Supporting efficient large model training on AMD Instinct™ GPUs with DeepSpeed 

6 min read

This post was co-authored by Jithun Nair and Aswin Mathews, members of technical staff at AMD. In recent years, large-scale deep learning models have demonstrated impressive capabilities, excelling at tasks across natural language processing, computer vision, and speech domains. Companies now use these models to power novel AI-driven user experiences across a whole spectrum of…Read more

Accelerate PyTorch training with torch-ort 

3 min read

With a simple change to your PyTorch training script, you can now speed up training large language models with torch_ort.ORTModule, running on the target hardware of your choice. Training deep learning models requires ever-increasing compute and memory resources. Today we release torch_ort.ORTModule, to accelerate distributed training of PyTorch models, reducing the time and resources needed…Read more

Delivering reliable production experiences with PyTorch Enterprise on Microsoft Azure 

3 min read

At Microsoft, we use PyTorch to power products such as Bing and Azure Cognitive Services and we actively contribute to several PyTorch open-source projects, including PyTorch Profiler, ONNX Runtime, DeepSpeed, and more. Today, we’re announcing a new initiative in collaboration with Facebook—the PyTorch Enterprise Support Program. This new program enables service providers to develop and…Read more