Pytorch/Xla Inference

PyTorch/XLA inference

Accelerate PyTorch workloads with PyTorch/XLA

Google Cloud Tech

PyTorch in 100 Seconds

Deep Dive: Compiling deep learning models, from XLA to PyTorch 2

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

Lightning Talk: The Fastest Path to Production: PyTorch Inference in Python - Mark Saroufim, Meta

PyTorch/XLA Internal | PyTorch Developer Day 2020

Leaner, Greener and Faster Pytorch Inference with Quantization

MLOps World: Machine Learning in Production

Lightning Talk: Large-Scale Distributed Training with Dynamo and... - Yeounoh Chung & Jiewen Tan

Production Inference Deployment with PyTorch

Practical Guide on PyTorch Inference Using AWS Inferentia: PyTorch Conference 2022 Poster

(Day 1 - Breakout Session) PyTorch Deep Dive

Lightning Talk: Accelerated Inference in PyTorch 2.X with Torch...- George Stefanakis & Dheeraj Peri

Accelerate PyTorch workloads with Cloud TPUs and OpenXLA

Google for Developers

PyTorch Expert Exchange: Efficient Generative Models: From Sparse to Distributed Inference

How Pytorch Powers Training Inference | Wanchao Liang, Kimish Patel, and Evan Smothers

Understanding the LLM Inference Workload - Mark Moyou, NVIDIA

Getting started with PyTorch for the IPU: running a basic model for training and inference

Optimizing PyTorch Auto sharding For Your Hardware 2024 04 25 09 40 GMT 7

Better Transformer: Accelerating Transformer Inference in PyTorch at PyTorch Conference 2022