GPU Programming

CS 179

This year, Spring 2020, CS179 is taught online, like the other Caltech classes, due to COVID-19.

The course is "live" and ready to go, starting on Monday, April 6, 2020. We won't be presenting video recordings or live lectures. The materials and slides are intended to be self-contained, found below.

The web page you're viewing is the main webpage for the course.

Due Dates & Office Hours

As of May 14, 2020, we will soon be transitioning to "appointment" style TA office hours. The purpose is for quick questions about your project, now that the assignments are mostly finished. Let a TA know by email that you will be wanting some help, ahead of time, for their regular office hours, or perhaps at other times.

Based on the 2020 Piazza surveys, homework sets are due Tuesdays 3 pm. The following dates should match the homework due dates on Piazza.

• Lab 1 is due Tuesday, April 14, 2020.
• Lab 2 is due Tuesday, April 21, 2020.
• Lab 3 is due Tuesday, April 28, 2020.
• Lab 4 AND Project Proposals are due Tuesday, May 5, 2020.
• Labs 5 and 6. Lab 5 is due on May 12, 2020, while Lab 6 is optional, and can count for 10% extra credit, and is due May 19, 2020.
• Final project deadlines. Final projects are due June 3 for seniors and grad students, and June 10 for everyone else. Note that the project proposal was due alongside Lab 4.

Office hours are on Zoom, every week. Times are in Pacific Time. See Piazza for Zoom links. As mentioned above, we may be transitioning to "appointment-style" office hours for your projects for quick questions as of May 14, since the homework assignments are mainly finished now.

Email a TA ahead of time to confirm, but they can likely be available at other times too, for quick questions to help you with your project, if you can set up a Zoom time with them in email.

• Saturday 1-4pm -- Ethan
• Sunday 1-4pm -- Alden
• Monday 1-4pm -- George

A Piazza link has been set up, CS179 Piazza, 2020.

Piazza will be the main forum for discussion, so it is important to make sure you are enrolled there!

For office hours with the TAs, we will be using Zoom, which allows screen sharing and real-time discussion. The Zoom meeting links will be posted on Piazza. It will be good for you to set up your Zoom account or system now, if this hasn't been done already.

You will be submitting your assignments on a GPU-enabled remote computer located at Caltech in the Barr lab.

The computer accounts have been set up now, and you should have received an email. Please test your accounts, and let us know if there is trouble!

This course covers 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 cover performance optimization and a few specific example GPU applications such as numerical mathematics, medical imaging, finance, and other fields, ending with a 4-week project of the student's choice.

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.

Students and TAs are in multiple time zones, so it was tricky to set up office hour times that were convenient enough.

As of May 14, we will be transitioning more to "appointment-style" office hours, now that the assignments are mainly finished. The purpose is for quick questions to help you with your projects. Email a TA ahead of time, and other times can likely be available.

Again, the original Office hours were:

• Saturday 1-4pm -- Ethan
• Sunday 1-4pm -- Alden
• Monday 1-4pm -- George

• Piazza Please ask through Piazza if you have a question/issue that likely affects other students. Piazza will be used to make announcements throughout the course.
• Global TA email: cs179.ta@gmail.com.
  But use Piazza, generally, for questions on the assignments or the material. These may be of interest to other people. Send an email to the TAs if you have something that only affects you or your project group.
• HW submission: You will be logging in remotely onto a Caltech computer in the Barr lab to submit your work. The TAs will log in there to test your work and grade it.
• IMPORTANT: updated for 2020 Instead of emailing your lab solution to the TA email, please put a zip file of your solution in your home directory on the remote Barr-lab computer, with the name lab[N]_2020_submission.zip .

  See Piazza for more details!

• 6 labs (60% of grade) (but in five weeks, due to COVID-19)
• 4 week project (40% of grade)

Please contact the Deans when there are unusual or difficult circumstances, since the Deans can give us more leeway than usual, if they feel your circumstance warrants it.  

Note! To pass the course, a "sufficient" number of "good" assignments will need to be submitted and graded before Drop Day!!! That's May 20, 2020. If you're behind or not doing well, please drop the course before Drop Day!! We may send out a "scary note" in email near that time, to students who may be in trouble of not passing, and might need to drop.

• Lab 1: assignment text. Zipped UNIX files (no updating for 2020)
  Note: please follow the instructions in the above text file instead of the instructions in the zipped folder

• Lab 2: assignment text UNIX files (no updating for 2020)

• Lab 3: assignment text UNIX files (no updating for 2020)

• Lab 4: assignment text UNIX files (no updating for 2020)
  Also, your Project Proposals will be due now, on Tuesday, May 5, so start working ahead of time on those, and feel free to ask the TAs if you need guidance.

• Lab 5: assignment text UNIX files (Lab 5 is due on May 12, 2020, while lab 6 which is optional, can count for 10% extra credit, and is due May 19, 2020)

  
  

For installing CUDA onto your own computer, you could also consider this Guide

(In 2019) DANGER! Especially for older non-Windows machines, make a Clone of the whole computer system before attempting installation! Don't try to install CUDA casually. You can easily lose your ability to log in and your entire laptop/desktop environment without this type of backup! The loss of a working computer environment can affect your other classes. With the clone backup, however, you should not lose too much time if there was a problem. But you should know how to clone your computer and then restore it!

Using the Barr machine in Annenberg will be a safer option.

FYI, Ubuntu 20.04 will be coming out shortly, and the installation process for CUDA will be a lot easier and safer, than on older Unix systems. We will try to create an instruction sheet, on how to do this.

To do the full partition backup, a suggested cloning tool is Clonezilla, where you can use these Clonezilla instructions as a reminder.
An excellent USB "burning" tool (for making a Clonezilla drive or the CUDA boot drive) is Rufus, although it requires a Windows environment to run it.

Other cloning and burning tools are acceptable, if you have your own favorites.

Finally, use this code to retrieve your hardware info after you setup CUDA.