Introduction to Parallel Programming – Introduction to OpenCL – OpenCL Device Architectures – Basic OpenCL – examples – Understanding OpenCL – Concurrency and Execution Model – Dissecting a CPU/GPU – OpenCL Implementation – OpenCL.
Case study: Convolution, Video Processing, Histogram and Mixed Particle Simulation – OpenCL Extensions – OpenCL Profiling and Debugging – WebCL, Applications of GPU Architecture like Gaming, Computer Vision, etc.
At the end of the course the students will be able to;
| Course Outcome | Bloom’s Taxonomy Level | |
| CO 1 | Understand GPU computing architecture | L2 |
| CO 2 | Code with GPU programming environments | L5 |
| CO 3 | Design and develop programs that make efficient use of the GPU processing power | L5 |
| CO 4 | Develop solutions to solve computationally intensive problems in various fields | L6 |
‘GPU Architecture and Programming’ is an elective course offered for the M. Tech. in Computer Science and Engineering program at School of Engineering, Amrita Vishwa Vidyapeetham.
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