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start adding butterflies #57

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6 changes: 4 additions & 2 deletions Project.toml
Original file line number Diff line number Diff line change
Expand Up @@ -10,13 +10,15 @@ Polyester = "f517fe37-dbe3-4b94-8317-1923a5111588"
SnoopPrecompile = "66db9d55-30c0-4569-8b51-7e840670fc0c"
StrideArraysCore = "7792a7ef-975c-4747-a70f-980b88e8d1da"
TriangularSolve = "d5829a12-d9aa-46ab-831f-fb7c9ab06edf"
VectorizedRNG = "33b4df10-0173-11e9-2a0c-851a7edac40e"

[compat]
LoopVectorization = "0.10,0.11, 0.12"
Polyester = "0.3.2,0.4.1, 0.5, 0.6"
LoopVectorization = "0.10, 0.11, 0.12"
Polyester = "0.3.2, 0.4.1, 0.5, 0.6"
SnoopPrecompile = "1"
StrideArraysCore = "0.1.13, 0.2.1, 0.3"
TriangularSolve = "0.1.1"
VectorizedRNG = "0.2.20"
julia = "1.5"

[extras]
Expand Down
5 changes: 3 additions & 2 deletions src/RecursiveFactorization.jl
Original file line number Diff line number Diff line change
@@ -1,9 +1,10 @@
module RecursiveFactorization

include("./lu.jl")
include("lu.jl")
include("butterflies.jl")

import SnoopPrecompile

SnoopPrecompile.@precompile_all_calls begin lu!(rand(2, 2)) end
SnoopPrecompile.@precompile_all_calls begin lu!([1.0 0.0; 0.0 1.0]) end

end # module
115 changes: 115 additions & 0 deletions src/butterflies.jl
Original file line number Diff line number Diff line change
@@ -0,0 +1,115 @@

using VectorizedRNG
using LinearAlgebra: Diagonal, I

@inline exphalf(x) = exp(x) * oftype(x, 0.5)
function 🦋!(wv, ::Val{SEED} = Val(888)) where {SEED}
T = eltype(wv)
mrng = VectorizedRNG.MutableXoshift(SEED)
GC.@preserve mrng begin rand!(exphalf, VectorizedRNG.Xoshift(mrng), wv, static(0),
T(-0.05), T(0.1)) end
end

function 🦋workspace(A, ::Val{SEED} = Val(888)) where {SEED}
Usz = 2size(A, 1)
Vsz = 2size(A, 2)
uv = similar(A, Usz + Vsz)
🦋!(uv, Val(SEED))
# (U=@view(wv[1:Usz]), V=@view(wv[1+Usz:end]))
(uv,)
end
const butterfly_workspace = 🦋workspace;

function 🦋mul_level!(A, u, v)
# for now, assume...
M, N = size(A)
Ml = M >>> 1
Nl = N >>> 1
Mh = M - Ml
Nh = N - Nl
@turbo for n in 1:Nl
for m in 1:Ml
A11 = A[m, n]
A21 = A[m + Mh, n]
A12 = A[m, n + Nh]
A22 = A[m + Mh, n + Nh]

T1 = A11 + A12
T2 = A21 + A22
T3 = A11 - A12
T4 = A21 - A22
C11 = T1 + T2
C21 = T1 - T2
C12 = T3 + T4
C22 = T3 - T4

u1 = u[m]
u2 = u[m + Mh]
v1 = v[n]
v2 = v[n + Nh]

A[m, n] = u1 * C11 * v1
A[m + Mh, n] = u2 * C21 * v1
A[m, n + Nh] = u1 * C12 * v2
A[m + Mh, n + Nh] = u2 * C22 * v2
end
end
end

function 🦋mul!(A, (uv,))
M, N = size(A)
@assert iszero(M & 3) & iszero(N & 3)
Mh = M >>> 1
Nh = N >>> 1
U₁ = @view(uv[1:Mh])
U₂ = @view(uv[(1 + Mh + Nh):(2 * Mh + Nh)])
V₁ = @view(uv[(Mh + 1):(Mh + Nh)])
V₂ = @view(uv[(1 + 2 * Mh + Nh):(2 * Mh + 2 * Nh)])
🦋mul_level!(@view(A[1:Mh, 1:Nh]), U₁, V₁)
🦋mul_level!(@view(A[(1 + Mh):M, 1:Nh]), U₂, V₁)
🦋mul_level!(@view(A[1:Mh, (1 + Nh):N]), U₁, V₂)
🦋mul_level!(@view(A[(1 + Mh):M, (1 + Nh):N]), U₂, V₂)
U = @view(uv[(1 + 2 * Mh + 2 * Nh):(2 * Mh + 2 * Nh + M)])
V = @view(uv[(1 + 2 * Mh + 2 * Nh + M):(2 * Mh + 2 * Nh + M + N)])
🦋mul_level!(@view(A[1:M, 1:N]), U, V)
A
end

function diagnegbottom(x)
N = length(x)
y = similar(x, N >>> 1)
z = similar(x, N >>> 1)
for n in 1:(N >>> 1)
y[n] = x[n]
end
for n in 1:(N >>> 1)
z[n] = x[n + (N >>> 1)]
end
Diagonal(y), Diagonal(z)
end
🦋(A, B) = [A B
A -B]

function materializeUV(A, (uv,))
M, N = size(A)
@assert iszero(M & 3) & iszero(N & 3)
Mh = M >>> 1
Nh = N >>> 1

U₁u, U₁l = diagnegbottom(@view(uv[1:Mh]))
U₂u, U₂l = diagnegbottom(@view(uv[(1 + Mh + Nh):(2 * Mh + Nh)]))
V₁u, V₁l = diagnegbottom(@view(uv[(Mh + 1):(Mh + Nh)]))
V₂u, V₂l = diagnegbottom(@view(uv[(1 + 2 * Mh + Nh):(2 * Mh + 2 * Nh)]))
Uu, Ul = diagnegbottom(@view(uv[(1 + 2 * Mh + 2 * Nh):(2 * Mh + 2 * Nh + M)]))
Vu, Vl = diagnegbottom(@view(uv[(1 + 2 * Mh + 2 * Nh + M):(2 * Mh + 2 * Nh + M + N)]))

Bu2 = [🦋(U₁u, U₁l) 0*I
0*I 🦋(U₂u, U₂l)]
Bu1 = 🦋(Uu, Ul)

Bv2 = [🦋(V₁u, V₁l) 0*I
0*I 🦋(V₂u, V₂l)]
Bv1 = 🦋(Vu, Vl)

(Bu2 * Bu1)', Bv2 * Bv1
end
24 changes: 24 additions & 0 deletions test/runtests.jl
Original file line number Diff line number Diff line change
Expand Up @@ -48,3 +48,27 @@ testlu(A::Adjoint, MF::Adjoint, BF) = testlu(parent(A), parent(MF), BF)
testlu(A, mylu(A, p, Val(false), check = false), BF)
end
end end

function wilkinson(N)
A = zeros(N, N)
A[1:(N+1):N*N] .= 1
A[:, end] .= 1
for n in 1:(N - 1)
for r in (n + 1):N
@inbounds A[r, n] = -1
end
end
A
end
@testset "🦋" begin
A800 = wilkinson(800);
B800 = similar(A800);
ws800 = RecursiveFactorization.🦋workspace(B800)
RecursiveFactorization.🦋mul!(copyto!(B800, A800), ws800)
U800, V800 = RecursiveFactorization.materializeUV(B800, ws800)
F800 = RecursiveFactorization.lu!(B800, Val(false))

b = rand(800)
x = V800 * (F800 \ (U800 * b))
@test norm(A800 * x .- b) <= 1e-12
end