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Conections with TransmuteDims.jl, TensorCast.jl and CUDA.jl v5. #25
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Hi, I am certainly willing to look into this, if one could point me to what exactly I should be looking for. It will anyway be interesting, because other than dropping the support for the |
Any updates? |
Asking again if there are any updates. It is an important issue, required to move to CUDA 5. |
Thanks for the reminder, I keep forgetting about this one. Hence, the whole block if isbitstype(T)
_A = UnsafeStridedView(pointer(A), sz, st, 0, identity)
_B = UnsafeStridedView(pointer(dst), size(dst), strides(dst), 0, identity)
_densecopy_strided!(_B, _A)
else
# This path may be slower than the default one. Not really tested, either.
_densecopy_strided!(dst, StridedView(A, sz, st, 0, identity))
end should just be replaced with _densecopy_strided!(dst, StridedView(A, sz, st, 0, identity)) Also, the @inline function _densecopy_strided!(dst, src)
T = eltype(dst)
LinearAlgebra.axpby!(one(T), src, zero(T), dst)
end can actually just be replaced with |
hey @mcabbott, can you implement these changes? |
Thanks for the info above. I was also trying a bit here: mcabbott/TransmuteDims.jl#43 and got tests passing, but perhaps there's a bit more to do. |
In the pull request (link) in TransmuteDims.jl, which is part of the TensorCast.jl package, about updating dependency for Strided.jl from v1 to v2 there was mentioned some code problems, which prevent this update (most probably problems lies with
UnsafeStridedView
). This dependency issue prevents compatibility of TensorCast.jl with CUDA.jl v4 and v5.The author of TransmuteDims.jl ( mcabbott) mentioned that these problems and required changes may be obvious to authors of Strided.jl. If you have time, can you look into it?
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