Systems Blogs#
Fast Image Generation and Editing with SGLang Diffusion on AMD GPUs
Serve and benchmark diffusion models for image generation and editing on AMD Instinct GPUs using SGLang Diffusion on ROCm.
Occupancy Math on the AMD MI355X GPU (CDNA4): A From-First-Principles Guide
Derive MI355X GPU (CDNA4) occupancy by hand: the four limiters, MXFP8 GEMM examples, and why matrix-bound kernels hit peak throughput at low occupancy.
RDC and RocProfiler Compared to DCGM for Commonly Used Metrics
Learn how CLI commands and Python code help you evaluate app performance without a profiler, with examples explaining what each metric means.
Primus Tuning Agent: Closing the Configuration-Search Loop
Use the Primus Tuning Agent to automatically find optimal LLM training configurations on AMD Instinct GPUs.
A Practical Guide to Running LLMs on AMD Radeon™ GPUs
This guide describes how to run LLMs on AMD Radeon™ GPUs using a range of partner frameworks, tools, and runtimes, with step-by-step setup instructions and performance optimization tips.
Deploying Serverless AI Inference on AMD GPU Clusters
This blog helps targeted audience in setting up AI inference serverless deployment in a kubernetes cluster with AMD accelerators. Blog aims to provide a comprehensive guide for deploying and scaling AI inference workloads on serverless infrastructre.
Primus Projection: Estimate Memory and Performance Before You Train
Learn how to use the Primus projection tool to estimate memory and performance for large-scale LLM training on AMD Instinct™ accelerator platforms.
Agentic Diagnosis for LLM Training at Scale
Explore how AI agents diagnose LLM training incidents — from RCCL hangs to throughput regressions — in one prompt with MaxText-Slurm.
MaxText-Slurm: Production-Grade LLM Training with Built-In Observability
MaxText-Slurm: A unified launch system for production-grade LLM training with observability on AMD GPU clusters.
Primus-Pipeline: A More Flexible and Scalable Pipeline Parallelism Implementation
Learn how to use our flexible and scalable pipeline parallelism framework with Primus backend and AMD hardware.
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.
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
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.
ROCm Revisited: Getting Started with HIP
New to HIP? This blog will introduce you to the HIP runtime API, its key concepts and installation and practical code examples to showcase its functionality.
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