Installing dask-hip#
2026-07-06
2 min read time
You can install dask-hip via AMD PyPI as described below. This is recommended for users of the package. For developers interested in modifying or contributing to the open-source dask-hip component, see the Build instructions.
See System requirements for information regarding supported operating systems, ROCm versions, and AMD GPUs before installing dask-hip.
ROCm component prerequisites#
dask-hip requires the amdsmi Python package, which is distributed with ROCm (not via AMD
PyPI). Install it from the ROCm installation before installing dask-hip. See AMD SMI documentation for more information.
cd /opt/rocm/share/amd_smi
pip install .
Install dask-hip via AMD PyPI#
Packaged versions of dask-hip and its dependencies are distributed via AMD PyPI. This section describes how to install dask-hip via this package index.
Create and activate a Conda environment with a compatible Python version, such as 3.11 or 3.12 as shown below. For more information on compatible Python versions, see System requirements.
conda create --name dask-hip python=3.12 # Specify your Python version
conda activate dask-hip
Alternatively, create a Python virtual environment:
python3 -m venv dask-hip-env
source dask-hip-env/bin/activate
dask-hip can then be installed into either environment using pip and the AMD PyPI URL:
pip install amd-dask-hip --extra-index-url=https://pypi.amd.com/rocm-7.2.3/simple/
hip-ucxx support#
To install the amd-distributed-hipucxx package for high-performance UCX communication
(ROCm-IPC, InfiniBand):
pip install amd-distributed-hipucxx --extra-index-url=https://pypi.amd.com/rocm-7.2.3/simple/
pynvml compatibility#
dask-hip bundles a pynvml2amdsmi compatibility shim that maps pynvml API calls to their
AMD SMI equivalents. This allows upstream packages such as dask.distributed to query GPU
information transparently on AMD hardware without modification.