Scaling TensorFlow to 300 million predictions per second
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Abstract (arXiv)
We present the process of transitioning machine learning models to the TensorFlow framework at a large scale in an online advertising ecosystem. In this talk we address the key challenges we faced and describe how we successfully tackled them; notably, implementing the models in TF and serving them efficiently with low latency using various optimization techniques.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 3 of its 7 references that are in the map. First posted on arXiv 20 Sep 2021.
Builds on
3 of 7 references.
References · 3
Built on by
Citing papers per year: 2022: 1; 2023: 1.
2 papers.