cuDF - GPU DataFrames
📢 cuDF can now be used as a no-code-change accelerator for pandas! To learn more, see here!
cuDF (pronounced "KOO-dee-eff") is a GPU DataFrame library
for loading, joining, aggregating, filtering, and otherwise
manipulating data. cuDF leverages
libcudf, a
blazing-fast C++/CUDA dataframe library and the Apache
Arrow columnar format to provide a
GPU-accelerated pandas API.
You can import cudf
directly and use it like pandas
:
import cudf
tips_df = cudf.read_csv("https://github.com/plotly/datasets/raw/master/tips.csv")
tips_df["tip_percentage"] = tips_df["tip"] / tips_df["total_bill"] * 100
print(tips_df.groupby("size").tip_percentage.mean())
Or, you can use cuDF as a no-code-change accelerator for pandas, using
cudf.pandas
.
cudf.pandas
supports 100% of the pandas API, utilizing cuDF for
supported operations and falling back to pandas when needed:
%load_ext cudf.pandas
import pandas as pd
tips_df = pd.read_csv("https://github.com/plotly/datasets/raw/master/tips.csv")
tips_df["tip_percentage"] = tips_df["tip"] / tips_df["total_bill"] * 100
print(tips_df.groupby("size").tip_percentage.mean())
Resources
See the RAPIDS install page for
the most up-to-date information and commands for installing cuDF
and other RAPIDS packages.
Installation
CUDA/GPU requirements
- CUDA 11.2+
- NVIDIA driver 450.80.02+
- Volta architecture or better (Compute Capability >=7.0)
Pip
cuDF can be installed via pip
from the NVIDIA Python Package Index.
Be sure to select the appropriate cuDF package depending
on the major version of CUDA available in your environment:
For CUDA 11.x:
pip install --extra-index-url=https://pypi.nvidia.com cudf-cu11
For CUDA 12.x:
pip install --extra-index-url=https://pypi.nvidia.com cudf-cu12
Conda
cuDF can be installed with conda (via miniforge) from the rapidsai
channel:
conda install -c rapidsai -c conda-forge -c nvidia \
cudf=24.12 python=3.12 cuda-version=12.5
We also provide nightly Conda packages built from the HEAD
of our latest development branch.
Note: cuDF is supported only on Linux, and with Python versions 3.10 and later.
See the RAPIDS installation guide for more OS and version info.
Build/Install from Source
See build instructions.
Contributing
Please see our guide for contributing to cuDF.