11:20am • Meta Llama 3 and the Future of Responsible AI Development - Helen Suk, Meta
11:50am • Building Scientific Computing Infrastructure Software with the PyTorch Ecosystem - Bharath Ramsundar, Deep Forest Sciences
12:20pm • Lightning Talk: Debiasing the Data Lifecycle - Shailvi Wakhlu, Shailvi Ventures LLC
12:30pm • Lightning Talk: Artificial Pervasiveness. Introducing the Large Ethics Model in AI Education - Aldo Pisano, University of Calabria
1:55pm • The Impact and Challenges of Open Source Generative Datasets and Models - Aaron Gokaslan, Cornell University
2:25pm • Lightning Talk: Beyond Zero: Eliminating Vulnerabilities in PyTorch Container Images - Patrick Smyth, Dan Fernandez & Srishti Hegde, Chainguard
2:35pm • Lightning Talk: Open Source Isn't Insecure - but Your Supply Chain Could Be - Dr. Kathleen Goeschel, Red Hat
2:55pm • A Distributed Stateful Dataloader for Large-Scale Pretraining - Davis Wertheimer, IBM & Linsong Chu, IBM Research
4:30pm • Lightning Talk: Controllable Human Body Animation for Synthetic Data Generation in Action Recognition Tasks - Matyas Bohacek, Stanford University & Vaclav Knapp, Smichovska stredni prumyslova skola a gymnazium
4:40pm • Lightning Talk: PyTorch-Wildlife: A Collaborative Deep Learning Framework for Conservation - Zhongqi Miao, Microsoft
5:00pm • Pushing the Performance Envelope : an Optimization Study for 3D Generative Modelling with PyTorch - Suvaditya Mukherjee & Shireen Chand, University of Southern California
11:25am • Lightning Talk: On-Device Profiling and Debugging with ExecuTorch - Olivia Liu & Vaun Puri, Meta
11:35am • Lightning Talk: LLMs on Edge with AI Accelerators - Chen Lai & Cemal Bilgin, Meta
12:25pm • Lightning Talk: New Activation Checkpointing APIs in PyTorch - Jeffrey Wan & Horace He, Meta
12:35pm • Lightning Talk: FlexAttention - the Flexibility of PyTorch + the Performance of FlashAttention - Yanbo Liang, Meta
2:00pm • Data-Dependent Shapes in PT2 - Edward Yang, Meta
2:30pm • Torch.Compile for Autograd, DDP and FSDP - Will Feng & Chien-Chin Huang & Simon Fan, Meta
3:00pm • Lightning Talk: What's New for PyTorch Developer Infrastructure - Sahan Paliskara & Catherine Lee, Meta
3:10pm • Lightning Talk: PyTorch Release Process - Andrey Talman, Meta Inc.
4:05pm • Lightning Talk: AOTriton: Ahead of Time Triton Kernel Libraries on ROCm - Joseph Groenenboom, AMD
4:15pm • Lightning Talk: Making the Most of Heterogeneous Memory Capacity Using PyTorch - Syed Ahmed, NVIDIA Corporation
4:35pm • Lightning Talk: Understanding and Optimizing PyTorch Models with Thunder - Thomas Viehmann & Luca Antiga, Lightning AI
4:45pm • Lightning Talk: D-Matrix LLM Compression Flow Based on Torch.Fx: Simplifying PTQ/QAT - Zifei Xu & Tristan Webb, d-Matrix Corporation
5:05pm • Lightning Talk: PyTorch/XLA Auto-Sharding - Yeounoh Chung, Google
5:15pm • Lightning Talk: Introduction to Torch.Distributed.Pipelining - Howard Huang & Ke Wen, Meta
11:25am • The Rise of `Transformers` in the Growing PyTorch Ecosystem - Arthur Zucker, Hugging Face
11:55am • Training MoEs at Scale with PyTorch - Mihir Patel, Databricks
12:25pm • Lightning Talk: Empowering Developers: Tools and Resources for Running Generative AI on Arm CPUs - Pareena Verma, Arm
12:35pm • Lightning Talk: Optimized PyTorch Inference on Aarch64 Linux CPUs - Sunita Nadampalli, Amazon (AWS)
2:00pm • VLLM: Easy, Fast, and Cheap LLM Serving for Everyone - Woosuk Kwon, UC Berkeley & Xiaoxuan Liu, UCB
2:30pm • Torchtitan: Large-Scale LLM Training Using Native PyTorch 3D Parallelism - Wanchao Liang, Meta
3:00pm • Slaying OOMs - Mark Saroufim & Jane Xu, Meta
4:05pm • Intel GPU in Upstream PyTorch: Expanding GPU Choices and Enhancing Backend Flexibility - Eikan Wang, Intel
4:35pm • Understanding the LLM Inference Workload - Mark Moyou, NVIDIA
5:05pm • Implementing a Custom Torch.Compile Backend - a Case Study - Maanav Dalal & Xavier Dupré, Microsoft
11:25am • Lightning Talk: Implementing and Using Iterable Datasets: What Could Go Wrong? - Nicolas Hug, Meta
11:35am • Lightning Talk: Fast, Scalable Distributed Training with StreamingDataset - Saaketh Narayan, Databricks
11:55am • Lightning Talk: Building and Supporting the Chinese PyTorch Community: Resources, Tutorials, and Engagement - Zesheng Zong, Huawei
12:05pm • Lightning Talk: Distributing a Million Open Models in the Wild: Lessons Learned from the Hugging Face Hub - Omar Sanseviero, Hugging Face
2:00pm • Building PyTorch Computer Vision Algorithms for 100 Skin Shades - Emmanuel Acheampong, roboMUA
2:30pm • Blobs to Clips: Efficient End-to-End Video Data Loading - Andrew Ho & Ahmad Sharif & Gokul Gunasekaran, Meta; Kaiyue Yang, Meta Platforms, Inc
4:05pm • Unlocking the Enigma: Crafting Unbiased, Transparent, and Explainable Large Language Models - Rashmi Nagpal, Patchstack
5:05pm • The Ethical Implications of AI and the Environment: A Focus on Water - Amber Hasan, Ethical Tech AI & Senegal Tuklor Williams, Broken Pencil Pictures llc