32 citations · 37 across the 7 of their papers we have counts for
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cs.AR2025
Bit-Accurate Modeling of GPU Matrix Multiply-Accumulate Units: Demystifying Numerical Discrepancy and Accuracy
Peichen Xie, Shuotao Xu, Yang Wang +2
Modern AI accelerators rely on matrix multiply-accumulate units (MMAUs), such as NVIDIA Tensor Cores and AMD Matrix Cores, to accelerate deep neural network workloads. MMAUs expose…
cs.AR2020★ 2 cited
Customizing Trusted AI Accelerators for Efficient Privacy-Preserving Machine Learning
Peichen Xie, Xuanle Ren, Guangyu Sun
The use of trusted hardware has become a promising solution to enable privacy-preserving machine learning. In particular, users can upload their private data and models to a hardwa…