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Accelerating MATLAB With GPU Computing: A Primer With Examples File Size: 4811 KB

Print Length: 238 pages

Publisher: Morgan Kaufmann; 1 edition (November 18, 2013)

Publication Date: November 18, 2013

Sold by: Digital Services LLC

Language: English

ASIN: B00GWMD6JW

Text-to-Speech: Enabled

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Best Sellers Rank: #1,050,983 Paid in Kindle Store (See Top 100 Paid in Kindle Store) #154 in Books > Computers & Technology > Programming > Parallel Programming #1138 in Books > Computers & Technology > Software > Mathematical & Statistical #1496 in Kindle Store > Kindle eBooks > Computers & Technology > Software

This book is well written for Matlab users who seeks a way of boosting up the speed of Matlab codes through parallel computing. The book is well organized to learn basic principles of accelerating computing speed as well as advanced programming techniques utilizing GPU-based parallel computing processing. The objectives of each chapter are clearly stated at the beginning of each chapter followed by series of examples so that one can clearly understand and practice the GPU programming techniques. This book also provides detailed instructions for installation and compiling steps for both PC and Mac users, and many screenshots of each step for quick follow-up. The power of the parallel computing is demonstrated by applying the GPU processing to computers graphics and medical imaging processing in the book that I think this book would be useful to the people in these fields.Personally, I have been struggling with slow processing speed of Matlab codes for modeling my complex systems biology data. I have been aware of the availability of Parallel Computing Toolbox which can be purchased from Mathworks to speed up Matlab codes using GPU processing. However, the usage of the commercial toolbox has been limited due to high cost of the commercial toolbox as well as limited access to the underlying structures. Now I am very happy to get to know this bookI highly recommend this book.

The book is just what it says - a primer with Matlab-mex-examples. If you are a Matlab programmer with some experience in C/C++, then this book takes you past the practical hurdles of downloading, setting up the system, linking your first few mex-files to CUDA (+ some open GPU-libs) and profiling the results. It helped me do this in a limited time and with very little effort. It also gets you started on the mindset and the tricks of GPU-data-crunching but for this, I'm sure there are much better books. There are some language issues (in parts of the book) and even a couple of bugs in the example code (suggesting the need for an editor?). But for the time it saves, and the information-gap it fills (Mathworks excellent documentation is focused on the Parallell Toolbox) the book is so worth the money.

It will undoubtedly pay for itself in time savings. Although this book covers both the Parallel Computing Toolbox and the direct use of CUDA via c-mex, this book is uniquely useful because I couldn’t find any book or online materials so far like this book which has a lot of details especially on the direct use of CUDA via c-mex of Matlab. The book has lots of detail and screenshots to guide you from basics such as environment setting with example codes, so it helps to even novice of both Matlab and CUDA. Since this book is not thick and easily read, we can go through the book quickly and can go to the next level. This book is good not only for the specific GPU usage for Matlab but also for general start of GPU coding.

Good book

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