AI - Applications & Models - Page 3#
QuickReduce FP4 Quantization and Benchmarking on MI355
Learn how QuickReduce uses FP4 quantization to accelerate all-reduce communication and evaluate its performance on AMD Instinct MI355 GPUs.
Semantic Fencing of Video Streams Using Embedding Splits from Vision Foundation Models
Learn how to semantically split vision datasets using foundation model embeddings on AMD GPUs to reduce leakage and improve evaluation.
Further Accelerating Kimi-K2.5 on AMD Instinct™ MI325X: W4A8 & W8A8 Quantization with AMD Quark
Quantize Kimi-K2.5 to W4A8 and W8A8 using AMD Quark and serve on MI325X with FlyDSL and AITER for further inference acceleration.
Accelerating ComfyUI Workflows on AMD Instinct™ MI355X GPUs with ROCm
We show that the MI355X delivers better performance than the B200 for ComfyUI after enabling PyTorch attention for gfx950.
AMD-Powered 3D Gaussian Splatting for Autonomous Driving Scenes
Run Street Gaussians on AMD Instinct MI300: migrate to latest gsplat, install on ROCm, and render dynamic street scenes.
Accelerating Mixture-of-Experts Execution with FarSkip-Collective Models
Explore a new MoE architecture designed for native computation-communication overlap, enabling efficient distributed execution.
FLy: A New Paradigm for Speculative Decoding — Accepting Semantically Correct Drafts Beyond Exact Match
This blog explores a new training-free loosely speculative decoding method, that can accept mismatches that are semantically valid and speedup original SPD method.
Serving CTR Recommendation Models with Triton Inference Server using the ONNX Runtime Backend
Learn how to deploy AI models on AMD GPUs with Triton Inference Server, now supporting ONNX Runtime and Python backends, and see performance benchmarks.
FlashInfer on ROCm: High‑Throughput Prefill Attention via AITER
FlashInfer is an open-source library for accelerating LLM serving that is now supported by ROCm.
Customizing Kernels with hipBLASLt TensileLite GEMM Tuning - Advanced User Guide
Master hipBLASLt TensileLite Tuning. Learn to build custom kernels that deliver 150%-250% faster GEMM performance on AMD Instinct™ MI300X GPUs
Deploy and Customize AMD Solution Blueprints
Learn how to deploy and customize AMD Solution Blueprints — from default deployment to swapping and reusing AMD Inference Microservices across multiple blueprints.
AMD Instinct™ GPUs MLPerf Inference v6.0 Submission
In this blog, we share the technical details of how we accomplish the results in our MLPerf Inference v6.0 submission.