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 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
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

Product Description
This book is devoted to the investigation of a special topic in theoretical computer science - communication complexity as an abstract measure of the complexity of computing problems. Its main aim is to show how the theoretical study of communication complexity can be useful in the process of designing effective parallel algorithms. The author shows how to get important information about the parallel complexity (parallel time, the number of processors, the descriptional complexity of the topology of the parallel architecture) of specific computing problems from knowledge of their communication complexity. The book is written as a textbook for undergraduate and graduate students and provides a careful explanation of the subject as well as motivation for further research. ... 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

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
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

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
Take an in-depth look at techniques for the design and analysis of parallel algorithms with this new text. The broad, balanced coverage of important core topics includes sorting and graph algorithms, discrete optimization techniques, and scientific computing applications. The authors focus on parallel algorithms for realistic machine models while avoiding architectures that are unrealizable in practice. They provide numerous examples and diagrams illustrating potentially difficult subjects and conclude each chapter with an extensive list of bibliographic references. In addition, problems of varying degrees of difficulty challenge readers at different levels. Introduction to Parallel Computing is an ideal tool for students and professionals who want insight into problem-solving with parallel computers. Features: *Presents parallel algorithms in terms of a small set of basic data communication operations, greatly simplifying the design and understanding of these algorithms. *Emphasizes practical issues of performance, efficiency, and scalability. *Provides a self-contained discussion of the basic concepts of parallel computer architectures.*Covers algorithms for scientific computation, such as dense and sparse matrix computations, linear system solving, finite elements, and FFT. *Discusses algorithms for combinatorial optimization, including branch-and-bound, unstructured tree search, and dynamic programming. *Incorporates various parallel programming models and languages as well as illustrative examples for commercially-available computers. Audience: Junior/Senior/Graduate Computer Science and Computer Engineering majors Professional/Reference Courses: Distributed Computing Parallel Programming Parallel Algorithms Prerequisites: Operating Systems and Analysis of Algorithms 0805331700B04062001 ... Read more

Customer Reviews (4)

Just great
Excellent introduction to the field, specially for the beginner. There is no other book as clear and concise as this one. If you need an introduction to parallel computing / programming, buy the second edition of this book now!

Essential 4 any prospective parallel computing professional
I bought this book when I was a 2nd grade CS student. I planned to start my research project in supercomputing field. So I decided to study the aspects of parallel computing starting by its concepts and programming. As a programmer I found that I would need the general view before coding. Kumar's book is great in which it gives you generalized overview of hardware and software architectures. He and his contributors don't take care of what system nor language you're using. Instead, they want you to learn Parallel Programming. Scientific and non-numerical algorithms are overviewed and explained mathematically. They prove everything they state by using mathematics. I don't know any better way. Do you? It's worth every penny.

Good book on parallel computing
This book is a very good one for the parallel computing fields. The most interesting parts of the book to me are the parallel alogrithms design & analysis. The ideas are explained clearly and the exercises are nice too. I would like to recommend this book to all my friends who are interested in parallel computing.

Great details and insightful
This one is must for someone who has needs an introductory course for parallel computing. It dealt with the fundamental of parallel computing in terms of algorithms decide. ... Read more

Product Description

This book targets development of efficient parallel computational methods for different scientific and technical applications. Readers who wish to design and implement efficient solutions on parallel and distributed computer systems are given insight into the theory of the computational methods through practical application being emphasized throughout. Features: Discusses development of algorithms for different applications plus other aspects related to parallel numerical solution of PDEs (e.g. grid refinement). Considers other numerical applications such as data retrieval by linear algebra approach and quasi Monte-Carlo methods. Covers molecular dynamics, computational quantum physics, analysis of bio-signals and image and video coding. Chapters overviews and conclusions with a discussion on future work. This concise volume provides the state-of-the-art in parallel and distributed computing, and is a must-read for practitioners, researchers and graduate students.

Product Description
This book provides various parallel programming approaches and analyses of their performances in detail.The book covers the timely topic of cluster programming, interesting to many programmers due to the recent availability of low-cost computers.Useful as a professional reference for programmers and system administrators. ... Read more

Customer Reviews (6)

Typical CS department book
I find this book to be poorly written.The examples are insufficient and the content is only a cursory introduction to parallel programming.My recommendation is to reaearch alternative publications relating to Parallel Programming.

Good book at senior or early grad school level
The book serves as a good introduction to several advanced computing techniques.It isn't for beginners in computer science or networking, and it isn't worth the list price.Unfortunately, the topic isn't something you are likely to find in a career, so it isn't useful to general computer science students.
It is great as a learning book, in-depth enough that you could use it for on-the-job learning.It covers the things you need to know for real-world use.

I would have given it 5 stars, except it isn't all that great as a reference; you will probably end up using online help for whatever communications package you use.It's the kind of book you read once or twice, then give away to younger collegues.

Wonderful book but don't pay full price
This is a really good introduction to Parallel Programming techniques, but its overpriced. Buy it used.

This book is used as a textbook in many computer science departments (hence the inflated price) but I found that even with the minimal computer science education I've had (mostly from self-study) I learned a lot and did not find this book overly difficult to follow.

Not for beginners
This would be a great reference manual, but I am using this test in my parallel processing course and the pseudocode is confusing and the MPI functions are introduced with poor descriptions.

Clear and informative book, but...
The book does quite well in explaining the concepts of parallel computing and programming, and I have very few complaints about anything actually written in the book.(A companion CD with some sample MPI/PVM programs would have been nice.)However, as well as this book is written and organized, it is almost comical to have this size of book (paperback, at that) costing nearly $...If the book would have cost about $.. less and had the companion CD, it would have been five stars. ... Read more

Product Description

Parallel Computing is a compelling vision of how computation can seamlessly scale from a single processor to virtually limitless computing power. Unfortunately, the scaling of application performance has not matched peak speed, and the programming burden for these machines remains heavy.The applications must be programmed to exploit parallelism in the most efficient way possible. Today, the responsibility for achieving the vision of scalable parallelism remains in the hands ofthe application developer.

This book represents the collected knowledge and experience of over 60 leading parallel computing researchers.They offer students, scientists and engineers a complete sourcebook with solid coverage ofparallel computing hardware, programming considerations, algorithms, software and enabling technologies, as well as several parallel application case studies. The Sourcebook of Parallel Computing offers extensivetutorials and detailed documentation of the advanced strategies produced by research over the last two decades
application case studies. The Sourcebook of Parallel Computing offers extensivetutorials and detailed documentation of the advanced strategies produced by research over the last two decades

* Provides a solid background in parallel computing technologies
* Examines the technologies available and teaches students and practitioners how to select and apply them
* Presents case studies in a range of application areas including Chemistry, Image Processing, Data Mining, Ocean Modeling and Earthquake Simulation
* Considers the future development of parallel computing technologies and the kinds of applications they will support ... Read more

Customer Reviews (1)

Parallel Computing - An inside out by Jack Dongarra!
...This book builds on the important work done at the Center for Research on Parallel Computation and within the academic community for over a decade. It is a definitive text on parallel Computing and should be a key reference for students,
researchers and practitioners in the field. The Sourcebook for Parallel Computing gives a thorough introduction to parallel applications, software technologies, enabling technologies, and algorithms. I highly recommend this great book to anyone
interested in a comprehensive and thoughtful treatment of the most important issues in parallel computing. The Features & Benefits of this book includes...but not limited to 1) Providing a solid background in parallel computing technologies 2) Examining the technologies available and teaches students and practitioners how to select and apply them 3) Presenting case studies in a range of application areas including Chemistry, Image Processing, Data Mining, Ocean Modeling and Earthquake and 4) Considering the future development of parallel computing technologies and the kinds of applications they will support. Worth buying this book, your money is invested! ... Read more

Product Description
Written by top researchers Larry Snyder and Calvin Lin, this highly anticipated first edition emphasizes the principles underlying parallel computation, explains the various phenomena, and clarifies why these phenomena represent opportunities or barriers to successful parallel programming. Introduction: Parallelism = Opportunities + Challenges; Introduction: Parallelism = Opportunities + Challenges; Reasoning about Performance; First Steps Towards Parallel Programming; Scalable Algorithmic Techniques; Programming with Threads; Local View Programming Languages; Global View Programming Languages; Assessing Our Knowledge; Future Directions in Parallel Programming; Capstone Project: Designing a Parallel Program. For all readers (particularly software engineers and computer system designers) interested in multi-core architecture and parallel programming. ... Read more

Customer Reviews (4)

Overpriced, Dated Content
This book is overpriced and the content is very very dated. Who wants to learn ZPL in today's world? If you want to learn about parallelism pickup a copy of Patterns for Parallel Programming Timothy G. Mattson, Beverly A. Sanders, Berna L. Massingill. Don't waste ur money on this book.

Riddled with errors
This book is absolutely riddled with errors. The sheer density of errors make the book unusable for any in-depth study.

abstracts essential ideas
Years ago I briefly worked on a hypercube, and when I got this book, I wondered how it had fared. Alas, the hypercube, at least under this name, rated no mention. Though there is a passing reference to a binary 3 cube which is a 3 dimensional hypercube.

The authors explain the current state of multiprocessor architectures. The few remaining computer CPU makers have efforts in this field. Intel, AMD, Sun and IBM. The book describes qualitatively the salient aspects of each. One nice thing about the discussion is that it focuses on this, without drowning you in unnecessary hardware details. This turns out to be a key theme of the book. It abstracts out essential hardware properties, so that you can appreciate these and apply the book's ideas without being tied to any given chip.

The book also describes an important type of multiprocessor. Cluster machines, where each node is typically some off the shelf CPU, buffed up with a lot of local memory. The key differences between clusters are often related to how the nodes are hooked to each other, by some type of bus or crossbar. Affordability is an important property of clusters; thus the maximal use of commodity hardware. (The hypercube that I mentioned earlier would be a cluster.)

For a programmer, there is one overriding idea that you should get from the book. For optimal performance, minimise the internodal communication, compared to the use of a node's cache. The access time of the former can be 2-5 orders of magnitude slower. Details vary with the given architectures, of course. But typically nothing else comes close, in terms of effects on your throughput.

excellent introductory text, both timely and timeless
I have done parallel programming on a variety of machines for many years, and have written some widely-used parallel numerical software. Now that I have graduate students of my own and teach courses in numerical and parallel computation, I've been hoping for a book like this to help my students understand the basic techniques, concepts, and problems common to most parallel programming, as well as to use as a reference for courses, without resorting to manuals bogged down in the details of specific architectures.A colleague of mine (who has a large company developing parallel tools and who for many years has taught a course on parallel scientific computing) pointed me to this text, and I'm much more pleased with it than with any recent book on the subject that I can recall.

The authors of this book clearly introduce key concepts of extracting parallelism, load balancing, performance analysis, and memory management with a number of well-selected examples and advice clearly stemming from long experience in the field.They describe numerous general principles in an accessible way, without getting bogged down in the theoretical models of dubious utility that are too common in this field.The book is timely, in that it exhibits a clear awareness of current architectural trends, but remains rightly focused on timeless ideas.

I suppose the authors cannot be blamed for devoting a chapter to the parallel programming language they have developed in their own work (ZPL), and it is balanced by chapters on the current popular low-level techniques like MPI and threads as well as brief discussions of other proposed high-level languages (although the mention of Cilk is a bit too brief for my tastes).But the real strength of the book is that it is not tied too closely to any particular language or implementation, and instead helps you to recognize fundamental ideas as they appear in various forms.

I do wish the book were a bit cheaper, but high textbook prices seem to be a fact of life.A more basic introduction to caches, and the connection between memory locality on serial computers and locality on parallel machines, would probably be helpful.The mention of the powerful idea of work stealing is too brief.And I'm sure I'll find many other things I dislike as I continue to use this book, but overall I'm quite happy with this book as a way to get students into this subject. ... Read more

Product Description
This is the first book on parallel MATLAB and the first parallel computing book focused on the design, code, debug, and test techniques required to quickly produce well-performing parallel programs.

MATLAB is currently the dominant language of technical computing with one million users worldwide, many of whom can benefit from the increased power offered by inexpensive multicore and multinode parallel computers. MATLAB is an ideal environment for learning about parallel computing, allowing the user to focus on parallel algorithms instead of the details of implementation.

Parallel MATLAB for Multicore and Multinode Computers covers more parallel algorithms and parallel programming models than any other parallel programming book due to the succinctness of MATLAB. It presents a hands-on approach with numerous example programs; wherever possible, the examples are drawn from widely known and well-documented parallel benchmark codes that are representative of many real applications across the field of technical computing.

Audience: Intended for professional scientists and engineers, as well as undergraduate or graduate students, who use MATLAB. It is suitable as either the primary book in a parallel computing class or as a supplementary text in a numerical computing class or a computer science algorithms class.

Contents: List of Figures; List of Tables; List of Algorithms; Preface; Acknowledgments; Part I: Fundamentals: Chapter 1: Primer: Notation and Interfaces; Chapter 2: Introduction to pMatlab; Chapter 3: Interacting with Distributed Arrays; Part II: Advanced Techniques: Chapter 4: Parallel Programming Models; Chapter 5: Advanced Distributed Array Programming; Chapter 6: Performance Metrics and Software Architecture; Part III: Case Studies: Chapter 7: Parallel Application Analysis; Chapter 8: Stream; Chapter 9: RandomAccess; Chapter 10: Fast Fourier Transform; Chapter 11: High Performance Linpack; Appendix: Notation for Hierarchical Parallel Multicore Algorithms; Index ... Read more

Product Description
Technological improvements continue to push back the frontier of processor speed in modern computers. Unfortunately, the computational intensity demanded by modern research problems grows even faster. Parallel computing has emerged as the most successful bridge to this computational gap, and many popular solutions have emerged based on its concepts, such as grid computing and massively parallel supercomputers. The Handbook of Parallel Computing and Statistics systematically applies the principles of parallel computing for solving increasingly complex problems in statistics research.

This unique reference weaves together the principles and theoretical models of parallel computing with the design, analysis, and application of algorithms for solving statistical problems. After a brief introduction to parallel computing, the book explores the architecture, programming, and computational aspects of parallel processing. Focus then turns to optimization methods followed by statistical applications. These applications include algorithms for predictive modeling, adaptive design, real-time estimation of higher-order moments and cumulants, data mining, econometrics, and Bayesian computation. Expert contributors summarize recent results and explore new directions in these areas.

Its intricate combination of theory and practical applications makes the Handbook of Parallel Computing and Statistics an ideal companion for helping solve the abundance of computation-intensive statistical problems arising in a variety of fields. ... Read more

Customer Reviews (2)

Excellent Overview of the State of the Art
It came as somewhat of a surprise to the industry that coupling together several PC's enabled the construction of what was in effect a supercomputer at a small fraction of the cost.

What began twenty or so years ago has now influenced the design of CPU's and the intereconnection 'LANs' that facilitate the transfer of data between the processors. And this clearly hasn't stopped. The AMD Opteron CPU's and Intel's PCI-Express are simply the latest innovations in silicon, and more is coming.

From a system architecture standpoint, we have (and the book discusses) clusters, Grids, and distributed processor systems -- all of which are fairly loosely defined with plenty of room for very good discussions over several beer.

What this book brings is an excellent introduction into the state of the art in parallel computers as it exists today. As is often the case with books that are pushing the state of the art, it is written by a large numnber of experts and edited together. Each chapter covers a particular area in depth from the design of the hardware to the languages (primarily Fortran and Java), to the solution of a series of common problems that are frequent in several different application areas.

This book is an excellent summary of parallel computing as it exists today. It would be of particular help to the person responsible for writing the proposal for an organization to buy/build one. The book is probably a bit too advanced for a course at an undergraduate level, but would be excellent for first year graduate students in a wide variety of fields from computer science to bio-informatics, data mining, cryptography or any number of other fields requiring heavy duty computation.

brings together a comprehensive review
A sturdy review of the different geometries of parallel machines, and of how to program them. Examples are given of algorithms that can be efficiently ported to these machines. The handbook is useful in summarising a lot of results scattered over conference proceedings and journal papers. The range of applications described is impressive.

The text is probably suited for a graduate level course. A bit too specialised for most undergrad CS majors. ... Read more

Product Description
An analytical overview of the state of the art, open problems, and future trends in heterogeneous parallel and distributed computing

This book provides an overview of the ongoing academic research, development, and uses of heterogeneous parallel and distributed computing in the context of scientific computing. Presenting the state of the art in this challenging and rapidly evolving area, the book is organized in five distinct parts:

• Heterogeneous Platforms: Taxonomy, Typical Uses, and Programming Issues

• Performance Models of Heterogeneous Platforms and Design of¿Heterogeneous Algorithms

• Performance: Implementation and Software

• Applications

• Future Trends

High Performance Heterogeneous Computing is a valuable¿reference for researchers and practitioners in the area of high performance heterogeneous computing. It also serves as an excellent supplemental text for graduate and postgraduate courses in related areas.

  ... Read more

Product Description
Summarizes the results of the projects of the High Performance Computing Center Stuttgart for the year 2000. Provides an overview of the recent developments in high performance computing and simulation. A showcase of novel numerical algorithms and state-of-the-art modeling. DLC: High-performance computing--Germany. ... Read more

Product Description
An authoritative guide to today's revolution in "commodity supercomputing, " this book brings together more than 100 of the field's leading practitioners, providing a single source for up-to-the-minute information on virtually every key system issue associated with high-performance cluster computing.Amazon.com Review
High Performance Cluster Computing contains academicarticles concerning supercomputing collected from researchers aroundthe world. Though targeted primarily at graduate students andresearchers in computer science, the general reader may find greatvalue in its overview of the current state of high-performancecomputing.

Computer science experts address many aspects of highperformance computing, beginning with the state-of-the-art conceptsand basic terminology related to cluster computing. Theirinvestigations provide immediate solutions to engineering problemslike optimized node arrangements for low-cost workstations yokedtogether to solve problems in parallel. One article describes such acluster created for the Department of Energy that uses 9,000 PentiumCPUs to model nuclear detonations.

Various contributors alsoconsider the requirements necessary for improving parallel programs interms of speed and logic, including reductions in network latenciesand enhanced file and I/O access. One contributor even suggests thatNetwork RAM--unused RAM in systems on the same network--may somedaychallenge the hard disk for fast--and permanent--data storage.

Inall, High Performance Cluster Computing works as an up-to-date,central repository of current thinking on interconnecting computersand processors to improve speed and performance. It provides avaluable roadmap of the state of the art in computer science researchas well as some potential benefits for forward-looking corporatecomputing professionals. --Richard Dragan ... Read more

Customer Reviews (3)

The worst you can think of...
This books is utter rubbish : edited by Buyya and NOT written by Buyya. It's simply a compilation of research articles written by different authors.

Rajkumar buyya has written ONLY the first introductory chapter, so his knowledge about the subject is seriously questionable.

On the top of that in the entire book, there's no coherence or focus at all. It simply wanders from one author to another researcher.

I am teaching at a university in Master's program, and I regret having purchased the book.

If you're not sure of what I've written, simply go thru' the index and you'd find different authors.

An excellent source of information on cluster computing
I used the two books as part of a course which I taught at IIT Delhi during July-Dec 1999. The course was called "Special Topics in Computers" and was credited by Masters students from the Departmentsof Electrical Engineering and Computer Science.The idea behind the coursewas to introduce elements of Distributed and Clustered Computing tostudents who have already got some background in Computer Architecture.Inmy opinion, a single course in Computer Architecture at the Masters levelcannot do justice to the developments that have taken place in thisexciting field over the past decades.I have been teaching ComputerArchitecture at IIT Delhi for about 8 years now and find that the number oftopics that I have to include in the course has been increasing veryquickly over the years! In 1992, when I first taught the course, I used toteach about Pipelined Computers, Systolic Arrays, SIMD array processors,and Multiprocessors. As time has passed, it has become necessary to includetopics such as high-performance interconnection networks, wormhole routing,cache coherence protocols, instruction pipelines, superscalar processors,and instruction-level parallelism.More recently, I have realized that itis also necessary to teach elements of distributed computing and clusteredcomputing.I believe that a course on selected topics from distributed andclustered computing is essential to all branches of Engineering today.

ØHigh-performance computing is essential to all branches of Engineering, andhigh-performance clustered computing on clusters of workstations/PCs makesa lot of economical sense.

Ø A course such as this is interesting becauseit is easy for the students to practice what is taught in such a classwithout too many infrastructures.This makes the course very exciting tostudents.When I taught parallel algorithms in my class, I could not askmy students to develop these algorithms for lack of good infrastructure. But a cluster of workstations and PCs is available in almost everyUniversity today.

Ø Distributed computing is highly popular withstudents.Students are eager to learn Java and network programming.

Rajkumar Buyya's edited volumes have arrived at the right time toprovide the right kind of teaching material for the type of course which Ihave mentioned above.The first volume covers architectural andsystem-level issues of clustered computing systems. It has 36 chaptersorganized into 4 sections, spanning 811 pages.Section I develops themotivation for high-performance clustered computing. Section II introducesvarious networking protocols and I/O mechanisms that are useful inclustered computing. Section III covers OS issues such as processscheduling and load balancing.Section IV includes a number of casestudies of existing systems.The editor has made a considerable effort ingathering learning material for the volume.I think that this volume couldbe an excellent text for an advanced course on Computer Architecture.Inthe course that I taught, I used parts of Section I and IV. To me, thesecond volume proved more useful.

The second volume concerns withapplications of clustered computing and applications programming.It isdivided into 3 sections.There are 29 chapters that span 604 pages.Bothvolumes have carefully prepared Glossaries and Indexes.The first sectionof the second volume is on various programming environments and developmenttools. Although I limited myself to the discussion of the Parallel VirtualMachine (PVM) and Message Passing Interface (MPI), the editor has alsoincluded entire chapters on linking of these two environments, activeobjects, component-based approach, LiPS, and WebOS.There is a chapter ofdebugging parallelized code that can be highly valuable for students anddevelopers of applications.The second section is on Java forhigh-performance computing.These topics raised a lot of interest amongstudents when I taught the course.The third section is on specificalgorithms and applications such as parallel genetic algorithms, parallelsimulation, distributed database systems, graphics and image processing. The authors who have contributed to the two volumes are all known expertsin the areas of Computer Architecture, Computer Networks, DistributedComputing, and Operating Systems.The authors and the editor must becongratulated on this extraordinary effort to compile so much usefulmaterial under one place.The books can not only serve as referencematerial to professional programmers in the modern IT industry, it can alsoserve as excellent teaching material for courses related to ComputerArchitecture, Distributed Computing, and Operating Systems.The web pagethat the editor has created for the book is also a wonderful repository oflearning material available on the web.I recommend these volumeswholeheartedly to all serious researchers and students interested in theareas of high-performance computing in general and clustered computing inparticular.

C.P. Ravikumar Professor, Department of ElectricalEngineering,Indian Institute of Technology, Delhi

good effort atlast
There is a good effort by the author to bring this book. I am sure this is helpful for research and development in the field of High performance Cluster computing.

I am very happy and proud to say that this author ismy classmate and very good friend of mine.

Sreekanth ... Read more

Product Description
The state of the art of high-performance computing

Prominent researchers from around the world have gathered to present the state-of-the-art techniques and innovations in high-performance computing (HPC), including:
* Programming models for parallel computing: graph-oriented programming (GOP), OpenMP, the stages and transformation (SAT) approach, the bulk-synchronous parallel (BSP) model, Message Passing Interface (MPI), and Cilk
* Architectural and system support, featuring the code tiling compiler technique, the MigThread application-level migration and checkpointing package, the new prefetching scheme of atomicity, a new "receiver makes right" data conversion method, and lessons learned from applying reconfigurable computing to HPC
* Scheduling and resource management issues with heterogeneous systems, bus saturation effects on SMPs, genetic algorithms for distributed computing, and novel task-scheduling algorithms
* Clusters and grid computing: design requirements, grid middleware, distributed virtual machines, data grid services and performance-boosting techniques, security issues, and open issues
* Peer-to-peer computing (P2P) including the proposed search mechanism of hybrid periodical flooding (HPF) and routing protocols for improved routing performance
* Wireless and mobile computing, featuring discussions of implementing the Gateway Location Register (GLR) concept in 3G cellular networks, maximizing network longevity, and comparisons of QoS-aware scatternet scheduling algorithms
* High-performance applications including partitioners, running Bag-of-Tasks applications on grids, using low-cost clusters to meet high-demand applications, and advanced convergent architectures and protocols

High-Performance Computing: Paradigm and Infrastructure is an invaluable compendium for engineers, IT professionals, and researchers and students of computer science and applied mathematics. ... Read more

Product Description
Discover how to streamline complex bioinformatics applications with parallel computing


This publication enables readers to handle more complex bioinformatics applications and larger and richer data sets. As the editor clearly shows, using powerful parallel computing tools can lead to significant breakthroughs in deciphering genomes, understanding genetic disease, designing customized drug therapies, and understanding evolution.

A broad range of bioinformatics applications is covered with demonstrations on how each one can be parallelized to improve performance and gain faster rates of computation. Current parallel computing techniques and technologies are examined, including distributed computing and grid computing. Readers are provided with a mixture of algorithms, experiments, and simulations that provide not only qualitative but also quantitative insights into the dynamic field of bioinformatics.

Parallel Computing for Bioinformatics and Computational Biology is a contributed work that serves as a repository of case studies, collectively demonstrating how parallel computing streamlines difficult problems in bioinformatics and produces better results. Each of the chapters is authored by an established expert in the field and carefully edited to ensure a consistent approach and high standard throughout the publication.

The work is organized into five parts:
* Algorithms and models
* Sequence analysis and microarrays
* Phylogenetics
* Protein folding
* Platforms and enabling technologies

Researchers, educators, and students in the field of bioinformatics will discover how high-performance computing can enable them to handle more complex data sets, gain deeper insights, and make new discoveries. ... Read more