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"Pacheco succeeds in introducing the reader to the key issues and considerations in parallel programming. The simplicity of the examples allows the reader to focus on parallel programming aspects rather than application logic. Including both MPI and Pthreads/OpenMP is a good way to illustrate the differences between message passing and shared-memory programming models. The discussions about analyzing the scalability and efficiency of the resulting parallel programs present a key aspect of developing real parallel programs. Finally, working through the same examples using all three facilities helps make this even more concrete."--W. Hu, "[T]his is a well-written book, appropriately targeted at junior undergraduates. Being easily digestible, it makes the difficult task of parallel programming come across a lot less daunting than I have seen in other texts. Admittedly, it is light on theory; however, the most memorable lessons in parallel programming are those learned from mistakes made. With over 100 programming exercises, learning opportunities abound."--Bernard Kuc, ACM's Computing With the coming of multicore processors and the cloud, parallel computing is most certainly not a niche area off in a corner of the computing world. Parallelism has become central to the efficient use of resources, and this new textbook by Peter Pacheco will go a long way toward introducing students early in their academic careers to both the art and practice of parallel computing. Duncan Buell Department of Computer Science and Engineering University of South Carolina An Introduction to Parallel Programming illustrates fundamental programming principles in the increasingly important area of shared memory programming using Pthreads and OpenMP and distributed memory programming using MPI. More importantly, it emphasizes good programming practices by indicating potential performance pitfalls. These topics are presented in the context of a variety of disciplines including computer science, physics and mathematics. The chapters include numerous programming exercises that range from easy to very challenging. This is an ideal book for students or professionals looking to learn parallel programming skills or to refresh their knowledge. Leigh Little Department of Computational Science The College at Brockport, The State University of New York An Introduction to Parallel Programming is a well written, comprehensive book on the field of parallel computing. Students and practitioners alike will appreciate the relevant, up-to-date information. Peter Pacheco's very accessible writing style combined with numerous interesting examples keeps the reader's attention. In a field that races forward at a dizzying pace, this book hangs on for the wild ride covering the ins and outs of parallel hardware and software. Kathy J. Liszka Department of Computer Science University of Akron Parallel computing is the future and this book really helps introduce this complicated subject with practical and useful examples. Andrew N. Sloss FBCS Consultant Engineer, ARM Author of ARM System Developer's Guide

Über den Autor und weitere Mitwirkende

Peter Pacheco received a PhD in mathematics from Florida State University. After completing graduate school, he became one of the first professors in UCLA's "Program in Computing, which teaches basic computer science to students at the College of Letters and Sciences there. Since leaving UCLA, he has been on the faculty of the University of San Francisco. At USF Peter has served as chair of the computer science department and is currently chair of the mathematics department. His research is in parallel scientific computing. He has worked on the development of parallel software for circuit simulation, speech recognition, and the simulation of large networks of biologically accurate neurons. Peter has been teaching parallel computing at both the undergraduate and graduate levels for nearly twenty years. He is the author of Parallel Programming with MPI, published by Morgan Kaufmann Publishers.

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18 von 18 Kunden fanden die folgende Rezension hilfreich
Good start to learn parallel 21. Juni 2011
Von Jaime Moreno - Veröffentlicht auf
Format: Gebundene Ausgabe Vine Kundenrezension eines kostenfreien Produkts ( Was ist das? )
This book is a good start for anyone that had done quite a bit of programming and is confident in their abilities to program traditional non-parallel programs and wants to learn parallel programming.

Good intro and review of material you will have learned in any computer architecture course in first chapters and reasons why you should learn parallel programming.
In later chapters you learn about task-parallelism vs data-parallelism in learning to rewrite serial program for parallel. The two main types of parallel systems, shared-memory, and distributed-memory are covered and explained.

MPI is used for the distributed-memory programming. Pthreads and OpenMP is used for the Shared-Memory programming examples. Examples like the Trapezoid Rule and sorting algorithms that lend themselves to parallel programming are demonstrated using MPI, Pthreads and OpenMP. There is also the pi approximation example using alternating series that I remember coding in my first programming course and wondering why it was so slow. It's used in the book to warn of the dangers of improperly scoping variables in parallel blocks. MPI does seem to be favored over the other two for some reason that I didn't get though. OpenMP seems to be the easiest to use and works out of the box on Windows, Linux, and Mac OS X with little to no extra work too so I don't know why the author didn't start off with OpenMP first. You'll need to be running Linux to be able to easily follow along with all the examples in the book if you are a hands on person like myself and want to actually compile and run all the example yourself. On Windows,to build MPI programs,you need the Windows HPC Server 2008 SDK installed. You can run the Pthreads examples on the Mac too but on Windows you'll need to install the Unix for Windows. I did get the sample code to work pretty easily using OpenMP. All the examples were text based it was also easy to time them and verify that the parallel version of the programs were faster. It would've been nice to see some graphical examples but I'm guessing OpenCL, CUDA or some other API is better suited for that since I've seen graphical examples using those API's. The final chapters does provide some guidance to which API to choose and their strengths and weaknesses though.

Since the book is intended for self-study it sure doesn't provide much help on setting up your development environment for parallel programming and seems to assume you'll figure it out on your own. Also, no answers were provided for any of the end of chapter problems which would really be helpful for self-study. The book website does provide some excellent slides to go with the book though.

Finally, parallel programming with GPU's seems to be gaining quite a bit of popularity lately but this book seems to totally ignore the topic except to refer you to other books on the subject.
20 von 21 Kunden fanden die folgende Rezension hilfreich
A very introductory Introduction 2. Januar 2012
Von Muhammad Ebraheem - Veröffentlicht auf
Format: Gebundene Ausgabe
I bought this book for a dual purpose: To use in a post-grad class I am taking, and to help me build a distributed systems that I am currently developing. The book is pedagogically exquisite. The presentation and explanations are ordered, logical and non-assuming, and that is where this books shines - and probably why it is getting all the good reviews here and elsewhere. However, the book stands very short of being practical to anything but the simplest of applications - compare it to other books that have similar titles, even with the word introduction in the title and you immediately see the difference. Having said that, I think this the best place to start, it the most approachable introduction to the subject, but in my opinion, it could have accommodated more content either on the design and analysis of parallel algorithms or on the details of implementing more than plain vanilla concurrent solutions.
4 von 5 Kunden fanden die folgende Rezension hilfreich
Good place to start 29. April 2011
Von J. A. Hansen - Veröffentlicht auf
Format: Gebundene Ausgabe Vine Kundenrezension eines kostenfreien Produkts ( Was ist das? )
I am a first year graduate student with no computer science background, other than one class I took five years ago on scientific computing where we used fortran and focused on writing simple programs to solve simple physical science problems. I am working in theoretical chemistry/physics and required to program extensively. One area we are focusing on is programming in parallel to get better performance. This text has been invaluable to me as an introduction to the field of parallel computing. While not complete self-contained (he states in the introduction that it is assumed the reader has taken an introductory computer science course) it is not hard for one mostly unfamiliar with computer science terms to come up to speed. His explanations are clear and concise and the examples he expounds clarify the topics masterfully. The exercises are reasonable and well thought out to help the reader gain a better understanding of how to efficiently program in parallel.

One particularly elucidating example for me, which he comes back to more than once throughout the text, is that of computing a sum. In the first chapter he uses this example to show that substantial speedups can be obtained by not just writing the program to run in parallel, but making the best use of resources. As a novice to computer science this was one my "ah-ha!" moments I had while reading this book and working through the exercises. This will forever be an invaluable addition to my library, and I highly recommend it for the uninitiated.

The only drawback is that it is written with the C language in mind, we still use fortran77 for several reasons, though this was only minor. With a freely available online text on C and other references on MPI and openMP in fortran I have been able to make a smooth transition for the work that I do. So even if you don't know C, or use it, this is still a useful source and reference.
1 von 1 Kunden fanden die folgende Rezension hilfreich
mostly about MIMD hardware 27. Februar 2011
Von W Boudville - Veröffentlicht auf
Format: Gebundene Ausgabe Vine Kundenrezension eines kostenfreien Produkts ( Was ist das? )
Pacheco provides a quick overview of the main types of parallel computing hardware that has been built. This includes the hypercube geometry, which I remember from working on one instance as a grad student.

At the highest level, we have MIMD [Multiple Input Multiple Data] and SIMD [Single Input Single Data] machines. SIMD systems are not dealt with much by the text. (Programming of those is fairly simple.) Instead, the text then makes the main division of MIMD hardware into distributed or shared memory systems. A distributed system has a group of CPUs, each with its own substantial memory, where the CPUs are then linked by some interconnect switching. While a shared memory system has a globally accessible memory.

A chapter is devoted to explaining the programming of distributed memory systems using the Message Passing Interface [MPI], which is a collection of library functions accessible via C, C++ and Fortran code.

Another chapter delves into shared memory programming using Pthreads. We can see that the division into distributed or shared memory hardware forces this fundamental separation of coding methods. This is the main lesson to grasp from the book.

As an aside, the author performs a tedious pedantic notation. He persists in everywhere writing 'shared-memory' and 'distributed-memory' and 'message-passing'. The hyphens are unnecessary. This reminds me of the early days of the Web around 1992, when WWW was sometimes described as the World-Wide Web by the New York Times and other publications.
Really Nice 16. März 2014
Von Pankaj Doharey - Veröffentlicht auf
Format: Kindle Edition Verifizierter Kauf
A very good book with intro to C language refresher. Its good for people with medium level expertise in C language , it covers quite a number of Libs, Really good for a beginner.
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