41 citations · 67 across the 11 of their papers we have counts for
22 papers
High fusion computers: The IoTs, edges, data centers, and humans-in-the-loop as a computer
Wanling Gao, Lei Wang, Mingyu Chen +13
Emerging and future applications rely heavily upon systems consisting of Internet of Things (IoT), edges, data centers, and humans-in-the-loop. Significantly different from warehou…
Shift-and-Balance Attention
Chunjie Luo, Jianfeng Zhan, Tianshu Hao +2
Attention is an effective mechanism to improve the deep model capability. Squeeze-and-Excite (SE) introduces a light-weight attention branch to enhance the network's representation…
HPC AI500: Representative, Repeatable and Simple HPC AI Benchmarking
Zihan Jiang, Wanling Gao, Fei Tang +6
Recent years witness a trend of applying large-scale distributed deep learning algorithms (HPC AI) in both business and scientific computing areas, whose goal is to speed up the tr…
FLBench: A Benchmark Suite for Federated Learning
Yuan Liang, Yange Guo, Yanxia Gong +3
Federated learning is a new machine learning paradigm. The goal is to build a machine learning model from the data sets distributed on multiple devices so-called an isolated data i…
HPC AI500: The Methodology, Tools, Roofline Performance Models, and Metrics for Benchmarking HPC AI Systems
Zihan Jiang, Lei Wang, Xingwang Xiong +6
The recent years witness a trend of applying large-scale distributed deep learning in both business and scientific computing areas, whose goal is to speed up the training time to a…
Finet: Using Fine-grained Batch Normalization to Train Light-weight Neural Networks
Chunjie Luo, Jianfeng Zhan, Lei Wang +1
To build light-weight network, we propose a new normalization, Fine-grained Batch Normalization (FBN). Different from Batch Normalization (BN), which normalizes the final summation…