HPU vs GPU - Benchmarking the Frontier of AI Hardware

In a comparison of deep learning hardware for computer vision, Habana Gaudi HPUs have emerged as a cost-effective alternative to the traditionally dominant NVIDIA GPUs. By benchmarking the YOLOv5 model training on the COCO dataset, it was found that the Habana Gaudi1 HPUs achieved a cost efficiency of $0.73 per epoch, outperforming the NVIDIA A100 GPUs, which cost $0.98 per epoch. This represents a 25% cost advantage for the Gaudi1 HPUs, although they are slower in terms of epoch time, indicating their potential for greater economic efficiency in model training. The study, conducted with AWS instances, illustrates the evolving landscape of AI hardware, with the promising Gaudi2 accelerators on the horizon potentially offering further advancements.