10:45am • Lightning Talk: State of PyTorch - Alban Desmaison, Meta
11:00am • Lightning Talk: TorchFix - a Linter for PyTorch-Using Code with Autofix Support - Sergii Dymchenko, Meta
11:15am • What's New for PyTorch Developer Infrastructure - Eli Uriegas & Omkar Salpekar, Meta
11:45am • PyTorch Korea User Group: The Beginning, Present, and Future - Junghwan Park, PyTorch Korea User Group
3:10pm • Lightning Talk: Triton Compiler - Thomas Raoux, OpenAI
3:25pm • Lightning Talk: Harnessing NVIDIA Tensor Cores: An Exploration of CUTLASS & OpenAI Triton - Matthew Nicely US, NVIDIA
3:40pm • Lightning Talk: PyTorch 2.0 on the ROCm Platform - Douglas Lehr, AMD
3:55pm • Lightning Talk: Enhancements Made to MPS Backend in PyTorch for Applications Running on Mac Platforms - Kulin Seth, Apple
4:10pm • Lightning Talk: Adding Backends for TorchInductor: Case Study with Intel GPU - Eikan Wang, Intel
4:25pm • Lightning Talk: Accelerated Inference in PyTorch 2.X with Torch-TensorRT - George Stefanakis & Dheeraj Peri, NVIDIA
4:55pm • Lightning Talk: Large-Scale Distributed Training with Dynamo and PyTorch/XLA SPMD - Yeounoh Chung & Jiewen Tan, Google
5:10pm • Lightning Talk: Streamlining Model Export with the New ONNX Exporter - Maanav Dalal & Aaron Bockover, Microsoft
5:25pm • Lightning Talk: Efficient Inference at the Edge: Performance You Need at the Lowest Power You Deserve - Felix Baum, Qualcomm
5:40pm • Lightning Talk: Accelerating LLM Training on Cerebras Wafer-Scale Cluster - Mark Browning; Natalia Vassilieva; Behzad Abghari & Emad Barsoum, Cerebras
5:55pm • Lightning Talk: Accelerating PyTorch Performance with OpenVINO - Yamini Nimmagadda, Devang Aggarwal & Mustafa Cavus, Intel
6:10pm • Lightning Talk: Orchestrating Machine Learning on Edge Devices with PyTorch and WebAssembly - Rishit Dagli, University of Toronto (Vector Institute and DGP Lab), Civo & Shivay Lamba, meilisearch
10:45am • Introducing ExecuTorch from PyTorch Edge: On-Device AI Stack and Ecosystem, and Our Unique Differentiators - Mergen Nachin & Orion Reblitz-Richardson, Meta
11:15am • PyTorch Edge: Developer Journey for Deploying AI Models Onto Edge Devices - Mengwei Liu & Angela Yi, Meta
11:45am • PyTorch Edge: Vendor Integration Journey for Compilers and Backends - Kimish Patel, & Chen Lai, Meta Platforms
3:10pm • Lightning Talk: The Fastest Path to Production: PyTorch Inference in Python - Mark Saroufim, Meta
3:25pm • Lightning Talk: Exploring PiPPY, Tensor Parallel and Torchserve for Large Model Inference - Hamid Shojanazeri, Meta
3:40pm • Lightning Talk: Standardizing CPU Benchmarking with TorchBench for PyTorch Community - Xu Zhao, Meta & Mingfei Ma, Intel
3:55pm • Lightning Talk: Profiling and Memory Debugging Tools for Distributed ML Workloads on GPUs - Aaron Shi, Meta
4:10pm • Lightning Talk: Building Intermediate Logging for PyTorch - Kunal Bhalla, Meta
4:25pm • Lightning Talk: PT2 Export - A Sound Full Graph Capture Mechanism for PyTorch - Avik Chaudhuri, Meta
4:55pm • Llama V2 in Azure AI for Finetuning, Evaluation and Deployment from the Model Catalog - Swati Gharse, Microsoft
5:25pm • The Evolving Landscape of Dataloading - Laurence Rouesnel, Meta
5:55pm • Cost Effectively Deploy Thousands of Fine Tuned Gen AI Models Like Llama Using TorchServe on AWS - Saurabh Trikande, Amazon Web Services (AWS); Li Ning, Amazon
9:00am • Keynote: Welcome & Opening Remarks - Ibrahim Haddad, Executive Director, PyTorch Foundation
9:05am • Keynote: How PyTorch Became the Foundation of the AI Revolution - Joe Spisak, Product Director, Meta
9:15am • Keynote: PyTorch 2.1 Technical Deep Dive
10:45am • What's New for Dynamic Shapes in PyTorch 2.1 - Edward Yang, Meta
11:15am • Lightning Talk: CUDAGraph in a Partial Graph World - Elias Ellison, Meta
11:30am • Lightning Talk: AOTInductor: Ahead-of-Time Compilation for PT2 Exported Models - Bin Bao, Meta
11:45am • Lightning Talk: Accelerating Inference on CPU with Torch.Compile - Jiong Gong, Intel
12:00pm • Lightning Talk: Lessons from Using Pytorch 2.0 Compile in IBM's Watsonx.AI Inference - Antoni Viros i Martin, IBM Research
1:10pm • Keynote: Welcome & Opening Remarks - Joe Spisak, Product Director, Meta
1:25pm • Keynote: Refik Anadol Studio: Rainforest AI Research - Christian Burke, Lead Data Scientist & Refik Anadol, Media Artist & Director, Refik Anadol Studio
1:40pm • Keynote: AMD & PyTorch: A Powerful Combination for Generative AI - Negin Oliver, Sr. Director, Data Center GPU & Accelerated Processing, AMD
1:45pm • Keynote: Building an Interoperable Ecosystem for Generative AI - Stella Biderman, Lead Scientist at Booz Allen Hamilton & Executive Director, EleutherAI
2:00pm • Keynote: The Promise of PyTorch as a General-Purpose Array-Oriented Computational Backend - Travis Oliphant, Founder & CEO, Quansight
2:10pm • Keynote: How to Leverage PyTorch to Scale AI Training and Inferencing - Raghu Ganti, Principal Research Scientist, IBM Research
2:25pm • Keynote: The Value of Open Source for the Enterprise - Priya Nagpurkar, Vice President, Hybrid Cloud Platform and Developer Productivity, IBM Research
2:30pm • Keynote: Intel and PyTorch: Enabling AI Everywhere with Ubiquitous Hardware and Open Software - Fan Zhao, Senior Director, Deep Learning Frameworks and Technology, Intel
2:35pm • Keynote: PyTorch Lightning: Powering the GenAI Revolution from Research to the Enterprise - William Falcon, Founder and CEO, Lightning AI
2:45pm • Keynote: The Llama Ecosystem: Past, Present and Future - Joe Spisak, Product Director, Meta
3:10pm • Accelerating Explorations in Vision and Multimodal AI Using Pytorch Libraries - Nicolas Hug, Philip Bontrager, Evan Smothers & Peng Chen, Meta
3:40pm • Getting Started with Pytorch 2.0 and Hugging Face Transformers - Philipp Schmid, Hugging Face
4:10pm • Training a LLaMA in your Backyard: fFne-tuning Very Large Models on Consumer Hardware - Sourab Mangrulkar & Younes Belkada, Hugging Face
4:55pm • Distributed Checkpoint - Iris Zhang & Chien-Chin Huang, Meta
5:25pm • Composable Distributed PT2(D) - Wanchao Liang, Meta Platforms, Inc.
5:55pm • Lessons Learned in WatsonX Training: Scaling Cloud-Native PyTorch FSDP to 20B Parameters - Davis Wertheimer & Supriyo Chakraborty, IBM
8:00am • Women and Non-Binary in PyTorch Breakfast with Quiana Berry, Red Hat
10:45am • Lightning Talk: Tensor Query Processing - Matteo Interlandi, Microsoft
11:00am • Lightning Talk: Energy-Efficient Deep Learning with PyTorch and Zeus - Jae-Won Chung, University of Michigan
11:15am • Lightning Talk: Tensor and 2D Parallelism - Rodrigo Kumpera & Junjie Wang, Meta
11:30am • Lightning Talk: Seismic Data to Subsurface Models with OpenFWI - Benjamin Consolvo, Intel
11:45am • LightningTalk: MultiRay: An Accelerated Embedding Service for Content Understanding - Michael Gschwind, Meta
12:00pm • Lightning Talk: Uplink Interference Optimizer, How to Optimize a Cellular Network in a Single Shot with GNNs - Oscar Llorente Gonzalez, Ericsson
3:10pm • Accelerating Generative AI - Christian Puhrsch & Horace He, Meta
3:40pm • Lightning Talk: TorchRL - RLHF Support - Vincent Moens, Meta
3:55pm • Lightning Talk: Diffusers: Bringing Cutting-Edge Diffusion Models to the Masses - Lysandre Debut, Hugging Face
4:10pm • Into Generative AI with PyTorch Lightning 2.0 - Luca Antiga & Carlos Mocholí, Lightning AI
4:55pm • TorchBench: Guarding the Performance of the PyTorch Ecosystem with Continuous Benchmarking - Xu Zhao, Meta
5:25pm • Lightning Talk: Simulating Quantum Systems with PyTorch - Pierre Guilmin, Alice & Bob
5:40pm • Lightning Talk: A Novel Domain Generalization Technique for Medical Imaging Using PyTorch - Dinkar Juyal, PathAI
5:55pm • Lightning Talk: Leveraging PyTorch 2.0 for Bias Reduction in AI - Christina Zhu, Visier
6:10pm • Lightning Talk: Dinosaur Bone Hunt - Bob Chesebrough, Intel
