Lightning Talk: State of PyTorch - Alban Desmaison, Meta - Speakers: Alban Desmaison Lightning Talk: TorchFix - a Linter for PyTorch-Using Code with Autofix Support - Sergii Dymchenko What's New for PyTorch Developer Infrastructure - Eli Uriegas & Omkar Salpekar Lightning Talk: Enhancements Made to MPS Backend in PyTorch for Applications Running... - Kulin Seth PyTorch Korea User Group: The Beginning, Present, and Future - Junghwan Park Lightning Talk: Triton Compiler - Thomas Raoux, OpenAI Lightning Talk: Harnessing NVIDIA Tensor Cores: An Exploration of CUTLASS & OpenAI..- Matthew Nicely Lightning Talk: PyTorch 2.0 on the ROCm Platform - Douglas Lehr, AMD Lightning Talk: Accelerated Inference in PyTorch 2.X with Torch...- George Stefanakis & Dheeraj Peri Lightning Talk: Large-Scale Distributed Training with Dynamo and... - Yeounoh Chung & Jiewen Tan Lightning Talk: Streamlining Model Export with the New ONNX Exporter - Maanav Dalal & Aaron Bockover Lightning Talk: Efficient Inference at the Edge: Performance You Need at the Lowest... - Felix Baum Lightning Talk: Accelerating LLM Training on Cerebras Wafer-Scale... - Mark; Natalia; Behzad & Emad Lightning Talk: Accelerating PyTorch Performance with OpenVINO - Yamini, Devang & Mustafa PyTorch Edge: Developer Journey for Deploying AI Models Onto Edge Devices - Mengwei Liu & Angela Yi PyTorch Edge: Vendor Integration Journey for Compilers and Backends - Kimish Patel, & Chen Lai Lightning Talk: The Fastest Path to Production: PyTorch Inference in Python - Mark Saroufim, Meta Lightning Talk: Exploring PiPPY, Tensor Parallel and Torchserve for Large... - Hamid Shojanazeri Lightning Talk: Standardizing CPU Benchmarking with TorchBench for PyTorch... - Xu Zhao & Mingfei Ma Lightning Talk: Profiling and Memory Debugging Tools for Distributed ML Workloads on GPUs- Aaron Shi Lightning Talk: Building Intermediate Logging for PyTorch - Kunal Bhalla, Meta Lightning Talk: PT2 Export - A Sound Full Graph Capture Mechanism for PyTorch - Avik Chaudhuri, Meta Llama V2 in Azure AI for Finetuning, Evaluation and Deployment from the Model Catalog - Swati Gharse Cost Effectively Deploy Thousands of Fine Tuned Gen AI Models Like... - Saurabh Trikande, Li Ning The Evolving Landscape of Dataloading - Laurence Rouesnel, Meta Lightning Talk: Adding Backends for TorchInductor: Case Study with Intel GPU - Eikan Wang, Intel Keynote: Welcome & Opening Remarks - Ibrahim Haddad, Executive Director, PyTorch Foundation Keynote: How PyTorch Became the Foundation of the AI Revolution - Joe Spisak, Product Director, Meta Keynote: PyTorch 2.1 Technical Deep Dive - Mario, Mark, Mergen, Joe, Peng, Will, Yanan What's New for Dynamic Shapes in PyTorch 2.1 - Edward Yang, Meta Lightning Talk: CUDAGraph in a Partial Graph World - Elias Ellison, Meta Lightning Talk: AOTInductor: Ahead-of-Time Compilation for PT2 Exported Models - Bin Bao, Meta Lightning Talk: Accelerating Inference on CPU with Torch.Compile - Jiong Gong, Intel Lightning Talk: Lessons from Using Pytorch 2.0 Compile in IBM's Watsonx.AI Inference - Antoni Martin Keynote: Welcome & Opening Remarks - Joe Spisak, Product Director, Meta Keynote: Refik Anadol Studio: Rainforest AI Research - Christian Burke & Refik Anadol Keynote: AMD & PyTorch: A Powerful Combination for Generative AI - Negin Oliver Keynote: Building an Interoperable Ecosystem for Generative AI - Stella Biderman Keynote: The Promise of PyTorch as a General-Purpose Array-Oriented Computational..- Travis Oliphant Keynote: How to Leverage PyTorch to Scale AI Training and Inferencing - Raghu Ganti Keynote: The Value of Open Source for the Enterprise - Priya Nagpurkar Keynote: Intel and PyTorch: Enabling AI Everywhere with Ubiquitous Hardware and Open... - Fan Zhao Keynote: PyTorch Lightning: Powering the GenAI Revolution from Research to the... - William Falcon Keynote: The Llama Ecosystem: Past, Present and Future - Joe Spisak, Product Director, Meta Accelerating Explorations in Vision and Multimodal AI Using Pytorch...- Nicolas, Philip, Evan & Peng Getting Started with Pytorch 2.0 and Hugging Face Transformers - Philipp Schmid, Hugging Face Training a LLaMA in your Backyard: Fine-tuning Very Large... - Sourab Mangrulkar & Younes Belkada Distributed Checkpoint - Iris Zhang & Chien-Chin Huang, Meta Composable Distributed PT2(D) - Wanchao Liang, Meta Platforms, Inc. Lessons Learned in WatsonX Training: Scaling Cloud-Native...- Davis Wertheimer & Supriyo Chakraborty Lightning Talk: State of PyTorch - Alban Desmaison, Meta - Speakers: Alban Desmaison Lightning Talk: TorchFix - a Linter for PyTorch-Using Code with Autofix Support - Sergii Dymchenko What's New for PyTorch Developer Infrastructure - Eli Uriegas & Omkar Salpekar Lightning Talk: Enhancements Made to MPS Backend in PyTorch for Applications Running... - Kulin Seth PyTorch Korea User Group: The Beginning, Present, and Future - Junghwan Park Lightning Talk: Triton Compiler - Thomas Raoux, OpenAI Lightning Talk: Harnessing NVIDIA Tensor Cores: An Exploration of CUTLASS & OpenAI..- Matthew Nicely Lightning Talk: PyTorch 2.0 on the ROCm Platform - Douglas Lehr, AMD Lightning Talk: Accelerated Inference in PyTorch 2.X with Torch...- George Stefanakis & Dheeraj Peri Lightning Talk: Large-Scale Distributed Training with Dynamo and... - Yeounoh Chung & Jiewen Tan Lightning Talk: Streamlining Model Export with the New ONNX Exporter - Maanav Dalal & Aaron Bockover Lightning Talk: Efficient Inference at the Edge: Performance You Need at the Lowest... - Felix Baum Lightning Talk: Accelerating LLM Training on Cerebras Wafer-Scale... - Mark; Natalia; Behzad & Emad Lightning Talk: Accelerating PyTorch Performance with OpenVINO - Yamini, Devang & Mustafa PyTorch Edge: Developer Journey for Deploying AI Models Onto Edge Devices - Mengwei Liu & Angela Yi PyTorch Edge: Vendor Integration Journey for Compilers and Backends - Kimish Patel, & Chen Lai Lightning Talk: The Fastest Path to Production: PyTorch Inference in Python - Mark Saroufim, Meta Lightning Talk: Exploring PiPPY, Tensor Parallel and Torchserve for Large... - Hamid Shojanazeri