This Tweet is currently unavailable. It might be loading or has been removed.
In 2010, GPUs first supported virtual memory, but despite decades of development around virtual memory, CUDA virtual memory had two major limitations. First, it didn’t support memory overcommitment. That is, when you allocate virtual memory with CUDA, it immediately backs that with physical pages. In contrast, typically you get a large virtual memory space and physical memory is only mapped to virtual addresses when first accessed. Second, to be safe, freeing and mallocing forced a GPU sync which slowed them down a ton. This made applications like pytorch essentially manage memory themselves instead of completely relying on CUDA.
Немецкий чиновник отказался участвовать в выборах и выиграл их14:47，详情可参考新收录的资料
После чего, американец назвал «отвратительным» визит Брауна в иранское посольство.，更多细节参见新收录的资料
Intel i7-10750H, Windows 11 (w/ MSVC 2022):。新收录的资料是该领域的重要参考
21:00, 11 марта 2026Бывший СССР