{"id":144103,"date":"2025-10-04T11:12:05","date_gmt":"2025-10-04T09:12:05","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/vypusk-zluda-5-universalnoj-otkrytoj-realizaczii-tehnologii-cuda"},"modified":"2025-10-04T11:12:05","modified_gmt":"2025-10-04T09:12:05","slug":"vypusk-zluda-5-universalnoj-otkrytoj-realizaczii-tehnologii-cuda","status":"publish","type":"post","link":"https:\/\/prohoster.info\/en\/blog\/news\/vypusk-zluda-5-universalnoj-otkrytoj-realizaczii-tehnologii-cuda","title":{"rendered":"The release of ZLUDA 5, a universal open implementation of CUDA technology.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Andrzej Janik presented the release of ZLUDA 5, an open-source implementation of CUDA technology. The project aims to enable the execution of unmodified CUDA applications on systems with non-NVIDIA GPUs, achieving performance close to that of applications running without layers. The project's code is written in Rust and is distributed under the MIT and Apache 2.0 licenses.       <\/p>\n<p>ZLUDA 5 has become the second significant release of the project, formed after cleaning the codebase of the code developed during Andrzej's time at AMD. Since 2022, Andrzej worked at AMD on creating a compatibility layer for AMD GPUs with CUDA, but the project was discontinued in 2024. In accordance with the terms of the contract and after receiving permission to publish from an AMD representative, Andrzej opened the code of the developments made during his time at AMD that enable running CUDA applications on top of the ROCm stack and HIP (Heterogeneous-computing Interface for Portability) runtime.     <\/p>\n<p>Last year, Andrzej was forced to remove the code from public access after a letter from lawyers indicated that the permission given during email correspondence was not legally binding. Following this, Andrzej began work on a new version of ZLUDA, based on the codebase that existed prior to his employment at AMD. The current development is focused on executing applications using CUDA to accelerate machine learning tasks. The project is currently limited to working on AMD GPUs but will be adapted for Intel GPUs in the future.       <\/p>\n<p>Key improvements in the new release:  <\/p>\n<ul>\n<li class=\"l\"> Initial support has been added for running llm.c, Llama.cpp, and PyTorch frameworks on top of ZLUDA for executing large language models utilizing CUDA optimizations applied to NVIDIA GPUs.\n<li class=\"l\"> Initial support has been implemented for running applications that leverage libraries such as cuBLAS, cuBLASLt, and nvml for enhanced performance.\n<li class=\"l\"> A zluda_trace layer has been added for tracing applications that use CUDA. With zluda_trace, issues can be diagnosed and shortcomings in ZLUDA can be identified that hinder the normal execution of applications.\n<li class=\"l\"> A command-line utility zoc (ZLUDA offline compiler) has been introduced, allowing the compilation of NVIDIA PTX instruction files into AMD RDNA intermediate representation (previously, this functionality was available in the form of library functions).\n<li class=\"l\"> The PTX module loader implements a caching mechanism for GPU kernel executions. Caching helps avoid repeated execution of resource-intensive operations that compile PTX (Parallel Thread Execution) instructions into machine code for a given GPU.<br \/>\n<br \/>Source: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=63997\">opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u0410\u043d\u0434\u0436\u0435\u0439 \u042f\u043d\u0438\u043a (Andrzej Janik) \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u0438\u043b \u0432\u044b\u043f\u0443\u0441\u043a ZLUDA 5, \u043e\u0442\u043a\u0440\u044b\u0442\u043e\u0439 \u0440\u0435\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0438 CUDA. \u0426\u0435\u043b\u044c\u044e \u043f\u0440\u043e\u0435\u043a\u0442\u0430 \u044f\u0432\u043b\u044f\u0435\u0442\u0441\u044f \u043f\u0440\u0435\u0434\u043e\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438\u0435 \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e\u0441\u0442\u0438 \u0437\u0430\u043f\u0443\u0441\u043a\u0430 \u043d\u0435\u043c\u043e\u0434\u0438\u0444\u0438\u0446\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u043f\u0440\u0438\u043b\u043e\u0436\u0435\u043d\u0438\u0439 CUDA \u043d\u0430 \u0441\u0438\u0441\u0442\u0435\u043c\u0430\u0445 \u0441 GPU, \u043e\u0442\u043b\u0438\u0447\u043d\u044b\u043c\u0438 \u043e\u0442 GPU NVIDIA, \u0441 \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u044c\u044e, \u0431\u043b\u0438\u0437\u043a\u043e\u0439 \u043a \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438 \u043f\u0440\u0438\u043b\u043e\u0436\u0435\u043d\u0438\u0439, \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0435\u043c\u044b\u0445 \u0431\u0435\u0437 \u043f\u0440\u043e\u0441\u043b\u043e\u0435\u043a. \u041a\u043e\u0434 \u043f\u0440\u043e\u0435\u043a\u0442\u0430 \u043d\u0430\u043f\u0438\u0441\u0430\u043d \u043d\u0430 \u044f\u0437\u044b\u043a\u0435 Rust \u0438 \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u044f\u0435\u0442\u0441\u044f \u043f\u043e\u0434 \u043b\u0438\u0446\u0435\u043d\u0437\u0438\u044f\u043c\u0438 MIT \u0438 Apache 2.0. ZLUDA 5 \u0441\u0442\u0430\u043b [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-144103","post","type-post","status-publish","format-standard","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.1.1 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u0410\u043d\u0434\u0436\u0435\u0439 \u042f\u043d\u0438\u043a (Andrzej Janik) \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u0438\u043b \u0432\u044b\u043f\u0443\u0441\u043a ZLUDA 5, \u043e\u0442\u043a\u0440\u044b\u0442\u043e\u0439 \u0440\u0435\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0438 CUDA.\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" 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