1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.DC2020★ 1 cited
DaSGD: Squeezing SGD Parallelization Performance in Distributed Training Using Delayed Averaging
Qinggang Zhou, Yawen Zhang, Pengcheng Li +4
The state-of-the-art deep learning algorithms rely on distributed training systems to tackle the increasing sizes of models and training data sets. Minibatch stochastic gradient de…
cs.ET2019
A Parallel Bitstream Generator for Stochastic Computing
Yawen Zhang, Runsheng Wang, Xinyue Zhang +5
Stochastic computing (SC) presents high error tolerance and low hardware cost, and has great potential in applications such as neural networks and image processing. However, the bi…