Developers Blogs#
Installing AMD HIP-Enabled GROMACS on HPC Systems: A LUMI Supercomputer Case Study
Installing AMD HIP-Enabled GROMACS on HPC Systems: A LUMI Supercomputer Case Study
Bridging the Last Mile: Deploying Hummingbird-XT for Efficient Video Generation on AMD Consumer-Grade Platforms
Learn how to use Hummingbird-XT and Hummingbird-XTX modelS to generate videos. Explore the video diffusion model acceleration solution, including dit distillation method and light VAE model.
Accelerating Multimodal Inference in vLLM: The One-Line Optimization for Large Multimodal Models
Learn how to optimize multimodal model inference with batch-level data parallelism for vision encoders in vLLM, achieving up to 45% throughput gains on AMD MI300X.
GEAK HIP: Expanding GEAK for HIP Code Optimization
Explore the GEAK frameworks AI-driven HIP code optimization for improved performance on AMD GPUs, including speedup examples and benefits for AI workloads.
Continuing the Momentum: Refining ROCm For The Next Wave Of AI and HPC
ROCm 7.1 builds on 7.0’s AI and HPC advances with faster performance, stronger reliability, and streamlined tools for developers and system builders.
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
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.
A Step-by-Step Walkthrough of Decentralized LLM Training on AMD GPUs
Learn how to train LLMs across decentralized clusters on AMD Instinct MI300 GPUs with DiLoCo and Prime—scale beyond one datacenter.
Medical Imaging on MI300X: SwinUNETR Inference Optimization
A practical guide to optimizing SwinUNETR inference on AMD Instinct™ MI300X GPUs for fast 3D segmentation of tumors in medical imaging.
Scaling AI Inference Performance with vLLM on AMD Instinct MI355X GPUs
Explore how MI355X performs against B200 in vLLM benchmarks across DeepSeek-R1, GPT-OSS-120B, Qwen3-235B and Llama-3.3-70B.
Day 0 Developer Guide: hipBLASLt Offline GEMM Tuning Script
Learn how to improve model performance with hipBLASLt offline tuning in our easy-to-use Day 0 tool for developers to optimize GEMM efficiency
MoE Training Best Practices on AMD GPUs
Learn how to optimize Mixture-of-Experts (MoE) model training on AMD Instinct GPUs with ROCm. Maximize your AI training performance now!
3D Scene Reconstruction from the Inside: Explore the Mathematics Behind gsplat
3D Scene Reconstruction from the Inside: Explore the Mathematics Behind gsplat
The vLLM MoE Playbook: A Practical Guide to TP, DP, PP and Expert Parallelism
Learn how to combine TP, DP, PP, and EP for MoE models. Discover proven strategies to maximize performance on your vLLM deployments.
Stability at Scale: AMD’s Full‑Stack Platform for Large‑Model Training
Primus streamlines LLM training on AMD GPUs with unified configs, multi-backend support, preflight validation, and structured logging.
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