{"id":31358,"date":"2019-10-31T21:40:51","date_gmt":"2019-10-31T18:40:51","guid":{"rendered":"https:\/\/prohoster.info\/blog\/tenzornye-i-rt-yadra-zanimayut-ne-tak-mnogo-mesta-na-graficheskih-protsessorah-nvidia-turing\/"},"modified":"2019-10-31T21:40:51","modified_gmt":"2019-10-31T18:40:51","slug":"tenzornye-i-rt-yadra-zanimayut-ne-tak-mnogo-mesta-na-graficheskih-protsessorah-nvidia-turing","status":"publish","type":"post","link":"https:\/\/prohoster.info\/nl\/blog\/news\/tenzornye-i-rt-yadra-zanimayut-ne-tak-mnogo-mesta-na-graficheskih-protsessorah-nvidia-turing","title":{"rendered":"Tensor- en RT-kernen nemen niet veel ruimte in op NVIDIA Turing grafische processors.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Al tijdens de aankondiging van de eerste grafische kaarten van de GeForce RTX 20-serie dachten velen dat de Turing grafische processors met hun behoorlijk grote afmetingen te maken hadden met extra blokken: RT-kernen en tensor kernen. Nu heeft een gebruiker op Reddit infraroodopnames van de Turing TU106 en TU116 processors geanalyseerd en geconcludeerd dat de nieuwe rekeneenheden niet zoveel ruimte innemen als aanvankelijk gedacht.<\/p>\n

\"Tensor-<\/p>\n

Laten we beginnen met te herinneren dat de Turing TU106 grafische processor de kleinste en meest compacte chip van NVIDIA is, met speciale RT-kernen voor ray tracing en tensor kernen voor de versnelling van artifici\u00eble intelligentie functies. Op zijn beurt mist de verwante Turing TU116 deze speciale rekeneenheden en daarom is ervoor gekozen om juist deze twee te vergelijken.<\/p>\n

\"Tensor-
\n\"Tensor-<\/p>\n

De NVIDIA Turing grafische processors zijn verdeeld in TPC-blokken, die elk een paar streaming multiprocessors bevatten, waarin alle rekenkernen zijn ondergebracht. Ook blijkt dat het Turing TU106 grafische processorblok slechts 1,95 mm\u00b2 groter is dan dat van de Turing TU116, wat neerkomt op 22%. Van deze oppervlakte komt 1,25 mm\u00b2 voor rekening van de tensor kernen, en slechts 0,7 mm\u00b2 van de RT-kernen.<\/p>\n

\"Tensor-
\n\"Tensor-<\/p>\n

Dit betekent dat zonder de nieuwe tensor- en RT-kernen de vlaggenschip Turing TU102 grafische processor, die aan de basis staat van de GeForce RTX 2080 Ti, niet 754 mm\u00b2 zou bedragen, maar 684 mm\u00b2 (36 TPC). Aan de andere kant zou de Turing TU104, die de basis vormt van de GeForce RTX 2080, 498 mm\u00b2 in plaats van 545 mm\u00b2 (24 TPC) kunnen innemen. Zoals te zien is, zouden de oudere Turing grafische processors, zelfs zonder de tensor- en RT-kernen, nog steeds vrij grote chips zijn. Beduidend groter dan de Pascal grafische processors.<\/p>\n

<\/center>
\n \"Tensor- <\/p>\n

Wat verklaart dan deze aanzienlijke afmetingen? Ten eerste is het cache-geheugen van de Turing grafische processors vergroot. Daarnaast is de omvang van de shaders vergroot, en bevatten de Turing chips grotere instructiesets en vergrote registers. Dit alles heeft niet alleen geleid tot een aanzienlijke verhoging van het oppervlak, maar ook van de prestaties van de Turing grafische processors. Bijvoorbeeld, de GeForce RTX 2060 op basis van TU106 levert bijna hetzelfde prestatieniveau als de GeForce GTX 1080 op basis van GP104. Laatstgenoemde heeft trouwens 25% meer CUDA-kernen, hoewel het een oppervlakte van 314 mm\u00b2 in vergelijking met de 410 mm\u00b2 van de nieuwe TU106 beslaat. <\/p>\n

<\/p>\n

<\/center><\/p>\n

\t\t\t\t


\n\t\t\t\t\t\t\t\t<\/center>
\n
Bron: 3dnews.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\u0415\u0449\u0451 \u0432\u043e \u0432\u0440\u0435\u043c\u044f \u0430\u043d\u043e\u043d\u0441\u0430 \u043f\u0435\u0440\u0432\u044b\u0445 \u0432\u0438\u0434\u0435\u043e\u043a\u0430\u0440\u0442 GeForce RTX 20-\u0439 \u0441\u0435\u0440\u0438\u0438 \u043c\u043d\u043e\u0433\u0438\u0435 \u043f\u043e\u0441\u0447\u0438\u0442\u0430\u043b\u0438, \u0447\u0442\u043e \u0441\u0432\u043e\u0438\u043c\u0438 \u0441\u043e\u0432\u0441\u0435\u043c \u043d\u0435 \u043c\u0430\u043b\u0435\u043d\u044c\u043a\u0438\u043c \u0433\u0430\u0431\u0430\u0440\u0438\u0442\u0430\u043c\u0438 \u0433\u0440\u0430\u0444\u0438\u0447\u0435\u0441\u043a\u0438\u0435 \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u043e\u0440\u044b Turing \u043e\u0431\u044f\u0437\u0430\u043d\u044b \u043d\u0430\u043b\u0438\u0447\u0438\u044e \u0434\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0445 \u0431\u043b\u043e\u043a\u043e\u0432: RT-\u044f\u0434\u0435\u0440 \u0438 \u0442\u0435\u043d\u0437\u043e\u0440\u043d\u044b\u0445 \u044f\u0434\u0435\u0440. \u0422\u0435\u043f\u0435\u0440\u044c \u0436\u0435 \u043e\u0434\u0438\u043d \u0438\u0437 \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u0435\u0439 Reddit \u043f\u0440\u043e\u0430\u043d\u0430\u043b\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u043b \u0438\u043d\u0444\u0440\u0430\u043a\u0440\u0430\u0441\u043d\u044b\u0435 \u0441\u043d\u0438\u043c\u043a\u0438 \u0433\u0440\u0430\u0444\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u043e\u0440\u043e\u0432 Turing TU106 \u0438 TU116 \u0438 \u0437\u0430\u043a\u043b\u044e\u0447\u0438\u043b, \u0447\u0442\u043e \u043d\u043e\u0432\u044b\u0435 \u0432\u044b\u0447\u0438\u0441\u043b\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0435 \u0431\u043b\u043e\u043a\u0438 \u0437\u0430\u043d\u0438\u043c\u0430\u044e\u0442 \u043d\u0435 \u0442\u0430\u043a \u043c\u043d\u043e\u0433\u043e \u043c\u0435\u0441\u0442\u0430, […]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":23324,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-31358","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\n","aioseo_head_json":{"title":"\ud83e\udd47Tensor- en RT-kernen nemen niet veel ruimte in op de NVIDIA Turing grafische processors | ProHoster","description":"Tijdens de aankondiging van de eerste GeForce RTX 20-serie videokaarten, dachten velen dat de behoorlijk grote afmetingen van de Turing-grafische processors te danken waren aan de extra blokken: RT-kernen en tensor-kernen.","canonical_url":"https:\/\/prohoster.info\/nl\/blog\/news\/tenzornye-i-rt-yadra-zanimayut-ne-tak-mnogo-mesta-na-graficheskih-protsessorah-nvidia-turing","robots":"max-image-preview:large","keywords":"","webmasterTools":{"miscellaneous":""},"schema":null,"og:locale":"nl_NL","og:site_name":"ProHoster | \u041a\u0443\u043f\u0438\u0442\u044c \u043d\u0430\u0434\u0435\u0436\u043d\u044b\u0439 \u0445\u043e\u0441\u0442\u0438\u043d\u0433 \u0434\u043b\u044f \u0441\u0430\u0439\u0442\u043e\u0432 \u0441 \u0437\u0430\u0449\u0438\u0442\u043e\u0439 \u043e\u0442 DDoS, VPS VDS \u0441\u0435\u0440\u0432\u0435\u0440\u044b","og:type":"article","og:title":"\ud83e\udd47\u0422\u0435\u043d\u0437\u043e\u0440\u043d\u044b\u0435 \u0438 RT-\u044f\u0434\u0440\u0430 \u0437\u0430\u043d\u0438\u043c\u0430\u044e\u0442 \u043d\u0435 \u0442\u0430\u043a \u043c\u043d\u043e\u0433\u043e \u043c\u0435\u0441\u0442\u0430 \u043d\u0430 \u0433\u0440\u0430\u0444\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u043e\u0440\u0430\u0445 NVIDIA Turing | ProHoster","og:description":"\u0415\u0449\u0451 \u0432\u043e \u0432\u0440\u0435\u043c\u044f \u0430\u043d\u043e\u043d\u0441\u0430 \u043f\u0435\u0440\u0432\u044b\u0445 \u0432\u0438\u0434\u0435\u043e\u043a\u0430\u0440\u0442 GeForce RTX 20-\u0439 \u0441\u0435\u0440\u0438\u0438 \u043c\u043d\u043e\u0433\u0438\u0435 \u043f\u043e\u0441\u0447\u0438\u0442\u0430\u043b\u0438, \u0447\u0442\u043e \u0441\u0432\u043e\u0438\u043c\u0438 \u0441\u043e\u0432\u0441\u0435\u043c \u043d\u0435 \u043c\u0430\u043b\u0435\u043d\u044c\u043a\u0438\u043c \u0433\u0430\u0431\u0430\u0440\u0438\u0442\u0430\u043c\u0438 \u0433\u0440\u0430\u0444\u0438\u0447\u0435\u0441\u043a\u0438\u0435 \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u043e\u0440\u044b Turing \u043e\u0431\u044f\u0437\u0430\u043d\u044b \u043d\u0430\u043b\u0438\u0447\u0438\u044e \u0434\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0445 \u0431\u043b\u043e\u043a\u043e\u0432: RT-\u044f\u0434\u0435\u0440 \u0438 \u0442\u0435\u043d\u0437\u043e\u0440\u043d\u044b\u0445 \u044f\u0434\u0435\u0440.","og:url":"https:\/\/prohoster.info\/nl\/blog\/news\/tenzornye-i-rt-yadra-zanimayut-ne-tak-mnogo-mesta-na-graficheskih-protsessorah-nvidia-turing","og:image":"https:\/\/prohoster.info\/wp-content\/uploads\/2021\/11\/logo-350.jpg","og:image:secure_url":"https:\/\/prohoster.info\/wp-content\/uploads\/2021\/11\/logo-350.jpg","og:image:width":350,"og:image:height":350,"article:published_time":"2019-10-31T18:40:51+00:00","article:modified_time":"2019-10-31T18:40:51+00:00","article:publisher":"https:\/\/www.facebook.com\/prohoster","article:author":"https:\/\/www.facebook.com\/prohoster"},"aioseo_meta_data":{"post_id":"31358","title":null,"description":null,"keywords":null,"keyphrases":null,"primary_term":null,"canonical_url":null,"og_title":null,"og_description":null,"og_object_type":"default","og_image_type":"default","og_image_url":null,"og_image_width":null,"og_image_height":null,"og_image_custom_url":null,"og_image_custom_fields":null,"og_video":null,"og_custom_url":null,"og_article_section":null,"og_article_tags":null,"twitter_use_og":false,"twitter_card":"default","twitter_image_type":"default","twitter_image_url":null,"twitter_image_custom_url":null,"twitter_image_custom_fields":null,"twitter_title":null,"twitter_description":null,"schema":{"blockGraphs":[],"customGraphs":[],"default":{"data":{"Article":[],"Course":[],"Dataset":[],"FAQPage":[],"Movie":[],"Person":[],"Product":[],"ProductReview":[],"Car":[],"Recipe":[],"Service":[],"SoftwareApplication":[],"WebPage":[]},"graphName":"","isEnabled":true},"graphs":[]},"schema_type":null,"schema_type_options":null,"pillar_content":false,"robots_default":true,"robots_noindex":false,"robots_noarchive":false,"robots_nosnippet":false,"robots_nofollow":false,"robots_noimageindex":false,"robots_noodp":false,"robots_notranslate":false,"robots_max_snippet":null,"robots_max_videopreview":null,"robots_max_imagepreview":"large","priority":null,"frequency":null,"local_seo":null,"seo_analyzer_scan_date":"2026-01-21 05:47:29","breadcrumb_settings":null,"limit_modified_date":false,"reviewed_by":null,"ai":null,"created":"2021-03-01 03:18:39","updated":"2026-01-21 05:47:29","focus_keyword":null,"additional_keywords":null,"truseo_locale":null},"gt_translate_keys":[{"key":"link","format":"url"}],"_links":{"self":[{"href":"https:\/\/prohoster.info\/nl\/wp-json\/wp\/v2\/posts\/31358","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/prohoster.info\/nl\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/prohoster.info\/nl\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/prohoster.info\/nl\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/prohoster.info\/nl\/wp-json\/wp\/v2\/comments?post=31358"}],"version-history":[{"count":0,"href":"https:\/\/prohoster.info\/nl\/wp-json\/wp\/v2\/posts\/31358\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/prohoster.info\/nl\/wp-json\/wp\/v2\/media\/23324"}],"wp:attachment":[{"href":"https:\/\/prohoster.info\/nl\/wp-json\/wp\/v2\/media?parent=31358"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/prohoster.info\/nl\/wp-json\/wp\/v2\/categories?post=31358"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/prohoster.info\/nl\/wp-json\/wp\/v2\/tags?post=31358"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}