Download Accelerating MATLAB with GPU Computing: A Primer with by Jung W. Suh, Youngmin Kim PDF

By Jung W. Suh, Youngmin Kim

Past simulation and set of rules improvement, many builders more and more use MATLAB even for product deployment in computationally heavy fields. This usually calls for that MATLAB codes run swifter through leveraging the disbursed parallelism of photos Processing devices (GPUs). whereas MATLAB effectively offers high-level features as a simulation device for swift prototyping, the underlying info and data wanted for using GPUs make MATLAB clients hesitate to step into it. Accelerating MATLAB with GPUs bargains a primer on bridging this gap.

Starting with the fundamentals, establishing MATLAB for CUDA (in home windows, Linux and Mac OS X) and profiling, it then courses clients via complex issues similar to CUDA libraries. The authors proportion their adventure constructing algorithms utilizing MATLAB, C++ and GPUs for big datasets, enhancing MATLAB codes to higher make the most of the computational strength of GPUs, and integrating them into advertisement software program items. in the course of the e-book, they reveal many instance codes that may be used as templates of C-MEX and CUDA codes for readers' tasks. obtain instance codes from the publisher's site: http://booksite.elsevier.com/9780124080805/

• exhibits easy methods to speed up MATLAB codes throughout the GPU for parallel processing, with minimum knowledge
• Explains the comparable historical past on undefined, structure and programming for ease of use
• offers uncomplicated labored examples of MATLAB and CUDA C codes in addition to templates that may be reused in real-world initiatives

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