26 citations · 26 across the 2 of their papers we have counts for
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cs.LG2020
Revisiting BFloat16 Training
Pedram Zamirai, Jian Zhang, Christopher R. Aberger +1
State-of-the-art generic low-precision training algorithms use a mix of 16-bit and 32-bit precision, creating the folklore that 16-bit hardware compute units alone are not enough t…
cs.LG2018
High-Accuracy Low-Precision Training
Christopher De Sa, Megan Leszczynski, Jian Zhang +4
Low-precision computation is often used to lower the time and energy cost of machine learning, and recently hardware accelerators have been developed to support it. Still, it has b…