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2020 – today
- 2024
[j9]Jiangfei Duan, Xiuhong Li, Ping Xu, Xingcheng Zhang, Shengen Yan, Yun Liang, Dahua Lin:
Proteus: Simulating the Performance of Distributed DNN Training. IEEE Trans. Parallel Distributed Syst. 35(10): 1867-1878 (2024)- [c21]Shiyao Li, Xuefei Ning, Luning Wang, Tengxuan Liu, Xiangsheng Shi, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang:
Evaluating Quantized Large Language Models. ICML 2024 - [i15]Tao Yuan, Xuefei Ning, Dong Zhou, Zhijie Yang, Shiyao Li, Minghui Zhuang, Zheyue Tan, Zhuyu Yao, Dahua Lin, Boxun Li, Guohao Dai, Shengen Yan, Yu Wang:
LV-Eval: A Balanced Long-Context Benchmark with 5 Length Levels Up to 256K. CoRR abs/2402.05136 (2024) - [i14]Shiyao Li, Xuefei Ning, Luning Wang, Tengxuan Liu, Xiangsheng Shi, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang:
Evaluating Quantized Large Language Models. CoRR abs/2402.18158 (2024) - [i13]Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Matthew B. Blaschko, Sergey Yekhanin, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang:
Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better. CoRR abs/2404.02241 (2024) - [i12]Zixuan Zhou, Xuefei Ning, Ke Hong, Tianyu Fu, Jiaming Xu, Shiyao Li, Yuming Lou, Luning Wang, Zhihang Yuan, Xiuhong Li, Shengen Yan, Guohao Dai, Xiao-Ping Zhang, Yuhan Dong, Yu Wang:
A Survey on Efficient Inference for Large Language Models. CoRR abs/2404.14294 (2024) - [i11]Si Xu, Zixiao Huang, Yan Zeng, Shengen Yan, Xuefei Ning, Haolin Ye, Sipei Gu, Chunsheng Shui, Zhezheng Lin, Hao Zhang, Sheng Wang, Guohao Dai, Yu Wang:
HetHub: A Heterogeneous distributed hybrid training system for large-scale models. CoRR abs/2405.16256 (2024) - [i10]Tianchen Zhao, Xuefei Ning, Tongcheng Fang, Enshu Liu, Guyue Huang, Zinan Lin, Shengen Yan, Guohao Dai, Yu Wang:
MixDQ: Memory-Efficient Few-Step Text-to-Image Diffusion Models with Metric-Decoupled Mixed Precision Quantization. CoRR abs/2405.17873 (2024) - [i9]Tianchen Zhao, Tongcheng Fang, Enshu Liu, Rui Wan, Widyadewi Soedarmadji, Shiyao Li, Zinan Lin, Guohao Dai, Shengen Yan, Huazhong Yang, Xuefei Ning, Yu Wang:
ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation. CoRR abs/2406.02540 (2024) - [i8]Zhihang Yuan, Pu Lu, Hanling Zhang, Xuefei Ning, Linfeng Zhang, Tianchen Zhao, Shengen Yan, Guohao Dai, Yu Wang:
DiTFastAttn: Attention Compression for Diffusion Transformer Models. CoRR abs/2406.08552 (2024) - [i7]Tianyu Fu, Haofeng Huang, Xuefei Ning, Genghan Zhang, Boju Chen, Tianqi Wu, Hongyi Wang, Zixiao Huang, Shiyao Li, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang:
MoA: Mixture of Sparse Attention for Automatic Large Language Model Compression. CoRR abs/2406.14909 (2024) - [i6]Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Matthew B. Blaschko, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang:
Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs. CoRR abs/2407.00945 (2024) - 2023
- [c20]Size Zheng, Siyuan Chen, Peidi Song, Renze Chen, Xiuhong Li, Shengen Yan, Dahua Lin, Jingwen Leng, Yun Liang:
Chimera: An Analytical Optimizing Framework for Effective Compute-intensive Operators Fusion. HPCA 2023: 1113-1126 - [i5]Jiangfei Duan, Xiuhong Li, Ping Xu, Xingcheng Zhang, Shengen Yan, Yun Liang, Dahua Lin:
Proteus: Simulating the Performance of Distributed DNN Training. CoRR abs/2306.02267 (2023) - 2022
- [j8]Peng Sun
, Yonggang Wen, Ruobing Han, Wansen Feng, Shengen Yan:
GradientFlow: Optimizing Network Performance for Large-Scale Distributed DNN Training. IEEE Trans. Big Data 8(2): 495-507 (2022) - [j7]Lipeng Wang, Qiong Luo, Shengen Yan:
DIESEL+: Accelerating Distributed Deep Learning Tasks on Image Datasets. IEEE Trans. Parallel Distributed Syst. 33(5): 1173-1184 (2022) - [j6]Zhisheng Ye, Peng Sun, Wei Gao, Tianwei Zhang, Xiaolin Wang, Shengen Yan, Yingwei Luo:
Astraea: A Fair Deep Learning Scheduler for Multi-Tenant GPU Clusters. IEEE Trans. Parallel Distributed Syst. 33(11): 2781-2793 (2022) - [j5]Size Zheng, Renze Chen, Yicheng Jin, Anjiang Wei, Bingyang Wu, Xiuhong Li, Shengen Yan, Yun Liang:
NeoFlow: A Flexible Framework for Enabling Efficient Compilation for High Performance DNN Training. IEEE Trans. Parallel Distributed Syst. 33(11): 3220-3232 (2022) - [c19]Lijuan Jiang, Ping Xu, Qianchao Zhu, Xiuhong Li, Shengen Yan, Xingcheng Zhang, Dahua Lin, Wenjing Ma, Zhouyang Li, Jun Liu, Jinming Ma, Minxi Jin, Chao Yang:
EasyView: Enabling and Scheduling Tensor Views in Deep Learning Compilers. ICPP 2022: 54:1-54:11 - [c18]Xiuhong Li, Shengen Yan, Lijuan Jiang, Ping Xu, Jinming Ma, Xingcheng Zhang, Dahua Lin:
LongTail-Bench: A Benchmark Suite for Domain-Specific Operators in Deep Learning. IISWC 2022: 282-295 - [c17]Size Zheng, Renze Chen, Anjiang Wei, Yicheng Jin, Qin Han, Liqiang Lu, Bingyang Wu, Xiuhong Li, Shengen Yan, Yun Liang:
AMOS: enabling automatic mapping for tensor computations on spatial accelerators with hardware abstraction. ISCA 2022: 874-887 - [i4]Ruofan Liang, Bingsheng He, Shengen Yan, Peng Sun:
A Simulation Platform for Multi-tenant Machine Learning Services on Thousands of GPUs. CoRR abs/2201.03175 (2022) - 2021
- [c16]Qinghao Hu, Peng Sun, Shengen Yan, Yonggang Wen, Tianwei Zhang:
Characterization and prediction of deep learning workloads in large-scale GPU datacenters. SC 2021: 104 - [i3]Qinghao Hu, Peng Sun, Shengen Yan, Yonggang Wen, Tianwei Zhang:
Characterization and Prediction of Deep Learning Workloads in Large-Scale GPU Datacenters. CoRR abs/2109.01313 (2021) - 2020
- [j4]Liancheng Jia, Yun Liang, Xiuhong Li, Liqiang Lu, Shengen Yan:
Enabling Efficient Fast Convolution Algorithms on GPUs via MegaKernels. IEEE Trans. Computers 69(7): 986-997 (2020) - [j3]Yun Liang, Liqiang Lu, Qingcheng Xiao, Shengen Yan:
Evaluating Fast Algorithms for Convolutional Neural Networks on FPGAs. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(4): 857-870 (2020) - [c15]Lei Xie, Jidong Zhai, Baodong Wu, Yuanbo Wang, Xingcheng Zhang, Peng Sun, Shengen Yan:
Elan: Towards Generic and Efficient Elastic Training for Deep Learning. ICDCS 2020: 78-88 - [c14]Lipeng Wang, Qiong Luo, Shengen Yan:
Accelerating Deep Learning Tasks with Optimized GPU-assisted Image Decoding. ICPADS 2020: 274-281 - [c13]Lipeng Wang, Songgao Ye, Baichen Yang, Youyou Lu, Hequan Zhang, Shengen Yan, Qiong Luo:
DIESEL: A Dataset-Based Distributed Storage and Caching System for Large-Scale Deep Learning Training. ICPP 2020: 20:1-20:11
2010 – 2019
- 2019
- [j2]Yiran Zhang, Long Chen, Xiangzhe An, Shengen Yan:
面向GPU计算平台的归约算法的性能优化研究 (Study on Performance Optimization of Reduction Algorithm Targeting GPU Computing Platform). 计算机科学 46(2): 306-314 (2019) - [c12]Xiuhong Li, Yun Liang, Shengen Yan, Liancheng Jia, Yinghan Li:
A coordinated tiling and batching framework for efficient GEMM on GPUs. PPoPP 2019: 229-241 - [i2]Peng Sun, Wansen Feng, Ruobing Han, Shengen Yan, Yonggang Wen:
Optimizing Network Performance for Distributed DNN Training on GPU Clusters: ImageNet/AlexNet Training in 1.5 Minutes. CoRR abs/1902.06855 (2019) - 2017
- [c11]Qingcheng Xiao, Yun Liang, Liqiang Lu, Shengen Yan, Yu-Wing Tai:
Exploring Heterogeneous Algorithms for Accelerating Deep Convolutional Neural Networks on FPGAs. DAC 2017: 62:1-62:6 - [c10]Liqiang Lu, Yun Liang, Qingcheng Xiao, Shengen Yan:
Evaluating Fast Algorithms for Convolutional Neural Networks on FPGAs. FCCM 2017: 101-108 - [c9]Peng Sun, Yonggang Wen, Ta Nguyen Binh Duong, Shengen Yan:
Towards Distributed Machine Learning in Shared Clusters: A Dynamically-Partitioned Approach. SMARTCOMP 2017: 1-6 - [i1]Peng Sun, Yonggang Wen, Ta Nguyen Binh Duong, Shengen Yan:
Towards Distributed Machine Learning in Shared Clusters: A Dynamically-Partitioned Approach. CoRR abs/1704.06738 (2017) - 2016
- [j1]Yunquan Zhang, Shigang Li, Shengen Yan, Huiyang Zhou:
A Cross-Platform SpMV Framework on Many-Core Architectures. ACM Trans. Archit. Code Optim. 13(4): 33:1-33:25 (2016) - [c8]Peng Sun, Yonggang Wen, Ta Nguyen Binh Duong, Shengen Yan:
Timed Dataflow: Reducing Communication Overhead for Distributed Machine Learning Systems. ICPADS 2016: 1110-1117 - 2014
- [c7]Qingqing Dang, Shengen Yan, Ren Wu:
A fast integral image generation algorithm on GPUs. ICPADS 2014: 624-631 - [c6]Chao Li, Yi Yang, Hongwen Dai, Shengen Yan, Frank Mueller, Huiyang Zhou:
Understanding the tradeoffs between software-managed vs. hardware-managed caches in GPUs. ISPASS 2014: 231-242 - [c5]Shengen Yan, Chao Li, Yunquan Zhang, Huiyang Zhou:
yaSpMV: yet another SpMV framework on GPUs. PPoPP 2014: 107-118 - 2013
- [c4]Weiyan Wang, Yunquan Zhang, Guoping Long, Shengen Yan, Haipeng Jia:
CLSIFT: An Optimization Study of the Scale Invariance Feature Transform on GPUs. HPCC/EUC 2013: 93-100 - [c3]Shengen Yan, Guoping Long, Yunquan Zhang:
StreamScan: fast scan algorithms for GPUs without global barrier synchronization. PPoPP 2013: 229-238 - 2012
- [c2]Haipeng Jia, Yunquan Zhang, Guoping Long, Jianliang Xu, Shengen Yan, Yan Li:
GPURoofline: A Model for Guiding Performance Optimizations on GPUs. Euro-Par 2012: 920-932 - [c1]Haipeng Jia, Yunquan Zhang, Guoping Long, Shengen Yan:
An Insightful Program Performance Tuning Chain for GPU Computing. ICA3PP (1) 2012: 502-516
Coauthor Index
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last updated on 2024-09-11 00:34 CEST by the dblp team
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