Developers Blogs#
GEMM Tuning within hipBLASLt– Part 2
Learn how to use hipblaslt-bench for offline GEMM tuning in hipBLASLt—benchmark, save, and apply custom-tuned kernels at runtime.
Running SwinUNETR on AMD MI300X GPUs
Learn how to setup, run and optimize SwinUNETR on AMD MI300X GPUs for fast medical imaging 3D segmentation of tumors using fast, large ROIs.
Optimizing Drug Discovery Tools on AMD MI300s Part 2: 3D Molecular Generation with SemlaFlow
Learn how to set up, run, and optimize SemlaFlow, a molecular generation tool, on AMD MI300X GPUs for faster drug discovery workflows
Elevating 3D Scene Rendering with GSplat
ROCm Port of GSplat - GPU accelerated rasterization of Gaussian splatting
Matrix Core Programming on AMD CDNA™3 and CDNA™4 architecture
This blog post explains how to use Matrix Cores on CDNA3 and CDNA4 architecture, with a focus on low-precision data types such as FP16, FP8, and FP4
Optimizing Drug Discovery Tools on AMD MI300X Part 1: Molecular Design with REINVENT
Learn how to set up, run, and optimize REINVENT4, a molecular design tool, on AMD MI300X GPUs for faster drug discovery workflows
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
GEMM Tuning within hipBLASLt - Part 1
We introduce a hipBLASLt tuning tool that lets developers optimize GEMM problem sizes and integrate them into the library.
AITER-Enabled MLA Layer Inference on AMD Instinct MI300X GPUs
AITER boosts DeepSeek-V3’s MLA on AMD MI300X GPUs with low-rank projections, shared KV paths & matrix absorption for 2× faster inference.
Introducing AMD EVLM: Efficient Vision-Language Models with Parameter-Space Visual Conditioning
A novel approach that replaces visual tokens with perception-conditioned weights, reducing compute while maintaining strong vision-language performance.
Primus: A Lightweight, Unified Training Framework for Large Models on AMD GPUs
Primus streamlines LLM training on AMD GPUs with unified configs, multi-backend support, preflight validation, and structured logging.
Introducing Instella-Math: Fully Open Language Model with Reasoning Capability
Instella-Math is AMD’s 3B reasoning model, trained on 32 MI300X GPUs with open weights, optimized for logic, math, and chain-of-thought tasks.