  The application of deep learning techniques resulted in remarkable
improvement of machine learning models. In this paper provides detailed
characterizations of deep learning models used in many Facebook social network
services. We present computational characteristics of our models, describe high
performance optimizations targeting existing systems, point out their
limitations and make suggestions for the future general-purpose/accelerated
inference hardware. Also, we highlight the need for better co-design of
algorithms, numerics and computing platforms to address the challenges of
workloads often run in data centers.
