Recent Posts - Page 8#
Technical Dive into AMD MLPerf Training v5.1 Submission
Learn about the technical details of how AMD achieved the results in the MLPerf Training v5.1 submission.
Reproducing AMD MLPerf Training v5.1 Submission Result
Learn how to reproduce AMD's MLPerf Training v5.1 submission result.
Training AI Weather Forecasting Models on AMD Instinct
Learn how deterministic and generative AI models for synoptic-scale weather forecasting are trained efficiently on AMD Instinct MI300X GPUs using the ROCm and GeoArches tools.
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.
Day 0 Developer Guide: hipBLASLt Offline GEMM Tuning Script
Learn how to improve model performance with hipBLASLt offline tuning in our easy-to-use Day 0 tool for developers to optimize GEMM efficiency
Stability at Scale: AMD’s Full‑Stack Platform for Large‑Model Training
Primus streamlines LLM training on AMD GPUs with unified configs, multi-backend support, preflight validation, and structured logging.
Retrieval Augmented Generation (RAG) with vLLM, LangChain and Chroma
Learn AI-powered knowledge retrieval that enriches prompts with proprietary data to deliver accurate and context-aware answers
High-Accuracy MXFP4, MXFP6, and Mixed-Precision Models on AMD GPUs
Learn to leverage AMD Quark for efficient MXFP4/MXFP6 quantization on AMD Instinct accelerators with high accuracy retention.
Nitro-E: A 304M Diffusion Transformer Model for High Quality Image Generation
Nitro-E is an extremely lightweight diffusion transformer model for high-quality image generation with only 304M paramters.
Performance Profiling on AMD GPUs - Part 3: Advanced Usage
Part 3 of our GPU profiling series guides beginners through practical steps to identify and optimize kernel bottlenecks using ROCm tools
STX-B0T: Real-time AI Robot Assistant Powered by RyzenAI and ROCm
STX-B0T explores the potential of RyzenAI PCs to power robotics applications on NPU+GPU. This blog demonstrates how our hardware and software interoperate to unlock real-time perception.
Empowering Developers to Build a Robust PyTorch Ecosystem on AMD ROCm™ with Better Insights and Monitoring
Production ROCm support for N-1 to N+1 PyTorch releases is in progress. The AI Software Head-Up Dashboard shows status of PyTorch on ROCm.