Recent Posts - Page 19#
Reimagining GPU Allocation in Kubernetes: Introducing the AMD GPU DRA Driver
Explore how the AMD GPU DRA Driver brings declarative, attribute-aware GPU scheduling to Kubernetes — learn how to request and manage GPUs natively
Installing AMD HIP-Enabled GROMACS on HPC Systems: A LUMI Supercomputer Case Study
Installing AMD HIP-Enabled GROMACS on HPC Systems: A LUMI Supercomputer Case Study
Athena-PRM: Enhancing Multimodal Reasoning with Data-Efficient Process Reward Models
Learn how to utilize a data-efficient Process Reward Model to enhance the reasoning ability of the Large Language/Multimodal Models.
Introducing the AMD Network Operator v1.0.0: Simplifying High-Performance Networking for AMD Platforms
Introducing the AMD Network Operator for automating high-performance AI NIC networking in Kubernetes for AI and HPC workloads
Bridging the Last Mile: Deploying Hummingbird-XT for Efficient Video Generation on AMD Consumer-Grade Platforms
Learn how to use Hummingbird-XT and Hummingbird-XTX modelS to generate videos. Explore the video diffusion model acceleration solution, including dit distillation method and light VAE model.
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.
High-Resolution Weather Forecasting with StormCast on AMD Instinct GPU Accelerators
A showcase for how to run high-resolution weather prediction models such as StormCast on AMD Instinct hardware.
Breaking the Accuracy-Speed Barrier: How MXFP4/6 Quantization Revolutionizes Image and Video Generation
Explore how MXFP4/6, supported by AMD Instinct™ MI350 series GPUs, achieves BF16-comparable image and video generation quality.
ROCm Fork of MaxText: Structure and Strategy
Learn how the ROCm fork of MaxText mirrors upstream while enabling offline testing, minimal datasets, and platform-agnostic, decoupled workflows.
ROCm MaxText Testing — Decoupled (Offline) and Cloud-Integrated Modes
Learn how to run MaxText unit tests on AMD ROCm GPUs in offline and cloud modes for fast validation, clear reports, and reproducible workflows.
Accelerating Multimodal Inference in vLLM: The One-Line Optimization for Large Multimodal Models
Learn how to optimize multimodal model inference with batch-level data parallelism for vision encoders in vLLM, achieving up to 45% throughput gains on AMD MI300X.
SparK: Query-Aware Unstructured Sparsity with Recoverable KV Cache Channel Pruning
In this blog we will discuss SparK, a training-free, plug-and-play method for KV cache compression in large language models (LLMs).