Comments (8)
I'm envisioning a single workspace held in Cuda
, that all conv ops shared. It would be re-allocated if a bigger workspace is needed. So after the first forward pass it would be the size of the biggest workspace, and then any subsequent passes wouldn't have to re-allocate
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what's the difference to CudaSlice?
from cudarc.
Not much, only that it wouldn't have a type generic on it. Although now that I think about it, we probably don't need this. What we really need is a way to reinterpret a CudaSlice<T>
into another type.
What i'd like to do for workspaces is store a CudaSlice<u8>
on Cuda, and then grab a view of those bytes as another type.
So maybe something like:
let mut workspace: CudaSlice<u8> = ...;
let _: CudaView<'_, f32> = workspace.transmute()
from cudarc.
ah ok; why not directly store it as f32 (dtype)?
from cudarc.
Because it needs to support f16, f32, and f64 dtypes, and the device won't necessarily know which one since it doesn't have a dtype generic on it (and I'd prefer not to add it).
from cudarc.
Because it needs to support f16, f32, and f64 dtypes, and the device won't necessarily know which one since it doesn't have a dtype generic on it (and I'd prefer not to add it).
but doesn’t e.g. conv2d has a dtype? and the workspace would have the same dtype, wouldn’t it? or where do you plan to use it
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coreylowman/dfdx@main...workspace
from cudarc.
hmm, ok, so everything runs on a single stream/one cudnn handle?
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