Shengen Yan

According to our database, Shengen Yan authored at least 42 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Proteus: Simulating the Performance of Distributed DNN Training.

Jiangfei Duan, Xiuhong Li, Ping Xu, Xingcheng Zhang, Shengen Yan, Yun Liang, Dahua Lin

IEEE Trans. Parallel Distributed Syst., October, 2024

CSKV: Training-Efficient Channel Shrinking for KV Cache in Long-Context Scenarios.

Luning Wang, Shiyao Li, Xuefei Ning, Zhihang Yuan, Shengen Yan, Guohao Dai, Yu Wang

CoRR, 2024

Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs.

Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Matthew B. Blaschko, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang

CoRR, 2024

MoA: Mixture of Sparse Attention for Automatic Large Language Model Compression.

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

CoRR, 2024

DiTFastAttn: Attention Compression for Diffusion Transformer Models.

Zhihang Yuan, Pu Lu, Hanling Zhang, Xuefei Ning, Linfeng Zhang, Tianchen Zhao, Shengen Yan, Guohao Dai, Yu Wang

CoRR, 2024

ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation.

Tianchen Zhao, Tongcheng Fang, Enshu Liu, Rui Wan, Widyadewi Soedarmadji, Shiyao Li, Zinan Lin, Guohao Dai, Shengen Yan, Huazhong Yang, Xuefei Ning, Yu Wang

CoRR, 2024

MixDQ: Memory-Efficient Few-Step Text-to-Image Diffusion Models with Metric-Decoupled Mixed Precision Quantization.

Tianchen Zhao, Xuefei Ning, Tongcheng Fang, Enshu Liu, Guyue Huang, Zinan Lin, Shengen Yan, Guohao Dai, Yu Wang

CoRR, 2024

HetHub: A Heterogeneous distributed hybrid training system for large-scale models.

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

CoRR, 2024

A Survey on Efficient Inference for Large Language Models.

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

CoRR, 2024

Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better.

Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Matthew B. Blaschko, Sergey Yekhanin, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang

CoRR, 2024

LV-Eval: A Balanced Long-Context Benchmark with 5 Length Levels Up to 256K.

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

CoRR, 2024

Evaluating Quantized Large Language Models.

Shiyao Li, Xuefei Ning, Luning Wang, Tengxuan Liu, Xiangsheng Shi, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Holistic Functionalization Approach to Optimizing Imperative Tensor Programs in Deep Learning.

Jinming Ma, Xiuhong Li, Zihan Wang, Xingcheng Zhang, Shengen Yan, Yuting Chen, Yueqian Zhang, Minxi Jin, Lijuan Jiang, Yun Liang, Chao Yang, Dahua Lin

Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

2023

Chimera: An Analytical Optimizing Framework for Effective Compute-intensive Operators Fusion.

Size Zheng, Siyuan Chen, Peidi Song, Renze Chen, Xiuhong Li, Shengen Yan, Dahua Lin, Jingwen Leng, Yun Liang

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2023

2022

NeoFlow: A Flexible Framework for Enabling Efficient Compilation for High Performance DNN Training.

Size Zheng, Renze Chen, Yicheng Jin, Anjiang Wei, Bingyang Wu, Xiuhong Li, Shengen Yan, Yun Liang

IEEE Trans. Parallel Distributed Syst., 2022

Astraea: A Fair Deep Learning Scheduler for Multi-Tenant GPU Clusters.

Zhisheng Ye, Peng Sun, Wei Gao, Tianwei Zhang, Xiaolin Wang, Shengen Yan, Yingwei Luo

IEEE Trans. Parallel Distributed Syst., 2022

DIESEL+: Accelerating Distributed Deep Learning Tasks on Image Datasets.

Lipeng Wang, Qiong Luo, Shengen Yan

IEEE Trans. Parallel Distributed Syst., 2022

GradientFlow: Optimizing Network Performance for Large-Scale Distributed DNN Training.

Peng Sun, Yonggang Wen, Ruobing Han, Wansen Feng, Shengen Yan

IEEE Trans. Big Data, 2022

A Simulation Platform for Multi-tenant Machine Learning Services on Thousands of GPUs.

Ruofan Liang, Bingsheng He, Shengen Yan, Peng Sun

CoRR, 2022

AMOS: enabling automatic mapping for tensor computations on spatial accelerators with hardware abstraction.

Size Zheng, Renze Chen, Anjiang Wei, Yicheng Jin, Qin Han, Liqiang Lu, Bingyang Wu, Xiuhong Li, Shengen Yan, Yun Liang

Proceedings of the ISCA '22: The 49th Annual International Symposium on Computer Architecture, New York, New York, USA, June 18, 2022

LongTail-Bench: A Benchmark Suite for Domain-Specific Operators in Deep Learning.

Xiuhong Li, Shengen Yan, Lijuan Jiang, Ping Xu, Jinming Ma, Xingcheng Zhang, Dahua Lin

Proceedings of the IEEE International Symposium on Workload Characterization, 2022

EasyView: Enabling and Scheduling Tensor Views in Deep Learning Compilers.

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

Proceedings of the 51st International Conference on Parallel Processing, 2022

2021

Characterization and prediction of deep learning workloads in large-scale GPU datacenters.

Qinghao Hu, Peng Sun, Shengen Yan, Yonggang Wen, Tianwei Zhang

Proceedings of the International Conference for High Performance Computing, 2021

2020

Evaluating Fast Algorithms for Convolutional Neural Networks on FPGAs.

Yun Liang, Liqiang Lu, Qingcheng Xiao, Shengen Yan

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020

Enabling Efficient Fast Convolution Algorithms on GPUs via MegaKernels.

Liancheng Jia, Yun Liang, Xiuhong Li, Liqiang Lu, Shengen Yan

IEEE Trans. Computers, 2020

DIESEL: A Dataset-Based Distributed Storage and Caching System for Large-Scale Deep Learning Training.

Lipeng Wang, Songgao Ye, Baichen Yang, Youyou Lu, Hequan Zhang, Shengen Yan, Qiong Luo

Proceedings of the ICPP 2020: 49th International Conference on Parallel Processing, 2020

Accelerating Deep Learning Tasks with Optimized GPU-assisted Image Decoding.

Lipeng Wang, Qiong Luo, Shengen Yan

Proceedings of the 26th IEEE International Conference on Parallel and Distributed Systems, 2020

Elan: Towards Generic and Efficient Elastic Training for Deep Learning.

Lei Xie, Jidong Zhai, Baodong Wu, Yuanbo Wang, Xingcheng Zhang, Peng Sun, Shengen Yan

Proceedings of the 40th IEEE International Conference on Distributed Computing Systems, 2020

2019

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).

Yiran Zhang, Long Chen, Xiangzhe An, Shengen Yan

计算机科学, 2019

Optimizing Network Performance for Distributed DNN Training on GPU Clusters: ImageNet/AlexNet Training in 1.5 Minutes.

Peng Sun, Wansen Feng, Ruobing Han, Shengen Yan, Yonggang Wen

CoRR, 2019

A coordinated tiling and batching framework for efficient GEMM on GPUs.

Xiuhong Li, Yun Liang, Shengen Yan, Liancheng Jia, Yinghan Li

Proceedings of the 24th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2019

2017

Towards Distributed Machine Learning in Shared Clusters: A Dynamically-Partitioned Approach.

Peng Sun, Yonggang Wen, Ta Nguyen Binh Duong, Shengen Yan

Proceedings of the 2017 IEEE International Conference on Smart Computing, 2017

Exploring Heterogeneous Algorithms for Accelerating Deep Convolutional Neural Networks on FPGAs.

Qingcheng Xiao, Yun Liang, Liqiang Lu, Shengen Yan, Yu-Wing Tai

Proceedings of the 54th Annual Design Automation Conference, 2017

2016

A Cross-Platform SpMV Framework on Many-Core Architectures.

Yunquan Zhang, Shigang Li, Shengen Yan, Huiyang Zhou

ACM Trans. Archit. Code Optim., 2016

Timed Dataflow: Reducing Communication Overhead for Distributed Machine Learning Systems.

Peng Sun, Yonggang Wen, Ta Nguyen Binh Duong, Shengen Yan

Proceedings of the 22nd IEEE International Conference on Parallel and Distributed Systems, 2016

2014

yaSpMV: yet another SpMV framework on GPUs.

Shengen Yan, Chao Li, Yunquan Zhang, Huiyang Zhou

Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2014

Understanding the tradeoffs between software-managed vs. hardware-managed caches in GPUs.

Chao Li, Yi Yang, Hongwen Dai, Shengen Yan, Frank Mueller, Huiyang Zhou

Proceedings of the 2014 IEEE International Symposium on Performance Analysis of Systems and Software, 2014

A fast integral image generation algorithm on GPUs.

Qingqing Dang, Shengen Yan, Ren Wu

Proceedings of the 20th IEEE International Conference on Parallel and Distributed Systems, 2014

2013

StreamScan: fast scan algorithms for GPUs without global barrier synchronization.

Shengen Yan, Guoping Long, Yunquan Zhang

Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2013

CLSIFT: An Optimization Study of the Scale Invariance Feature Transform on GPUs.

Weiyan Wang, Yunquan Zhang, Guoping Long, Shengen Yan, Haipeng Jia

Proceedings of the 10th IEEE International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing, 2013

2012

An Insightful Program Performance Tuning Chain for GPU Computing.

Haipeng Jia, Yunquan Zhang, Guoping Long, Shengen Yan

Proceedings of the Algorithms and Architectures for Parallel Processing, 2012

GPURoofline: A Model for Guiding Performance Optimizations on GPUs.

Haipeng Jia, Yunquan Zhang, Guoping Long, Jianliang Xu, Shengen Yan, Yan Li

Proceedings of the Euro-Par 2012 Parallel Processing - 18th International Conference, 2012