What Is NVIDIA RAPIDS?
By Karthick Selvam · Published
RAPIDS is a suite of open-source libraries from NVIDIA for GPU-accelerated data science and analytics.
Core libraries
cuDF (a pandas-like DataFrame library), cuML (machine learning algorithms with a scikit-learn-like API) and cuGraph (graph analytics).
Zero-code-change acceleration
The cudf.pandas accelerator mode can run existing pandas code on the GPU, falling back to the CPU for unsupported operations. A similar cuml.accel mode exists for some scikit-learn workloads.
Scaling and Spark
Dask enables multi-GPU and multi-node scaling, and the RAPIDS Accelerator for Apache Spark speeds up Spark SQL and DataFrame jobs on GPUs.
When it helps
Large tabular datasets, heavy joins and group-bys, and iterative model training typically see the biggest gains. Small datasets may not benefit.
Frequently asked questions
Is RAPIDS free?
Yes, the libraries are open source under the Apache 2.0 licence.
Related programmes
- GPU Programming with CUDA
- Accelerated Data Science with NVIDIA RAPIDS
- Building and Serving LLM Apps with NVIDIA NIM & NeMo
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NVIDIA & GPU Computing guides
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What Are NVIDIA NIM and NeMo?
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