Mathematical Statistical

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

By Jung W. Suh,Youngmin Kim

Beyond 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 quicker by means of leveraging the dispensed parallelism of photos Processing devices (GPUs). whereas MATLAB effectively offers high-level services as a simulation device for swift prototyping, the underlying information and data wanted for using GPUs make MATLAB clients hesitate to step into it. Accelerating MATLAB with GPUs bargains a primer on bridging this hole.

Starting with the fundamentals, establishing MATLAB for CUDA (in home windows, Linux and Mac OS X) and profiling, it then courses clients via complicated issues corresponding to CUDA libraries. The authors proportion their adventure constructing algorithms utilizing MATLAB, C++ and GPUs for big datasets, editing MATLAB codes to raised make the most of the computational strength of GPUs, and integrating them into advertisement software program products.  through the e-book, they exhibit many instance codes that may be used as templates of C-MEX and CUDA codes for readers’ projects.  obtain instance codes from the publisher's web site:

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

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