Software tools & optimizations#
Discover the latest blogs about ROCm software tools, libraries, and performance optimizations to help you get the most out of your AMD hardware.
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
LLM Inference Optimization Using AMD GPU Partitioning
Demonstrate how to leverage compute and memory partitioning features in ROCm to scale model serving.
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
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.
Deep Dive into Primus: High-Performance Training for Large Language Models
Learn how to achieve peak dense LLM training performance on AMD Instinct™ GPUs using Primus’s unified CLI and optimized backend presets.
Reimagining GPU Allocation in Kubernetes: Introducing the AMD GPU DRA Driver
Explore how the AMD GPU DRA Driver brings declarative, attribute-aware GPU scheduling to Kubernetes — learn how to request and manage GPUs natively
Introducing the AMD Network Operator v1.0.0: Simplifying High-Performance Networking for AMD Platforms
Introducing the AMD Network Operator for automating high-performance AI NIC networking in Kubernetes for AI and HPC workloads
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.
Getting Started with AMD AI Workbench: Deploying and Managing AI Workloads
Learn how to deploy and manage AI workloads with AMD AI Workbench, a low-code interface for developers to manage AI inference deployments
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!
3D Scene Reconstruction from the Inside: Explore the Mathematics Behind gsplat
3D Scene Reconstruction from the Inside: Explore the Mathematics Behind gsplat