{"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\/pt\/blog\/news\/nvidia-introduces-cuda-rust-for-developing-gpu-kernels-in-rust","title":{"rendered":"A NVIDIA apresentou o CUDA Rust para desenvolvimento de n\u00facleos de GPU na linguagem Rust","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

A empresa NVIDIA anunciou o desenvolvimento do conjunto de ferramentas CUDA Rust, que permite usar a linguagem Rust para desenvolver n\u00facleos execut\u00e1veis no lado da GPU. O conjunto de ferramentas garante seguran\u00e7a no manuseio de mem\u00f3ria durante a compila\u00e7\u00e3o e evita a ocorr\u00eancia de condi\u00e7\u00f5es de corrida. No pr\u00f3ximo ano, o CUDA Rust deve ser aprimorado para um n\u00edvel adequado ao desenvolvimento de projetos pr\u00e1ticos, semelhante aos conjuntos de ferramentas CUDA C++ e CUDA Python. <\/p>\n

A ferramenta CUDA Rust suporta dois modelos de desenvolvimento de n\u00facleos executados em paralelo \u2014 SIMT (Single Instruction, Multiple Threads) e Tile. O modelo SIMT permite definir a l\u00f3gica de um \u00fanico fluxo em um n\u00edvel baixo, executar milhares desses fluxos e gerenci\u00e1-los. O modelo Tile oferece um n\u00edvel mais alto de abstra\u00e7\u00e3o, onde, em vez de gerenciar explicitamente fluxos individuais, s\u00e3o definidos algoritmos de a\u00e7\u00e3o com blocos de dados (tile), e todas as manipula\u00e7\u00f5es de fluxos, sincroniza\u00e7\u00e3o de acesso, gerenciamento de mem\u00f3ria e distribui\u00e7\u00e3o de dados entre os n\u00facleos tensorais s\u00e3o assumidas pelo compilador Tile IR. <\/p>\n

Para desenvolvimento na linguagem Rust usando o modelo SIMT, est\u00e1 sendo desenvolvido o compilador cuda-oxide, que permite compilar c\u00f3digo na linguagem Rust, utilizando o sistema de tipos padr\u00e3o e o modelo de propriedade de Rust, diretamente em instru\u00e7\u00f5es para execu\u00e7\u00e3o em m\u00e1quina virtual<\/a> CUDA PTX (Parallel Thread Execution). Os n\u00facleos para GPU s\u00e3o criados em Rust padr\u00e3o, mas executados em um ambiente no_std e s\u00f3 podem usar fun\u00e7\u00f5es da biblioteca libcore e abstra\u00e7\u00f5es Rust especializadas, sem acesso \u00e0 biblioteca padr\u00e3o Rust (libstd). <\/p>\n

Nos n\u00facleos CUDA em Rust, \u00e9 permitida a aplica\u00e7\u00e3o de seguran\u00e7a atrav\u00e9s do sistema de tipos (safe), uso de blocos unsafe e acesso a instru\u00e7\u00f5es de hardware de baixo n\u00edvel. Para garantir a seguran\u00e7a, \u00e9 proposto o tipo DisjointSlice, que garante que cada thread tenha acesso exclusivo apenas aos seus dados. O c\u00f3digo cuda-oxide \u00e9 distribu\u00eddo sob a licen\u00e7a Apache 2.0. <\/p>\n

Para a aplica\u00e7\u00e3o do modelo Tail, \u00e9 sugerida a biblioteca cutile-rs, que permite usar a linguagem idiom\u00e1tica Rust para criar c\u00f3digos que s\u00e3o compilados diretamente em n\u00facleos CUDA. A cutile-rs aplica as r\u00edgidas regras de propriedade e empr\u00e9stimo propostas pelo Rust ao c\u00f3digo executado na GPU. O n\u00facleo \u00e9 estruturado como um programa de thread \u00fanica que opera em um bloco de dados, enquanto o compilador divide os c\u00e1lculos em threads e gerencia sua sincroniza\u00e7\u00e3o. As threads t\u00eam acesso compartilhado a tensores imut\u00e1veis, e o acesso seguro a tensores mut\u00e1veis \u00e9 conseguido atrav\u00e9s de sua divis\u00e3o em blocos n\u00e3o sobrepostos. O c\u00f3digo cutile-rs \u00e9 distribu\u00eddo sob a licen\u00e7a Apache 2.0.
\n
Fonte: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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\u0438 CUDA Python. \u0418\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u0430\u0440\u0438\u0439 […]<\/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\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\n","aioseo_head_json":{"title":"\ud83e\udd47A NVIDIA apresentou CUDA Rust para o desenvolvimento de n\u00facleos GPU na linguagem Rust | ProHoster","description":"A NVIDIA anunciou o desenvolvimento de ferramentas CUDA Rust, que permitem o uso da linguagem Rust para o desenvolvimento de n\u00facleos executados na 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