This release is a pre-release and may not be stable for production use.
Dask CUDA
Various utilities to improve deployment and management of Dask workers on CUDA-enabled systems.
This library is experimental, and its API is subject to change at any time without notice.
Example
from dask_cuda import LocalCUDACluster
from dask.distributed import Client
cluster = LocalCUDACluster()
client = Client(cluster)
Documentation is available here.
What this is not
This library does not automatically convert your Dask code to run on GPUs.
It only helps with deployment and management of Dask workers in multi-GPU systems. Parallelizing GPU libraries like RAPIDS and CuPy with Dask is an ongoing effort. You may wish to read about this effort at blog.dask.org for more information. Additional information about Dask-CUDA can also be found in the docs.
1 maintainer
Metadata
1 maintainer
Release files for dask-cuda 0.18.0a201130
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| File | Size | Uploaded | Provenance | Actions |
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Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
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| dask_cuda-0.18.0a201130-py3-none-any.whl | Python 3 | none | any | Details for dask_cuda-0.18.0a201130-py3-none-any.whl |
Total release size: 95.4 kB
Release files / dask-cuda-0.18.0a201130.tar.gz
| Download URL | dask-cuda-0.18.0a201130.tar.gz |
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Release files / dask_cuda-0.18.0a201130-py3-none-any.whl
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