[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"portal-settings:figure:de":3,"public-menus:all":45,"post:directx-is-becoming-an-ml-platform-what-linear-algebra-and-neural-shaders-mean-for-future-games:de":531,"related:post:directx-is-becoming-an-ml-platform-what-linear-algebra-and-neural-shaders-mean-for-future-games:de:1":2059},{"statusCode":4,"data":5,"message":44},200,{"tenantId":6,"lang":7,"defaultLang":8,"siteUrl":9,"contactEmail":10,"brandName":11,"logoUrl":12,"siteName":11,"siteDescription":13,"ogImage":14,"robotsIndex":15,"socialLinks":14,"reservedSlugs":14,"seoPolicy":16},"figure","de","en","https:\u002F\u002Ffigure.rocks","info@stajic.de","Figure Rocks","\u002Ffavicon-32x32.png","",null,true,{"branding":17,"relatedContent":18,"crossDomainLinks":19},{"logoUrl":12},{"enabled":15},[20,23,26,29,32,35,38,41],{"url":21,"label":22,"isActive":15,"showInFooter":15,"includeInSameAs":15},"https:\u002F\u002Floving.rocks","loving.rocks",{"url":24,"label":25,"isActive":15,"showInFooter":15,"includeInSameAs":15},"https:\u002F\u002Fstajic.de","stajic.de",{"url":27,"label":28,"isActive":15,"showInFooter":15,"includeInSameAs":15},"https:\u002F\u002Fbazify.com","bazify.com",{"url":30,"label":31,"isActive":15,"showInFooter":15,"includeInSameAs":15},"https:\u002F\u002Fbazify.de","bazify.de",{"url":33,"label":34,"isActive":15,"showInFooter":15,"includeInSameAs":15},"https:\u002F\u002F2mesta.com","2mesta.com",{"url":36,"label":37,"isActive":15,"showInFooter":15,"includeInSameAs":15},"https:\u002F\u002F2mesta.de","2mesta.de",{"url":39,"label":40,"isActive":15,"showInFooter":15,"includeInSameAs":15},"https:\u002F\u002Fbazify.at","bazify.at",{"url":42,"label":43,"isActive":15,"showInFooter":15,"includeInSameAs":15},"https:\u002F\u002Fweb-hoch3.de","web-hoch3.de","Portal settings resolved",[46],{"id":47,"name":48,"location":49,"isActive":15,"isDefault":15,"items":50},2,"Main Menu","sidebar",[51,65,176,298,391,467],{"id":52,"title":53,"url":61,"target":62,"icon":63,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":64},"1",{"de":54,"en":55,"es":56,"fr":57,"it":55,"ru":58,"sr":59,"zh":60},"Startseite","Home","Inicio","Accueil","Главная","Početna","首页","\u002F","_self","i-lucide-home",[],{"id":66,"title":67,"url":69,"target":62,"icon":70,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":72},"2",{"de":68,"en":68,"es":68,"fr":68,"it":68,"ru":68,"sr":68,"zh":68},"amiibo","\u002Famiibo","i-lucide-scan-line","custom",[73,85,92,106,120,134,148,162],{"id":74,"title":75,"url":69,"target":62,"icon":83,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":84},"2-1",{"de":76,"en":77,"es":78,"fr":79,"it":79,"ru":80,"sr":81,"zh":82},"amiibo-Hub","amiibo Hub","Centro amiibo","Hub amiibo","Хаб amiibo","amiibo centar","amiibo 中心","i-lucide-layout-grid",[],{"id":86,"title":87,"url":89,"target":62,"icon":90,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":91},"1772724791061",{"de":88,"en":88},"Franchise","\u002Famiibo\u002Ffranchise","i-lucide-star",[],{"id":93,"title":94,"url":103,"target":62,"icon":104,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":105},"2-3",{"de":95,"en":96,"es":97,"fr":98,"it":99,"ru":100,"sr":101,"zh":102},"Region & Verpackung (EU\u002FUS\u002FJP)","Region & Packaging (EU\u002FUS\u002FJP)","Región y embalaje (UE\u002FEE. UU.\u002FJP)","Région & Emballage (UE\u002FUS\u002FJP)","Regione & Confezione (EU\u002FUS\u002FJP)","Регион & упаковка (EU\u002FUS\u002FJP)","Region & pakovanje (EU\u002FUS\u002FJP)","地区 & 包装 (EU\u002FUS\u002FJP)","\u002Famiibo-library\u002Famiibo-editions-and-regions","i-lucide-globe",[],{"id":107,"title":108,"url":117,"target":62,"icon":118,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":119},"2-4",{"de":109,"en":110,"es":111,"fr":112,"it":113,"ru":114,"sr":115,"zh":116},"Schnellidentifikations-Checkliste","Fast Identification Checklist","Lista de identificación rápida","Liste d'identification rapide","Checklist identificazione rapida","Чек-лист быстрой идентификации","Kontrolna lista za brzu identifikaciju","快速识别清单","\u002Famiibo\u002Fidentify-checklist","i-lucide-list-checks",[],{"id":121,"title":122,"url":131,"target":62,"icon":132,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":133},"2-6",{"de":123,"en":124,"es":125,"fr":126,"it":127,"ru":128,"sr":129,"zh":130},"Tipps für Sealed-Sammlungen","Sealed Collection Tips","Consejos de colección sellada","Conseils collection scellée","Consigli collezione sigillata","Советы по коллекции Sealed","Saveti za zapečaćene kolekcije","密封收藏贴士","\u002Famiibo\u002Fsealed-tips","i-lucide-shield-check",[],{"id":135,"title":136,"url":145,"target":62,"icon":146,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":147},"2-5",{"de":137,"en":138,"es":139,"fr":140,"it":141,"ru":142,"sr":143,"zh":144},"Zustand & Bewertung","Condition & Grading","Estado & Graduación","État & Évaluation","Condizioni & Valutazione","Состояние & Оценка","Stanje & ocenjivanje","品相与分级","\u002Famiibo-library\u002Famiibo-condition-and-grading","i-lucide-badge-check",[],{"id":149,"title":150,"url":159,"target":62,"icon":160,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":161},"2-2",{"de":151,"en":152,"es":153,"fr":154,"it":155,"ru":156,"sr":157,"zh":158},"Ausgaben & Nachdrucke","Editions & Reprints","Ediciones & Reimpresiones","Éditions & Réimpressions","Edizioni & ristampe","Издания & переиздания","Izdanja & reizdanja","版本 & 重印","\u002Famiibo\u002Fcollecting\u002F","i-lucide-layers",[],{"id":163,"title":164,"url":173,"target":62,"icon":174,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":175},"2-7",{"de":165,"en":166,"es":167,"fr":168,"it":169,"ru":170,"sr":171,"zh":172},"Nachdruck-Timeline","Reprint Timeline","Cronología de reimpresión","Chronologie des réimpressions","Cronologia ristampe","Хронология переизданий","Hronologija reprinta","重印时间轴","\u002Freference\u002Ftimelines\u002Famiibo-reprint-timeline","i-lucide-timer",[],{"id":177,"title":178,"url":187,"target":62,"icon":188,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":189},"3",{"de":179,"en":180,"es":181,"fr":182,"it":183,"ru":184,"sr":185,"zh":186},"Spiele","Games","Juegos","Jeux","Giochi","Игры","Igre","游戏","\u002Fgames","i-lucide-gamepad-2",[190,202,216,230,244,257,271,285],{"id":191,"title":192,"url":187,"target":62,"icon":83,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":201},"3-1",{"de":193,"en":194,"es":195,"fr":196,"it":197,"ru":198,"sr":199,"zh":200},"Spiele-Hub","Games Hub","Centro de juegos","Hub de jeux","Hub Giochi","Игровой центр","Centar za igre","游戏中心",[],{"id":203,"title":204,"url":213,"target":62,"icon":214,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":215},"1-1",{"de":205,"en":206,"es":207,"fr":208,"it":209,"ru":210,"sr":211,"zh":212},"Neu & Angesagt","New & Trending","Novedades & Tendencias","Nouveautés & Tendances","Novità & Tendenze","Новинки & тренды","Novo & Popularno","新品 & 热门","\u002Fnews\u002Fgaming-news","i-lucide-sparkles",[],{"id":217,"title":218,"url":227,"target":62,"icon":228,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":229},"1-2",{"de":219,"en":220,"es":221,"fr":222,"it":223,"ru":224,"sr":225,"zh":226},"Angebote","Deals","Ofertas","Offres","Offerte","Акции","Ponude","优惠","\u002Fdeals","i-lucide-badge-percent",[],{"id":231,"title":232,"url":241,"target":62,"icon":242,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":243},"1-3",{"de":233,"en":234,"es":235,"fr":236,"it":237,"ru":238,"sr":239,"zh":240},"Release-Kalender","Release Calendar","Calendario de lanzamientos","Calendrier des sorties","Calendario delle uscite","Календарь релизов","Kalendar izdanja","发布日历","\u002Freleases","i-lucide-calendar-days",[],{"id":245,"title":246,"url":254,"target":62,"icon":255,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":256},"3-2",{"de":247,"en":248,"es":249,"fr":250,"it":251,"sr":252,"zh":253},"amiibo-kompatible Spiele","amiibo-Compatible Games","Juegos compatibles con Amiibo","Jeux compatibles Amiibo","Giochi compatibili con amiibo","Amiibo kompatibilne igre","Amiibo 兼容游戏","\u002Freference\u002Fcompatibility","i-lucide-check-circle-2",[],{"id":258,"title":259,"url":268,"target":62,"icon":269,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":270},"3-3",{"de":260,"en":261,"es":262,"fr":263,"it":264,"ru":265,"sr":266,"zh":267},"Wie amiibo funktionieren","How amiibo work","Cómo funcionan los Amiibo","Comment fonctionnent les Amiibo","Come funzionano gli Amiibo","Как работают Amiibo","Kako Amiibo rade","Amiibo 如何运作","\u002Fgames\u002Fhow-amiibo-unlocks-work","i-lucide-puzzle",[],{"id":272,"title":273,"url":282,"target":62,"icon":283,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":284},"3-4",{"de":274,"en":275,"es":276,"fr":277,"it":278,"ru":279,"sr":280,"zh":281},"Beste Amiibo pro Spiel","Best amiibo per Game","Mejores Amiibo por juego","Meilleurs Amiibo par jeu","Migliori Amiibo per gioco","Лучшие Amiibo по играм","Najbolji Amiibo po igri","各游戏最佳 Amiibo","\u002Fgames\u002Fbest-amiibo-per-game","i-lucide-award",[],{"id":286,"title":287,"url":295,"target":62,"icon":296,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":297},"3-5",{"de":288,"en":289,"es":290,"fr":291,"it":292,"ru":293,"sr":294},"Freischaltbares & Belohnungen","Unlockables & Rewards","Desbloqueables & Recompensas","Déblocables & Récompenses","Sbloccabili & Ricompense","Разблокировки & награды","Otključavanja & nagrade","\u002Fgames\u002Funlocks-and-benefits","i-lucide-gift",[],{"id":299,"title":300,"url":308,"target":62,"icon":309,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":310},"4",{"de":301,"en":302,"es":303,"it":304,"ru":305,"sr":306,"zh":307},"Sammeln","Collecting","Coleccionismo","Collezionismo","Коллекционирование","Kolekcionarstvo","收藏","\u002Fcollecting","i-lucide-gem",[311,322,336,349,363,377],{"id":312,"title":313,"url":320,"target":62,"icon":83,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":321},"4-1",{"de":314,"en":315,"fr":316,"it":317,"ru":318,"zh":319},"Sammel-Hub","Collecting Hub","Hub de collecte","Hub di raccolta","Центр сбора","收藏中心","\u002Famiibo\u002Fcollecting",[],{"id":323,"title":324,"url":333,"target":62,"icon":334,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":335},"4-2",{"de":325,"en":326,"es":327,"fr":328,"it":329,"ru":330,"sr":331,"zh":332},"Kaufberatung","Buying Guide","Guía de compra","Guide d'achat","Guida all'acquisto","Гид покупателя","Vodič za kupovinu","购买指南","\u002Famiibo-library\u002Famiibo-buying-smart","i-lucide-shopping-bag",[],{"id":337,"title":338,"url":346,"target":62,"icon":347,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":348},"4-3",{"de":339,"en":339,"es":340,"fr":341,"it":342,"ru":343,"sr":344,"zh":345},"Fake vs Real","Falso vs. Real","Faux vs Vrai","Falso vs Vero","Фейк vs Оригинал","Lažno vs Pravo","真假对比","\u002Famiibo-library\u002Famiibo-buying-smart\u002Favoid-fake-listings","i-lucide-scan",[],{"id":350,"title":351,"url":360,"target":62,"icon":361,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":362},"4-4",{"de":352,"en":353,"es":354,"fr":355,"it":356,"ru":357,"sr":358,"zh":359},"Aufbewahrung & Präsentation","Storage & Display","Almacenamiento & exhibición","Rangement & Présentation","Contenitori & Esposizione","Хранение & витрины","Odlaganje & izlaganje","存储 & 展示","\u002Famiibo-library\u002Famiibo-care-and-storage","i-lucide-box",[],{"id":364,"title":365,"url":374,"target":62,"icon":375,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":376},"4-5",{"de":366,"en":367,"es":368,"fr":369,"it":370,"ru":371,"sr":372,"zh":373},"Preisübersicht","Price Guide","Guía de precios","Guide des prix","Guida ai prezzi","Гид по ценам","Cenovnik","价格指南","\u002Fcollections\u002Fprice-guide","i-lucide-bar-chart-3",[],{"id":378,"title":379,"url":388,"target":62,"icon":389,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":390},"4-6",{"de":380,"en":381,"es":382,"fr":383,"it":384,"ru":385,"sr":386,"zh":387},"Raritäten","Rare Finds","Hallazgos únicos","Trouvailles rares","Pezzi rari","Редкие находки","Retki nalazi","稀有发现","\u002Fcollections\u002Frare-and-notable","i-lucide-trophy",[],{"id":392,"title":393,"url":401,"target":62,"icon":402,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":403},"5",{"de":394,"en":395,"es":396,"fr":395,"it":397,"ru":398,"sr":399,"zh":400},"Technik","Tech","Tecnología","Tecnologia","Технологии","Tehnologija","科技","\u002Ftech","i-lucide-cpu",[404,415,427,440,453],{"id":405,"title":406,"url":401,"target":62,"icon":83,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":414},"5-1",{"de":407,"en":407,"es":408,"fr":409,"it":410,"ru":411,"sr":412,"zh":413},"Tech Hub","Centro tecnológico","Hub Tech","Hub Tecnologico","Технохаб","Tehnološki centar","科技中心",[],{"id":416,"title":417,"url":424,"target":62,"icon":425,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":426},"5-2",{"de":418,"en":419,"fr":420,"it":421,"ru":422,"zh":423},"Audio- & Mikrofonqualität","Audio & Mic Quality","Qualité audio & micro","Qualità audio & mic","Качество звука & микрофона","音频 & 麦克风质量","\u002Fgear\u002Faudio","i-lucide-mic",[],{"id":428,"title":429,"url":437,"target":62,"icon":438,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":439},"5-3",{"de":430,"en":431,"es":432,"fr":433,"it":434,"sr":435,"zh":436},"Controller & Zubehör","Controllers & Accessories","Mandos & accesorios","Manettes & accessoires","Controller & Accessori","Kontroleri & dodatna oprema","控制器 & 配件","\u002Fgear\u002Fcontrols","i-lucide-joystick",[],{"id":441,"title":442,"url":450,"target":62,"icon":451,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":452},"5-4",{"de":443,"en":444,"es":445,"fr":446,"it":447,"ru":448,"sr":449},"Displays & Aufnahme","Displays & Capture","Pantallas & Captura","Écrans & Capture","Display & Acquisizione","Дисплеи & Захват","Ekrani & snimanje","\u002Fgear\u002Fdisplays","i-lucide-monitor",[],{"id":454,"title":455,"url":464,"target":62,"icon":465,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":466},"5-5",{"de":456,"en":457,"es":458,"fr":459,"it":460,"ru":461,"sr":462,"zh":463},"Netzwerkstabilität","Network Stability","Estabilidad de la red","Stabilité du réseau","Stabilità della rete","Стабильность сети","Stabilnost mreže","网络稳定性","\u002Fplaybooks\u002Fnetwork-stability","i-lucide-wifi",[],{"id":468,"title":469,"url":477,"target":62,"icon":478,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":479},"6",{"de":470,"en":470,"es":471,"fr":472,"it":473,"ru":474,"sr":475,"zh":476},"Shop","Tienda","Boutique","Negozio","Магазин","Prodavnica","商店","\u002Fshop","i-lucide-shopping-cart",[480,492,498,506,519],{"id":481,"title":482,"url":477,"target":62,"icon":490,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":491},"6-1",{"de":483,"en":484,"es":485,"fr":486,"ru":487,"sr":488,"zh":489},"Shop-Hub","Shop Hub","Centro de compras","Espace Boutique","Центр магазина","Centar za kupovinu","购物中心","i-lucide-store",[],{"id":493,"title":494,"url":496,"target":62,"icon":70,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":497},"6-2",{"de":68,"en":68,"es":495,"fr":495,"it":495,"sr":495,"zh":495},"Amiibo","\u002Famiibo-shop",[],{"id":499,"title":500,"url":503,"target":62,"icon":504,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":505},"6-3",{"de":501,"en":501,"es":501,"fr":501,"it":501,"ru":501,"sr":501,"zh":502},"LEGO","乐高","\u002Flego-shop","i-lucide-blocks",[],{"id":507,"title":508,"url":516,"target":62,"icon":517,"isActive":15,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":518},"6-4",{"de":509,"en":510,"es":511,"fr":512,"it":513,"sr":514,"zh":515},"Figuren & Sammlerstücke","Figures & Collectibles","Figuras & Coleccionables","Figurines & Objets de collection","Figure & Collezionismo","Figure & kolekcionarstvo","手办 & 收藏品","\u002Fshop\u002Ffigures","i-lucide-package",[],{"id":520,"title":521,"url":528,"target":62,"icon":529,"isActive":15,"type":71,"productId":14,"categoryId":14,"shopCategoryId":14,"articleId":14,"pageId":14,"portfolioId":14,"children":530},"6-5",{"de":522,"en":522,"fr":523,"it":524,"ru":525,"sr":526,"zh":527},"Gaming Gear","Équipement gaming","Accessori gaming","Игровое снаряжение","Gejming oprema","游戏装备","\u002Fgaming-gear-shop","i-lucide-headphones",[],{"statusCode":4,"data":532,"message":2058},{"id":533,"title":534,"slug":535,"content":536,"contentJson":537,"excerpt":1179,"featuredImage":1180,"featuredImageAlt":1181,"featuredImageCaption":14,"featuredImageTitle":14,"featuredImageCopyright":14,"featuredImageAuthor":14,"featuredImageSourceUrl":14,"featuredImageLicense":14,"featuredImageIsAiGenerated":720,"status":1182,"publishedAt":1183,"createdAt":1184,"updatedAt":1185,"seoLocalePaths":1186,"categories":1195,"author":1216,"translations":1220},"446","DirectX wird zu einer ML-Plattform: Was lineare Algebra und neuronale Shader für zukünftige Spiele bedeuten","directx-is-becoming-an-ml-platform-what-linear-algebra-and-neural-shaders-mean-for-future-games","\u003Cp>DirectX ist nicht mehr nur eine Grafik-API, die traditionelle Shader an die GPU sendet. Microsoft fügt maschinelle Lernprimitive direkt zu HLSL hinzu und einen zweiten Pfad zum Ausführen größerer ML-Graphen innerhalb des DirectX-Ökosystems. Das verändert, wo neuronales Rendering in zukünftigen PC-Spielen stattfinden kann.\u003C\u002Fp>\n\u003Caside class=\"editorjs-callout editorjs-callout--info my-6 rounded-xl border p-5 border-blue-300 bg-blue-50 dark:border-blue-900 dark:bg-blue-950\u002F20\" role=\"note\">\u003Cstrong class=\"block mb-2 text-gray-900 dark:text-gray-100\">Direkte Antwort\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">\u003Cstrong>DirectX wird zu einer ML-fähigen Grafikplattform.\u003C\u002Fstrong> Kleine neuronale Arbeitslasten können direkt in Shadern über DX Linear Algebra ausgeführt werden, während größere Modelle vom DirectX Compute Graph Compiler anvisiert werden. Das Ziel ist es, Spiel-Engines die Nutzung von GPU-KI-Hardware zu ermöglichen, ohne für jede Technik einen separaten herstellerspezifischen Pfad zu erstellen.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Caside class=\"editorjs-callout editorjs-callout--note my-6 rounded-xl border p-5 border-gray-300 bg-gray-50 dark:border-gray-700 dark:bg-gray-900\u002F40\" role=\"note\">\u003Cstrong class=\"block mb-2 text-gray-900 dark:text-gray-100\">Aktueller Status\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">Stand September 2026 ist \u003Cstrong>DX Linear Algebra noch eine Vorschau-Technologie\u003C\u002Fstrong> im Shader Model 6.10 \u002F Agility SDK Vorschau-Pfad. Microsoft kündigte den DirectX Compute Graph Compiler für die private Vorschau an, nicht als breit verfügbares Retail-Feature. Dieser Artikel erklärt die Architektur und Richtung, nicht die Behauptung, dass jedes aktuelle Spiel es heute nutzen kann.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Cnav class=\"editorjs-toc\" data-editorjs-toc=\"true\" aria-label=\"Inhalt\">\u003Cstrong class=\"editorjs-toc__title\">Inhalt\u003C\u002Fstrong>\u003Col class=\"editorjs-toc__list editorjs-toc__list--depth-0\">\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-5\" class=\"editorjs-toc__link\">Warum neuronales Rendering neue DirectX-Primitive benötigt\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-9\" class=\"editorjs-toc__link\">Das zweistufige DirectX ML-Modell\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-12\" class=\"editorjs-toc__link\">Was DX Linear Algebra einem Shader tatsächlich bietet\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-17\" class=\"editorjs-toc__link\">Warum Cooperative Vector nur der Anfang war\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-21\" class=\"editorjs-toc__link\">Was kann tatsächlich in einem Shader ausgeführt werden?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-24\" class=\"editorjs-toc__link\">Warum dies für den Texturspeicher wichtig ist\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-29\" class=\"editorjs-toc__link\">Warum vollständige Modelle einen anderen Weg benötigen\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-33\" class=\"editorjs-toc__link\">Die Grenze zwischen Shader und Graph\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-35\" class=\"editorjs-toc__link\">Warum herstellerübergreifende Unterstützung wichtiger ist als ein weiteres KI-Feature\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-40\" class=\"editorjs-toc__link\">Welche Hardware unterstützt die aktuelle Vorschau?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-44\" class=\"editorjs-toc__link\">Neural Rendering wird zur Infrastruktur\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-49\" class=\"editorjs-toc__link\">Der Neural Rendering Stack wird zunehmend geschichtet\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-51\" class=\"editorjs-toc__link\">Warum einheitliches Profiling wichtig ist\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-55\" class=\"editorjs-toc__link\">Das bedeutet nicht, dass jeder Shader zu einem neuronalen Netzwerk wird\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-59\" class=\"editorjs-toc__link\">Der neuronale Shader-Werttest\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-61\" class=\"editorjs-toc__link\">Was das für Gamer bedeutet\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-65\" class=\"editorjs-toc__link\">Was würde diese Antwort ändern?\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-69\" class=\"editorjs-toc__link\">Einschränkungen\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-72\" class=\"editorjs-toc__link\">Fazit\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-76\" class=\"editorjs-toc__link\">FAQ\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-78\" class=\"editorjs-toc__link\">Glossar\u003C\u002Fa>\u003C\u002Fli>\u003Cli class=\"editorjs-toc__item\">\u003Ca href=\"#section-80\" class=\"editorjs-toc__link\">Primärquellen\u003C\u002Fa>\u003C\u002Fli>\u003C\u002Fol>\u003C\u002Fnav>\n\u003Ch2 id=\"section-5\">Warum neuronales Rendering neue DirectX-Primitive benötigt\u003C\u002Fh2>\n\u003Cp>Moderne GPUs enthalten bereits spezialisierte Hardware für Matrixoperationen, die im maschinellen Lernen verwendet werden. Das Problem für einen Spielentwickler ist nicht nur, ob diese Hardware existiert, sondern wie man effizient aus einer Echtzeit-Grafikpipeline darauf zugreift.\u003C\u002Fp>\n\u003Cp>Microsoft erforschte dies zuerst mit Cooperative Vector-Unterstützung. Im Jahr 2026 entwickelte sich diese Arbeit zu einem breiteren DirectX Linear Algebra-Design, das sowohl Vektor-Matrix- als auch Matrix-Matrix-Operationen unterstützt.\u003C\u002Fp>\n\u003Cp>Das ist wichtig, weil verschiedene neuronale Rendering-Aufgaben unterschiedliche Formen haben. Ein winziges Modell, das Materialverhalten pro Pixel bewertet, ist nicht die gleiche Arbeitslast wie ein großes Super-Resolution- oder Denoising-Diagramm.\u003C\u002Fp>\n\u003Ch2 id=\"section-9\">Das zweistufige DirectX ML-Modell\u003C\u002Fh2>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Zwei Wege, wie ML in die DirectX-Grafikpipeline gelangen kann\u003C\u002Fh3>\u003Cdiv class=\"flex flex-col sm:flex-row gap-3\">\u003Cdiv class=\"editorjs-process__step min-w-0 flex-1 rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">1\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">1. Shader-Level-ML\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Kleine neuronale oder linear-algebraische Arbeitslasten werden direkt aus HLSL neben traditionellem Shader-Code ausgeführt.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__arrow shrink-0 self-center text-xl text-gray-400 rotate-90 sm:rotate-0\" aria-hidden=\"true\">→\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0 flex-1 rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">2\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">2. DX Linear Algebra\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Der Shader kann hardwarebeschleunigte Vektor- und Matrixoperationen anfordern, anstatt jedes ML-Primitiv manuell zu implementieren.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__arrow shrink-0 self-center text-xl text-gray-400 rotate-90 sm:rotate-0\" aria-hidden=\"true\">→\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0 flex-1 rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">3\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">3. Modell-Level-ML\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Größere neuronale Netzwerke werden als vollständige Berechnungsgraphen dargestellt, anstatt als handgeschriebene Shader-Fragmente.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__arrow shrink-0 self-center text-xl text-gray-400 rotate-90 sm:rotate-0\" aria-hidden=\"true\">→\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0 flex-1 rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">4\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">4. DirectX Compute Graph Compiler\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Microsofts geplanter Compiler-Pfad analysiert und senkt diese Graphen in optimierte GPU-Arbeitslasten, die in D3D12-Warteschlangen und Befehlslisten integriert sind.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Caside class=\"editorjs-callout editorjs-callout--success my-6 rounded-xl border p-5 border-emerald-300 bg-emerald-50 dark:border-emerald-900 dark:bg-emerald-950\u002F20\" role=\"note\">\u003Cstrong class=\"block mb-2 text-gray-900 dark:text-gray-100\">Der einfache Unterschied\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">\u003Cstrong>DX Linear Algebra:\u003C\u002Fstrong> kleine ML-Mathematik in den Shader einfügen.\u003Cbr>\u003Cstrong>Compute Graph Compiler:\u003C\u002Fstrong> ein größeres ML-Modell als Graph in die Engine bringen.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Ch2 id=\"section-12\">Was DX Linear Algebra einem Shader tatsächlich bietet\u003C\u002Fh2>\n\u003Cp>Traditionelles HLSL ist um Grafik- und Compute-Operationen herum aufgebaut. Neuronale Arbeitslasten stützen sich stark auf lineare Algebra: Vektoren, Matrizen, Multiplikation, Akkumulation und Datenlayouts, die für diese Operationen optimiert sind.\u003C\u002Fp>\n\u003Cp>Die Shader Model 6.10-Vorschau fügt erstklassige Matrix-APIs hinzu, damit Entwickler diese Arbeitslasten direkter ausdrücken und den Treiber sie auf spezialisierte Hardware abbilden lassen können.\u003C\u002Fp>\n\u003Cp>Microsofts Vorschau vom April 2026 beschreibt dies ausdrücklich als einen einheitlichen Pfad für neuronales Rendering, ML und Bildverarbeitungs-Arbeitslasten und nicht als eine reine Grafikfunktion.\u003C\u002Fp>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Traditionelle Shader-Mathematik vs. ML-orientierte Shader-Mathematik\u003C\u002Fh3>\u003Cdiv class=\"overflow-x-auto\">\u003Ctable class=\"w-full border-collapse\">\u003Cthead>\u003Ctr>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left dark:border-gray-700 dark:bg-gray-900\">\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Traditioneller Shader-Fokus\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">ML-orientierter Fokus\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Typische Arbeit\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Hardware-Pfad\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Entwicklerausdruck\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-17\">Warum Cooperative Vector nur der Anfang war\u003C\u002Fh2>\n\u003Cp>Cooperative Vector ermöglichte es Shader-Threads, Vektor-Matrix-Arbeit anzufordern, die Treiber auf spezialisierte Hardware abbilden konnten. Das war nützlich für hochgradig parallele Pro-Pixel-Arbeitslasten.\u003C\u002Fp>\n\u003Cp>Microsoft kam später zu dem Schluss, dass viele wichtige ML-Workloads mehr als Vektor-Matrix-Operationen benötigen. Superauflösung, Entrauschen, zeitliche Rekonstruktion, größere Bildmodelle und allgemeine Inferenz können Matrix-Matrix-Operationen und gemeinsame Arbeit über viele Threads hinweg erfordern.\u003C\u002Fp>\n\u003Cp>DX Linear Algebra erweitert daher das Modell, anstatt Cooperative Vector als die endgültige Abstraktion zu behandeln.\u003C\u002Fp>\n\u003Ch2 id=\"section-21\">Was kann tatsächlich in einem Shader ausgeführt werden?\u003C\u002Fh2>\n\u003Cp>Die interessantesten ML-Workloads auf Shader-Ebene sind klein genug, um in der Nähe der Grafikdaten ausgeführt zu werden, auf denen sie operieren.\u003C\u002Fp>\n\u003Cdiv class=\"overflow-x-auto\">\u003Ctable class=\"w-full border-collapse\">\u003Cthead>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-2 text-left font-semibold\">Workload\u003C\u002Fth>\u003Cth class=\"border border-gray-300 px-4 py-2 text-left font-semibold\">Warum ML auf Shader-Ebene passt\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Neuronale Texturkompression\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Ein kleines Netzwerk kann Texturinformationen in der Nähe des Punktes rekonstruieren, an dem der Shader sie benötigt\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Neuronale Materialbewertung\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Eine gelernte Funktion kann teure handgeschriebene Materialmathematik ersetzen oder ergänzen\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Neuronales Radiance-Caching\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Inferenz pro Pixel oder lokal kann Beleuchtungsinformationen aus gelerntem Szenenverhalten schätzen\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Kleine Entrauschungs-\u002FRekonstruktionskerne\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">ML-Operationen können direkt neben der Rendering-Stufe liegen, die sie verbessern\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Bildverarbeitungsinferenz\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-2\">Matrixoperationen können in die GPU-Verarbeitung eingebettet werden, ohne eine separate externe Laufzeitumgebung\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003C\u002Fdiv>\n\u003Ch2 id=\"section-24\">Warum dies für den Texturspeicher wichtig ist\u003C\u002Fh2>\n\u003Cp>Eines von Microsofts wiederkehrenden Beispielen ist die neuronale Texturkompression.\u003C\u002Fp>\n\u003Cp>Anstatt jeden Texturkanal mit herkömmlicher Genauigkeit zu speichern, kann ein Spiel eine kompaktere Darstellung speichern und ein kleines neuronales Netzwerk verwenden, um Details während des Renderings zu rekonstruieren.\u003C\u002Fp>\n\u003Cp>Das tauscht etwas GPU-Inferenzarbeit gegen geringeren Speicher- oder Speicherdruck. Der genaue Nutzen hängt von der Technik und der Hardware ab, aber die architektonische Änderung ist wichtig: Einige visuelle Details können zu Berechnung anstatt zu gespeicherten Daten werden.\u003C\u002Fp>\n\u003Caside class=\"editorjs-referral my-6\">\u003Ca href=\"https:\u002F\u002Ffigure.rocks\u002Fde\u002Fblog\u002Fvram-usage-is-not-vram-requirement-why-a-full-memory-meter-does-not-tell-the-whole-story\" class=\"flex flex-col sm:flex-row gap-4 rounded-xl border border-gray-200 dark:border-gray-700 p-4 transition hover:border-primary-500\">\u003Cdiv class=\"min-w-0 flex-1\">\u003Cstrong class=\"block text-lg text-gray-900 dark:text-gray-100\">VRAM-Nutzung ist keine VRAM-Anforderung: Warum ein voller Speicheranzeiger nicht die ganze Geschichte erzählt\u003C\u002Fstrong>\u003Cp class=\"mt-2 text-sm text-gray-600 dark:text-gray-300\">Ein praktischer Leitfaden zu VRAM-Kapazität, Residenzbudgets, Working Sets und warum Speicherdruck komplizierter ist als eine einzelne Nutzungszahl.\u003C\u002Fp>\u003Cspan class=\"mt-3 inline-flex text-sm font-medium text-primary-600 dark:text-primary-400\">VRAM-Leitfaden lesen →\u003C\u002Fspan>\u003C\u002Fdiv>\u003C\u002Fa>\u003C\u002Faside>\n\u003Ch2 id=\"section-29\">Warum vollständige Modelle einen anderen Weg benötigen\u003C\u002Fh2>\n\u003Cp>Ein paar Matrixoperationen in HLSL von Hand zu schreiben, ist für kleine neuronale Funktionen praktikabel. Es wird viel weniger praktikabel, wenn der Workload ein vollständiges modernes Modell mit vielen Schichten, Abhängigkeiten und Zwischentensoren ist.\u003C\u002Fp>\n\u003Cp>Microsofts DirectX Compute Graph Compiler ist für diese größere Klasse von Workloads konzipiert.\u003C\u002Fp>\n\u003Cp>Anstatt das Modell als benutzerdefinierten Shader-Code neu zu schreiben, kann der Compiler einen Berechnungsgraphen akzeptieren, den gesamten Graphen analysieren, Speicher planen, Operationen fusionieren und das Ergebnis in GPU-Arbeit umsetzen, die sich in DirectX 12 integriert.\u003C\u002Fp>\n\u003Ch2 id=\"section-33\">Die Grenze zwischen Shader und Graph\u003C\u002Fh2>\n\u003Csection class=\"editorjs-comparison my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Wann der ML-Workload in HLSL vs. einen Modellcompiler gehört\u003C\u002Fh3>\u003Cdiv class=\"overflow-x-auto\">\u003Ctable class=\"w-full border-collapse\">\u003Cthead>\u003Ctr>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left dark:border-gray-700 dark:bg-gray-900\">\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Pfad auf Shader-Ebene\u003C\u002Fth>\u003Cth class=\"border border-gray-300 bg-gray-50 px-4 py-3 text-left font-semibold dark:border-gray-700 dark:bg-gray-900\">Pfad auf Modellebene\u003C\u002Fth>\u003C\u002Ftr>\u003C\u002Fthead>\u003Ctbody>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Modellgröße\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Ausführungsstil\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Erstellung\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Optimierungsumfang\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003Ctr>\u003Cth class=\"border border-gray-300 px-4 py-3 text-left font-semibold dark:border-gray-700\">Typische Verwendung\u003C\u002Fth>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003Ctd class=\"border border-gray-300 px-4 py-3 dark:border-gray-700\">\u003C\u002Ftd>\u003C\u002Ftr>\u003C\u002Ftbody>\u003C\u002Ftable>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-35\">Warum herstellerübergreifende Unterstützung wichtiger ist als ein weiteres KI-Feature\u003C\u002Fh2>\n\u003Cp>AMD, Intel, NVIDIA und Qualcomm bieten unterschiedliche GPU-Architekturen und unterschiedliche Formen dedizierter Matrixbeschleunigung.\u003C\u002Fp>\n\u003Cp>Eine DirectX-Abstraktion gibt Microsoft und den Treiberherstellern einen Ort, um gängige HLSL- oder ML auf Graph-Ebene in den korrekten Hardware-Pfad zu übersetzen.\u003C\u002Fp>\n\u003Cp>Das macht nicht jede GPU gleich schnell, aber es kann den Bedarf einer Spiel-Engine reduzieren, für jeden Hersteller eine völlig andere Neural-Rendering-API zu implementieren.\u003C\u002Fp>\n\u003Caside class=\"editorjs-callout editorjs-callout--note my-6 rounded-xl border p-5 border-gray-300 bg-gray-50 dark:border-gray-700 dark:bg-gray-900\u002F40\" role=\"note\">\u003Cstrong class=\"block mb-2 text-gray-900 dark:text-gray-100\">Portabilität ist die eigentliche Plattformgeschichte\u003C\u002Fstrong>\u003Cdiv class=\"text-gray-700 dark:text-gray-200\">Das Interessante ist nicht, dass DirectX „KI ausführen“ kann. GPUs konnten das bereits. Die Plattformveränderung besteht darin, dass \u003Cstrong>ML durch eine gemeinsame Grafik-API und Toolchain ausdrückbar wird\u003C\u002Fstrong>.\u003C\u002Fdiv>\u003C\u002Faside>\n\u003Ch2 id=\"section-40\">Welche Hardware unterstützt die aktuelle Vorschau?\u003C\u002Fh2>\n\u003Cp>Die Antwort hängt von der spezifischen Linear-Algebra-Operation und dem Vorschau-Treiber ab.\u003C\u002Fp>\n\u003Cp>Die Unterstützungstabelle von Microsofts Agility SDK 1.721 Vorschau listet LinAlg VectorAccumulate für AMD Radeon RX 9000 Series Hardware, Intel Xe2-oder-neuer Hardware über einen kommenden Treiber und NVIDIA RTX Hardware über den unterstützten Vorschau-Pfad auf.\u003C\u002Fp>\n\u003Cp>Dies ist eine Unterstützung aus der Vorschau-Ära, keine universelle Einzelhandelsgarantie. Hardware- und Treiberunterstützung können sich vor der Finalisierung ändern.\u003C\u002Fp>\n\u003Ch2 id=\"section-44\">Neural Rendering wird zur Infrastruktur\u003C\u002Fh2>\n\u003Cp>DLSS, FSR und andere neuronale Grafiktechnologien werden oft als Markenfunktionen diskutiert, die im Einstellungsmenü eines Spiels sichtbar sind.\u003C\u002Fp>\n\u003Cp>DirectX Linear Algebra deutet auf eine tiefgreifendere Veränderung hin. Die neuronale Operation kann zu einem internen Implementierungsdetail innerhalb des Renderers werden, anstatt eine einzelne optionale Post-Processing-Funktion zu sein.\u003C\u002Fp>\n\u003Cp>Ein Entwickler könnte ML für Texturen, Materialien, Beleuchtung, Rekonstruktion oder andere lokale Funktionen nutzen, ohne jede einzelne als verbraucherorientierten KI-Schalter offenzulegen.\u003C\u002Fp>\n\u003Caside class=\"editorjs-referral my-6\">\u003Ca href=\"https:\u002F\u002Ffigure.rocks\u002Fde\u002Fblog\u002Fdlss-5-is-not-just-upscaling-what-3d-guided-neural-rendering-actually-changes\" class=\"flex flex-col sm:flex-row gap-4 rounded-xl border border-gray-200 dark:border-gray-700 p-4 transition hover:border-primary-500\">\u003Cdiv class=\"min-w-0 flex-1\">\u003Cstrong class=\"block text-lg text-gray-900 dark:text-gray-100\">DLSS 5 ist nicht nur Upscaling: Was 3D-geführtes Neural Rendering tatsächlich verändert\u003C\u002Fstrong>\u003Cp class=\"mt-2 text-sm text-gray-600 dark:text-gray-300\">Wie Neural Rendering über Upscaling und generierte Frames hinaus in die Material- und Beleuchtungsrekonstruktion innerhalb der Grafikpipeline vordringt.\u003C\u002Fp>\u003Cspan class=\"mt-3 inline-flex text-sm font-medium text-primary-600 dark:text-primary-400\">Lies den DLSS 5 Neural-Rendering-Leitfaden →\u003C\u002Fspan>\u003C\u002Fdiv>\u003C\u002Fa>\u003C\u002Faside>\n\u003Ch2 id=\"section-49\">Der Neural Rendering Stack wird zunehmend geschichtet\u003C\u002Fh2>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Eine mögliche zukünftige DirectX-Spielpipeline\u003C\u002Fh3>\u003Cdiv class=\"grid grid-cols-1 md:grid-cols-2 xl:grid-cols-3 gap-4\">\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">1\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">Traditionelle Engine-Arbeit\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Simulation, Geometrie, Sichtbarkeit und Basis-Rendering bleiben Standardaufgaben der Engine.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">2\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">Inline-Neural-Shader\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Kleine gelernte Funktionen rekonstruieren Texturen, Materialien oder Beleuchtung innerhalb von HLSL.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">3\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">Größere ML-Graphen\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Vollständige Rekonstruktions- oder Inferenzmodelle werden über einen DirectX-Pfad auf Graph-Ebene ausgeführt.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">4\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">Hersteller-Hardware-Mapping\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Treiber bilden gängige DirectX-Operationen auf die spezialisierten KI- und Matrix-Einheiten der GPU ab.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">5\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">PIX-Sichtbarkeit\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Grafik- und ML-Arbeit können zusammen profiliert werden, anstatt in getrennten undurchsichtigen Laufzeitumgebungen zu leben.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-51\">Warum einheitliches Profiling wichtig ist\u003C\u002Fh2>\n\u003Cp>Eine neuronale Arbeitslast, die die Bildqualität verbessert, kann einem Spiel dennoch schaden, wenn sie unerwartet Frame-Zeit, Speicherbandbreite oder VRAM verbraucht.\u003C\u002Fp>\n\u003Cp>Microsoft bezieht ausdrücklich die einheitliche PIX-Sichtbarkeit als Teil der Compute Graph Compiler-Richtung ein. Das ist wichtig, weil Entwickler Grafik- und ML-Arbeit in derselben Frame-Aufzeichnung sehen müssen.\u003C\u002Fp>\n\u003Cp>Wenn Neural Rendering zur Infrastruktur wird, muss es wie jede andere Rendering-Stufe messbar sein.\u003C\u002Fp>\n\u003Ch2 id=\"section-55\">Das bedeutet nicht, dass jeder Shader zu einem neuronalen Netzwerk wird\u003C\u002Fh2>\n\u003Cp>Herkömmliche Shader-Mathematik bleibt für viele Workloads effizient, deterministisch und leicht nachvollziehbar.\u003C\u002Fp>\n\u003Cp>Eine neuronale Funktion ist sinnvoll, wenn sie etwas Teures effizienter annähern oder rekonstruieren, Daten komprimieren oder eine Qualität erzeugen kann, die sonst zu viel konventionelle Rechenleistung oder Speicher erfordern würde.\u003C\u002Fp>\n\u003Cp>Die richtige Architektur wird hybrid bleiben.\u003C\u002Fp>\n\u003Ch2 id=\"section-59\">Der neuronale Shader-Werttest\u003C\u002Fh2>\n\u003Csection class=\"editorjs-process my-6\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Wann ergibt es tatsächlich Sinn, ML in die Rendering-Pipeline zu integrieren?\u003C\u002Fh3>\u003Cdiv class=\"grid grid-cols-1 md:grid-cols-2 xl:grid-cols-3 gap-4\">\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">1\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">1. Identifizieren Sie den teuren traditionellen Vorgang\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Welche Rechen-, Bandbreiten-, Speicher- oder Speicherkosten versuchen Sie zu ersetzen?\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">2\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">2. Definieren Sie den neuronalen Ersatz\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Was kann ein kleines Modell rekonstruieren, vorhersagen oder komprimieren?\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">3\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">3. Messen Sie die Inferenzkosten\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Das ML-Modell selbst verbraucht GPU-Zeit, Speicher und Bandbreite.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">4\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">4. Messen Sie die Qualitätsstabilität\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Achten Sie auf zeitliche Artefakte, Rekonstruktionsfehler und Fehlerfälle.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">5\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">5. Messen Sie die Nettoeinsparungen\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Die Technik ist nur nützlich, wenn die vermiedenen traditionellen Kosten die zusätzlichen ML-Kosten wert sind.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv class=\"editorjs-process__step min-w-0  rounded-xl border border-gray-200 dark:border-gray-700 p-4\">\u003Cdiv class=\"text-xs font-semibold text-gray-500 dark:text-gray-400\">6\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 font-semibold text-gray-900 dark:text-gray-100\">6. Testen Sie über verschiedene Anbieter hinweg\u003C\u002Fdiv>\u003Cdiv class=\"mt-1 text-sm text-gray-600 dark:text-gray-300\">Eine DirectX-Abstraktion hilft bei der Portabilität, aber die tatsächliche Hardware-Leistung unterscheidet sich weiterhin.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-61\">Was das für Gamer bedeutet\u003C\u002Fh2>\n\u003Cp>Gamer werden wahrscheinlich nie einen Schalter „DX Linear Algebra“ in einem Grafikmenü sehen.\u003C\u002Fp>\n\u003Cp>Die wahrscheinliche Auswirkung ist indirekt: kleinere Textur-Footprints, bessere Lichtrekonstruktion, effizientere neuronale Grafik oder neue visuelle Techniken, die praktikabel werden, weil die Engine über einen Standardpfad auf Matrixbeschleunigung zugreifen kann.\u003C\u002Fp>\n\u003Cp>Das Feature ist als Infrastruktur wichtiger denn als Marke.\u003C\u002Fp>\n\u003Ch2 id=\"section-65\">Was würde diese Antwort ändern?\u003C\u002Fh2>\n\u003Cp>Die größte Unsicherheit ist die endgültige Retail-Form dieser APIs. DX Linear Algebra befindet sich noch in der Vorschau, und der Compute Graph Compiler hat noch keine breite Retail-Verfügbarkeit erreicht.\u003C\u002Fp>\n\u003Cp>Die endgültige Hardware-Unterstützung, API-Details, Compiler-Verhalten und Engine-Adoption können sich ändern, bevor diese Systeme zur normalen Infrastruktur für ausgelieferte Spiele werden.\u003C\u002Fp>\n\u003Cp>Wenn große Engines die Abstraktionen direkt übernehmen, könnten neuronale Shader viel häufiger werden, ohne dass einzelne Spielteams jede Technik von Grund auf implementieren müssen.\u003C\u002Fp>\n\u003Ch2 id=\"section-69\">Einschränkungen\u003C\u002Fh2>\n\u003Cp>Dieser Artikel erklärt Microsofts dokumentierte DirectX-Architektur und Vorschau-APIs. Er behauptet nicht, dass DX Linear Algebra derzeit die Leistung in jedem Spiel verbessert oder dass der Compute Graph Compiler ein fertiges Retail-Produkt ist.\u003C\u002Fp>\n\u003Cp>Microsofts Beispiele beschreiben Fähigkeiten und beabsichtigte Verwendung. Reale Vorteile hängen vom Modell, der Engine-Integration, der GPU-Architektur, den Treibern und dem Workload ab.\u003C\u002Fp>\n\u003Ch2 id=\"section-72\">Fazit\u003C\u002Fh2>\n\u003Cp>Die wichtige DirectX-Änderung ist nicht ein weiteres Kontrollkästchen namens KI.\u003C\u002Fp>\n\u003Cp>Sie besteht darin, dass maschinelles Lernmathematik in das Grafikprogrammiermodell selbst einzieht. Kleine neuronale Funktionen können in Shadern sitzen, größere Modelle können in Richtung Graph-Level-Kompilierung wandern, und dieselbe DirectX-Toolchain kann diese Arbeitslasten über mehrere GPU-Hersteller hinweg verfügbar machen.\u003C\u002Fp>\n\u003Cp>So hört neuronales Rendering auf, ein einziges gebrandetes Feature zu sein, und wird Teil der Rendering-Infrastruktur.\u003C\u002Fp>\n\u003Ch2 id=\"section-76\">FAQ\u003C\u002Fh2>\n\u003Csection class=\"editorjs-faq my-6 rounded-xl border border-gray-200 p-5 dark:border-gray-700\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">DirectX Lineare Algebra und neuronale Shader\u003C\u002Fh3>\u003Cdiv id=\"faq1\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">Was ist DirectX Lineare Algebra?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Es ist ein DirectX\u002FHLSL-Feature-Set für hardwarebeschleunigte Vektor- und Matrixoperationen, die von maschinellem Lernen, neuronalem Rendering und Bildverarbeitungs-Workloads genutzt werden.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv id=\"faq2\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">Was ist ein neuronaler Shader?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Eine nützliche allgemein verständliche Beschreibung ist ein Shader, der eine gelernte neuronale Funktion oder einen ML-Inferenzschritt als Teil seiner Grafikarbeit enthält.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv id=\"faq3\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">Ist DX Lineare Algebra bereits ein normales DirectX-Einzelhandelsfeature?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Stand September 2026 befindet es sich noch im Vorschau-Pfad von Shader Model 6.10 \u002F Agility SDK.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv id=\"faq4\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">Was ist der DirectX Compute Graph Compiler?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Es ist Microsofts angekündigte ML-Compiler-API auf Modellebene, die größere Berechnungsgraphen aufnehmen und in optimierte, in D3D12 integrierte GPU-Workloads überführen soll.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv id=\"faq5\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">Warum nicht jedes ML-Modell direkt in HLSL ausführen?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Kleine Funktionen eignen sich gut für die Autorenschaft auf Shader-Ebene, während große Modelle von Ganzgraph-Optimierung, Speicherplanung und Operator-Fusion profitieren.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003Cdiv id=\"faq6\" class=\"border-t border-gray-200 py-4 first:border-t-0 dark:border-gray-700\">\u003Ch4 class=\"font-semibold text-gray-900 dark:text-gray-100\">Wird dies DLSS oder FSR ersetzen?\u003C\u002Fh4>\u003Cdiv class=\"mt-2 text-gray-600 dark:text-gray-300\">Nicht direkt. DirectX bietet eine niedrigere Infrastrukturebene, die Hersteller und Entwickler für neuronale Grafik nutzen können. Gebrandete Technologien können weiterhin ihre eigenen Modelle und Integrationsstrategien implementieren.\u003C\u002Fdiv>\u003C\u002Fdiv>\u003C\u002Fsection>\n\u003Ch2 id=\"section-78\">Glossar\u003C\u002Fh2>\n\u003Csection class=\"editorjs-glossary my-6 rounded-xl border border-gray-200 dark:border-gray-700 p-5\">\u003Ch3 class=\"mb-3 text-lg font-semibold\">Wichtige DirectX-ML-Begriffe\u003C\u002Fh3>\u003Cdl>\u003Cdiv id=\"dx-linear-algebra\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">DX Lineare Algebra\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">DirectX\u002FHLSL-APIs für beschleunigte Vektor- und Matrixoperationen, die für neuronales Rendering, ML und Bildverarbeitungs-Workloads gedacht sind.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"cooperative-vector\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">Cooperative Vector\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Ein früherer DirectX-Ansatz für beschleunigte Vektor-Matrix-Operationen innerhalb von Shadern, der half, den Pfad für neuronales Rendering auf Shader-Ebene zu etablieren.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"shader-model-6-10\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">Shader Model 6.10\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Die Vorschau-Shadermodell-Generation, die die aktuellen DirectX-Lineare-Algebra-Matrix-APIs enthält.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"compute-graph-compiler\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">DirectX Compute Graph Compiler\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Microsofts angekündigte Compiler-API zum Optimieren und Ausführen größerer ML-Berechnungsgraphen als native DirectX-GPU-Workloads.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"neural-shader\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">Neuronaler Shader\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Ein praktischer Begriff für einen Shader, der gelernte Inferenz oder neuronale Berechnung als Teil der Grafikverarbeitung durchführt.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"shader-or-graph-boundary\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">Shader-or-Graph-Grenze\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Ein Figure-Rocks-Modell zur Entscheidung, ob eine ML-Arbeitslast als kleine Inline-Shader-Mathematik oder als größerer Berechnungsgraph auf Modellebene gehört.\u003C\u002Fdd>\u003C\u002Fdiv>\u003Cdiv id=\"neural-shader-value-test\" class=\"border-t border-gray-200 dark:border-gray-700 py-3 first:border-t-0\">\u003Cdt class=\"font-semibold text-gray-900 dark:text-gray-100\">Neural Shader Value Test\u003C\u002Fdt>\u003Cdd class=\"mt-1 text-gray-600 dark:text-gray-300\">Ein Figure-Rocks-Workflow zur Entscheidung, ob die durch eine neuronale Technik vermiedenen traditionellen Compute- oder Speicherkosten ihre Inferenzkosten und Qualitätskompromisse wert sind.\u003C\u002Fdd>\u003C\u002Fdiv>\u003C\u002Fdl>\u003C\u002Fsection>\n\u003Ch2 id=\"section-80\">Primärquellen\u003C\u002Fh2>\n\u003Ca href=\"https:\u002F\u002Fdevblogs.microsoft.com\u002Fdirectx\u002Fevolving-directx-for-the-ml-era-on-windows\u002F\" target=\"_blank\" rel=\"noopener noreferrer\" class=\"editorjs-link-tool block border border-gray-200 dark:border-gray-700 rounded-lg p-4 transition text-gray-900 dark:text-gray-100 hover:border-primary-500 hover:bg-primary-50 dark:hover:bg-gray-900 hover:text-gray-900 dark:hover:text-gray-100\">\u003Cstrong class=\"block font-semibold\">Microsoft DirectX — DirectX für die ML-Ära unter Windows weiterentwickeln\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Offizieller Architekturüberblick der GDC 2026 zu ML auf Shader-Ebene, DX Lineare Algebra und dem DirectX Compute Graph Compiler.\u003C\u002Fp>\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fdevblogs.microsoft.com\u002Fdirectx\u002Fd3d12-linalg-preview\u002F\" target=\"_blank\" rel=\"noopener noreferrer\" class=\"editorjs-link-tool block border border-gray-200 dark:border-gray-700 rounded-lg p-4 transition text-gray-900 dark:text-gray-100 hover:border-primary-500 hover:bg-primary-50 dark:hover:bg-gray-900 hover:text-gray-900 dark:hover:text-gray-100\">\u003Cstrong class=\"block font-semibold\">Microsoft DirectX — D3D12 LinAlg Matrix Preview\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Offizielle Vorschau vom April 2026, die die einheitlichen Lineare-Algebra-APIs, Matrixoperationen und die Motivation für neuronales Rendering erläutert.\u003C\u002Fp>\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fdevblogs.microsoft.com\u002Fdirectx\u002Fannouncing-agilitysdk-721-preview-and-more-shader-model-6-10-features\u002F\" target=\"_blank\" rel=\"noopener noreferrer\" class=\"editorjs-link-tool block border border-gray-200 dark:border-gray-700 rounded-lg p-4 transition text-gray-900 dark:text-gray-100 hover:border-primary-500 hover:bg-primary-50 dark:hover:bg-gray-900 hover:text-gray-900 dark:hover:text-gray-100\">\u003Cstrong class=\"block font-semibold\">Microsoft DirectX — Agility SDK 1.721 Preview\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Offizielles Release vom Mai 2026, das Shader-Model-6.10-Lineare-Algebra-Updates und Vorschau-Hardwareunterstützung dokumentiert.\u003C\u002Fp>\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fdeveloper.microsoft.com\u002Fen-us\u002Fgames\u002Farticles\u002F2026\u002F03\u002Fgdc-2026-evolving-directx-for-ml-era-on-windows\u002F\" target=\"_blank\" rel=\"noopener noreferrer\" class=\"editorjs-link-tool block border border-gray-200 dark:border-gray-700 rounded-lg p-4 transition text-gray-900 dark:text-gray-100 hover:border-primary-500 hover:bg-primary-50 dark:hover:bg-gray-900 hover:text-gray-900 dark:hover:text-gray-100\">\u003Cstrong class=\"block font-semibold\">Microsoft Game Dev — GDC 2026: DirectX für die ML-Ära weiterentwickeln\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Offizielle Zusammenfassung von Microsoft Game Dev, die ML auf Shader- und Modellebene und die Rolle des Compute Graph Compiler erklärt.\u003C\u002Fp>\u003C\u002Fa>\n\u003Ca href=\"https:\u002F\u002Fdevblogs.microsoft.com\u002Fdirectx\u002Fcooperative-vector\u002F\" target=\"_blank\" rel=\"noopener noreferrer\" class=\"editorjs-link-tool block border border-gray-200 dark:border-gray-700 rounded-lg p-4 transition text-gray-900 dark:text-gray-100 hover:border-primary-500 hover:bg-primary-50 dark:hover:bg-gray-900 hover:text-gray-900 dark:hover:text-gray-100\">\u003Cstrong class=\"block font-semibold\">Microsoft DirectX — D3D12 Cooperative Vector\u003C\u002Fstrong>\u003Cp class=\"text-sm text-gray-600 dark:text-gray-400\">Offizieller Hintergrund zu hardwarebeschleunigten Vektor-\u002FMatrixoperationen und neuronalem Rendering direkt aus Shader-Threads.\u003C\u002Fp>\u003C\u002Fa>",{"time":538,"blocks":539,"version":1178},1790378056855,[540,546,554,561,568,574,579,584,589,594,614,621,626,631,636,641,668,673,678,683,688,693,698,722,727,732,737,742,751,756,761,766,771,776,809,814,819,824,829,835,840,845,850,855,860,865,870,875,883,888,909,914,919,924,929,934,939,944,949,954,978,983,988,993,998,1003,1008,1013,1018,1023,1028,1033,1038,1043,1048,1053,1058,1088,1093,1127,1132,1142,1151,1160,1169],{"id":541,"data":542,"type":544,"tunes":545},"intro",{"text":543},"DirectX ist nicht mehr nur eine Grafik-API, die traditionelle Shader an die GPU sendet. Microsoft fügt maschinelle Lernprimitive direkt zu HLSL hinzu und einen zweiten Pfad zum Ausführen größerer ML-Graphen innerhalb des DirectX-Ökosystems. Das verändert, wo neuronales Rendering in zukünftigen PC-Spielen stattfinden kann.","paragraph",{},{"id":547,"data":548,"type":552,"tunes":553},"direct",{"body":549,"title":550,"variant":551},"\u003Cstrong>DirectX wird zu einer ML-fähigen Grafikplattform.\u003C\u002Fstrong> Kleine neuronale Arbeitslasten können direkt in Shadern über DX Linear Algebra ausgeführt werden, während größere Modelle vom DirectX Compute Graph Compiler anvisiert werden. Das Ziel ist es, Spiel-Engines die Nutzung von GPU-KI-Hardware zu ermöglichen, ohne für jede Technik einen separaten herstellerspezifischen Pfad zu erstellen.","Direkte Antwort","info","callout",{},{"id":555,"data":556,"type":552,"tunes":560},"status-note",{"body":557,"title":558,"variant":559},"Stand September 2026 ist \u003Cstrong>DX Linear Algebra noch eine Vorschau-Technologie\u003C\u002Fstrong> im Shader Model 6.10 \u002F Agility SDK Vorschau-Pfad. Microsoft kündigte den DirectX Compute Graph Compiler für die private Vorschau an, nicht als breit verfügbares Retail-Feature. Dieser Artikel erklärt die Architektur und Richtung, nicht die Behauptung, dass jedes aktuelle Spiel es heute nutzen kann.","Aktueller Status","note",{},{"id":562,"data":563,"type":566,"tunes":567},"toc",{"title":564,"maxLevel":565,"minLevel":47},"Inhalt",3,"tableOfContents",{},{"id":569,"data":570,"type":572,"tunes":573},"h-why",{"text":571,"level":47},"Warum neuronales Rendering neue DirectX-Primitive benötigt","header",{},{"id":575,"data":576,"type":544,"tunes":578},"p-why-1",{"text":577},"Moderne GPUs enthalten bereits spezialisierte Hardware für Matrixoperationen, die im maschinellen Lernen verwendet werden. Das Problem für einen Spielentwickler ist nicht nur, ob diese Hardware existiert, sondern wie man effizient aus einer Echtzeit-Grafikpipeline darauf zugreift.",{},{"id":580,"data":581,"type":544,"tunes":583},"p-why-2",{"text":582},"Microsoft erforschte dies zuerst mit Cooperative Vector-Unterstützung. Im Jahr 2026 entwickelte sich diese Arbeit zu einem breiteren DirectX Linear Algebra-Design, das sowohl Vektor-Matrix- als auch Matrix-Matrix-Operationen unterstützt.",{},{"id":585,"data":586,"type":544,"tunes":588},"p-why-3",{"text":587},"Das ist wichtig, weil verschiedene neuronale Rendering-Aufgaben unterschiedliche Formen haben. Ein winziges Modell, das Materialverhalten pro Pixel bewertet, ist nicht die gleiche Arbeitslast wie ein großes Super-Resolution- oder Denoising-Diagramm.",{},{"id":590,"data":591,"type":572,"tunes":593},"h-two-level",{"text":592,"level":47},"Das zweistufige DirectX ML-Modell",{},{"id":595,"data":596,"type":612,"tunes":613},"two-level-flow",{"steps":597,"title":610,"orientation":611},[598,601,604,607],{"label":599,"description":600},"1. Shader-Level-ML","Kleine neuronale oder linear-algebraische Arbeitslasten werden direkt aus HLSL neben traditionellem Shader-Code ausgeführt.",{"label":602,"description":603},"2. DX Linear Algebra","Der Shader kann hardwarebeschleunigte Vektor- und Matrixoperationen anfordern, anstatt jedes ML-Primitiv manuell zu implementieren.",{"label":605,"description":606},"3. Modell-Level-ML","Größere neuronale Netzwerke werden als vollständige Berechnungsgraphen dargestellt, anstatt als handgeschriebene Shader-Fragmente.",{"label":608,"description":609},"4. DirectX Compute Graph Compiler","Microsofts geplanter Compiler-Pfad analysiert und senkt diese Graphen in optimierte GPU-Arbeitslasten, die in D3D12-Warteschlangen und Befehlslisten integriert sind.","Zwei Wege, wie ML in die DirectX-Grafikpipeline gelangen kann","auto","processFlow",{},{"id":615,"data":616,"type":552,"tunes":620},"simple-diff",{"body":617,"title":618,"variant":619},"\u003Cstrong>DX Linear Algebra:\u003C\u002Fstrong> kleine ML-Mathematik in den Shader einfügen.\u003Cbr>\u003Cstrong>Compute Graph Compiler:\u003C\u002Fstrong> ein größeres ML-Modell als Graph in die Engine bringen.","Der einfache Unterschied","success",{},{"id":622,"data":623,"type":572,"tunes":625},"h-linalg",{"text":624,"level":47},"Was DX Linear Algebra einem Shader tatsächlich bietet",{},{"id":627,"data":628,"type":544,"tunes":630},"p-linalg-1",{"text":629},"Traditionelles HLSL ist um Grafik- und Compute-Operationen herum aufgebaut. Neuronale Arbeitslasten stützen sich stark auf lineare Algebra: Vektoren, Matrizen, Multiplikation, Akkumulation und Datenlayouts, die für diese Operationen optimiert sind.",{},{"id":632,"data":633,"type":544,"tunes":635},"p-linalg-2",{"text":634},"Die Shader Model 6.10-Vorschau fügt erstklassige Matrix-APIs hinzu, damit Entwickler diese Arbeitslasten direkter ausdrücken und den Treiber sie auf spezialisierte Hardware abbilden lassen können.",{},{"id":637,"data":638,"type":544,"tunes":640},"p-linalg-3",{"text":639},"Microsofts Vorschau vom April 2026 beschreibt dies ausdrücklich als einen einheitlichen Pfad für neuronales Rendering, ML und Bildverarbeitungs-Arbeitslasten und nicht als eine reine Grafikfunktion.",{},{"id":642,"data":643,"type":666,"tunes":667},"math-table",{"rows":644,"title":657,"layout":658,"columns":659},[645,649,653],{"id":646,"label":647,"values":648},"work","Typische Arbeit",[13,13],{"id":650,"label":651,"values":652},"hardware","Hardware-Pfad",[13,13],{"id":654,"label":655,"values":656},"code","Entwicklerausdruck",[13,13],"Traditionelle Shader-Mathematik vs. ML-orientierte Shader-Mathematik","table",[660,663],{"id":661,"label":662},"traditional","Traditioneller Shader-Fokus",{"id":664,"label":665},"ml","ML-orientierter Fokus","comparison",{},{"id":669,"data":670,"type":572,"tunes":672},"h-coop",{"text":671,"level":47},"Warum Cooperative Vector nur der Anfang war",{},{"id":674,"data":675,"type":544,"tunes":677},"p-coop-1",{"text":676},"Cooperative Vector ermöglichte es Shader-Threads, Vektor-Matrix-Arbeit anzufordern, die Treiber auf spezialisierte Hardware abbilden konnten. Das war nützlich für hochgradig parallele Pro-Pixel-Arbeitslasten.",{},{"id":679,"data":680,"type":544,"tunes":682},"p-coop-2",{"text":681},"Microsoft kam später zu dem Schluss, dass viele wichtige ML-Workloads mehr als Vektor-Matrix-Operationen benötigen. Superauflösung, Entrauschen, zeitliche Rekonstruktion, größere Bildmodelle und allgemeine Inferenz können Matrix-Matrix-Operationen und gemeinsame Arbeit über viele Threads hinweg erfordern.",{},{"id":684,"data":685,"type":544,"tunes":687},"p-coop-3",{"text":686},"DX Linear Algebra erweitert daher das Modell, anstatt Cooperative Vector als die endgültige Abstraktion zu behandeln.",{},{"id":689,"data":690,"type":572,"tunes":692},"h-usecases",{"text":691,"level":47},"Was kann tatsächlich in einem Shader ausgeführt werden?",{},{"id":694,"data":695,"type":544,"tunes":697},"p-use-1",{"text":696},"Die interessantesten ML-Workloads auf Shader-Ebene sind klein genug, um in der Nähe der Grafikdaten ausgeführt zu werden, auf denen sie operieren.",{},{"id":699,"data":700,"type":658,"tunes":721},"usecases-table",{"content":701,"stretched":720,"withHeadings":15},[702,705,708,711,714,717],[703,704],"Workload","Warum ML auf Shader-Ebene passt",[706,707],"Neuronale Texturkompression","Ein kleines Netzwerk kann Texturinformationen in der Nähe des Punktes rekonstruieren, an dem der Shader sie benötigt",[709,710],"Neuronale Materialbewertung","Eine gelernte Funktion kann teure handgeschriebene Materialmathematik ersetzen oder ergänzen",[712,713],"Neuronales Radiance-Caching","Inferenz pro Pixel oder lokal kann Beleuchtungsinformationen aus gelerntem Szenenverhalten schätzen",[715,716],"Kleine Entrauschungs-\u002FRekonstruktionskerne","ML-Operationen können direkt neben der Rendering-Stufe liegen, die sie verbessern",[718,719],"Bildverarbeitungsinferenz","Matrixoperationen können in die GPU-Verarbeitung eingebettet werden, ohne eine separate externe Laufzeitumgebung",false,{},{"id":723,"data":724,"type":572,"tunes":726},"h-texture",{"text":725,"level":47},"Warum dies für den Texturspeicher wichtig ist",{},{"id":728,"data":729,"type":544,"tunes":731},"p-tex-1",{"text":730},"Eines von Microsofts wiederkehrenden Beispielen ist die neuronale Texturkompression.",{},{"id":733,"data":734,"type":544,"tunes":736},"p-tex-2",{"text":735},"Anstatt jeden Texturkanal mit herkömmlicher Genauigkeit zu speichern, kann ein Spiel eine kompaktere Darstellung speichern und ein kleines neuronales Netzwerk verwenden, um Details während des Renderings zu rekonstruieren.",{},{"id":738,"data":739,"type":544,"tunes":741},"p-tex-3",{"text":740},"Das tauscht etwas GPU-Inferenzarbeit gegen geringeren Speicher- oder Speicherdruck. Der genaue Nutzen hängt von der Technik und der Hardware ab, aber die architektonische Änderung ist wichtig: Einige visuelle Details können zu Berechnung anstatt zu gespeicherten Daten werden.",{},{"id":743,"data":744,"type":749,"tunes":750},"ref-vram",{"url":745,"title":746,"excerpt":747,"ctaLabel":748},"https:\u002F\u002Ffigure.rocks\u002Fde\u002Fblog\u002Fvram-usage-is-not-vram-requirement-why-a-full-memory-meter-does-not-tell-the-whole-story","VRAM-Nutzung ist keine VRAM-Anforderung: Warum ein voller Speicheranzeiger nicht die ganze Geschichte erzählt","Ein praktischer Leitfaden zu VRAM-Kapazität, Residenzbudgets, Working Sets und warum Speicherdruck komplizierter ist als eine einzelne Nutzungszahl.","VRAM-Leitfaden lesen","referralArticle",{},{"id":752,"data":753,"type":572,"tunes":755},"h-models",{"text":754,"level":47},"Warum vollständige Modelle einen anderen Weg benötigen",{},{"id":757,"data":758,"type":544,"tunes":760},"p-models-1",{"text":759},"Ein paar Matrixoperationen in HLSL von Hand zu schreiben, ist für kleine neuronale Funktionen praktikabel. Es wird viel weniger praktikabel, wenn der Workload ein vollständiges modernes Modell mit vielen Schichten, Abhängigkeiten und Zwischentensoren ist.",{},{"id":762,"data":763,"type":544,"tunes":765},"p-models-2",{"text":764},"Microsofts DirectX Compute Graph Compiler ist für diese größere Klasse von Workloads konzipiert.",{},{"id":767,"data":768,"type":544,"tunes":770},"p-models-3",{"text":769},"Anstatt das Modell als benutzerdefinierten Shader-Code neu zu schreiben, kann der Compiler einen Berechnungsgraphen akzeptieren, den gesamten Graphen analysieren, Speicher planen, Operationen fusionieren und das Ergebnis in GPU-Arbeit umsetzen, die sich in DirectX 12 integriert.",{},{"id":772,"data":773,"type":572,"tunes":775},"h-boundary",{"text":774,"level":47},"Die Grenze zwischen Shader und Graph",{},{"id":777,"data":778,"type":666,"tunes":808},"boundary-table",{"rows":779,"title":800,"layout":658,"columns":801},[780,784,788,792,796],{"id":781,"label":782,"values":783},"size","Modellgröße",[13,13],{"id":785,"label":786,"values":787},"location","Ausführungsstil",[13,13],{"id":789,"label":790,"values":791},"authoring","Erstellung",[13,13],{"id":793,"label":794,"values":795},"optimization","Optimierungsumfang",[13,13],{"id":797,"label":798,"values":799},"use","Typische Verwendung",[13,13],"Wann der ML-Workload in HLSL vs. einen Modellcompiler gehört",[802,805],{"id":803,"label":804},"shader","Pfad auf Shader-Ebene",{"id":806,"label":807},"graph","Pfad auf Modellebene",{},{"id":810,"data":811,"type":572,"tunes":813},"h-crossvendor",{"text":812,"level":47},"Warum herstellerübergreifende Unterstützung wichtiger ist als ein weiteres KI-Feature",{},{"id":815,"data":816,"type":544,"tunes":818},"p-cross-1",{"text":817},"AMD, Intel, NVIDIA und Qualcomm bieten unterschiedliche GPU-Architekturen und unterschiedliche Formen dedizierter Matrixbeschleunigung.",{},{"id":820,"data":821,"type":544,"tunes":823},"p-cross-2",{"text":822},"Eine DirectX-Abstraktion gibt Microsoft und den Treiberherstellern einen Ort, um gängige HLSL- oder ML auf Graph-Ebene in den korrekten Hardware-Pfad zu übersetzen.",{},{"id":825,"data":826,"type":544,"tunes":828},"p-cross-3",{"text":827},"Das macht nicht jede GPU gleich schnell, aber es kann den Bedarf einer Spiel-Engine reduzieren, für jeden Hersteller eine völlig andere Neural-Rendering-API zu implementieren.",{},{"id":830,"data":831,"type":552,"tunes":834},"portability-note",{"body":832,"title":833,"variant":559},"Das Interessante ist nicht, dass DirectX „KI ausführen“ kann. GPUs konnten das bereits. Die Plattformveränderung besteht darin, dass \u003Cstrong>ML durch eine gemeinsame Grafik-API und Toolchain ausdrückbar wird\u003C\u002Fstrong>.","Portabilität ist die eigentliche Plattformgeschichte",{},{"id":836,"data":837,"type":572,"tunes":839},"h-support",{"text":838,"level":47},"Welche Hardware unterstützt die aktuelle Vorschau?",{},{"id":841,"data":842,"type":544,"tunes":844},"p-support-1",{"text":843},"Die Antwort hängt von der spezifischen Linear-Algebra-Operation und dem Vorschau-Treiber ab.",{},{"id":846,"data":847,"type":544,"tunes":849},"p-support-2",{"text":848},"Die Unterstützungstabelle von Microsofts Agility SDK 1.721 Vorschau listet LinAlg VectorAccumulate für AMD Radeon RX 9000 Series Hardware, Intel Xe2-oder-neuer Hardware über einen kommenden Treiber und NVIDIA RTX Hardware über den unterstützten Vorschau-Pfad auf.",{},{"id":851,"data":852,"type":544,"tunes":854},"p-support-3",{"text":853},"Dies ist eine Unterstützung aus der Vorschau-Ära, keine universelle Einzelhandelsgarantie. Hardware- und Treiberunterstützung können sich vor der Finalisierung ändern.",{},{"id":856,"data":857,"type":572,"tunes":859},"h-infra",{"text":858,"level":47},"Neural Rendering wird zur Infrastruktur",{},{"id":861,"data":862,"type":544,"tunes":864},"p-infra-1",{"text":863},"DLSS, FSR und andere neuronale Grafiktechnologien werden oft als Markenfunktionen diskutiert, die im Einstellungsmenü eines Spiels sichtbar sind.",{},{"id":866,"data":867,"type":544,"tunes":869},"p-infra-2",{"text":868},"DirectX Linear Algebra deutet auf eine tiefgreifendere Veränderung hin. Die neuronale Operation kann zu einem internen Implementierungsdetail innerhalb des Renderers werden, anstatt eine einzelne optionale Post-Processing-Funktion zu sein.",{},{"id":871,"data":872,"type":544,"tunes":874},"p-infra-3",{"text":873},"Ein Entwickler könnte ML für Texturen, Materialien, Beleuchtung, Rekonstruktion oder andere lokale Funktionen nutzen, ohne jede einzelne als verbraucherorientierten KI-Schalter offenzulegen.",{},{"id":876,"data":877,"type":749,"tunes":882},"ref-dlss5",{"url":878,"title":879,"excerpt":880,"ctaLabel":881},"https:\u002F\u002Ffigure.rocks\u002Fde\u002Fblog\u002Fdlss-5-is-not-just-upscaling-what-3d-guided-neural-rendering-actually-changes","DLSS 5 ist nicht nur Upscaling: Was 3D-geführtes Neural Rendering tatsächlich verändert","Wie Neural Rendering über Upscaling und generierte Frames hinaus in die Material- und Beleuchtungsrekonstruktion innerhalb der Grafikpipeline vordringt.","Lies den DLSS 5 Neural-Rendering-Leitfaden",{},{"id":884,"data":885,"type":572,"tunes":887},"h-stack",{"text":886,"level":47},"Der Neural Rendering Stack wird zunehmend geschichtet",{},{"id":889,"data":890,"type":612,"tunes":908},"stack-flow",{"steps":891,"title":907,"orientation":611},[892,895,898,901,904],{"label":893,"description":894},"Traditionelle Engine-Arbeit","Simulation, Geometrie, Sichtbarkeit und Basis-Rendering bleiben Standardaufgaben der Engine.",{"label":896,"description":897},"Inline-Neural-Shader","Kleine gelernte Funktionen rekonstruieren Texturen, Materialien oder Beleuchtung innerhalb von HLSL.",{"label":899,"description":900},"Größere ML-Graphen","Vollständige Rekonstruktions- oder Inferenzmodelle werden über einen DirectX-Pfad auf Graph-Ebene ausgeführt.",{"label":902,"description":903},"Hersteller-Hardware-Mapping","Treiber bilden gängige DirectX-Operationen auf die spezialisierten KI- und Matrix-Einheiten der GPU ab.",{"label":905,"description":906},"PIX-Sichtbarkeit","Grafik- und ML-Arbeit können zusammen profiliert werden, anstatt in getrennten undurchsichtigen Laufzeitumgebungen zu leben.","Eine mögliche zukünftige DirectX-Spielpipeline",{},{"id":910,"data":911,"type":572,"tunes":913},"h-pix",{"text":912,"level":47},"Warum einheitliches Profiling wichtig ist",{},{"id":915,"data":916,"type":544,"tunes":918},"p-pix-1",{"text":917},"Eine neuronale Arbeitslast, die die Bildqualität verbessert, kann einem Spiel dennoch schaden, wenn sie unerwartet Frame-Zeit, Speicherbandbreite oder VRAM verbraucht.",{},{"id":920,"data":921,"type":544,"tunes":923},"p-pix-2",{"text":922},"Microsoft bezieht ausdrücklich die einheitliche PIX-Sichtbarkeit als Teil der Compute Graph Compiler-Richtung ein. Das ist wichtig, weil Entwickler Grafik- und ML-Arbeit in derselben Frame-Aufzeichnung sehen müssen.",{},{"id":925,"data":926,"type":544,"tunes":928},"p-pix-3",{"text":927},"Wenn Neural Rendering zur Infrastruktur wird, muss es wie jede andere Rendering-Stufe messbar sein.",{},{"id":930,"data":931,"type":572,"tunes":933},"h-not-everything",{"text":932,"level":47},"Das bedeutet nicht, dass jeder Shader zu einem neuronalen Netzwerk wird",{},{"id":935,"data":936,"type":544,"tunes":938},"p-not-1",{"text":937},"Herkömmliche Shader-Mathematik bleibt für viele Workloads effizient, deterministisch und leicht nachvollziehbar.",{},{"id":940,"data":941,"type":544,"tunes":943},"p-not-2",{"text":942},"Eine neuronale Funktion ist sinnvoll, wenn sie etwas Teures effizienter annähern oder rekonstruieren, Daten komprimieren oder eine Qualität erzeugen kann, die sonst zu viel konventionelle Rechenleistung oder Speicher erfordern würde.",{},{"id":945,"data":946,"type":544,"tunes":948},"p-not-3",{"text":947},"Die richtige Architektur wird hybrid bleiben.",{},{"id":950,"data":951,"type":572,"tunes":953},"h-test",{"text":952,"level":47},"Der neuronale Shader-Werttest",{},{"id":955,"data":956,"type":612,"tunes":977},"value-test",{"steps":957,"title":976,"orientation":611},[958,961,964,967,970,973],{"label":959,"description":960},"1. Identifizieren Sie den teuren traditionellen Vorgang","Welche Rechen-, Bandbreiten-, Speicher- oder Speicherkosten versuchen Sie zu ersetzen?",{"label":962,"description":963},"2. Definieren Sie den neuronalen Ersatz","Was kann ein kleines Modell rekonstruieren, vorhersagen oder komprimieren?",{"label":965,"description":966},"3. Messen Sie die Inferenzkosten","Das ML-Modell selbst verbraucht GPU-Zeit, Speicher und Bandbreite.",{"label":968,"description":969},"4. Messen Sie die Qualitätsstabilität","Achten Sie auf zeitliche Artefakte, Rekonstruktionsfehler und Fehlerfälle.",{"label":971,"description":972},"5. Messen Sie die Nettoeinsparungen","Die Technik ist nur nützlich, wenn die vermiedenen traditionellen Kosten die zusätzlichen ML-Kosten wert sind.",{"label":974,"description":975},"6. Testen Sie über verschiedene Anbieter hinweg","Eine DirectX-Abstraktion hilft bei der Portabilität, aber die tatsächliche Hardware-Leistung unterscheidet sich weiterhin.","Wann ergibt es tatsächlich Sinn, ML in die Rendering-Pipeline zu integrieren?",{},{"id":979,"data":980,"type":572,"tunes":982},"h-gamers",{"text":981,"level":47},"Was das für Gamer bedeutet",{},{"id":984,"data":985,"type":544,"tunes":987},"p-gamers-1",{"text":986},"Gamer werden wahrscheinlich nie einen Schalter „DX Linear Algebra“ in einem Grafikmenü sehen.",{},{"id":989,"data":990,"type":544,"tunes":992},"p-gamers-2",{"text":991},"Die wahrscheinliche Auswirkung ist indirekt: kleinere Textur-Footprints, bessere Lichtrekonstruktion, effizientere neuronale Grafik oder neue visuelle Techniken, die praktikabel werden, weil die Engine über einen Standardpfad auf Matrixbeschleunigung zugreifen kann.",{},{"id":994,"data":995,"type":544,"tunes":997},"p-gamers-3",{"text":996},"Das Feature ist als Infrastruktur wichtiger denn als Marke.",{},{"id":999,"data":1000,"type":572,"tunes":1002},"h-change",{"text":1001,"level":47},"Was würde diese Antwort ändern?",{},{"id":1004,"data":1005,"type":544,"tunes":1007},"p-change-1",{"text":1006},"Die größte Unsicherheit ist die endgültige Retail-Form dieser APIs. DX Linear Algebra befindet sich noch in der Vorschau, und der Compute Graph Compiler hat noch keine breite Retail-Verfügbarkeit erreicht.",{},{"id":1009,"data":1010,"type":544,"tunes":1012},"p-change-2",{"text":1011},"Die endgültige Hardware-Unterstützung, API-Details, Compiler-Verhalten und Engine-Adoption können sich ändern, bevor diese Systeme zur normalen Infrastruktur für ausgelieferte Spiele werden.",{},{"id":1014,"data":1015,"type":544,"tunes":1017},"p-change-3",{"text":1016},"Wenn große Engines die Abstraktionen direkt übernehmen, könnten neuronale Shader viel häufiger werden, ohne dass einzelne Spielteams jede Technik von Grund auf implementieren müssen.",{},{"id":1019,"data":1020,"type":572,"tunes":1022},"h-limit",{"text":1021,"level":47},"Einschränkungen",{},{"id":1024,"data":1025,"type":544,"tunes":1027},"p-limit-1",{"text":1026},"Dieser Artikel erklärt Microsofts dokumentierte DirectX-Architektur und Vorschau-APIs. Er behauptet nicht, dass DX Linear Algebra derzeit die Leistung in jedem Spiel verbessert oder dass der Compute Graph Compiler ein fertiges Retail-Produkt ist.",{},{"id":1029,"data":1030,"type":544,"tunes":1032},"p-limit-2",{"text":1031},"Microsofts Beispiele beschreiben Fähigkeiten und beabsichtigte Verwendung. Reale Vorteile hängen vom Modell, der Engine-Integration, der GPU-Architektur, den Treibern und dem Workload ab.",{},{"id":1034,"data":1035,"type":572,"tunes":1037},"h-conclusion",{"text":1036,"level":47},"Fazit",{},{"id":1039,"data":1040,"type":544,"tunes":1042},"p-conc-1",{"text":1041},"Die wichtige DirectX-Änderung ist nicht ein weiteres Kontrollkästchen namens KI.",{},{"id":1044,"data":1045,"type":544,"tunes":1047},"p-conc-2",{"text":1046},"Sie besteht darin, dass maschinelles Lernmathematik in das Grafikprogrammiermodell selbst einzieht. Kleine neuronale Funktionen können in Shadern sitzen, größere Modelle können in Richtung Graph-Level-Kompilierung wandern, und dieselbe DirectX-Toolchain kann diese Arbeitslasten über mehrere GPU-Hersteller hinweg verfügbar machen.",{},{"id":1049,"data":1050,"type":544,"tunes":1052},"p-conc-3",{"text":1051},"So hört neuronales Rendering auf, ein einziges gebrandetes Feature zu sein, und wird Teil der Rendering-Infrastruktur.",{},{"id":1054,"data":1055,"type":572,"tunes":1057},"h-faq",{"text":1056,"level":47},"FAQ",{},{"id":1059,"data":1060,"type":1059,"tunes":1087},"faq",{"items":1061,"title":1086},[1062,1066,1070,1074,1078,1082],{"id":1063,"answer":1064,"question":1065},"faq1","Es ist ein DirectX\u002FHLSL-Feature-Set für hardwarebeschleunigte Vektor- und Matrixoperationen, die von maschinellem Lernen, neuronalem Rendering und Bildverarbeitungs-Workloads genutzt werden.","Was ist DirectX Lineare Algebra?",{"id":1067,"answer":1068,"question":1069},"faq2","Eine nützliche allgemein verständliche Beschreibung ist ein Shader, der eine gelernte neuronale Funktion oder einen ML-Inferenzschritt als Teil seiner Grafikarbeit enthält.","Was ist ein neuronaler Shader?",{"id":1071,"answer":1072,"question":1073},"faq3","Stand September 2026 befindet es sich noch im Vorschau-Pfad von Shader Model 6.10 \u002F Agility SDK.","Ist DX Lineare Algebra bereits ein normales DirectX-Einzelhandelsfeature?",{"id":1075,"answer":1076,"question":1077},"faq4","Es ist Microsofts angekündigte ML-Compiler-API auf Modellebene, die größere Berechnungsgraphen aufnehmen und in optimierte, in D3D12 integrierte GPU-Workloads überführen soll.","Was ist der DirectX Compute Graph Compiler?",{"id":1079,"answer":1080,"question":1081},"faq5","Kleine Funktionen eignen sich gut für die Autorenschaft auf Shader-Ebene, während große Modelle von Ganzgraph-Optimierung, Speicherplanung und Operator-Fusion profitieren.","Warum nicht jedes ML-Modell direkt in HLSL ausführen?",{"id":1083,"answer":1084,"question":1085},"faq6","Nicht direkt. DirectX bietet eine niedrigere Infrastrukturebene, die Hersteller und Entwickler für neuronale Grafik nutzen können. Gebrandete Technologien können weiterhin ihre eigenen Modelle und Integrationsstrategien implementieren.","Wird dies DLSS oder FSR ersetzen?","DirectX Lineare Algebra und neuronale Shader",{},{"id":1089,"data":1090,"type":572,"tunes":1092},"h-glossary",{"text":1091,"level":47},"Glossar",{},{"id":1094,"data":1095,"type":1094,"tunes":1126},"glossary",{"title":1096,"entries":1097},"Wichtige DirectX-ML-Begriffe",[1098,1102,1106,1110,1114,1118,1122],{"term":1099,"anchor":1100,"definition":1101},"DX Lineare Algebra","dx-linear-algebra","DirectX\u002FHLSL-APIs für beschleunigte Vektor- und Matrixoperationen, die für neuronales Rendering, ML und Bildverarbeitungs-Workloads gedacht sind.",{"term":1103,"anchor":1104,"definition":1105},"Cooperative Vector","cooperative-vector","Ein früherer DirectX-Ansatz für beschleunigte Vektor-Matrix-Operationen innerhalb von Shadern, der half, den Pfad für neuronales Rendering auf Shader-Ebene zu etablieren.",{"term":1107,"anchor":1108,"definition":1109},"Shader Model 6.10","shader-model-6-10","Die Vorschau-Shadermodell-Generation, die die aktuellen DirectX-Lineare-Algebra-Matrix-APIs enthält.",{"term":1111,"anchor":1112,"definition":1113},"DirectX Compute Graph Compiler","compute-graph-compiler","Microsofts angekündigte Compiler-API zum Optimieren und Ausführen größerer ML-Berechnungsgraphen als native DirectX-GPU-Workloads.",{"term":1115,"anchor":1116,"definition":1117},"Neuronaler Shader","neural-shader","Ein praktischer Begriff für einen Shader, der gelernte Inferenz oder neuronale Berechnung als Teil der Grafikverarbeitung durchführt.",{"term":1119,"anchor":1120,"definition":1121},"Shader-or-Graph-Grenze","shader-or-graph-boundary","Ein Figure-Rocks-Modell zur Entscheidung, ob eine ML-Arbeitslast als kleine Inline-Shader-Mathematik oder als größerer Berechnungsgraph auf Modellebene gehört.",{"term":1123,"anchor":1124,"definition":1125},"Neural Shader Value Test","neural-shader-value-test","Ein Figure-Rocks-Workflow zur Entscheidung, ob die durch eine neuronale Technik vermiedenen traditionellen Compute- oder Speicherkosten ihre Inferenzkosten und Qualitätskompromisse wert sind.",{},{"id":1128,"data":1129,"type":572,"tunes":1131},"h-sources",{"text":1130,"level":47},"Primärquellen",{},{"id":1133,"data":1134,"type":1140,"tunes":1141},"src-ms-ml-era",{"link":1135,"meta":1136},"https:\u002F\u002Fdevblogs.microsoft.com\u002Fdirectx\u002Fevolving-directx-for-the-ml-era-on-windows\u002F",{"image":1137,"title":1138,"description":1139},{"url":13},"Microsoft DirectX — DirectX für die ML-Ära unter Windows weiterentwickeln","Offizieller Architekturüberblick der GDC 2026 zu ML auf Shader-Ebene, DX Lineare Algebra und dem DirectX Compute Graph Compiler.","linkTool",{},{"id":1143,"data":1144,"type":1140,"tunes":1150},"src-ms-linalg",{"link":1145,"meta":1146},"https:\u002F\u002Fdevblogs.microsoft.com\u002Fdirectx\u002Fd3d12-linalg-preview\u002F",{"image":1147,"title":1148,"description":1149},{"url":13},"Microsoft DirectX — D3D12 LinAlg Matrix Preview","Offizielle Vorschau vom April 2026, die die einheitlichen Lineare-Algebra-APIs, Matrixoperationen und die Motivation für neuronales Rendering erläutert.",{},{"id":1152,"data":1153,"type":1140,"tunes":1159},"src-ms-agility721",{"link":1154,"meta":1155},"https:\u002F\u002Fdevblogs.microsoft.com\u002Fdirectx\u002Fannouncing-agilitysdk-721-preview-and-more-shader-model-6-10-features\u002F",{"image":1156,"title":1157,"description":1158},{"url":13},"Microsoft DirectX — Agility SDK 1.721 Preview","Offizielles Release vom Mai 2026, das Shader-Model-6.10-Lineare-Algebra-Updates und Vorschau-Hardwareunterstützung dokumentiert.",{},{"id":1161,"data":1162,"type":1140,"tunes":1168},"src-ms-gdc",{"link":1163,"meta":1164},"https:\u002F\u002Fdeveloper.microsoft.com\u002Fen-us\u002Fgames\u002Farticles\u002F2026\u002F03\u002Fgdc-2026-evolving-directx-for-ml-era-on-windows\u002F",{"image":1165,"title":1166,"description":1167},{"url":13},"Microsoft Game Dev — GDC 2026: DirectX für die ML-Ära weiterentwickeln","Offizielle Zusammenfassung von Microsoft Game Dev, die ML auf Shader- und Modellebene und die Rolle des Compute Graph Compiler erklärt.",{},{"id":1170,"data":1171,"type":1140,"tunes":1177},"src-ms-coop",{"link":1172,"meta":1173},"https:\u002F\u002Fdevblogs.microsoft.com\u002Fdirectx\u002Fcooperative-vector\u002F",{"image":1174,"title":1175,"description":1176},{"url":13},"Microsoft DirectX — D3D12 Cooperative Vector","Offizieller Hintergrund zu hardwarebeschleunigten Vektor-\u002FMatrixoperationen und neuronalem Rendering direkt aus Shader-Threads.",{},"2.31","DirectX geht über traditionelle Grafik-Shader hinaus. Microsoft fügt hardwarebeschleunigte lineare Algebra direkt zu HLSL hinzu sowie einen separaten Pfad für größere ML-Modelle, wodurch das Fundament für neuronale Texturen, erlernte Materialien, neuronale Beleuchtung und andere KI-gesteuerte Rendering-Techniken gelegt wird.","\u002Fuploads\u002F2026\u002F09\u002Fdirectx-is-becoming-an-ml-platform-what-linear-algebra-and-neural-shaders-mean-for-future-games-1790378019857-utigyk.webp","directx-is-becoming-an-ml-platform-what-linear-algebra-and-neural-shaders-mean-for-future-games-1790378019857-utigyk","PUBLISHED","2026-09-25T17:12:00.000Z","2026-09-25T23:12:37.728Z","2026-09-26T06:45:35.226Z",{"en":1187,"de":1188,"sr":1189,"es":1190,"fr":1191,"it":1192,"ru":1193,"zh":1194},"\u002Fblog\u002Fdirectx-is-becoming-an-ml-platform-what-linear-algebra-and-neural-shaders-mean-for-future-games","\u002Fde\u002Fblog\u002Fdirectx-is-becoming-an-ml-platform-what-linear-algebra-and-neural-shaders-mean-for-future-games","\u002Fsr\u002Fblog\u002Fdirectx-is-becoming-an-ml-platform-what-linear-algebra-and-neural-shaders-mean-for-future-games","\u002Fes\u002Fblog\u002Fdirectx-is-becoming-an-ml-platform-what-linear-algebra-and-neural-shaders-mean-for-future-games","\u002Ffr\u002Fblog\u002Fdirectx-is-becoming-an-ml-platform-what-linear-algebra-and-neural-shaders-mean-for-future-games","\u002Fit\u002Fblog\u002Fdirectx-is-becoming-an-ml-platform-what-linear-algebra-and-neural-shaders-mean-for-future-games","\u002Fru\u002Fblog\u002Fdirectx-is-becoming-an-ml-platform-what-linear-algebra-and-neural-shaders-mean-for-future-games","\u002Fzh\u002Fblog\u002Fdirectx-is-becoming-an-ml-platform-what-linear-algebra-and-neural-shaders-mean-for-future-games",[1196,1200,1204,1208,1212],{"id":1197,"name":1198,"slug":1199},251,"Unschärfe und Persistenz","blur-and-persistence",{"id":1201,"name":1202,"slug":1203},252,"Overdrive und Smearing","overdrive-and-smearing",{"id":1205,"name":1206,"slug":1207},253,"Bildwiederholrate und Klarheit","refresh-and-clarity",{"id":1209,"name":1210,"slug":1211},430,"Animal Crossing","animal-crossing",{"id":1213,"name":1214,"slug":1215},220,"Design im Dienste der Nutzung","design-that-serves-use",{"id":392,"login":1217,"email":1218,"displayName":1219},"aleksandar","aleksandar@stajic.de","Aleksandar Stajic",[1221,1726],{"lang":8,"title":1222,"content":1223,"contentJson":1224,"excerpt":1725},"DirectX Is Becoming an ML Platform: What Linear Algebra and Neural Shaders Mean for Future Games","{\"time\":1790405124627,\"blocks\":[{\"id\":\"intro\",\"type\":\"paragraph\",\"data\":{\"text\":\"DirectX is no longer only a graphics API that sends traditional shaders to the GPU. Microsoft is adding machine-learning primitives directly to HLSL and a second path for running larger ML graphs inside the DirectX ecosystem. That changes where neural rendering can live inside future PC games.\"},\"tunes\":{}},{\"id\":\"direct\",\"type\":\"callout\",\"data\":{\"variant\":\"info\",\"title\":\"Direct answer\",\"body\":\"\u003Cstrong>DirectX is becoming an ML-capable graphics platform.\u003C\u002Fstrong> Small neural workloads can run directly inside shaders through DX Linear Algebra, while larger models are being targeted by the DirectX Compute Graph Compiler. The goal is to let game engines use GPU AI hardware without building a separate vendor-specific path for every technique.\"},\"tunes\":{}},{\"id\":\"status-note\",\"type\":\"callout\",\"data\":{\"variant\":\"note\",\"title\":\"Current status\",\"body\":\"As of September 2026, \u003Cstrong>DX Linear Algebra is still a preview technology\u003C\u002Fstrong> in the Shader Model 6.10 \u002F Agility SDK preview path. Microsoft announced the DirectX Compute Graph Compiler for private preview rather than as a broadly shipping retail feature. This article explains the architecture and direction, not a claim that every current game can use it today.\"},\"tunes\":{}},{\"id\":\"toc\",\"type\":\"tableOfContents\",\"data\":{\"title\":\"Contents\",\"minLevel\":2,\"maxLevel\":3},\"tunes\":{}},{\"id\":\"h-why\",\"type\":\"header\",\"data\":{\"text\":\"Why neural rendering needs new DirectX primitives\",\"level\":2},\"tunes\":{}},{\"id\":\"p-why-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"Modern GPUs already contain specialized hardware for matrix operations used by machine learning. The problem for a game developer is not only whether that hardware exists, but how to access it efficiently from a real-time graphics pipeline.\"},\"tunes\":{}},{\"id\":\"p-why-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"Microsoft first explored this with Cooperative Vector support. In 2026, that work evolved into a broader DirectX Linear Algebra design that supports both vector-matrix and matrix-matrix operations.\"},\"tunes\":{}},{\"id\":\"p-why-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"That matters because different neural-rendering jobs have different shapes. A tiny model evaluating material behavior per pixel is not the same workload as a large super-resolution or denoising graph.\"},\"tunes\":{}},{\"id\":\"h-two-level\",\"type\":\"header\",\"data\":{\"text\":\"The Two-Level DirectX ML Model\",\"level\":2},\"tunes\":{}},{\"id\":\"two-level-flow\",\"type\":\"processFlow\",\"data\":{\"title\":\"Two ways ML can enter the DirectX graphics pipeline\",\"orientation\":\"auto\",\"steps\":[{\"label\":\"1. Shader-level ML\",\"description\":\"Small neural or linear-algebra workloads execute directly from HLSL alongside traditional shader code.\"},{\"label\":\"2. DX Linear Algebra\",\"description\":\"The shader can request hardware-accelerated vector and matrix operations instead of manually implementing every ML primitive.\"},{\"label\":\"3. Model-level ML\",\"description\":\"Larger neural networks are represented as complete computation graphs rather than hand-written shader fragments.\"},{\"label\":\"4. DirectX Compute Graph Compiler\",\"description\":\"Microsoft's planned compiler path analyzes and lowers those graphs into optimized GPU workloads integrated with D3D12 queues and command lists.\"}]},\"tunes\":{}},{\"id\":\"simple-diff\",\"type\":\"callout\",\"data\":{\"variant\":\"success\",\"title\":\"The simple difference\",\"body\":\"\u003Cstrong>DX Linear Algebra:\u003C\u002Fstrong> put small ML math inside the shader.\u003Cbr>\u003Cstrong>Compute Graph Compiler:\u003C\u002Fstrong> bring a larger ML model into the engine as a graph.\"},\"tunes\":{}},{\"id\":\"h-linalg\",\"type\":\"header\",\"data\":{\"text\":\"What DX Linear Algebra actually gives a shader\",\"level\":2},\"tunes\":{}},{\"id\":\"p-linalg-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"Traditional HLSL is built around graphics and compute operations. Neural workloads rely heavily on linear algebra: vectors, matrices, multiplication, accumulation and data layouts optimized for those operations.\"},\"tunes\":{}},{\"id\":\"p-linalg-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"The Shader Model 6.10 preview adds first-class matrix APIs so developers can express those workloads more directly and let the driver map them to specialized hardware.\"},\"tunes\":{}},{\"id\":\"p-linalg-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"Microsoft's April 2026 preview explicitly describes this as a unified path for neural rendering, ML and image-processing workloads rather than a graphics-only feature.\"},\"tunes\":{}},{\"id\":\"math-table\",\"type\":\"comparison\",\"data\":{\"title\":\"Traditional shader math vs ML-oriented shader math\",\"layout\":\"table\",\"columns\":[{\"id\":\"traditional\",\"label\":\"Traditional shader focus\"},{\"id\":\"ml\",\"label\":\"ML-oriented focus\"}],\"rows\":[{\"id\":\"work\",\"label\":\"Typical work\",\"values\":[\"\",\"\"]},{\"id\":\"hardware\",\"label\":\"Hardware path\",\"values\":[\"\",\"\"]},{\"id\":\"code\",\"label\":\"Developer expression\",\"values\":[\"\",\"\"]}]},\"tunes\":{}},{\"id\":\"h-coop\",\"type\":\"header\",\"data\":{\"text\":\"Why Cooperative Vector was only the beginning\",\"level\":2},\"tunes\":{}},{\"id\":\"p-coop-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"Cooperative Vector allowed shader threads to request vector-matrix work that drivers could map to specialized hardware. That was useful for highly parallel per-pixel workloads.\"},\"tunes\":{}},{\"id\":\"p-coop-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"Microsoft later concluded that many important ML workloads need more than vector-matrix operations. Super resolution, denoising, temporal reconstruction, larger image models and general inference can require matrix-matrix operations and shared work across many threads.\"},\"tunes\":{}},{\"id\":\"p-coop-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"DX Linear Algebra therefore broadens the model instead of treating Cooperative Vector as the final abstraction.\"},\"tunes\":{}},{\"id\":\"h-usecases\",\"type\":\"header\",\"data\":{\"text\":\"What can actually run inside a shader?\",\"level\":2},\"tunes\":{}},{\"id\":\"p-use-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"The most interesting shader-level ML workloads are small enough to execute close to the graphics data they operate on.\"},\"tunes\":{}},{\"id\":\"usecases-table\",\"type\":\"table\",\"data\":{\"withHeadings\":true,\"stretched\":false,\"content\":[[\"Workload\",\"Why shader-level ML fits\"],[\"Neural texture compression\",\"A small network can reconstruct texture information near the point where the shader needs it\"],[\"Neural material evaluation\",\"A learned function can replace or augment expensive hand-authored material math\"],[\"Neural radiance caching\",\"Per-pixel or local inference can estimate lighting information from learned scene behavior\"],[\"Small denoising\u002Freconstruction kernels\",\"ML operations can sit directly beside the rendering stage they improve\"],[\"Image-processing inference\",\"Matrix operations can be embedded into GPU processing without a separate external runtime\"]]},\"tunes\":{}},{\"id\":\"h-texture\",\"type\":\"header\",\"data\":{\"text\":\"Why this matters for texture memory\",\"level\":2},\"tunes\":{}},{\"id\":\"p-tex-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"One of Microsoft's recurring examples is neural texture compression.\"},\"tunes\":{}},{\"id\":\"p-tex-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"Instead of storing every texture channel at conventional fidelity, a game can store a more compact representation and use a small neural network to reconstruct detail during rendering.\"},\"tunes\":{}},{\"id\":\"p-tex-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"That trades some GPU inference work for lower storage or memory pressure. The exact benefit depends on the technique and hardware, but the architectural change is important: some visual detail can become computation instead of stored data.\"},\"tunes\":{}},{\"id\":\"ref-vram\",\"type\":\"referralArticle\",\"data\":{\"url\":\"https:\u002F\u002Ffigure.rocks\u002Fblog\u002Fvram-usage-is-not-vram-requirement-why-a-full-memory-meter-does-not-tell-the-whole-story\",\"title\":\"VRAM Usage Is Not VRAM Requirement: Why a Full Memory Meter Does Not Tell the Whole Story\",\"excerpt\":\"A practical guide to VRAM capacity, residency budgets, working sets and why memory pressure is more complicated than one usage number.\",\"ctaLabel\":\"Read the VRAM guide\"},\"tunes\":{}},{\"id\":\"h-models\",\"type\":\"header\",\"data\":{\"text\":\"Why full models need a different path\",\"level\":2},\"tunes\":{}},{\"id\":\"p-models-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"Hand-writing a few matrix operations in HLSL is practical for small neural functions. It becomes much less practical when the workload is a complete modern model with many layers, dependencies and intermediate tensors.\"},\"tunes\":{}},{\"id\":\"p-models-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"Microsoft's DirectX Compute Graph Compiler is designed for this larger class of workload.\"},\"tunes\":{}},{\"id\":\"p-models-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"Instead of rewriting the model as custom shader code, the compiler can accept a computation graph, analyze the whole graph, plan memory, fuse operations and lower the result into GPU work that integrates with DirectX 12.\"},\"tunes\":{}},{\"id\":\"h-boundary\",\"type\":\"header\",\"data\":{\"text\":\"The Shader-or-Graph Boundary\",\"level\":2},\"tunes\":{}},{\"id\":\"boundary-table\",\"type\":\"comparison\",\"data\":{\"title\":\"When the ML workload belongs in HLSL vs a model compiler\",\"layout\":\"table\",\"columns\":[{\"id\":\"shader\",\"label\":\"Shader-level path\"},{\"id\":\"graph\",\"label\":\"Model-level path\"}],\"rows\":[{\"id\":\"size\",\"label\":\"Model size\",\"values\":[\"\",\"\"]},{\"id\":\"location\",\"label\":\"Execution style\",\"values\":[\"\",\"\"]},{\"id\":\"authoring\",\"label\":\"Authoring\",\"values\":[\"\",\"\"]},{\"id\":\"optimization\",\"label\":\"Optimization scope\",\"values\":[\"\",\"\"]},{\"id\":\"use\",\"label\":\"Typical use\",\"values\":[\"\",\"\"]}]},\"tunes\":{}},{\"id\":\"h-crossvendor\",\"type\":\"header\",\"data\":{\"text\":\"Why cross-vendor support matters more than another AI feature\",\"level\":2},\"tunes\":{}},{\"id\":\"p-cross-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"AMD, Intel, NVIDIA and Qualcomm expose different GPU architectures and different forms of dedicated matrix acceleration.\"},\"tunes\":{}},{\"id\":\"p-cross-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"A DirectX abstraction gives Microsoft and the driver vendors a place to translate common HLSL or graph-level ML into the correct hardware path.\"},\"tunes\":{}},{\"id\":\"p-cross-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"That does not make every GPU equally fast, but it can reduce the need for a game engine to implement a completely different neural-rendering API for every vendor.\"},\"tunes\":{}},{\"id\":\"portability-note\",\"type\":\"callout\",\"data\":{\"variant\":\"note\",\"title\":\"Portability is the real platform story\",\"body\":\"The interesting part is not that DirectX can “run AI.” GPUs already could. The platform change is that \u003Cstrong>ML becomes expressible through a common graphics API and toolchain\u003C\u002Fstrong>.\"},\"tunes\":{}},{\"id\":\"h-support\",\"type\":\"header\",\"data\":{\"text\":\"What hardware supports the current preview?\",\"level\":2},\"tunes\":{}},{\"id\":\"p-support-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"The answer depends on the specific Linear Algebra operation and preview driver.\"},\"tunes\":{}},{\"id\":\"p-support-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"Microsoft's Agility SDK 1.721 preview support table lists LinAlg VectorAccumulate for AMD Radeon RX 9000 Series hardware, Intel Xe2-or-newer hardware through an upcoming driver, and NVIDIA RTX hardware through the supported preview path.\"},\"tunes\":{}},{\"id\":\"p-support-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"This is preview-era support, not a universal retail guarantee. Hardware and driver support can change before finalization.\"},\"tunes\":{}},{\"id\":\"h-infra\",\"type\":\"header\",\"data\":{\"text\":\"Neural rendering is becoming infrastructure\",\"level\":2},\"tunes\":{}},{\"id\":\"p-infra-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"DLSS, FSR and other neural graphics technologies are often discussed as branded features visible in a game's settings menu.\"},\"tunes\":{}},{\"id\":\"p-infra-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"DirectX Linear Algebra points to a deeper change. The neural operation can become an internal implementation detail inside the renderer rather than a single optional post-processing feature.\"},\"tunes\":{}},{\"id\":\"p-infra-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"A developer could use ML for textures, materials, lighting, reconstruction or other local functions without exposing each one as a consumer-facing AI toggle.\"},\"tunes\":{}},{\"id\":\"ref-dlss5\",\"type\":\"referralArticle\",\"data\":{\"url\":\"https:\u002F\u002Ffigure.rocks\u002Fblog\u002Fdlss-5-is-not-just-upscaling-what-3d-guided-neural-rendering-actually-changes\",\"title\":\"DLSS 5 Is Not Just Upscaling: What 3D-Guided Neural Rendering Actually Changes\",\"excerpt\":\"How neural rendering is moving beyond upscaling and generated frames into material and lighting reconstruction inside the graphics pipeline.\",\"ctaLabel\":\"Read the DLSS 5 neural-rendering guide\"},\"tunes\":{}},{\"id\":\"h-stack\",\"type\":\"header\",\"data\":{\"text\":\"The Neural Rendering Stack is becoming layered\",\"level\":2},\"tunes\":{}},{\"id\":\"stack-flow\",\"type\":\"processFlow\",\"data\":{\"title\":\"A possible future DirectX game pipeline\",\"orientation\":\"auto\",\"steps\":[{\"label\":\"Traditional engine work\",\"description\":\"Simulation, geometry, visibility and base rendering remain standard engine responsibilities.\"},{\"label\":\"Inline neural shaders\",\"description\":\"Small learned functions reconstruct textures, materials or lighting inside HLSL.\"},{\"label\":\"Larger ML graphs\",\"description\":\"Full reconstruction or inference models execute through a graph-level DirectX path.\"},{\"label\":\"Vendor hardware mapping\",\"description\":\"Drivers map common DirectX operations onto the GPU's specialized AI and matrix units.\"},{\"label\":\"PIX visibility\",\"description\":\"Graphics and ML work can be profiled together instead of living in separate opaque runtimes.\"}]},\"tunes\":{}},{\"id\":\"h-pix\",\"type\":\"header\",\"data\":{\"text\":\"Why unified profiling matters\",\"level\":2},\"tunes\":{}},{\"id\":\"p-pix-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"A neural workload that improves image quality can still damage a game if it unexpectedly consumes frame time, memory bandwidth or VRAM.\"},\"tunes\":{}},{\"id\":\"p-pix-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"Microsoft explicitly includes unified PIX visibility as part of the Compute Graph Compiler direction. That matters because developers need to see graphics and ML work in the same frame capture.\"},\"tunes\":{}},{\"id\":\"p-pix-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"If neural rendering becomes infrastructure, it must be measurable like any other rendering stage.\"},\"tunes\":{}},{\"id\":\"h-not-everything\",\"type\":\"header\",\"data\":{\"text\":\"This does not mean every shader will become a neural network\",\"level\":2},\"tunes\":{}},{\"id\":\"p-not-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"Traditional shader math remains efficient, deterministic and easy to reason about for many workloads.\"},\"tunes\":{}},{\"id\":\"p-not-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"A neural function makes sense when it can approximate or reconstruct something expensive more efficiently, compress data, or produce quality that would otherwise require too much conventional compute or memory.\"},\"tunes\":{}},{\"id\":\"p-not-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"The right architecture will remain hybrid.\"},\"tunes\":{}},{\"id\":\"h-test\",\"type\":\"header\",\"data\":{\"text\":\"The Neural Shader Value Test\",\"level\":2},\"tunes\":{}},{\"id\":\"value-test\",\"type\":\"processFlow\",\"data\":{\"title\":\"When does putting ML into the rendering pipeline actually make sense?\",\"orientation\":\"auto\",\"steps\":[{\"label\":\"1. Identify the expensive traditional operation\",\"description\":\"What compute, bandwidth, memory or storage cost are you trying to replace?\"},{\"label\":\"2. Define the neural substitute\",\"description\":\"What can a small model reconstruct, predict or compress?\"},{\"label\":\"3. Measure inference cost\",\"description\":\"The ML model itself consumes GPU time, memory and bandwidth.\"},{\"label\":\"4. Measure quality stability\",\"description\":\"Look for temporal artifacts, reconstruction errors and failure cases.\"},{\"label\":\"5. Measure net savings\",\"description\":\"The technique is useful only if the avoided traditional cost is worth the added ML cost.\"},{\"label\":\"6. Test across vendors\",\"description\":\"A DirectX abstraction helps portability, but real hardware performance still differs.\"}]},\"tunes\":{}},{\"id\":\"h-gamers\",\"type\":\"header\",\"data\":{\"text\":\"What this means for gamers\",\"level\":2},\"tunes\":{}},{\"id\":\"p-gamers-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"Gamers may never see a “DX Linear Algebra” switch in a graphics menu.\"},\"tunes\":{}},{\"id\":\"p-gamers-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"The likely impact is indirect: smaller texture footprints, better lighting reconstruction, more efficient neural graphics, or new visual techniques that become practical because the engine can access matrix acceleration through a standard path.\"},\"tunes\":{}},{\"id\":\"p-gamers-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"The feature is more important as infrastructure than as a brand.\"},\"tunes\":{}},{\"id\":\"h-change\",\"type\":\"header\",\"data\":{\"text\":\"What would change this answer?\",\"level\":2},\"tunes\":{}},{\"id\":\"p-change-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"The biggest uncertainty is the final retail shape of these APIs. DX Linear Algebra remains in preview, and the Compute Graph Compiler has not yet reached broad retail availability.\"},\"tunes\":{}},{\"id\":\"p-change-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"Final hardware support, API details, compiler behavior and engine adoption may change before these systems become normal shipping-game infrastructure.\"},\"tunes\":{}},{\"id\":\"p-change-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"If major engines adopt the abstractions directly, neural shaders could become much more common without individual game teams implementing every technique from scratch.\"},\"tunes\":{}},{\"id\":\"h-limit\",\"type\":\"header\",\"data\":{\"text\":\"Limitations\",\"level\":2},\"tunes\":{}},{\"id\":\"p-limit-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"This article explains Microsoft's documented DirectX architecture and preview APIs. It does not claim that DX Linear Algebra currently improves performance in every game or that the Compute Graph Compiler is a finished retail product.\"},\"tunes\":{}},{\"id\":\"p-limit-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"Microsoft's examples describe capability and intended use. Real benefits depend on the model, engine integration, GPU architecture, drivers and workload.\"},\"tunes\":{}},{\"id\":\"h-conclusion\",\"type\":\"header\",\"data\":{\"text\":\"Conclusion\",\"level\":2},\"tunes\":{}},{\"id\":\"p-conc-1\",\"type\":\"paragraph\",\"data\":{\"text\":\"The important DirectX change is not another checkbox called AI.\"},\"tunes\":{}},{\"id\":\"p-conc-2\",\"type\":\"paragraph\",\"data\":{\"text\":\"It is that machine-learning math is moving into the graphics programming model itself. Small neural functions can sit inside shaders, larger models can move toward graph-level compilation, and the same DirectX toolchain can expose those workloads across multiple GPU vendors.\"},\"tunes\":{}},{\"id\":\"p-conc-3\",\"type\":\"paragraph\",\"data\":{\"text\":\"That is how neural rendering stops being one branded feature and starts becoming part of the rendering infrastructure.\"},\"tunes\":{}},{\"id\":\"h-faq\",\"type\":\"header\",\"data\":{\"text\":\"FAQ\",\"level\":2},\"tunes\":{}},{\"id\":\"faq\",\"type\":\"faq\",\"data\":{\"title\":\"DirectX Linear Algebra and neural shaders\",\"items\":[{\"id\":\"faq1\",\"question\":\"What is DirectX Linear Algebra?\",\"answer\":\"It is a DirectX\u002FHLSL feature set for hardware-accelerated vector and matrix operations used by machine learning, neural rendering and image-processing workloads.\"},{\"id\":\"faq2\",\"question\":\"What is a neural shader?\",\"answer\":\"A useful plain-English description is a shader that includes a learned neural function or ML inference step as part of its graphics work.\"},{\"id\":\"faq3\",\"question\":\"Is DX Linear Algebra already a normal retail DirectX feature?\",\"answer\":\"As of September 2026 it remains in the Shader Model 6.10 \u002F Agility SDK preview path.\"},{\"id\":\"faq4\",\"question\":\"What is the DirectX Compute Graph Compiler?\",\"answer\":\"It is Microsoft's announced model-level ML compiler API intended to take larger computation graphs and lower them into optimized GPU workloads integrated with D3D12.\"},{\"id\":\"faq5\",\"question\":\"Why not run every ML model directly in HLSL?\",\"answer\":\"Small functions fit shader-level authoring well, while large models benefit from whole-graph optimization, memory planning and operator fusion.\"},{\"id\":\"faq6\",\"question\":\"Will this replace DLSS or FSR?\",\"answer\":\"Not directly. DirectX provides lower-level infrastructure that vendors and developers can use for neural graphics. Branded technologies can still implement their own models and integration strategies.\"}]},\"tunes\":{}},{\"id\":\"h-glossary\",\"type\":\"header\",\"data\":{\"text\":\"Glossary\",\"level\":2},\"tunes\":{}},{\"id\":\"glossary\",\"type\":\"glossary\",\"data\":{\"title\":\"Key DirectX ML terms\",\"entries\":[{\"term\":\"DX Linear Algebra\",\"definition\":\"DirectX\u002FHLSL APIs for accelerated vector and matrix operations intended for neural rendering, ML and image-processing workloads.\",\"anchor\":\"dx-linear-algebra\"},{\"term\":\"Cooperative Vector\",\"definition\":\"An earlier DirectX approach for accelerated vector-matrix operations inside shaders that helped establish the shader-level neural-rendering path.\",\"anchor\":\"cooperative-vector\"},{\"term\":\"Shader Model 6.10\",\"definition\":\"The preview shader-model generation containing the current DirectX Linear Algebra matrix APIs.\",\"anchor\":\"shader-model-6-10\"},{\"term\":\"DirectX Compute Graph Compiler\",\"definition\":\"Microsoft's announced compiler API for optimizing and executing larger ML computation graphs as native DirectX GPU workloads.\",\"anchor\":\"compute-graph-compiler\"},{\"term\":\"Neural shader\",\"definition\":\"A practical term for a shader that performs learned inference or neural computation as part of graphics processing.\",\"anchor\":\"neural-shader\"},{\"term\":\"Shader-or-Graph Boundary\",\"definition\":\"A Figure Rocks model for deciding whether an ML workload belongs as small inline shader math or as a larger model-level computation graph.\",\"anchor\":\"shader-or-graph-boundary\"},{\"term\":\"Neural Shader Value Test\",\"definition\":\"A Figure Rocks workflow for deciding whether the traditional compute or memory cost avoided by a neural technique is worth its inference cost and quality trade-offs.\",\"anchor\":\"neural-shader-value-test\"}]},\"tunes\":{}},{\"id\":\"h-sources\",\"type\":\"header\",\"data\":{\"text\":\"Primary sources\",\"level\":2},\"tunes\":{}},{\"id\":\"src-ms-ml-era\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fdevblogs.microsoft.com\u002Fdirectx\u002Fevolving-directx-for-the-ml-era-on-windows\u002F\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"Microsoft DirectX — Evolving DirectX for the ML Era on Windows\",\"description\":\"Official GDC 2026 architecture overview covering shader-level ML, DX Linear Algebra and the DirectX Compute Graph Compiler.\"}},\"tunes\":{}},{\"id\":\"src-ms-linalg\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fdevblogs.microsoft.com\u002Fdirectx\u002Fd3d12-linalg-preview\u002F\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"Microsoft DirectX — D3D12 LinAlg Matrix Preview\",\"description\":\"Official April 2026 preview explaining the unified Linear Algebra APIs, matrix operations and neural-rendering motivation.\"}},\"tunes\":{}},{\"id\":\"src-ms-agility721\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fdevblogs.microsoft.com\u002Fdirectx\u002Fannouncing-agilitysdk-721-preview-and-more-shader-model-6-10-features\u002F\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"Microsoft DirectX — Agility SDK 1.721 Preview\",\"description\":\"Official May 2026 release documenting Shader Model 6.10 Linear Algebra updates and preview hardware support.\"}},\"tunes\":{}},{\"id\":\"src-ms-gdc\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fdeveloper.microsoft.com\u002Fen-us\u002Fgames\u002Farticles\u002F2026\u002F03\u002Fgdc-2026-evolving-directx-for-ml-era-on-windows\u002F\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"Microsoft Game Dev — GDC 2026: Evolving DirectX for the ML Era\",\"description\":\"Official Microsoft Game Dev summary explaining shader-level and model-level ML and the role of the Compute Graph Compiler.\"}},\"tunes\":{}},{\"id\":\"src-ms-coop\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fdevblogs.microsoft.com\u002Fdirectx\u002Fcooperative-vector\u002F\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"Microsoft DirectX — D3D12 Cooperative Vector\",\"description\":\"Official background on hardware-accelerated vector\u002Fmatrix operations and neural rendering directly from shader threads.\"}},\"tunes\":{}}],\"version\":\"2.31.6\"}",{"time":1225,"blocks":1226,"version":1724},1790405124627,[1227,1231,1236,1241,1245,1249,1253,1257,1261,1265,1280,1285,1289,1293,1297,1301,1320,1324,1328,1332,1336,1340,1344,1365,1369,1373,1377,1381,1388,1392,1396,1400,1404,1408,1433,1437,1441,1445,1449,1454,1458,1462,1466,1470,1474,1478,1482,1486,1493,1497,1517,1521,1525,1529,1533,1537,1541,1545,1549,1553,1576,1580,1584,1588,1592,1596,1600,1604,1608,1612,1616,1620,1624,1628,1632,1636,1639,1662,1666,1688,1692,1699,1705,1711,1718],{"id":541,"data":1228,"type":544,"tunes":1230},{"text":1229},"DirectX is no longer only a graphics API that sends traditional shaders to the GPU. Microsoft is adding machine-learning primitives directly to HLSL and a second path for running larger ML graphs inside the DirectX ecosystem. That changes where neural rendering can live inside future PC games.",{},{"id":547,"data":1232,"type":552,"tunes":1235},{"body":1233,"title":1234,"variant":551},"\u003Cstrong>DirectX is becoming an ML-capable graphics platform.\u003C\u002Fstrong> Small neural workloads can run directly inside shaders through DX Linear Algebra, while larger models are being targeted by the DirectX Compute Graph Compiler. The goal is to let game engines use GPU AI hardware without building a separate vendor-specific path for every technique.","Direct answer",{},{"id":555,"data":1237,"type":552,"tunes":1240},{"body":1238,"title":1239,"variant":559},"As of September 2026, \u003Cstrong>DX Linear Algebra is still a preview technology\u003C\u002Fstrong> in the Shader Model 6.10 \u002F Agility SDK preview path. Microsoft announced the DirectX Compute Graph Compiler for private preview rather than as a broadly shipping retail feature. This article explains the architecture and direction, not a claim that every current game can use it today.","Current status",{},{"id":562,"data":1242,"type":566,"tunes":1244},{"title":1243,"maxLevel":565,"minLevel":47},"Contents",{},{"id":569,"data":1246,"type":572,"tunes":1248},{"text":1247,"level":47},"Why neural rendering needs new DirectX primitives",{},{"id":575,"data":1250,"type":544,"tunes":1252},{"text":1251},"Modern GPUs already contain specialized hardware for matrix operations used by machine learning. The problem for a game developer is not only whether that hardware exists, but how to access it efficiently from a real-time graphics pipeline.",{},{"id":580,"data":1254,"type":544,"tunes":1256},{"text":1255},"Microsoft first explored this with Cooperative Vector support. In 2026, that work evolved into a broader DirectX Linear Algebra design that supports both vector-matrix and matrix-matrix operations.",{},{"id":585,"data":1258,"type":544,"tunes":1260},{"text":1259},"That matters because different neural-rendering jobs have different shapes. A tiny model evaluating material behavior per pixel is not the same workload as a large super-resolution or denoising graph.",{},{"id":590,"data":1262,"type":572,"tunes":1264},{"text":1263,"level":47},"The Two-Level DirectX ML Model",{},{"id":595,"data":1266,"type":612,"tunes":1279},{"steps":1267,"title":1278,"orientation":611},[1268,1271,1273,1276],{"label":1269,"description":1270},"1. Shader-level ML","Small neural or linear-algebra workloads execute directly from HLSL alongside traditional shader code.",{"label":602,"description":1272},"The shader can request hardware-accelerated vector and matrix operations instead of manually implementing every ML primitive.",{"label":1274,"description":1275},"3. Model-level ML","Larger neural networks are represented as complete computation graphs rather than hand-written shader fragments.",{"label":608,"description":1277},"Microsoft's planned compiler path analyzes and lowers those graphs into optimized GPU workloads integrated with D3D12 queues and command lists.","Two ways ML can enter the DirectX graphics pipeline",{},{"id":615,"data":1281,"type":552,"tunes":1284},{"body":1282,"title":1283,"variant":619},"\u003Cstrong>DX Linear Algebra:\u003C\u002Fstrong> put small ML math inside the shader.\u003Cbr>\u003Cstrong>Compute Graph Compiler:\u003C\u002Fstrong> bring a larger ML model into the engine as a graph.","The simple difference",{},{"id":622,"data":1286,"type":572,"tunes":1288},{"text":1287,"level":47},"What DX Linear Algebra actually gives a shader",{},{"id":627,"data":1290,"type":544,"tunes":1292},{"text":1291},"Traditional HLSL is built around graphics and compute operations. Neural workloads rely heavily on linear algebra: vectors, matrices, multiplication, accumulation and data layouts optimized for those operations.",{},{"id":632,"data":1294,"type":544,"tunes":1296},{"text":1295},"The Shader Model 6.10 preview adds first-class matrix APIs so developers can express those workloads more directly and let the driver map them to specialized hardware.",{},{"id":637,"data":1298,"type":544,"tunes":1300},{"text":1299},"Microsoft's April 2026 preview explicitly describes this as a unified path for neural rendering, ML and image-processing workloads rather than a graphics-only feature.",{},{"id":642,"data":1302,"type":666,"tunes":1319},{"rows":1303,"title":1313,"layout":658,"columns":1314},[1304,1307,1310],{"id":646,"label":1305,"values":1306},"Typical work",[13,13],{"id":650,"label":1308,"values":1309},"Hardware path",[13,13],{"id":654,"label":1311,"values":1312},"Developer expression",[13,13],"Traditional shader math vs ML-oriented shader math",[1315,1317],{"id":661,"label":1316},"Traditional shader focus",{"id":664,"label":1318},"ML-oriented focus",{},{"id":669,"data":1321,"type":572,"tunes":1323},{"text":1322,"level":47},"Why Cooperative Vector was only the beginning",{},{"id":674,"data":1325,"type":544,"tunes":1327},{"text":1326},"Cooperative Vector allowed shader threads to request vector-matrix work that drivers could map to specialized hardware. That was useful for highly parallel per-pixel workloads.",{},{"id":679,"data":1329,"type":544,"tunes":1331},{"text":1330},"Microsoft later concluded that many important ML workloads need more than vector-matrix operations. Super resolution, denoising, temporal reconstruction, larger image models and general inference can require matrix-matrix operations and shared work across many threads.",{},{"id":684,"data":1333,"type":544,"tunes":1335},{"text":1334},"DX Linear Algebra therefore broadens the model instead of treating Cooperative Vector as the final abstraction.",{},{"id":689,"data":1337,"type":572,"tunes":1339},{"text":1338,"level":47},"What can actually run inside a shader?",{},{"id":694,"data":1341,"type":544,"tunes":1343},{"text":1342},"The most interesting shader-level ML workloads are small enough to execute close to the graphics data they operate on.",{},{"id":699,"data":1345,"type":658,"tunes":1364},{"content":1346,"stretched":720,"withHeadings":15},[1347,1349,1352,1355,1358,1361],[703,1348],"Why shader-level ML fits",[1350,1351],"Neural texture compression","A small network can reconstruct texture information near the point where the shader needs it",[1353,1354],"Neural material evaluation","A learned function can replace or augment expensive hand-authored material math",[1356,1357],"Neural radiance caching","Per-pixel or local inference can estimate lighting information from learned scene behavior",[1359,1360],"Small denoising\u002Freconstruction kernels","ML operations can sit directly beside the rendering stage they improve",[1362,1363],"Image-processing inference","Matrix operations can be embedded into GPU processing without a separate external runtime",{},{"id":723,"data":1366,"type":572,"tunes":1368},{"text":1367,"level":47},"Why this matters for texture memory",{},{"id":728,"data":1370,"type":544,"tunes":1372},{"text":1371},"One of Microsoft's recurring examples is neural texture compression.",{},{"id":733,"data":1374,"type":544,"tunes":1376},{"text":1375},"Instead of storing every texture channel at conventional fidelity, a game can store a more compact representation and use a small neural network to reconstruct detail during rendering.",{},{"id":738,"data":1378,"type":544,"tunes":1380},{"text":1379},"That trades some GPU inference work for lower storage or memory pressure. The exact benefit depends on the technique and hardware, but the architectural change is important: some visual detail can become computation instead of stored data.",{},{"id":743,"data":1382,"type":749,"tunes":1387},{"url":1383,"title":1384,"excerpt":1385,"ctaLabel":1386},"https:\u002F\u002Ffigure.rocks\u002Fblog\u002Fvram-usage-is-not-vram-requirement-why-a-full-memory-meter-does-not-tell-the-whole-story","VRAM Usage Is Not VRAM Requirement: Why a Full Memory Meter Does Not Tell the Whole Story","A practical guide to VRAM capacity, residency budgets, working sets and why memory pressure is more complicated than one usage number.","Read the VRAM guide",{},{"id":752,"data":1389,"type":572,"tunes":1391},{"text":1390,"level":47},"Why full models need a different path",{},{"id":757,"data":1393,"type":544,"tunes":1395},{"text":1394},"Hand-writing a few matrix operations in HLSL is practical for small neural functions. It becomes much less practical when the workload is a complete modern model with many layers, dependencies and intermediate tensors.",{},{"id":762,"data":1397,"type":544,"tunes":1399},{"text":1398},"Microsoft's DirectX Compute Graph Compiler is designed for this larger class of workload.",{},{"id":767,"data":1401,"type":544,"tunes":1403},{"text":1402},"Instead of rewriting the model as custom shader code, the compiler can accept a computation graph, analyze the whole graph, plan memory, fuse operations and lower the result into GPU work that integrates with DirectX 12.",{},{"id":772,"data":1405,"type":572,"tunes":1407},{"text":1406,"level":47},"The Shader-or-Graph Boundary",{},{"id":777,"data":1409,"type":666,"tunes":1432},{"rows":1410,"title":1426,"layout":658,"columns":1427},[1411,1414,1417,1420,1423],{"id":781,"label":1412,"values":1413},"Model size",[13,13],{"id":785,"label":1415,"values":1416},"Execution style",[13,13],{"id":789,"label":1418,"values":1419},"Authoring",[13,13],{"id":793,"label":1421,"values":1422},"Optimization scope",[13,13],{"id":797,"label":1424,"values":1425},"Typical use",[13,13],"When the ML workload belongs in HLSL vs a model compiler",[1428,1430],{"id":803,"label":1429},"Shader-level path",{"id":806,"label":1431},"Model-level path",{},{"id":810,"data":1434,"type":572,"tunes":1436},{"text":1435,"level":47},"Why cross-vendor support matters more than another AI feature",{},{"id":815,"data":1438,"type":544,"tunes":1440},{"text":1439},"AMD, Intel, NVIDIA and Qualcomm expose different GPU architectures and different forms of dedicated matrix acceleration.",{},{"id":820,"data":1442,"type":544,"tunes":1444},{"text":1443},"A DirectX abstraction gives Microsoft and the driver vendors a place to translate common HLSL or graph-level ML into the correct hardware path.",{},{"id":825,"data":1446,"type":544,"tunes":1448},{"text":1447},"That does not make every GPU equally fast, but it can reduce the need for a game engine to implement a completely different neural-rendering API for every vendor.",{},{"id":830,"data":1450,"type":552,"tunes":1453},{"body":1451,"title":1452,"variant":559},"The interesting part is not that DirectX can “run AI.” GPUs already could. The platform change is that \u003Cstrong>ML becomes expressible through a common graphics API and toolchain\u003C\u002Fstrong>.","Portability is the real platform story",{},{"id":836,"data":1455,"type":572,"tunes":1457},{"text":1456,"level":47},"What hardware supports the current preview?",{},{"id":841,"data":1459,"type":544,"tunes":1461},{"text":1460},"The answer depends on the specific Linear Algebra operation and preview driver.",{},{"id":846,"data":1463,"type":544,"tunes":1465},{"text":1464},"Microsoft's Agility SDK 1.721 preview support table lists LinAlg VectorAccumulate for AMD Radeon RX 9000 Series hardware, Intel Xe2-or-newer hardware through an upcoming driver, and NVIDIA RTX hardware through the supported preview path.",{},{"id":851,"data":1467,"type":544,"tunes":1469},{"text":1468},"This is preview-era support, not a universal retail guarantee. Hardware and driver support can change before finalization.",{},{"id":856,"data":1471,"type":572,"tunes":1473},{"text":1472,"level":47},"Neural rendering is becoming infrastructure",{},{"id":861,"data":1475,"type":544,"tunes":1477},{"text":1476},"DLSS, FSR and other neural graphics technologies are often discussed as branded features visible in a game's settings menu.",{},{"id":866,"data":1479,"type":544,"tunes":1481},{"text":1480},"DirectX Linear Algebra points to a deeper change. The neural operation can become an internal implementation detail inside the renderer rather than a single optional post-processing feature.",{},{"id":871,"data":1483,"type":544,"tunes":1485},{"text":1484},"A developer could use ML for textures, materials, lighting, reconstruction or other local functions without exposing each one as a consumer-facing AI toggle.",{},{"id":876,"data":1487,"type":749,"tunes":1492},{"url":1488,"title":1489,"excerpt":1490,"ctaLabel":1491},"https:\u002F\u002Ffigure.rocks\u002Fblog\u002Fdlss-5-is-not-just-upscaling-what-3d-guided-neural-rendering-actually-changes","DLSS 5 Is Not Just Upscaling: What 3D-Guided Neural Rendering Actually Changes","How neural rendering is moving beyond upscaling and generated frames into material and lighting reconstruction inside the graphics pipeline.","Read the DLSS 5 neural-rendering guide",{},{"id":884,"data":1494,"type":572,"tunes":1496},{"text":1495,"level":47},"The Neural Rendering Stack is becoming layered",{},{"id":889,"data":1498,"type":612,"tunes":1516},{"steps":1499,"title":1515,"orientation":611},[1500,1503,1506,1509,1512],{"label":1501,"description":1502},"Traditional engine work","Simulation, geometry, visibility and base rendering remain standard engine responsibilities.",{"label":1504,"description":1505},"Inline neural shaders","Small learned functions reconstruct textures, materials or lighting inside HLSL.",{"label":1507,"description":1508},"Larger ML graphs","Full reconstruction or inference models execute through a graph-level DirectX path.",{"label":1510,"description":1511},"Vendor hardware mapping","Drivers map common DirectX operations onto the GPU's specialized AI and matrix units.",{"label":1513,"description":1514},"PIX visibility","Graphics and ML work can be profiled together instead of living in separate opaque runtimes.","A possible future DirectX game pipeline",{},{"id":910,"data":1518,"type":572,"tunes":1520},{"text":1519,"level":47},"Why unified profiling matters",{},{"id":915,"data":1522,"type":544,"tunes":1524},{"text":1523},"A neural workload that improves image quality can still damage a game if it unexpectedly consumes frame time, memory bandwidth or VRAM.",{},{"id":920,"data":1526,"type":544,"tunes":1528},{"text":1527},"Microsoft explicitly includes unified PIX visibility as part of the Compute Graph Compiler direction. That matters because developers need to see graphics and ML work in the same frame capture.",{},{"id":925,"data":1530,"type":544,"tunes":1532},{"text":1531},"If neural rendering becomes infrastructure, it must be measurable like any other rendering stage.",{},{"id":930,"data":1534,"type":572,"tunes":1536},{"text":1535,"level":47},"This does not mean every shader will become a neural network",{},{"id":935,"data":1538,"type":544,"tunes":1540},{"text":1539},"Traditional shader math remains efficient, deterministic and easy to reason about for many workloads.",{},{"id":940,"data":1542,"type":544,"tunes":1544},{"text":1543},"A neural function makes sense when it can approximate or reconstruct something expensive more efficiently, compress data, or produce quality that would otherwise require too much conventional compute or memory.",{},{"id":945,"data":1546,"type":544,"tunes":1548},{"text":1547},"The right architecture will remain hybrid.",{},{"id":950,"data":1550,"type":572,"tunes":1552},{"text":1551,"level":47},"The Neural Shader Value Test",{},{"id":955,"data":1554,"type":612,"tunes":1575},{"steps":1555,"title":1574,"orientation":611},[1556,1559,1562,1565,1568,1571],{"label":1557,"description":1558},"1. Identify the expensive traditional operation","What compute, bandwidth, memory or storage cost are you trying to replace?",{"label":1560,"description":1561},"2. Define the neural substitute","What can a small model reconstruct, predict or compress?",{"label":1563,"description":1564},"3. Measure inference cost","The ML model itself consumes GPU time, memory and bandwidth.",{"label":1566,"description":1567},"4. Measure quality stability","Look for temporal artifacts, reconstruction errors and failure cases.",{"label":1569,"description":1570},"5. Measure net savings","The technique is useful only if the avoided traditional cost is worth the added ML cost.",{"label":1572,"description":1573},"6. Test across vendors","A DirectX abstraction helps portability, but real hardware performance still differs.","When does putting ML into the rendering pipeline actually make sense?",{},{"id":979,"data":1577,"type":572,"tunes":1579},{"text":1578,"level":47},"What this means for gamers",{},{"id":984,"data":1581,"type":544,"tunes":1583},{"text":1582},"Gamers may never see a “DX Linear Algebra” switch in a graphics menu.",{},{"id":989,"data":1585,"type":544,"tunes":1587},{"text":1586},"The likely impact is indirect: smaller texture footprints, better lighting reconstruction, more efficient neural graphics, or new visual techniques that become practical because the engine can access matrix acceleration through a standard path.",{},{"id":994,"data":1589,"type":544,"tunes":1591},{"text":1590},"The feature is more important as infrastructure than as a brand.",{},{"id":999,"data":1593,"type":572,"tunes":1595},{"text":1594,"level":47},"What would change this answer?",{},{"id":1004,"data":1597,"type":544,"tunes":1599},{"text":1598},"The biggest uncertainty is the final retail shape of these APIs. DX Linear Algebra remains in preview, and the Compute Graph Compiler has not yet reached broad retail availability.",{},{"id":1009,"data":1601,"type":544,"tunes":1603},{"text":1602},"Final hardware support, API details, compiler behavior and engine adoption may change before these systems become normal shipping-game infrastructure.",{},{"id":1014,"data":1605,"type":544,"tunes":1607},{"text":1606},"If major engines adopt the abstractions directly, neural shaders could become much more common without individual game teams implementing every technique from scratch.",{},{"id":1019,"data":1609,"type":572,"tunes":1611},{"text":1610,"level":47},"Limitations",{},{"id":1024,"data":1613,"type":544,"tunes":1615},{"text":1614},"This article explains Microsoft's documented DirectX architecture and preview APIs. It does not claim that DX Linear Algebra currently improves performance in every game or that the Compute Graph Compiler is a finished retail product.",{},{"id":1029,"data":1617,"type":544,"tunes":1619},{"text":1618},"Microsoft's examples describe capability and intended use. Real benefits depend on the model, engine integration, GPU architecture, drivers and workload.",{},{"id":1034,"data":1621,"type":572,"tunes":1623},{"text":1622,"level":47},"Conclusion",{},{"id":1039,"data":1625,"type":544,"tunes":1627},{"text":1626},"The important DirectX change is not another checkbox called AI.",{},{"id":1044,"data":1629,"type":544,"tunes":1631},{"text":1630},"It is that machine-learning math is moving into the graphics programming model itself. Small neural functions can sit inside shaders, larger models can move toward graph-level compilation, and the same DirectX toolchain can expose those workloads across multiple GPU vendors.",{},{"id":1049,"data":1633,"type":544,"tunes":1635},{"text":1634},"That is how neural rendering stops being one branded feature and starts becoming part of the rendering infrastructure.",{},{"id":1054,"data":1637,"type":572,"tunes":1638},{"text":1056,"level":47},{},{"id":1059,"data":1640,"type":1059,"tunes":1661},{"items":1641,"title":1660},[1642,1645,1648,1651,1654,1657],{"id":1063,"answer":1643,"question":1644},"It is a DirectX\u002FHLSL feature set for hardware-accelerated vector and matrix operations used by machine learning, neural rendering and image-processing workloads.","What is DirectX Linear Algebra?",{"id":1067,"answer":1646,"question":1647},"A useful plain-English description is a shader that includes a learned neural function or ML inference step as part of its graphics work.","What is a neural shader?",{"id":1071,"answer":1649,"question":1650},"As of September 2026 it remains in the Shader Model 6.10 \u002F Agility SDK preview path.","Is DX Linear Algebra already a normal retail DirectX feature?",{"id":1075,"answer":1652,"question":1653},"It is Microsoft's announced model-level ML compiler API intended to take larger computation graphs and lower them into optimized GPU workloads integrated with D3D12.","What is the DirectX Compute Graph Compiler?",{"id":1079,"answer":1655,"question":1656},"Small functions fit shader-level authoring well, while large models benefit from whole-graph optimization, memory planning and operator fusion.","Why not run every ML model directly in HLSL?",{"id":1083,"answer":1658,"question":1659},"Not directly. DirectX provides lower-level infrastructure that vendors and developers can use for neural graphics. Branded technologies can still implement their own models and integration strategies.","Will this replace DLSS or FSR?","DirectX Linear Algebra and neural shaders",{},{"id":1089,"data":1663,"type":572,"tunes":1665},{"text":1664,"level":47},"Glossary",{},{"id":1094,"data":1667,"type":1094,"tunes":1687},{"title":1668,"entries":1669},"Key DirectX ML terms",[1670,1673,1675,1677,1679,1682,1685],{"term":1671,"anchor":1100,"definition":1672},"DX Linear Algebra","DirectX\u002FHLSL APIs for accelerated vector and matrix operations intended for neural rendering, ML and image-processing workloads.",{"term":1103,"anchor":1104,"definition":1674},"An earlier DirectX approach for accelerated vector-matrix operations inside shaders that helped establish the shader-level neural-rendering path.",{"term":1107,"anchor":1108,"definition":1676},"The preview shader-model generation containing the current DirectX Linear Algebra matrix APIs.",{"term":1111,"anchor":1112,"definition":1678},"Microsoft's announced compiler API for optimizing and executing larger ML computation graphs as native DirectX GPU workloads.",{"term":1680,"anchor":1116,"definition":1681},"Neural shader","A practical term for a shader that performs learned inference or neural computation as part of graphics processing.",{"term":1683,"anchor":1120,"definition":1684},"Shader-or-Graph Boundary","A Figure Rocks model for deciding whether an ML workload belongs as small inline shader math or as a larger model-level computation graph.",{"term":1123,"anchor":1124,"definition":1686},"A Figure Rocks workflow for deciding whether the traditional compute or memory cost avoided by a neural technique is worth its inference cost and quality trade-offs.",{},{"id":1128,"data":1689,"type":572,"tunes":1691},{"text":1690,"level":47},"Primary sources",{},{"id":1133,"data":1693,"type":1140,"tunes":1698},{"link":1135,"meta":1694},{"image":1695,"title":1696,"description":1697},{"url":13},"Microsoft DirectX — Evolving DirectX for the ML Era on Windows","Official GDC 2026 architecture overview covering shader-level ML, DX Linear Algebra and the DirectX Compute Graph Compiler.",{},{"id":1143,"data":1700,"type":1140,"tunes":1704},{"link":1145,"meta":1701},{"image":1702,"title":1148,"description":1703},{"url":13},"Official April 2026 preview explaining the unified Linear Algebra APIs, matrix operations and neural-rendering motivation.",{},{"id":1152,"data":1706,"type":1140,"tunes":1710},{"link":1154,"meta":1707},{"image":1708,"title":1157,"description":1709},{"url":13},"Official May 2026 release documenting Shader Model 6.10 Linear Algebra updates and preview hardware support.",{},{"id":1161,"data":1712,"type":1140,"tunes":1717},{"link":1163,"meta":1713},{"image":1714,"title":1715,"description":1716},{"url":13},"Microsoft Game Dev — GDC 2026: Evolving DirectX for the ML Era","Official Microsoft Game Dev summary explaining shader-level and model-level ML and the role of the Compute Graph Compiler.",{},{"id":1170,"data":1719,"type":1140,"tunes":1723},{"link":1172,"meta":1720},{"image":1721,"title":1175,"description":1722},{"url":13},"Official background on hardware-accelerated vector\u002Fmatrix operations and neural rendering directly from shader threads.",{},"2.31.6","DirectX is moving beyond traditional graphics shaders. Microsoft is adding hardware-accelerated linear algebra directly to HLSL and a separate path for larger ML models, laying the foundation for neural textures, learned materials, neural lighting and other AI-driven rendering techniques.",{"lang":7,"title":534,"content":536,"contentJson":1727,"excerpt":1179},{"time":538,"blocks":1728,"version":1178},[1729,1732,1735,1738,1741,1744,1747,1750,1753,1756,1764,1767,1770,1773,1776,1779,1792,1795,1798,1801,1804,1807,1810,1820,1823,1826,1829,1832,1835,1838,1841,1844,1847,1850,1867,1870,1873,1876,1879,1882,1885,1888,1891,1894,1897,1900,1903,1906,1909,1912,1921,1924,1927,1930,1933,1936,1939,1942,1945,1948,1958,1961,1964,1967,1970,1973,1976,1979,1982,1985,1988,1991,1994,1997,2000,2003,2006,2016,2019,2030,2033,2038,2043,2048,2053],{"id":541,"data":1730,"type":544,"tunes":1731},{"text":543},{},{"id":547,"data":1733,"type":552,"tunes":1734},{"body":549,"title":550,"variant":551},{},{"id":555,"data":1736,"type":552,"tunes":1737},{"body":557,"title":558,"variant":559},{},{"id":562,"data":1739,"type":566,"tunes":1740},{"title":564,"maxLevel":565,"minLevel":47},{},{"id":569,"data":1742,"type":572,"tunes":1743},{"text":571,"level":47},{},{"id":575,"data":1745,"type":544,"tunes":1746},{"text":577},{},{"id":580,"data":1748,"type":544,"tunes":1749},{"text":582},{},{"id":585,"data":1751,"type":544,"tunes":1752},{"text":587},{},{"id":590,"data":1754,"type":572,"tunes":1755},{"text":592,"level":47},{},{"id":595,"data":1757,"type":612,"tunes":1763},{"steps":1758,"title":610,"orientation":611},[1759,1760,1761,1762],{"label":599,"description":600},{"label":602,"description":603},{"label":605,"description":606},{"label":608,"description":609},{},{"id":615,"data":1765,"type":552,"tunes":1766},{"body":617,"title":618,"variant":619},{},{"id":622,"data":1768,"type":572,"tunes":1769},{"text":624,"level":47},{},{"id":627,"data":1771,"type":544,"tunes":1772},{"text":629},{},{"id":632,"data":1774,"type":544,"tunes":1775},{"text":634},{},{"id":637,"data":1777,"type":544,"tunes":1778},{"text":639},{},{"id":642,"data":1780,"type":666,"tunes":1791},{"rows":1781,"title":657,"layout":658,"columns":1788},[1782,1784,1786],{"id":646,"label":647,"values":1783},[13,13],{"id":650,"label":651,"values":1785},[13,13],{"id":654,"label":655,"values":1787},[13,13],[1789,1790],{"id":661,"label":662},{"id":664,"label":665},{},{"id":669,"data":1793,"type":572,"tunes":1794},{"text":671,"level":47},{},{"id":674,"data":1796,"type":544,"tunes":1797},{"text":676},{},{"id":679,"data":1799,"type":544,"tunes":1800},{"text":681},{},{"id":684,"data":1802,"type":544,"tunes":1803},{"text":686},{},{"id":689,"data":1805,"type":572,"tunes":1806},{"text":691,"level":47},{},{"id":694,"data":1808,"type":544,"tunes":1809},{"text":696},{},{"id":699,"data":1811,"type":658,"tunes":1819},{"content":1812,"stretched":720,"withHeadings":15},[1813,1814,1815,1816,1817,1818],[703,704],[706,707],[709,710],[712,713],[715,716],[718,719],{},{"id":723,"data":1821,"type":572,"tunes":1822},{"text":725,"level":47},{},{"id":728,"data":1824,"type":544,"tunes":1825},{"text":730},{},{"id":733,"data":1827,"type":544,"tunes":1828},{"text":735},{},{"id":738,"data":1830,"type":544,"tunes":1831},{"text":740},{},{"id":743,"data":1833,"type":749,"tunes":1834},{"url":745,"title":746,"excerpt":747,"ctaLabel":748},{},{"id":752,"data":1836,"type":572,"tunes":1837},{"text":754,"level":47},{},{"id":757,"data":1839,"type":544,"tunes":1840},{"text":759},{},{"id":762,"data":1842,"type":544,"tunes":1843},{"text":764},{},{"id":767,"data":1845,"type":544,"tunes":1846},{"text":769},{},{"id":772,"data":1848,"type":572,"tunes":1849},{"text":774,"level":47},{},{"id":777,"data":1851,"type":666,"tunes":1866},{"rows":1852,"title":800,"layout":658,"columns":1863},[1853,1855,1857,1859,1861],{"id":781,"label":782,"values":1854},[13,13],{"id":785,"label":786,"values":1856},[13,13],{"id":789,"label":790,"values":1858},[13,13],{"id":793,"label":794,"values":1860},[13,13],{"id":797,"label":798,"values":1862},[13,13],[1864,1865],{"id":803,"label":804},{"id":806,"label":807},{},{"id":810,"data":1868,"type":572,"tunes":1869},{"text":812,"level":47},{},{"id":815,"data":1871,"type":544,"tunes":1872},{"text":817},{},{"id":820,"data":1874,"type":544,"tunes":1875},{"text":822},{},{"id":825,"data":1877,"type":544,"tunes":1878},{"text":827},{},{"id":830,"data":1880,"type":552,"tunes":1881},{"body":832,"title":833,"variant":559},{},{"id":836,"data":1883,"type":572,"tunes":1884},{"text":838,"level":47},{},{"id":841,"data":1886,"type":544,"tunes":1887},{"text":843},{},{"id":846,"data":1889,"type":544,"tunes":1890},{"text":848},{},{"id":851,"data":1892,"type":544,"tunes":1893},{"text":853},{},{"id":856,"data":1895,"type":572,"tunes":1896},{"text":858,"level":47},{},{"id":861,"data":1898,"type":544,"tunes":1899},{"text":863},{},{"id":866,"data":1901,"type":544,"tunes":1902},{"text":868},{},{"id":871,"data":1904,"type":544,"tunes":1905},{"text":873},{},{"id":876,"data":1907,"type":749,"tunes":1908},{"url":878,"title":879,"excerpt":880,"ctaLabel":881},{},{"id":884,"data":1910,"type":572,"tunes":1911},{"text":886,"level":47},{},{"id":889,"data":1913,"type":612,"tunes":1920},{"steps":1914,"title":907,"orientation":611},[1915,1916,1917,1918,1919],{"label":893,"description":894},{"label":896,"description":897},{"label":899,"description":900},{"label":902,"description":903},{"label":905,"description":906},{},{"id":910,"data":1922,"type":572,"tunes":1923},{"text":912,"level":47},{},{"id":915,"data":1925,"type":544,"tunes":1926},{"text":917},{},{"id":920,"data":1928,"type":544,"tunes":1929},{"text":922},{},{"id":925,"data":1931,"type":544,"tunes":1932},{"text":927},{},{"id":930,"data":1934,"type":572,"tunes":1935},{"text":932,"level":47},{},{"id":935,"data":1937,"type":544,"tunes":1938},{"text":937},{},{"id":940,"data":1940,"type":544,"tunes":1941},{"text":942},{},{"id":945,"data":1943,"type":544,"tunes":1944},{"text":947},{},{"id":950,"data":1946,"type":572,"tunes":1947},{"text":952,"level":47},{},{"id":955,"data":1949,"type":612,"tunes":1957},{"steps":1950,"title":976,"orientation":611},[1951,1952,1953,1954,1955,1956],{"label":959,"description":960},{"label":962,"description":963},{"label":965,"description":966},{"label":968,"description":969},{"label":971,"description":972},{"label":974,"description":975},{},{"id":979,"data":1959,"type":572,"tunes":1960},{"text":981,"level":47},{},{"id":984,"data":1962,"type":544,"tunes":1963},{"text":986},{},{"id":989,"data":1965,"type":544,"tunes":1966},{"text":991},{},{"id":994,"data":1968,"type":544,"tunes":1969},{"text":996},{},{"id":999,"data":1971,"type":572,"tunes":1972},{"text":1001,"level":47},{},{"id":1004,"data":1974,"type":544,"tunes":1975},{"text":1006},{},{"id":1009,"data":1977,"type":544,"tunes":1978},{"text":1011},{},{"id":1014,"data":1980,"type":544,"tunes":1981},{"text":1016},{},{"id":1019,"data":1983,"type":572,"tunes":1984},{"text":1021,"level":47},{},{"id":1024,"data":1986,"type":544,"tunes":1987},{"text":1026},{},{"id":1029,"data":1989,"type":544,"tunes":1990},{"text":1031},{},{"id":1034,"data":1992,"type":572,"tunes":1993},{"text":1036,"level":47},{},{"id":1039,"data":1995,"type":544,"tunes":1996},{"text":1041},{},{"id":1044,"data":1998,"type":544,"tunes":1999},{"text":1046},{},{"id":1049,"data":2001,"type":544,"tunes":2002},{"text":1051},{},{"id":1054,"data":2004,"type":572,"tunes":2005},{"text":1056,"level":47},{},{"id":1059,"data":2007,"type":1059,"tunes":2015},{"items":2008,"title":1086},[2009,2010,2011,2012,2013,2014],{"id":1063,"answer":1064,"question":1065},{"id":1067,"answer":1068,"question":1069},{"id":1071,"answer":1072,"question":1073},{"id":1075,"answer":1076,"question":1077},{"id":1079,"answer":1080,"question":1081},{"id":1083,"answer":1084,"question":1085},{},{"id":1089,"data":2017,"type":572,"tunes":2018},{"text":1091,"level":47},{},{"id":1094,"data":2020,"type":1094,"tunes":2029},{"title":1096,"entries":2021},[2022,2023,2024,2025,2026,2027,2028],{"term":1099,"anchor":1100,"definition":1101},{"term":1103,"anchor":1104,"definition":1105},{"term":1107,"anchor":1108,"definition":1109},{"term":1111,"anchor":1112,"definition":1113},{"term":1115,"anchor":1116,"definition":1117},{"term":1119,"anchor":1120,"definition":1121},{"term":1123,"anchor":1124,"definition":1125},{},{"id":1128,"data":2031,"type":572,"tunes":2032},{"text":1130,"level":47},{},{"id":1133,"data":2034,"type":1140,"tunes":2037},{"link":1135,"meta":2035},{"image":2036,"title":1138,"description":1139},{"url":13},{},{"id":1143,"data":2039,"type":1140,"tunes":2042},{"link":1145,"meta":2040},{"image":2041,"title":1148,"description":1149},{"url":13},{},{"id":1152,"data":2044,"type":1140,"tunes":2047},{"link":1154,"meta":2045},{"image":2046,"title":1157,"description":1158},{"url":13},{},{"id":1161,"data":2049,"type":1140,"tunes":2052},{"link":1163,"meta":2050},{"image":2051,"title":1166,"description":1167},{"url":13},{},{"id":1170,"data":2054,"type":1140,"tunes":2057},{"link":1172,"meta":2055},{"image":2056,"title":1175,"description":1176},{"url":13},{},"Post erfolgreich abgerufen",{"items":2060,"source":2132,"manualIds":2133,"manualMatchedIds":2134},[2061,2067,2073,2079,2085,2091,2097,2103,2109,2114,2120,2126],{"id":2062,"slug":2063,"title":2064,"excerpt":2065,"featuredImage":14,"publishedAt":2066},"419","celeste","Celeste","Das Celeste-amiibo gehört zur Animal Crossing-amiibo-Figurenreihe, die während der ersten Welle von Figuren veröffentlicht wurde, die dem Animal Crossing-Universum gewidmet sind. Wie andere Figuren in dieser Kollektion fungiert es als kleiner NFC-Träger, der mit Nintendos amiibo-Ökosystem verbunden ist. Beim Scannen verknüpft die Figur den Charakter Celeste mit kompatiblen Spielen. Der Wert des amiibo liegt hauptsächlich darin, Charakterauftritte und kleine Gameplay-Interaktionen zu ermöglichen, die ansonsten nur unter bestimmten Umständen auftreten.","2026-03-06T14:42:00.000Z",{"id":2068,"slug":2069,"title":2070,"excerpt":2071,"featuredImage":14,"publishedAt":2072},"415","reese","Reese","Das Reese-amiibo gehört zur Animal Crossing-Serie von Nintendo-amiibo-Figuren und repräsentiert einen der Ladenbesitzer der Stadtökonomie in den Animal Crossing-Spielen. Wie bei anderen Figuren dieser Reihe liegt der Wert weniger im Kunststoffobjekt selbst als vielmehr im NFC-Chip im Inneren des Sockels. Beim Scannen mit kompatiblen Nintendo-Systemen löst die Figur kleine Interaktionen im Spiel aus, schaltet Charakterauftritte frei oder ermöglicht je nach Titel zusätzliche Dialoge und Gegenstände.","2026-03-06T09:00:00.000Z",{"id":2074,"slug":2075,"title":2076,"excerpt":2077,"featuredImage":14,"publishedAt":2078},"241","overdrive-tuning-the-clean-way-to-reduce-blur-without-ghosting","Overdrive-Tuning: Der saubere Weg, Unschärfe ohne Ghosting zu reduzieren","Overdrive kann die Klarheit verbessern oder hässliche Halos erzeugen. Nutzen Sie diese einfache Methode, um die saubere mittlere Einstellung zu wählen, die Unschärfe ohne Ghosting-Artefakte reduziert.","2026-02-21T03:30:00.000Z",{"id":2080,"slug":2081,"title":2082,"excerpt":2083,"featuredImage":14,"publishedAt":2084},"418","blathers","Blathers","Der Eugen-amiibo ist Teil der Animal Crossing-Figurenserie, die während der umfassenderen Markteinführung von Nintendos amiibo-Plattform veröffentlicht wurde. Jede Figur kombiniert eine kleine Sammlerfigur mit einem NFC-Chip im Sockel. Wenn sie auf ein kompatibles Lesegerät gestellt wird, liest die Konsole die in der Figur gespeicherte Charakter-ID aus. In der Praxis ermöglicht dies bestimmten Spielen, direkt auf den Charakter Bezug zu nehmen. Der Eugen-amiibo bietet hauptsächlich Zugriff auf Auftritte des Museumskurators oder kleine charakterbezogene Funktionen in unterstützten Animal Crossing-Titeln.","2026-03-06T13:06:00.000Z",{"id":2086,"slug":2087,"title":2088,"excerpt":2089,"featuredImage":14,"publishedAt":2090},"413","tom-nook","Tom Nook","Innerhalb der Animal Crossing amiibo-Figurenreihe stellt der Tom Nook amiibo eine der zentralen Figuren der Serie dar. Die Figur erschien während der ersten Welle spezieller Animal Crossing amiibo. Der Veröffentlichungszeitpunkt variierte je nach Region leicht, fällt aber im Großen und Ganzen in den November 2015. Die Figur trägt das Ebenbild von Tom Nook, einem Charakter, der seit den frühesten Animal Crossing-Titeln präsent ist und dessen Rolle sich langsam vom Ladenbesitzer zum Infrastruktur-Organisator des Dorflebens gewandelt hat. Der amiibo fungiert primär als Charakter-Schlüssel: Durch das Scannen wird Tom Nook in mehrere kompatible Nintendo-Spiele eingefügt, wodurch kleine Interaktionen, Charakter-Inhalte oder thematische Boni freigeschaltet werden.","2026-03-05T13:20:00.000Z",{"id":2092,"slug":2093,"title":2094,"excerpt":2095,"featuredImage":14,"publishedAt":2096},"423","kapp-n","Kapp’n","Der Käpten-amiibo gehört zur Animal Crossing-amiibo-Figurenserie, die während der ersten Welle von Figuren im Zusammenhang mit der Serie veröffentlicht wurde. Wie andere Figuren dieser Serie enthält er einen kleinen NFC-Chip, der das physische Objekt mit verschiedenen Nintendo-Spielen verknüpft. Das Scannen der Figur aktiviert charakterbezogene Inhalte. Der praktische Nutzen der Figur liegt hauptsächlich in der Möglichkeit, Käpten in unterstützte Titel zu rufen und kleine thematische Inhalte freizuschalten, die mit seiner Rolle in der Serie verbunden sind.","2026-03-06T15:42:00.000Z",{"id":2098,"slug":2099,"title":2100,"excerpt":2101,"featuredImage":14,"publishedAt":2102},"420","resetti","Resetti","Die Resetti-amiibo gehört zur Animal Crossing-amiibo-Figurenreihe, die während der frühen Expansion von Nintendos NFC-basierten Charakterfiguren veröffentlicht wurde. Wie andere in dieser Serie fungiert die Figur als physische Darstellung eines Charakters, kombiniert mit einem kleinen NFC-Chip, der mit kompatiblen Nintendo-Systemen kommuniziert. Wenn sie gescannt wird, verknüpft die Figur den Charakter Mr. Resetti mit unterstützten Spielen und schaltet kleine Interaktionen oder Charakterauftritte frei, die mit seiner Rolle im Animal Crossing-Universum verbunden sind.","2026-03-06T13:59:00.000Z",{"id":2104,"slug":2105,"title":2106,"excerpt":2107,"featuredImage":14,"publishedAt":2108},"127","motion-clarity-why-blur-happens-and-the-fixes-that-actually-work","Bewegungsschärfe: Warum Unschärfe entsteht und die Lösungen, die wirklich funktionieren","Bewegungsunschärfe ist nicht nur eine Einstellung — sie ist Timing plus Persistenz. Lerne die praktische Reihenfolge: richtiger Modus, richtige Bildwiederholrate, dann die wenigen Klarheits-Fixes, auf die es ankommt.","2026-02-20T11:00:00.000Z",{"id":2110,"slug":2111,"title":2111,"excerpt":2112,"featuredImage":14,"publishedAt":2113},"417","Lottie","Die Lottie-amiibo gehört zur Animal Crossing amiibo-Figurenreihe, die in der frühen Phase von Nintendos amiibo-Programm veröffentlicht wurde. Sie stellt den kleinen Otter-Charakter dar, der aus dem Designbüro in Animal Crossing: Happy Home Designer bekannt ist. Wie andere Figuren dieser Serie enthält das Objekt einen kleinen NFC-Chip. Wenn sie von kompatiblen Nintendo-Systemen gescannt wird, verknüpft die Figur den Charakter mit spielinternen Systemen und schaltet kleine Teile zugehöriger Inhalte frei.","2026-03-06T12:48:00.000Z",{"id":2115,"slug":2116,"title":2117,"excerpt":2118,"featuredImage":14,"publishedAt":2119},"421","kicks","Kicks","Das Schubert-amiibo gehört zur Animal Crossing amiibo-Figurenserie, die während des frühen Ausbaus von Nintendos NFC-Figuren-Ökosystem veröffentlicht wurde. Wie die anderen Charaktere in dieser Serie fungiert die Figur als physischer Schlüssel, der sich über NFC mit kompatiblen Nintendo-Spielen verbindet. Beim Scannen verknüpft das amiibo den Charakter Schubert mit verschiedenen In-Game-Systemen. Der praktische Nutzen ist einfach: Er ermöglicht Spielern den Zugriff auf charakterspezifische Interaktionen, kleine Freischaltungen oder thematische Inhalte, abhängig vom unterstützten Titel.","2026-03-06T15:31:00.000Z",{"id":2121,"slug":2122,"title":2123,"excerpt":2124,"featuredImage":14,"publishedAt":2125},"416","cyrus","Cyrus","Der Cyrus-amiibo gehört zur Animal Crossing amiibo-Figurenreihe, die in dem Zeitraum veröffentlicht wurde, als Nintendo die Serie um physische NFC-Figuren erweiterte. Er fungiert als Brücke zwischen der Kunststofffigur und unterstützten Nintendo-Spielen. Wenn er gescannt wird, wird der im NFC-Chip gespeicherte Charakter im Spiel zugänglich. Der praktische Wert der Figur liegt darin, Interaktionen und Inhalte mit Bezug zu Cyrus zu ermöglichen, die ansonsten verborgen oder schwerer zu erreichen bleiben.","2026-03-06T08:32:00.000Z",{"id":2127,"slug":2128,"title":2129,"excerpt":2130,"featuredImage":14,"publishedAt":2131},"207","120hz-feels-worse-the-diagnosis-checklist-wrong-mode-vrr-range-caps","120Hz fühlen sich schlechter an? Diagnose-Checkliste (Falscher Modus, VRR-Bereich, Caps)","Eine höhere Bildwiederholrate kann Instabilitäten aufdecken. Nutze diese Checkliste, um zu diagnostizieren, warum sich 120 Hz schlechter anfühlen: falscher Modus, falscher Bildwiederholpfad, VRR-Bereichsprobleme oder fehlende Caps.","2026-02-20T20:30:00.000Z","fallback",[],[]]