{"id":28789,"date":"2024-07-30T23:56:00","date_gmt":"2024-07-30T15:56:00","guid":{"rendered":"https:\/\/www.granitefirm.com\/blog\/us\/?p=28789"},"modified":"2026-03-24T09:53:05","modified_gmt":"2026-03-24T01:53:05","slug":"cuda-strengthen-moat","status":"publish","type":"post","link":"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/","title":{"rendered":"How does CUDA strengthen the moat of Nvidia&#8217;s monopoly?"},"content":{"rendered":"\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #ffffff;color:#ffffff\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #ffffff;color:#ffffff\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Introduction_to_CUDA\" >Introduction to CUDA<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#What_is_CUDA\" >What is CUDA?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Release_of_CUDA\" >Release of CUDA<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#How_was_CUDA_invented\" >How was CUDA invented?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Use\" >Use<\/a><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#General_processing\" >General processing<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#GPU_and_CUDA_Mainly_used_for_acceleration\" >GPU and CUDA Mainly used for acceleration<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Biggest_disadvantage\" >Biggest disadvantage<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Closed_but_not_open\" >Closed but not open<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Why_does_CUDA_form_a_moat\" >Why does CUDA form a moat?<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Better_execution_efficiency\" >Better execution efficiency<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Covers_a_wide_range_of_functions\" >Covers a wide range of functions<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Widely_accepted\" >Widely accepted<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Broad_usage_base\" >Broad usage base<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#How_many_customers_use_it\" >How many customers use it?<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Competitors\" >Competitors<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Closed_solutions\" >Closed solutions<\/a><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#AMDs_ROCm\" >AMD&#8217;s ROCm<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-19\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Huaweis_CANN\" >Huawei&#8217;s CANN<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-20\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Open_solutions\" >Open solutions<\/a><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-21\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#OpenCL\" >OpenCL<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-22\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#OpenAIs_Triton\" >OpenAI\u2019s Triton<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-23\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#oneAPI\" >oneAPI<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-24\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#ZLUDA\" >ZLUDA<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-25\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Mojo\" >Mojo<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-26\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Emulator\" >Emulator<\/a><ul class='ez-toc-list-level-4' ><li class='ez-toc-heading-level-4'><a class=\"ez-toc-link ez-toc-heading-27\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Scale\" >Scale<\/a><\/li><\/ul><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-28\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Nvidias_Countermeasures\" >Nvidia&#8217;s Countermeasures<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-29\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#No_emulation_or_compatibility_schemes\" >No emulation or compatibility schemes<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-30\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Continuous_enhancement_of_functions\" >Continuous enhancement of functions<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-31\" href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/#Related_articles\" >Related articles<\/a><\/li><\/ul><\/nav><\/div>\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Introduction_to_CUDA\"><\/span>Introduction to CUDA<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_CUDA\"><\/span>What is CUDA?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>CUDA is a parallel computing platform and programming model that allows general-purpose computing on Nvidia&#8217;s GPUs. The platform enables developers to harness the power of GPUs for parallel computing to accelerate computationally demanding applications.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Release_of_CUDA\"><\/span>Release of CUDA<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Nvidia released CUDA in 2007. CUDA is a programming environment provided by Nvidia GPU to customers, allowing customers to call and access all functions provided by Nvidia GPU through this software interface.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"How_was_CUDA_invented\"><\/span>How was CUDA invented?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Huang Jensen has said: Because in the field of video games we choose, you not only want it to be beautiful, but also want it to be dynamic and be able to create a virtual world. We extend it step by step and introduce it to scientific computing. One of the first applications was molecular dynamics simulations and another was seismic processing, which is basically inverse physics. Seismic processing is very similar to CT reconstruction and is another form of inverse physics. So we solved the problem step by step, expanded to adjacent industries, and finally solved these problems.<\/p>\n\n\n\n<p>Please note: Jensen Huang is not just talking about the computer or video game industry.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Use\"><\/span>Use<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<h4 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"General_processing\"><\/span>General processing<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>CUDA is Nvidia&#8217;s parallel computing platform and application programming interface. Because of CUDA, Nvidia&#8217;s GPU is not limited to computer display, but can be used for other purposes and general processing.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"GPU_and_CUDA_Mainly_used_for_acceleration\"><\/span>GPU and CUDA Mainly used for acceleration<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>Unlike a general-purpose computer, once the processor is built in, everything eventually works. But GPUs are accelerated computers, which means you need to ask yourself, what are you trying to accelerate? There is no such thing as a universal accelerator.<\/p>\n\n\n\n<p>Algorithms are different for different purposes. If you create a processor that specializes in these algorithms and supplements the CPU with the tasks it is good at, then in theory, you can greatly speed up the operation of the application. The reason is that typically 5% to 10% of the code takes up 99.99% of the running time.<\/p>\n\n\n\n<p>If you use Huida&#8217;s GPU and CUDA to process those 5% of the program code, on the accelerator, technically, you can increase the speed of the application by 100 times.<\/p>\n\n\n\n<p>Almost everything related to machine learning is evolving. It can be SQL data processing, Spark type data processing, or vector database type processing, processing unstructured or structured data, which are all data frames. We accelerate these tremendously, but in order to do that, you need a top-level library &#8212; and that&#8217;s CUDA.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Biggest_disadvantage\"><\/span>Biggest disadvantage<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>CUDA&#8217;s biggest drawback is its lack of portability, as it only runs on Nvidia&#8217;s chips.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Closed_but_not_open\"><\/span>Closed but not open<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Just like Apple&#8217;s approach, CUDA is Nvidia&#8217;s unique software interface and can only be used on Nvidia&#8217;s hardware. It is a closed software interface that is not open to the public.<\/p>\n\n\n\n<p>Precisely because of its closure, it has strengthened its uniqueness, strengthened Nvidia&#8217;s competitiveness, and increased Nvidia&#8217;s overall monopoly.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Why_does_CUDA_form_a_moat\"><\/span>Why does CUDA form a moat?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Better_execution_efficiency\"><\/span>Better execution efficiency<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>It is generally considered faster, better supported through a wide range of libraries and software tools, and is generally considered a more mature platform with a wider user base than OpenCL.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Covers_a_wide_range_of_functions\"><\/span>Covers a wide range of functions<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>For example, CUDA provides cuDNN (a library for neural network operations), cuOpt (a library for combinatorial optimization), and cuQuantum (a library for quantum simulations and simulations). , and many other libraries, such as cuDF for data frame processing, SQL-like functionality. So all these different libraries needed to be invented that could reorganize the algorithms in the application so that the Nvidia GPU accelerators could work. If you use these libraries, you can achieve 100 times acceleration and get more speed, which is amazing.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Widely_accepted\"><\/span>Widely accepted<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>We noticed that CUDA seemed to have greater traction within the deep learning software community and was a more attractive skill for job seekers overall. It is the only standard supported by Google&#8217;s TensorFlow and Microsoft&#8217;s CNTK, and is the main standard for most other deep learning frameworks.<\/p>\n\n\n\n<p>Today, many artificial intelligence deep learning frameworks (including Caffe2, Chainer, Databricks, H2O.ai, Keras, MATLAB, MXNet, PyTorch, Theano, and Torch) rely on CUDA to provide support for GPUs.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Broad_usage_base\"><\/span>Broad usage base<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>The biggest advantage of Nvidia chips is that it took nearly 20 years to develop and accelerate graphics chip operations for AI applications&#8211;CUDA, this forms a strong moat that is difficult for competitors to cross.<\/p>\n\n\n\n<p>Since most AI systems and applications already run on Nvidia&#8217;s CUDA, developers have to rewrite these systems for other processors (such as AMD&#8217;s MI 300, Intel&#8217;s Gaudi 3, or Amazon&#8217;s Trainium) and application, time-consuming and risky.<\/p>\n\n\n\n<p>In short, Nvidia\u2019s CUDA currently dominates the back-end architecture. Replacing the development environment of CUDA is more difficult than replacing chips and channels.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"How_many_customers_use_it\"><\/span>How many customers use it?<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>During COMPUTEX 2023, Nvidia revealed that CUDA has more than 4 million developers, more than 3,000 applications, and an astonishing 40 million CUDA downloads, reaching an astonishing 25 million times in 2022 alone. In addition, 15,000 new startups have been established on the Nvidia platform, and 40,000 large enterprises around the world are using CUDA for accelerated computing.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Competitors\"><\/span>Competitors<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Closed_solutions\"><\/span>Closed solutions<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<h4 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"AMDs_ROCm\"><\/span>AMD&#8217;s ROCm<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>Nvida released CUDA in 2007, and AMD released ROCm as a peer-to-peer solution as late as 2016. CUDA has supported Linux and Windows platforms since its inception. The latter has only supported Linux systems for a long time and does not support updates to some Linux systems. It will only support Windows platforms in April 2023.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Huaweis_CANN\"><\/span>Huawei&#8217;s CANN <span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>CANN (Compute Architecture for Neural Networks) is a heterogeneous computing architecture launched by Huawei for AI scenarios. It supports multiple AI frameworks, serves AI processors and programming, and supports the computing efficiency of Huawei&#8217;s Ascend AI processor. key platform.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Open_solutions\"><\/span>Open solutions<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<h4 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"OpenCL\"><\/span>OpenCL<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>OpenCL is CUDA&#8217;s first better-known competitor, launched in 2009. However, although the richness of OpenCL looks attractive, it does not perform as well as CUDA on Nvidia GPUs, making the latter increasingly popular. Today, most deep learning frameworks either lack OpenCL support, or provide CUDA first, and then provide an OpenCL version later.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"OpenAIs_Triton\"><\/span>OpenAI\u2019s Triton<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>OpenAI also developed the artificial intelligence application software Triton in 2019. Engineers from many companies, including Meta, Microsoft and Google, are involved in developing the open source Triton.<\/p>\n\n\n\n<p>Triton was initially only available for Favida GPUs, but now also supports Favorite Gaudi and AMD&#8217;s MI300 GPUs. Among them, Meta\u2019s self-developed AI chip MTIA also uses Triton, becoming a potential competitor in the market.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"oneAPI\"><\/span>oneAPI<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>Intel, Alphabet, ARM and Qualcomm are all members of the UXL Foundation, which is developing a CUDA alternative based on Intel&#8217;s open source platform <a href=\"https:\/\/en.wikipedia.org\/wiki\/OneAPI_(compute_acceleration)\" target=\"_blank\" rel=\"noreferrer noopener\">oneAPI<\/a>.<\/p>\n\n\n\n<p>oneAPI is designed for use across different computing accelerator (coprocessor) architectures, including GPUs, AI accelerators and field programmable gate arrays (FPGAs). The main purpose is to eliminate the need for developers to maintain separate code libraries, multiple programming languages, tools and workflows for each architecture; the program only needs to be written once and can be used on different hardware architectures.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"ZLUDA\"><\/span>ZLUDA<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>The emergence of ZLUDA, an open source porting project, allows Nvidia&#8217;s CUDA and AMD&#8217;s ROCm two computing architectures to be used together, and ultimately supports GPU computing.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Mojo\"><\/span>Mojo<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>Chris Lattner, a well-known senior engineer who has worked at Apple, Tesla and Alphabet, has launched Mojo, a programming language for AI developers. It focuses on writing AI programming languages \u200b\u200bacross hardware platforms without using CUDA, easing the Programming compatible stress.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Emulator\"><\/span>Emulator<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<h4 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Scale\"><\/span>Scale<span class=\"ez-toc-section-end\"><\/span><\/h4>\n\n\n\n<p>A British start-up company has launched a CUDA program compilation tool for AMD, which is free for commercial use. The original program code does not require any modification or conversion, and the AMD chip can also execute programs specifically written for CUDA. This set of software tools is called SCALE, and the developers position it as a GPGPU (general-purpose GPU) programming toolset.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Nvidias_Countermeasures\"><\/span>Nvidia&#8217;s Countermeasures<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"No_emulation_or_compatibility_schemes\"><\/span>No emulation or compatibility schemes<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Starting in 2021, Nvidia has prohibited other hardware platforms from using the analog layer to run CUDA software, but only issued a warning in the online EULA user agreement.<\/p>\n\n\n\n<p>Nvida will update the EULA agreement of CUDA 11.6 version in March 2024. One of them states, &#8220;You may not reverse engineer, decompile, or disassemble any results generated using this SKD and translate them on non-Nvidia platforms.&#8221; There is speculation that this move is aimed at third-party projects such as ZLUDA, in which Intel and AMD are participating, as well as compatibility solutions from Chinese manufacturers such as Denglin Technology GPU+ and MetaX Technology.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Continuous_enhancement_of_functions\"><\/span>Continuous enhancement of functions<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Huang Renxi said at the second quarter teaching conference in August 2024: Accelerated operations start with the CUDA-X function library. The new database opens up new markets for Huida, and Huida has launched many new databases, including CUDA-X Accelerated Polars, Pandas and the leading data science and data processing library Spark, as well as CUVI- for vector databases. S.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"200\" height=\"100\" src=\"https:\/\/www.granitefirm.com\/blog\/us\/wp-content\/uploads\/sites\/2\/2024\/07\/cuda-Custom.jpg\" alt=\"CUDA\" class=\"wp-image-28791\"\/><figcaption class=\"wp-element-caption\">credit: Ideogram<\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Related_articles\"><\/span>Related articles<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2026\/03\/23\/tsmc-ceo-appalling-remarks\/\">&#8220;TSMC CEO appalling remarks on Chinese robots, inferiority to nVidia Huang<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2025\/10\/14\/nvidia-investment-empire\/\">Portfolio of Nvidia investment empire <\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2025\/07\/06\/the-thinking-machine\/\">A must-read for Nvidia investors\uff02The Thinking Machine\uff02<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2025\/08\/24\/ai-inference-chips\/\">AI inference chips vs. training chips<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2025\/05\/15\/oligopoly-enterprise\/\">The world&#8217;s most well-known oligopoly companies<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2025\/02\/08\/deepseek-rout\/\">DeepSeek routed the global AI and stock<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2025\/02\/12\/chinese-ai-companies\/\">Chinese AI progress and top companies<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2025\/02\/02\/ai-agent-software-trend\/\">AI Agent will be the next wave of software industry<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/10\/09\/geoffrey-hinton-nobel-prize\/\">Geoffrey Hinton, 2024 Nobel Physics winner, inadvertently helped Nvida transform to AI overlord<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/10\/12\/nobel-chemistry-ai-expert\/\">2024 Nobel Chemistry Prize awarded to 3 AI experts, accurately predict the 3D structure of proteins<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/12\/22\/comparison-gpu-and-asic\/\">Comparison of AI chips GPU and ASIC<\/a>&#8221; <\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/30\/cuda-strengthen-moat\/\" target=\"_blank\" rel=\"noreferrer noopener\">How does CUDA strengthen the moat of Nvidia&#8217;s monopoly?<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/09\/04\/nvidias-new-business\/#google_vignette\" target=\"_blank\" rel=\"noreferrer noopener\">Nvidia&#8217;s new business set to grow its share price<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2025\/06\/10\/spectrum-x-and-quantum-x\/\">Spectrum-X and Quantum-X switches, Nvidia&#8217;s new territory<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/24\/top-vendors-and-uses-of-gpu\/\" target=\"_blank\" rel=\"noreferrer noopener\">Top vendors and uses of GPU<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/07\/02\/asic-getting-bigger\/\" target=\"_blank\" rel=\"noreferrer noopener\">ASIC market is getting bigger, and related listed companies in the US and Taiwan<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2021\/06\/24\/nvidia-changes-gaming-rules\/\" target=\"_blank\" rel=\"noreferrer noopener\">How does nVidia make money, Nvidia is changing the gaming rules<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2023\/12\/11\/nvidias-monopoly\/\" target=\"_blank\" rel=\"noreferrer noopener\">The reasons for Nvidia\u2019s monopoly and the challenges it faces<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2022\/01\/29\/arm-acquired-by-nvidia\/\">Why nVidia failed to acquire ARM?<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2023\/07\/02\/revisiting-nvidia\/\">Revisiting Nvidia: The Absolute Leader in Artificial Intelligence, Data Center, and Graphics<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2024\/05\/25\/will-intel-go-bankrupt\/\" target=\"_blank\" rel=\"noreferrer noopener\">Will Intel go bankrupt?<\/a>&#8220;<\/li>\n\n\n\n<li>&#8220;<a href=\"https:\/\/www.granitefirm.com\/blog\/us\/2021\/10\/30\/how-does-intel-make-money-and-the-benefits-to-invest-in-it\/\">How does Intel make money? 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I am not responsible for the correctness, opinions, and immediacy of the content and information of the article. Readers must make their own judgments.<\/em><\/li>\n\n\n\n<li><em>I shall not be liable for any damages or other legal liabilities for the direct or indirect losses caused by the readers&#8217; direct or indirect reliance on and reference to the information on this site, or all the responsibilities arising therefrom, as a result of any investment behavior.<\/em><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Today, many artificial intelligence deep learning frameworks (including Caffe2, Chainer, Databricks, H2O.ai, Keras, MATLAB, MXNet, PyTorch, Theano, and Torch) rely on CUDA to provide support for GPUs.<\/p>\n","protected":false},"author":1,"featured_media":28791,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[110,1305],"tags":[2,348,556,1309,41,169,209],"class_list":["post-28789","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-semiconductor","category-diversified-conglomerate-group","tag-aapl","tag-amd","tag-arm","tag-img","tag-intc","tag-nvda","tag-qcom"],"_links":{"self":[{"href":"https:\/\/www.granitefirm.com\/blog\/us\/wp-json\/wp\/v2\/posts\/28789","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.granitefirm.com\/blog\/us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.granitefirm.com\/blog\/us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.granitefirm.com\/blog\/us\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.granitefirm.com\/blog\/us\/wp-json\/wp\/v2\/comments?post=28789"}],"version-history":[{"count":35,"href":"https:\/\/www.granitefirm.com\/blog\/us\/wp-json\/wp\/v2\/posts\/28789\/revisions"}],"predecessor-version":[{"id":41333,"href":"https:\/\/www.granitefirm.com\/blog\/us\/wp-json\/wp\/v2\/posts\/28789\/revisions\/41333"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.granitefirm.com\/blog\/us\/wp-json\/wp\/v2\/media\/28791"}],"wp:attachment":[{"href":"https:\/\/www.granitefirm.com\/blog\/us\/wp-json\/wp\/v2\/media?parent=28789"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.granitefirm.com\/blog\/us\/wp-json\/wp\/v2\/categories?post=28789"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.granitefirm.com\/blog\/us\/wp-json\/wp\/v2\/tags?post=28789"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}