Keynote: Welcome & Opening Remarks - Matt White, Executive Director, PyTorch Foundation Keynote: PyTorch Technical Deep Dive - P. Bialecki, P. Wu, W. Constable, K. Khandelwal & M. Yuan Keynote: Open Language Models (OLMo): Accelerating the Science of Language Modeling Hanna Hajishirzi Keynote: Enabling Generative AI on the Edge - Cormac Brick, Principal Engineer, Google Sponsored Keynote: The Lightning AI OSS Stack for Accelerating the AI Lifecycle - Luca Antiga Sponsored Keynote: Enabling AI Everywhere with PyTorch and Intel - Kismat Singh, Intel Sponsored Keynote: From Containers to Cognition: Conducting the AI Orchestra - Taylor Dolezal Keynote Panel Discussion: Responsible AI - K. Rooney, K. Varshney, S. Hooker, A. Madry, R. Bommasani Keynote: Welcome Back & Opening Remarks Keynote: Why You Should Think Twice Before Paying for an Evaluation Tool - Chip Huyen, Voltron Data Keynote: Navigating the Architectural Timeline of LLMs - Sebastian Raschka, Lightning AI Keynote: Building an Advanced Knowledge Assistant - Jerry Liu, Co-Founder & CEO, LlamaIndex Keynote: Ray: A Distributed Framework for Heterogeneous Computing - Ion Stoica, UC Berkeley Keynote: Community Awards Sponsored Keynote: Accelerating AI: How AMD and PyTorch Drive Innovation with Sea... Anush Elangovan Sponsored Keynote: Optimizing AI Inference for Large Language Models - Mudhakar Srivatsa, IBM Keynote Panel Discussion: Scaling & Benchmarking Unlocking the Enigma: Crafting Unbiased, Transparent, and Explainable Large Languag... Rashmi Nagpal Building PyTorch Computer Vision Algorithms for 100 Skin Shades - Emmanuel Acheampong, roboMUA Lightning Talk: Fast, Scalable Distributed Training with StreamingDataset - Saaketh Narayan Implementing a Custom Torch.Compile Backend - A Case Study - Maanav Dalal & Yulong Wang, Microsoft Intel GPU in Upstream PyTorch: Expanding GPU Choices and Enhancing Back... Eikan Wang & Min Jean Cho Understanding the LLM Inference Workload - Mark Moyou, NVIDIA Slaying OOMs - Mark Saroufim & Jane Xu, Meta Torchtitan: Large-Scale LLM Training Using Native PyTorch 3D Parallel... Wanchao Liang & Linsong Chu vLLM: Easy, Fast, and Cheap LLM Serving for Everyone - Woosuk Kwon & Xiaoxuan Liu, UC Berkeley Lightning Talk: AOTriton: Ahead of Time Triton Kernel Libraries on ROCm - Jeff Daily, AMD Lightning Talk: Optimized PyTorch Inference on aarch64 Linux CPUs - Sunita Nadampalli, Amazon (AWS) Lightning Talk: Empowering Developers: Tools and Resources for Running Generative A... Pareena Verma The Rise of `Transformers` in the Growing PyTorch Ecosystem - Arthur Zucker, Hugging Face Torch.Compile for Autograd, DDP and FSDP - Will Feng , Chien-Chin Huang & Simon Fan, Meta Lightning Talk: PyTorch Release Process - Andrey Talman, Meta Lightning Talk: What's New for PyTorch Developer Infrastructure - Sahan Paliskara & Catherine Lee Data-Dependent Shapes in PT2 - Edward Yang, Meta Lightning Talk: Making the Most of Heterogeneous Memory Capacity Using PyTorch - Syed Ahmed, NVIDIA Lightning Talk: FlexAttention - The Flexibility of PyTorch + The Performa... Yanbo Liang & Horace He Lightning Talk: New Activation Checkpointing APIs in PyTorch - Jeffrey Wan & Horace He, Meta Sponsored Session: Torchchat: A Showcase of PyTorch LLM Ubiquity - Jack Khuu & Jesse White, Meta Lightning Talk: LLMs on Edge with AI Accelerators - Chen Lai, Kimish Patel & Cemal Bilgin, Meta Pushing the Performance Envelope: An Optimization Study for 3... Suvaditya Mukherjee & Shireen Chand A Distributed Stateful Dataloader for Large-Scale Pretraining - Davis Wertheimer & Linsong Chu Lightning Talk: In-Transit Machine Learning Using PyTorch on Frontier Exascale System- Vineeth Gutta Lightning Talk: On-Device Profiling and Debugging with ExecuTorch - Olivia Liu & Vaun Puri, Meta Lightning Talk: Introduction to Torch.Distributed.Pipelining - Howard Huang & Ke Wen, Meta Lightning Talk: PyTorch/XLA Auto-Sharding - Yeounoh Chung, Google Lightning Talk: Sparsifying Vision Transformers with Minimal Accuracy Loss - Jesse Cai, Meta Lightning Talk: Beyond Zero: Eliminating Vulnerabili... Patrick Smyth, Dan Fernandez & Srishti Hegde Building Scientific Computing Infrastructure Software with the PyTorch Ecosystem - Bharath Ramsundar Meta Llama 3 and the Future of Responsible AI Development - Spencer Whitman & Vincent Gonguet, Meta DL Compiler Panel Discussion - P. Tillet, J. Ansel, J. Pienaar, T. Chen, M. Zolotukhin, P. Wu Keynote: Welcome & Opening Remarks - Matt White, Executive Director, PyTorch Foundation Keynote: PyTorch Technical Deep Dive - P. Bialecki, P. Wu, W. Constable, K. Khandelwal & M. Yuan Keynote: Open Language Models (OLMo): Accelerating the Science of Language Modeling Hanna Hajishirzi Keynote: Enabling Generative AI on the Edge - Cormac Brick, Principal Engineer, Google Sponsored Keynote: The Lightning AI OSS Stack for Accelerating the AI Lifecycle - Luca Antiga Sponsored Keynote: Enabling AI Everywhere with PyTorch and Intel - Kismat Singh, Intel Sponsored Keynote: From Containers to Cognition: Conducting the AI Orchestra - Taylor Dolezal Keynote Panel Discussion: Responsible AI - K. Rooney, K. Varshney, S. Hooker, A. Madry, R. Bommasani Keynote: Welcome Back & Opening Remarks Keynote: Why You Should Think Twice Before Paying for an Evaluation Tool - Chip Huyen, Voltron Data Keynote: Navigating the Architectural Timeline of LLMs - Sebastian Raschka, Lightning AI Keynote: Building an Advanced Knowledge Assistant - Jerry Liu, Co-Founder & CEO, LlamaIndex Keynote: Ray: A Distributed Framework for Heterogeneous Computing - Ion Stoica, UC Berkeley Keynote: Community Awards Sponsored Keynote: Accelerating AI: How AMD and PyTorch Drive Innovation with Sea... Anush Elangovan Sponsored Keynote: Optimizing AI Inference for Large Language Models - Mudhakar Srivatsa, IBM Keynote Panel Discussion: Scaling & Benchmarking Unlocking the Enigma: Crafting Unbiased, Transparent, and Explainable Large Languag... Rashmi Nagpal Building PyTorch Computer Vision Algorithms for 100 Skin Shades - Emmanuel Acheampong, roboMUA Lightning Talk: Fast, Scalable Distributed Training with StreamingDataset - Saaketh Narayan Implementing a Custom Torch.Compile Backend - A Case Study - Maanav Dalal & Yulong Wang, Microsoft Intel GPU in Upstream PyTorch: Expanding GPU Choices and Enhancing Back... Eikan Wang & Min Jean Cho Understanding the LLM Inference Workload - Mark Moyou, NVIDIA Slaying OOMs - Mark Saroufim & Jane Xu, Meta Torchtitan: Large-Scale LLM Training Using Native PyTorch 3D Parallel... Wanchao Liang & Linsong Chu vLLM: Easy, Fast, and Cheap LLM Serving for Everyone - Woosuk Kwon & Xiaoxuan Liu, UC Berkeley Lightning Talk: AOTriton: Ahead of Time Triton Kernel Libraries on ROCm - Jeff Daily, AMD Lightning Talk: Optimized PyTorch Inference on aarch64 Linux CPUs - Sunita Nadampalli, Amazon (AWS) Lightning Talk: Empowering Developers: Tools and Resources for Running Generative A... Pareena Verma The Rise of `Transformers` in the Growing PyTorch Ecosystem - Arthur Zucker, Hugging Face Torch.Compile for Autograd, DDP and FSDP - Will Feng , Chien-Chin Huang & Simon Fan, Meta Lightning Talk: PyTorch Release Process - Andrey Talman, Meta Lightning Talk: What's New for PyTorch Developer Infrastructure - Sahan Paliskara & Catherine Lee Data-Dependent Shapes in PT2 - Edward Yang, Meta Lightning Talk: Making the Most of Heterogeneous Memory Capacity Using PyTorch - Syed Ahmed, NVIDIA Lightning Talk: FlexAttention - The Flexibility of PyTorch + The Performa... Yanbo Liang & Horace He Lightning Talk: New Activation Checkpointing APIs in PyTorch - Jeffrey Wan & Horace He, Meta Sponsored Session: Torchchat: A Showcase of PyTorch LLM Ubiquity - Jack Khuu & Jesse White, Meta