chopperhack19

Source code for the BNL GPU Hackathon

Data for Testing

• https://portal.nersc.gov/project/hacc/aphearin/BNLHack19/
• https://drive.google.com/file/d/1JZn3fbBELazpnrlw-0WiGzBkNZaFlT_7/view?usp=sharing

Code organization notes

• The code in the sf_history subpackage maps galaxy properties onto halos. For example, the mean_sfr function maps SFR onto halos across time; this function needs to be integrated to map stellar mass onto halos.
• The code in the mock_obs subpackage computes summary statistics of the galaxy population. The numba_gw_hist function calculates a Gaussian-weighted histogram, the kernel underlying a stellar mass function.

Getting Setup at BNL

1. Install miniconda.

   I've been told it is better to keep it out of your home area, but that might just be my account. I made a directory on the global scratch area, symlinked it to my home area, and then installed there.

   The global scratch area is /hpcgpfs01/scratch.

2. Use conda init to setup your shell if you did not install it while doing miniconda.

Deprecation notice

This repository has been archived and is no longer maintained. The code is provided for historical reference and may contain unpatched or unknown vulnerabilities. It should not be used in production systems.

4. Add module load "cuda/9.0" to your ~/.bashrc.

5. Install all of the software you need in your base conda env (e.g., numba, pytest, numpy, scipy, jax, etc.).

6. Get a node srun --pty -A hackathon -N 1 --exclusive -p long -t 3:00:00 /bin/bash