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Poster
Ballroom B - Position 16
MegaBlocks: Efficient Sparse Training with Mixture-of-Experts
In Sparsity 1: Models and Algorithms
Trevor Gale · Deepak Narayanan · Cliff Young · Matei Zaharia
[ Paper] 
Poster
Ballroom B - Position 2
Tutel: Adaptive Mixture-of-Experts at Scale
In Parallel and Distributed Systems 1: Parallelism
Changho Hwang · Wei Cui · Yifan Xiong · Ziyue Yang · Ze Liu · Han Hu · Zilong Wang · Rafael Salas · Jithin Jose · Prabhat Ram · HoYuen Chau · Peng Cheng · Fan Yang · Mao Yang · Yongqiang Xiong
[ Paper]  [ Slides] 
Poster
Ballroom B - Position 31
GiPH: Generalizable Placement Learning for Adaptive Heterogeneous Computing
In ML for Systems
Yi Hu · Chaoran Zhang · Edward Andert · Harshul Singh · Aviral Shrivastava · James Laudon · Yanqi Zhou · Bob Iannucci · Carlee Joe-Wong
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 5
Communication-Efficient Graph Neural Networks with Probabilistic Neighborhood Expansion Analysis and Caching
In Parallel and Distributed Systems 2: Communication
Tim Kaler · Alexandros Iliopoulos · Philip Murzynowski · Tao Schardl · Charles E. Leiserson · Jie Chen
[ Paper]  [ Poster] 
Poster
Ballroom B - Position 17
Uniform Sparsity in Deep Neural Networks
In Sparsity 1: Models and Algorithms
Saurav Muralidharan
[ Paper]  [ Poster] 
Poster
Ballroom B - Position 46
SUBGRAPH STATIONARY HARDWARE-SOFTWARE INFERENCE CO-DESIGN
In Edge
Payman Behnam · Alexey Tumanov · Tushar Krishna · Pranav Gadikar · Yangyu Chen · Jianming Tong · Yue Pan · Abhimanyu Rajeshkumar Bambhaniya · Alind Khare
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 29
GlueFL: Reconciling Client Sampling and Model Masking for Bandwidth Efficient Federated Learning
In Federated Learning
Shiqi He · Qifan Yan · Feijie Wu · Lanjun Wang · Mathias Lécuyer · Ivan Beschastnikh
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 21
Exploiting Hardware Utilization and Adaptive Dataflow for Efficient Sparse Convolution in 3D Point Clouds
In Sparsity 2: Systems
Ke Hong · Zhongming Yu · Guohao Dai · Xinhao Yang · Yaoxiu Lian · 泽浩 刘 · Ningyi Xu · Yu Wang
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 26
FedTree: A Federated Learning System For Trees
In Federated Learning
Qinbin Li · Zhaomin Wu · Yanzheng Cai · yuxuan han · Ching Man Yung · Tianyuan Fu · Bingsheng He
[ Paper] 
Poster
Ballroom B - Position 11
RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid Network
In Memory Optimization
Vitaliy Chiley · Vithursan Thangarasa · Abhay Gupta · Anshul Samar · Joel Hestness · Dennis DeCoste
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 7
On Optimizing the Communication of Model Parallelism
In Parallel and Distributed Systems 2: Communication
Yonghao Zhuang · Lianmin Zheng · Zhuohan Li · Eric Xing · Qirong Ho · Joseph Gonzalez · Ion Stoica · Hao Zhang · Hexu Zhao
[ Paper]  [ Poster] 
Poster
Ballroom B - Position 39
HyperGef: A Framework Enabling Efficient Fusion for Hypergraph Neural Network on GPUs
In Emerging Models and Domains
Zhongming Yu · Guohao Dai · Shang Yang · Genghan Zhang · Hengrui Zhang · Feiwen Zhu · June Yang · Jishen Zhao · Yu Wang
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 12
Validating Large Language Models with ReLM
In Correctness and Security
Michael Kuchnik · Virginia Smith · George Amvrosiadis
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 19
Efficient GPU Kernels for N:M-Sparse Weights in Deep Learning
In Sparsity 2: Systems
Bin Lin · Ningxin Zheng · Lei Wang · Shijie Cao · Lingxiao Ma · Quanlu Zhang · Yi Zhu · Ting Cao · Jilong Xue · Yuqing Yang · Fan Yang
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 8
Transcending Runtime-Memory Tradeoffs in Checkpointing by being Fusion Aware
In Memory Optimization
Horace He · Shangdi Yu
[ Paper]  [ Poster] 
Poster
Ballroom B - Position 23
Efficiently Scaling Transformer Inference
In Measurement and Analysis
Reiner Pope · Sholto Douglas · Aakanksha Chowdhery · Jacob Devlin · James Bradbury · Jonathan Heek · Kefan Xiao · Shivani Agrawal · Jeff Dean
[ Paper]  [ Poster] 
Poster
Ballroom B - Position 24
Hotline Profiler: Automatic Annotation and A Multi-Scale Timeline for Visualizing Time-Use in DNN Training
In Measurement and Analysis
Daniel Snider · Fanny Chevalier · Gennady Pekhimenko
[ Paper]  [ Slides] 
Poster
Ballroom B - Position 28
On Noisy Evaluation in Federated Hyperparameter Tuning
In Federated Learning
Kevin Kuo · Pratiksha Thaker · Mikhail Khodak · John Nguyen · Daniel Jiang · Ameet Talwalkar · Virginia Smith
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 6
Adaptive Message Quantization and Parallelization for Distributed Full-graph GNN Training
In Parallel and Distributed Systems 2: Communication
Borui Wan · Juntao Zhao · Chuan Wu
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 32
Learning to Parallelize with OpenMP by Augmented Heterogeneous AST Representation
In ML for Systems
Le Chen · Quazi Ishtiaque Mahmud · Hung Phan · Nesreen Ahmed · Ali Jannesari
[ Paper]  [ Poster] 
Poster
Ballroom B - Position 25
ApproxCaliper: A Programmable Framework for Application-aware Neural Network Optimization
In Measurement and Analysis
Yifan Zhao · Hashim Sharif · Peter Pao-Huang · Vatsin Shah · Arun Narenthiran Sivakumar · Mateus Valverde Gasparino · Abdulrahman Mahmoud · Nathan Zhao · Sarita Adve · Girish Chowdhary · Sasa Misailovic · Vikram Adve
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 33
Virtual Machine Allocation with Lifetime Predictions
In ML for Systems
Hugo Barbalho · Patricia Kovaleski · Beibin Li · Luke Marshall · Marco Molinaro · Abhisek Pan · Eli Cortez · Matheus Leao · Harsh Patwari · Zuzu Tang · Larissa Rozales Gonçalves · David Dion · Thomas Moscibroda · Ishai Menache
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 37
XRBench: An Extended Reality (XR) Machine Learning Benchmark Suite for the Metaverse
In Emerging Models and Domains
Hyoukjun Kwon · Krishnakumar Nair · Jamin Seo · Jason Yik · Debabrata Mohapatra · Dongyuan Zhan · JINOOK SONG · Peter Capak · Peizhao Zhang · Peter Vajda · Colby Banbury · Mark Mazumder · Liangzhen Lai · Ashish Sirasao · Tushar Krishna · Harshit Khaitan · Vikas Chandra · Vijay Janapa Reddi
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 30
AutoScratch: ML-Optimized Cache Management for Inference-Oriented GPUs
In ML for Systems
Yaosheng Fu · Evgeny Bolotin · Aamer Jaleel · Gal Dalal · Shie Mannor · Jacob Subag · Noam Korem · Michael Behar · David Nellans
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 20
Unified Convolution Framework: A compiler-based approach to support sparse convolutions
In Sparsity 2: Systems
Jaeyeon Won · Changwan Hong · Charith Mendis · Joel Emer · Saman Amarasinghe
[ Paper] 
Poster
Ballroom B - Position 45
Edge Impulse: An MLOps Platform for Tiny Machine Learning
In Edge
colby banbury · Vijay Janapa Reddi · Alexander Elium · Shawn Hymel · David Tischler · Daniel Situnayake · Carl Ward · Louis Moreau · Jenny Plunkett · Matthew Kelcey · Mathijs Baaijens · Alessandro Grande · Dmitry Maslov · Arthur Beavis · Jan Jongboom · Jessica Quaye
[ Paper] 
Poster
Ballroom B - Position 3
Breadth-First Pipeline Parallelism
In Parallel and Distributed Systems 1: Parallelism
Joel Lamy-Poirier
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 9
Safe Optimized Static Memory Allocation for Parallel Deep Learning
In Memory Optimization
Ioannis Lamprou · Zhen Zhang · Javier de Juan · Hang Yang · Yongqiang Lai · Etienne Filhol · Cedric Bastoul
[ Paper]  [ Slides] 
Poster
Ballroom B - Position 38
Renee: END-TO-END TRAINING OF EXTREME CLASSIFICATION MODELS
In Emerging Models and Domains
Vidit Jain · Jatin Prakash · Deepak Saini · Jian Jiao · Ramachandran Ramjee · Manik Varma
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 43
RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure
In Storage, Scheduling, and Networking
Mark Zhao · Dhruv Choudhary · Devashish Tyagi · Ajay Somani · Max Kaplan · Sung-Han Lin · Sarunya Pumma · Jongsoo Park · Aarti Basant · Niket Agarwal · Carole-Jean Wu · Christos Kozyrakis
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 10
Reducing Activation Recomputation in Large Transformer Models
In Memory Optimization
Vijay Anand Korthikanti · Jared Casper · Sangkug Lym · Lawrence McAfee · Michael Andersch · Mohammad Shoeybi · Bryan Catanzaro
[ Paper]  [ Poster] 
Poster
Ballroom B - Position 22
Sparsity-Aware Memory Interface Architecture using Stacked XORNet Compression for Accelerating Pruned-DNN Models
In Sparsity 2: Systems
Younghoon Byun · Seungsik Moon · Baeseong Park · Se Jung Kwon · Dongsoo Lee · Gunho Park · Eunji Yoo · Jung Gyu Min · Youngjoo Lee
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 34
ALCOP: Automatic Load-Compute Pipelining in Deep Learning Compiler for AI-GPUs
In Compilers
Guyue Huang · Yang Bai · Liu Liu · Yuke Wang · Bei Yu · Yufei Ding · Yuan Xie
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 44
Practical Edge Kernels for Integer-Only Vision Transformers Under Post-training Quantization
In Edge
Zining Zhang · Bingsheng He · Zhenjie Zhang
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 27
FLINT: A Platform for Federated Learning Integration
In Federated Learning
Ewen Wang · Boyi Chen · Mosharaf Chowdhury · Ajay Kannan · Franco Liang
[ Paper]  [ Poster] 
Poster
Ballroom B - Position 15
Building Verified Neural Networks for Computer Systems with Ouroboros
In Correctness and Security
Cheng Tan · Changliu Liu · Zhihao Jia · Tianhao Wei
[ Paper]  [ Poster] 
Poster
Ballroom B - Position 4
Cupcake: A Compression Scheduler for Scalable Communication-Efficient Distributed Training
In Parallel and Distributed Systems 2: Communication
Zhuang Wang · Xinyu Wu · Zhaozhuo Xu · T. S. Eugene Ng
[ Paper]  [ Slides] 
Poster
Ballroom B - Position 14
Be Careful with PyPI Packages: You May Unconsciously Spread Backdoor Model Weights
In Correctness and Security
Tianhang Zheng · Hao Lan · Baochun Li
[ Paper]  [ Poster] 
Poster
Ballroom B - Position 1
PipeFisher: Efficient Training of Large Language Models Using Pipelining and Fisher Information Matrices
In Parallel and Distributed Systems 1: Parallelism
Kazuki Osawa · Shigang Li · Torsten Hoefler
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 35
SIRIUS: Harvesting Whole-Program Optimization Opportunities for DNNs
In Compilers
YIJIN LI · Jiacheng Zhao · Sun Qianqi · Haohui Mai · Lei Chen · Wanlu Cao · Yanfan Chen · Li zhicheng · YING LIU · Xinyuan Zhang · Xiyu Shi · Jie Zhao · Jingling Xue · HUIMIN CUI · XiaoBing Feng
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 36
X-RLFLOW: GRAPH REINFORCEMENT LEARNING FOR NEURAL NETWORK SUBGRAPHS TRANSFORMATION
In Compilers
Guoliang HE · Sean Parker · Eiko Yoneki
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 41
μ-TWO: 3× Faster Multi-Model Training with Orchestration and Memory Optimization
In Storage, Scheduling, and Networking
Sanket Purandare · Abdul Wasay · Stratos Idreos · Animesh Jain
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 42
PyTorch RPC: Distributed Deep Learning Built on Tensor-Optimized Remote Procedure Calls
In Storage, Scheduling, and Networking
Pritam Damania · Shen Li · Alban Desmaison · Alisson Azzolini · Brian Vaughan · Edward Yang · Gregory Chanan · Guoqiang Jerry Chen · Hongyi Jia · Howard Huang · Joseph Spisak · Luca Wehrstedt · Lucas Hosseini · Manoj Krishnan · Omkar Salpekar · Pavel Belevich · Rohan Varma · Satendra Gera · Wanchao Liang · Shihao Xu · Soumith Chintala · Chaoyang He · Amir Ziashahabi · Salman Avestimehr · · Zachary DeVito
[ Paper]  [ Slides] 
Poster
Ballroom B - Position 18
Cuttlefish: Low-Rank Model Training without All the Tuning
In Sparsity 1: Models and Algorithms
Hongyi Wang · Saurabh Agarwal · Pongsakorn U-chupala · Yoshiki Tanaka · Eric Xing · Dimitris Papailiopoulos
[ Paper]  [ Poster] 
Poster
Ballroom B - Position 40
Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models
In Storage, Scheduling, and Networking
Daochen Zha · Louis Feng · Liang Luo · Bhargav Bhushanam · Zirui Liu · Yusuo Hu · Jade Nie · Yuzhen Huang · Yuandong Tian · Arun Kejariwal · Xia Hu
[ Paper]  [ Slides]  [ Poster] 
Poster
Ballroom B - Position 13
SysNoise: Exploring and Benchmarking Training-Deployment System Inconsistency
In Correctness and Security
Yan Wang · Yuhang Li · Ruihao Gong · Aishan Liu · yanfei wang · Jian Hu · Yongqiang Yao · Yunchen Zhang · tianzi xiaotian · Fengwei Yu · Xianglong Liu
[ Paper]  [ Slides]  [ Poster] 
Registration Desk
Mon Jun 05 04:30 AM -- 01:00 PM (PDT) None
Registration Desk
Break
Mon Jun 05 05:00 AM -- 05:45 AM (PDT) None
Coffee Break
Opening Remarks
Mon Jun 05 05:45 AM -- 06:00 AM (PDT) @ Ballroom C None
Opening Remarks
Session
Mon Jun 05 06:00 AM -- 07:00 AM (PDT) @ Ballroom C None
Parallel and Distributed Systems 1: Parallelism
Coffee Break
Mon Jun 05 07:00 AM -- 07:30 AM (PDT) None
Coffee Break
Invited Talk
Mon Jun 05 07:30 AM -- 08:30 AM (PDT) @ Ballroom C None
Improving the Quality and Factuality of Large Language Model Applications
Matei Zaharia
Break
Mon Jun 05 08:30 AM -- 10:30 AM (PDT) None
Lunch Break, on your own
Round Table Discussion
Mon Jun 05 09:45 AM -- 10:30 AM (PDT) None
Round Table Discussion
Session
Mon Jun 05 10:30 AM -- 11:50 AM (PDT) @ Ballroom C None
Memory Optimization
Coffee Break
Mon Jun 05 11:50 AM -- 12:20 PM (PDT) None
Coffee Break
Session
Mon Jun 05 12:20 PM -- 01:40 PM (PDT) @ Ballroom C None
Correctness and Security
Session
Mon Jun 05 01:40 PM -- 02:40 PM (PDT) @ Ballroom C None
Sparsity 1: Models and Algorithms
Poster Session / Reception
Mon Jun 05 02:40 PM -- 05:00 PM (PDT) @ Ballroom B None
Poster Session/Reception
Registration Desk
Tue Jun 06 04:30 AM -- 01:00 PM (PDT) None
Registration Desk
Break
Tue Jun 06 05:30 AM -- 06:00 AM (PDT) None
Coffee Break
Session
Tue Jun 06 06:00 AM -- 07:00 AM (PDT) @ Ballroom C None
Measurement and Analysis
Coffee Break
Tue Jun 06 07:00 AM -- 07:30 AM (PDT) None
Coffee Break
Invited Talk
Tue Jun 06 07:30 AM -- 08:30 AM (PDT) @ Ballroom C None
Do we need Attention?
Alexander Rush
Break
Tue Jun 06 08:30 AM -- 10:30 AM (PDT) None
Lunch Break, on your own
Session
Tue Jun 06 10:30 AM -- 11:50 AM (PDT) @ Ballroom C None
Parallel and Distributed Systems 2: Communication
Coffee Break
Tue Jun 06 11:50 AM -- 12:20 PM (PDT) None
Coffee Break
Session
Tue Jun 06 12:20 PM -- 01:40 PM (PDT) @ Ballroom C None
Federated Learning
Session
Tue Jun 06 01:40 PM -- 03:00 PM (PDT) @ Ballroom C None
ML for Systems
Registration Desk
Wed Jun 07 04:30 AM -- 01:00 PM (PDT) None
Registration Desk
Break
Wed Jun 07 05:30 AM -- 06:00 AM (PDT) None
Coffee Break
Session
Wed Jun 07 06:00 AM -- 07:00 AM (PDT) @ Ballroom C None
Compilers
Coffee Break
Wed Jun 07 07:00 AM -- 07:30 AM (PDT) None
Coffee Break
Session
Wed Jun 07 07:30 AM -- 08:30 AM (PDT) @ Ballroom C None
Emerging Models and Domains
Break
Wed Jun 07 08:30 AM -- 10:30 AM (PDT) None
Lunch Break, on your own
Session
Wed Jun 07 10:30 AM -- 12:20 PM (PDT) @ Ballroom C None
Sparsity 2: Systems
Coffee Break
Wed Jun 07 11:50 AM -- 12:20 PM (PDT) None
Coffee Break
Session
Wed Jun 07 12:20 PM -- 01:40 PM (PDT) @ Ballroom C None
Storage, Scheduling, and Networking
Session
Wed Jun 07 01:40 PM -- 02:40 PM (PDT) @ Ballroom C None
Edge
Registration Desk
Thu Jun 08 04:00 AM -- 09:00 AM (PDT) None
Registration Desk
Workshop
Thu Jun 08 05:00 AM -- 02:00 PM (PDT) @ Room 238 None
2nd Workshop on Practical Adoption Challenges of ML for Systems in Industry
Deniz Altınbüken · Lyric Doshi · Milad Hashemi · Martin Maas
Workshop
Thu Jun 08 05:00 AM -- 02:00 PM (PDT) @ Room 241 None
Benchmarking Machine Learning Workloads on Emerging Hardware
Tom St John · Murali Emani · Wenqian Dong
Workshop
Thu Jun 08 05:30 AM -- 02:00 PM (PDT) @ Room 239 None
Research On Algorithms & Data Structures (ROADS) to Mega-AI Models
Zhaozhuo Xu · Aditya Desai · Anshumali Shrivastava
Workshop
Thu Jun 08 05:45 AM -- 03:20 PM (PDT) @ Room 247 None
Workshop on Decentralized and Collaborative Learning
Binhang Yuan · Beidi Chen · Virginia Smith · Ce Zhang · Christopher Re
Workshop
Thu Jun 08 05:50 AM -- 02:05 PM (PDT) @ Room 242 None
Workshop on Federated Learning Systems
Dimitris Stripelis · Chaoyang He · Hongyi Wang · Tian Li · Praneeth Vepakomma · Bo Li · Eric Xing
Workshop
Thu Jun 08 06:00 AM -- 12:00 PM (PDT) @ Room 246 None
Resource-Constrained Learning in Wireless Networks
Navid NaderiAlizadeh · M. Hadi Amini · Virginia Smith · Ahmed Alkhateeb · Ravikumar Balakrishnan · Arash Behboodi · Jakob Hoydis · Christoph Studer
Workshop
Thu Jun 08 06:00 AM -- 02:15 PM (PDT) @ Room 248 None
The 3rd On-Device Intelligence Workshop
Vijay Janapa Reddi · Paul Whatmough · Vikas Chandra · Pete Warden · Brian Plancher · Colby Banbury · Matthew Stewart
Workshop
Thu Jun 08 06:50 AM -- 02:00 PM (PDT) @ Room 240 None
Workshop on Systems for Next-Gen AI Paradigms
Jason Yik · Brian Anderson · Charlotte Frenkel · Vijay Janapa Reddi · Zergham Ahmed
Coffee Break
Thu Jun 08 07:00 AM -- 07:30 AM (PDT) None
Coffee Break
Coffee Break
Thu Jun 08 12:00 PM -- 12:30 PM (PDT) None
Coffee Break