Developers Blogs#
ROCm 10.0: A Decade of Open Compute, Built for the Age of Agentic AI
Explore what's new in ROCm 10.0, headlined by ROCm.AI, the ROCm CLI, AMD Skills, and Hyperloom, alongside the ROCm Core SDK and platform-wide improvements
Exploring XGBoost: A Deep Dive
A single source explanation of XGBoost features and its working principles.
Memory Instruction Scheduling for Lock-Stepped Kernels on AMD Instinct™ MI300X: Introducing the Series
Explore how instruction scheduling eases stalls on AMD Instinct MI300X in a new blog series. This intro covers the motivating example and methodology.
Bring Claude Code On‑Prem with AMD Instinct GPUs
Start running Claude Code securely with a self-hosted SGLang LLM on AMD Instinct MI355X 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.
Building a High-Performance Video Inference Pipeline with ROCm Libraries Using C/C++
Learn how to build a powerful, GPU-accelerated video analytics pipeline with ROCm, combining rocDecode for fast hardware video decoding and MIGraphX for efficient AI-powered analysis and inference.
GEAK V3: Agent-Driven, Repository-Level GPU Kernel Optimization across HIP, Triton, and FlyDSL on AMD GPUs
Explore GEAK v3: agent-driven, repository-level GPU kernel optimization across HIP, Triton, and FlyDSL on AMD Instinct™ GPUs.
Triton-Based Optimization of Video Sparse Attention on ROCm
Optimize video sparse attention on ROCm with GEAK and linear global context for faster, more stable video generation on AMD GPUs.
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.
Introducing ROCm™ AMD Infinity Context: A Purpose-Built KV Cache Tier for Distributed Inference
Explore ROCm AMD Infinity Context (AIC), AMD's open KV cache tier built on AMD Infinity Storage for distributed LLM inference.
Scaling MiniMax-M3 Inference with Distributed Serving and Operator Co-Design on AMD Instinct MI355X GPUs
Optimize MiniMax-M3 inference on AMD Instinct™ MI355X GPUs with ATOM online quantization, AITER sparse attention, FP8 KV cache, and EAGLE3.
Understanding Attention Algorithms and Their Backends for Image and Video Generation
Practical guide to attention backends in ComfyUI on AMD describing how to optimize performance, memory, and stability with the right configuration.
AUP Learning Cloud: Streamlining AI Education on AMD
An all-in-one ROCm JupyterHub platform that deploys GPU-ready AI teaching environments on AMD hardware with one installer and open-source teaching labs.
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.
ROCm 7.14: TheRock Goes Production and Expands AMD's AI Software Platform
Explore what's new in ROCm 7.14: TheRock goes production, expanded hardware support, stronger AI frameworks, and enhanced profiling tools.
ROCm 7.13: Expanding Hardware, Tools, and Reach
Explore what's new in the ROCm 7.13 release, featuring expanded hardware support, GPU virtualization, enhanced developer tooling, and TheRock's modular packaging.
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