Posts by Yao Fu
An Introduction to Primus-Turbo: A Library for Accelerating Transformer Models on AMD GPUs
- 19 September 2025
With the rapid growth of large-scale models, acceleration libraries are facing higher demands: they must deliver exceptional performance, offer comprehensive functionality, and remain easy to use. To meet these needs, we introduce Primus-Turbo — part of the Primus product family (see our previous blog for background). Primus-Turbo is designed around three core principles: performance, completeness, and ease of use. It supports training, inference, and a wide range of application scenarios, providing developers with a solid foundation to efficiently build and optimize large models on the ROCm platform. See Figure 1 below for a comprehensive stack coverage of Primus-Turbo.
Primus: A Lightweight, Unified Training Framework for Large Models on AMD GPUs
- 22 August 2025
Training large language models (LLMs) at scale is inherently complex. Different frameworks expose inconsistent interfaces, multi-GPU and distributed setups require brittle scripting, and backend-specific quirks introduce overhead that slows down training iterations. Primus tackles these challenges with a streamlined, backend-agnostic training framework that helps developers launch, customize, and scale training jobs faster on AMD GPUs.
Day 0 Developer Guide: Running the Latest Open Models from OpenAI on AMD AI Hardware
- 05 August 2025
OpenAI has officially released its open models: gpt-oss-120b and gpt-oss-20b. AMD now provides out-of-the-box, day 0 support for the latest open models from OpenAI, enabling developers to easily fine-tune and deploy across cloud to client environments using AMD hardware, the AMD ROCm™ and AMD Ryzen™ AI software stack, and seamless open source integrations. At AMD, we’re excited to announce day 0 support across our AI hardware, including our flagship AMD Instinct™ MI355X and MI300X GPUs, AMD Radeon™ AI PRO R9700 GPUs, and AMD Ryzen™ AI processors.
Optimized ROCm Docker for Distributed AI Training
- 13 March 2025
This blog will introduce you to the updated AMD Docker image, specifically built and optimized for distributed training. As you will see, the optimized AMD ROCm Docker image makes training large AI models faster and more efficient. It includes updates such as better fine-tuning tools, improved performance for multi-GPU setups, and support for FP8 precision, which helps speed up training while using less memory, and can provide you with an overall smoother and more efficient training experience on popular models such as Flux and Llama 3.1 running on AMD GPUs.