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We are excited to announce the release of PyTorch® 2.3 (release note)! PyTorch 2.3 offers…

1.0 Summary We show that by implementing column-major scheduling to improve data locality, we can…

In this blog, we demonstrate the scalability of FSDP with a pre-training exemplar, a 7B…

This post is the fourth part of a multi-series blog focused on how to accelerate…

Overview PyTorch is a Python-based framework for developing deep learning models. It is one of…

TL;DR Leveraging a first principles approach, we showcase a step by step process undertaken to…

We demonstrate how to finetune a 7B parameter model on a typical consumer GPU (NVIDIA…

Multi-model endpoints (MMEs) are a powerful feature of Amazon SageMaker designed to simplify the deployment and operation…

This post is the third part of a multi-series blog focused on how to accelerate…

This is part 2 of the Understanding GPU Memory blog series. Our first post Understanding GPU…

1. Introduction PyTorch 2.0 (abbreviated as PT2) can significantly improve the training and inference performance of…

Introduction PyTorch 2.0 (PT2) offers a compiled execution mode which rewrites Python bytecode to extract sequences…

During your time with PyTorch on GPUs, you may be familiar with this common error…

Lightning Talk 1: Seismic Data to Subsurface Models with OpenFWI Speaker: Benjamin Consolvo, AI Software…

This post is the second part of a multi-series blog focused on how to accelerate…