<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:media="http://search.yahoo.com/mrss/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AMD GPUOpen</title><description>Gaming and graphics technologies from AMD</description><link>https://gpuopen.com/</link><atom:link href="https://gpuopen.com/feed.xml" rel="self" type="application/rss+xml"/><item><title>WMMA guide for AMD RDNA 4 architecture GPUs - part 3</title><link>https://gpuopen.com/learn/wmma-guide-amd-rdna-4-gpus-part-3/</link><guid isPermaLink="true">https://gpuopen.com/learn/wmma-guide-amd-rdna-4-gpus-part-3/</guid><description>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.</description><pubDate>Tue, 02 Jun 2026 19:02:00 GMT</pubDate><media:content type="image/jpeg" width="1280" height="720" medium="image" url="https://gpuopen.com/_astro/wmma_rdna4_pt3_featured.ClZjn8Mn.jpg"/><enclosure url="https://gpuopen.com/_astro/wmma_rdna4_pt3_featured.ClZjn8Mn.jpg" type="image/jpeg"/><category>hip</category><category>architecture</category><category>getting-started</category><category>hip</category><category>maths</category><category>memory</category><category>ml</category><category>optimization</category><category>performance</category><category>rdna</category><category>technical-articles</category></item><item><title>WMMA guide for AMD RDNA 4 architecture GPUs - part 2</title><link>https://gpuopen.com/learn/wmma-guide-amd-rdna-4-gpus-part-2/</link><guid isPermaLink="true">https://gpuopen.com/learn/wmma-guide-amd-rdna-4-gpus-part-2/</guid><description>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.</description><pubDate>Tue, 02 Jun 2026 19:01:00 GMT</pubDate><media:content type="image/jpeg" width="1280" height="720" medium="image" url="https://gpuopen.com/_astro/wmma_rdna4_pt2b_featured.CdSF_7ru.jpg"/><enclosure url="https://gpuopen.com/_astro/wmma_rdna4_pt2b_featured.CdSF_7ru.jpg" type="image/jpeg"/><category>hip</category><category>architecture</category><category>getting-started</category><category>hip</category><category>maths</category><category>memory</category><category>ml</category><category>optimization</category><category>performance</category><category>rdna</category><category>technical-articles</category></item><item><title>WMMA guide for AMD RDNA 4 architecture GPUs - part 1</title><link>https://gpuopen.com/learn/wmma-guide-amd-rdna-4-gpus-part-1/</link><guid isPermaLink="true">https://gpuopen.com/learn/wmma-guide-amd-rdna-4-gpus-part-1/</guid><description>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.</description><pubDate>Tue, 02 Jun 2026 19:00:00 GMT</pubDate><media:content type="image/jpeg" width="1280" height="720" medium="image" url="https://gpuopen.com/_astro/wmma_rdna4_pt1b_featured.DzaFBi3a.jpg"/><enclosure url="https://gpuopen.com/_astro/wmma_rdna4_pt1b_featured.DzaFBi3a.jpg" type="image/jpeg"/><category>hip</category><category>architecture</category><category>getting-started</category><category>hip</category><category>maths</category><category>memory</category><category>ml</category><category>optimization</category><category>performance</category><category>rdna</category><category>technical-articles</category></item><item><title>Announcing AMD Schola v2.1: state trees, scale, and a richer training stack</title><link>https://gpuopen.com/learn/announcing-schola-v2-1/</link><guid isPermaLink="true">https://gpuopen.com/learn/announcing-schola-v2-1/</guid><description>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.</description><pubDate>Tue, 19 May 2026 06:04:00 GMT</pubDate><media:content type="image/jpeg" width="1280" height="720" medium="image" url="https://gpuopen.com/_astro/schola-2-1-featured.BTHZI3lM.jpg"/><enclosure url="https://gpuopen.com/_astro/schola-2-1-featured.BTHZI3lM.jpg" type="image/jpeg"/><category>gpu-open-sdks</category><category>gpuopen-third-party</category><category>schola</category><category>unreal</category><category>game-development</category><category>getting-started</category><category>ml</category><category>product-blogs</category><category>technical-articles</category><category>tools</category></item><item><title>AMD DGF: An Open Geometry Compression Standard</title><link>https://gpuopen.com/learn/amd-dgf-an-open-geometry-compression-standard/</link><guid isPermaLink="true">https://gpuopen.com/learn/amd-dgf-an-open-geometry-compression-standard/</guid><description>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.</description><pubDate>Thu, 07 May 2026 20:51:00 GMT</pubDate><media:content type="image/png" width="1280" height="720" medium="image" url="https://gpuopen.com/_astro/featured-dgf-blog.B1KuAYhx.png"/><enclosure url="https://gpuopen.com/_astro/featured-dgf-blog.B1KuAYhx.png" type="image/png"/><category>dense-geometry-format</category><category>gpu-open-sdks</category><category>third-party-apis</category><category>vulkan</category><category>compression</category><category>game-development</category><category>graphics-apis</category><category>memory</category><category>optimization</category><category>performance</category><category>product-blogs</category><category>raytracing</category><category>research</category><category>technical-articles</category><category>tools</category></item><item><title>Introducing AMD DGF SuperCompression</title><link>https://gpuopen.com/learn/introducing-amd-dgf-supercompression/</link><guid isPermaLink="true">https://gpuopen.com/learn/introducing-amd-dgf-supercompression/</guid><description>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.</description><pubDate>Thu, 07 May 2026 14:37:00 GMT</pubDate><media:content type="image/jpeg" width="1280" height="720" medium="image" url="https://gpuopen.com/_astro/amd_dgf_supercompression_featured.CSXwcWXk.jpg"/><enclosure url="https://gpuopen.com/_astro/amd_dgf_supercompression_featured.CSXwcWXk.jpg" type="image/jpeg"/><category>dense-geometry-format</category><category>gpu-open-sdks</category><category>gpuopen-third-party</category><category>third-party-apis</category><category>vulkan</category><category>compression</category><category>game-development</category><category>getting-started</category><category>graphics-apis</category><category>memory</category><category>optimization</category><category>performance</category><category>product-blogs</category><category>raytracing</category><category>technical-articles</category><category>tools</category></item><item><title>Introducing MiniDXNN: MLP library for DirectX 12</title><link>https://gpuopen.com/learn/minidxnn-mlp-library-for-dx12/</link><guid isPermaLink="true">https://gpuopen.com/learn/minidxnn-mlp-library-for-dx12/</guid><description>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.</description><pubDate>Thu, 09 Apr 2026 01:21:00 GMT</pubDate><media:content type="image/jpeg" width="1280" height="720" medium="image" url="https://gpuopen.com/_astro/amd_minidxnn_featured.BEkkricX.jpg"/><enclosure url="https://gpuopen.com/_astro/amd_minidxnn_featured.BEkkricX.jpg" type="image/jpeg"/><category>driver</category><category>gpu-open-tools</category><category>microsoft</category><category>microsoft-agility-sdk</category><category>microsoft-directx</category><category>game-development</category><category>getting-started</category><category>graphics-apis</category><category>ml</category><category>performance</category><category>product-blogs</category><category>tools</category></item><item><title>How GOALS delivers sustained, competitive esports performance on handheld PCs - part 1</title><link>https://gpuopen.com/learn/how-goals-delivers-performance-handheld-pcs-part1/</link><guid isPermaLink="true">https://gpuopen.com/learn/how-goals-delivers-performance-handheld-pcs-part1/</guid><description>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.</description><pubDate>Thu, 02 Apr 2026 09:00:00 GMT</pubDate><media:content type="image/jpeg" width="1280" height="720" medium="image" url="https://gpuopen.com/_astro/goals_blog_pt1_featured.Jn9325Tb.jpg"/><enclosure url="https://gpuopen.com/_astro/goals_blog_pt1_featured.Jn9325Tb.jpg" type="image/jpeg"/><category>amd-device-library-extra</category><category>driver</category><category>unreal</category><category>architecture</category><category>game-development</category><category>memory</category><category>optimization</category><category>performance</category><category>rdna</category><category>ryzen</category><category>technical-articles</category><category>tools</category></item><item><title>How GOALS delivers sustained, competitive esports performance on handheld PCs - part 2</title><link>https://gpuopen.com/learn/how-goals-delivers-performance-handheld-pcs-part2/</link><guid isPermaLink="true">https://gpuopen.com/learn/how-goals-delivers-performance-handheld-pcs-part2/</guid><description>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.</description><pubDate>Thu, 02 Apr 2026 09:00:00 GMT</pubDate><media:content type="image/jpeg" width="1200" height="720" medium="image" url="https://gpuopen.com/_astro/goals_blog_pt2_featured.CK_aeNfD.jpg"/><enclosure url="https://gpuopen.com/_astro/goals_blog_pt2_featured.CK_aeNfD.jpg" type="image/jpeg"/><category>amd-device-library-extra</category><category>amd-fsr-framegeneration</category><category>amd-fsr-sdk</category><category>amd-fsr-upscaling</category><category>architecture</category><category>game-development</category><category>memory</category><category>optimization</category><category>performance</category><category>rdna</category><category>ryzen</category><category>technical-articles</category><category>tools</category></item><item><title>Welcome to the AMD FSR SDK 2.2, now available on GPUOpen</title><link>https://gpuopen.com/learn/amd-fsr-sdk-2-2-now-available/</link><guid isPermaLink="true">https://gpuopen.com/learn/amd-fsr-sdk-2-2-now-available/</guid><description>The AMD FSR™ &quot;Redstone&quot; SDK 2.2 update delivers ML-powered FSR Upscaling 4.1 and FSR Ray Regeneration 1.1 optimized for AMD RDNA™ 4 graphics, enabling higher visual fidelity and performance with analytical fallbacks to scale across handhelds, consoles, and PCs.</description><pubDate>Mon, 23 Mar 2026 09:00:00 GMT</pubDate><media:content type="image/png" width="1280" height="720" medium="image" url="https://gpuopen.com/_astro/featured_white_amd_fsr_sdk.CSz0w4hi.png"/><enclosure url="https://gpuopen.com/_astro/featured_white_amd_fsr_sdk.CSz0w4hi.png" 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