433 citations · 1.2k across the 21 of their papers we have counts for
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Performance Evaluation of Deep Learning Tools in Docker Containers
Pengfei Xu, Shaohuai Shi, Xiaowen Chu
With the success of deep learning techniques in a broad range of application domains, many deep learning software frameworks have been developed and are being updated frequently to…
Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs
Shaohuai Shi, Qiang Wang, Xiaowen Chu
Deep learning frameworks have been widely deployed on GPU servers for deep learning applications in both academia and industry. In training deep neural networks (DNNs), there are m…
Speeding up Convolutional Neural Networks By Exploiting the Sparsity of Rectifier Units
Shaohuai Shi, Xiaowen Chu
Rectifier neuron units (ReLUs) have been widely used in deep convolutional networks. An ReLU converts negative values to zeros, and does not change positive values, which leads to…
Supervised Learning Based Algorithm Selection for Deep Neural Networks
Shaohuai Shi, Pengfei Xu, Xiaowen Chu
Many recent deep learning platforms rely on third-party libraries (such as cuBLAS) to utilize the computing power of modern hardware accelerators (such as GPUs). However, we observ…
GPGPU Performance Estimation with Core and Memory Frequency Scaling
Qiang Wang, Xiaowen Chu
Graphics Processing Units (GPUs) support dynamic voltage and frequency scaling (DVFS) in order to balance computational performance and energy consumption. However, there still lac…