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Title: | Parallel computing - practical approach on CUDA programming | Authors: | Nguyen Hoai Phuong | Keywords: | CUDA programming;Parallel computing;Image processing;Matlab;C++;Mechanisms | Issue Date: | 2018 | Publisher: | Vietnamese-German University | Abstract: | CUDA is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs. In GPU-accelerated applications, the sequential part of the workload runs on the CPU – which is optimized for single-threaded performance – while the compute intensive portion of the application runs on thousands of GPU cores in parallel. When using CUDA, developers program in popular languages such as C, C++, Fortran, Python and MATLAB and express parallelism through extensions in the form of a few basic keywords. This thesis project aims to provide a fast and simple introduction as well as step-by-step instruction for applying CUDA programming into image processing or imaging field, which normally requires tremendous computation workforce but can be easily parallelized. Through practical approach, programmers can directly modify their available algorithm which initially runs in successive order to parallel processing on CUDA device. |
URI(1): | http://epub.vgu.edu.vn/handle/dlibvgu/904 |
Appears in Collections: | Mechatronics & Sensor Systems Technology (MSST) |
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