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10:50am • Lightning Talk: d-Matrix LLM Compression Flow Based on Torch.Fx: Simplifying PTQ/QAT - Zifei Xu & Tristan Webb, d-Matrix Corporation
11:05am • Lightning Talk: LLMs on Edge with AI Accelerators - Chen Lai, Kimish Patel & Cemal Bilgin, Meta
11:20am • Sponsored Session: Torchchat: A Showcase of PyTorch LLM Ubiquity - Jack Khuu & Jesse White, Meta
11:50am • Lightning Talk: New Activation Checkpointing APIs in PyTorch - Jeffrey Wan & Horace He, Meta
12:00pm • Lightning Talk: FlexAttention - The Flexibility of PyTorch + The Performance of FlashAttention - Yanbo Liang & Horace He, Meta
12:10pm • Lightning Talk: Making the Most of Heterogeneous Memory Capacity Using PyTorch - Syed Ahmed, NVIDIA Corporation
2:15pm • Data-Dependent Shapes in PT2 - Edward Yang, Meta
2:45pm • Lightning Talk: What's New for PyTorch Developer Infrastructure - Sahan Paliskara & Catherine Lee, Meta
3:00pm • Lightning Talk: PyTorch Release Process - Andrey Talman, Meta
3:15pm • Torch.Compile for Autograd, DDP and FSDP - Will Feng , Chien-Chin Huang & Simon Fan, Meta
4:05pm • Lightning Talk: Debiasing the Data Lifecycle - Shailvi Wakhlu, Shailvi Ventures LLC
4:20pm • CANCELED: Lightning Talk: PyTorch-Wildlife: A Collaborative Deep Learning Framework for Conservation - Zhongqi Miao, Microsoft
4:35pm • Unlocking the Enigma: Crafting Unbiased, Transparent, and Explainable Large Language Models - Rashmi Nagpal, Patchstack
5:05pm • CANCELED: The Ethical Implications of AI and the Environment: A Focus on Water - Amber Hasan, Ethical Tech AI & Senegal Tuklor Williams, Broken Pencil Pictures llc
10:50am • The Rise of `Transformers` in the Growing PyTorch Ecosystem - Arthur Zucker, Hugging Face
11:20am • Training MoEs at Scale with PyTorch - Mihir Patel & Brian Chu, Databricks
11:50am • Lightning Talk: Empowering Developers: Tools and Resources for Running Generative AI on Arm CPUs - Pareena Verma, Arm
12:00pm • Lightning Talk: Optimized PyTorch Inference on aarch64 Linux CPUs - Sunita Nadampalli, Amazon (AWS)
12:10pm • Lightning Talk: AOTriton: Ahead of Time Triton Kernel Libraries on ROCm - Jeff Daily, AMD
2:15pm • vLLM: Easy, Fast, and Cheap LLM Serving for Everyone - Woosuk Kwon & Xiaoxuan Liu, UC Berkeley
2:45pm • Torchtitan: Large-Scale LLM Training Using Native PyTorch 3D Parallelism - Wanchao Liang, Meta & Linsong Chu, IBM Research
3:15pm • Slaying OOMs - Mark Saroufim & Jane Xu, Meta
4:05pm • Understanding the LLM Inference Workload - Mark Moyou, NVIDIA
4:35pm • Intel GPU in Upstream PyTorch: Expanding GPU Choices and Enhancing Backend Flexibility - Eikan Wang & Min Jean Cho, Intel
5:05pm • Implementing a Custom Torch.Compile Backend - A Case Study - Maanav Dalal & Yulong Wang, Microsoft
9:00am • Keynote: Welcome Back & Opening Remarks
9:07am • Keynote: Why You Should Think Twice Before Paying for an Evaluation Tool - Chip Huyen, VP of AI & OSS, Voltron Data
9:24am • Keynote: Navigating the Architectural Timeline of LLMs - Sebastian Raschka, Staff Research Engineer, Lightning AI
9:41am • Keynote: Building an Advanced Knowledge Assistant - Jerry Liu, Co-Founder & CEO, LlamaIndex
9:58am • Keynote: Ray: A Distributed Framework for Heterogeneous Computing - Ion Stoica, Professor, UC Berkeley
10:15am • Keynote: Contributor Awards
1:25pm • Sponsored Keynote: Accelerating AI: How AMD and PyTorch Drive Innovation with Seamless Day-0 Support and High Performance - Anush Elangovan, CVP Software Development, AMD
1:32pm • Sponsored Keynote: Optimizing AI Inference for Large Language Models - Mudhakar Srivatsa, Distinguished Engineer, IBM
1:40pm • Keynote Panel Discussion: Scaling & Benchmarking - Anastasios Nikolas Angelopoulos, UC Berkeley/LMSYS; Lisa Dunlap, UC Berkeley; James Bradbury, Anthropic; Tri Dao, together.ai; Aparna Ramani & Soumith Chintala, Meta
10:50am • Sponsored Session: Democratizing AI: Powering the Future with Arm’s Global Compute Ecosystem - Gian Marco Iodice, Arm
11:20am • Lightning Talk: Building and Supporting the Chinese PyTorch Community: Resources, Tutorials, and Engagement - Zong Zesheng, Huawei
11:35am • Lightning Talk: Distributing a Million Open Models in the Wild: Lessons Learned from the Hugging Face Hub - Omar Sanseviero, Hugging Face
11:50am • Lightning Talk: Understanding and Optimizing PyTorch Models with Thunder - Luca Antiga, Lightning AI
12:00pm • Lightning Talk: Fast, Scalable Distributed Training with StreamingDataset - Saaketh Narayan, Databricks
12:10pm • Lightning Talk: Implementing and Using Iterable Datasets: What Could Go Wrong? - Nicolas Hug, Meta
2:15pm • Building PyTorch Computer Vision Algorithms for 100 Skin Shades - Emmanuel Acheampong, roboMUA
2:45pm • Blobs to Clips: Efficient End-to-End Video Data Loading - Andrew Ho & Ahmad Sharif, Meta
3:15pm • Sponsored Session: PyTorch Support by Google Enabling Performance from Cloud to Edge - Mark Sherwood & Shauheen Zahirazami, Google
4:05pm • Startup Showcase