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Intel Threading Building Blocks: Outfitting C++ for Multi-Core Processor Parallelism (Paperback)

~ (Author), Reinders James (Author)
Key Phrases: template class, standard template library, loop parallelization, Threading Building Blocks, Examples Example, Packet Processing Pipeline (more...)

3.7 out of 5 stars See all reviews (3 customer reviews)

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Editorial Reviews

Product Description

Multi-core chips from Intel and AMD offer a dramatic boost in speed and responsiveness, and plenty of opportunities for multiprocessing on ordinary desktop computers. But they also present a challenge: More than ever, multithreading is a requirement for good performance. This guide explains how to maximize the benefits of these processors through a portable C++ library that works on Windows, Linux, Macintosh, and Unix systems. With it, you'll learn how to use Intel Threading Building Blocks (TBB) effectively for parallel programming -- without having to be a threading expert.

Written by James Reinders, Chief Evangelist of Intel Software Products, and based on the experience of Intel's developers and customers, this book explains the key tasks in multithreading and how to accomplish them with TBB in a portable and robust manner. With plenty of examples and full reference material, the book lays out common patterns of uses, reveals the gotchas in TBB, and gives important guidelines for choosing among alternatives in order to get the best performance.

You'll learn how Intel Threading Building Blocks:

Enables you to specify tasks instead of threads for better portability, easier programming, more understandable source code, and better performance and scalability in general
Focuses on the goal of parallelizing computationally intensive work to deliver high-level solutions
Is compatible with other threading packages, and doesn't force you to pick one package for your entire program
Emphasizes scalable, data-parallel programming, which allows program performance to increase as you add processors
Relies on generic programming, which enables you to write the best possible algorithms with the fewest constraints

Any C++ programmer who wants to write an application to run on a multi-core system will benefit from this book. TBB is also very approachable for a C programmer or a C++ programmer without much experience with templates. Best of all, you don't need experience with parallel programming or multi-core processors to use this book.

About the Author

James Reinders, Chief Evangelist of Intel Software Products, is a senior engineer who joined Intel Corporation in 1989 and has contributed to a number of projects, including the world's first TeraFLOP supercomputer (ASCI Red), compilers and architecture work for the iWarp, Pentium Pro, Pentium II, Itanium, and Pentium 4 processors. He has years of experience in processor architecture, optimizing compilers, parallel computer architecture, and making products for software developers.

Reinders is also the editorial columnist for the monthly "The Gauntlet" at www.devX.go-parallel.com, as well as the author of the Intel Press book titled "VTune Performance Analyzer Essentials" and contributor to the new book "Multi-Core Programming."

Product Details

Paperback: 332 pages
Publisher: O'Reilly Media; illustrated edition edition (July 12, 2007)
Language: English
ISBN-10: 0596514808
ISBN-13: 978-0596514808
Product Dimensions: 9.1 x 7 x 0.9 inches
Shipping Weight: 1.1 pounds (View shipping rates and policies)

Average Customer Review: 3.7 out of 5 stars See all reviews (3 customer reviews)

Amazon.com Sales Rank: #274,242 in Books (See Bestsellers in Books)
Popular in these categories: (What's this?)
#20 in Books > Computers & Internet > Programming > Software Design, Testing & Engineering > Performance Optimization
#27 in Books > Computers & Internet > Hardware > Parallel Processing Computers

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Inside This Book (learn more)

Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
template class, standard template library, loop parallelization, namespace tbb, splitting constructor, scalable allocator, grainsize parameter, concurrent hash map, scalable malloc, allocate continuation, scalable memory allocator, concurrent containers, scheduler bypass, automatic grain size, allocator argument, scheduler mit, scheduler init, void spawn, threading packages, recursive ranges, void operator delete, mit object, pipeline class, task stealing, bool empty

Key Phrases - Capitalized Phrases (CAPs): (learn more)
Threading Building Blocks, Examples Example, Packet Processing Pipeline, Amdahl's Law, Mutex Concept, Addison Wesley, Range Concept, Thinking Parallel, Open Dynamics Engine, Better Matrix Multiply, Think Parallel, Basic Algorithms, The Game of Life, Parallel-reduce Examples, Pseudosignature Semantics, Intel Thread Checker, Advanced Task Programming, Class Class, Members See Table, Visualizing Task Stealing, Model Types, The Multiples, Same Task, Game Threading Example, Other Threading Packages

What Do Customers Ultimately Buy After Viewing This Item?

	57% buy the item featured on this page: Intel Threading Building Blocks: Outfitting C++ for Multi-Core Processor Parallelism 3.7 out of 5 stars (3) $33.22
	21% buy The Art of Multiprocessor Programming 4.4 out of 5 stars (10) $56.65
	10% buy Professional Multicore Programming: Design and Implementation for C++ Developers (Wrox Programmer to Programmer) 4.5 out of 5 stars (2) $37.79
	9% buy Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation) 4.3 out of 5 stars (3) $31.00

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82 of 84 people found the following review helpful:

3.0 out of 5 stars Potentially useful technology, book could be better, August 25, 2007

By	J. S. Hardman "Consultant software developer ... (Near London, UK) - See all my reviews (REAL NAME)

There are many views of how best to implement multi-threading and with multi-core processors now common the topic is becoming ever more relevant. Of course the best implementation method really depends on what you are trying to do. Are you implementing something that waits for a price update message from a derivatives exchange, parses the message, updates cached data, writes a log and forwards the message on to an algorithmic trading engine? If so, you'll probably be attracted to techniques different from someone calculating risk, bond prices etc. There is no one technique that suits every job.

Anyone working with multi-threading (and parallelism in general) keeps an eye on what techniques other people are using to see whether they may be useful. That's why I bought this book (Intel Threading Building Blocks) and TBB certainly looks like it will be of use for some multi-threaded applications that I develop, although not for all.

Starting with the most important question - have I learnt anything from reading this book. Yes, and I've learnt a couple of bits from reading the TBB source code too (downloadable from the web). Now for the detail...

Having read the book, am I now about to start using the Intel Threading Building Blocks library (downloadable from Intel)? The answer is yes, for some applications on some hardware architectures, but not for all of my multi-threaded applications. Importantly in terms of this book though, the first reason I looked at the TBB source code was to answer questions raised when reading the book, and that is my main issue with this book. For a developer who already has extensive multi-threading experience, this book raises quite a few questions that it doesn't answer.

Even some of the things that this book does answer are tucked away in the text a long way into the book. Here are three examples:
(1) The book tells you to create tasks, not explicitly work with threads. Where is the best description of a task? Page 267. It's not even in a glossary, but tucked away in the examples chapter. Somewhere in the first chapter would have been more useful.
(2) Personally, if I am told within the first few pages that TBB is based on the idea of developers implementing their systems as small tasks that are scheduled by the TBB scheduler I am immediately going to ask how that task is handled at a technical level. Ok, we're told quickly that it's written as a functor, and that functors may be executed on different cores, but does that mean that a thread is chosen from a thread pool to execute each functor, that (on Windows) fibers are used, that there is one manager thread running per core (with processor affinity set?) with each manager pulling tasks from its own queue, what are the performance implications of context switching and locking, etc? The author may think that the reader doesn't need this level of detail, but if somebody is going to the trouble of writing multithreaded code to improve performance I would think it very likely that they will want to know what is happening beneath the surface to ensure that they are using the best techniques. Some details of the scheduler are provided much further into the book (for instance we discover that last-in, first-out deques are used), but not enough and far too late.
(3) On page 133 there are two paragraphs discussing when task-based programming is inappropriate, a bit late in my opinion for those people for whom it does turn out to be inappropriate.

I also have issues with some of the things presented as absolute fact in the book. For example "Race conditions are less catastrophic than deadlocks". I disagree. With a deadlock your program stops, you know about it very quickly, you investigate and you sort it out. If it happens, it'll probably only happen once. With a race condition you may not even realise it exists, the application produces subtly incorrect results and hence your functionality goes awry. If that means your algorithmic trading engine decides to buy a million shares instead of doing nothing (or selling) then you are going to lose a lot of money very quickly. Possibly not just once, but day after day until you realise the race condition is there.

Then there are the bits that are just plain confusing. Here are two examples:
(a) We are told on page 271 that Task stealing is "Terrible" and "will disrupt cached data", but are told on page 283 that TBB is "unique because it rests on a few key decisions" including "Use task stealing". Hmmm...
(b) The code comment on page 231, "2 = 1 for SideShow and C". I know what it means, but adding a verb phrase would prevent the moment when the reader wonders just which proof is about to be presented that "2 = 1".

On the plus side, the book does discuss the split/join pattern, pipelines, atomic operations, benefits of working in user space, issues with the standard new operator (and hence libraries that make use of it), caching issues etc. There is also a chapter on general "Keys to Success" which is useful. There are also some reasonable examples towards the end of the book (although some half way through would be better replaced - demonstrating a point is one thing, but demonstrating it with realistic code is better).

Possibly outside the intended scope of the book, it might have been useful to briefly describe grid computing and whether Intel have plans to add a layer above TBB for use across grids instead of just on one machine, or whether Intel's plans for grid computing simply rely on a completely different model.

So to summarise, the TBB library from Intel looks like it could be very useful, this book will certainly get you started using it, but have no doubt that this book could have been better. Buy it if you will be using TBB, but until somebody writes a better book be prepared to read the TBB source code to find the answers to your deeper questions, or simply ask questions on Intel's web-site.

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12 of 12 people found the following review helpful:

5.0 out of 5 stars Opens up your thinking about parallelism, January 27, 2008

By	rdf "rdf_acm" (Cambridge, Ma. USA) - See all my reviews

I agree with Hardman's review as far as it goes -- the book cannot go into as much detail as he would like since it is designed to be cross platform (and surprisingly also applicable to other similar chips e.g., AMD).

On the other hand, this book opens you up to an important area: how can you use a small number of cores to speed up your program, including those programs that appear serial at first (and maybe second) glance e.g., the cumulative sum of a vector.

The book has a lot of depth on the algorithms used and works through applications of differing complexity and varied domains.

As an extra bonus it provides annotated pointers to its intellectual predecessors, albeit not as extensive as Hillis' book.The Connection Machine (Artificial Intelligence)

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2 of 13 people found the following review helpful:

3.0 out of 5 stars Interesting, April 26, 2008

By	W. Mackenzie - See all my reviews (REAL NAME)

I bought this book with the hope that I could find the answers to solving a couple of problems.

The first problem being writing parallel threaded code in a standardized way.

The second problem being writing the OS threads and associated message queues in a way that is abstracted from the OS.

In the end I have not used the lessons from this book yet. After reading it I was left with the impression that the inventors are on to something novel; however, the implementation is not yet complete. I find myself asking if this winds up being like Sony's Betamax.

Only time will tell.

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