Featured Posts
ROCm 7.9 Technology Preview: ROCm Core SDK and TheRock Build System
Introduce ROCm Core SDK, and learn to install and build ROCm components easily using TheRock.
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
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
Reproducing the AMD Instinct™ GPUs MLPerf Inference v5.1 Submission
In this blog, we will provide step by step instruction on how to reproduce AMD's MLPerf Inference v5.1 Submission
High-Accuracy MXFP4, MXFP6, and Mixed-Precision Models on AMD GPUs
Learn to leverage AMD Quark for efficient MXFP4/MXFP6 quantization on AMD Instinct accelerators with high accuracy retention.
Nitro-E: A 304M Diffusion Transformer Model for High Quality Image Generation
Nitro-E is an extremely lightweight diffusion transformer model for high-quality image generation with only 304M paramters.
STX-B0T: Real-time AI Robot Assistant Powered by RyzenAI and ROCm
STX-B0T explores the potential of RyzenAI PCs to power robotics applications on NPU+GPU. This blog demonstrates how our hardware and software interoperate to unlock real-time perception.
Performance Profiling on AMD GPUs - Part 3: Advanced Usage
Part 3 of our GPU profiling series guides beginners through practical steps to identify and optimize kernel bottlenecks using ROCm 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.
AMD ROCm: Powering the World's Fastest Supercomputers
Discover how ROCm drives the world’s top supercomputers, from El Capitan to Frontier, and why its shaping the future of scalable, open and sustainable HPC
Empowering Developers to Build a Robust PyTorch Ecosystem on AMD ROCm™ with Better Insights and Monitoring
Production ROCm support for N-1 to N+1 PyTorch releases is in progress. The AI Software Head-Up Dashboard shows status of PyTorch on ROCm.
Kimi-K2-Instruct: Enhanced Out-of-the-Box Performance on AMD Instinct MI355 Series GPUs
Learn how AMD Instinct MI355 Series GPUs deliver competitive Kimi-K2 inference with faster TTFT, lower latency, and strong throughput.
Announcing MONAI 1.0.0 for AMD ROCm: Breakthrough AI Acceleration for Medical Imaging Models on AMD Instinct™ GPUs
Learn how to use Medical Open Network for Artificial Intelligence (MONAI) 1.0 on ROCm, with examples and demonstrations.
Medical Imaging on MI300X: Optimized SwinUNETR for Tumor Detection
Learn how to setup, run and optimize SwinUNETR on AMD MI300X GPUs for fast medical imaging 3D segmentation of tumors using fast, large ROIs.
Gumiho: A New Paradigm for Speculative Decoding — Earlier Tokens in a Draft Sequence Matter More
Gumiho boosts LLM inference with early-token accuracy, blending serial + parallel decoding for speed, accuracy, and ROCm-optimized deployment.
GEMM Tuning within hipBLASLt– Part 2
Learn how to use hipblaslt-bench for offline GEMM tuning in hipBLASLt—benchmark, save, and apply custom-tuned kernels at runtime.
Elevating 3D Scene Rendering with GSplat
ROCm Port of GSplat - GPU accelerated rasterization of Gaussian splatting
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
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