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The MATLAB® programming environment is often perceived as a platform suitable for prototyping and modeling but not for "serious" applications. One of the main complaints is that MATLAB is just too slow.
Accelerating MATLAB Performance aims to correct this perception by describing multiple ways to greatly improve MATLAB program speed. Packed with thousands of helpful tips, it leaves no stone unturned, discussing every aspect of MATLAB.
Ideal for novices and professionals alike, the book describes MATLAB performance in a scale and depth never before published. It takes a comprehensive approach to MATLAB performance, illustrating numerous ways to attain the desired speedup.
The book covers MATLAB, CPU, and memory profiling and discusses various tradeoffs in performance tuning. It describes the application in MATLAB of standard tuning techniques used in the software industry, as well as methods that are specific to MATLAB such as using different data types or built-in functions.
The book discusses MATLAB vectorization, parallelization (implicit and explicit), optimization, memory management, chunking, and caching. It explains MATLAB's memory model and details how it can be leveraged. It describes the use of GPU, MEX, FPGA, and other forms of compiled code, as well as techniques for speeding up deployed applications. It details specific tips for MATLAB GUI, graphics, and I/O. It also reviews a wide variety of utilities, libraries, and toolboxes that can help to improve performance.
Sufficient information is provided to allow readers to immediately apply the suggestions to their own MATLAB programs. Extensive references are also included to allow those who wish to expand the treatment of a particular topic to do so easily.
Supported by an active website and numerous code examples, the book will help readers rapidly attain significant reductions in development costs and program run times.
- Sales Rank: #554078 in Books
- Brand: imusti
- Published on: 2014-12-11
- Original language: English
- Number of items: 1
- Dimensions: 10.00" h x 7.25" w x 1.75" l, .0 pounds
- Binding: Hardcover
- 785 pages
- CRC Press
Review
… a very interesting new book on MATLAB® performance … covering basic tools and an appropriate range of specific programming techniques. The book seems to take a whole-system approach … helping readers understand the big picture of how to get better performance.
―Michelle Hirsch, Ph.D., Head of MATLAB® Product Management, The MathWorks Inc.
Most helpful customer reviews
5 of 5 people found the following review helpful.
Extremely valuable
By rsd22
In the first hour of reading it this book paid for itself -> Chapter 8 on the use of MEX to incorporate Fortran routines into Matlab. While I use Matlab daily I (embarrassingly) had never investigated the possibility of accelerating performance using MEX. I thought (incorrectly) that the Matlab compiler, which I do not have, would be required on my machine to create MEX functions. Maybe the material in Chapter 8 is old hat for most potential readers, but for me it was eye-opening. However, even if the use of MEX is familiar, I'll bet that any serious Matlab user will find a similarly valuable idea somewhere in this information-packed book. In contrast to the author's earlier book on Undocumented Matlab, I think that the information here is more likely to remain stable in ongoing releases. I would add a caution that the book is not written for, nor will it be useful for, the newcomer to Matlab or the casual user. Check the author's blog to see the level at which the book is written.
1 of 1 people found the following review helpful.
A must-read for MATLAB programmers
By Cary
This book contains a universe of real-life, valuable insights from one of (if not) the top MATLAB programmers in the world. If you want to improve your coding skills, this is the book that will take you to the next level.
0 of 1 people found the following review helpful.
Helpful, but if you want to fully leverage all ...
By Wavefunction
Helpful, but if you want to fully leverage all cores of your machine and not just optimize for a single core (or however many cores you can make use of with parallel toolbox), you should consider using mex combined with OpenMP or some other form of multiple threading. It is true you can optimize Matlab to a much larger degree than most people realize, but you will still probably find mex and multithreading to be faster.
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