Developers Blogs - Page 2#
Accelerating Graph Layout with AI and ROCm on AMD GPUs
Case study of using AI coding agents to optimize graph layout using GPUs.
Debugging NaN Results in CK Tile GEMM: A rocgdb Detective Story
Learn GPU kernel debugging with rocgdb through a real case: tracing NaN outputs to a one-character typo in CK Tile GEMM
ROCm 7.2: Smarter, Faster, and More Scalable for Modern AI Workloads
we highlight the latest ROCm 7.2 enhancements for AMD Instinct GPUs, designed to boost AI and HPC performance
ROCm Becomes a First-Class Platform in the vLLM Ecosystem
ROCm is now a first-class vLLM platform: official wheels + Docker, stronger CI, and faster LLM & multimodal inference on AMD Instinct GPUs.
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.
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.
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
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.