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Wei Lin 0016
Person information
- affiliation: Alibaba Group, China
- affiliation (former): Microsoft, Redmond, WA, USA
Other persons with the same name
- Wei Lin — disambiguation page
- Wei Lin 0001
— Case Western Reserve University, Department of Electrical Engineering and Computer Science, Cleveland, OH, USA (and 2 more)
- Wei Lin 0002
- Wei Lin 0003
- Wei Lin 0004
- Wei Lin 0005 — Sun Yat-sen University (Zhongshan University), Department of Mathematics, China
- Wei Lin 0006 — Northwestern Polytechnical University, School of Science, Xi'an, China (and 1 more)
- Wei Lin 0007 — Northwestern Polytechnical University, School of Computer Science, China
- Wei Lin 0008 — California Institute of Technology
- Wei Lin 0009 — University of Pennsylvania, Department of Radiology, USA
- Wei Lin 0010 — Tsinghua University, Department of Computer Science and Technology, Beijing, China
- Wei Lin 0011 — Oregon State University, Corvallis, OR, USA
- Wei Lin 0012 — State University of New York at Stony Brook, Department of Biomedical Engineering, NY, USA
- Wei Lin 0013
- Wei Lin 0014
- Wei Lin 0015 — University of Darmstadt, Germany
- Wei Lin 0017
- Wei Lin 0018
- Wei Lin 0019
- Wei Lin 0020
- Wei Lin 0021
- Wei Lin 0022
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2020 – today
- 2024
- [j11]Jiandong Mu
Boosting the Convergence of Reinforcement Learning-Based Auto-Pruning Using Historical Data. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 43(2): 548-561 (2024) - [c55]Yi Cheng, Renjun Hu, Haochao Ying, Xing Shi, Jian Wu, Wei Lin:
Arithmetic Feature Interaction Is Necessary for Deep Tabular Learning. AAAI 2024: 11516-11524 - [c54]Zixiang Ding, Guoqing Jiang, Shuai Zhang, Lin Guo, Wei Lin:
How to Trade Off the Quantity and Capacity of Teacher Ensemble: Learning Categorical Distribution to Stochastically Employ a Teacher for Distillation. AAAI 2024: 17915-17923 - [c53]Shiwei Zhang
HAP: SPMD DNN Training on Heterogeneous GPU Clusters with Automated Program Synthesis. EuroSys 2024: 524-541 - [c52]Biao Sun, Ziming Huang, Hanyu Zhao, Wencong Xiao, Xinyi Zhang, Yong Li, Wei Lin:
Llumnix: Dynamic Scheduling for Large Language Model Serving. OSDI 2024: 173-191 - [c51]Donglin Zhuang, Zhen Zheng, Haojun Xia, Xiafei Qiu, Junjie Bai, Wei Lin, Shuaiwen Leon Song:
MonoNN: Enabling a New Monolithic Optimization Space for Neural Network Inference Tasks on Modern GPU-Centric Architectures. OSDI 2024: 989-1005 - [i50]Bin Lin, Tao Peng, Chen Zhang, Minmin Sun, Lanbo Li, Hanyu Zhao, Wencong Xiao, Qi Xu, Xiafei Qiu, Shen Li, Zhigang Ji, Yong Li, Wei Lin:
Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache. CoRR abs/2401.02669 (2024) - [i49]Shiwei Zhang, Lansong Diao, Chuan Wu, Zongyan Cao, Siyu Wang, Wei Lin:
HAP: SPMD DNN Training on Heterogeneous GPU Clusters with Automated Program Synthesis. CoRR abs/2401.05965 (2024) - [i48]Yi Cheng, Renjun Hu, Haochao Ying, Xing Shi, Jian Wu, Wei Lin:
Arithmetic Feature Interaction Is Necessary for Deep Tabular Learning. CoRR abs/2402.02334 (2024) - [i47]Xiang Li, Zhenyu Li, Chen Shi, Yong Xu, Qing Du, Mingkui Tan, Jun Huang, Wei Lin:
AlphaFin: Benchmarking Financial Analysis with Retrieval-Augmented Stock-Chain Framework. CoRR abs/2403.12582 (2024) - [i46]Jiatong Li, Renjun Hu, Kunzhe Huang, Yan Zhuang, Qi Liu, Mengxiao Zhu, Xing Shi, Wei Lin:
PertEval: Unveiling Real Knowledge Capacity of LLMs with Knowledge-Invariant Perturbations. CoRR abs/2405.19740 (2024) - [i45]Biao Sun, Ziming Huang, Hanyu Zhao, Wencong Xiao, Xinyi Zhang, Yong Li, Wei Lin:
Llumnix: Dynamic Scheduling for Large Language Model Serving. CoRR abs/2406.03243 (2024) - [i44]Xiufeng Shu, Ruidong Han, Xiang Li, Wei Lin:
Adaptive Utilization of Cross-scenario Information for Multi-scenario Recommendation. CoRR abs/2407.19727 (2024) - [i43]Xinyi Zhang, Hanyu Zhao, Wencong Xiao, Xianyan Jia, Fei Xu, Yong Li, Wei Lin, Fangming Liu:
Rubick: Exploiting Job Reconfigurability for Deep Learning Cluster Scheduling. CoRR abs/2408.08586 (2024) - 2023
- [j10]Hanyu Zhao
GoldMiner: Elastic Scaling of Training Data Pre-Processing Pipelines for Deep Learning. Proc. ACM Manag. Data 1(2): 193:1-193:25 (2023) - [j9]Zhen Zheng
BladeDISC: Optimizing Dynamic Shape Machine Learning Workloads via Compiler Approach. Proc. ACM Manag. Data 1(3): 206:1-206:29 (2023) - [j8]Haojun Xia, Zhen Zheng, Yuchao Li, Donglin Zhuang, Zhongzhu Zhou, Xiafei Qiu, Yong Li, Wei Lin, Shuaiwen Leon Song:
Flash-LLM: Enabling Low-Cost and Highly-Efficient Large Generative Model Inference With Unstructured Sparsity. Proc. VLDB Endow. 17(2): 211-224 (2023) - [j7]Shiwei Zhang
Expediting Distributed DNN Training With Device Topology-Aware Graph Deployment. IEEE Trans. Parallel Distributed Syst. 34(4): 1281-1293 (2023) - [c50]Zaifeng Pan
RECom: A Compiler Approach to Accelerating Recommendation Model Inference with Massive Embedding Columns. ASPLOS (4) 2023: 268-286 - [c49]Yangjie Zhou, Jingwen Leng, Yaoxu Song, Shuwen Lu, Mian Wang, Chao Li, Minyi Guo, Wenting Shen, Yong Li, Wei Lin, Xiangwen Liu, Hanqing Wu:
uGrapher: High-Performance Graph Operator Computation via Unified Abstraction for Graph Neural Networks. ASPLOS (2) 2023: 878-891 - [c48]Ziyue Hua, Wei Lin, Luyao Ren, Zongyang Li, Lu Zhang, Wenpin Jiao, Tao Xie:
GDsmith: Detecting Bugs in Cypher Graph Database Engines. ISSTA 2023: 163-174 - [c47]Mingzhen Li
EasyScale: Elastic Training with Consistent Accuracy and Improved Utilization on GPUs. SC 2023: 55:1-55:14 - [i42]Ziji Shi, Le Jiang, Ang Wang, Jie Zhang, Xianyan Jia, Yong Li, Chencan Wu, Jialin Li, Wei Lin:
TAP: Accelerating Large-Scale DNN Training Through Tensor Automatic Parallelisation. CoRR abs/2302.00247 (2023) - [i41]Shiwei Zhang, Xiaodong Yi, Lansong Diao, Chuan Wu, Siyu Wang, Wei Lin:
Expediting Distributed DNN Training with Device Topology-Aware Graph Deployment. CoRR abs/2302.06126 (2023) - [i40]Shiwei Zhang, Lansong Diao, Siyu Wang, Zongyan Cao, Yiliang Gu, Chang Si, Ziji Shi, Zhen Zheng, Chuan Wu, Wei Lin:
Auto-Parallelizing Large Models with Rhino: A Systematic Approach on Production AI Platform. CoRR abs/2302.08141 (2023) - [i39]Siyu Wang, Zongyan Cao, Chang Si, Lansong Diao, Jiamang Wang, Wei Lin:
Ada-Grouper: Accelerating Pipeline Parallelism in Preempted Network by Adaptive Group-Scheduling for Micro-Batches. CoRR abs/2303.01675 (2023) - [i38]Di Jin, Luzhi Wang, Yizhen Zheng, Guojie Song, Fei Jiang, Xiang Li, Wei Lin, Shirui Pan:
Dual Intent Enhanced Graph Neural Network for Session-based New Item Recommendation. CoRR abs/2305.05848 (2023) - [i37]Yuting Zhang, Yiqing Wu, Ran Le, Yongchun Zhu, Fuzhen Zhuang, Ruidong Han, Xiang Li, Wei Lin, Zhulin An, Yongjun Xu:
Modeling Dual Period-Varying Preferences for Takeaway Recommendation. CoRR abs/2306.04370 (2023) - [i36]Bin Yin, Junjie Xie, Yu Qin, Zixiang Ding, Zhichao Feng, Xiang Li, Wei Lin:
Heterogeneous Knowledge Fusion: A Novel Approach for Personalized Recommendation via LLM. CoRR abs/2308.03333 (2023) - [i35]Haojun Xia, Zhen Zheng, Yuchao Li, Donglin Zhuang, Zhongzhu Zhou, Xiafei Qiu, Yong Li, Wei Lin, Shuaiwen Leon Song:
Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity. CoRR abs/2309.10285 (2023) - 2022
- [j6]Yun Liang
An Efficient Hardware Design for Accelerating Sparse CNNs With NAS-Based Models. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 41(3): 597-613 (2022) - [j5]Xiaodong Yi
Optimizing DNN Compilation for Distributed Training With Joint OP and Tensor Fusion. IEEE Trans. Parallel Distributed Syst. 33(12): 4694-4706 (2022) - [c46]Zhen Zheng, Xuanda Yang, Pengzhan Zhao, Guoping Long, Kai Zhu, Feiwen Zhu, Wenyi Zhao, Xiaoyong Liu, Jun Yang, Jidong Zhai, Shuaiwen Leon Song, Wei Lin:
AStitch: enabling a new multi-dimensional optimization space for memory-intensive ML training and inference on modern SIMT architectures. ASPLOS 2022: 359-373 - [c45]Shiwei Zhang, Lansong Diao, Chuan Wu, Siyu Wang, Wei Lin:
Accelerating large-scale distributed neural network training with SPMD parallelism. SoCC 2022: 403-418 - [c44]Chengyu Wang, Minghui Qiu, Taolin Zhang, Tingting Liu, Lei Li, Jianing Wang, Ming Wang, Jun Huang, Wei Lin:
EasyNLP: A Comprehensive and Easy-to-use Toolkit for Natural Language Processing. EMNLP (Demos) 2022: 22-29 - [c43]Yuanxing Zhang, Langshi Chen, Siran Yang, Man Yuan
PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender Systems. ICDE 2022: 3453-3466 - [c42]Ziyue Luo, Xiaodong Yi, Guoping Long, Shiqing Fan, Chuan Wu, Jun Yang, Wei Lin:
Efficient Pipeline Planning for Expedited Distributed DNN Training. INFOCOM 2022: 340-349 - [c41]Wei Lin, Lu Zhang, Haotian Zhang, Kailai Shao, Mingming Zhang, Tao Xie:
TaintSQL: Dynamically Tracking Fine-Grained Implicit Flows for SQL Statements. ISSRE 2022: 1-12 - [c40]Jiabei Liu, Weiming Zhuang, Yonggang Wen, Jun Huang, Wei Lin:
Optimizing Federated Unsupervised Person Re-identification via Camera-aware Clustering. MMSP 2022: 1-6 - [c39]Qizhen Weng, Wencong Xiao, Yinghao Yu, Wei Wang, Cheng Wang, Jian He, Yong Li, Liping Zhang, Wei Lin, Yu Ding:
MLaaS in the Wild: Workload Analysis and Scheduling in Large-Scale Heterogeneous GPU Clusters. NSDI 2022: 945-960 - [c38]Xianyan Jia, Le Jiang, Ang Wang, Wencong Xiao, Ziji Shi, Jie Zhang, Xinyuan Li, Langshi Chen, Yong Li, Zhen Zheng, Xiaoyong Liu, Wei Lin:
Whale: Efficient Giant Model Training over Heterogeneous GPUs. USENIX ATC 2022: 673-688 - [i34]Yuanxing Zhang, Langshi Chen, Siran Yang, Man Yuan, Huimin Yi, Jie Zhang, Jiamang Wang, Jianbo Dong, Yunlong Xu, Yue Song, Yong Li, Di Zhang, Wei Lin, Lin Qu, Bo Zheng:
PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender Systems. CoRR abs/2204.04903 (2022) - [i33]Ziyue Luo, Xiaodong Yi, Guoping Long, Shiqing Fan, Chuan Wu, Jun Yang, Wei Lin:
Efficient Pipeline Planning for Expedited Distributed DNN Training. CoRR abs/2204.10562 (2022) - [i32]Chengyu Wang, Minghui Qiu, Taolin Zhang, Tingting Liu, Lei Li, Jianing Wang, Ming Wang, Jun Huang, Wei Lin:
EasyNLP: A Comprehensive and Easy-to-use Toolkit for Natural Language Processing. CoRR abs/2205.00258 (2022) - [i31]Wei Lin, Ziyue Hua, Luyao Ren, Zongyang Li, Lu Zhang, Tao Xie:
GDsmith: Detecting Bugs in Graph Database Engines. CoRR abs/2206.08530 (2022) - [i30]Mingzhen Li, Wencong Xiao, Biao Sun, Hanyu Zhao, Hailong Yang, Shiru Ren, Zhongzhi Luan, Xianyan Jia, Yi Liu, Yong Li, Depei Qian, Wei Lin:
EasyScale: Accuracy-consistent Elastic Training for Deep Learning. CoRR abs/2208.14228 (2022) - [i29]Xiaodong Yi, Shiwei Zhang, Lansong Diao, Chuan Wu, Zhen Zheng, Shiqing Fan, Siyu Wang, Jun Yang, Wei Lin:
Optimizing DNN Compilation for Distributed Training with Joint OP and Tensor Fusion. CoRR abs/2209.12769 (2022) - 2021
- [j4]Yingda Chen, Jiamang Wang, Yifeng Lu, Ying Han, Zhiqiang Lv, Xuebin Min, Hua Cai, Wei Zhang, Haochuan Fan, Chao Li, Tao Guan, Wei Lin, Yangqing Jia, Jingren Zhou:
Fangorn: Adaptive Execution Framework for Heterogeneous Workloads on Shared Clusters. Proc. VLDB Endow. 14(12): 2972-2985 (2021) - [j3]Yanghua Peng
DL2: A Deep Learning-Driven Scheduler for Deep Learning Clusters. IEEE Trans. Parallel Distributed Syst. 32(8): 1947-1960 (2021) - [c37]Bencheng Yan, Pengjie Wang, Jinquan Liu, Wei Lin, Kuang-Chih Lee, Jian Xu, Bo Zheng:
Binary Code based Hash Embedding for Web-scale Applications. CIKM 2021: 3563-3567 - [c36]Bencheng Yan, Pengjie Wang, Kai Zhang, Wei Lin, Kuang-Chih Lee, Jian Xu, Bo Zheng:
Learning Effective and Efficient Embedding via an Adaptively-Masked Twins-based Layer. CIKM 2021: 3568-3572 - [c35]Minghui Qiu, Peng Li, Chengyu Wang, Haojie Pan, Ang Wang, Cen Chen, Xianyan Jia, Yaliang Li, Jun Huang, Deng Cai, Wei Lin:
EasyTransfer: A Simple and Scalable Deep Transfer Learning Platform for NLP Applications. CIKM 2021: 4075-4084 - [c34]Kai Zhu, Wenyi Zhao, Zhen Zheng, Tianyou Guo
DISC: A Dynamic Shape Compiler for Machine Learning Workloads. EuroMLSys@EuroSys 2021: 89-95 - [c33]Chengyu Wang, Haojie Pan, Yuan Liu, Kehan Chen, Minghui Qiu, Wei Zhou, Jun Huang, Haiqing Chen, Wei Lin, Deng Cai:
MeLL: Large-scale Extensible User Intent Classification for Dialogue Systems with Meta Lifelong Learning. KDD 2021: 3649-3659 - [c32]Yuexiang Xie, Zhen Wang, Yaliang Li, Bolin Ding, Nezihe Merve Gürel, Ce Zhang, Minlie Huang, Wei Lin, Jingren Zhou:
FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data. KDD 2021: 3795-3805 - [c31]Shiqing Fan, Yi Rong, Chen Meng, Zongyan Cao, Siyu Wang, Zhen Zheng, Chuan Wu
DAPPLE: a pipelined data parallel approach for training large models. PPoPP 2021: 431-445 - [c30]Xu Ma, Pengjie Wang, Hui Zhao, Shaoguo Liu, Chuhan Zhao, Wei Lin, Kuang-Chih Lee, Jian Xu, Bo Zheng:
Towards a Better Tradeoff between Effectiveness and Efficiency in Pre-Ranking: A Learnable Feature Selection based Approach. SIGIR 2021: 2036-2040 - [c29]Feng Li, Bencheng Yan, Qingqing Long, Pengjie Wang, Wei Lin, Jian Xu, Bo Zheng:
Explicit Semantic Cross Feature Learning via Pre-trained Graph Neural Networks for CTR Prediction. SIGIR 2021: 2161-2165 - [i28]Junyang Lin, Rui Men, An Yang, Chang Zhou, Ming Ding, Yichang Zhang, Peng Wang, Ang Wang, Le Jiang, Xianyan Jia, Jie Zhang, Jianwei Zhang, Xu Zou, Zhikang Li, Xiaodong Deng, Jie Liu, Jinbao Xue, Huiling Zhou, Jianxin Ma, Jin Yu, Yong Li, Wei Lin, Jingren Zhou, Jie Tang, Hongxia Yang:
M6: A Chinese Multimodal Pretrainer. CoRR abs/2103.00823 (2021) - [i27]Kai Zhu, Wenyi Zhao, Zhen Zheng, Tianyou Guo, Pengzhan Zhao, Junjie Bai, Jun Yang, Xiaoyong Liu, Lansong Diao, Wei Lin:
DISC: A Dynamic Shape Compiler for Machine Learning Workloads. CoRR abs/2103.05288 (2021) - [i26]Xu Ma, Pengjie Wang, Hui Zhao, Shaoguo Liu, Chuhan Zhao, Wei Lin, Kuang-Chih Lee, Jian Xu, Bo Zheng:
Towards a Better Tradeoff between Effectiveness and Efficiency in Pre-Ranking: A Learnable Feature Selection based Approach. CoRR abs/2105.07706 (2021) - [i25]Feng Li, Bencheng Yan, Qingqing Long, Pengjie Wang, Wei Lin, Jian Xu, Bo Zheng:
Explicit Semantic Cross Feature Learning via Pre-trained Graph Neural Networks for CTR Prediction. CoRR abs/2105.07752 (2021) - [i24]An Yang, Junyang Lin, Rui Men, Chang Zhou, Le Jiang, Xianyan Jia, Ang Wang, Jie Zhang, Jiamang Wang, Yong Li, Di Zhang, Wei Lin, Lin Qu, Jingren Zhou, Hongxia Yang:
Exploring Sparse Expert Models and Beyond. CoRR abs/2105.15082 (2021) - [i23]Jiandong Mu, Mengdi Wang, Feiwen Zhu, Jun Yang, Wei Lin, Wei Zhang:
Boosting the Convergence of Reinforcement Learning-based Auto-pruning Using Historical Data. CoRR abs/2107.08815 (2021) - [i22]Bencheng Yan, Pengjie Wang, Kai Zhang, Wei Lin, Kuang-Chih Lee, Jian Xu, Bo Zheng:
Learning Effective and Efficient Embedding via an Adaptively-Masked Twins-based Layer. CoRR abs/2108.11513 (2021) - [i21]Bencheng Yan, Pengjie Wang, Jinquan Liu, Wei Lin, Kuang-Chih Lee, Jian Xu, Bo Zheng:
Binary Code based Hash Embedding for Web-scale Applications. CoRR abs/2109.02471 (2021) - [i20]Junyang Lin, An Yang, Jinze Bai, Chang Zhou, Le Jiang, Xianyan Jia, Ang Wang, Jie Zhang, Yong Li, Wei Lin, Jingren Zhou, Hongxia Yang:
M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining. CoRR abs/2110.03888 (2021) - 2020
- [c28]Xiaodong Yi
Optimizing distributed training deployment in heterogeneous GPU clusters. CoNEXT 2020: 93-107 - [c27]Shuai Wang, Dan Li, Jiansong Zhang, Wei Lin:
CEFS: compute-efficient flow scheduling for iterative synchronous applications. CoNEXT 2020: 136-148 - [c26]Qiangpeng Yang, Jun Huang, Wei Lin:
SwapText: Image Based Texts Transfer in Scenes. CVPR 2020: 14688-14697 - [c25]Jiandong Mu, Mengdi Wang, Lanbo Li, Jun Yang, Wei Lin, Wei Zhang:
A History-Based Auto-Tuning Framework for Fast and High-Performance DNN Design on GPU. DAC 2020: 1-6 - [c24]Daoyuan Chen, Yaliang Li, Minghui Qiu, Zhen Wang, Bofang Li, Bolin Ding, Hongbo Deng, Jun Huang, Wei Lin, Jingren Zhou:
AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search. IJCAI 2020: 2463-2469 - [c23]Xiaodong Yi
Fast Training of Deep Learning Models over Multiple GPUs. Middleware 2020: 105-118 - [c22]Mengli Cheng, Minghui Qiu, Xing Shi, Jun Huang, Wei Lin:
One-shot Text Field labeling using Attention and Belief Propagation for Structure Information Extraction. ACM Multimedia 2020: 340-348 - [c21]Wencong Xiao, Shiru Ren, Yong Li, Yang Zhang, Pengyang Hou, Zhi Li, Yihui Feng, Wei Lin, Yangqing Jia:
AntMan: Dynamic Scaling on GPU Clusters for Deep Learning. OSDI 2020: 533-548 - [i19]Daoyuan Chen, Yaliang Li, Minghui Qiu, Zhen Wang, Bofang Li, Bolin Ding, Hongbo Deng, Jun Huang, Wei Lin, Jingren Zhou:
AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search. CoRR abs/2001.04246 (2020) - [i18]Qiangpeng Yang, Hongsheng Jin, Jun Huang, Wei Lin:
SwapText: Image Based Texts Transfer in Scenes. CoRR abs/2003.08152 (2020) - [i17]Shiqing Fan, Yi Rong
DAPPLE: A Pipelined Data Parallel Approach for Training Large Models. CoRR abs/2007.01045 (2020) - [i16]Siyu Wang, Yi Rong
Auto-MAP: A DQN Framework for Exploring Distributed Execution Plans for DNN Workloads. CoRR abs/2007.04069 (2020) - [i15]Yuexiang Xie, Zhen Wang, Yaliang Li, Bolin Ding, Nezihe Merve Gürel, Ce Zhang, Minlie Huang, Wei Lin, Jingren Zhou:
Interactive Feature Generation via Learning Adjacency Tensor of Feature Graph. CoRR abs/2007.14573 (2020) - [i14]Mengli Cheng, Minghui Qiu, Xing Shi, Jun Huang, Wei Lin:
One-shot Text Field Labeling using Attention and Belief Propagation for Structure Information Extraction. CoRR abs/2009.04153 (2020) - [i13]Zhen Zheng, Pengzhan Zhao, Guoping Long, Feiwen Zhu, Kai Zhu, Wenyi Zhao, Lansong Diao, Jun Yang, Wei Lin:
FusionStitching: Boosting Memory Intensive Computations for Deep Learning Workloads. CoRR abs/2009.10924 (2020) - [i12]Yiwu Yao, Yuchao Li, Chengyu Wang, Tianhang Yu, Houjiang Chen, Xiaotang Jiang, Jun Yang, Jun Huang, Wei Lin, Hui Shu, Chengfei Lv:
INT8 Winograd Acceleration for Conv1D Equipped ASR Models Deployed on Mobile Devices. CoRR abs/2010.14841 (2020) - [i11]Ang Wang, Xianyan Jia, Le Jiang, Jie Zhang, Yong Li, Wei Lin:
Whale: A Unified Distributed Training Framework. CoRR abs/2011.09208 (2020) - [i10]Minghui Qiu, Peng Li, Hanjie Pan, Chengyu Wang, Ang Wang, Cen Chen, Yaliang Li, Dehong Gao, Jun Huang, Yong Li, Jun Yang, Deng Cai, Wei Lin:
EasyTransfer - A Simple and Scalable Deep Transfer Learning Platform for NLP Applications. CoRR abs/2011.09463 (2020) - [i9]Chen Xing, Wencong Xiao, Yong Li, Wei Lin:
Focusing More on Conflicts with Mis-Predictions Helps Language Pre-Training. CoRR abs/2012.08789 (2020)
2010 – 2019
- 2019
- [j2]Rong Zhu, Kun Zhao, Hongxia Yang, Wei Lin, Chang Zhou, Baole Ai, Yong Li, Jingren Zhou:
AliGraph: A Comprehensive Graph Neural Network Platform. Proc. VLDB Endow. 12(12): 2094-2105 (2019) - [c20]Lixue Xia, Lansong Diao, Zhao Jiang, Hao Liang, Kai Chen, Li Ding, Shunli Dou, Zibin Su, Meng Sun, Jiansong Zhang, Wei Lin:
PAI-FCNN: FPGA Based Inference System for Complex CNN Models. ASAP 2019: 107-114 - [c19]Liqiang Lu, Jiaming Xie, Ruirui Huang, Jiansong Zhang, Wei Lin, Yun Liang:
An Efficient Hardware Accelerator for Sparse Convolutional Neural Networks on FPGAs. FCCM 2019: 17-25 - [c18]Lansong Diao, Zhao Jiang, Hao Liang, Chang'an Ye, Kai Chen, Li Ding, Shunli Dou, Meng Sun, Lixue Xia, Jiansong Zhang, Wei Lin:
PAI-FCNN: FPGA Based CNN Inference System. FPGA 2019: 184 - [c17]Liqiang Lu, Yun Liang, Ruirui Huang, Wei Lin, Xiaoyuan Cui, Jiansong Zhang:
Speedy: An Accelerator for Sparse Convolutional Neural Networks on FPGAs. FPGA 2019: 187 - [c16]Jiansong Zhang, Lixue Xia, Zhao Jiang, Hao Liang, Jiaoyan Chen, Shouda Liu, Wei Lin, Yuan Xie:
Ouroboros: An Inference Engine for Deep Learning Based TTS on Embedded Devices. Hot Chips Symposium 2019: 1-28 - [c15]Qiangpeng Yang, Hongsheng Jin, Mengli Cheng, Wenmeng Zhou, Jun Huang, Wei Lin:
Scene Text Recognition with Auto-Aligned Feature Generator. ICDM 2019: 1426-1431 - [c14]Mengdi Wang, Chen Meng, Guoping Long, Chuan Wu
Characterizing Deep Learning Training Workloads on Alibaba-PAI. IISWC 2019: 189-202 - [i8]Rong Zhu, Kun Zhao, Hongxia Yang, Wei Lin, Chang Zhou, Baole Ai, Yong Li, Jingren Zhou:
AliGraph: A Comprehensive Graph Neural Network Platform. CoRR abs/1902.08730 (2019) - [i7]Yanghua Peng, Yixin Bao, Yangrui Chen, Chuan Wu, Chen Meng, Wei Lin:
DL2: A Deep Learning-driven Scheduler for Deep Learning Clusters. CoRR abs/1909.06040 (2019) - [i6]Mengdi Wang, Chen Meng, Guoping Long, Chuan Wu, Jun Yang, Wei Lin, Yangqing Jia:
Characterizing Deep Learning Training Workloads on Alibaba-PAI. CoRR abs/1910.05930 (2019) - [i5]Guoping Long, Jun Yang, Wei Lin:
FusionStitching: Boosting Execution Efficiency of Memory Intensive Computations for DL Workloads. CoRR abs/1911.11576 (2019) - 2018
- [c13]Minghui Qiu, Liu Yang, Feng Ji, Wei Zhou, Jun Huang, Haiqing Chen, W. Bruce Croft, Wei Lin:
Transfer Learning for Context-Aware Question Matching in Information-seeking Conversations in E-commerce. ACL (2) 2018: 208-213 - [c12]Qing Zhang, Mengru Zhang, Mengdi Wang
Efficient Deep Learning Inference Based on Model Compression. CVPR Workshops 2018: 1695-1702 - [c11]Qiangpeng Yang, Mengli Cheng, Wenmeng Zhou, Yan Chen, Minghui Qiu, Wei Lin:
IncepText: A New Inception-Text Module with Deformable PSROI Pooling for Multi-Oriented Scene Text Detection. IJCAI 2018: 1071-1077 - [i4]Qiangpeng Yang, Mengli Cheng, Wenmeng Zhou, Yan Chen, Minghui Qiu, Wei Lin, Wei Chu:
IncepText: A New Inception-Text Module with Deformable PSROI Pooling for Multi-Oriented Scene Text Detection. CoRR abs/1805.01167 (2018) - [i3]Minghui Qiu, Liu Yang, Feng Ji, Weipeng Zhao, Wei Zhou, Jun Huang, Haiqing Chen, W. Bruce Croft, Wei Lin:
Transfer Learning for Context-Aware Question Matching in Information-seeking Conversations in E-commerce. CoRR abs/1806.05434 (2018) - [i2]Guoping Long, Jun Yang, Kai Zhu, Wei Lin:
FusionStitching: Deep Fusion and Code Generation for Tensorflow Computations on GPUs. CoRR abs/1811.05213 (2018) - [i1]Mengdi Wang, Qing Zhang, Jun Yang, Xiaoyuan Cui, Wei Lin:
Graph-Adaptive Pruning for Efficient Inference of Convolutional Neural Networks. CoRR abs/1811.08589 (2018) - 2016
- [c10]Wei Lin, Haochuan Fan, Zhengping Qian, Junwei Xu, Sen Yang, Jingren Zhou, Lidong Zhou:
StreamScope: Continuous Reliable Distributed Processing of Big Data Streams. NSDI 2016: 439-453 - 2015
- [j1]Xuepeng Fan, Zhenyu Guo, Hai Jin, Xiaofei Liao, Jiaxing Zhang, Hucheng Zhou, Sean McDirmid, Wei Lin, Jingren Zhou, Lidong Zhou:
Spotting Code Optimizations in Data-Parallel Pipelines through PeriSCOPE. IEEE Trans. Parallel Distributed Syst. 26(6): 1718-1731 (2015) - 2014
- [c9]Tian Xiao, Jiaxing Zhang, Hucheng Zhou, Zhenyu Guo, Sean McDirmid, Wei Lin, Wenguang Chen, Lidong Zhou:
Nondeterminism in MapReduce considered harmful? an empirical study on non-commutative aggregators in MapReduce programs. ICSE Companion 2014: 44-53 - [c8]Tian Xiao, Zhenyu Guo, Hucheng Zhou, Jiaxing Zhang, Xu Zhao, Chencheng Ye, Xi Wang, Wei Lin, Wenguang Chen, Lidong Zhou:
Cybertron: pushing the limit on I/O reduction in data-parallel programs. OOPSLA 2014: 895-908 - [c7]Eric Boutin, Jaliya Ekanayake, Wei Lin, Bing Shi, Jingren Zhou, Zhengping Qian, Ming Wu, Lidong Zhou:
Apollo: Scalable and Coordinated Scheduling for Cloud-Scale Computing. OSDI 2014: 285-300 - 2013
- [c6]Sihan Li, Hucheng Zhou, Haoxiang Lin
A characteristic study on failures of production distributed data-parallel programs. ICSE 2013: 963-972 - 2012
- [c5]Jiaxing Zhang, Hucheng Zhou, Rishan Chen, Xuepeng Fan, Zhenyu Guo, Haoxiang Lin, Jack Li, Wei Lin, Jingren Zhou, Lidong Zhou:
Optimizing Data Shuffling in Data-Parallel Computation by Understanding User-Defined Functions. NSDI 2012: 295-308 - [c4]Zhenyu Guo, Xuepeng Fan, Rishan Chen, Jiaxing Zhang, Hucheng Zhou, Sean McDirmid, Chang Liu, Wei Lin, Jingren Zhou, Lidong Zhou:
Spotting Code Optimizations in Data-Parallel Pipelines through PeriSCOPE. OSDI 2012: 121-133 - [c3]Jingren Zhou, Nicolas Bruno, Wei Lin:
Advanced partitioning techniques for massively distributed computation. SIGMOD Conference 2012: 13-24 - 2010
- [c2]Bingsheng He
Comet: batched stream processing for data intensive distributed computing. SoCC 2010: 63-74
2000 – 2009
- 2009
- [c1]Bingsheng He, Mao Yang, Zhenyu Guo, Rishan Chen, Wei Lin, Bing Su, Hongyi Wang, Lidong Zhou:
Wave Computing in the Cloud. HotOS 2009
Coauthor Index
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