Getting Started
Heat is a Python package for accelerated and distributed tensor computations. Internally, it is based on PyTorch. Consequently, all operating systems that support Python and PyTorch also support a Heat installation. Currently, this list contains at least Linux, MacOS and Windows. However, most of our development is done under Linux and interoperability should therefore be optimal.
Prerequisites
Python
Heat requires Python 3.7 or greater. You can check your Python by running:
python3 --version
If you do not have a recent installation on you system, you may want to upgrade it.
sudo apt-get update && sudo apt-get install python3
sudo dnf update python3
If you have no administrator privileges on your system, because you are working on a cluster for example, make sure to check its user guide, the module system (module spider python) or get in touch with the administrators.
Optional Dependencies
You can accelerate computations with Heat in different ways. For GPU acceleration ensure that you have a CUDA installation on your system. Distributed computations require an MPI stack on your computer. We recommend MVAPICH or OpenMPI. Finally, for parallel data I/O, Heat offers interface to HDF5 and NetCDF. You can obtain these packages using your operating system’s package manager.
Installation
Virtual Environments
We highly recommend to use virtual environments (venv) for managing your Python packages. A virtual environment is a self-contained directory tree for a particular Python version and its packages. It allows you not only to install packages without administrator privileges, install pip, Python’s package manager, but also to have multiple package environments with different package versions in parallel.
You can find the complete manual for venv in the Python documentation. Below is a small code snippet that creates a new virtual environment in your home directory (~/.virtualenvs/heat). The subsequent command enables the environment. You can access the Python interpreter by typing python and PIP with pip.
python3 -m venv ~/.virtualenvs/heatenv
source ~/.virtualenvs/heatenv/bin/activate
You can deactivate a virtual environment by executing:
deactivate
pip
Official Heat releases are made available on the Python Package Index (PyPI). You obtain the latest version by running:
pip install heat
Optionally, you can enable and install HDF5 and/or NetCDF support by adding the respective extra requirements as follows.
pip install 'heat[hdf5,netcdf]'
Verification
To ensure that Heat was installed correctly, you can run this tiny code snippet that creates a vector with 10 entries.
python -c "import heat as ht; print(ht.arange(10))"
You should see the following output
DNDarray([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=ht.int32, device=cpu:0, split=None)
Building From Source
For most users a Heat installation from pip will be the most simple. However, if you want to test out the latest features or even want to contribute to Heat, you will need to build from source. At first, clone our repository by running:
git clone https://github.com/helmholtz-analytics/heat.git
Afterwards, change to the cloned source code directory and run the setup scripts.
$ cd heat
$ pip install -e '.[hdf5, netcdf]'
Support Channels
We use StackOverflow as a forum for questions about Heat. If you do not find an answer to your question, then please ask a new question there and be sure to tag it with “pyheat”.