AI Blogs#
From Ingestion to Inference: RAG Pipelines on AMD GPUs
Build a RAG enhanced GenAI application that improves the quality of model responses by incorporating data that is missing in the model training data.
Enabling FlashInfer on ROCm for Accelerated LLM Serving
FlashInfer is an open-source library for accelerating LLM serving that is now supported by ROCm.
GPU Partitioning Made Easy: Pack More AI Workloads Using AMD GPU Operator
What’s New in AMD GPU Operator: Learn About GPU Partitioning and New Kubernetes Features
Coding Agents on AMD GPUs: Fast LLM Pipelines for Developers
Accelerate AI-assisted coding with agentic workflows on AMD GPUs. Deploy DeepSeek-V3.1 via SGLang, vLLM, or llama.cpp to power fast, scalable coding agents
ROCm 7.0: An AI-Ready Powerhouse for Performance, Efficiency, and Productivity
Discover how ROCm 7.0 integrates AI across every layer, combining hardware enablement, frameworks, model support, and a suite of optimized tools
Llama.cpp Meets Instinct: A New Era of Open-Source AI Acceleration
performance optimizations for llama.cpp on AMD Instinct GPUs
Day 0 Developer Guide: Running the Latest Open Models from OpenAI on AMD AI Hardware
Day 0 support across our AI hardware ecosystem from our flagship AMD InstinctTM MI355X and MI300X GPUs, AMD Radeon™ AI PRO R700 GPUs and AMD Ryzen™ AI Processors
Unlocking GPU-Accelerated Containers with the AMD Container Toolkit
Simplify GPU acceleration in containers with the AMD Container Toolkit—streamlined setup, runtime hooks, and full ROCm integration.
Day-0 Support for the SGLang-Native RL Framework - slime on AMD Instinct™ GPUs
Learn how to deploy slime on AMD GPUs for high-performance RL training with ROCm optimization
Accelerating Audio-Driven Video Generation: WAN2.2-S2V on AMD ROCm
This blog will highlight AMD ROCm’s ability to power next-generation audio-to-video models with simple, reproducible workflows.
A Simple Design for Serving Video Generation Models with Distributed Inference
Minimalist FastAPI + Redis + Torchrun design for serving video generation models with distributed inference.
Optimizing Drug Discovery Tools on AMD MI300X Part 1: Molecular Design with REINVENT
Learn how to set up, run, and optimize REINVENT4, a molecular design tool, on AMD MI300X GPUs for faster drug discovery workflows
Matrix Core Programming on AMD CDNA™3 and CDNA™4 architecture
This blog post explains how to use Matrix Cores on CDNA3 and CDNA4 architecture, with a focus on low-precision data types such as FP16, FP8, and FP4
An Introduction to Primus-Turbo: A Library for Accelerating Transformer Models on AMD GPUs
Primus streamlines training on AMD ROCm, from fine-tuning to massive pretraining on MI300X GPUs—faster, safer, and easier to debug
Efficient LLM Serving with MTP: DeepSeek V3 and SGLang on AMD Instinct GPUs
This blog will show you how to speed up LLM inference with Multi-Token Prediction in DeepSeek V3 & SGLang on AMD Instinct GPUs
GEMM Tuning within hipBLASLt - Part 1
We introduce a hipBLASLt tuning tool that lets developers optimize GEMM problem sizes and integrate them into the library.
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