Parallel Processing Computers Books - Page 3

Parallel Distributed Processing, Vol. 1: Foundations

David E. Rumelhart, James L. McClelland, the PDP Research Group

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Total reviews: 2 Average rating: 5.0 of 5

Editorial Review:

This two-volume work is now considered a classic in the field. It presents the results of the Parallel Distributed Processing (PDP) group's work in the early 1980s and provides a good overview of the earlier neural network research. The PDP approach (also known as connectionism among other things) is based on the conviction that various aspects of cognitive activity are thought of in terms of massively parallel processing. The first volume starts with the general framework and continues with an analysis of learning mechanisms and various mathematical and computational tools important in the analysis of neural networks. The chapter on backpropagation is written by Rumelhart, Hinton, and Williams, who codiscovered the algorithm in 1986. The second volume is written with a psychological and biological emphasis. It explores the relationship of PDP to various aspects of human cognition. The book is a comprehensive research survey of its time and most of the book's results and methods are still at the foundation of the neural network field.

Unit Testing in Java: How Tests Drive the Code (The Morgan Kaufmann Series in Software Engineering and Programming)

Johannes Link

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Total reviews: 9 Average rating: 4.5 of 5

Editorial Review:

Software testing is indispensable and is one of the most discussed topics in software development today. Many companies address this issue by assigning a dedicated software testing phase towards the end of their development cycle. However, quality cannot be tested into a buggy application. Early and continuous unit testing has been shown to be crucial for high quality software and low defect rates. Yet current books on testing ignore the developer's point of view and give little guidance on how to bring the overwhelming amount of testing theory into practice. Unit Testing in Java represents a practical introduction to unit testing for software developers. It introduces the basic test-first approach and then discusses a large number of special issues and problem cases. The book instructs developers through each step and motivates them to explore further.

*Shows how the discovery and avoidance of software errors is a demanding and creative activity in its own right and can build confidence early in a project.
*Demonstrates how automated tests can detect the unwanted effects of small changes in code within the entire system.
*Discusses how testing works with persistency, concurrency, distribution, and web applications.
*Includes a discussion of testing with C++ and Smalltalk.

How to Build a Beowulf: A Guide to the Implementation and Application of PC Clusters (Scientific and Engineering Computation)

Thomas Sterling, Donald J. Becker, Daniel F. Savarese

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Total reviews: 13 Average rating: 2.5 of 5

Editorial Review:

How to Build a Beowulf covers the essentials of today's "cheap supercomputing" that is available with off-the-shelf PC hardware running Linux. Filled with advice from the experts, this book is a working guide to the essentials of planning, installing, and running a Beowulf cluster.

After an introduction to Beowulf and parallel computing in general, the authors describe the advantages to and organization of a typical Beowulf setup. They next describe the basic PC hardware (which will be familiar to many Intel users). The do-it-yourself impulse in Beowulf supercomputing is strong, and the authors show how to choose everything from a CPU and memory to networking options (including TCP/IP basics and Fast Ethernet). They cover hardware and software installation and the basics of configuring Linux on Beowulf nodes (which do the work of parallel processing).

Next the book covers issues of security and system administration of a Beowulf cluster. (Here the authors strike a balance between accessibility and security with the concept of a "guarded Beowulf.") They cover a variety of Linux utilities for remote computing and administration.

An essential piece of Beowulf technology is the Message Passing Interface (MPI), a set of APIs that permit programmers to develop parallel programs in C/C++ and FORTRAN. With MPI, programs running on different CPUs can pass messages and share the same data. The samples that round out this book are excellent--a ray-tracing example, a parallel sorting algorithm, and a cellular automata program. The authors do a good job of explaining the issues of taking advantage of parallelism within Beowulf software. --Richard Dragan

High Performance Parallel Database Processing and Grid Databases (Wiley Series on Parallel and Distributed Computing)

David Taniar, Clement H. C. Leung, Wenny Rahayu, Sushant Goel

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Editorial Review:

This book targets the theoretical/conceptual details needed to form a base of understanding and then delivers information on development, implementations, and analytical modeling of parallel databases. It includes key information on new developments with grid databases. Also uses a theoretical and practical balance to support in-depth study of parallel query processing offered by modern DBMS as well as hands on experience of parallel query algorithms development, implementation, and analysis.

Parallel Programming in OpenMP

Rohit Chandra, Leo Dagum, Dave Kohr, Dror Maydan, Jeff McDonald, Ramesh Menon

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Total reviews: 5 Average rating: 4.0 of 5

Editorial Review:

The OpenMP standard allows programmers to take advantage of new shared-memory multiprocessor systems from vendors like Compaq, Sun, HP, and SGI. Aimed at the working researcher or scientific C/C++ or Fortran programmer, Parallel Programming in OpenMP both explains what this standard is and how to use it to create software that takes full advantage of parallel computing.

At its heart, OpenMP is remarkably simple. By adding a handful of compiler directives (or pragmas) in Fortran or C/C++, plus a few optional library calls, programmers can "parallelize" existing software without completely rewriting it. This book starts with simple examples of how to parallelize "loops"--iterative code that in scientific software might work with very large arrays. Sample code relies primarily on Fortran (undoubtedly the language of choice for high-end numerical software) with descriptions of the equivalent calls and strategies in C/C++. Each sample is thoroughly explained, and though the style in this book is occasionally dense, it does manage to give plenty of practical advice on how to make code run in parallel efficiently. The techniques explored include how to tweak the default parallelized directives for specific situations, how to use parallel regions (beyond simple loops), and the dos and don'ts of effective synchronization (with critical sections and barriers). The book finishes up with some excellent advice for how to cooperate with the cache mechanisms of today's OpenMP-compliant systems.

Overall, Parallel Programming in OpenMP introduces the competent research programmer to a new vocabulary of idioms and techniques for parallelizing software using OpenMP. Of course, this standard will continue to be used primarily for academic or research computing, but now that OpenMP machines by major commercial vendors are available, even business users can benefit from this technology--for high-end forecasting and modeling, for instance. This book fills a useful niche by describing this powerful new development in parallel computing. --Richard Dragan

Topics covered:

• Overview of the OpenMP programming standard for shared-memory multiprocessors
• Description of OpenMP parallel hardware
• OpenMP directives for Fortran and pragmas for C/C++
• Parallelizing simple loops
• parallel do / parallel for directives
• Shared and private scoping for thread variables
• reduction operations
• Data dependencies and how to remove them
• OpenMP performance issues (sufficient work, balancing the load in loops, scheduling options)
• Parallel regions
• How to parallelize arbitrary blocks of code (master and slave threads, threadprivate directives and the copyin clause)
• Parallel task queues
• Dividing work based on thread numbers
• Noniterative work sharing
• Restrictions on work-sharing
• Orphaning
• Nested parallel regions
• Controlling parallelism in OpenMP, including controlling the number of threads, dynamic threads, and OpenMP library calls for threads
• OpenMP synchronization
• Avoiding data races
• Critical section directives (named and nested critical sections and the atomic directive
• Runtime OpenMP library lock routines
• Event synchronization (barrier directives and ordered sections)
• Custom synchronization, including the flush directive
• Programming tips for synchronization
• Performance issues with OpenMP
• Amdahl's Law
• Load balancing for parallelized code
• Hints for writing parallelized code that fits into processor caches
• Avoiding false sharing
• Synchronization hints
• Performance issues for bus-based and Non-Uniform Memory Access (NUMA) machines
• OpenMP quick reference

Parallel Scientific Computing in C++ and MPI: A Seamless Approach to Parallel Algorithms and their Implementation

George Em Karniadakis, Robert M. Kirby II

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Customer Reviews:
Total reviews: 4 Average rating: 4.0 of 5

101 things to do with your pet supercomputer 4 out of 5 stars.
8 of 8 people found this review helpful.

Scientific parallel computing is what this book is all about, and it does a very good job kneading MPI into the mathematical dough. The book assumes knowledge of mathematics (through Calculus, in some sections, and quite a bit of linear algebra) and little programming experience. This is not a book on C++ programming (not even close, and it does not pretend to be), nor is it a book on MPI programming, parallel computer design, or even the setting up of a suitable software development environment. In fact, it assumes all of the above, which leaves the way uncluttered for the exploration of the application of parallel algorithms upon familiar mathematical concepts.

An introductory C++ section is provided to get things rolling, though the level of C++ in the book amounts to simple classes and cin / cout in lieu of C's `printf' nonsense. This is good news, because it maintains the book's focus on the parallelization of mathematical procedures rather than on the irrelevant details of how cute it would all look wrapped up in a needlessly complex object hierarchy. Basic applied C++ and MPI, as and when needed to get the job done.

I personally use this text at home on my home-grown parallel Linux computer to investigate the partitioning of algorithms, such as going from a complex function to a Taylor series that may then be distributed to compute nodes.

Further MPI, C/C++, and extremely high-level parallel concepts are introduced through the book in a natural progression, as the problems at hand require their introduction. This keeps the book from being bogged down and off-topic. Kudos to the authors for remaining on course through a sea of such tempting distractions.
The book is the `how'. BYOW:)
ps: my CD was damaged so couldn't evaluate it.
4-stars

Editorial Review:

This book provides a seamless approach to numerical algorithms, modern programming techniques and parallel computing. These concepts and tools are usually taught serially across different courses and different textbooks, thus observing the connection between them. The necessity of integrating these subjects usually comes after such courses are concluded (e.g., during a first job or a thesis project), thus forcing the student to synthesize what is perceived to be three independent subfields into one in order to produce a solution. The book includes both basic and advanced topics and places equal emphasis on the discretization of partial differential equations and on solvers. Advanced topics include wavelets, high-order methods, non-symmetric systems and parallelization of sparse systems. A CD-ROM accompanies the text.

Grid Computing (On Demand Series)

Joshy Joseph, Craig Fellenstein

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Total reviews: 4 Average rating: 4.0 of 5

Editorial Review:

According to John Patrick, IBM's vice-president for Internet strategies, "thenext big thing will be grid computing."The purpose of this book will be to describe several interesting and uniqueaspects of this exciting new topic. Grid Computing is a type of parallel anddistributed system set-up that enables and encourages the sharing ofgeographically dispersed resources. In many ways, it represents theconvergence of supercomputing and web services. The book highlights manyachievements in this innovative computer science field, and it is intended to beof value to a wide spectrum of readers around the world regardless. IBM israpidly establishing itself as the global leader in the topic of Grid Computing.This book not only address IBM's leadership progress in the field, but otherglobal enterprise initiatives, specific areas of interests, synergies between manyenterprise partners in this field, and current/future deliveries in the field ofGrid Computing. Today, there is no other book like this one that explains thepromise and IBM's plans for this important initiative.

Algorithms Sequential & Parallel: A Unified Approach (Electrical and Computer Engineering Series)

Russ Miller, Laurence Boxer

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Total reviews: 3 Average rating: 5.0 of 5

Editorial Review:

With multi-core processors replacing traditional processors and the movement to multiprocessor workstations and servers, parallel computing has moved from a specialty area to the core of computer science. In order to provide efficient and cost-effective solutions to problems, algorithms must be designed for multiprocessor systems. Algorithms Sequential and Parallel: A Unified Approach 2/E provides a state-of-the-art approach to an algorithms course. The book considers algorithms, paradigms, and the analysis of solutions to critical problems for sequential and parallel models of computation in a unified fashion. This gives practicing engineers and scientists, undergraduates, and beginning graduate students a background in algorithms for sequential and parallel algorithms within one text. Prerequisites include fundamentals of data structures, discrete mathematics, and calculus. FEATURES: • Discusses practical applications of algorithms (e.g., efficient methods to solve critical problems in computational geometry, image processing, graph theory, and scientific computing) • Provides information updated from the previous edition, including discussions of coarse-grained parallel computing • Mathematical tools are developed in the early chapters • Includes exercises at the end of each chapter that vary in difficulty, from confidence-building problems to research-oriented problems

Numerical Recipes in Fortran 90, Vol. 2

William H. Press, Saul A. Teukolsky, William T. Vetterling, Brian P. Flannery

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Total reviews: 3 Average rating: 3.0 of 5

Program listings 1 out of 5 stars.
23 of 23 people found this review helpful.

Although the original FORTRAN77 version of Numerical Recipes is highly acclaimed (and rightfully so, it is really worth every buck) I do not recommend this FORTRAN90 book. I was very disappointed when I received it. A huge part of the book only contains F90 program listings for the same routines that are derived and discussed in detail in Volume I (F77). The two new introductory chapters make it not worth buying the book. Instead, get the Numerical Recipes CD-ROM which includes the source code for C, F77, F90 and other languages and maybe a good introductory or reference book on F90.

(The review of "oblinqued" down below is obviously referring to the original book as the F90 book was not available in 1991).

Editorial Review:

The second volume of the Fortran Numerical Recipes series, Numerical Recipes in Fortran 90 contains a detailed introduction to the Fortran 90 language and to the basic concepts of parallel programming, plus source code for all routines from the second edition of Numerical Recipes. This volume does not repeat any of the discussion of what individual programs actually do, the mathematical methods they utilize, or how to use them.

Win32 Multithreaded Programming

Aaron Cohen, Mike Woodring

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Total reviews: 11 Average rating: 4.5 of 5

Editorial Review:

Many Windows developers still write code as if their application is a single entity that, while it is running, has complete control of all system resources. This legacy from the days of DOS means that developers frequently fail to take advantage of Win32's support of multiple threads of execution to improve their application's performance or to enhance its functionality. For instance, a main thread can handle interactions with the user, while a background "worker" thread can handle repainting the application window or performing some background calculations. But multithreaded programming means more than adding threads; it also requires that the code be thread-safe.

Win32 Multithread Programming explains the concepts of multithreaded programs, thus providing the developer with the knowledge necessary to skillfully construct efficient and complex applications. From basic thread synchronization using mutexes and semaphores, to advanced topics like creating reusable thread pools or implementing a deferred processing queue, the book uses real-world applications and carefully constructed examples to illustrate the principles of multithreaded programming. Some of the topics include:

• How the Windows operating systems handle threads
• Multithreading primitives in the Win32 API
• Techniques for generating thread-safe dynamic link libraries
• Advanced techniques for thread synchronization
• Basic scenarios for synchronizing threads
• Common designs for building multithreaded user interfaces

The CD-ROM accompanying the book features Mcl, the authors' C++ class library for multithreaded programming, which both wraps multithreaded API functions and easily supports more complex multithreaded scenarios. For programmers using MFC, an additional library, Mcl4Mfc, is included for MFC compatibility.

Win32 Multithread Programming is an essential resource for any developer interested in learning about Win32 multithreaded programming in order to create high-performance, effective applications.