20 citations · 39 across the 2 of their papers we have counts for
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cs.LG2021★ 20 cited
FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference
Daya Khudia, Jianyu Huang, Protonu Basu +4
Deep learning models typically use single-precision (FP32) floating point data types for representing activations and weights, but a slew of recent research work has shown that com…
cs.LG2018
Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications
Jongsoo Park, Maxim Naumov, Protonu Basu +25
The application of deep learning techniques resulted in remarkable improvement of machine learning models. In this paper provides detailed characterizations of deep learning models…