Recent Posts - Page 2#
HPC Coding Agent - Part 2: An MCP Tool for Code Optimization with OpenEvolve
Learn how to use OpenEvolve as an MCP tool with an AI agent for agentic code optimization
MaxText-Slurm: Production-Grade LLM Training with Built-In Observability
MaxText-Slurm: A unified launch system for production-grade LLM training with observability on AMD GPU clusters.
Streamlining Recommendation Model Training on AMD Instinct™ GPUs
Explore how the ROCm training docker can be used for recommendation model training on Instinct GPUs, along with a guide on configuring the workload.
Exploring Use Cases for Scalable AI: Implementing Ray with ROCm 7 Support for Efficient ML Workflows
Ray with ROCm helps you scale AI applications for training and inference workloads on AMD GPUs.
Getting Started with AMD Resource Manager: Efficient Sharing of AMD Instinct™ GPUs for R&D Teams and AI Practitioners
Learn how to utilize the AMD Resource Manager by following this step-by-step guide on how to setup projects, share compute resources and monitor resource utilization.
JAX-AITER: Bringing AMD’s Optimized AI Kernels to JAX on ROCm™
Use JAX-AITER to run AMD’s AITER-optimized AI kernels from JAX on AMD ROCm, starting with faster multi-head attention and expanding to more ops.
PyTorch Offline Tuning with TunableOp
Learn how to accelerate PyTorch workloads with TunableOp offline tuning—record, tune separately, and deploy faster inference.
Primus-Pipeline: A More Flexible and Scalable Pipeline Parallelism Implementation
Learn how to use our flexible and scalable pipeline parallelism framework with Primus backend and AMD hardware.
FlyDSL: Expert GPU Kernel Development with the Ease of MLIR Python Native DSL on AMD GPUs
FlyDSL is a Python-first, MLIR-native DSL for expert GPU kernel development and tuning on AMD GPUs.
Introducing hipThreads: A C++ - Style Concurrency Library for AMD GPUs
Discover how hipThreads lets you write hip::thread just like std::thread and unlock GPU acceleration with minimal code changes.
Adaptive Top-K Selection: Eliminating Performance Cliffs Across All K Values on AMD GPUs
Explore adaptive Top-K on MI300X! See how auto-selection and hardware optimizations like DPP and double buffering drive peak efficiency.
Advanced MXFP4 Quantization: Combining Fine-Tuned Rotations with SmoothQuant for Near-Lossless Compression
Showcase advanced algorithms available in AMD Quark for efficient MXFP4 quantization on AMD Instinct accelerators with high accuracy retention.