Polars and NVIDIA engineers are teaming up to introduce GPU acceleration to Polars DataFrames, promising a significant boost in speed for specific workloads. The collaboration will result in a GPU engine that allows users to choose whether to run their data workloads on the CPU or GPU. This new functionality, which will be introduced as a feature flag, will be maintained by NVIDIA and integrated into the Polars project soon. GPUs excel in parallel processing, making them ideal for matrix and vector operations in deep learning algorithms. The partnership between Polars and the RAPIDS team will make GPU acceleration more accessible to a wider range of users.
https://pola.rs/posts/polars-on-gpu/