NVIDIA has released the cuDF library as a replacement for the popular pandas among data professionals, now entering the GA status after being open-sourced last year. This version works almost identically to the original pandas, eliminating the need for any code modifications.
The new cuDF is part of the RAPIDS suite developed by NVIDIA, utilizing GPU-accelerated libraries. Despite this, the API remains similar to the original library, much like cuML aims to mimic scikit-learn.
The new cuDF strives to automatically utilize GPU if available; otherwise, it will run on the CPU instead. All the functions of pandas are included, allowing for a seamless transition of code to run on cuDF continuously.
The advantage of cuDF is that it performs certain types of tasks faster than using just the CPU, such as loading very large tables that would previously take minutes can now be done in a matter of seconds.
cuDF is an open-source library that is available for free use. Organizations looking for support can purchase it through the upcoming NVIDIA AI Enterprise 5.0 release.
TLDR: NVIDIA has introduced cuDF as a GPU-accelerated replacement for pandas, offering similar functionality and performance enhancements for data processing tasks.
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