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Environment Setup

Prerequisites

Our Environment Setup for Reference

We run all the experiments on linux machines and did not test on Windows.

Here are a few environment we have tested for reference:

  • NVIDIA A6000 48GBx8, Ubuntu 24.04, CUDA 12.4
  • NVIDIA H100 96GBx2, Red Hat Enterprise Linux 9.5, CUDA 12.6.
  • NVIDIA H100 80GBx8, Ubuntu 24.04, CUDA 12.4
  • NVIDIA H200 141GBx8, Ubuntu 24.04, CUDA 12.4

Environment Setup

  1. Config SSH key for GitHub. One of the dependencies, MASE, requires SSH to clone and install. Please set up ~/.ssh/config accordingly (refer to Connecting to GitHub with SSH).

  2. Clone the project repository

    git clone https://github.com/AICrossSim/NewComputeBench.git
cd NewComputeBench
git submodule update --init

  3. Create a new conda environment

    conda env create -f environment.yaml

  4. Activate the new environment and install required packages

    conda activate new-compute

    We recommend check if the python and pip in $PATH are from the conda environment: 

    which python
which pip

    Then install the required packages: 

    pip install -r requirements.txt

  5. (Optional) You may want to log in Wandb to track the training logs.

    wandb login