https://github.com/rapidsai/rapids-examples
https://github.com/rapidsai/rapids-examples
Last synced: 6 months ago
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- Host: GitHub
- URL: https://github.com/rapidsai/rapids-examples
- Owner: rapidsai
- Created: 2021-01-26T18:46:10.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2023-02-24T15:52:14.000Z (almost 3 years ago)
- Last Synced: 2024-04-14T03:13:29.621Z (over 1 year ago)
- Language: Jupyter Notebook
- Size: 9.7 MB
- Stars: 31
- Watchers: 7
- Forks: 24
- Open Issues: 12
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Metadata Files:
- Readme: README.md
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README
# Rapids Examples
### Assumptions
1. [Conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install) is installed.
2. [CUDA](https://developer.nvidia.com/cuda-downloads) 10.0 > is installed and on the PATH.
## Examples List
| Example | Description |
|:-------:| :-----------------------------------------------|
[python-kernel-wrapper](./python-kernel-wrapper) | Demonstrates processing python cudf dataframes in a cuda kernel
[pycuda\_cudf\_integration](./pycuda_cudf_integration) | Demonstrates processing python cudf dataframes using `pycuda`
[tfidf-benchmark](./tfidf-benchmark) | Benchmarks NLP text processing pipeline in cuML + Dask vs. Apache Spark
[rapids_triton_example](./rapids_triton_example) | Example of using RAPIDS+Pytorch with Nvidia Triton.
[cuBERT_topic_modelling](./cuBERT_topic_modelling) | Leveraging BERT, TF-IDF and NVIDIA RAPIDS to create easily interpretable topics.