11 citations · 23 across the 8 of their papers we have counts for
8 papers
SuperBench: Improving Cloud AI Infrastructure Reliability with Proactive Validation
Yifan Xiong, Yuting Jiang, Ziyue Yang +17
Reliability in cloud AI infrastructure is crucial for cloud service providers, prompting the widespread use of hardware redundancies. However, these redundancies can inadvertently…
SuperScaler: Supporting Flexible DNN Parallelization via a Unified Abstraction
Zhiqi Lin, Youshan Miao, Guodong Liu +10
With the growing model size, deep neural networks (DNN) are increasingly trained over massive GPU accelerators, which demands a proper parallelization plan that transforms a DNN mo…
PIT: Optimization of Dynamic Sparse Deep Learning Models via Permutation Invariant Transformation
Ningxin Zheng, Huiqiang Jiang, Quanlu Zhang +8
Dynamic sparsity, where the sparsity patterns are unknown until runtime, poses a significant challenge to deep learning. The state-of-the-art sparsity-aware deep learning solutions…
Argus: A Fully Transparent Incentive System for Anti-Piracy Campaigns (Extended Version)
Xian Zhang, Xiaobing Guo, Zixuan Zeng +7
Anti-piracy is fundamentally a procedure that relies on collecting data from the open anonymous population, so how to incentivize credible reporting is a question at the center of…
Agatha: Smart Contract for DNN Computation
Zihan Zheng, Peichen Xie, Xian Zhang +6
Smart contract is one of the core features of Ethereum and has inspired many blockchain descendants. Since its advent, the verification paradigm of smart contract has been improvin…
TextNAS: A Neural Architecture Search Space tailored for Text Representation
Yujing Wang, Yaming Yang, Yiren Chen +7
Learning text representation is crucial for text classification and other language related tasks. There are a diverse set of text representation networks in the literature, and how…
Towards Efficient Large-Scale Graph Neural Network Computing
Lingxiao Ma, Zhi Yang, Youshan Miao +4
Recent deep learning models have moved beyond low-dimensional regular grids such as image, video, and speech, to high-dimensional graph-structured data, such as social networks, br…
RPC Considered Harmful: Fast Distributed Deep Learning on RDMA
Jilong Xue, Youshan Miao, Cheng Chen +3
Deep learning emerges as an important new resource-intensive workload and has been successfully applied in computer vision, speech, natural language processing, and so on. Distribu…