Book

ProfInfer: An eBPF-based Fine-Grained LLM Inference Profiler Bohua Zou, Debayan Roy, Dhimankumar Yogesh Airao, Weihao Xu, Binqi Sun, Yutao Liu, Haibo Chen

Conference

SpecDiff-2: Scaling Diffusion Drafter Alignment For Faster Speculative Decoding Jameson Sandler, Jacob Christopher, Tom Hartvigsen, Ferdinando Fioretto

Conference

CDLM: Consistency Diffusion Language Models for Faster Sampling Minseo Kim, Chenfeng Xu, Coleman Hooper, Harman Singh, Ben Athiwaratkun, Ce Zhang, Kurt Keutzer, Amir Gholami

Conference

Unified LLM Model for Power, Performance, and Area Prediction from Hardware Code Armin Abdollahi, Mehdi Kamal, Massoud Pedram

Conference

SuperInfer: SLO-Aware Rotary Scheduling and Memory Management for LLM Inference on Superchips Jiahuan Yu, Mingtao Hu, Zichao Lin, Minjia Zhang

Conference

HELIOS : Adaptive Model And Early-Exit Selection for Efficient LLM Inference Serving Avinash Kumar, Shashank Nag, Jason Clemons, Lizy K. John, Poulami Das

Conference

Scaling Up Large Language Models Serving Systems for Semantic Job Search Kayhan Behdin, Qingquan Song, Sriram Vasudevan, Jian Sheng, Xiaojing Ma, Z Zhou, Chuanrui Zhu, Guoyao Li, Chanh Nguyen, Sayan Ghosh, Hejian Sang, Ata Fatahi, Sundara Raman Ramachandran, Xiaoqing Wang, Qing Lan, Vinay Y S, Qi Guo, Caleb Johnson, Zhipeng Wang, Fedor Borisyuk

Conference

Massive-Scale Out-Of-Core UMAP on the GPU Jinsol Park, Corey J. Nolet, Edward Raff, Tim Oates, Akira Naruse

Conference

AccelOpt: A Self-Improving LLM Agentic System for AI Accelerator Kernel Optimization Genghan Zhang, Shaowei Zhu, Anjiang Wei, Zhenyu Song, Allen Nie, Zhen Jia, Nandita Vijaykumar, Yida Wang, Kunle Olukotun

Conference

BOOST: BOttleneck-Optimized Scalable Training Framework for Low-Rank Large Language Models Zhengyang Wang, Ziyue Liu, Ruijie Zhang, Avinash Maurya, Bogdan Nicolae, Paul Hovland, Franck Cappello, Zheng Zhang

Conference

TiDAR: Think in Diffusion, Talk in Autoregression Jingyu Liu, Xin Dong, Zhifan Ye, Rishabh Mehta, Yonggan Fu, Vartika Singh, Ce Zhang, Pavlo Molchanov

Conference

Rethinking DVFS for Mobile LLMs: Unified Energy-Aware Scheduling with CORE Zongpu Zhang, Pranab Dash, Qiang Xu, Y. Charlie Hu, Jian Li, Haibing Guan

Conference

ZK-APEX: ZERO-KNOWLEDGE APPROXIMATE PERSONALIZED UNLEARNING WITH EXECUTABLE PROOFS Mohammad M Maheri, Sunil Cotterill, Alex Davidson, Hamed Haddadi

Conference

Zero redundancy distributed learning with differential privacy Zhiqi Bu, Justin Chiu, Ruixuan Liu, Sheng Zha, George Karypis

Conference

CATWILD: Compiler Autotuning for TPU workloads in the Wild Ignacio Cano, Yu Wang, Mike Burrows, Ziqiang Feng, Matheus Camargo, Chao Wang, David Liu, Tengyu Sun, Alexander Wertheim, Arissa Wongpanich, Christof Angermueller, Hyojun Kim, Wenqi Cao, Aleksey Orekhov, Amit Sabne, Emma Sevastian, Mehrdad Khani, Karthik Srinivasa Murthy, Berkin Ilbeyi, Subhankar Shah, Ryan Lefever, Arjun Khare, Ankit Sinha, Peter Ma, Matt Bierbaum, Jeremiah Wilke, Emily Donahue, Sami Abu-El-Haija, Nikhil Sarda, Vineetha Govindaraj, Shobha Vasudevan, Kirill Gugaev, Idan Nachman, Jie Sun, Jose Baiocchi Paredes, Samrat Ghosh, Domagoj Babic, Zongwei Zhou, Naveen Kumar, Phitchaya Phothilimthana

Conference

GriNNder: Breaking the Memory Capacity Wall in Full-Graph GNN Training with Storage Offloading Jaeyong Song, Seongyeon Park, Hongsun Jang, Jaewon Jung, Hunseong Lim, Junguk Hong, Jinho Lee

Conference

ExecuTorch - A Unified PyTorch Solution to Run ML Models On-Device Mergen Nachin, Digant Desai, Stephen Jia, Chen Lai, Mengwei Liu, Jacob Szwejbka, Raziel Alvarez, RJ Ascani, Dave Bort, Manuel Candales, Andrew Caples, Yanan Cao, Zhengxu Chen, Soumith Chintala, Gregory Comer, Tanvir Islam, Songhao Jia, Tarun Karuturi, Jack Khuu, Abhinay Kukkadapu, Tugsbayasgalan Manlaibaatar, Andrew Or, Kimish Patel, Siddartha Pothapragada, Lucy Qiu, Supriya Rao, Orion Reblitz-Richardson, Max Ren, Scott Roy, Anthony Shoumikhin, Scott Wolchok, Guang Yang, Angela Yi, Martin Yuan, Hansong Zhang, Jack Zhang, Jerry Zhang, Shunting Zhang, Cagatay Bilgin

Conference

EarthSight: A Distributed Framework for Low-Latency Satellite Intelligence Ansel Erol, Seungjun Lee, Divya Mahajan

Conference

XProf: An Open, Scalable, and Extensible Profiling System for the Modern ML Stack Robert Hundt, Naveen Kumar, Jose Baiocchi Paredes, Scott Goodson, Clive Verghese, Prasanna Rengasamy, Kelvin Le, Jiya Zhang, Charles Alaras, Yin Zhang, Kan Cai, Jiten Thakkar, Sai Ganesh Bandiatmakuri, Yogesh SY, Aniruddha N. Udipi, Vikas Agarwal

Conference

Breaking the Ice: Analyzing Cold Start Latency in vLLM Huzaifa Shaaban Kabakibo, Animesh Trivedi, Lin Wang

Conference

Attribution-based Sparse Activation in Large Language Models Jifeng Song, Xiangyu Yin, Boyuan Yang, Kai Huang, Weichen Liu, Wei Gao

Conference

Once-for-All Channel Mixers (HyperTinyPW): Generative Compression for TinyML Yassien Shaalan

Conference

Ontology-Guided Long-Term Agent Memory for Conversational RAG Shuang Cao, Rui Li

Conference

GUARD: SCALABLE STRAGGLER DETECTION AND NODE HEALTH MANAGEMENT FOR LARGE-SCALE TRAINING Guanliang Liu, Abhinandan Patni, congzhu lin, Zoe zeng, Jack Wittmayer, yinghong liu, josh wu, Anthony Ko, Alexander Zhipa, Ashvin Nihalani, Binxuan Huang, Cong cheng, Mi Sun, Vijay Rajakumar, Rejith George Joseph, Parthasarathy Govindarajen

Conference

FlashInfer-Bench: Building the Virtuous Cycle for AI-driven LLM Systems Shanli Xing, Yiyan Zhai, Alexander Jiang, Yixin Dong, Yong Wu, Zihao Ye, Charlie F. Ruan, Yingyi Huang, Yineng Zhang, Liangsheng Yin, Aksara Bayyapu, Luis Ceze, Tianqi Chen

Conference

CRAFT: Fine-Grained Cost-Aware Expert Replication For Efficient Mixture-of-Experts Serving Adrian Zhao, Zhenkun Cai, Zhenyu Song, Lingfan Yu, Haozheng Fan, Jun Wu, Yida Wang, Nandita Vijaykumar

Conference

Stream2LLM: Overlap Context Streaming and Prefill for Reduced Time-to-First-Token Rajveer Bachkaniwala, Chengqi Luo, Richard So, Divya Mahajan, Kexin Rong

Conference

FlexTrain: Scalable Hybrid-Parallel Training with Elastic Resource Utilization and Consistent Accuracy Weilin Cai, Diandian Gu, Baoquan Zhong, Jun Wang, Zhuolin Zheng, Gaohong Liu, Jiang Kaihua, Shuguang Wang, Wencong Xiao, Jiayi Huang

Conference

SAKURAONE: An Open Ethernet–Based AI HPC System and Its Observed Workload Dynamics in a Single-Tenant LLM Development Environment Fumikazu KONISHI, Yuuki Tsubouchi, Hirofumi Tsuruta

Conference

PRISM: Parametrically Refactor Inference for Speculative Decoding Draft Models Xuliang Wang, Yuetao Chen, Maochan Zhen, Fang Liu, Xinzhou Zheng, Xingwu Liu, Hong Xu, Ming Li

Conference

Efficient Long-Context Language Model Training by Core Attention Disaggregation Yonghao Zhuang, Junda Chen, Bo Pang, Yi Gu, Yibo Zhu, Yimin Jiang, Ion Stoica, Hao Zhang, Eric P. Xing

Conference

Demystifying the Mixture of Experts Serving Tax Pratyush Patel, Dayeol Lee, Shintaro Iwasaki, Arvind Krishnamurthy

Conference

Sparing Strategies to Minimize Reliability Impact On Large Training Jobs Kevin Quirk, Matthew Lennie, Ehsan K. Ardestani, Satyajeet Singh Ahuja, Matthew Bergeron, Andrew Grier, Zhaodong Wang, Mustafa Ozdal, Xu Zhang, Abhinav Triguna, Ying Zhang, Mathew Oldham, Chunqiang Tang

Conference

SkipKV: Selective Skipping of KV Generation and Storage for Efficient Inference with Large Reasoning Models Jiayi Tian, Seyedarmin Azizi, Yequan Zhao, Erfan Baghaei Potraghloo, Sean McPherson, Sharath Nittur Sridhar, Zhengyang Wang, Zheng Zhang, Massoud Pedram, Souvik Kundu

Conference

PROMPTS: PeRformance Optimization via Multi-Agent Planning for LLM Training and Serving Yuran Ding, Ruobing Han, Xiaofan Zhang, Xinwei Chen

Conference

Wave: A Symbolic Python DSL And Compiler for High-Performance Machine Learning Harsh Menon, Oleksandr Zinenko, Gaurav Verma, Stanley Winata, Ivan Butygin, Nithin Meganathan, Sanket Pandit, William Hatch, Surya Jasper, Megan Kuo, Sahil Faizal, Ashay Rane, Aurore De Spirlet, Martin Paul Lücke

Conference

A Lightweight High-Throughput Collective-Capable NoC for Large-Scale ML Accelerators Luca Colagrande, Lorenzo Leone, Chen Wu, Tim Fischer, Raphael Roth, Luca Benini

Conference

Meeting SLOs, Slashing Hours: Automated Enterprise LLM Optimization with OptiKIT Nicholas Santavas, Kareem Eissa, Patrycja Cieplicka, Piotr Florek, Matteo Nulli, Stefan Vasilev, Seyyed Hadi Hashemi, Antonios Gasteratos, Shahram Khadivi

Conference

SONAR: Benchmarking Topology and Collaboration in Decentralized Learning Joyce Yuan, Yichuan Shi, Abhishek Singh, Rishi Sharma, Ramesh Raskar, Jonas Blanc, Martin Jaggi

Conference

Virtual Machine NUMA Placement at Scale: Learning the Norm, Shielding the Tail Yibo Zhao, Tianyuan Wu, Hui Xue, Qi Chen, Zhenhua Han, Zikai Xu, Yuntai Chang, Rui Gao, Steve Deng, Ray Jui-Hao Chiang, Mingxia Li, Yuqing Yang, Cheng Tan, Fan Yang, Peng Cheng, Yongqiang Xiong, Lili Qiu, Lidong Zhou

Conference

Automated Algorithm Design for Auto-Tuning Optimizers Floris-Jan Willemsen, Niki van Stein, Ben van Werkhoven

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RaidServe: High-performance Resilient Serving Ziyi Xu, Zhiqiang Xie, Swapnil Gandhi, Christos Kozyrakis

Conference

Toward Principled LLM Safety Testing: Solving the Jailbreak Oracle Problem Shuyi Lin, Anshuman Suri, Alina Oprea, Cheng Tan

Conference

HetRL: Efficient Reinforcement Learning for LLMs in Heterogeneous Environments Yongjun He, Shuai Zhang, Jiading Gai, Xiyuan Zhang, Boran Han, Bernie Wang, Huzefa Rangwala, George Karypis

Conference

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

Conference

MLCommons Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces Srinivas Sridharan, Andy Balogh, Bradford M. Beckmann, Brian Coutinho, Louis Feng, Sheng Fu, Sanshan Gao, Mehryar Garakani, Taekyung Heo, David Kanter, Josh Ladd, Ziwei Li, Winston Liu, Changhai Man, Dan Mihailescu, Spandan More, Joongun Park, Ashwin Ramachandran, Vinay Ramakrishnaiah, Saeed Rashidi, Vijay Janapa Reddi, Puneet Sharma, Phio Tian, William Won, Hanjiang Wu, Huan Xu, Jinsun Yoo, Tushar Krishna

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AIRS: Scaling Live Inference in Resource Constrained Environments Nilesh Jagnik, Xiaohao Yang, Tuan Do, Chelsea Chen, Harshvardhan GM

Conference

Speculative Decoding: Performance or Illusion? Xiaoxuan Liu, Jiaxiang Yu, Jongseok Park, Ion Stoica, Alvin Cheung

Conference

ProTrain: Efficient LLM Training via Automatic Memory Management Hanmei Yang, Jin Zhou, Yao Fu, Xiaoqun Wang, Ramine Roane, Hui Guan, Tongping Liu

Conference

BatchLLM: Optimizing Large Batched LLM Inference with Global Prefix Sharing and Throughput-oriented Token Batching Zhen Zheng, Xin Ji, Taosong Fang, Fanghao Zhou, Chuanjie Liu, Gang Peng

Conference

DisAgg: Distributed Aggregators for Efficient Secure Aggregation Haaris Mehmood, Giorgos Tatsis, Dimitrios Alexopoulos, Karthikeyan Saravanan, Jie Xu, Anastasios Drosou, Mete Ozay

Conference

OSWorld-Human: Benchmarking the Efficiency of Computer-Use Agents Reyna Abhyankar, Qi Qi, Yiying Zhang

Conference

SwiftGS: Algorithm and System Co-Optimization for Fast 3D Gaussian Splatting on GPUs Lingjun Gao, Zhican Wang, Zhiwen Mo, Hongxiang Fan

Conference

PARROT: Persuasion and Agreement Robustness Rating of Output Truth — A Sycophancy Robustness Benchmark for LLMs Yusuf Çelebi, Özay Ezerceli, Mahmoud El Hussieni

Conference

Search Your Block Floating Point Scales! Tanmaey Gupta, Hayden Prairie, Xiaoxia wu, Reyna Abhyankar, Qingyang Wu, Austin Silveria, Pragaash Ponnusamy, Jue Wang, Ben Athiwaratkun, Leon Song, Tri Dao, Daniel Y. Fu, Chris De Sa

Conference

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

Conference

StreamDiffusionV2: A Streaming System for Dynamic and Interactive Video Generation Tianrui Feng, Zhi Li, Shuo Yang, Haocheng Xi, Muyang Li, Xiuyu Li, Lvmin Zhang, Keting Yang, Kelly Peng, Song Han, Maneesh Agrawala, Kurt Keutzer, Akio Kodaira, Chenfeng Xu

Conference

Pylo: Towards Accessible Learned Optimizers in PyTorch Paul Janson, Benjamin Thérien, Quentin Anthony, Xiaolong Huang, Abhinav Moudgil, Eugene Belilovsky

Conference

FaaScale: Unlocking Fast LLM Scaling for Serverless Inference Minchen Yu, Rui Yang, Chaobo Jia, Zhaoyuan Su, Sheng Yao, Tingfeng Lan, Yuchen Yang, Zirui Wang, Yue Cheng, Wei Wang, Ao Wang, Ruichuan Chen

Conference

FarSkip-Collective: Unhobbling Blocking Communication in Mixture of Experts Models Yonatan Dukler, Guihong Li, Deval Shah, Jiang Liu, Vikram Appia, Emad Barsoum

Conference

REPARO: LOSS-RESILIENT GENERATIVE CODEC FOR VIDEO CONFERENCING Tianhong Li, Vibhaalakshmi Sivaraman, Pantea Karimi, Lijie Fan, Mohammad Alizadeh, Dina Katabi

Conference

OPKV: A High-Throughput Plugin-Driven Framework for Recallable Sparsity in Paged KV Cache Systems Huazheng Lao, Xiaofeng Li, Rui Xu, Long Chen, Xia Zhu, Jinquan Zhang

Conference

MAC-Attention: a Match--Amend--Complete scheme for fast and accurate attention computation Jinghan Yao, Sam Ade Jacobs, Walid Krichene, Masahiro Tanaka, Dhabaleswar Panda

Conference

TokenWeave: Efficient Compute-Communication Overlap for Distributed LLM Inference Raja Gond, Nipun Kwatra, Ramachandran Ramjee

Conference

When Enough is Enough: Rank-Aware Early Termination for Vector Search Jianan Lu, Asaf Cidon, Michael Freedman

Conference

Spira: Exploiting Voxel Data Structural Properties for Efficient Sparse Convolution in Point Cloud Networks Dionysios Adamopoulos, Anastasia Poulopoulou, Georgios Goumas, Christina Giannoula

Conference

Efficient, VRAM-Constrained xLM Inference on Clients Aditya Ukarande, Deep Shekhar, Marc Blackstein, Ram Rangan

Conference

MTraining: Distributed Dynamic Sparse Attention for Efficient Ultra-Long Context Training Wenxuan Li, Chengruidong Zhang, Huiqiang Jiang, Yucheng Li, Yuqing Yang, Lili Qiu

Conference

TeleRAG: Efficient Retrieval-Augmented Generation Inference with Lookahead Retrieval Chien-Yu Lin, Keisuke Kamahori, Yiyu Liu, Xiaoxiang Shi, Madhav Kashyap, Yile Gu, Rulin Shao, Zihao Ye, Kan Zhu, Rohan Kadekodi, Stephanie Wang, Arvind Krishnamurthy, Luis Ceze, Baris Kasikci

Conference

MorphServe: Efficient and Workload-Aware LLM Serving via Runtime Quantized Layer Swapping and KV Cache Resizing Zhaoyuan Su, Zeyu Zhang, Tingfeng Lan, Zirui Wang, Haiying Shen, Juncheng Yang, Yue Cheng

Conference

CSLE: A Reinforcement Learning Platform for Autonomous Security Management Kim Hammar

Conference

The OpenHands Software Agent SDK: A Composable and Extensible Foundation for Production Agents Xingyao Wang, Simon Rosenberg, Juan Michelini, Calvin Smith, Hoang H. Tran, Engel Nyst, Rohit Malhotra, Xuhui Zhou, Valerie Chen, Robert Brennan, Graham Neubig

Conference

Agentic Operator Generation for ML ASICs Alec Hammond, Aram Markosyan, Aman Dontula, Simon Mahns, Zacharias Fisches, Dmitrii Pedchenko, Keyur Muzumdar, Natacha Supper, Site Cao, Haishan Zhu, Mark Saroufim, Joe Isaacson, Laura Wang, Warren Hunt, Kaustubh Gondkar, Roman Levenstein, Gabriel Synnaeve, Richard Li, Jacob Kahn, Ajit Mathews

Conference

MoEBlaze: Breaking the Memory Wall for Efficient MoE Training on Modern GPUs Jiyuan Zhang, Yining Liu, Siqi Yan, Lisen Deng, Jennifer Cao, Shuqi Yang, Bi Xue, Min Ni, Shen Li

Conference

Blueprint, Bootstrap, and Bridge: A Security Look at NVIDIA GPU Confidential Computing Zhongshu Gu, Enriquillo Valdez, Salman Ahmed, Julian James Stephen, Michael Le, Hani Jamjoom, Shixuan Zhao, Zhiqiang Lin

Conference

Matrix: Peer-to-Peer Multi-Agent Synthetic Data Generation Framework Dong Wang, Yang Li, Ansong Ni, Ching-Feng Yeh, Youssef Emad, Xinjie Lei, Liam Robbins, Karthik Padthe, Hu Xu, Xian Li, Asli Celikyilmaz, Ramya Raghavendra, LIFEI HUANG, Carole-Jean Wu, Shang-Wen Li

Conference

NEST: Network- and Memory-Aware Device Placement for Distributed Deep Learning Irene Wang, Vishnu Varma Venkata, Arvind Krishnamurthy, Divya Mahajan

Conference

FlexiCache: Leveraging Temporal Stability of Attention Heads for Efficient KV Cache Management Nazmul Takbir, HamidReza Alikhani Koshkak, Nikil Dutt, Sangeetha Abdu Jyothi

Conference

G-HEMP: FAST MULTI-GPU PRIVATE INFERENCE FOR LARGE-SCALE GCNS WITH HOMOMORPHIC ENCRYPTION Ran Ran, Zhaoting Gong, Zhaowei Li, Xianting Lu, Jiajia Li, Wujie Wen

Conference

When Machine Learning Isn’t Sure: Building Resilient ML-Based Computer Systems by Embracing Uncertainty Varun Gohil, Nevena Stojkovic, Noman Bashir, Sundar Dev, Gaurang Upasani, David Lo, Parthasarathy Ranganathan, Christina Delimitrou

Conference

Shannonic: Efficient Entropy-Optimal Compression for ML Workloads Kareem Ibrahim, Mohammadjavad Maheronnaghsh, Andreas Moshovos

Conference

Optimizing Deployment Configurations for LLM Inference Sung Min Cho, Jaewon Lee, Chunqiang Tang, Yejin Lee, Geonhwa Jeong, Anca Agape, Scott Batura, Vincent Boivin, Stephen Chen, Renfei Chen, Sijia Chen, Yan Cui, Bradley Davis, Zhaoxia (Summer) Deng, Nick Egebo, Emad El-Haraty, Sebastien Estienne, Lu Fang, Josh Fromm, Raj Ganapathy, Vedanuj Goswami, Leo Guo, Ye Hu, Chenheli Hua, Jianyu Huang, Aya Ibrahim, Niranjan Jagannath, Hongyi Jia, Changkyu Kim, Shikai Li, Brandon Liu, Jiawen Liu, Ajit Mathews, Xiaozhu Meng, Vlad Tiberiu Mihailescu, Amit Nagpal, Maxim Naumov, Michal Ostrowski, Jialin Ouyang, Jason Park, Sarunya Pumma, Ye Qi, Zixi Qi, Jeremy Reizenstein, Rajasi Saha, Nandhini Santhanam, Zhan Shu, Ruan Silva, Grigory Sizov, Jon Maltiel Swenson, Brandon Taylor, Chris Thi, Adolfo Victoria, Yunfan Wang, Pengchao Wang, Wenchen Wang, Xiaodong Wang, Bram Wasti, Wei Xu, Qirui Yang, Jingyi Yang, Hector Yuen, Zhengyuan Zhang, Jing Zhang, Jenny Zhen, Yanjun Zhou

Conference

FlashAgents: Accelerating Multi-Agent LLM Systems via Streaming Prefill Overlap Taosong Fang, Zhen Zheng, Zhengzhao Ma, Yaojie Lu, Hongyu Lin, Xianpei Han, Le Sun

Conference

SHIP: SRAM-Based Huge Inference Pipelines for Fast LLM Serving Andrew Bitar, Aravind Vellora Vayalapra, Baorui Zhou, Matt Boyd, Charlie Wang, Sahil Parmar, Eugene Sha, Gautam Rayaprolu, Peter Hicks, Alex Bowe, Roberto DiCecco, Santosh Raghavan, Evan Patrick, Josip Smolcic, David Han, Kris Kang, Andy Rock, Josh Hay, Mohamed Eldafrawy, Mikhail Kandel, Daulet Zhanguzin, Omar Kilani, Liming Gong, Andrew Paprotskyi, Arash Taheri-Dezfouli, Josh Fender, Andrew Ling

Conference

FP8-Flow-MoE: A Casting-Free FP8 Recipe without Double Quantization Error Fengjuan Wang, Zhiyi Su, Xingzhu Hu, Cheng Wang, Mou Sun

Conference

Hippocampus: An Efficient and Scalable Memory Module for Agentic AI Yi Li, Lianjie Cao, Faraz Ahmed, Puneet Sharma, Bingzhe Li

Conference

MixLLM: LLM Quantization with Global Mixed-precision between Output-features and Highly-efficient System Design Zhen Zheng, Xiaonan Song, Chuanjie Liu

Conference

FlashAttention-4: Algorithm and Kernel Pipelining Co-Design for Asymmetric Hardware Scaling Ted Zadouri, Markus Hoehnerbach, Jay Shah, Vijay Thakkar, Tri Dao

Conference

ContextPilot: Fast Long-Context Inference via Context Reuse Yinsicheng Jiang, Yeqi Huang, Liang Cheng, Cheng Deng, Xuan Sun, Luo Mai

Conference

ProToken: Token-Level Attribution for Federated Large Language Models Waris Gill, Ahmad Humayun, Ali Anwar, Muhammad Ali Gulzar

Conference

PLA-Serve: A Prefill-Length-Aware LLM Serving System JIANSHU SHE, Zonghang li, Hongchao Du, Shangyu Wu, Wenhao Zheng, Eric P. Xing, Zhengzhong Liu, Huaxiu Yao, Jason Xue, Qirong Ho

Conference

ApproxMLIR : Accuracy-Aware Compiler for Compound ML System Hao Ren, Yi Mu, Sasa Misailovic

Conference

DynaFlow: Transparent and Flexible Intra-Device Parallelism via Programmable Operator Scheduling Yi Pan, Yile Gu, Jinbin Luo, Yibo Wu, Ziren Wang, Hongtao Zhang, Ziyi Xu, Shengkai Lin, Baris Kasikci, Stephanie Wang

Conference

Flashlight: PyTorch Compiler Extensions to Accelerate Attention Variants Bozhi You, Irene Wang, Zelal Su Mustafaoglu, Abhinav Jangda, Angélica Moreira, Roshan Dathathri, Divya Mahajan, Keshav Pingali

Conference

HipKittens: Fast and Furious AMD Kernels William Hu, Drew Wadsworth, Sean Siddens, Stanley Winata, Daniel Y. Fu, Ryan Swann, Muhammad Osama, Christopher Ré, Simran Arora

Conference

Optimizing PyTorch Inference with LLM-Based Multi-Agent Systems Kirill Nagaitsev, Luka Grbcic, Samuel Williams, Costin Iancu

Conference

Zorse: Optimizing LLM Training Efficiency on Heterogeneous GPU Clusters Runsheng Guo, Utkarsh Anand, Khuzaima Daudjee, Rathijit Sen

Conference

CAGE: Curvature-Aware Gradient Estimation For Accurate Quantization-Aware Training Soroush Tabesh, Mher Safaryan, Andrei Panferov, Alexandra Volkova, Dan Alistarh

Conference

From Tokens to Layers: Redefining Stall-Free Scheduling for MoE Serving with Layered Prefill Gunjun Lee, Jiwon Kim, Jaiyoung Park, Younjoo Lee, Jung Ho Ahn

Conference

AgenticCache: Cache-Driven Asynchronous Planning for Embodied AI Agents Hojoon Kim, Yuheng Wu, Thierry Tambe

Conference

BLASST: Dynamic BLocked Attention Sparsity via Softmax Thresholding Jiayi Yuan, Cameron Shinn, Kai Xu, Jingze Cui, George Klimiashvili, Guangxuan Xiao, Perkz Zheng, Bo Li, Yuxin Zhou, Zhouhai Ye, Weijie You, Tian Zheng, Dominic Brown, Pengbo Wang, Markus Hoehnerbach, Richard Cai, Julien Demouth, John D. Owens, Xia Hu, Song Han, Timmy Liu, Huizi Mao

Conference

Locality-Aware Beam Scheduling for Efficient Test-Time Compute with a Consumer-grade GPU Hsing-Ti Wang, Hung-Tso Shiao, Chia-Lin Yang

Conference

PLayer-FL: A Principled Approach to Personalized Layer-wise Cross-Silo Federated Learning Ahmed Elhussein, Florent Pollet, Gamze Gürsoy

Conference

Beat the long tail: Distribution-Aware Speculative Decoding for RL Training ZELEI SHAO, Vikranth Srivatsa, Sanjana Srivastava, Qingyang Wu, Alpay Ariyak, Xiaoxia wu, Ameen Patel, Jue Wang, Percy Liang, Tri Dao, Ce Zhang, Yiying Zhang, Ben Athiwaratkun, Chenfeng Xu, Junxiong Wang

Conference

VeriMoA: A Mixture-of-Agents Framework for Spec-to-HDL Generation Heng Ping, Arijit Bhattacharjee, Peiyu Zhang, Shixuan Li, Wei Yang, Anzhe Cheng, Xiaole Zhang, Jesse Thomason, Ali Jannesari, Nesreen Ahmed, Paul Bogdan

Conference

AXLearn: Modular, Hardware-Agnostic Large Model Training Mark Lee, Chang Lan, Tom Gunter, John Peebles, Hanzhi Zhou, Xuan Kelvin Zou, Sneha Bangalore, Chung-Cheng Chiu, Nan Du, Xianzhi Du, Philipp Dufter, Liang He, Ruixuan Hou, Haoshuo Huang, Dongseong Hwang, Xiang Kong, Jinhao Lei, Tao Lei, Ethan Li, Li Li, Jiarui Lu, Zhiyun Lu, Yiping Ma, David Qiu, Vivek Rathod, Senyu Tong, Zhucheng Tu, Chong Wang, Jianyu Wang, Yongqiang Wang, Zirui Wang, Floris Weers, Sam Wiseman, Guoli Yin, Bowen Zhang, Xiyou Zhou, Danyang Zhuo, Cheng Leong, Ruoming Pang

Conference

Beyond the Buzz: A Pragmatic Take on Inference Disaggregation Tiyasa Mitra, Ritika Borkar, Nidhi Bhatia, Shivam Raj, Hongkuan Zhou, Yan Ru Pei, Vishwanath Venkatesan, Kyle Kranen, Ramon Matas, Dheevatsa Mudigere, Ritchie Zhao, Maximilian Golub, Arpan Dutta, Suresh Nambi, Sailaja Madduri, Dharmesh Jani, Brian Pharris, Itay Neeman, Bita Darvish Rouhani

Conference

HexiScale: Facilitating Large Language Model Training over Heterogeneous Hardware Ran Yan, YOUHE JIANG, Xiaonan Nie, Fangcheng Fu, Bin CUI, Binhang Yuan

Conference

veScale-FSDP: Flexible and High-Performance FSDP at Scale Zezhou Wang, Youjie Li, Zhiqi Lin, Jiacheng Yang, Cong Xie, Guanyu Feng, Zheng Zhong, Ziyue Huang, Hongyu Zhu, Zhi Zhang, Yanghua Peng, Xin Liu

Conference

Cost-aware Duration Prediction for Software Upgrades in Datacenters Yi Ding, Aijia Gao, Thibaud Ryden, Michal Sedlak, Essam Ewaisha, Igor Marnat, Henry Hoffmann

Conference

GhostServe: A Lightweight Checkpointing System in the Shadow for Fault-Tolerant LLM Serving Shakya Jayakody, Youpeng Zhao, Chinmay Dhanraj Nehate, Jun Wang

Conference

Learning from Less: Measuring the Effectiveness of RLVR in Low Data and Compute Regimes Justin Bauer, Thomas Walshe, Derek Pham, Harit Vishwakarma, Armin Parchami, Frederic Sala, Paroma Varma

Conference

db-SP: Accelerating Sparse Attention for Visual Generative Models with Dual-Balanced Sequence Parallelism Siqi Chen, Ke Hong, Tianchen Zhao, Ruiqi Xie, Zhenhua Zhu, Xudong Zhang, Yu Wang

Conference

Charon: A Unified and Fine-Grained Simulator for Large-Scale LLM Training and Inference Mengtian Yang, Zhekun Zhang, Mingheng Wu, Jianwen Yan, Hanshi Sun, Li-Wen Chang

Conference

ReSpec: Towards Optimizing Speculative Decoding in Reinforcement Learning Systems Qiaoling Chen, Zijun Liu, Peng Sun, Shenggui Li, Guoteng Wang, Ziming Liu, Yonggang Wen, Siyuan Feng, Tianwei Zhang

Conference

fabric-lib: RDMA Point-to-Point Communication for LLM Systems Nandor Licker, Kevin Hu, Vladimir Zaytsev, Lequn Chen

Conference

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

Conference

Hawkeye: Reproducing GPU-Level Non-Determinism Erez Badash, Dan Boneh, Ilan Komargodski, Megha Srivastava

Conference

LEANN: A Low-Storage Overhead Vector Index Yichuan Wang, Zhifei Li, Shu Liu, Yongji Wu, Ziming Mao, Yilong Zhao, Xiao Yan, Zhiying Xu, Yang Zhou, Ion Stoica, Sewon Min, Matei Zaharia, Joseph E. Gonzalez

Conference

Kitty: Accurate and Efficient 2-bit KV Cache Quantization with Dynamic Channel-wise Precision Boost Haojun Xia, Xiaoxia wu, Jisen Li, Tsai-chuan Wu, Junxiong Wang, Jue Wang, Chenxi Li, Aman Singhal, Alay Dilipbhai Shah, Alpay Ariyak, Donglin Zhuang, Zhongzhu Zhou, Ben Athiwaratkun, Zhen Zheng, Shuaiwen Song

Conference

DriftBench: Measuring and Predicting Infrastructure Drift in LLM Serving Systems Gianluigi Vitale

Conference

IntAttention: A Fully Integer Attention Pipeline for Efficient Edge Inference Wanli Zhong, Haibo Feng, Zirui Zhou, Hanyang Peng, Shiqi Yu

Conference

BEAM: Joint Resource–Power Optimization for Energy-Efficient LLM Inference under SLO contraints Hyunjae Lee, Sangjin Choi, Seungjae Lim, Youngjin Kwon

Conference

BOute: Cost-Efficient LLM Serving with Heterogeneous LLMs and GPUs via Multi-Objective Bayesian Optimization YOUHE JIANG, Fangcheng Fu, Eiko Yoneki

Conference

Practical Adversarial Multi-Armed Bandits with Sublinear Runtime Kasper Overgaard Mortensen, Ama Bembua Bainson, Mathias Ravn Tversted, Kristoffer Strube Græm, Renata Borovica-Gajic, Andrea Paudice, Davide Mottin, Panagiotis Karras

Conference

ADR: AN AGENTIC DETECTION SYSTEMFORENTERPRISE AGENTIC AI SECURITY Chenning Li, Pan Hu, Justin Xu, Baris Ozbas, Olivia Liu, Caroline Van, Manxue Li, Wei Zhou, Mohammad Alizadeh, Pengyu Zhang, KK Sriramadhesikan, Ming Zhang

Conference

TriInfer: Hybrid EPD Disaggregation for Efficient Multimodal Large Language Model Inference Xianzhe Dong, Tongxuan Liu, Yuting Zeng, Weizhe Huang, Xiaoyang Zhao, Siyu Wu, Liangyu Liu, Yang Liu, Yu Wu, Hailong Yang, Ke Zhang, Jing Li

Conference

FreeScale: Distributed Training for Sequence Recommendation Models with Minimal Scaling Cost Chenhao Feng, Haoli Zhang, Shakhzod Ali-zade, Yanli Zhao, Liang Luo, Jennifer Cao, Lisen Deng, Siqiao Chen, Chenyu Zhao, Tristan Rice, Daniel Johnson, Min Si, Tiantu Xu, Yi Zhang, Evgenii Kolpakov, Siqi Yan, Chuanhao Zhuge, Min Ni, Bi Xue, Qunshu Zhang, Shen Li

Conference

FLoRIST: Singular Value Thresholding for Efficient and Accurate Federated Fine-Tuning of Large Language Models Hariharan Ramesh, Jyotikrishna Dass

Conference

Dataflow Is All You Need Darshan Gandhi, Pushkar Nandkar, David Koeplinger, Nasim Farahini, Romy Tsoupidi, Samuel Rydh, Matheen Musaddiq, Tuowen Zhao, Reid Goodbar, Nathan Sheeley, Leon Zhang, Matthew Shaffer, John Long, Han Wang, Angela Wang, Arjun Sabnis, Joshua Brot, Yun Du, Hakan Zeffer, Mingran Wang, Raghu Prabhakar

Conference

DreamDDP: Accelerating Low-Bandwidth Geo-Distributed LLM Training with Layer-wise Partial Synchronization zhenheng Tang, Zichen TANG, Junlin Huang, Xinglin Pan, Rudan Yan, Yuxin Wang, Amelie Chi Zhou, Shaohuai Shi, Xiaowen Chu, Bo Li

Conference

Using Span Queries to Optimize Cache and Attention Locality Paul Castro, Nick Mitchell, Nathan Ordonez, Thomas Parnell, Mudhakar Srivatsa, Antoni Viros-i-Martin

Conference

Privatar: Scalable Privacy-preserving Multi-user VR via Secure Offloading Jianming Tong, Hanshen Xiao, Krishna Kumar Nair, Hao Kang, Ashish Sirasao, Ziqi Zhang, G. Edward Suh, Tushar Krishna

Conference

Machine Learning Fleet Efficiency: Improving TPU Systems at Scale with ML Productivity Goodput Arissa Wongpanich, Tayo Oguntebi, Jose Baiocchi Paredes, Yu Wang, Phitchaya Phothilimthana, Ritwika Mitra, Zongwei Zhou, Naveen Kumar, Vijay Janapa Reddi

Conference

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels Stuart H. Sul, Simran Arora, Benjamin F. Spector, Christopher Ré

Conference

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