{"schema_version":"onlylabs.public_signal.v1","title":"Scaleway Writing: Can Your CUDA Code Run on All GPUs?","description":"Scaleway writing signal with public source context, captured evidence pages, related signals, and category-scoped analysis context.","url":"https://onlylabs.fyi/signals/666030ee-7f92-4f0c-a9ee-4861d12197d8","json_url":"https://onlylabs.fyi/signals/666030ee-7f92-4f0c-a9ee-4861d12197d8/signal.json","generated_at":"2026-06-08T15:45:31.226+00:00","org":{"slug":"scaleway","name":"Scaleway","category":"neocloud","category_label":"Neocloud","dossier_url":"https://onlylabs.fyi/labs/scaleway","dossier_json_url":"https://onlylabs.fyi/labs/scaleway/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/666030ee-7f92-4f0c-a9ee-4861d12197d8","signal_json":"https://onlylabs.fyi/signals/666030ee-7f92-4f0c-a9ee-4861d12197d8/signal.json","source":"https://www.scaleway.com/en/blog/can-your-cuda-code-run-on-all-gpus/","lab_dossier":"https://onlylabs.fyi/labs/scaleway","lab_dossier_json":"https://onlylabs.fyi/labs/scaleway/dossier.json","analysis":"https://onlylabs.fyi/analysis/scaleway","analysis_json":"https://onlylabs.fyi/analysis/scaleway/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/scaleway/evidence.json","category":"https://onlylabs.fyi/neoclouds","category_json":"https://onlylabs.fyi/neoclouds.json","category_feed":"https://onlylabs.fyi/neoclouds/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json?category=neocloud","topic":"https://onlylabs.fyi/topics/talking","topic_signals_json":"https://onlylabs.fyi/topics/talking/signals.json?category=neocloud","topic_feed":"https://onlylabs.fyi/topics/talking/feed.xml?category=neocloud","data_business":null},"answer_pack":{"answer":"Scaleway published Can Your CUDA Code Run on All GPUs?. 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Deploy • Antoine Radet, Cédric Courtaud • 06/11/25 • 7 min read Nowadays, Graphic Processing Units (GPUs) are presented as the chips making Artificial Intelligence a reality. But, for long, those chips interested mostly gamers and game developers, as they were originally built to efficiently render the stunning graphics one would expect from modern video games. The connection between these two worlds may not be straightforward. Yet there are, in fact, many similarities in the kind of computations involved in 3D graphics rendering and in chatting with a Large Language Model (LLM) . As a result, the surge in demand for AI capabilities caused high-end GPUs to move from gaming rigs to datacenters. GPUs are great but require a specific development environment to be programmed. Nowadays, CUDA is a very popular GPU programming environment for non-graphical applications. CUDA is a rich ecosystem, widely adopted thanks to its ergonomics, extensive tooling and libraries, and large community of developers. However, it remains fundamentally tied to NVIDIA hardware. 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In short, the GPU world will approach what we see in the real world • CPU power, which was previously held hostage to calculate the sparse pre-GPU world,..."},{"url":"https://www.scaleway.com/en/blog/can-your-cuda-code-run-on-all-gpus/","final_url":"https://www.scaleway.com/en/blog/can-your-cuda-code-run-on-all-gpus/","title":"Can Your CUDA Code Run on All GPUs?","http_status":200,"content_type":"text/html; charset=utf-8","capture_method":"plain","fetched_at":"2026-06-07T21:15:25.679336+00:00","bytes":168820,"raw_path":"bfb6cf277d84d515adca1cc376f913bb9717b2a676ddc5be195fb78427fa8a49.html","content_hash":"1e961a25332402ffbb0bb384ffe6467c3ad570387e769f217ad74934b83602db","excerpt_chars":1200,"truncated":true,"excerpt":"Can Your CUDA Code Run on All GPUs? Deploy • Antoine Radet, Cédric Courtaud • 06/11/25 • 7 min read Nowadays, Graphic Processing Units (GPUs) are presented as the chips making Artificial Intelligence a reality. But, for long, those chips interested mostly gamers and game developers, as they were originally built to efficiently render the stunning graphics one would expect from modern video games. The connection between these two worlds may not be straightforward. Yet there are, in fact, many similarities in the kind of computations involved in 3D graphics rendering and in chatting with a Large Language Model (LLM) . As a result, the surge in demand for AI capabilities caused high-end GPUs to move from gaming rigs to datacenters. GPUs are great but require a specific development environment to be programmed. Nowadays, CUDA is a very popular GPU programming environment for non-graphical applications. CUDA is a rich ecosystem, widely adopted thanks to its ergonomics, extensive tooling and libraries, and large community of developers. However, it remains fundamentally tied to NVIDIA hardware. 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