cuDF pandas accelerator mode (cudf.pandas) is built on cuDF and accelerates pandas code on the GPU. It supports 100% of the Pandas API, using the GPU for supported operations, and automatically falling back to pandas for other operations.

%load_ext cudf.pandas
# pandas API is now GPU accelerated

import pandas as pd

df = pd.read_csv("filepath")  # uses the GPU!
df.groupby("col").mean()  # uses the GPU!
df.rolling(window=3).sum()  # uses the GPU!
df.apply(set, axis=1)  # uses the CPU (fallback)

Try it on Google Colab!#

Zero Code Change Acceleration

Just %load_ext cudf.pandas in Jupyter, or pass -m cudf.pandas on the command line.

Third-Party Library Compatible

cudf.pandas is compatible with most third-party libraries that use pandas.

Run the same code on CPU or GPU

Nothing changes, not even your import statements, when going from CPU to GPU.

100% of the Pandas API

Combines the full flexibility of Pandas with blazing fast performance of cuDF

cudf.pandas is now Generally Available (GA) as part of the cudf package. See RAPIDS Quick Start to get up-and-running with cudf.