Developers Blogs#
Resilient Large-Scale Training: Integrating TorchFT with TorchTitan on AMD GPUs
Achieve resilient, checkpoint-less distributed training on AMD GPUs by integrating TorchFT with TorchTitan on Primus-SaFE.
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
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.
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.
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.
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.
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.
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!
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