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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Extra info for Accelerating MATLAB with GPU Computing: A Primer with Examples
SetText("Touched me " + touchCount + " time(s)"); } } Let’s dissect Listing 2–1 so you can understand what it’s doing. We’ll leave the nittygritty details for later chapters. All we want is to get a sense of what’s happening here. The source code file starts off with the standard Java package declaration and a couple of imports. Most Android framework classes are located in the android package. Button; Next, we define our HelloWorldActivity and let it extend the base class Activity, which is provided by the Android framework API.
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Figure 2–13 shows what the DDMS perspective usually looks like. CHAPTER 2: First Steps with the Android SDK As always, there are a couple of specific views that are suitable for our task at hand. In this case, we want to gather information about all the processes, their VMs and threads, the current state of the heap, LogCat information about a specific connected device, and so on. The Devices view displays all currently connected emulators and devices, as well as all the processes running on them.