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Use Octavian.jl for large mixed-mode CPU calculations. #125

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be74c17
Use Octavian.jl for large mixed-mode CPU calculations.
maleadt Jul 2, 2023
4dac743
Only run with coverage on 1.9.
maleadt Jul 3, 2023
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19 changes: 12 additions & 7 deletions .buildkite/pipeline.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,8 @@ steps:
- JuliaCI/julia#v1:
version: "{{matrix.julia}}"
- JuliaCI/julia-test#v1: ~
- JuliaCI/julia-coverage#v1: ~
- JuliaCI/julia-coverage#v1:
coverage: "{{matrix.coverage}}"
agents:
queue: "juliagpu"
cuda: "*"
Expand All @@ -31,12 +32,16 @@ steps:
- "1.6"
- "1.7"
- "1.8"
- "1.9"
# - "nightly"
# adjustments:
# - with:
# julia: "nightly"
# soft_fail: true
coverage:
- "false"
adjustments:
- with:
julia: "1.9"
coverage: true
# - with:
# julia: "nightly"
# coverage: "false"
# soft_fail: true

- group: ":racehorse: Benchmarks"
steps:
Expand Down
1 change: 1 addition & 0 deletions test/Project.toml
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Expand Up @@ -5,5 +5,6 @@ Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
Octavian = "6fd5a793-0b7e-452c-907f-f8bfe9c57db4"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
XUnit = "3e3c03f2-1a94-11e9-2981-050a4ca824ab"
35 changes: 27 additions & 8 deletions test/matmul.jl
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Original file line number Diff line number Diff line change
@@ -1,7 +1,26 @@
using CUDA
using ForwardDiff
using GemmKernels
using LinearAlgebra
import Octavian, LinearAlgebra

# for large, non-BLAS-compatible matrices, use Octavian.
matmul!(C, A, B, alpha=true, beta=false) = LinearAlgebra.mul!(C, A, B, alpha, beta)
function matmul!(C::Array,
A::Union{Array, LinearAlgebra.Transpose{<:Any, <:Array},
LinearAlgebra.Adjoint{<:Any, <:Array}},
B::Union{Array, LinearAlgebra.Transpose{<:Any, <:Array},
LinearAlgebra.Adjoint{<:Any, <:Array}},
alpha::Bool=true, beta::Bool=false)
supported = eltype(C) <: LinearAlgebra.BlasFloat &&
eltype(A) <: LinearAlgebra.BlasFloat &&
eltype(B) <: LinearAlgebra.BlasFloat &&
eltype(C) == eltype(A) == eltype(B)
if !supported && (sizeof(C) > 2^20 || sizeof(A) > 2^20 || sizeof(B) > 2^20)
Octavian.matmul!(C, A, B, alpha, beta)
else
LinearAlgebra.mul!(C, A, B, alpha, beta)
end
end

################################################################################

Expand Down Expand Up @@ -63,7 +82,7 @@ using LinearAlgebra
new_a_h = transpose_a ? transpose(a_h) : a_h
new_b_h = transpose_b ? transpose(b_h) : b_h

mul!(c_h, new_a_h, new_b_h, alpha, beta)
matmul!(c_h, new_a_h, new_b_h, alpha, beta)
if A_type <: Integer
@test c_h ≈ Array(d)
else
Expand Down Expand Up @@ -121,7 +140,7 @@ using LinearAlgebra
new_a_h = transpose_a ? transpose(a_h) : a_h
new_b_h = transpose_b ? transpose(b_h) : b_h

mul!(c_h, new_a_h, new_b_h, alpha, beta)
matmul!(c_h, new_a_h, new_b_h, alpha, beta)
@test c_h ≈ Array(d) rtol=sqrt(eps(A_type))
end
end
Expand Down Expand Up @@ -222,7 +241,7 @@ using LinearAlgebra
new_a_h = transpose_a ? transpose(a_h) : a_h
new_b_h = transpose_b ? transpose(b_h) : b_h

mul!(c_h, new_a_h, new_b_h, alpha, beta)
matmul!(c_h, new_a_h, new_b_h, alpha, beta)
@test c_h ≈ Array(d) rtol=sqrt(eps(AB_type))
end
end
Expand Down Expand Up @@ -274,7 +293,7 @@ using LinearAlgebra
new_a_h = transpose_a ? transpose(a_h) : a_h
new_b_h = transpose_b ? transpose(b_h) : b_h

mul!(c_h, new_a_h, new_b_h, true, true)
matmul!(c_h, new_a_h, new_b_h, true, true)
@test c_h .+ Array(bias) ≈ Array(d) rtol=sqrt(eps(Float16))
end
end
Expand Down Expand Up @@ -319,7 +338,7 @@ using LinearAlgebra
new_a_h = transpose_a ? transpose(a_h) : a_h
new_b_h = transpose_b ? transpose(b_h) : b_h

mul!(c_h, Diagonal(new_a_h), new_b_h, true, true)
matmul!(c_h, Diagonal(new_a_h), new_b_h, true, true)
@test c_h ≈ Array(d) rtol=sqrt(eps(Float16))
end
end
Expand Down Expand Up @@ -383,7 +402,7 @@ using LinearAlgebra
new_a_h = transpose_a ? transpose(new_a_h) : new_a_h
new_b_h = transpose_b ? transpose(new_b_h) : new_b_h

mul!(c_h, new_a_h, new_b_h, true, true)
matmul!(c_h, new_a_h, new_b_h, true, true)
@test c_h ≈ Array(d) rtol=sqrt(eps(Float16))
end
end
Expand Down Expand Up @@ -436,7 +455,7 @@ using LinearAlgebra
c_dual = reinterpret(ForwardDiff.Dual{Float32,Float32,1}, c_h)
d_dual = reinterpret(ForwardDiff.Dual{Float32,Float32,1}, Array(d))

mul!(c_dual, a_dual, b_dual, true, true)
matmul!(c_dual, a_dual, b_dual, true, true)
@test c_dual ≈ d_dual rtol=sqrt(eps(Float16))
end
end
Expand Down