Zihao Ye

According to our database, Zihao Ye authored at least 13 papers between 2019 and 2024.

Collaborative distances:

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

2024

NanoFlow: Towards Optimal Large Language Model Serving Throughput.

Kan Zhu, Yilong Zhao, Liangyu Zhao, Gefei Zuo, Yile Gu, Dedong Xie, Yufei Gao, Qinyu Xu, Tian Tang, Zihao Ye, Keisuke Kamahori, Chien-Yu Lin, Stephanie Wang, Arvind Krishnamurthy, Baris Kasikci

CoRR, 2024

Atom: Low-Bit Quantization for Efficient and Accurate LLM Serving.

Yilong Zhao, Chien-Yu Lin, Kan Zhu, Zihao Ye, Lequn Chen, Size Zheng, Luis Ceze, Arvind Krishnamurthy, Tianqi Chen, Baris Kasikci

Proceedings of the Seventh Annual Conference on Machine Learning and Systems, 2024

Punica: Multi-Tenant LoRA Serving.

Lequn Chen, Zihao Ye, Yongji Wu, Danyang Zhuo, Luis Ceze, Arvind Krishnamurthy

Proceedings of the Seventh Annual Conference on Machine Learning and Systems, 2024

vMCU: Coordinated Memory Management and Kernel Optimization for DNN Inference on MCUs.

Size Zheng, Renze Chen, Meng Li, Zihao Ye, Luis Ceze, Yun Liang

Proceedings of the Seventh Annual Conference on Machine Learning and Systems, 2024

2023

Relax: Composable Abstractions for End-to-End Dynamic Machine Learning.

Ruihang Lai, Junru Shao, Siyuan Feng, Steven S. Lyubomirsky, Bohan Hou, Wuwei Lin, Zihao Ye, Hongyi Jin, Yuchen Jin, Jiawei Liu, Lesheng Jin, Yaxing Cai, Ziheng Jiang, Yong Wu, Sunghyun Park, Prakalp Srivastava, Jared G. Roesch, Todd C. Mowry, Tianqi Chen

CoRR, 2023

SparseTIR: Composable Abstractions for Sparse Compilation in Deep Learning.

Zihao Ye, Ruihang Lai, Junru Shao, Tianqi Chen, Luis Ceze

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023

TensorIR: An Abstraction for Automatic Tensorized Program Optimization.

Siyuan Feng, Bohan Hou, Hongyi Jin, Wuwei Lin, Junru Shao, Ruihang Lai, Zihao Ye, Lianmin Zheng, Cody Hao Yu, Yong Yu, Tianqi Chen

Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023

2022

Graphiler: Optimizing Graph Neural Networks with Message Passing Data Flow Graph.

Zhiqiang Xie, Minjie Wang, Zihao Ye, Zheng Zhang, Rui Fan

Proceedings of the Fifth Conference on Machine Learning and Systems, 2022

2020

Transformer on a Diet.

Chenguang Wang, Zihao Ye, Aston Zhang, Zheng Zhang, Alexander J. Smola

CoRR, 2020

DGL-KE: Training Knowledge Graph Embeddings at Scale.

Da Zheng, Xiang Song, Chao Ma, Zeyuan Tan, Zihao Ye, Jin Dong, Hao Xiong, Zheng Zhang, George Karypis

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

FeatGraph: a flexible and efficient backend for graph neural network systems.

Yuwei Hu, Zihao Ye, Minjie Wang, Jiali Yu, Da Zheng, Mu Li, Zheng Zhang, Zhiru Zhang, Yida Wang

Proceedings of the International Conference for High Performance Computing, 2020

2019

BP-Transformer: Modelling Long-Range Context via Binary Partitioning.

Zihao Ye, Qipeng Guo, Quan Gan, Xipeng Qiu, Zheng Zhang

CoRR, 2019

Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs.

Minjie Wang, Lingfan Yu, Da Zheng, Quan Gan, Yu Gai, Zihao Ye, Mufei Li, Jinjing Zhou, Qi Huang, Chao Ma, Ziyue Huang, Qipeng Guo, Hao Zhang, Haibin Lin, Junbo Zhao, Jinyang Li, Alexander J. Smola, Zheng Zhang

CoRR, 2019