In any case, in 2019, CUDA added a more comprehensive virtual memory system that allowed for overcommitment and didn’t force syncing, among other things. In 2023, PyTorch made use of it with expandable segments that map more physical memory onto segments as needed, and uses the non-syncing alloc/free operations. We can enable this with PYTORCH_CUDA_ALLOC_CONF expandable_segments:True, but it's not on by default.
I don’t think Anthropic is doing this to intentionally degrade anyone’s experience. They’re clearly trying to optimize. But it was disruptive enough that I felt the need to decompile the binary to figure out what was going on, and doing it silently on paying users is the wrong way to go about it.
第三十二章 加强海洋开发利用保护。关于这个话题，搜狗输入法提供了深入分析
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