Xinwei (Mason) Fu
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Xinwei (Mason) Fu, Ph.D. |
Bio
I am a Senior Applied Scientist at AWS. Our team focuses on optimizing systems and compilers to advance large-scale model training and inference on AWS homegrown accelerators.
Prior to joining Amazon, I earned my Ph.D. in Computer Science from Virginia Tech, where I had the privilege of being advised by Dr. Changwoo Min and Dr. Dongyoon Lee.
Research Interests
Machine Learning System
Software Reliability
Publications
EKKA: Automated diagnosis of silent errors in LLM inference
Yile Gu, Zhen Zhang, Shaowei Zhu, Xinwei Fu, Jun Wu, Yida Wang, and Baris Kasikci
In Proceedings of the 43rd International Conference on Machine Learning (ICML 2026)
CactusDB: Unlock Co-Optimization Opportunities for SQL Queries and AI/ML Model Inferences
Lixi Zhou, Kanchan Chowdhury, Lulu Xie, Jaykumar Tandel, Zhiwei Fan, Xinwei Fu, and Jia Zou
In Proceedings of the 42nd IEEE International Conference on Data Engineering (ICDE 2026)
InferF: Declarative Factorization of AI/ML Inferences over Joins
Kanchan Chowdhury, Lixi Zhou, Lulu Xie, Xinwei Fu, and Jia Zou
In Proceedings of the 2026 ACM on Management of Data (SIGMOD 2026)
PipeFill: Using GPUs During Bubbles in Pipeline-parallel LLM Training
Daiyaan Arfeen, Zhen Zhang, Xinwei Fu, Gregory R. Ganger, and Yida Wang
In Proceedings of the 8th Annual Conference on Machine Learning and Systems (MLSys 2025)
ScaleFusion: Scalable Inference of Spatial-Temporal Diffusion Transformers for High-Resolution Long Video Generation
Jiacheng Yang, Jun Wu, Zhen Zhang, Xinwei Fu, Zhiying Xu, Zhen Jia, Yida Wang, and Gennady Pekhimenko
In Proceedings of the 8th Annual Conference on Machine Learning and Systems (MLSys 2025)
Distributed Training of Large Language Models on AWS Trainium
Xinwei Fu, Zhen Zhang, Haozheng Fan, Guangtai Huang, Mohammad El-Shabani, Randy Huang, Rahul Solanki, Fei Wu, Ron Diamant, and Yida Wang
In Proceedings of the 15th ACM Symposium on Cloud Computing (SoCC 2024)
HLAT: High-quality Large Language Model Pre-trained on AWS Trainium
Haozheng Fan, Hao Zhou, Guangtai Huang, Parameswaran Raman, Xinwei Fu, Gaurav Gupta, Dhananjay Ram, Yida Wang, and Jun Huan
In Proceedings of the 2024 IEEE International Conference on Big Data (IEEE BigData 2024)
Gemini: Fast Failure Recovery in Distributed Training with In-Memory Checkpoints
Zhuang Wang, Zhen Jia, Shuai Zheng, Zhen Zhang, Xinwei Fu, T. S. Eugene Ng, and Yida Wang
In Proceedings of the 29th ACM Symposium on Operating Systems Principles (SOSP 2023)
Durinn: Adversarial Memory and Thread Interleaving for Detecting Durable Linearizability Bugs
Xinwei Fu, Dongyoon Lee, and Changwoo Min
In Proceedings of the 16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 2022)
[paper | slides | code]
ReplayCache: Enabling Volatile Caches for Energy Harvesting Systems
Jianping Zeng, Jongouk Choi, Xinwei Fu, Ajay P. Shreepathi, Dongyoon Lee, Changwoo Min, and Changhee Jung
In Proceedings of the 13rd annual non-volatile memories workshop (NVMW 2022)
[paper | slides]
Witcher: Systematic Crash Consistency Testing for Non-Volatile Memory Key-Value Stores
Xinwei Fu, Wook-Hee Kim, Ajay Paddayuru Shreepathi, Mohannad Ismail, Sunny Wadkar, Dongyoon Lee, and Changwoo Min
In Proceedings of the 28th ACM Symposium on Operating Systems Principles (SOSP 2021)
[paper | slides | code | video]
PACTree: A High Performance Persistent Range Index Using PAC Guidelines
Wook-Hee Kim, R. Madhava Krishnan, Xinwei Fu, Sanidhya Kashyap, and Changwoo Min
In Proceedings of the 28th ACM Symposium on Operating Systems Principles (SOSP 2021)
[paper | slides | code | video]
ReplayCache: Enabling Volatile Caches for Energy Harvesting Systems
Jianping Zeng, Jongouk Choi, Xinwei Fu, Ajay Paddayuru Shreepathi, Dongyoon Lee, Changwoo Min, and Changhee Jung
In Proceedings of the 54th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO 2021)
[paper | slides]
TIPS: Making Volatile Index Structures Persistent with DRAM-NVMM Tiering
R. Madhava Krishnan, Wook-Hee Kim, Xinwei Fu, Sumit Kumar Monga, Hee Won Lee, Minsung Jang, Ajit Mathew, and Changwoo Min
In Proceedings of USENIX Annual Technical Conference (ATC 2021)
[paper | slides | code | video]
Durable Transactional Memory Can Scale with TimeStone
R.Madhava Krishnan, Jaeho Kim, Ajit Mathew, Xinwei Fu, Anthony Demeri, Changwoo Min and Sudarsun Kannan
In Proceedings of the 11th Annual Non-Volatile Memories Workshop (NVMW 2020)
[paper | code]
Durable Transactional Memory Can Scale with TimeStone
R.Madhava Krishnan, Jaeho Kim, Ajit Mathew, Xinwei Fu, Anthony Demeri, Changwoo Min and Sudarsun Kannan
In Proceedings of ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2020)
[paper | slides | code | video]
EdgeWise: A Better Stream Processing Engine for the Edge
Xinwei Fu, Talha Ghaffar, James C. Davis and Dongyoon Lee
In Proceedings of USENIX Annual Technical Conference (ATC 2019)
[paper | slides | code | video]
nAdroid: Statically Detecting Ordering Violations in Android Applications
Xinwei Fu, Dongyoon Lee, and Changhee Jung
In Proceedings of IEEE/ACM International Symposium on Code Generation and Optimization (CGO 2018)
[paper | code]
Services
Conference Committee Activities
Program Committee, USENIX Symposium on Operating Systems Design and Implementation (OSDI). 2026
Program Committee, Annual Conference on Machine Learning and Systems (MLSys). 2025, 2026
Program Committee, USENIX Annual Technical Conference (ATC). 2023, 2024, 2025
Program Committee, IEEE International Parallel & Distributed Processing Symposium (IPDPS). 2025
Program Committee, ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES). 2023
Artifact Evaluation Program Committee, IEEE/ACM International Symposium on Code Generation and Optimization (CGO). 2019
Conference Organizing Activities
Artifact Evaluation Co-Chair, ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES). 2023