Data Science - Software Tools & Optimizations#
ROCm 7.2: Smarter, Faster, and More Scalable for Modern AI Workloads
we highlight the latest ROCm 7.2 enhancements for AMD Instinct GPUs, designed to boost AI and HPC performance
Accelerating Vector Search: hipVS and hipRAFT on AMD
Learn how hipVS accelerates vector search on AMD Instinct GPUs, with notebook demos for semantic search, RAG, and recommendation systems.
Introducing ROCm-LS: Accelerating Life Science Workloads with AMD Instinct™ GPUs
Accelerate life science and medical workloads with ROCm-LS, AMDs GPU-optimized toolkit for faster multidimensional image processing and vision.
Announcing hipCIM: A Cutting-Edge Solution for Accelerated Multidimensional Image Processing
Fully utilize the power of AMDs Instinct GPUs to process and interpret detailed multidimensional images with lightning speed.
Introducing ROCm-DS: GPU-Accelerated Data Science for AMD Instinct™ GPUs
Accelerate data science with ROCm-DS: AMD’s GPU-optimized toolkit for faster data frames and graph analytics using hipDF and hipGRAPH
Optimizing DeepseekV3 Inference on SGLang Using ROCm Profiling Tools
Dive into kernel-level profiling of DeepseekV3 on SGLang—identify GPU bottlenecks and boost large language model performance using ROCm
Installing ROCm from source with Spack
Install ROCm and PyTorch from source using Spack. Learn how to optimize builds, manage dependencies, and streamline your GPU software stacks.
Understanding RCCL Bandwidth and xGMI Performance on AMD Instinct™ MI300X
The blog explains the reasons behind RCCL bandwidth limitations and xGMI performance constraints, and provides actionable steps to maximize link efficiency on AMD MI300X
SmoothQuant model inference on AMD Instinct MI300X using Composable Kernel
SmoothQuant model inference on AMD Instinct MI300X using Composable Kernel
