GPU Programming

CS 179

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. The course will introduce NVIDIA's parallel computing language, CUDA. Beyond covering the CUDA programming model and syntax, the course will also discuss GPU architecture, high performance computing on GPUs, parallel algorithms, CUDA libraries, and applications of GPU computing.

Problem sets will cover performance optimization and specific GPU applications such as numerical mathematics, medical imaging, finance, and other fields.

This quarter we will also cover uses of the GPU in Machine Learning.

Labwork will require significant programming. A working knowledge of the C programming language will be necessary. Although CS 24 is not a prerequisite, it (or equivalent systems programming experience) is strongly recommended.

9 units; third term.

• Piazza Please ask through Piazza if you have a question/issue that likely affects other students.
• TA email: cs179.ta@gmail.com. Use Piazza, generally, for questions on the assignments or the material. These may be of interest to other people. Send an email to the TA's if you have something that only affects you or your project group.

Sunday 2pm-5pm Tyler

Monday 8pm-10pm Bobby

Tuesday 7pm-9pm Aadyot

104 Annenberg, instructional laboratory

• 6 labs (60% of grade)
• 4 week project (40% of grade)