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reduce doesn't query src backend if backend specified #23

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b1a466f
reduce doesn't query src backend if backend specified (to support Map…
dstahlke Feb 16, 2025
3acadd0
unit tests for reduce_1d of range and mappedarray
dstahlke Feb 17, 2025
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4 changes: 2 additions & 2 deletions src/reduce/mapreduce_1d.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -125,14 +125,14 @@ function mapreduce_1d(
blocks = (len + num_per_block - 1) ÷ num_per_block

if !isnothing(temp)
@argcheck get_backend(temp) === get_backend(src)
@argcheck get_backend(temp) === backend
@argcheck eltype(temp) === typeof(init)
@argcheck length(temp) >= blocks * 2
dst = temp
else
# Figure out type for destination
dst_type = typeof(init)
dst = similar(src, dst_type, blocks * 2)
dst = KernelAbstractions.allocate(backend, dst_type, blocks * 2)
end

# Later the kernel will be compiled for views anyways, so use same types
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1 change: 1 addition & 0 deletions test/Project.toml
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Expand Up @@ -2,6 +2,7 @@
Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
KernelAbstractions = "63c18a36-062a-441e-b654-da1e3ab1ce7c"
MappedArrays = "dbb5928d-eab1-5f90-85c2-b9b0edb7c900"
Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
14 changes: 14 additions & 0 deletions test/runtests.jl
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Expand Up @@ -2,6 +2,7 @@ import AcceleratedKernels as AK
using KernelAbstractions
using Test
using Random
using MappedArrays
import Pkg


Expand Down Expand Up @@ -756,6 +757,12 @@ end
max_tasks=16,
min_elems=1000,
)

# Range input
@test AK.sum(1234:100_000, backend) == sum(1234:100000)

# MappedArrays input
@test AK.sum(mappedarray(x->x*x, 1234:100_000), backend) == sum(x->x*x, 1234:100000)
end


Expand All @@ -778,6 +785,7 @@ end
end
end


# Fuzzy correctness testing
for _ in 1:100
for dims in 1:3
Expand Down Expand Up @@ -964,6 +972,12 @@ end
v = array_from_host([Point(rand(Float32), rand(Float32)) for _ in 1:10_042])
temp = similar(v, Tuple{Float32, Float32})
f(v, temp)

# Range input
@test AK.mapreduce(x->x*x, +, 1234:100_000, backend, init=Int64(10)) == sum(x->x*x, 1234:100000, init=Int64(10))

# MappedArrays input
@test AK.mapreduce(x->2*x, +, mappedarray(x->x*x, 1234:100_000), backend, init=Int64(10)) == sum(x->2*x*x, 1234:100000, init=Int64(10))
end


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