1. CS791v Homework and Submission
Rui (Ray) Wu

2. Overview How to submit homework How to install CUDA toolkit
How to use Cubix

3. How to submit homework Step 1: Register for a GitHub student account
Step 2: Download Rui’s GitHub template repository:
Step 3: Add Rui as your collaborator

4. Step 1: Register a GitHub student account
Apply for a UNR edu address. Instructions are here:
Register for a GitHub student account:
With a GitHub student account you can create a private repository (for free) ,

5. Step 2: Download Rui’s GitHub template repository
Here is the link:
Folder structure: include (header files), src (.cpp and .cu), build (DON’T UPLOAD, files generated by the “make” command), README file (introduction)
A similar folder structure is acceptable, e.g. data (.csv)
Three special files:
.gitignore: what kind files will not be uploaded
makefile: commands to compile your program and generate executable file. Here is a tutorial how to write a makefile:
Cmake: more power but more complex. CMake recognizes which compilers to use for a given kind of source. Daniel provides PA0 cmake file. Here is a tutorial on Cmake:

6. Step 3: Add Rui as your collaborator
My GitHub id: ruiwu1990
Live demo how to add: settings->collaborators->type Rui’s ID
How I will check your homework: I will ONLY use Make in the TERMINAL, so test it in a terminal before the deadline.
Place all your homework in the same repository (PA0, PA1, …)
Cuda IDEs will be introduced in the next class

7. How to install the CUDA toolkit
Ubuntu 16.04
First you need to check if the driver is installed, by using “nvidia-smi”
If “cannot communicate with graphic card”, follow instructions:

8. How to install the CUDA toolkit
Here is the download link:
Latest version is 9.1 but it is not stable. We are using 9.0 in this course
Step 1, you need to cd into the download folder
Step 2: sudo apt-key add /var/cuda-repo-9-0-local/7fa2af80.pub
After Step 4, you may need to run: sudo apt-get -f install

9. How to install the CUDA toolkit
Setup your PATH variable
This tells your shell where to find the executable file->nvcc
apt install nvidia-cuda-toolkit may work BUT it changes the paths and makes the installation of other tools more difficult.
If it does not work: try this:

10. How to use Cubix First you need a Cubix account (cse account)
Some of you already have one,
The rest need to ask for one: CSE Admins,
replace <username> with your username
If you execute any GPU program in Cubix, you need to use Slurm:
Slurm: a workload manager and manages all the execution requests in queues.

11. How to use Cubix Environmental parameter setup
Execute program: srun nvcc ./PA0
Other slurm commands:

12. PA0
If everything is installed correctly:
If not:
Let’s do a live demo

13. Questions & Comments?
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