Product Description
High Perfomance Computing and the Art of Parallel Computing provides a non-technical introduction to High Performance Computing applications together with advice about how beginners can start to write parallel programs. Using case studies to show where HPC has already been used and providing examples for other areas of application to geography, GIS and the social sciences, it provides a plain and practical introduction to a subject that is usually surrounded by complex computer jargon. ... Read more

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High Quality Content by WIKIPEDIA articles! X10 is a programming language being developed by IBM at the Thomas J. Watson Research Center as part of the PERCS project funded by DARPA's High Productivity Computing Systems (HPCS) program. Its primary authors are Kemal Ebcioglu, Vijay Saraswat, and Vivek Sarkar. X10 is designed specifically for parallel programming. It is an "extended subset" of the Java programming language, strongly resembling it in most aspects, but featuring additional support for arrays and concurrency. X10 uses a Partitioned global address space model. It supports both object-oriented and non-object-oriented programming paradigms. ... Read more

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High Quality Content by WIKIPEDIA articles! In computer science, a semaphore is a protected variable or abstract data type which constitutes a classic method of controlling access by several processes to a common resource in a parallel programming environment. A semaphore generally takes one of two forms: binary and counting. A binary semaphore is a simple "true/false" (locked/unlocked) flag that controls access to a single resource. A counting semaphore is a counter for a set of available resources. Either semaphore type may be employed to prevent a race condition. On the other hand, a semaphore is of no value in preventing resource deadlock, such as illustrated by the dining philosophers problem. ... Read more

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Parallel computing has become a reality; this book brings together the work of researchers who share the goal of making parallel programming easier and more accessible. Five main areas are covered:

Papers in the environments area describe a system called MP, and a graphical programming environment. The area of visualisation and monitoring is the largest. Subjects include the PRISM system from Thinking Machines Corporation, validation using program models and event traces, and a variety of generic visualisation and monitoring systems. Also included is the adaptation of a portable performance measurement system to a multi-transputer monitoring system. Models papers include the Enterprise model, interprocessor communication using shared objects, a system called SYMPLE and a virtual processor model for massively parallel systems. The applications papers concentrate primarily on ways to help the programmer develop scalable applications. In the area of tools and toolkits there are papers describing the SIGMA II program analysis and restructuring library, and a debugger called HyperDEBU for parallel logic programs. ... Read more

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Integrating associative processing concepts with massivelyparallel SIMD technology, this volume explores a model for accessingdata bycontent rather than abstract address mapping. ... Read more

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This comprehensive new text from author Kai Hwang covers four important aspects of parallel and distributed computing -- principles, technology, architecture, and programming -- and can be used for several upper-level courses. ... Read more

Customer Reviews (3)

Very interesting conceptual basis, but
The information provided in this book are a bit out of date, the description way to light harted, no pictures of the physical arrangement of the physical implementation are provided.
Most of the graphics and graphs are of appaling quality.
The web references--even the updated ones on the first autors home-page--are out of date.

Don't get me wrong: I learned a lot about computer architecture from Prof. Hwang's other books way back in the eighties, this one has a very interesting conceptual basis but is lacking on needed detail. You can learn a lot from this book, but you need the whole of the web to supplement it; for this the price is way over the top.

Scalable Parallel Rubbish
The only reason to buy this book is under force. Aka taking a course where this book is mandatory. Its ill planned, ill conceived and not organized in a proper way.

Useless opus
This is the worst book that I ever read. The authors did not even bothered to proofread it. One would think that people writing on the subject of system architecture will be organizing the material logically.Not these two clowns.The only reason you might want to spend yourhard-earned money is if you are under the duress of taking professor'sHwang course at USC.This is the only way they can cell this worthlessbook. Wish I could return it to the publisher. P.S. A good example on hownot to write the computer book (or any technical text book). POd ... Read more

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This set includes Parallel Computer Architecture: A Hardware/Software Approach by David Culler and J.P. Singh with Anoop Gupta and Parallel Programming with MPI by Peter Pacheco. ... Read more

Product Description
This is the first book to explain the language Unified Parallel C and its use. Authors El-Ghazawi, Carlson, and Sterling are among the developers of UPC, with close links with the industrial members of the UPC consortium. Their text covers background material on parallel architectures and algorithms, and includes UPC programming case studies. This book represents an invaluable resource for the growing number of UPC users and applications developers. More information about UPC can be found at: http://upc.gwu.edu/ ... Read more

Customer Reviews (1)

interesting superset of C, but why did it not extend C++?
Think of this book as the equivalent of Kernighan and Ritchie's epochal book on C programming. It aspires to the same role, with respect to Unified Parallel C. Clearly, for ease of understanding the book, you should have already programmed in C. Which is a pretty safe assumption, as C has been and still is one of the most common languages.

UPC is a superset of C, so all existing C programs can run under UPC recompilation. The crucial difference is that UPC permits a set of threads, where these are fixed at runtime. A thread can have private variables, that other threads cannot access. Or it can have shared variables, so that threads can easily communicate. The latter is a nice aspect. Perhaps you have dealt with interprocess communications? Under unix, there are all sorts of complicated methods to do so. Locks, semaphores etc. By contrast, the text shows that accessing shared variables in UPC is quite easy.

Perhaps the biggest drawback about UPC is that it is not object oriented. The scaling difficulties with C code are well known, and proved crucial in driving the use of C++ and Java, and C# for that matter. If only the designers had chosen to have UPC extend C++, instead of C. But perhaps there were performance drawbacks in doing so, or that the resultant UPC compiler would have been too hard to build? The book avoids this discussion. ... Read more

Product Description
This book provides a basic, in-depth look at techniques for the design and analysis of parallel algorithms and for programming them on commercially available parallel platforms.Principles of parallel algorithms design and different parallel programming models are both discussed, with extensive coverage of MPI, POSIX threads, and Open MP.This second edition includes two new chapters on the principles of parallel programming and programming paradigms, as well as new information on portability.For programmers wanting to gain proficiency in all aspects of parallel programming. ... Read more

Customer Reviews (7)

Solid material but not clean enough
I like this book very much. I have used it for a course I am about to finish.

It provides a solid foundation for anyone interested in parallel computing on distributed memory architectures. Although there is some material on shared memory machines, this material is fairly limited which might be something the authors should change for a 3rd edition given the times we're living in.

The complaint I would raise is that the book doesn't always feel "clean". It's hard to give a concrete example but sometimes you really have to spend some time to understand where a communication time complexity comes from even though the author's refer to a table of communication time complexities. Why? Because the table is based on that the underlying architecture is a hypercube which isn't really made explicit anywhere (?).

Too many mistakes.
I agree with the other reviewers who have said that this book is sloppy. There are just far too many mistakes for a 2nd edition book; very discouraging in an Addison-Wesley print.

The content is OK, and fairly thorough, but as another reviewer noted, there's considerable handwaving going on in some of the explanations.

Bottom line: a cleaned-up 3rd edition could be a very good textbook. Too bad I'm stuck with the 2nd edition :(

Worst text book ever written..
This book is extremely poorly written.The authors glaze over complex equations and magically come up with answers that don't make any sense.For example, to anyone having taken a prior architecture course the author's are completely wrong in the majority of cache performance analysis done early on in the book.Problems associated with that topic force the reader to dumb-down quite a bit to achieve their "expected" answer.

The user is left in most cases to derive the bizarre math that is involved through the authors' hand-waiving.
One of my personal favorites is from a formula derivation given on page 340, the sequence follows from the text as:

n^2=Ktwnp,
n=Ktwp,
n^2=K^2tw^2p^2,<--what, did I miss something here?
W=K^2tw^2p^2,

On top of that there are numerous typos in the sparse visual examples that do exist.Thus it makes it even more confounding to read through.

If you are evaluating the text for a possible parallel computing course.Don't waste your time or money with this text, your students will thank you.If you are student looking to take a class that uses this text...dropping a brick on your foot might be more enjoyable.If you think I'm a disgruntled student trying to seek revenge, I'm not.I did fine in the course, and I just want to make sure that no one else gets blind-sided by the non-sensical garbage that is this text.If there was a negative rating...this would be below 1 star.

Better read Journals than this book
I bought the book a few months ago as textbook for my semester class in high performance computing.After reading the first 3 chapters I realized that this book is a waste.The examples are only solved partially, a lot of jargons (they should have put the terminology in separate table, maybe).

I was hoping, by reading the book I'd learn something essential and got the basic philosophy of high-performance computing/parallel processing.Instead, I got more confused than before reading it! (I used to be real-time software programmer, so the field is not totally new to me).The authors tried to put everything in this small 633-pages book.

Even my professor said it is useless to read the book and refer us to other papers [Robertazzi's papers], and yes, these IEEE/ACM papers are much clearly explained and understood!I also found that a website is much better explaining the concept.Another book is also I guess better: "Fundamentals of Parallel Processing" by Harry F. Jordan and Gita Alaghband.

Don't waste your money on this book.

Great book, but...
Yes, this is definitely a good book. The discussions on some of the topics are in depth. Parallel algorithm designs are considered from several different angles (mostly from theoretical performance's point of view). One definitely has to get some backgrounds in algorithms before one can digest the contents of this book, thus I recommend this book only for juniors, seniors, graduate students. From the theoretical point of view this book is great, but from the "experimental" point of view is not. It lacks examples and exercises on doing the theory in the actual parallel computers. Thus you have to develop your own MPI (or openMP) understanding and apply it to the topics discussed in this book. ... Read more

Product Description
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. ... Read more

Customer Reviews (3)

Should be improved.
The authors attempted to combine introductory material in C++, numerical methods and parallel computing. That is quite a brave endevaour. They certainly break the new ground writing an introductory material for a "simulation scientist", but I believe they have achieved mixed success.

On the one hand, the material they present on all subjects is really top quality, packed with 100% usefull information. Bibliography is also very good and usefull. But the organisation of the book is quite confusing. They introduce all the topics toogether - throughtout the book. Hence each chapter introduces some numerical algorithms, few new concepts in C++ and eventually MPI. I beleive a novice would experience serious difficulties following it. For example, authors introduce objects before introducing curly braces "{}" as scope delimiters and before semicolon ";" as statement delimiters.

Further, very soon after introducung the very basic concepts in C++, the authors move on to BLAS. BLAS is usefull, of course, but a novice in C++ may wonder why does he needs libraries written in Fortran, if C++ is a language of the choice for numerical computations. (At least it is claimed so by the authors).

Another confusing example is the one of memory memory access. In section 2.2.6 Memory Management, (pg. 41) the authors introduce basic concepts of memory management and how can loop constructs influence the efficiency of the code. Very usefull indeed, no question about it. But very soon bellow, in section 2.2.8 Exploiting the Structure of the Sparse Matrices, they come up with the claim (pg. 58): "... optimization-savy individuals, as the old saying goes, often miss the forest for the threes" :-( Hence, a novice reader might think: "Well, why do I need to worry about the memory management explained just 17 pages above?".

My most serious critic of this book by far (and I hope the authors will read this) are the contents pages. The contents list only chapters and first level sub-chapters. Secind level chapters are not present!!! That makes the book very hard to use as a reference material. That is really a pitty, since there is some good material in it which is hard to find and might stay hidden. (For example, the chapter I mentioned above: 2.2.6 Memory management is NOT in the contents, so I had to browse slowly throught the book to find it and refer it here). I suggest the authors introduce: "Contents at a glance" (the present one) and a "Detailed Contents", where one could find references to all the chapters in the book. The contents is THE reason why I gave this book 3 stars instead of 4. One it lost on the confusing organisation of the book.

I think the authors should have organised the book in four parts: 1 - Numerical algorithms, 2 - C++ and 3 - Parallel computing with MPI, 4 - Advanced topics. Part 1 could introduce numerical algorithms and have pointers to their implementations in Part 2 and corresponding parallel implementations in Part 3. Part 2 and 3 could have started with introductions, which a reader already familiar with those subjects, could skip. Part 4, could bring advanced topics, such as optimisation, BLAS, etc.

Bottom line, it is:

- brave and usefull endevaour,
- full of excellent material,
- organized confusingly,
- and has a very poor contents.

Buy it if you are simulation scientist or teacher, but prepare to struggle with its organisation and contents.

Combining mathematics with modern computing
The book contains advanced numerical mathematics algorithms and
fundamental elements of parallel computation.
It will be useful for those academic instructors who believe that students should be shown the entire solution process
from mathematical problem definition to computer implementation. It has been used as a textbook at several leading American and European universities.
The authors professors Karniadakis and Kilby are innovatorswho demonstrate that combining education ofapplied mathematics with computer science is possible and extremely useful for students and their future employers.

Great book to get acquainted with numerical analysis
This book is great in describing some of the most important concepts and algorithms needed for the beginning numerical analyst.The book claims that it can be picked up by a complete novice and teach C++, MPI, and scientfic computing.I would say that the math goes very quickly and not quite as rigorous as necessary for the typical novice.The C++ is pretty basic but still the book leaves the reader a sense of confusion.This is largely because the book treats a large amount of the library functions as black boxes.The MPI starts very basic and gradually introduces the major concepts.

My recommendation for anyone reading the book is to supplement it with a good linear algebra book (such as Demmel) and book on C++ (The C++ programming language).For further study on MPI, Using MPI would be a good supplement. That way whenever you have a concept that isn't fully described, you have a source to get it from.

The book gets a high rating for going over the right content and doing so in a applied manner that gives the reader the skills to become a numerical analyst. ... Read more

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This text includes introductory material,exercises, more depth of analysis and coverage of the most successful current parallel computers, including the Connection Machine's CM-S and Intel's Paragon XP/S. ... Read more

Product Description

Innovations in hardware architecture, like hyper-threading or multicore processors, mean that parallel computing resources are available for inexpensive desktop computers. In only a few years, many standard software products will be based on concepts of parallel programming implemented on such hardware, and the range of applications will be much broader than that of scientific computing, up to now the main application area for parallel computing.

Rauber and Rünger take up these recent developments in processor architecture by giving detailed descriptions of parallel programming techniques that are necessary for developing efficient programs for multicore processors as well as for parallel cluster systems and supercomputers. Their book is structured in three main parts, covering all areas of parallel computing: the architecture of parallel systems, parallel programming models and environments, and the implementation of efficient application algorithms. The emphasis lies on parallel programming techniques needed for different architectures.

The main goal of the book is to present parallel programming techniques that can be used in many situations for many application areas and which enable the reader to develop correct and efficient parallel programs. Many examples and exercises are provided to show how to apply the techniques. The book can be used as both a textbook for students and a reference book for professionals. The presented material has been used for courses in parallel programming at different universities for many years.

Product Description
Expert guidance for those programming today’s dual-core processors PCs

As PC processors explode from one or two to now eight processors, there is an urgent need for programmers to master concurrent programming. This book dives deep into the latest technologies available to programmers for creating professional parallel applications using C#, .NET 4, and Visual Studio 2010. The book covers task-based programming, coordination data structures, PLINQ, thread pools, asynchronous programming model, and more. It also teaches other parallel programming techniques, such as SIMD and vectorization.

• Teaches programmers professional-level, task-based, parallel programming with C#, .NET 4, and Visual Studio 2010
• Covers concurrent collections, coordinated data structures, PLINQ, thread pools, asynchronous programming model, Visual Studio 2010 debugging, and parallel testing and tuning
• Explores vectorization, SIMD instructions, and additional parallel libraries

Master the tools and technology you need to develop thread-safe concurrent applications for multi-core systems, with Professional Parallel Programming with C#. ... Read more

Product Description
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

Customer Reviews (1)

up to date view of parallel computing
Scott offers the student an integrated and up to date view of parallel computing. It takes into account the type of hardware currently available. From specialised CPUs to mass produced Intel and AMD chips. Different types of architecture are explained. In the last 25 years, there has been much experimentation with various ways to cluster computers to work on a common task, and Scott shows the best available.

At the software level, you can get an idea of how to custom code to take advantage of multiple CPUs. Certainly, there are compilers that take standard code, which normally runs on 1 CPU, and can, to some extent, produce binaries for concurrent operation. But you can also take advantage of your expert knowledge of your problem and algorithm, to split the latter's code accordingly. ... Read more