News - AMD GPUOpen

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	New AMD Radeon Developer Tool Suite update brings shader source code, Extended PIX Markers, and command-line capture The new AMD Radeon Developer Tool Suite release delivers RGP 2.7 with shader source code viewing, instruction‑level divergence metrics, and Extended PIX Marker support, expanded hardware compatibility, and updates across RGD, RRA, RMV, RGA, and RDP.
	WMMA guide for AMD RDNA 4 architecture GPUs - part 3 Learn how to implement fast in-register matrix transpose on AMD RDNA™ 4 architecture GPUs with a WMMA-based identity trick, delivering a lightweight, memory-free alternative proven in Llama.cpp.
	WMMA guide for AMD RDNA 4 architecture GPUs - part 2 Achieve peak AMD RDNA™ 4 architecture memory bandwidth for low-precision GEMM by fusing WMMA to double the K dimension, enabling 128-bit loads for FP8/INT8, and matching hipBLAS results bit-for-bit.
	WMMA guide for AMD RDNA 4 architecture GPUs - part 1 Practical guide to fusing GEMMs on AMD RDNA™ 4 architecture, covering WMMA layout, a transpose-by-swapping A/B technique, HIP sample code, and hipBLAS-verified results used in Llama.cpp.
	Announcing AMD Schola v2.1: state trees, scale, and a richer training stack AMD Schola v2.1 deepens Unreal Engine integration, adding StateTree support, Kubernetes-oriented distributed training, stronger Minari workflows, and much more to streamline training and inference at scale.
	AMD DGF: An Open Geometry Compression Standard AMD is partnering with Samsung on a multivendor Vulkan extension for Dense Geometry Format (DGF) to help enable dramatically smaller geometry, reduced memory/latency for ray-traced real‑time 3D, and easier engine integration.
	Introducing AMD DGF SuperCompression AMD DGF SuperCompression (DGFS) cuts DGF geometry file sizes while preserving exact block reconstruction and enabling fast decode to either DGF blocks or conventional meshlets for cross-device deployment.
	Introducing MiniDXNN: MLP library for DirectX 12 MiniDXNN is a native HLSL and DirectX 12 library for lightning-fast MLP inference leveraging AMD Radeon™ RX 9000 series matrix cores via cooperative vector APIs, delivering optimized kernels, samples, full source and docs to remove compute interop friction.
	How GOALS delivers sustained, competitive esports performance on handheld PCs - part 1 The first part of a developer-first look at how GOALS leverages AMD Ryzen APUs and the ADLX SDK to implement a system that reduces power, fan noise and carbon footprint across legacy and handheld hardware while preserving competitive performance.
	How GOALS delivers sustained, competitive esports performance on handheld PCs - part 2 The second part of how GOALS optimizes AMD Ryzen handheld PC gaming performance using AMD FSR Upscaling and Frame Generation, handcrafted device profiles, football-aware animation budgeting, and battery-aware scalability for sustained play.