The use of Graphics Processing Units for rendering is well known, but their power for general parallel computation has only recently been explored. Parallel algorithms running on GPUs can often achieve up to 100x speedup over similar CPU algorithms, with many existing applications for physics simulations, signal processing, financial modeling, neural networks, and countless other fields.
This course will cover programming techniques for the GPU, focusing on visualization and simulation of various systems. Labs will cover specific applications in graphics, physics, and other topics. The course will introduce nVidia's parallel computing architecture, CUDA. The course will cover basic CUDA commands and syntax, as well as several optimizations for CUDA code and utilization of CUDA libraries.Labwork will require extensive programming. Some experience with computer graphics algorithms is preferred, but not required. A working knowledge of the C programming language will be necessary.
9 units; third term.
|Instructors:|| Connor DeFanti - email@example.com
Kevin Yuh - firstname.lastname@example.org
|Supervising professors:|| Professor
Al Barr - email@example.com
Professor Mathieu Desbrun - firstname.lastname@example.org
|Time and place:|| MWF 5:00-5:55 PM
|Office Hours:|| Connor DeFanti - Tuesdays, 8:00-10:00 PM
Kevin Yuh - Mondays, 8:00-10:00 PM
Ben Yuan - Tuesdays, 7:00-9:00 PM
104 Annenberg, instructional laboratory
|Grading policy:|| There will be 8 labs, each worth 100 points, or 10%
of your grade. At the end of the quarter, there will be one final
project worth 200 points, or 20% of your grade. Extensions may be
granted if the TA's see it appropriate. E grades will not be granted
unless under extreme circumstances.
|Lectures and recitations:||1. Class Introduction PPT
2. Lab 1 Recitation PPT PDF
3. Lecture 3 PPT PDF
4. Lecture 4, Lab 2 Recitation PPT PDF
5. Lecture 5: CUDA Memory PPT PDF
6. Lecture 6: CUDA and Graphics PPT PDF
7. Lecture 7: Lab 3 Recitation PPT PDF
CUDA Setup Instructions
HTML version of the OpenGL Red Book
The CUDA Zone
NVIDIA CUDA Programming Guide 2.0
CUDA Reference Manual 2.0
CUDA PTX ISA 1.2