PyVideo.org · PyTorch Conference 2023 (original) (raw)
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
