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pardiso: format
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@j-fu
j-fu committed Jun 5, 2024
1 parent 372ea1e commit 0c0de1c
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11 changes: 5 additions & 6 deletions ext/LinearSolvePardisoExt.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -27,9 +27,9 @@ function LinearSolve.init_cacheval(alg::PardisoJL,

if isnothing(vendor)
if Pardiso.panua_is_available()
vendor=:Panua
vendor = :Panua

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else
vendor=:MKL
vendor = :MKL
end
end

Expand All @@ -42,7 +42,7 @@ function LinearSolve.init_cacheval(alg::PardisoJL,

# for mkl 1 means conjugated and 2 means transposed.
# https://www.intel.com/content/www/us/en/docs/onemkl/developer-reference-c/2024-0/pardiso-iparm-parameter.html#IPARM37
transposed_iparm = 2
transposed_iparm = 2

solver
else
Expand All @@ -53,15 +53,15 @@ function LinearSolve.init_cacheval(alg::PardisoJL,
solver = Pardiso.PardisoSolver()
Pardiso.pardisoinit(solver)
solver_type !== nothing && Pardiso.set_solver!(solver, solver_type)

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solver

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else
error("Panua Pardiso is not available.")

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end
else
error("Pardiso vendor must be either `:MKL` or `:Panua`")
end

if matrix_type !== nothing
Pardiso.set_matrixtype!(solver, matrix_type)
else
Expand Down Expand Up @@ -125,7 +125,6 @@ function LinearSolve.init_cacheval(alg::PardisoJL,
b)
end

>>>>>>> main
return solver
end

Expand Down
17 changes: 8 additions & 9 deletions src/extension_algs.jl
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Expand Up @@ -108,7 +108,7 @@ All values default to `nothing` and the solver internally determines the values
given the input types, and these keyword arguments are only for overriding the
default handling process. This should not be required by most users.
"""
MKLPardisoFactorize(; kwargs...) = PardisoJL(; vendor=:MKL, solver_type = 0, kwargs...)
MKLPardisoFactorize(; kwargs...) = PardisoJL(; vendor = :MKL, solver_type = 0, kwargs...)

"""
```julia
Expand Down Expand Up @@ -136,8 +136,7 @@ All values default to `nothing` and the solver internally determines the values
given the input types, and these keyword arguments are only for overriding the
default handling process. This should not be required by most users.
"""
MKLPardisoIterate(; kwargs...) = PardisoJL(; vendor=:MKL, solver_type = 1, kwargs...)

MKLPardisoIterate(; kwargs...) = PardisoJL(; vendor = :MKL, solver_type = 1, kwargs...)

"""
```julia
Expand Down Expand Up @@ -165,7 +164,8 @@ All values default to `nothing` and the solver internally determines the values
given the input types, and these keyword arguments are only for overriding the
default handling process. This should not be required by most users.
"""
PanuaPardisoFactorize(; kwargs...) = PardisoJL(; vendor=:Panua, solver_type = 0, kwargs...)
PanuaPardisoFactorize(; kwargs...) = PardisoJL(;

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vendor = :Panua, solver_type = 0, kwargs...)

"""
```julia
Expand All @@ -188,8 +188,7 @@ All values default to `nothing` and the solver internally determines the values
given the input types, and these keyword arguments are only for overriding the
default handling process. This should not be required by most users.
"""
PanuaPardisoIterate(; kwargs...) = PardisoJL(; vendor=:Panua, solver_type = 1, kwargs...)

PanuaPardisoIterate(; kwargs...) = PardisoJL(; vendor = :Panua, solver_type = 1, kwargs...)

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"""
```julia
Expand All @@ -198,7 +197,7 @@ PardisoJL(; nprocs::Union{Int, Nothing} = nothing,
matrix_type = nothing,
iparm::Union{Vector{Tuple{Int, Int}}, Nothing} = nothing,
dparm::Union{Vector{Tuple{Int, Int}}, Nothing} = nothing,
vendor::Union{Symbol,Nothing} = nothing
vendor::Union{Symbol, Nothing} = nothing
)
```
Expand All @@ -225,15 +224,15 @@ struct PardisoJL{T1, T2} <: LinearSolve.SciMLLinearSolveAlgorithm
cache_analysis::Bool
iparm::Union{Vector{Tuple{Int, Int}}, Nothing}
dparm::Union{Vector{Tuple{Int, Int}}, Nothing}
vendor::Union{Symbol,Nothing}
vendor::Union{Symbol, Nothing}

function PardisoJL(; nprocs::Union{Int, Nothing} = nothing,
solver_type = nothing,
matrix_type = nothing,
cache_analysis = false,
iparm::Union{Vector{Tuple{Int, Int}}, Nothing} = nothing,
dparm::Union{Vector{Tuple{Int, Int}}, Nothing} = nothing,
vendor::Union{Symbol,Nothing}=nothing )
vendor::Union{Symbol, Nothing} = nothing)
ext = Base.get_extension(@__MODULE__, :LinearSolvePardisoExt)
if ext === nothing
error("PardisoJL requires that Pardiso is loaded, i.e. `using Pardiso`")
Expand Down
203 changes: 109 additions & 94 deletions test/pardiso/pardiso.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -18,18 +18,26 @@ cache_kwargs = (; abstol = 1e-8, reltol = 1e-8, maxiter = 30)

prob2 = LinearProblem(A2, b2)

algs=[PardisoJL()]
algs=LinearSolve.SciMLLinearSolveAlgorithm[PardisoJL()]
solvers=Pardiso.AbstractPardisoSolver[]
extended_algs=LinearSolve.SciMLLinearSolveAlgorithm[PardisoJL()]

if Pardiso.mkl_is_available()
algs=vcat(algs,[MKLPardisoFactorize(), MKLPardisoIterate()])
push!(algs,MKLPardisoFactorize())
push!(solvers,Pardiso.MKLPardisoSolver())
extended_algs=vcat(extended_algs,[MKLPardisoFactorize(), MKLPardisoIterate()])
@info "Testing MKL Pardiso"
end

if Pardiso.panua_is_available()
algs=vcat(algs,[PanuaPardisoFactorize(), PanuaPardisoIterate()])
push!(algs,PanuaPardisoFactorize())
push!(solvers,Pardiso.PardisoSolver())
extended_algs=vcat(extended_algs,[PanuaPardisoFactorize(), PanuaPardisoIterate()])
@info "Testing Panua Pardiso"
end


for alg in algs
for alg in extended_algs
u = solve(prob1, alg; cache_kwargs...).u
@test A1 * u ≈ b1

Expand All @@ -38,7 +46,6 @@ for alg in algs
@test A2 * u ≈ b2
end

return


Random.seed!(10)
Expand All @@ -48,24 +55,27 @@ b1 = rand(n);
b2 = rand(n);
prob = LinearProblem(copy(A), copy(b1))

prob = LinearProblem(copy(A), copy(b1))

linsolve = init(prob, UMFPACKFactorization())
sol11 = solve(linsolve)
linsolve = LinearSolve.set_b(sol11.cache, copy(b2))
sol12 = solve(linsolve)
linsolve = LinearSolve.set_A(sol12.cache, copy(A2))
sol13 = solve(linsolve)

linsolve = init(prob, MKLPardisoFactorize())
sol31 = solve(linsolve)
linsolve = LinearSolve.set_b(sol31.cache, copy(b2))
sol32 = solve(linsolve)
linsolve = LinearSolve.set_A(sol32.cache, copy(A2))
sol33 = solve(linsolve)

@test sol11.u ≈ sol31.u
@test sol12.u ≈ sol32.u
@test sol13.u ≈ sol33.u

for alg in algs
linsolve = init(prob, alg)
sol31 = solve(linsolve)
linsolve = LinearSolve.set_b(sol31.cache, copy(b2))
sol32 = solve(linsolve)
linsolve = LinearSolve.set_A(sol32.cache, copy(A2))
sol33 = solve(linsolve)
@test sol11.u ≈ sol31.u
@test sol12.u ≈ sol32.u
@test sol13.u ≈ sol33.u
end


# Test for problem from #497
Expand All @@ -78,87 +88,92 @@ function makeA()
return(A)
end

A=makeA()
u0=fill(0.1,size(A,2))
linprob = LinearProblem(A, A*u0)
u = LinearSolve.solve(linprob, PardisoJL())
@test norm(u-u0) < 1.0e-14

for alg in algs
A=makeA()
u0=fill(0.1,size(A,2))
linprob = LinearProblem(A, A*u0)
u = LinearSolve.solve(linprob, alg)
@test norm(u-u0) < 1.0e-14
end


# Testing and demonstrating Pardiso.set_iparm! for MKLPardisoSolver
solver = Pardiso.MKLPardisoSolver()
iparm = [
(1, 1),
(2, 2),
(3, 0),
(4, 0),
(5, 0),
(6, 0),
(7, 0),
(8, 20),
(9, 0),
(10, 13),
(11, 1),
(12, 1),
(13, 1),
(14, 0),
(15, 0),
(16, 0),
(17, 0),
(18, -1),
(19, -1),
(20, 0),
(21, 0),
(22, 0),
(23, 0),
(24, 10),
(25, 0),
(26, 0),
(27, 1),
(28, 0),
(29, 0),
(30, 0),
(31, 0),
(32, 0),
(33, 0),
(34, 0),
(35, 0),
(36, 0),
(37, 0),
(38, 0),
(39, 0),
(40, 0),
(41, 0),
(42, 0),
(43, 0),
(44, 0),
(45, 0),
(46, 0),
(47, 0),
(48, 0),
(49, 0),
(50, 0),
(51, 0),
(52, 0),
(53, 0),
(54, 0),
(55, 0),
(56, 0),
(57, 0),
(58, 0),
(59, 0),
(60, 0),
(61, 0),
(62, 0),
(63, 0),
(64, 0)
]

for i in iparm
Pardiso.set_iparm!(solver, i...)
end

for i in Base.OneTo(length(iparm))
@test Pardiso.get_iparm(solver, i) == iparm[i][2]

# Testing and demonstrating Pardiso.set_iparm! for MKLPardisoSolver
for solver in solvers
iparm = [
(1, 1),
(2, 2),
(3, 0),
(4, 0),
(5, 0),
(6, 0),
(7, 0),
(8, 20),
(9, 0),
(10, 13),
(11, 1),
(12, 1),
(13, 1),
(14, 0),
(15, 0),
(16, 0),
(17, 0),
(18, -1),
(19, -1),
(20, 0),
(21, 0),
(22, 0),
(23, 0),
(24, 10),
(25, 0),
(26, 0),
(27, 1),
(28, 0),
(29, 0),
(30, 0),
(31, 0),
(32, 0),
(33, 0),
(34, 0),
(35, 0),
(36, 0),
(37, 0),
(38, 0),
(39, 0),
(40, 0),
(41, 0),
(42, 0),
(43, 0),
(44, 0),
(45, 0),
(46, 0),
(47, 0),
(48, 0),
(49, 0),
(50, 0),
(51, 0),
(52, 0),
(53, 0),
(54, 0),
(55, 0),
(56, 0),
(57, 0),
(58, 0),
(59, 0),
(60, 0),
(61, 0),
(62, 0),
(63, 0),
(64, 0)
]

for i in iparm
Pardiso.set_iparm!(solver, i...)
end

for i in Base.OneTo(length(iparm))
@test Pardiso.get_iparm(solver, i) == iparm[i][2]
end
end

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