Data Science - Applications & Models#
Using Gradient Boosting Libraries on MI300X for Financial Risk Prediction
This blog shows how to run LightGBM and ThunderGBM GPU-accelerated training on AMD Instinct MI300X GPUs with ROCm for finance focused workloads.
Medical Imaging on MI300X: SwinUNETR Inference Optimization
A practical guide to optimizing SwinUNETR inference on AMD Instinct™ MI300X GPUs for fast 3D segmentation of tumors in medical imaging.
Plug-and-Play CuPy on ROCm: Data Analytics Acceleration Made Simple
Learn about how to enhance your analytics project with the latest AMD CuPy release.
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.
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
Medical Imaging on MI300X: Optimized SwinUNETR for Tumor Detection
Learn how to setup, run and optimize SwinUNETR on AMD MI300X GPUs for fast medical imaging 3D segmentation of tumors using fast, large ROIs.
Running SOTA AI-based Weather Forecasting models on AMD Instinct
We look at a few State of the Art AI models in weather forecasting, and demonstrate how to run them on AMD Instinct MI300X in a step-by-step fashion.
Benchmarking Reasoning Models: From Tokens to Answers
Learn how to benchmark reasoning tasks. Use Qwen3 and vLLM to test true reasoning performance, not just how fast words are generated.
Accelerate DeepSeek-R1 Inference: Integrate AITER into SGLang
Boost DeepSeek-R1 with AITER: Step-by-step SGLang integration for high-performance MoE, GEMM, and attention ops on AMD GPUs
Accelerated JPEG decoding on AMD Instinct™ GPUs with rocJPEG
Learn how to decompress JPEG files at breakneck speeds for your AI, vision, and content delivery workloads using rocJPEG and AMD Instinct GPUs.
Seismic stencil codes - part 2
Seismic Stencil Codes - Part 2: In the previous post, recall that the kernel with stencil computation in the z-direction suffered from low effective bandwidth. This low performance comes from generating substantial amounts of data to movement to global memory.
Seismic stencil codes - part 3
Seismic Stencil Codes - Part 3: In the last two blog posts, we developed a HIP kernel capable of computing high order finite differences commonly needed in seismic wave propagation.