Recent Posts - Page 15#
ROCm Revisited: Getting Started with HIP
New to HIP? This blog will introduce you to the HIP runtime API, its key concepts and installation and practical code examples to showcase its functionality.
ROCm Revisited: Evolution of the High-Performance GPU Computing Ecosystem
Learn how ROCm evolved to support HPC, AI, and containerized workloads with modern tools, libraries, and deployment options.
The ROCm Revisited Series
We present our ROCm Revisited Series. Discover ROCm's role in leading edge supercomputing, its growing ecosystem-from HIP, to developer tools-powering AI, HPC, and data science across multi-GPU and cluster systems
AMD’s MLPerf Training Debut: Optimizing LLM Fine-Tuning with Instinct™ GPUs
Explore the techniques we used to improve the training performance on MI300X and MI325X in our MLPerf Training 5.0 submission.
Reproduce AMD's MLPerf Training v5.0 Submission Result with Instinct™ GPUs
Follow this step-by-step guide to reproduce AMDs MLPerf 5.0 Training Submission with Instinct GPUs using ROCm
High-Throughput BERT-L Pre-Training on AMD Instinct™ GPUs: A Practical Guide
Learn how to optimize BERT-L training with mixed precision and Flash Attention v2 on AMD Instinct GPUs — follow our tested MLPerf-compliant step-by-step guide.
Scale LLM Inference with Multi-Node Infrastructure
Learn how to horizontally scale LLM inference using open-source tools on MI300X, with vLLM, nginx, Prometheus, and Grafana.
HIP 7.0 Is Coming: What You Need to Know to Stay Ahead
Get ready for HIP 7.0—explore key API changes that boost CUDA compatibility and streamline portable GPU development, start preparing your code today.
ROCm Runfile Installer Is Here!
Overview of ROCm Runfile Installer introduced in ROCm 6.4, allowing a complete single package for driver and ROCm installation without internet connectivity
From Theory to Kernel: Implement FlashAttention-v2 with CK-Tile
Learn how to implement FlashAttention-v2 with CK-Tile: minimize memory overhead, maximize compute efficiency, and scale on AMD GPUs
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
AMD Integrates llm-d on AMD Instinct MI300X Cluster For Distributed LLM Serving
AMD Integrates llm-d on AMD Instinct MI300X Cluster For Distributed LLM Serving