{"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\/sl\/blog\/news\/nvidia-introduces-cuda-rust-for-developing-gpu-kernels-in-rust","title":{"rendered":"NVIDIA je predstavila CUDA Rust za razvoj GPU kernel-a na jeziku Rust.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Podjetje NVIDIA je napovedalo razvoj orodij CUDA Rust, ki omogo\u010dajo uporabo jezika Rust za razvoj jeder, ki se izvajajo na GPU-ju. Orodje zagotavlja varnost dela s pomnilnikom v fazi kompilacije in prepre\u010duje nastanek stanj dirke. V naslednjem letu na\u010drtujejo, da bo CUDA Rust dosegla raven, primerno za razvoj delovnih projektov, podobno orodjem CUDA C++ in CUDA Python.       <\/p>\n<p>CUDA Rust orodjarje podpira dva modela razvoja paralelno izvr\u0161avanih jeder \u2014 SIMT (Single Instruction, Multiple Threads) in Tale. Model SIMT omogo\u010da nizkoudobno dolo\u010danje logike posameznega toka, zagon tiso\u010dih takih tokov in njihovo upravljanje. Model Tile ponuja vi\u0161jo stopnjo abstrakcije, pri kateri namesto izrecnega upravljanja z individualnimi tokovi dolo\u010damo algoritme delovanja z bloki podatkov (tile), medtem ko prevajalnik Tile IR prevzame vse manipulacije s tokovi, sinhronizacijo dostopa, upravljanje s pomnilnikom in razporeditev podatkov po tensornih jeder.       <\/p>\n<p>Za razvoj v jeziku Rust z uporabo modela SIMT se razvija prevajalnik cuda-oxide, ki omogo\u010da prevajanje kode v jeziku Rust, ki uporablja standardni sistem tipov in model lastni\u0161tva Rust, neposredno v ukaze za izvajanje v <a class=\"wpil_keyword_link\" href=\"https:\/\/prohoster.info\/sl\/vps\/abuzoustojchivye-vps\/\"   title=\"virtualni napravi\" data-wpil-keyword-link=\"linked\">virtualni napravi<\/a> CUDA PTX (Parallel Thread Execution). Jedra za GPU so ustvarjena v obi\u010dajnem Rustu, vendar se izvajajo v okolju no_std in lahko uporabljajo le funkcije iz knji\u017enice libcore in specializirane Rust-abstrakcije, brez dostopa do standardne knji\u017enice Rust (libstd).   <\/p>\n<p>V CUDA-jedrih na Rustu je dovoljeno uporabljati za\u0161\u010dito prek sistema tipov (safe), uporabo blokov unsafe in dostopanje do nizko ravninskih strojnih navodil. Za zagotavljanje varnosti je predlagan tip DisjointSlice, ki zagotavlja, da vsak tok prejme izklju\u010dni dostop le do svojih podatkov. Koda cuda-oxide se distribuira pod licenco Apache 2.0.    <\/p>\n<p>Za uporabo modela Tail je na voljo knji\u017enica cutile-rs, ki omogo\u010da uporabo idiomatskega jezika Rust za ustvarjanje kode, ki se neposredno prevaja v CUDA-jedra. Cutile-rs uporablja stroga pravila lastni\u0161tva in izposojanja, predlagana v Rustu, za kodo, ki se izvaja na GPU. Jedro je zasnovano kot enotna nit, ki deluje z enoto podatkov, medtem ko prevajalnik sam razdeli izra\u010dune na niti in zagotavlja njihovo sinhronizacijo. Nitim je omogo\u010den skupni dostop do nespremenljivih tenzorjev, za varen dostop do spremenljivih tenzorjev pa se uporablja njihovo deljenje na nepovezane bloke. Koda cutile-rs je na voljo pod licenco 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 5.0.4 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u041a\u043e\u043c\u043f\u0430\u043d\u0438\u044f NVIDIA 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