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Conferences / PyTorch Conference

PyTorch Conference 2024

Sep 18–19, 2024 · Fort Mason Center, San Francisco, CA, United States

Conference
PyTorch Conference Data science & ML
Dates
Sep 18, 2024 – Sep 19, 2024
Venue
Fort Mason Center
Place
San Francisco, CA, United States
Format
In person
Status
Past
Attendance
1,500
PyTorch blog recap: 'gathered nearly 1,500 AI researchers, developers, and enthusiasts' (approximate).
Website
events.linuxfoundation.org
Recorded
31 sponsors · 146 speaker appearances
Notes
Full Sched programme recorded (95 sessions incl. DL Compiler and Fine Tuning mini-summits, breaks excluded); affiliations as shown on Sched. Registration prices not shown on the archived LF register page.

Ticket prices

No ticket prices recorded

Sponsors 31

Speakers and talks 146

SpeakerCompanyRoleTalkLinks
Aleksander MądryOpenAIKeynoteKeynote Panel Discussion: Responsible AI—
Anastasios AngelopolousLMArenaKeynoteKeynote Panel Discussion: Scaling & Benchmarking—
Anush ElangovanAMDKeynoteSponsored Keynote: Accelerating AI: How AMD and PyTorch Drive Innovation with Seamless Day-0 Support and High Performance—
Aparna RamaniMetaKeynoteKeynote Panel Discussion: Scaling & Benchmarking—
Chip HuyenTep StudioKeynoteKeynote: Why You Should Think Twice Before Paying for an Evaluation Tool—
Cormac BrickGoogleKeynoteKeynote: Enabling Generative AI on the Edge—
Hanna HajishirziUW/AI2KeynoteKeynote: Open Language Models (OLMo): Accelerating the Science of Language Modeling—
Ion StoicaUC BerkeleyKeynoteKeynote: Ray: A Distributed Framework for Heterogeneous Computing—
James BradburyAnthropicKeynoteKeynote Panel Discussion: Scaling & Benchmarking—
Jerry LiuLlamaIndexKeynoteKeynote: Building an Advanced Knowledge Assistant—
Kartikay KhandelwalMetaKeynoteKeynote: PyTorch Technical Deep Dive—
Kismat SinghIntelKeynoteSponsored Keynote: Enabling AI Everywhere with PyTorch and Intel—
Kush VarshneyIBMKeynoteKeynote Panel Discussion: Responsible AI—
Lisa DunlapUCB/LMSysKeynoteKeynote Panel Discussion: Scaling & Benchmarking—
Luca AntigaLightning AIKeynoteSponsored Keynote: The Lightning AI OSS Stack for Accelerating the AI Lifecycle—
Matt WhiteThe Linux FoundationKeynoteKeynote: Welcome & Opening Remarks—
Mengtao (Martin) YuanMetaKeynoteKeynote: PyTorch Technical Deep Dive—
Mudhakar SrivatsaIBMKeynoteSponsored Keynote: Optimizing AI Inference for Large Language Models—
Peng WuMetaKeynoteKeynote: PyTorch Technical Deep Dive—
PhD—KeynoteKeynote: Navigating the Architectural Timeline of LLMs—
Piotr BialeckiNVIDIAKeynoteKeynote: PyTorch Technical Deep Dive—
Rishi BommasaniStanford Center for Research on Foundation ModelsKeynoteKeynote Panel Discussion: Responsible AI—
Sara HookerCohereKeynoteKeynote Panel Discussion: Responsible AI—
Sebastian RaschkaLightning AIKeynoteKeynote: Navigating the Architectural Timeline of LLMs—
Taylor DolezalCloud Native Computing FoundationKeynoteSponsored Keynote: From Containers to Cognition: Conducting the AI Orchestra—
Tri DaoTogether AIKeynoteKeynote Panel Discussion: Scaling & Benchmarking—
Will ConstableMetaKeynoteKeynote: PyTorch Technical Deep Dive—
Aakanksha ChowdheryMetaPanelistPanel Discussion—
Adnan HoqueIBMPosterPoster Presentations—
Alban DesmaisonMetaLightning talkLightning Talk: A Whirlwind Tour of PyTorch Extension Points—
Alex SinIntelPosterPoster Presentations—
Alexis BaudronSonyLightning talkLightning Talk: Mobile Computational Photography with PyTorch: Low-Light Denoising—
Alexis ConneauOpenAIPanelistPanel Discussion—
Andrey TalmanMetaLightning talkLightning Talk: PyTorch Release Process—
Angela YiMetaLightning talkLightning Talk: What’s New in Export?—
Angela YiMetaPosterPoster Presentations—
Animesh JainMetaPosterPoster Presentations—
Antoni Viros i MartinIBMPosterPoster Presentations—
Avik ChaudhuriMetaLightning talkLightning Talk: What’s New in Export?—
Bin BaoMetaPosterPoster Presentations—
Blair BirdsellSurespan ConstructionPosterPoster Presentations—
Brian HirshMetaPosterPoster Presentations—
Catherine LeeMetaLightning talkLightning Talk: What's New for PyTorch Developer Infrastructure—
CEMAL BilginMetaLightning talkLightning Talk: LLMs on Edge with AI Accelerators—
Chen LaiMeteaLightning talkLightning Talk: LLMs on Edge with AI Accelerators—
Chien-Chin HuangMetaPosterPoster Presentations—
Chih-Chieh YangIBMPosterPoster Presentations—
Chirag PandyaMetaPosterPoster Presentations—
Dan FernandezChainguardLightning talkLightning Talk: Beyond Zero: Eliminating Vulnerabilities in PyTorch Container Images—
Daniel HanUnslothSpeakerHacks to Make LLM Training Faster—
Daniel HazizaMetaPosterPoster Presentations—
Diogo VenâncioUniversity of Lisbon | INESC-IDPosterPoster Presentations—
Eikan WangIntelPosterPoster Presentations—
Emma NingMicrosoftPosterPoster Presentations—
Eric YangGooglePosterPoster Presentations—
Evan SmothersMetaSpeakertorchtune: Easy and Accessible Finetuning in Native PyTorch—
Hailey SchoelkopfEleutherAIPanelistPanel Discussion—
Hansong ZhangMetaPosterPoster Presentations—
Hao WuGeorge Mason UniversityPosterPoster Presentations—
Hiroshi InoueIBMPosterPoster Presentations—
Horace HeMetaPosterPoster Presentations—
Horace HeMetaLightning talkLightning Talk: New Activation Checkpointing APIs in PyTorch—
Horace HeMetaLightning talkLightning Talk: FlexAttention - The Flexibility of PyTorch + The Performance of FlashAttention—
Howard HuangMetaLightning talkLightning Talk: Introduction to Torch.Distributed.Pipelining—
Huamin LiMetaPosterPoster Presentations—
Hyoyoung ChangPyTorchPosterPoster Presentations—
Iris ZhangMetaPosterPoster Presentations—
Jack ClaytonModularPosterPoster Presentations—
Jacques PienaarGooglePanelistDL Compiler Panel Discussion—
Jacques PienaarGoogleSpeaker[MLIR] Enabling Composition of Kernels and Compilers—
Jason AnselMetaSpeaker[HALIDE] A Halide Backend for TorchInductor—
Jason AnselMetaPanelistDL Compiler Panel Discussion—
Jeff DailyAMDLightning talkLightning Talk: AOTriton: Ahead of Time Triton Kernel Libraries on ROCm—
Jeffrey WanMetaLightning talkLightning Talk: New Activation Checkpointing APIs in PyTorch—
Jesse CaiMetaLightning talkLightning Talk: Sparsifying Vision Transformers with Minimal Accuracy Loss—
Jesse CaiMetaPosterPoster Presentations—
Joe SpisakReflection AISpeakerThe State of the Llama Ecosystem—
Joel SchlosserMetaPosterPoster Presentations—
Joshua LochnerHugging FacePosterPoster Presentations—
Junghwan ParkPyTorchKRPosterPoster Presentations—
KaiChao YOUTsinghua UniversityPosterPoster Presentations—
Kartikay KhandelwalMetaHostWelcome to the PyTorch Ecosystem for LLM Fine-tuning Mini Summit—
Ke WenMetaLightning talkLightning Talk: Introduction to Torch.Distributed.Pipelining—
Kimish PatelMetaLightning talkLightning Talk: LLMs on Edge with AI Accelerators—
Kshama PawarMicrosoftPosterPoster Presentations—
Laikh TewariNVIDIAPosterPoster Presentations—
Louie TsaiIntelPosterPoster Presentations—
Luca AntigaLightning AILightning talkLightning Talk: Understanding and Optimizing PyTorch Models with Thunder—
Lucas PasqualinPyTorchPosterPoster Presentations—
Manfei BaiGooglePosterPoster Presentations—
Michał SzołuchaNVIDIAPosterPoster Presentations—
Mikayla GawareckiMetaPosterPoster Presentations—
Mikhail ZolotukhinModularPanelistDL Compiler Panel Discussion—
Mikhail ZolotukhinModularSpeaker[MOJO] Lifting PT to New Heights with MAX and Mojo—
Mingfei MaIntelPosterPoster Presentations—
Na LiGooglePosterPoster Presentations—
Nick KreegerModularPosterPoster Presentations—
Nicolas HugMetaLightning talkLightning Talk: Implementing and Using Iterable Datasets: What Could Go Wrong?—
Oguz UlgenMetaPosterPoster Presentations—
Olivia LiuMetaLightning talkLightning Talk: On-Device Profiling and Debugging with ExecuTorch—
Omar SansevieroHugging FaceLightning talkLightning Talk: Distributing a Million Open Models in the Wild: Lessons Learned from the Hugging Face Hub—
Pareena VermaArmLightning talkLightning Talk: Empowering Developers: Tools and Resources for Running Generative AI on Arm CPUs—
Patrick SmythChainguardLightning talkLightning Talk: Beyond Zero: Eliminating Vulnerabilities in PyTorch Container Images—
Pauline ShoGooglePosterPoster Presentations—
Peng WuMetaPanelistDL Compiler Panel Discussion—
Phil TilletOpenAIPanelistDL Compiler Panel Discussion—
Phil TilletOpenAISpeaker[TRITON] Maximizing Kernel Development Productivity Under Performance Constraints—
Pragaash PonnusamyTogether AISpeakerTogether Goes Brrr: Threading Research & Production with Torch Compile—
Qidong ZhaoNorth Carolina State UniversityPosterPoster Presentations—
Richard ZouMetaLightning talkLightning Talk: Extending PyTorch with Custom Python/C++/CUDA Operators—
Rostan TABETNVIDIAPosterPoster Presentations—
Roy AllelaAmazon Web ServicesPosterPoster Presentations—
Saaketh NarayanDatabricksLightning talkLightning Talk: Fast, Scalable Distributed Training with StreamingDataset—
Sahan PaliskaraMetaLightning talkLightning Talk: What's New for PyTorch Developer Infrastructure—
Shailvi WakhluShailvi Ventures LLCLightning talkLightning Talk: Debiasing the Data Lifecycle—
Sheng QinMetaPosterPoster Presentations—
Sherlock HuangMetaPosterPoster Presentations—
Sijia ChenMetaPosterPoster Presentations—
Sreen TallamMetaPosterPoster Presentations—
Srishti HegdeChainguardLightning talkLightning Talk: Beyond Zero: Eliminating Vulnerabilities in PyTorch Container Images—
Sunita NadampalliAmazon Web ServicesLightning talkLightning Talk: Optimized PyTorch Inference on aarch64 Linux CPUs—
Susi GentschUniversity of BonnLightning talkLightning Talk: HieroGlyph2Text: A PyTorch-Powered Pipeline for Automated Egyptian Hieroglyph Translation from Image—
Syed AhmedNVIDIALightning talkLightning Talk: Making the Most of Heterogeneous Memory Capacity Using PyTorch—
Tabari AlexanderIBMPosterPoster Presentations—
Tianqi ChenCMU and NVIDIASpeaker[TVM] Universally Deploy Large-language Models via ML Compilation—
Tianqi ChenCMU and NVIDIAPanelistDL Compiler Panel Discussion—
Tianyu LiuMetaPosterPoster Presentations—
Tim DettmersAi2 & Carnegie Mellon UniversityPanelistPanel Discussion—
Titus Von KoellerHugging FacePosterPoster Presentations—
Tristan RiceMetaPosterPoster Presentations—
Tristan Webbd-MatrixLightning talkLightning Talk: d-Matrix LLM Compression Flow Based on Torch.Fx: Simplifying PTQ/QAT—
Tugsbayasgalan ManlaibaatarMetaLightning talkLightning Talk: What’s New in Export?—
Varun Puri—Lightning talkLightning Talk: On-Device Profiling and Debugging with ExecuTorch—
Vasiliy KuznetsovMetaLightning talkLightning Talk: Low Precision Dtypes in PyTorch—
Vineeth GuttaUniversity of DelawareLightning talkLightning Talk: In-Transit Machine Learning Using PyTorch on Frontier Exascale System—
Wei SunMetaPosterPoster Presentations—
William WenMetaPosterPoster Presentations—
Wing LianAxolotl AISpeakerThe Challenges of Building an Opinionated Open Source LLM Framework—
Yanbo LiangMetaPosterPoster Presentations—
Yanbo LiangMetaLightning talkLightning Talk: FlexAttention - The Flexibility of PyTorch + The Performance of FlashAttention—
Yeounoh ChungGoogleLightning talkLightning Talk: PyTorch/XLA Auto-Sharding—
Yidi WUMetaLightning talkLightning Talk: What’s New in Export?—
Yu Chin Fabian LimIBMPosterPoster Presentations—
Zesheng ZongHuaweiLightning talkLightning Talk: Building and Supporting the Chinese PyTorch Community: Resources, Tutorials, and Engagement—
Zhongqi MiaoMicrosoftLightning talkCANCELED: Lightning Talk: PyTorch-Wildlife: A Collaborative Deep Learning Framework for Conservation—
Zifei Xud-MatrixLightning talkLightning Talk: d-Matrix LLM Compression Flow Based on Torch.Fx: Simplifying PTQ/QAT—

Sources