| Description
| With modern technology developing, the data is increasingly huge. It caused difficulties in data processing, analysis and applications. Over the decades, graphics processing unit (GPU) has not only expanded the scope of application of graphics processing platforms, but also the application of the high performance computing. Its many-core computing architecture and high memory bandwidth advance the high performance computing with low cost. Thus how to integrate a modern GPU architecture with NVIDIA’s compute unified device architecture (CUDA) technology to enhance overall operational efficiency has become one of the important issues. In order to discuss this important topic, this course is aimed to cover the basis as follows：
1. Introduction to the big data
2. Introduction to the principles of parallel programming
3. Introduction to GPU-CUDA interfaces
4. GPU programming using CUDA
5. Optimization of GPU-CUDA programming
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