This is a walkthrough demo on machine learning to be run on HCC. For more information, visit OS2G's HCC Resource page.
HCC has a large and wide array of resources that have been used to do all kinds of amazing research! Take a look at the recorded talk video for a quick explaination or watch Hongfeng's complete talk, the slides from which are included in this repo.
The four basic steps you need to know how to do in order to use the HCC (explained in more detail in the talk recording), found on slide 4 of HCC's Kickstart Slides from 2019, are:
- Logging into HCC clusters using PuTTY(Windows)/Terminal(Mac).
- Managing files on the cluster (navigating the filesystem).
- Using modules (software) installed on the clusters.
- Submitting jobs using a job scheduler (SLURM!).
There are lots of other useful details about best practices and other details that can be found in the recording/slides, but you can easily learn the basics without needing them.
This is where we tell 'em what we're gonna tell em and have them create the initial files (ls, cd, touch), concludes with the bash file doing the slurm hello world (see HCC tutorial materials)
this is where we explain all the different SLURM options (some may not be relevant until used by the python file)
This is where the fun begins
TODO:
- add/review comments explaining the code to the python file
- fill out the rest of these sections
- replicate and confirm alex's $h1t works