Reclaim in cuDNN conv algorithm search #1711
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Is there something we can do on the NNlibCUDA side while this lands in the next release (I don't know how long that will take but the last tag was in july)? |
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I'm not sure if CUDA.jl does backports, but if so I'd be happy to replicate this PR against any backport branch as well. |
I've done backports in the past, so I'd be fine doing another backports release. |
maleadt
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This dramatically improves the maximum batch size Flux models with conv layers can support without OOMing on GPU, e.g. https://discourse.julialang.org/t/memory-challenges-for-flux-on-resnet/85385.
maleadt
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Jan 6, 2023
This dramatically improves the maximum batch size Flux models with conv layers can support without OOMing on GPU, e.g. https://discourse.julialang.org/t/memory-challenges-for-flux-on-resnet/85385.
simonbyrne
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Nov 13, 2023
This dramatically improves the maximum batch size Flux models with conv layers can support without OOMing on GPU, e.g. https://discourse.julialang.org/t/memory-challenges-for-flux-on-resnet/85385.
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Per discussion on Slack. This dramatically improves the maximum batch size Flux models with conv layers can support without OOMing on GPU, e.g. https://discourse.julialang.org/t/memory-challenges-for-flux-on-resnet/85385.