{"id":155631,"date":"2023-01-17T06:26:30","date_gmt":"2023-01-17T12:26:30","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2023\/01\/how-nvidias-cuda-monopoly-in-machine-learning-is-breaking-openai-triton-and-pytorch-2-0"},"modified":"2023-01-17T06:26:30","modified_gmt":"2023-01-17T12:26:30","slug":"how-nvidias-cuda-monopoly-in-machine-learning-is-breaking-openai-triton-and-pytorch-2-0","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2023\/01\/how-nvidias-cuda-monopoly-in-machine-learning-is-breaking-openai-triton-and-pytorch-2-0","title":{"rendered":"How Nvidia\u2019s CUDA Monopoly In Machine Learning Is Breaking \u2014 OpenAI Triton And PyTorch 2.0"},"content":{"rendered":"<p><\/p>\n<p><iframe style=\"display: block; margin: 0 auto; width: 100%; aspect-ratio: 4\/3; object-fit: contain;\" src=\"https:\/\/www.youtube.com\/embed\/ppWKVg-VxmQ?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; encrypted-media; gyroscope;\n   picture-in-picture\" allowfullscreen><\/iframe><\/p>\n<p>Over the last decade, the landscape of machine learning software development has undergone significant changes. Many frameworks have come and gone, but most have relied heavily on leveraging Nvidia\u2019s CUDA and performed best on Nvidia GPUs. However, with the arrival of PyTorch 2.0 and OpenAI\u2019s Triton, Nvidia\u2019s dominant position in this field, mainly due to its software moat, is being disrupted.<\/p>\n<p>This report will touch on topics such as why Google\u2019s TensorFlow lost out to PyTorch, why Google hasn\u2019t been able to capitalize publicly on its early leadership of AI, the major components of machine learning model training time, the memory capacity\/bandwidth\/cost wall, model optimization, why other AI hardware companies haven\u2019t been able to make a dent in Nvidia\u2019s dominance so far, why hardware will start to matter more, how Nvidia\u2019s competitive advantage in CUDA is wiped away, and a major win one of Nvidia\u2019s competitors has at a large cloud for training silicon.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Over the last decade, the landscape of machine learning software development has undergone significant changes. Many frameworks have come and gone, but most have relied heavily on leveraging Nvidia\u2019s CUDA and performed best on Nvidia GPUs. However, with the arrival of PyTorch 2.0 and OpenAI\u2019s Triton, Nvidia\u2019s dominant position in this field, mainly due to [\u2026]<\/p>\n","protected":false},"author":556,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[],"class_list":["post-155631","post","type-post","status-publish","format-standard","hentry","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/155631","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/556"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=155631"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/155631\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=155631"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=155631"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=155631"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}