Read the blog post here: https://developer.nvidia.com/blog/even-easier-introduction-cuda/
- Make many small commits as you go through each step.
- Add your .cu files:
- add.cu
- add_block.cu
- add_grid.cu
- Upload profiling results. This can be a [Markdown] or plain text table or a data file (e.g. Excel, Google Sheets) with a image figure (png, jpg, etc). Note, these may be impacted by other students running on the GPU at the same time.
You can access the GPU server for this course ('keroppi') using ssh:
ssh yourSmithUserName@keroppi
You can run this command in either Terminal (MacOS) or PowerShell/Command Prompt (Windows). Your password is set to your 99 number but must be changed upon login. You will need to be on campus or logged in via the VPN to the Smith network.
I have installed several command line (CLI) editors:
- vi/vim
- nano
- micro
- emacs
Please let me know if there are any others you would like installed. Also, I've posted a short tutorial on using VS Code on Moodle.
You can [install CUDA locally] if you have an NVIDIA GPU.
Upload your answers to questions 2. and 3. in the Exercises section.
Browse through the Related Resources and Where to From Here sections along with other links.