AI Blogs#
Low Kruskal-Rank Adaptation
Learn how Kruskal rank can enhance LoRA by replacing the conventional matrix-rank formulation for more efficient training.
Productionizing TurboQuant on AMD GPUs for KV-Cache-Bound LLM Inference
Productionized TurboQuant 4-bit KV-cache quantization on AMD GPUs via vLLM, with custom kernels and accuracy analysis on agentic workloads.
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.
ORBIT-2 based Weather and Climate Downscaling and Downscaled Global Forecasts on AMD Instinct
A showcase for how to run GenCast’s weather prediction with ORBIT-2’s high-resolution downscaling on AMD Instinct hardware.
Styled Text Image Generation with Eruku on AMD
Hands-on, reproducible guide to train and run Eruku on LUMI supercomputer, powered by AMD Instinct MI250X GPUs.
Elevate Your LLM Inference: Autoscaling with Ray, ROCm 7.0.0, and SkyPilot
Learn how to use multi-node and multi-cluster autoscaling in the Ray framework on ROCm 7.0.0 with SkyPilot
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.
Quickly Developing Powerful Flash Attention Using TileLang on AMD Instinct MI300X GPU
Learn how to leverage TileLang to develop your own kernel. Explore the power to fully utilize AMD GPUs
Out-of-the-Box ROLL Support on AMD GPUs: Accelerating Reinforcement Learning at Scale
Learn how to run Alibaba's ROLL RL framework out-of-the-box on AMD Instinct™ GPUs with ROCm
Enabling Speculative Speculative Decoding on MI300X
This is an introduction of speculative speculative decoding method. We enable this method on the AMD Instinct MI300x GPUs and report the results.
AI Inference on AMD Ryzen™ AI Max Processor
Hands-on: run Qwen3.5 9B–122B on Ryzen™ AI Max+ with 128GB UMA and Ollama, with generation benchmarks and a clear UMA setup path on Ubuntu/ROCm.
Diffusion-based Atmospheric Downscaling on AMD Instinct GPUs
Read this blog post to learn about and understand the theory of downscaling models. Also learn how to run a particular model, CorrDiff, on AMD GPUs.
Adapting AIM LLMs For Specific Use Cases Through Fine-Tuning in AMD AI Workbench
Learn how to adapt and fine-tune an AIM LLM in AMD AI Workbench GUI for specialization or specific use cases.
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
vLLM-ATOM: Unlocking Native AMD Performance in the vLLM Ecosystem
Use ATOM as an out-of-tree vLLM plugin to keep vLLM compatibility while enabling AMD-optimized attention, model execution, and multi-model support including Kimi-K2.5.
TraceLens: Democratizing AI Performance Analysis
Explore how TraceLens automates profiler trace analysis to pinpoint bottlenecks and optimize AI workloads.
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