LinearSolve.jl/ext/LinearSolveFastLapackInterfaceExt.jl at 73450a5cf5f3e66ce033fe30d21306b99b61e09c · SciML/LinearSolve.jl · GitHub

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module LinearSolveFastLapackInterfaceExt

using LinearSolve, LinearAlgebra
using LinearSolve: LinearVerbosity
using FastLapackInterface

struct WorkspaceAndFactors{W, F}
    workspace::W
    factors::F
end

function LinearSolve.init_cacheval(
        ::FastLUFactorization, A, b, u, Pl, Pr,
        maxiters::Int, abstol, reltol, verbose::Union{LinearVerbosity, Bool},
        assumptions::OperatorAssumptions
    )
    ws = LUWs(A)
    return WorkspaceAndFactors(
        ws, LinearSolve.ArrayInterface.lu_instance(convert(AbstractMatrix, A))
    )
end

function SciMLBase.solve!(
        cache::LinearSolve.LinearCacheType, alg::FastLUFactorization; kwargs...
    )
    A = cache.A
    A = convert(AbstractMatrix, A)
    ws_and_fact = LinearSolve.@get_cacheval(cache, :FastLUFactorization)
    if cache.isfresh
        # we will fail here if A is a different *size* than in a previous version of the same cache.
        # it may instead be desirable to resize the workspace.
        LinearSolve.@set! ws_and_fact.factors = LinearAlgebra.LU(
            LAPACK.getrf!(
                ws_and_fact.workspace,
                A
            )...
        )
        cache.cacheval = ws_and_fact
        cache.isfresh = false
    end
    y = ldiv!(cache.u, cache.cacheval.factors, cache.b)
    return SciMLBase.build_linear_solution(alg, y, nothing, cache)
end

function LinearSolve.init_cacheval(
        alg::FastQRFactorization{NoPivot}, A::AbstractMatrix, b, u, Pl, Pr,
        maxiters::Int, abstol, reltol, verbose::Union{LinearVerbosity, Bool},
        assumptions::OperatorAssumptions
    )
    ws = QRWYWs(A; blocksize = alg.blocksize)
    return WorkspaceAndFactors(
        ws,
        LinearSolve.ArrayInterface.qr_instance(convert(AbstractMatrix, A))
    )
end
function LinearSolve.init_cacheval(
        ::FastQRFactorization{ColumnNorm}, A::AbstractMatrix, b, u, Pl, Pr,
        maxiters::Int, abstol, reltol, verbose::Union{LinearVerbosity, Bool},
        assumptions::OperatorAssumptions
    )
    ws = QRpWs(A)
    return WorkspaceAndFactors(
        ws,
        LinearSolve.ArrayInterface.qr_instance(convert(AbstractMatrix, A))
    )
end

function LinearSolve.init_cacheval(
        alg::FastQRFactorization, A, b, u, Pl, Pr,
        maxiters::Int, abstol, reltol, verbose::Union{LinearVerbosity, Bool},
        assumptions::OperatorAssumptions
    )
    return init_cacheval(
        alg, convert(AbstractMatrix, A), b, u, Pl, Pr,
        maxiters::Int, abstol, reltol, verbose::Union{LinearVerbosity, Bool},
        assumptions::OperatorAssumptions
    )
end

function SciMLBase.solve!(
        cache::LinearSolve.LinearCacheType, alg::FastQRFactorization{P};
        kwargs...
    ) where {P}
    A = cache.A
    A = convert(AbstractMatrix, A)
    ws_and_fact = LinearSolve.@get_cacheval(cache, :FastQRFactorization)
    if cache.isfresh
        # we will fail here if A is a different *size* than in a previous version of the same cache.
        # it may instead be desirable to resize the workspace.
        if P === NoPivot
            LinearSolve.@set! ws_and_fact.factors = LinearAlgebra.QRCompactWY(
                LAPACK.geqrt!(
                    ws_and_fact.workspace,
                    A
                )...
            )
        else
            LinearSolve.@set! ws_and_fact.factors = LinearAlgebra.QRPivoted(
                LAPACK.geqp3!(
                    ws_and_fact.workspace,
                    A
                )...
            )
        end
        cache.cacheval = ws_and_fact
        cache.isfresh = false
    end
    y = ldiv!(cache.u, cache.cacheval.factors, cache.b)
    return SciMLBase.build_linear_solution(alg, y, nothing, cache)
end

end