Beware of misleading GPU vs CPU benchmarks
Do you use NumPy, Pandas, or scikit-learn and want to get faster results?
Nvidia has created GPU-based replacements for each of these with the shared promise of extra speed.
For example, if you visit the front page of NVidia’s RAPIDS project, you’ll see benchmarks showing cuDF, a GPU-based Pandas replacement, is 15× to 80× faster than Pandas!
Unfortunately, while those speed-ups are impressive, they are also misleading.
GPU-based libraries might be the answer to your performance problems… or they might be an an unnecessary and expensive distraction.
Problem #1: Comparing against a single CPU core
Those benchmarks showing cuDF is 15× to 80× faster than Pandas may be accurate, but they’re comparing against Pandas running on a single CPU core.
Specifically, the RAPIDS page says