Yu Zhao

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GPU Programming part of Parallel Computing in the Computer Science Curriculum:Modules:Modules Mini-collection
As modern Graphics Processing Unit (GPU) harnessed more and more horsepower, programmers began to use GPU for General Purpose computation, instead of just for graphics rendering. NVIDIA® Corporation developed CUDA, a parallel computing platform and programming model, to improve computing performance for parallel computation problems. In this module, we will learn how to solve parallel problems more efficiently by writing programs in CUDA C Programming Language and then executes them on GPUs based on CUDA architecture. This module uses the CUDA parallel computing platform; developer's SDK and toolkit can be found on NVIDIA's website. Module Characteristics Languages Supported: CRelevant Parallel Computing Concepts: Data ParallelismOperating System Supported: Mac OS, Linux, WindowsPossible Course Use: Programming Languages, Hardware Design, Parallel Computing SystemsRecommended Teaching Level: intermediate, Advanced