Advance preparation for laptops

Most of the exercises to be performed during the school are intended to be done on cloud-based resources (e.g., the SSL BinderHub at U. of Chicago) as recommended by the instructors. But the exercises can be also be done on personal laptops with suitable preparation.

Also, some of the exercises require downloading, compiling, and running files, either directly on the personal laptops of participants, or on other resources that are available and can be accessed remotely through laptops. In order to do the exercises directly on a personal laptop, certain tools (compilers, etc.) must be installed in advance. This page describes how to install the appropriate software versions, as well as how to perform simple tests to verify that a laptop installation works correctly.

Git & GitHub

  • All participants should have a GitHub account. It's free.
  • Please create a SSH key pair and add it to your GitHub account. This is required in order to push local changes to a GitHub repository. For this, please follow the instructions from GitHub (note that you can select your operating system on the top).
  • While we try to repeat the basics, some familiarity with git is recommended. A good starting point (aimed at complete beginners) is for example this tutorial.
  • If you have learned about git previously, how about taking a look at a git cheat sheet to refresh your knowledge?

conda & Anaconda

The Python portions of the workshop can be run in a local conda environment. You can obtain miniconda or Anaconda for this purpose. We will provided suggested environment files, so miniconda is fine unless you already have the Anaconda Python distribution. You can always type conda install anaconda to install the rest of the Anaconda default package collection if you really want to. We will be using the conda-forge and pytorch channels.


The Terminal app provides you with a Unix shell, either bash or zsh, as well as many command-line tools. Much of what you will need (apart from miniconda) seems to be preinstalled on the latest M1-, M2-, and M3-based Macs with macOS Sonoma.

For installing the other requirements, we highly recommend the Homebrew package manager. (If you are already familiar with MacPorts, you can use it instead.) Learn more about Homebrew at To install it:

/bin/bash -c "$(curl -fsSL"

Be sure to follow the instructions in the output to add Homebrew's path to your shell environment.

If Apple's Xcode Command Line Tools weren't previously installed (and if your Mac needs them), then the Homebrew installation should have taken care of that for you as well. You may also find that Apple's full Xcode distribution is required in order to build codes successfully on macOS, even if you use conda and Homebrew. Xcode is a free (if slow) download from the App Store.

Now, install a recent C/C++ compiler, or at least an OpenMP library. The default Apple system compiler (clang) does not support OpenMP out of the box, which is used in some lectures. One way to overcome this problem is to install the GNU Compiler Collection (GCC), version >= 4.8.

In the terminal, these are the commands to install GCC in Homebrew:

brew install gcc

The default version of GCC installed by Homebrew is currently gcc-14. Thus the correct command to use for calling the C/C++ compiler is gcc-14 or c++-14. These commands are located in /usr/local/bin, which should be in your PATH. (Be aware that macOS Sonoma has similar, built-in commands called gcc and c++ in /usr/bin, but all such commands are straight-up copies of clang. Similarly, in earlier versions of macOS, gcc is just Clang in an emulation mode, while c++ is a symlink to clang++.)

For those who would prefer to do the exercises with Apple Clang, instructions on how to install and use a compatible OpenMP library are here. Again, Homebrew is a very convenient source for obtaining the necessary software. If you are interested in enhancing your Homebrew installation with other useful tools, see the post "Setup a new Mac" or "Setup an Apple Silicon Mac" for suggestions.


Make sure you have a GNU C/C++ compiler >= 4.8 installed.


Windows 10 and 11 -- set up a Linux shell with WSL 2, install git, then follow Linux instructions.

Compiler test

Edit a file containing the following C program. Call it omptest.c:

#include <omp.h>
#include <stdio.h>

int main () {
    #pragma omp parallel
        printf("Hello world\n");

Then compile and run the file as follows (you may need to substitute gcc-14 as your compiler name in macOS, see above):

gcc -fopenmp omptest.c -o omptest; ./omptest

The output should contain one occurrence of "Hello world" for each virtual core in your system.

Setup instructions for the ML tutorial

The machine learning tutorial will use the SSL BinderHub at U. of Chicago. Detailed setup instructions will be presented during the school.