903 citations · 2.5k across the 78 of their papers we have counts for
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cs.DC2018★ 176 cited
SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks
Linnan Wang, Jinmian Ye, Yiyang Zhao +5
Going deeper and wider in neural architectures improves the accuracy, while the limited GPU DRAM places an undesired restriction on the network design domain. Deep Learning (DL) pr…
cs.DC2016★ 5 cited
Efficient Communications in Training Large Scale Neural Networks
Linnan Wang, Wei Wu, George Bosilca +2
We consider the problem of how to reduce the cost of communication that is required for the parallel training of a neural network. The state-of-the-art method, Bulk Synchronous Par…
cs.DC2015★ 9 cited
BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing
Linnan Wang, Wei Wu, Jianxiong Xiao +1
Basic Linear Algebra Subprograms (BLAS) are a set of low level linear algebra kernels widely adopted by applications involved with the deep learning and scientific computing. The m…