Tech Ref

You should make a cs377 directory under your home directory on your CS account, and protect it:

$ cd
$ mkdir cs377
$ chmod 700 cs377

Your programming assignments should each be saved in a subdirectory named cs377. This makes it easy to use the submit377 script for each individual assignment, as well as keeps your assignments organized.

$ cd cs377
$ mkdir prog1
$ cd prog1
~~~ repeat: edit, compile, run
~~~ until: your program is ready to submit
$ cd ..
$ submit377 asmt1 prog1

Here is a technical reference for setting up language environments on spaceserver, then compiling and running your programs. Be sure you have a home bin directory, and if you don't, create one via:

$ cd 
$ mkdir bin
$ cd bin

Next, use the following commands to copy the scripts you'll need to use concurrent programming languages on your CS linux account:

$ cp ~mlsmith/bin/set-upc-env ./

To set up kroc's environment:

$  source /usr/local/bin/kroc-setup.sh

To compile and run a kroc (occam) program:

$ kroc myprog.occ
$ ./myprog

To compile a program that uses the course library: (like the ones we'll be compiling in class)

$ kroc myproc.occ -lcourse

To set up UPC's environment:

$ source ~/bin/set-upc-env

To compile and run a UPC program:

$ upcc -T n myprog.upc
$ upcrun myprog

(where n is the number of threads you would like myprog.upc to spawn at runtime)

Vassar CS Department's GPGPU cluster: hpc

• hpc is the cluster's head node and a virtual machine (VM)
• webpage: https://hpc.cs.vassar.edu/ (accessible only behind CS firewall)
• uses Slurm (Simple Linux Resource Manager) to run jobs (interactive or batch)
  
  

Must ssh to hpc (from behind the CS firewall):

$ ssh vassarID@hpc.cs.vassar.edu

To compile (using Nvidia C compiler):

$ nvcc -o my-cuda-prog my-cuda-prog.cu

To run interactive: (using slurm)

$ srun my-cuda-prog

To run batch: (using slurm–requires script)

$ sbatch my-cuda-script