Python on NVIDIA Grace
Python is an interpreted, high-level, general-purpose programming language, with interpreters that are available for many operating systems and architectures, including Arm64. Python 2.7 went end-of-life on January 1, 2020, so we recommended that you upgrade to a Python 3.x version.
Installing Python packages
When pip, the standard package installer for Python, is used, it pulls the packages from Python Package Index and other indexes. If pip cannot find a pre-compiled package, it automatically downloads, compiles, and builds the package from source code. It typically takes a few more minutes to install the package from source code than from pre-built, especially for large packages (for example, pandas).
To install common Python packages from the source code, you need to install the following development tools:
On RedHat
sudo yum install "@Development tools" python3-pip python3-devel blas-devel gcc-gfortran lapack-devel
python3 -m pip install --user --upgrade pip
On Debian/Ubuntu
sudo apt update
sudo apt-get install build-essential python3-pip python3-dev libblas-dev gfortran liblapack-dev
python3 -m pip install --user --upgrade pip
Scientific and Numerical Applications
Python relies on native code to achieve high performance. For scientific and numerical applications, NumPy and SciPy provide an interface to high performance computing libraries such as ATLAS, BLAS, BLIS, OpenBLAS, and so on. These libraries contain code tuned for Arm64 processors, and especially the Arm Neoverse V2 core found in NVIDIA Grace.
We recommend that you use the latest software versions as much as possible. If the latest version migration is not feasible, ensure that it is at least the minimum version recommended below. Multiple fixes related to data precision and correctness on Arm64 went into OpenBLAS between v0.3.9 and v0.3.17 and the following SciPy and NumPy versions have been upgraded OpenBLAS from v0.3.9 to OpenBLAS v0.3.17.
Here are the minimum versions:
- OpenBLAS: >= v0.3.17
- SciPy: >= v1.7.2
- NumPy: >= 1.21.1
The default SciPy and NumPy binary installations with pip3 install numpy scipy
are configured to use OpenBLAS. The default installations of SciPy and NumPy
are easy to setup and well tested.
Anaconda and Conda
Anaconda is a distribution of the Python and R programming languages for scientific computing that aim to simplify package management and deployment.
Anaconda has had support for Arm64 via AWS Graviton 2 since since 2021, so Anaconda works very well on NVIDIA Grace. Instructions to install the full Anaconda package installer can be found at https://docs.anaconda.com/. Anaconda also offers a lightweight version called Miniconda which is a small, bootstrap version of Anaconda that includes only conda, Python, the packages they depend on, and a small number of other useful packages, including pip, zlib and a few others.