AMD ROCm™ Blogs

AI Inference Orchestration with Kubernetes on Instinct MI300X, Part 1
This blog is part 1 of a series aimed at providing a comprehensive, step-by-step guide for deploying and scaling AI inference workloads with Kubernete...

GEMM Kernel Optimization For AMD GPUs
Guide to how GEMMs can be tuned for optimal performance of AI models on AMD GPUs...

Enhancing AI Training with AMD ROCm Software
AMD's GPU training optimizations deliver peak performance for advanced AI models through ROCm software stack....

Best practices for competitive inference optimization on AMD Instinct™ MI300X GPUs
Learn how to optimize large language model inference using vLLM on AMD's MI300X GPUs for enhanced performance and efficiency....

Announcing the AMD GPU Operator and Metrics Exporter
This post announces the AMD GPU Operator for Kubernetes and and the Device Metrics Exporter, including instructions for getting started with these new...

Distributed fine-tuning of MPT-30B using Composer on AMD GPUs
This blog uses Composer, a distributed framework, on AMD GPUs to fine-tune MPT-30B in single node as well as multinode...

Vision Mamba on AMD GPU with ROCm
This blog explores Vision Mamba (Vim), an innovative and efficient backbone for vision tasks and evaluate its performance on AMD GPUs with ROCm....

Getting started with AMD ROCm containers: from base images to custom solutions
Getting started with AMD ROCm containers: from base images to custom solutions...

Boosting Computational Fluid Dynamics Performance with AMD Instinct™ MI300X
The blog introduces CFD Ansys Fluent benchmarks and provides hands-on guide on installing and running four different Fluent models on AMD GPUs using R...

Zyphra Introduces Frontier Training Kernels for Transformers and SSMs on AMD Instinct MI300X Accelerators
This blog shows Zyphra's new training kernels for transformers and hybrid models on AMD Instinct MI300X accelerators, surpassing the H100s performance...

Introducing AMD's Next-Gen Fortran Compiler
In this post we present a brief preview of AMD's [Next-Gen Fortran Compiler](https://github.com/amd/InfinityHub-CI/blob/main/fortran/README.md), our n...

Stone Ridge Expands Reservoir Simulation Options with AMD Instinct™ Accelerators
Stone Ridge Technology (SRT) pioneered the use of GPUs for high performance reservoir simulation (HPC) nearly a decade ago with ECHELON, its flagship ...

Triton Inference Server with vLLM on AMD GPUs
This blog provides a how-to guide on setting up a Triton Inference Server with vLLM backend powered by AMD GPUs, showcasing robust performance with se...
Transformer based Encoder-Decoder models for image-captioning on AMD GPUs
The blog introduces image captioning and provides hands-on tutorials on three different Transformer-based encoder-decoder image captioning models: ViT...

Quantized 8-bit LLM training and inference using bitsandbytes on AMD GPUs
Learn how to use bitsandbytes’ 8-bit representations techniques, 8-bit optimizer and LLM.int8, to optimize your LLMs training and inference using ROCm...

SGLang: Fast Serving Framework for Large Language and Vision-Language Models on AMD GPUs
Discover SGLang, a fast serving framework designed for large language and vision-language models on AMD GPUs, supporting efficient runtime and a flexi...

Getting to Know Your GPU: A Deep Dive into AMD SMI
This post introduces AMD System Management Interface (amd-smi), explaining how you can use it to access your GPU’s performance and status data...

Introducing the AMD ROCm™ Offline Installer Creator: Simplifying Deployment for AI and HPC
Presenting and demonstrating the use of the ROCm Offline Installer Creator, a tool enabling simple deployment of ROCm in disconnected environments in ...