Research
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2026
Ekka: Automated Diagnosis of Silent Errors in LLM Inference
Blog post — June 29, 2026 — Yile Gu, Zhen Zhang, Shaowei Zhu, Xinwei Fu, Jun Wu, Yida Wang, Baris Kasikci
TraceLab: Characterizing Coding Agent Workloads for LLM Serving
BlogNew ResearchInference & ServingAgents
Blog post — June 25, 2026 — Kan Zhu, Mathew Jacob, Chenxi Ma, Yi Pan, Stephanie Wang, Arvind Krishnamurthy, Baris Kasikci
M*: A Modular, Extensible, Serving System for Multimodal Models
BlogNew ResearchInference & ServingMultimodalProgrammable Systems
Blog post — June 19, 2026 — Atindra Jha, Naomi Sagan, Keisuke Kamahori, Xikai (Noah) Meng, Rohan Sanda, Luke Zettlemoyer, Olivia Hsu, Jure Leskovec, Baris Kasikci, Stephanie Wang
Introducing Piper: A Programmable Distributed Training System
BlogNew ResearchTrainingProgrammable Systems
Blog post — June 5, 2026 — Megan Frisella, Shubham Tiwari, Andy Ruan, Yi Pan, Parker Gustafson, Mat Jacob, Gilbert Bernstein, Stephanie Wang
SyFI Team Wins CUDA Kernel Agent Contest at MLSys 2026
Blog post — May 28, 2026 — Keisuke Kamahori, Steven Gao, Vic Shihang Li, Wei Shen, Yile Gu
Let AI Agents Write Your Serving Stack with VibeServe
BlogNew ResearchInference & ServingAgents
Blog post — May 12, 2026 — Keisuke Kamahori, Shihang Vic Li, Simon Peter, Baris Kasikci
SyFI in January 2026: A Big Month for Systems-Driven AI Research
BlogLab UpdateInference & ServingTrainingML + Data
Blog post — January 31, 2026 — UW SyFI Lab
Ekka: Automated Diagnosis of Silent Errors in LLM Inference
Yile Gu, Zhen Zhang, Shaowei Zhu, Xinwei Fu, Jun Wu, Yida Wang, Baris Kasikci — International Conference on Machine Learning (ICML) (2026)
TraceLab: Characterizing Coding Agent Workloads for LLM Serving
PaperInference & ServingAgents
Kan Zhu, Mathew Jacob, Chenxi Ma, Yi Pan, Stephanie Wang, Arvind Krishnamurthy, Baris Kasikci (2026)
Piper: A Programmable Distributed Training System
PaperTrainingProgrammable Systems
Megan Frisella, Shubham Tiwari, Andy Ruan, Yi Pan, Parker Gustafson, Mat Jacob, Gilbert Bernstein, Stephanie Wang (2026)
M*: A Modular, Extensible, Serving System for Multimodal Models
PaperInference & ServingMultimodalProgrammable Systems
Atindra Jha, Naomi Sagan, Keisuke Kamahori, Irmak Sivgin, Rohan Sanda, Steven Gao, Mark Horowitz, Luke Zettlemoyer, Olivia Hsu, Jure Leskovec, Baris Kasikci, Stephanie Wang (2026)
MURMUR: An Efficient Inference System for Long-Form ASR
PaperInference & ServingMultimodal
Wei-Tzu Lee, Keisuke Kamahori, Baris Kasikci (2026)
VibeServe: Can AI Agents Build Bespoke LLM Serving Systems?
PaperInference & ServingAgents
Keisuke Kamahori, Shihang Li, Simon Peter, Baris Kasikci (2026)
VoxServe: Streaming-Centric Serving System for Speech Language Models
PaperInference & ServingMultimodal
Keisuke Kamahori, Wei-Tzu Lee, Atindra Jha, Rohan Kadekodi, Stephanie Wang, Arvind Krishnamurthy, Baris Kasikci (2026)
Reducing the GPU Memory Bottleneck with Lossless Compression for ML
Aditya K Kamath, Arvind Krishnamurthy, Marco Canini, Simon Peter — European Conference on Computer Systems (EuroSys) (2026)
FlashInfer-Bench: Building the Virtuous Cycle for AI-driven LLM Systems
PaperInference & ServingAgents
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 — Annual Conference on Machine Learning and Systems (MLSys) (2026)
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 — Annual Conference on Machine Learning and Systems (MLSys) (2026)
DynaFlow: Transparent and Flexible Intra-Device Parallelism via Programmable Operator Scheduling
PaperInference & ServingProgrammable Systems
Yi Pan, Yile Gu, Jinbin Luo, Yibo Wu, Ziren Wang, Hongtao Zhang, Ziyi Xu, Shengkai Lin, Baris Kasikci, Stephanie Wang — Annual Conference on Machine Learning and Systems (MLSys) (2026)
Unleashing Scalable Context Parallelism for Foundation Models Pre-Training via FCP
Yilong Zhao, Xiaonan Nie, Kan Zhu, Shuang Ma, Zhichao Lai, Hongxiang Hao, Yang Zhou, Baris Kasikci, Ion Stoica — Annual Conference on Machine Learning and Systems (MLSys) (2026)
TeleRAG: Efficient Retrieval-Augmented Generation Inference with Lookahead Retrieval
PaperInference & ServingML + Data
Chien-Yu Lin, Keisuke Kamahori, Yiyu Liu, Xiaoxiang Shi, Madhav Kashyap, Yile Gu, Rulin Shao, Zihao Ye, Kan Zhu, Stephanie Wang, Arvind Krishnamurthy, Rohan Kadekodi, Luis Ceze, Baris Kasikci — Annual Conference on Machine Learning and Systems (MLSys) (2026)
Tactic: Adaptive Sparse Attention with Clustering and Distribution Fitting for Long-Context LLMs
Kan Zhu, Tian Tang, Qinyu Xu, Yile Gu, Zhichen Zeng, Rohan Kadekodi, Liangyu Zhao, Ang Li, Arvind Krishnamurthy, Baris Kasikci — International Conference on Learning Representations (ICLR) (2026)
2025
Meet LLMc: Beating All Compression with LLMs
BlogNew ResearchInference & Serving
Blog post — October 3, 2025 — UW SyFI Lab
Efficient Serving of SpeechLMs with VoxServe
BlogNew ResearchInference & ServingMultimodal
Blog post — September 29, 2025 — Keisuke Kamahori, Baris Kasikci
The Streaming Batch Model for Efficient and Fault-Tolerant Heterogeneous Execution
Frank Sifei Luan, Ron Yifeng Wang, Yile Gu, Ziming Mao, Charlotte Lin, Amog Kamsetty, Hao Chen, Cheng Su, Balaji Veeramani, Scott Lee, SangBin Cho, Clark Zinzow, Eric Liang, Ion Stoica, Stephanie Wang (2025)
Programmable and Adaptive Scheduling for Distributed Systems
Yuyao Wang, Xiangfeng Zhu, Ratul Mahajan, Stephanie Wang — Hot Topics in Networks (HotNets) (2025)
Piper: Towards Flexible Pipeline Parallelism for PyTorch
PaperTrainingProgrammable Systems
Megan Frisella, Arvin Oentoro, Xiangyu Gao, Gilbert Bernstein, Stephanie Wang — Practical Adoption Challenges of ML for Systems (PACMI) (2025)
LiteASR: Efficient Automatic Speech Recognition with Low-Rank Approximation
PaperInference & ServingMultimodal
Keisuke Kamahori, Jungo Kasai, Noriyuki Kojima, Baris Kasikci — Conference on Empirical Methods in Natural Language Processing (EMNLP) (2025)
FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving
PaperInference & Serving Best Paper Award
Zihao Ye, Lequn Chen, Ruihang Lai, Wuwei Lin, Yineng Zhang, Stephanie Wang, Tianqi Chen, Baris Kasikci, Vinod Grover, Arvind Krishnamurthy, Luis Ceze — Annual Conference on Machine Learning and Systems (MLSys) (2025)
Argos: Detecting Dynamic Anomalies in the Cloud with Rule Generation
PaperAgentsReliability & Energy
Yile Gu, Hoang Doan Nguyen, Demirhan Celik, Sifat Hasan, Yifan Xiong, Jonathan Mace, Yuting Jiang, Yigong Hu, Baris Kasikci, Peng Cheng — arXiv preprint (2025) (2025)
NanoFlow: Towards Optimal Large Language Model Serving Throughput
Kan Zhu, Yufei Gao, Yilong Zhao, Liangyu Zhao, Gefei Zuo, Yile Gu, Dedong Xie, Tian Tang, Qinyu Xu, Zihao Ye, Keisuke Kamahori, Chien-Yu Lin, Ziren Wang, Stephanie Wang, Arvind Krishnamurthy, Baris Kasikci — Symposium on Operating Systems Design and Implementation (OSDI) (2025)
Magneton: Optimizing Energy Efficiency of ML Systems via Differential Energy Debugging
Yi Pan, Wenbo Qian, Dedong Xie, Ruiyan Hu, Yigong Hu, Baris Kasikci — arXiv preprint (2025) (2025)
Towards ML System Extensibility
Weixin Deng, Andy Ruan, Megan Frisella, Kai-Hsun Chen, SangBin Cho, Jack Tigar Humphries, Rui Qiao, Stephanie Wang — Hot Topics in Operating Systems (HotOS) (2025)
Fiddler: CPU-GPU Orchestration for Fast Inference of Mixture-of-Experts Models
Keisuke Kamahori, Tian Tang, Yile Gu, Kan Zhu, Baris Kasikci — International Conference on Learning Representations (ICLR) (2025)
2024
Datacomp-LM: In search of the next generation of training sets for language models
Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Gadre, Hritik Bansal, Etash Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Chandu, Thao Nguyen, Igor Vasiljevic, Sham Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar — Conference on Neural Information Processing Systems (NeurIPS) (2024)
Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference
Jiaming Tang, Yilong Zhao, Kan Zhu, Guangxuan Xiao, Baris Kasikci, Song Han — International Conference on Machine Learning (ICML) (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 — Annual Conference on Machine Learning and Systems (MLSys) (2024)