embedded computing", then clearly it is imperative that you read this book. If you are involved in computer system design or programming, you must still read this book, because it will take you to places where the views are spectacular. You don't necessarily have to agree with every point the authors make, but you will understand what they are trying to say, and they will make you think.” From the Foreword by Robert Colwell, R&E Colwell & Assoc. Inc The fact that there are more embedded computers than general-purpose computers and that we are impacted by hundreds of them every day is no longer news. What is news is that their increasing performance requirements, complexity and capabilities demand a new approach to their design. Fisher, Faraboschi, and Young describe a new age of embedded computing design, in which the processor is central, making the approach radically distinct from contemporary practices of embedded systems design. They demonstrate why it is essential to take a computing-centric and system-design approach to the traditional elements of nonprogrammable components, peripherals, interconnects and buses. These elements must be unified in a system design with high-performance processor architectures, microarchitectures and compilers, and with the compilation tools, debuggers and simulators needed for application development. In this landmark text, the authors apply their expertise in highly interdisciplinary hardware/software development and VLIW processors to illustrate this change in embedded computing. VLIW architectures have long been a popular choice in embedded systems design, and while VLIW is a running theme throughout the book, embedded computing is the core topic. Embedded Computing examines both in a book filled with fact and opinion based on the authors many years of R&D experience. Features: · Complemented by a unique, professional-quality embedded tool-chain on the authors' website, http://www.vliw.org/book · Combines technical depth with real-world experience · Comprehensively explains the differences between general purpose computing systems and embedded systems at the hardware, software, tools and operating system levels. · Uses concrete examples to explain and motivate the trade-offs.
Introduction to Parallel Computing by Wesley Petersen,Peter Arbenz Pdf
In the last few years, courses on parallel computation have been developed and offered in many institutions in the UK, Europe and US as a recognition of the growing significance of this topic in mathematics and computer science. There is a clear need for texts that meet the needs of students and lecturers and this book, based on the author's lecture at ETH Zurich, is an ideal practical student guide to scientific computing on parallel computers working up from a hardware instruction level, to shared memory machines, and finally to distributed memory machines. Aimed at advanced undergraduate and graduate students in applied mathematics, computer science, and engineering, subjects covered include linear algebra, fast Fourier transform, and Monte-Carlo simulations, including examples in C and, in some cases, Fortran. This book is also ideal for practitioners and programmers.
Scientific Parallel Computing by L. Ridgway Scott,Terry Clark,Babak Bagheri Pdf
What does Google's management of billions of Web pages have in common with analysis of a genome with billions of nucleotides? Both apply methods that coordinate many processors to accomplish a single task. From mining genomes to the World Wide Web, from modeling financial markets to global weather patterns, parallel computing enables computations that would otherwise be impractical if not impossible with sequential approaches alone. Its fundamental role as an enabler of simulations and data analysis continues an advance in a wide range of application areas. Scientific Parallel Computing is the first textbook to integrate all the fundamentals of parallel computing in a single volume while also providing a basis for a deeper understanding of the subject. Designed for graduate and advanced undergraduate courses in the sciences and in engineering, computer science, and mathematics, it focuses on the three key areas of algorithms, architecture, languages, and their crucial synthesis in performance. The book's computational examples, whose math prerequisites are not beyond the level of advanced calculus, derive from a breadth of topics in scientific and engineering simulation and data analysis. The programming exercises presented early in the book are designed to bring students up to speed quickly, while the book later develops projects challenging enough to guide students toward research questions in the field. The new paradigm of cluster computing is fully addressed. A supporting web site provides access to all the codes and software mentioned in the book, and offers topical information on popular parallel computing systems. Integrates all the fundamentals of parallel computing essential for today's high-performance requirements Ideal for graduate and advanced undergraduate students in the sciences and in engineering, computer science, and mathematics Extensive programming and theoretical exercises enable students to write parallel codes quickly More challenging projects later in the book introduce research questions New paradigm of cluster computing fully addressed Supporting web site provides access to all the codes and software mentioned in the book
INTRODUCTION TO PARALLEL PROCESSING by M. Sasikumar,Dinesh Shikhare,Ravi P. Prakash Pdf
Written with a straightforward and student-centred approach, this extensively revised, updated and enlarged edition presents a thorough coverage of the various aspects of parallel processing including parallel processing architectures, programmability issues, data dependency analysis, shared memory programming, thread-based implementation, distributed computing, algorithms, parallel programming languages, debugging, parallelism paradigms, distributed databases as well as distributed operating systems. The book, now in its second edition, not only provides sufficient practical exposure to the programming issues but also enables its readers to make realistic attempts at writing parallel programs using easily available software tools. With all the latest information incorporated and several key pedagogical attributes included, this textbook is an invaluable learning tool for the undergraduate and postgraduate students of computer science and engineering. It also caters to the students pursuing master of computer application. What’s New to the Second Edition • A new chapter named Using Parallelism Effectively has been added covering a case study of parallelising a sorting program, and introducing commonly used parallelism models. • Sections describing the map-reduce model, top-500.org initiative, Indian efforts in supercomputing, OpenMP system for shared memory programming, etc. have been added. • Numerous sections have been updated with current information. • Several questions have been incorporated in the chapter-end exercises to guide students from examination and practice points of view.
Introduction to Parallel and Vector Solution of Linear Systems by James M. Ortega Pdf
Although the origins of parallel computing go back to the last century, it was only in the 1970s that parallel and vector computers became available to the scientific community. The first of these machines-the 64 processor llliac IV and the vector computers built by Texas Instruments, Control Data Corporation, and then CRA Y Research Corporation-had a somewhat limited impact. They were few in number and available mostly to workers in a few government laboratories. By now, however, the trickle has become a flood. There are over 200 large-scale vector computers now installed, not only in government laboratories but also in universities and in an increasing diversity of industries. Moreover, the National Science Foundation's Super computing Centers have made large vector computers widely available to the academic community. In addition, smaller, very cost-effective vector computers are being manufactured by a number of companies. Parallelism in computers has also progressed rapidly. The largest super computers now consist of several vector processors working in parallel. Although the number of processors in such machines is still relatively small (up to 8), it is expected that an increasing number of processors will be added in the near future (to a total of 16 or 32). Moreover, there are a myriad of research projects to build machines with hundreds, thousands, or even more processors. Indeed, several companies are now selling parallel machines, some with as many as hundreds, or even tens of thousands, of processors.
Parallel Programming by Bertil Schmidt,Jorge Gonzalez-Dominguez,Christian Hundt,Moritz Schlarb Pdf
Parallel Programming: Concepts and Practice provides an upper level introduction to parallel programming. In addition to covering general parallelism concepts, this text teaches practical programming skills for both shared memory and distributed memory architectures. The authors’ open-source system for automated code evaluation provides easy access to parallel computing resources, making the book particularly suitable for classroom settings. Covers parallel programming approaches for single computer nodes and HPC clusters: OpenMP, multithreading, SIMD vectorization, MPI, UPC++ Contains numerous practical parallel programming exercises Includes access to an automated code evaluation tool that enables students the opportunity to program in a web browser and receive immediate feedback on the result validity of their program Features an example-based teaching of concept to enhance learning outcomes
High Performance Computing and the Art of Parallel Programming by Stan Openshaw,Ian Turton Pdf
This book provides a non-technical introduction to High Performance Computing applications together with advice about how beginners can start to write parallel programs. The authors show what HPC can offer geographers and social scientists and how it can be used in GIS. They provide examples of where it has already been used and suggestions for other areas of application in geography and the social sciences. Case studies drawn from geography explain the key principles and help to understand the logic and thought processes that lie behind the parallel programming.