| Name | dask-cuda JSON |
| Version |
24.12.0
JSON |
| download |
| home_page | None |
| Summary | Utilities for Dask and CUDA interactions |
| upload_time | 2024-12-12 18:21:00 |
| maintainer | None |
| docs_url | None |
| author | NVIDIA Corporation |
| requires_python | >=3.10 |
| license | Apache 2.0 |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
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
-------
```python
from dask_cuda import LocalCUDACluster
from dask.distributed import Client
cluster = LocalCUDACluster()
client = Client(cluster)
```
Documentation is available [here](https://docs.rapids.ai/api/dask-cuda/nightly/).
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](https://rapids.ai) and
[CuPy](https://cupy.chainer.org) with Dask is an ongoing effort. You may wish
to read about this effort at [blog.dask.org](https://blog.dask.org) for more
information. Additional information about Dask-CUDA can also be found in the
[docs](https://docs.rapids.ai/api/dask-cuda/nightly/).
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