AI Blogs#
VSA: Accelerating Video Diffusion Inference with Sparse Attention on AMD GPUs
Accelerate video diffusion inference with VSA sparse attention: up to 3.31x attention kernel-time speedup on AMD Instinct MI308X GPUs
Reverse-Engineering hipBLASLt TensileLite Kernels: From Solution Name to a Tuning Config
Pin the pool's best kernel into a TensileLite tuning config by decoding its solution name, so an expanded re-tune can only match or beat it.
Introducing AMD CDNA™ 5 and the AMD Helios™ Rackscale Solution
Introducing AMD CDNA 5, the AMD Instinct MI455X GPU, and the AMD Helios rackscale solution: an open, integrated platform for rack-scale AI.
Closing the GPU Cluster Validation Gap: A Kubernetes-Native Approach with CVF
Learn how to validate AMD GPU clusters end-to-end with CVF: hardware acceptance, mesh bandwidth, RDMA, and RCCL testing in one pipeline.
Enabling Language-specific Reasoning in Multilingual Models with Reinforcement Learning
Learn how to train multilingual reasoning models with reinforcement learning and extend context windows on AMD Instinct GPUs.
Introducing Instella-MoE: A State-of-the-Art Fully Open Mixture-of-Experts Language Model
Explore Instella-MoE-16B-A3B, AMD’s fully open 16B MoE LLM with 2.8B active params per token, trained on AMD Instinct™ MI300 & MI325 GPUs.
Onboard and Deploy Custom Models in AMD AI Workbench
Learn how to deploy custom models in AMD AI Workbench, utilizing the AIM Engine, orchestration, scaling, profile parameters and API keys.
Efficient MiniMax-M3 Inference on AMD Instinct GPUs with ATOM and ATOMesh
Serve and benchmark MiniMax-M3 on AMD Instinct MI355X GPUs using ATOM and ATOMesh with EAGLE3 speculative decoding.
AMD GPU Operator v1.5.0: DRA Support, Automated GPU Node Recovery, and Expanded Kubernetes Infrastructure Control
Discover how AMD GPU Operator v1.5.0 improves GPU scheduling, automates node recovery, and expands Kubernetes control.
Serve Kimi-K2.5-MXFP4 on MI355X with ATOM
Serve Kimi-K2.5-MXFP4 on MI355X with ATOM and gfx950 block-scaled FP4 kernels for optimized LLM inference.
Hyperloom - Autonomous Agentic Inference Optimization for AMD GPUs
Hyperloom is a new open-source, agentic system aimed at automating the time-consuming task of optimizing end-to-end inference workloads.
Introducing AMD ROCm™ Infera: Scaling Goodput for Agentic AI with Distributed Inference Orchestration
Explore how AMD ROCm Infera orchestrates distributed inference to scale goodput for agentic AI on AMD Instinct GPUs.
Styled Text Image Generation with Eruku on AMD
Hands-on, reproducible guide to train and run Eruku on LUMI supercomputer, powered by AMD Instinct MI250X GPUs.
Elevate Your LLM Inference: Autoscaling with Ray, ROCm 7.0.0, and SkyPilot
Learn how to use multi-node and multi-cluster autoscaling in the Ray framework on ROCm 7.0.0 with SkyPilot
Building Robotics Applications with Ryzen AI and ROS 2
This blog post gives a walkthrough of how to deploy a robotics application on the AI PC integrated with ROS - the robot operating system. We showcase Ryzen AI CVML Library to do perception tasks like depth estimation and develop a custom ROS 2 node which allows easy integration with the ROS ecosystem and standard components.
Quickly Developing Powerful Flash Attention Using TileLang on AMD Instinct MI300X GPU
Learn how to leverage TileLang to develop your own kernel. Explore the power to fully utilize AMD GPUs
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