{"id":183381,"date":"2026-09-17T16:54:32","date_gmt":"2026-09-17T14:54:32","guid":{"rendered":"https:\/\/prohoster.info\/blog\/news\/nvidia-predstavila-cuda-rust-dlya-razrabotki-gpu-yader-na-yazyke-rust"},"modified":"2026-09-17T16:54:36","modified_gmt":"2026-09-17T14:54:36","slug":"nvidia-introduces-cuda-rust-for-developing-gpu-kernels-in-rust","status":"publish","type":"post","link":"https:\/\/prohoster.info\/hr\/blog\/news\/nvidia-introduces-cuda-rust-for-developing-gpu-kernels-in-rust","title":{"rendered":"NVIDIA je predstavila CUDA Rust za razvoj GPU jezgri na jeziku Rust","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Tvrtka NVIDIA najavila je razvoj alata CUDA Rust, koji omogu\u0107uje kori\u0161tenje jezika Rust za razvoj jezgri izvr\u0161avanih na strani GPU-a. Alat osigurava sigurnost u radu s memorijom tijekom faze kompilacije i sprje\u010dava pojavu stanja utrke. Sljede\u0107e godine planiraju dovesti CUDA Rust do razine koja je pogodna za razvoj radnih projekata, sli\u010dnih alatima CUDA C++ i CUDA Python.       <\/p>\n<p>CUDA Rust alata podr\u017eava dva modela razvoja paralelno izvr\u0161avanih jezgra \u2014 SIMT (Single Instruction, Multiple Threads) i Tile. SIMT model omogu\u0107uje nisko razinu definiranja logike jednog toka, pokretanje tisu\u0107a takvih tokova i upravljanje njima. Tile model nudi vi\u0161u razinu apstrakcije, u kojoj se umjesto eksplicitnog upravljanja pojedinim tokovima definiraju algoritmi akcije s blokovima podataka (tile), dok sve manipulacije s tokovima, sinkronizaciju pristupa, upravljanje memorijom i raspodjelu podataka po tenzorskim jezgrama preuzima kompajler Tile IR.       <\/p>\n<p>Za razvoj na jeziku Rust s kori\u0161tenjem modela SIMT, razvija se kompajler cuda-oxide, koji omogu\u0107uje kompiliranje koda na jeziku Rust, koji koristi standardni sustav tipova i model vlasni\u0161tva Rust, izravno u instrukcije za izvr\u0161avanje u <a class=\"wpil_keyword_link\" href=\"https:\/\/prohoster.info\/hr\/vps\/abuzoustojchivye-vps\/\"   title=\"virtualnoj ma\u0161ini\" data-wpil-keyword-link=\"linked\">virtualnoj ma\u0161ini<\/a> CUDA PTX (Parallel Thread Execution). Jezgre za GPU se kreiraju na obi\u010dnom Rust-u, ali se izvr\u0161avaju u okru\u017eenju no_std i mogu koristiti samo funkcije iz knji\u017enice libcore i specijalizirane Rust-apstrakcije, bez pristupa standardnoj knji\u017enici Rust (libstd).   <\/p>\n<p>U CUDA-jesgrenama na Rustu dopu\u0161tena je primjena za\u0161tite kroz sustav tipova (safe), kori\u0161tenje blokova unsafe i pristup niskonivonim hardverskim instrukcijama. Za osiguranje sigurnosti predlo\u017een je tip DisjointSlice, koji jam\u010di da svaki tok dobiva ekskluzivni pristup samo svojim podacima. Kod cuda-oxide distribuira se pod licencom Apache 2.0.    <\/p>\n<p>Za primjenu Tail modela, predlo\u017eena je biblioteka cutile-rs koja omogu\u0107ava kori\u0161tenje idiomatskog jezika Rust za kreiranje koda koji se izravno prevodi u CUDA jezgre. Cutile-rs primjenjuje stroga pravila vlasni\u0161tva i posudbe predlo\u017eena u Rust-u za kod koji se izvr\u0161ava na GPU-u. Jezgra se oblikuje kao jednonitna programska jedinica koja obra\u0111uje blok podataka, a sam kompajler dijeli izra\u010dune na niti i osigurava njihovu sinhronizaciju. Nitima se omogu\u0107ava zajedni\u010dki pristup nepromjenjivim tenzorima, dok se za siguran pristup promjenjivim tenzorima koristi njihovo dijeljenje na nepodudarne blokove. Kod cutile-rs distribuira se pod licencom Apache 2.0.<br \/>\n<br \/>Izvor: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=66295\">opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041a\u043e\u043c\u043f\u0430\u043d\u0438\u044f NVIDIA \u043e\u0431\u044a\u044f\u0432\u0438\u043b\u0430 \u043e \u0440\u0430\u0437\u0432\u0438\u0442\u0438\u0438 \u0438\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u0430\u0440\u0438\u044f CUDA Rust, \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u044e\u0449\u0435\u0433\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u044f\u0437\u044b\u043a Rust \u0434\u043b\u044f \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u044f\u0434\u0435\u0440, \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0435\u043c\u044b\u0445 \u043d\u0430 \u0441\u0442\u043e\u0440\u043e\u043d\u0435 GPU. \u0418\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u0430\u0440\u0438\u0439 \u043e\u0431\u0435\u0441\u043f\u0435\u0447\u0438\u0432\u0430\u0435\u0442 \u0431\u0435\u0437\u043e\u043f\u0430\u0441\u043d\u043e\u0441\u0442\u044c \u0440\u0430\u0431\u043e\u0442\u044b \u0441 \u043f\u0430\u043c\u044f\u0442\u044c\u044e \u043d\u0430 \u044d\u0442\u0430\u043f\u0435 \u043a\u043e\u043c\u043f\u0438\u043b\u044f\u0446\u0438\u0438 \u0438 \u043f\u0440\u0435\u0434\u043e\u0442\u0432\u0440\u0430\u0449\u0430\u0435\u0442 \u0432\u043e\u0437\u043d\u0438\u043a\u043d\u043e\u0432\u0435\u043d\u0438\u0435 \u0441\u043e\u0441\u0442\u043e\u044f\u043d\u0438\u0439 \u0433\u043e\u043d\u043a\u0438. \u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0435\u043c \u0433\u043e\u0434\u0443 CUDA Rust \u043f\u043b\u0430\u043d\u0438\u0440\u0443\u044e\u0442 \u0434\u043e\u0432\u0435\u0441\u0442\u0438 \u0434\u043e \u0443\u0440\u043e\u0432\u043d\u044f, \u043f\u0440\u0438\u0433\u043e\u0434\u043d\u043e\u0433\u043e \u0434\u043b\u044f \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u0440\u0430\u0431\u043e\u0447\u0438\u0445 \u043f\u0440\u043e\u0435\u043a\u0442\u043e\u0432, \u0430\u043d\u0430\u043b\u043e\u0433\u0438\u0447\u043d\u043e\u0433\u043e \u0438\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u0430\u0440\u0438\u044f\u043c CUDA C++ \u0438 CUDA Python. \u0418\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u0430\u0440\u0438\u0439 [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":10,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-183381","post","type-post","status-publish","format-standard","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.5 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u041a\u043e\u043c\u043f\u0430\u043d\u0438\u044f NVIDIA 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