Accelerating Explorations in Vision and Multimodal AI Using Pytorch Libraries

Accelerating Generative AI

Composable Distributed PT2(D)

Cost Effectively Deploy Thousands of Fine Tuned Gen AI Models Like Llama Using TorchServe on AWS

Distributed Checkpoint

Getting Started with Pytorch 2.0 and Hugging Face Transformers

Into Generative AI with PyTorch Lightning 2.0

Introducing ExecuTorch from PyTorch Edge: On-Device AI Stack and Ecosystem, and Our Unique Differentiators

Keynote: AMD & PyTorch: A Powerful Combination for Generative AI

Keynote: Building an Interoperable Ecosystem for Generative AI

Keynote: How PyTorch Became the Foundation of the AI Revolution

Keynote: How to Leverage PyTorch to Scale AI Training and Inferencing

Keynote: Intel and PyTorch: Enabling AI Everywhere with Ubiquitous Hardware and Open Software

Keynote: PyTorch 2.1 Technical Deep Dive

Keynote: PyTorch Lightning: Powering the GenAI Revolution from Research to the Enterprise

Keynote: Refik Anadol Studio: Rainforest AI Research

Keynote: The Llama Ecosystem: Past, Present and Future

Keynote: The Promise of PyTorch as a General-Purpose Array-Oriented Computational Backend

Keynote: The Value of Open Source for the Enterprise

Keynote: Welcome & Opening Remarks

Keynote: Welcome & Opening Remarks 2

Lessons Learned in WatsonX Training: Scaling Cloud-Native PyTorch FSDP to 20B Parameters

Lightning Talk: A Novel Domain Generalization Technique for Medical Imaging Using PyTorch

Lightning Talk: Accelerated Inference in PyTorch 2.X with Torch-TensorRT

Lightning Talk: Accelerating Inference on CPU with Torch.Compile

Lightning Talk: Accelerating LLM Training on Cerebras Wafer-Scale Cluster

Lightning Talk: Accelerating PyTorch Performance with OpenVINO

Lightning Talk: Adding Backends for TorchInductor: Case Study with Intel GPU

Lightning Talk: AOTInductor: Ahead-of-Time Compilation for PT2 Exported Models

Lightning Talk: Building Intermediate Logging for PyTorch

Lightning Talk: CUDAGraph in a Partial Graph World

Lightning Talk: Diffusers: Bringing Cutting-Edge Diffusion Models to the Masses

Lightning Talk: Dinosaur Bone Hunt

Lightning Talk: Efficient Inference at the Edge: Performance You Need at the Lowest Power You Deserve

Lightning Talk: Energy-Efficient Deep Learning with PyTorch and Zeus

Lightning Talk: Enhancements Made to MPS Backend in PyTorch for Applications Running on Mac Platforms

Lightning Talk: Exploring PiPPY, Tensor Parallel and Torchserve for Large Model Inference

Lightning Talk: Harnessing NVIDIA Tensor Cores: An Exploration of CUTLASS & OpenAI Triton

Lightning Talk: Large-Scale Distributed Training with Dynamo and Triton

Lightning Talk: Lessons from Using Pytorch 2.0 Compile in IBM's Watsonx.AI Inference

Lightning Talk: Leveraging PyTorch 2.0 for Bias Reduction in AI

Lightning Talk: Orchestrating Machine Learning on Edge Devices with PyTorch and WebAssembly

Lightning Talk: Profiling and Memory Debugging Tools for Distributed ML Workloads on GPUs

Lightning Talk: PT2 Export - A Sound Full Graph Capture Mechanism for PyTorch

Lightning Talk: PyTorch 2.0 on the ROCm Platform

Lightning Talk: Seismic Data to Subsurface Models with OpenFWI

Lightning Talk: Simulating Quantum Systems with PyTorch

Lightning Talk: Standardizing CPU Benchmarking with TorchBench for PyTorch Community

Lightning Talk: State of PyTorch

Lightning Talk: Streamlining Model Export with the New ONNX Exporter

Lightning Talk: Tensor and 2D Parallelism

Lightning Talk: Tensor Query Processing

Lightning Talk: The Fastest Path to Production: PyTorch Inference in Python

Lightning Talk: TorchFix - a Linter for PyTorch-Using Code with Autofix Support

Lightning Talk: TorchRL - RLHF Support

Lightning Talk: Triton Compiler

Lightning Talk: Uplink Interference Optimizer, How to Optimize a Cellular Network in a Single Shot with GNNs

LightningTalk: MultiRay: An Accelerated Embedding Service for Content Understanding

Llama V2 in Azure AI for Finetuning, Evaluation and Deployment from the Model Catalog

PyTorch Edge: Developer Journey for Deploying AI Models Onto Edge Devices

PyTorch Edge: Vendor Integration Journey for Compilers and Backends

PyTorch Korea User Group: The Beginning, Present, and Future

The Evolving Landscape of Dataloading

TorchBench: Guarding the Performance of the PyTorch Ecosystem with Continuous Benchmarking

Training a LLaMA in your Backyard: Fine-tuning Very Large Models on Consumer Hardware

What's New for Dynamic Shapes in PyTorch 2.1

What's New for PyTorch Developer Infrastructure