{"id":1179,"date":"2026-08-26T19:04:26","date_gmt":"2026-08-26T16:04:26","guid":{"rendered":"https:\/\/www.tayfnews.tech\/tr\/?p=1179"},"modified":"2026-08-26T19:04:26","modified_gmt":"2026-08-26T16:04:26","slug":"vllm-sunum-motoruna-google-cloud-tpu-destegi-entegre-edildi","status":"publish","type":"post","link":"https:\/\/www.tayfnews.tech\/tr\/technology\/vllm-sunum-motoruna-google-cloud-tpu-destegi-entegre-edildi\/","title":{"rendered":"vLLM Sunum Motoruna Google Cloud TPU Deste\u011fi Entegre Edildi"},"content":{"rendered":"<p>Google Cloud, kurumsal geli\u015ftiricilerin Google Kubernetes Engine (GKE) kullanarak y\u00fcksek talepli g\u00f6mme hatlar\u0131n\u0131 (embedding pipelines) esnek bir \u015fekilde \u00f6l\u00e7eklendirmesini sa\u011flamak i\u00e7in tasarlanan stratejik bir mimari g\u00fcncelleme ile <strong>vLLM<\/strong> sunum motoruna resmen yerle\u015fik Tensor \u0130\u015flem Birimi (TPU) deste\u011fi getirdi. Bu entegrasyon, \u00f6zellikle kurumsal sistemlerin tek bir \u00e7\u0131kar\u0131m ge\u00e7i\u015fi i\u00e7inde devasa veri hacimlerini ve uzun s\u00fcreli token ufuklar\u0131n\u0131 i\u015flemeye y\u00f6neldi\u011fi bir d\u00f6nemde, modern yapay zeka da\u011f\u0131t\u0131mlar\u0131ndaki kritik altyap\u0131 darbo\u011fazlar\u0131n\u0131 ortadan kald\u0131r\u0131yor.<\/p>\n<h2>Bulut TPU&#8217;lar\u0131nda Uzun \u0130\u00e7erik Zorluklar\u0131n\u0131n \u00dcstesinden Gelmek<\/h2>\n<p>Geli\u015fmi\u015f dil ve \u00e7ok mod\u00fcll\u00fc modeller giderek daha sofistike hale geldik\u00e7e, <strong>Qwen3-Embedding-8B<\/strong> gibi mimarilerin gerektirdi\u011fi %15.000&#8217;den fazla token s\u0131n\u0131r\u0131 gibi kapsaml\u0131 ba\u011flamlar\u0131 i\u015fleme end\u00fcstri talebi f\u0131rlad\u0131. Bu \u00f6l\u00e7ekteki dizileri y\u00f6netmek, tipik olarak i\u015f y\u00fckleri geleneksel GPU mimarilerinden uzakla\u015ft\u0131r\u0131ld\u0131\u011f\u0131nda ciddi bellek par\u00e7alanmas\u0131na, gecikme cezalar\u0131na ve say\u0131sal karars\u0131zl\u0131\u011fa neden olur.<\/p>\n<p>Bu engelleri hafifletmek i\u00e7in Google&#8217;\u0131n m\u00fchendislik ekibi, do\u011frudan Cloud TPU&#8217;lar\u0131n mimarisine uyarlanm\u0131\u015f donan\u0131ma \u00f6zel bir dizi optimizasyon uygulad\u0131:<\/p>\n<ul>\n<li><strong>Donan\u0131ma uygun tens\u00f6r hizalama:<\/strong> Bellek i\u015flemlerinin TPU matris \u00e7arp\u0131m k\u0131s\u0131tlamalar\u0131na kesinlikle uymas\u0131n\u0131 sa\u011flayarak sessiz bilgi i\u015flem durmalar\u0131n\u0131 \u00f6nler.<\/li>\n<li><strong>JAX\/XLA derleme \u00f6n \u0131s\u0131tmas\u0131:<\/strong> Canl\u0131 \u00e7\u0131kar\u0131m isteklerinden \u00f6nce y\u00fcr\u00fctme grafiklerini haz\u0131rlayarak \u00e7al\u0131\u015fma zaman\u0131 derleme gecikme s\u0131\u00e7ramalar\u0131n\u0131 ortadan kald\u0131r\u0131r.<\/li>\n<li><strong>Hibrit StepPool mimarisi:<\/strong> Yo\u011fun bellek y\u00fckleri s\u0131ras\u0131nda veri ak\u0131\u015f\u0131n\u0131 optimize etmek i\u00e7in par\u00e7al\u0131 \u00f6n dolgu y\u00f6netimini dinamik olarak koordine eder.<\/li>\n<\/ul>\n<p>Google Cloud, bu hedefli geli\u015ftirmeler sayesinde geleneksel referans GPU taban \u00e7izgileriyle kar\u015f\u0131la\u015ft\u0131r\u0131ld\u0131\u011f\u0131nda neredeyse kusursuz say\u0131sal e\u015fde\u011ferlik elde etmeyi ba\u015fard\u0131. Bu teknik uyum, \u00f6zel h\u0131zland\u0131r\u0131c\u0131 donan\u0131ma ge\u00e7i\u015fin, hassas bilgi retrieval-augmented generation (RAG) ortamlar\u0131nda do\u011fruluk sapmas\u0131na veya \u00e7\u0131kt\u0131 bozulmas\u0131na neden olmamas\u0131n\u0131 sa\u011flar.<\/p>\n<h2>An\u0131nda Eri\u015filebilirlik ve Geli\u015ftirici Kaynaklar\u0131<\/h2>\n<p>Bu yetenekleri operasyonel hale getirmek isteyen kurulu\u015flar, yeni yap\u0131land\u0131rmalara an\u0131nda eri\u015febilir ve bunlar\u0131 da\u011f\u0131tabilir. Google, eksiksiz kurulum tariflerini <strong>AI-Hypercomputer GitHub deposu<\/strong> arac\u0131l\u0131\u011f\u0131yla a\u00e7\u0131k kaynakl\u0131 hale getirdi. Bu varl\u0131klar, m\u00fchendislere esnek GKE k\u00fcmeleri aras\u0131nda sorunsuz bir \u015fekilde \u00f6l\u00e7eklendirme yapabilen y\u00fcksek verimli anlamsal alma uygulamalar\u0131 olu\u015fturmak i\u00e7in gereken temel ara\u00e7lar\u0131 sa\u011flar.<\/p>\n<p><em>Kaynak: <a href=\"https:\/\/developers.googleblog.com\/enterprise-grade-precision-for-long-context-multimodal-embedding-inference-on-cloud-tpu\/\" target=\"_blank\" rel=\"noopener noreferrer\">Orijinal Makale<\/a><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Google Cloud, vLLM sunum motoruna yerle\u015fik TPU deste\u011fi entegre ederek b\u00fcy\u00fck \u00f6l\u00e7ekli uzun i\u00e7erikli g\u00f6pi hatlar\u0131 i\u00e7in esnek \u00f6l\u00e7eklendirme sa\u011fl\u0131yor.<\/p>\n","protected":false},"author":1,"featured_media":1178,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"googlesitekit_rrm_CAowrrDMDA:productID":"","tayfnews_source_url":"","footnotes":"","rank_math_focus_keyword":"TPU Deste\u011fi, Google Cloud, vLLM sunum motoru, Donan\u0131m, Bulut Bili\u015fim, Teknoloji","rank_math_title":"vLLM Sunum Motoruna Google Cloud TPU Deste\u011fi Entegre Edildi","rank_math_description":"Google Cloud, vLLM sunum motoruna yerle\u015fik TPU deste\u011fi entegre ederek b\u00fcy\u00fck \u00f6l\u00e7ekli uzun i\u00e7erikli g\u00f6pi hatlar\u0131 i\u00e7in esnek \u00f6l\u00e7eklendirme sa\u011fl\u0131yor."},"categories":[2],"tags":[],"class_list":["post-1179","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology"],"_links":{"self":[{"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/posts\/1179","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/comments?post=1179"}],"version-history":[{"count":1,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/posts\/1179\/revisions"}],"predecessor-version":[{"id":1180,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/posts\/1179\/revisions\/1180"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/media\/1178"}],"wp:attachment":[{"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/media?parent=1179"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/categories?post=1179"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tayfnews.tech\/tr\/wp-json\/wp\/v2\/tags?post=1179"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}