Developers Blogs#
Optimizing MI300X Inter-Chiplet Communication via the RCCL Tuner API
Learn how to build a topology-aware RCCL tuner plugin for MI300X CPX/NPS4 mode and validate it with rccl-tests.
Accelerating LLM Inference on AMD GPUs with Low-Latency GEMMs
Learn how FlyDSL low-latency GEMMs speed up LLM decode on AMD GPUs with Split-K, K-slice parallelism, and an LDS-based pipeline.
OpenXLA and JAX - ROCm Support and the State of CI
Learn how OpenXLA and JAX run on AMD ROCm: what landed this year, how every PR is gated on real Instinct hardware, and how to get started.
MXFP6 and MXFP4 Mixed Precision for Accelerating Dense LLMs on AMD Instinct MI355X
W_MXFP4_A_MXFP6 quantization on AMD Instinct MI355X improves LLM throughput and latency while recovering accuracy versus MXFP4.
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.
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.
Continuing the Momentum: Refining ROCm For The Next Wave Of AI and HPC
ROCm 7.1 builds on 7.0’s AI and HPC advances with faster performance, stronger reliability, and streamlined tools for developers and system builders.
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
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.
Efficient and Portable 3D Explorable World Generation on AMD GPUs
Learn how to run Matrix3D world generation on AMD GPUs more smoothly and efficiently.
Utilizing AMD Schola and UnrealRoboticsLab with AMD ROCm™ Software to Train a Robotic Arm
Learn how to combine MuJoCo physics, Unreal Engine, and Schola to train a 6-DOF robot arm with reinforcement learning on AMD hardware.
Customizing Kernels with hipBLASLt TensileLite GEMM Tuning - Advanced User Guide
Master hipBLASLt TensileLite Tuning. Learn to build custom kernels that deliver 150%-250% faster GEMM performance on AMD Instinct™ MI300X GPUs
Building and Deploying Custom hipBLASLt Libraries on AMD Instinct GPUs
Learn how to manage hipBLASLt environments with custom source builds, RPM/DEB packaging, and version switching on AMD Instinct GPUs.
Dropless MoE Training in JAX with Primus-Turbo
Learn how to train dropless MoE in JAX/MaxText with Primus-Turbo's grouped GEMM and DeepEP all-to-all for faster, more memory-efficient training.
Performance Profiling on AMD GPUs - Part 4: Fortran OpenMP Offload Edition
Guides developers through profiling and optimizing Fortran OpenMP GPU offload applications using ROCm tools
From Build to Benchmark: ONNX Model Serving with Triton Inference Server on AMD GPUs
Step-by-step guide to building, deploying, and benchmarking ONNX models with Triton Inference Server and MIGraphX on AMD GPUs
Stay informed
- Subscribe to our RSS feed (Requires an RSS reader available as browser plugins.)
- Signup for the ROCm newsletter
- View our blog statistics