Zihao Ye

According to our database, Zihao Ye authored at least 25 papers between 2019 and 2026.

Collaborative distances:

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

2026

Event Tensor: A Unified Abstraction for Compiling Dynamic Megakernel.

Hongyi Jin, Bohan Hou, Guanjie Wang, Ruihang Lai, Jinqi Chen, Zihao Ye, Yaxing Cai, Yixin Dong, Xinhao Cheng, Zhihao Zhang, Yilong Zhao, Yingyi Huang, Lijie Yang, Jinchen Jiang, Gabriele Oliaro, Jianan Ji, Xupeng Miao, Vinod Grover, Todd C. Mowry, Zhihao Jia, Tianqi Chen

CoRR, April, 2026

AVO: Agentic Variation Operators for Autonomous Evolutionary Search.

Terry Chen, Zhifan Ye, Bing Xu, Zihao Ye, Timmy Liu, Ali Hassani, Tianqi Chen, Andrew Kerr, Haicheng Wu, Yang Xu, Yu-Jung Chen, Hanfeng Chen, Aditya Kane, Ronny Krashinsky, Ming-Yu Liu, Vinod Grover, Luis Ceze, Roger A. Bringmann, John Tran, Wei Liu, Fung Xie, Michael Lightstone, Humphrey Shi

CoRR, March, 2026

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits.

Edward Lin, Sahil Modi, Siva Kumar Sastry Hari, Qijing Huang, Zhifan Ye, Nestor Qin, Fengzhe Zhou, Yuan Zhang, Jingquan Wang, Sana Damani, Dheeraj Peri, Ouye Xie, Aditya Kane, Moshe Maor, Michael Behar, Triston Cao, Rishabh Mehta, Vartika Singh, Vikram Sharma Mailthody, Terry Chen, Zihao Ye, Hanfeng Chen, Tianqi Chen, Vinod Grover, Wei Chen, Wei Liu, Eric Chung, Luis Ceze, Roger A. Bringmann, Cyril Zeller, Michael Lightstone, Christos Kozyrakis, Humphrey Shi

CoRR, March, 2026

Axe: A Simple Unified Layout Abstraction for Machine Learning Compilers.

Bohan Hou, Hongyi Jin, Guanjie Wang, Jinqi Chen, Yaxing Cai, Lijie Yang, Zihao Ye, Yaoyao Ding, Ruihang Lai, Tianqi Chen

CoRR, January, 2026

FlashInfer-Bench: Building the Virtuous Cycle for AI-driven LLM Systems.

Shanli Xing, Yiyan Zhai, Alexander Jiang, Yixin Dong, Yong Wu, Zihao Ye, Charlie Ruan, Yingyi Huang, Yineng Zhang, Liangsheng Yin, Aksara Bayyapu, Luis Ceze, Tianqi Chen

CoRR, January, 2026

2025

Mirage Persistent Kernel: A Compiler and Runtime for Mega-Kernelizing Tensor Programs.

Xinhao Cheng, Zhihao Zhang, Yu Zhou, Jianan Ji, Jinchen Jiang, Zepeng Zhao, Ziruo Xiao, Zihao Ye, Yingyi Huang, Ruihang Lai, Hongyi Jin, Bohan Hou, Mengdi Wu, Yixin Dong, Anthony Yip, Zihao Ye, Songting Wang, Wenqin Yang, Xupeng Miao, Tianqi Chen, Zhihao Jia

CoRR, December, 2025

Mirage Persistent Kernel: A Compiler and Runtime for Mega-Kernelizing Tensor Programs.

Xinhao Cheng, Zhihao Zhang, Yu Zhou, Jianan Ji, Jinchen Jiang, Zepeng Zhao, Ziruo Xiao, Zihao Ye, Yingyi Huang, Ruihang Lai, Hongyi Jin, Bohan Hou, Mengdi Wu, Yixin Dong, Anthony Yip, Zihao Ye, Songting Wang, Wenqin Yang, Xupeng Miao, Tianqi Chen, Zhihao Jia

CoRR, December, 2025

Accelerating Large-Scale Reasoning Model Inference with Sparse Self-Speculative Decoding.

Yilong Zhao, Jiaming Tang, Kan Zhu, Zihao Ye, Chi-Chih Chang, Chaofan Lin, Jongseok Park, Guangxuan Xiao, Mohamed S. Abdelfattah, Mingyu Gao, Baris Kasikci, Song Han, Ion Stoica

CoRR, December, 2025

TeleRAG: Efficient Retrieval-Augmented Generation Inference with Lookahead Retrieval.

Chien-Yu Lin, Keisuke Kamahori, Yiyu Liu, Xiaoxiang Shi, Madhav Mahesh Kashyap, Yile Gu, Rulin Shao, Zihao Ye, Kan Zhu, Stephanie Wang, Arvind Krishnamurthy, Rohan Kadekodi, Luis Ceze, Baris Kasikci

CoRR, February, 2025

NanoFlow: Towards Optimal Large Language Model Serving Throughput.

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

Proceedings of the 19th USENIX Symposium on Operating Systems Design and Implementation, 2025

FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving.

Zihao Ye, Lequn Chen, Ruihang Lai, Wuwei Lin, Yineng Zhang, Stephanie Wang, Tianqi Chen, Baris Kasikci, Vinod Grover, Arvind Krishnamurthy, Luis Ceze

Proceedings of the Eighth Conference on Machine Learning and Systems, 2025

MagicPIG: LSH Sampling for Efficient LLM Generation.

Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, Yang Zhou, Jianyu Zhang, Niklas Nolte, Yuandong Tian, Matthijs Douze, Léon Bottou, Zhihao Jia, Beidi Chen

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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

Ruihang Lai, Junru Shao, Siyuan Feng, Steven 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 Roesch, Todd C. Mowry, Tianqi Chen

Proceedings of the 30th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2025

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

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