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.
Getting Started with AMD Resource Manager: Efficient Sharing of AMD Instinct™ GPUs for R&D Teams and AI Practitioners
Learn how to utilize the AMD Resource Manager by following this step-by-step guide on how to setup projects, share compute resources and monitor resource utilization.
JAX-AITER: Bringing AMD’s Optimized AI Kernels to JAX on ROCm™
Use JAX-AITER to run AMD’s AITER-optimized AI kernels from JAX on AMD ROCm, starting with faster multi-head attention and expanding to more ops.
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.
FlyDSL: Expert GPU Kernel Development with the Ease of MLIR Python Native DSL on AMD GPUs
FlyDSL is a Python-first, MLIR-native DSL for expert GPU kernel development and tuning on AMD GPUs.
Introducing hipThreads: A C++ - Style Concurrency Library for AMD GPUs
Discover how hipThreads lets you write hip::thread just like std::thread and unlock GPU acceleration with minimal code changes.
Advanced MXFP4 Quantization: Combining Fine-Tuned Rotations with SmoothQuant for Near-Lossless Compression
Showcase advanced algorithms available in AMD Quark for efficient MXFP4 quantization on AMD Instinct accelerators with high accuracy retention.
Adaptive Top-K Selection: Eliminating Performance Cliffs Across All K Values on AMD GPUs
Explore adaptive Top-K on MI300X! See how auto-selection and hardware optimizations like DPP and double buffering drive peak efficiency.
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.