IRC logs of Freenode #BZFlag for Friday, 2019-12-13

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Flashtupone: macsforme: I don't know much about how GL uses the GPU, but what I've learned from writing CUDA code is that memory allocation is one of the slowest things you can do on a GPU03:52
Flashbut, I don't see any correlation between CPU memory and GPU memory (unless you use "managed" memory ... that may be an NVidia-only thing)03:52
Flashso the optimization in this PR isn't obvious (yet)03:53
FlashI'm guessing that the indices you are tracking somehow relate to GPU memory, but there should be a difference between allocating memory and copying from host to device memory03:53
FlashThis might be a very difficult optimization03:53
tuponeFlash: all the allocation management I'm doing on the PR is about GPU memory (I guess. I think it depends on the driver). CPU memory I don't care in this PR. And for the copy from host to device i do with the vertexData things and it is done only when data changes (or the thing is reset)07:20
tuponeMost of the data (not yet, but in the following PR) will stay fixed there: bzflag world mostly07:21
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BZNotifybzflag: atupone synchronized pull request #232 "Vertex buffers object handling" (https://git.io/Je9kl)07:48
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BZNotifybzflag: atupone synchronized pull request #232 "Vertex buffers object handling" (https://git.io/Je9kl)12:51
BZNotifybzflag: atupone synchronized pull request #232 "Vertex buffers object handling" (https://git.io/Je9kl)13:01
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BZNotifybzflag: atupone synchronized pull request #232 "Vertex buffers object handling" (https://git.io/Je9kl)13:27
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BZNotifybzflag: atupone synchronized pull request #232 "Vertex buffers object handling" (https://git.io/Je9kl)18:17
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BZNotifybzflag: atupone synchronized pull request #232 "Vertex buffers object handling" (https://git.io/Je9kl)22:34
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