Installation

KvikIO can be installed using Conda/Mamba or from source.

Conda/Mamba

We strongly recommend using mamba inplace of conda, which we will do throughout the documentation.

Install the stable release from the rapidsai channel like:

# Install in existing environment
mamba install -c rapidsai -c conda-forge kvikio
# Create new environment (CUDA 11.8)
mamba create -n kvikio-env -c rapidsai -c conda-forge python=3.10 cuda-version=11.8 kvikio
# Create new environment (CUDA 12.0)
mamba create -n kvikio-env -c rapidsai -c conda-forge python=3.10 cuda-version=12.0 kvikio

Install the nightly release from the rapidsai-nightly channel like:

# Install in existing environment
mamba install -c rapidsai-nightly -c conda-forge kvikio
# Create new environment (CUDA 11.8)
mamba create -n kvikio-env -c rapidsai-nightly -c conda-forge python=3.10 cuda-version=11.8 kvikio
# Create new environment (CUDA 12.0)
mamba create -n kvikio-env -c rapidsai-nightly -c conda-forge python=3.10 cuda-version=12.0 kvikio

Note

If the nightly install doesn’t work, set channel_priority: flexible in your .condarc.

Build from source

In order to setup a development environment run:

# CUDA 11.8
mamba env create --name kvikio-dev --file conda/environments/all_cuda-118_arch-x86_64.yaml
# CUDA 12.0
mamba env create --name kvikio-dev --file conda/environments/all_cuda-120_arch-x86_64.yaml

To build and install the extension run:

./build.sh kvikio

One might have to define CUDA_HOME to the path to the CUDA installation.

In order to test the installation, run the following:

pytest tests/

And to test performance, run the following:

python benchmarks/single-node-io.py