Comments (5)
Maybe as a higher-order scan(f, ..; inclusive=true)
function?
from cuarrays.jl.
I have a simple and naive version of cumsum
working. I can turn this into a version of accumulate!
. Should I add this as a PR here?
from cuarrays.jl.
Yes that would be nice! Is it based on the CUDAnative example?
from cuarrays.jl.
Happy to help work on this and contribute an efficient scan
implementation.
I'm particularly interested in an efficient non-destructive mean(c, dims)
where c
is a non-contiguous view as it currently devolves into scalar operations.
The scan example seems to overwrite the array. I guess to make a non-destructive version you would take the work-efficient and accumulate into a temporary array?
Currently mean
is pretty fast but I couldn't figure out how it's implemented.
from cuarrays.jl.
Fixed by #447
from cuarrays.jl.
Related Issues (20)
- similar(PermutedDimsArray(::CuArray)) isa Array HOT 1
- In CuArrays v2.0, GPU operation takes hours to run for the first time HOT 5
- sum!(y::CuVector, x::CuMatrix) throws InvalidIRError error
- Where can I find
- Where can I find All the using instructions of CuArrays? HOT 3
- add implicit float conversion to math functions HOT 4
- Multiplication between mixed types doesn't drop leading dimensions HOT 2
- Very slow 4D broadcast in 2.0.1 HOT 1
- Failed to detect installed CUDA version. HOT 1
- Sum function is slow HOT 8
- CURAND_STATUS_PREEXISTING_FAILURE with v2.0.1 but not v1.7.3 HOT 8
- Deadlock during memory free HOT 5
- Indexing CuArrays with Empty Ranges Errors HOT 5
- Sum, any, etc. with function is no longer implemented HOT 7
- Training Halts when Using CuArrarys HOT 6
- CUBLAS initialization HOT 1
- Performance issue with v2.1.0 compared with v1.7.3 HOT 4
- .+ CartesianIndices: InvalidIRError: compiling kernel broadcast HOT 1
- Package fails to load HOT 4
- Project.toml becoming stale (many notable package downgrades) HOT 1
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from cuarrays.jl.