AI - Applications & Models - Page 4#
Efficient Hyperparameter Optimization for Autonomous Driving Models with AMD Instinct GPU Partitioning
Accelerate HPO for autonomous driving models using AMD MI300X GPU partitioning for higher throughput, efficiency, and parallelism.
Accelerating Diffusers and xDiT Image Generation with MXFP4 using AMD Quark on AMD Instinct™ MI350 GPUs
Accelerate Diffusers and xDiT FLUX.1-dev image generation on AMD Instinct MI350 GPUs using AMD Quark MXFP4 quantization.
Building a GPU-Resident YOLO26 Object Detection Pipeline on the AMD Radeon™ AI PRO R9700 GPU
Build a GPU-resident object detection pipeline on AMD GPUs with rocDecode, DLPack, and MIGraphX. Frames stay in VRAM end to end.
Accelerating Large-Scale LLM Inference on AMD Instinct MI350X/MI355X with Eagle3 and AMD Quark
Learn how the AMD Quark team enables Eagle3 speculative decoding for Kimi-K2.5 and MiniMax-M2.5 on AMD Instinct MI355X GPUs with ROCm, vLLM, and InferenceX.
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.
Faster Kimi-K2.5-W4A8 Decoding with EAGLE3 on AMD Instinct™ MI325X
Add EAGLE3 speculative decoding and three MoE/FMHA kernel-tuning patches to Kimi-K2.5-W4A8 inference on AMD Instinct™ MI325X with SGLang, AITER, and FlyDSL.
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.
Comparative Analysis of Scale-Out RoCE Network Traffic Patterns and Loads in Training Large Language Models
Compares RoCE network traffic patterns and loads across GPT-4, Llama 3, DeepSeek-V2, and Grok 4.0 LLM training to guide AI infrastructure design.
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.
Technical Dive into AMD's MLPerf Training v6.0 Submission
In this blog, we share the technical details of how we accomplish the results in our MLPerf Training v6.0 submission.
Reproducing AMD MLPerf Training v6.0 Submission Result
Learn how to reproduce AMD's MLPerf Training v6.0 submission result.
Low Kruskal-Rank Adaptation
Learn how Kruskal rank can enhance LoRA by replacing the conventional matrix-rank formulation for more efficient training.