29:18

PyTorch Expert Exchange Hacker Cup AI

01:41

PyTorch Conference 2024 Highlights

09:26

Together Goes Brrr: Threading Research & Production with Torch Compile - Pragaash Ponnusamy

08:50

Lightning Talk: Low Precision Dtypes in PyTorch - Vasiliy Kuznetsov, Meta

24:21

Running State-of-Art Gen AI Models on-Device with NPU Acceleration - Felix Baum, Qualcomm

21:16

Sponsored Session: NeMo-Aligner: A Scalable Toolkit for Model Alignment - Gerald Shen & Jimmy Zhang

10:50

[TVM] Universally Deploy Large-language Models via ML Compilation - Tianqi Chen, CMU & OctoAI

14:02

Lightning Talk: Sparsifying Vision Transformers with Minimal Accuracy Loss - Jesse Cai, Meta

20:37

State of PyTorch - Ji Li & Damien Sereni, Meta

08:28

Lightning Talk: Mobile Computational Photography with PyTorch: Low-Light Denoising - Alexis Baudron

08:09

[HALIDE] A Halide Backend for TorchInductor - Jason Ansel, Meta

10:01

[TRITON] Maximizing Kernel Development Productivity Under Performance Constraints - Philip Tillet

28:30

Sponsored Session: Accelerating AI Innovation: High Performance PyT... Robert Suderman & Ian Nordeng

09:17

The Challenges of Building an Opinionated Open Source LLM Framework - Wing Lian, Axolotl AI

13:34

Lightning Talk: What’s New in Ex... Angela Yi, Tugsbayasgalan Manlaibaatar, Avik Chaudhuri & Yidi Wu

03:41

Maximizing Training Throughput Using Torch.Compile and FSDP - L. Chu, A. Viros i Martin, B. Vaughan

35:31

DL Compiler Panel Discussion - P. Tillet, J. Ansel, J. Pienaar, T. Chen, M. Zolotukhin, P. Wu

20:51

Meta Llama 3 and the Future of Responsible AI Development - Spencer Whitman & Vincent Gonguet, Meta

21:53

TorchInductor CPU Backend Advancements: New Features and Performance Imp... Jiong Gong & Leslie Fang

28:05

Building Scientific Computing Infrastructure Software with the PyTorch Ecosystem - Bharath Ramsundar

01:22

Welcome to the PyTorch Ecosystem for LLM Fine-tuning Mini Summit - Kartikay Khandelwal, Meta

14:08

Lightning Talk: A Whirlwind Tour of PyTorch Extension Points - Alban Desmaison, Meta

07:58

Hacks to Make LLM Training Faster - Daniel Han, Unsloth AI

08:32

Lightning Talk: Extending PyTorch with Custom Python/C++/CUDA Operators - Richard Zou, Meta

09:33

[MOJO] Lifting PT to New Heights with MAX and Mojo - Mikhail Zolotukhin, Modular

11:13

[MLIR] Enabling Composition of Kernels and Compilers - Jacques Pienaar, Google

17:25

The State of the Llama Ecosystem - Joe Spisak, Meta

20:14

ExecuTorch Beta and on-Device Generative AI Support - Mergen Nachin & Mengtao (Martin) Yuan, Meta

15:58

torchtune: Easy and Accessible Finetuning in Native PyTorch - Evan Smothers, Meta

12:16

Lightning Talk: Beyond Zero: Eliminating Vulnerabili... Patrick Smyth, Dan Fernandez & Srishti Hegde

36:00

Panel Discussion - T. Dettmers, H. Schoelkopf, A. Chowdhery, A. Conneau, Moderated by K. Khandelwal

11:11

Lightning Talk: What's New for PyTorch Developer Infrastructure - Sahan Paliskara & Catherine Lee

12:31

Lightning Talk: New Activation Checkpointing APIs in PyTorch - Jeffrey Wan & Horace He, Meta

11:26

Lightning Talk: Making the Most of Heterogeneous Memory Capacity Using PyTorch - Syed Ahmed, NVIDIA

12:06

Lightning Talk: In-Transit Machine Learning Using PyTorch on Frontier Exascale System- Vineeth Gutta

17:41

Lightning Talk: FlexAttention - The Flexibility of PyTorch + The Performa... Yanbo Liang & Horace He

24:19

Sponsored Session: Torchchat: A Showcase of PyTorch LLM Ubiquity - Jack Khuu & Jesse White, Meta

18:53

Training MoEs at Scale with PyTorch - Mihir Patel & Brian Chu, Databricks

07:42

Lightning Talk: PyTorch/XLA Auto-Sharding - Yeounoh Chung, Google

14:13

Lightning Talk: On-Device Profiling and Debugging with ExecuTorch - Olivia Liu & Vaun Puri, Meta

12:45

Lightning Talk: Introduction to Torch.Distributed.Pipelining - Howard Huang & Ke Wen, Meta

19:13

Pushing the Performance Envelope: An Optimization Study for 3... Suvaditya Mukherjee & Shireen Chand

23:54

A Distributed Stateful Dataloader for Large-Scale Pretraining - Davis Wertheimer & Linsong Chu

25:24

Data-Dependent Shapes in PT2 - Edward Yang, Meta

12:09

Lightning Talk: LLMs on Edge with AI Accelerators - Chen Lai, Kimish Patel & Cemal Bilgin, Meta

09:34

Lightning Talk: PyTorch Release Process - Andrey Talman, Meta

22:23

Torch.Compile for Autograd, DDP and FSDP - Will Feng , Chien-Chin Huang & Simon Fan, Meta

24:20

Torchtitan: Large-Scale LLM Training Using Native PyTorch 3D Parallel... Wanchao Liang & Linsong Chu

23:33

vLLM: Easy, Fast, and Cheap LLM Serving for Everyone - Woosuk Kwon & Xiaoxuan Liu, UC Berkeley

11:32

Lightning Talk: AOTriton: Ahead of Time Triton Kernel Libraries on ROCm - Jeff Daily, AMD

13:10

Lightning Talk: Optimized PyTorch Inference on aarch64 Linux CPUs - Sunita Nadampalli, Amazon (AWS)

12:18

Lightning Talk: Empowering Developers: Tools and Resources for Running Generative A... Pareena Verma

18:38

The Rise of `Transformers` in the Growing PyTorch Ecosystem - Arthur Zucker, Hugging Face

25:42

Slaying OOMs - Mark Saroufim & Jane Xu, Meta

05:06

Sponsored Keynote: From Containers to Cognition: Conducting the AI Orchestra - Taylor Dolezal

05:58

Sponsored Keynote: Enabling AI Everywhere with PyTorch and Intel - Kismat Singh, Intel

06:08

Sponsored Keynote: The Lightning AI OSS Stack for Accelerating the AI Lifecycle - Luca Antiga

14:09

Keynote: Enabling Generative AI on the Edge - Cormac Brick, Principal Engineer, Google

17:16

Keynote: Open Language Models (OLMo): Accelerating the Science of Language Modeling Hanna Hajishirzi

50:56

Keynote: PyTorch Technical Deep Dive - P. Bialecki, P. Wu, W. Constable, K. Khandelwal & M. Yuan