179 citations · 308 across the 6 of their papers we have counts for
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cs.AR2021★ 19 cited
First-Generation Inference Accelerator Deployment at Facebook
Michael Anderson, Benny Chen, Stephen Chen +112
In this paper, we provide a deep dive into the deployment of inference accelerators at Facebook. Many of our ML workloads have unique characteristics, such as sparse memory accesse…
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…