Simplify a ton since the bound is now v1.9

Project.toml

@@ -62,33 +62,33 @@ ArrayInterface = "7.4.11"
 BandedMatrices = "1"
 BlockDiagonals = "0.1"
 ConcreteStructs = "0.2"
-DocStringExtensions = "0.8, 0.9"
+DocStringExtensions = "0.9"
 EnumX = "1"
-EnzymeCore = "0.5, 0.6"
-FastLapackInterface = "1, 2"
+EnzymeCore = "0.6"
+FastLapackInterface = "2"
 GPUArraysCore = "0.1"
 HYPRE = "1.4.0"
 InteractiveUtils = "1.6"
 IterativeSolvers = "0.9.3"
 Libdl = "1.6"
-LinearAlgebra = "1.6"
+LinearAlgebra = "1.9"
 KLU = "0.3.0, 0.4"
 KernelAbstractions = "0.9"
 Krylov = "0.9"
-KrylovKit = "0.5, 0.6"
+KrylovKit = "0.6"
 MKL = "0.6"
 PrecompileTools = "1"
 Preferences = "1"
 RecursiveArrayTools = "2"
 RecursiveFactorization = "0.2.8"
 Reexport = "1"
 Requires = "1"
-SciMLBase = "1.82, 2"
-SciMLOperators = "0.2, 0.3"
-Setfield = "0.7, 0.8, 1"
-SparseArrays = "1.6"
+SciMLBase = "2"
+SciMLOperators = "0.3"
+Setfield = "1"
+SparseArrays = "1.9"
 Sparspak = "0.3.6"
-SuiteSparse = "1.6"
+SuiteSparse = "1.9"
 UnPack = "1"
 julia = "1.9"
 

src/LinearSolve.jl

@@ -46,7 +46,7 @@ PrecompileTools.@recompile_invalidations begin
     import Preferences
 end
 
-if VERSION >= v"1.8" && Preferences.@load_preference("TriggerMKLLBT", true)
+if Preferences.@load_preference("TriggerMKLLBT", true)
    using MKL
 end
 

src/appleaccelerate.jl

@@ -209,12 +209,10 @@ end
 default_alias_A(::AppleAccelerateLUFactorization, ::Any, ::Any) = false
 default_alias_b(::AppleAccelerateLUFactorization, ::Any, ::Any) = false
 
-const PREALLOCATED_APPLE_LU = @static if VERSION >= v"1.8" 
+const PREALLOCATED_APPLE_LU = begin
     A = rand(0, 0)
     luinst = ArrayInterface.lu_instance(A)
     LU(luinst.factors, similar(A, Cint, 0), luinst.info), Ref{Cint}()
-else
-    nothing
 end
 
 function LinearSolve.init_cacheval(alg::AppleAccelerateLUFactorization, A, b, u, Pl, Pr,

src/default.jl

@@ -97,11 +97,7 @@
     if assump.condition === OperatorCondition.IllConditioned || !assump.issq
         DefaultLinearSolver(DefaultAlgorithmChoice.QRFactorization)
     else
-        @static if VERSION >= v"1.8-"
-            DefaultLinearSolver(DefaultAlgorithmChoice.LUFactorization)
-        else
-            DefaultLinearSolver(DefaultAlgorithmChoice.QRFactorization)
-        end
+        DefaultLinearSolver(DefaultAlgorithmChoice.LUFactorization)
     end
 end
 
@@ -110,11 +106,7 @@
     if assump.condition === OperatorCondition.IllConditioned || !assump.issq
         DefaultLinearSolver(DefaultAlgorithmChoice.QRFactorization)
     else
-        @static if VERSION >= v"1.8-"
-            DefaultLinearSolver(DefaultAlgorithmChoice.LUFactorization)
-        else
-            DefaultLinearSolver(DefaultAlgorithmChoice.QRFactorization)
-        end
+        DefaultLinearSolver(DefaultAlgorithmChoice.LUFactorization)
     end
 end
 
@@ -124,11 +116,7 @@
     if assump.condition === OperatorCondition.IllConditioned || !assump.issq
         DefaultLinearSolver(DefaultAlgorithmChoice.QRFactorization)
     else
-        @static if VERSION >= v"1.8-"
-            DefaultLinearSolver(DefaultAlgorithmChoice.LUFactorization)
-        else
-            DefaultLinearSolver(DefaultAlgorithmChoice.QRFactorization)
-        end
+        DefaultLinearSolver(DefaultAlgorithmChoice.LUFactorization)
     end
 end
 
@@ -162,7 +150,7 @@
                 __conditioning(assump) === OperatorCondition.WellConditioned)
                 if length(b) <= 10
                     DefaultAlgorithmChoice.GenericLUFactorization
-                elseif VERSION >= v"1.8" && appleaccelerate_isavailable()
+                elseif appleaccelerate_isavailable()
                     DefaultAlgorithmChoice.AppleAccelerateLUFactorization
                 elseif (length(b) <= 100 || (isopenblas() && length(b) <= 500) ||
                        (usemkl && length(b) <= 200)) &&
@@ -327,11 +315,7 @@
 end
 defaultalg_symbol(::Type{<:GenericFactorization{typeof(ldlt!)}}) = :LDLtFactorization
 
-@static if VERSION >= v"1.7"
-    defaultalg_symbol(::Type{<:QRFactorization{ColumnNorm}}) = :QRFactorizationPivoted
-else
-    defaultalg_symbol(::Type{<:QRFactorization{Val{true}}}) = :QRFactorizationPivoted
-end
+defaultalg_symbol(::Type{<:QRFactorization{ColumnNorm}}) = :QRFactorizationPivoted
 
 """
 if alg.alg === DefaultAlgorithmChoice.LUFactorization

src/deprecated.jl

@@ -79,13 +79,6 @@ function set_cacheval(cache::LinearCache, alg_cache)
     end
 end
 
-@static if VERSION >= v"1.9" # qualified names only supported in Julia 1.9
-    @deprecate SciMLBase.solve(cache::LinearCache, args...; kwargs...) SciMLBase.solve!(cache::LinearCache,
-        args...;
-        kwargs...) false
-else
-    function SciMLBase.solve(cache::LinearCache, args...; kwargs...)
-        @warn "SciMLBase.solve(cache::LinearCache, args...; kwargs...) is deprecated for SciMLBase.solve!(cache::LinearCache, args...; kwargs...) to follow the CommonSolve.jl interface."
-        SciMLBase.solve!(cache::LinearCache, args...; kwargs...)
-    end
-end
+@deprecate SciMLBase.solve(cache::LinearCache, args...; kwargs...) SciMLBase.solve!(cache::LinearCache,
+    args...;
+    kwargs...) false

src/extension_algs.jl

@@ -51,15 +51,12 @@
 """
 struct HYPREAlgorithm <: SciMLLinearSolveAlgorithm
     solver::Any
-
-    @static if VERSION >= v"1.9-"
-        function HYPREAlgorithm(solver)
-            ext = Base.get_extension(@__MODULE__, :LinearSolveHYPREExt)
-            if ext === nothing
-                error("HYPREAlgorithm requires that HYPRE is loaded, i.e. `using HYPRE`")
-            else
-                return new{}(solver)
-            end
+    function HYPREAlgorithm(solver)
+        ext = Base.get_extension(@__MODULE__, :LinearSolveHYPREExt)
+        if ext === nothing
+            error("HYPREAlgorithm requires that HYPRE is loaded, i.e. `using HYPRE`")
+        else
+            return new{}(solver)
         end
     end
 end
@@ -75,14 +72,12 @@
     Using this solver requires adding the package CUDA.jl, i.e. `using CUDA`
 """
 struct CudaOffloadFactorization <: LinearSolve.AbstractFactorization
-    @static if VERSION >= v"1.9-"
-        function CudaOffloadFactorization()
-            ext = Base.get_extension(@__MODULE__, :LinearSolveCUDAExt)
-            if ext === nothing
-                error("CudaOffloadFactorization requires that CUDA is loaded, i.e. `using CUDA`")
-            else
-                return new{}()
-            end
+    function CudaOffloadFactorization()
+        ext = Base.get_extension(@__MODULE__, :LinearSolveCUDAExt)
+        if ext === nothing
+            error("CudaOffloadFactorization requires that CUDA is loaded, i.e. `using CUDA`")
+        else
+            return new{}()
         end
     end
 end
@@ -133,83 +128,51 @@
 """
 MKLPardisoIterate(; kwargs...) = PardisoJL(; solver_type = 1, kwargs...)
 
-@static if VERSION >= v"1.9-"
-    """
-    ```julia
-    PardisoJL(; nprocs::Union{Int, Nothing} = nothing,
-                solver_type = nothing,
-                matrix_type = nothing,
-                iparm::Union{Vector{Tuple{Int, Int}}, Nothing} = nothing,
-                dparm::Union{Vector{Tuple{Int, Int}}, Nothing} = nothing)
-    ```
-
-    A generic method using MKL Pardiso. Specifying `solver_type` is required.
-
-    !!! note
-
-        Using this solver requires adding the package Pardiso.jl, i.e. `using Pardiso`
-
-    ## Keyword Arguments
-
-    For the definition of the keyword arguments, see the Pardiso.jl documentation.
-    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.
-    """
-    struct PardisoJL{T1, T2} <: LinearSolve.SciMLLinearSolveAlgorithm
-        nprocs::Union{Int, Nothing}
-        solver_type::T1
-        matrix_type::T2
-        iparm::Union{Vector{Tuple{Int, Int}}, Nothing}
-        dparm::Union{Vector{Tuple{Int, Int}}, Nothing}
-
-        function PardisoJL(; nprocs::Union{Int, Nothing} = nothing,
+"""
+```julia
+PardisoJL(; nprocs::Union{Int, Nothing} = nothing,
             solver_type = nothing,
             matrix_type = nothing,
             iparm::Union{Vector{Tuple{Int, Int}}, Nothing} = nothing,
             dparm::Union{Vector{Tuple{Int, Int}}, Nothing} = nothing)
-            ext = Base.get_extension(@__MODULE__, :LinearSolvePardisoExt)
-            if ext === nothing
-                error("PardisoJL requires that Pardiso is loaded, i.e. `using Pardiso`")
-            else
-                T1 = typeof(solver_type)
-                T2 = typeof(matrix_type)
-                @assert T1 <: Union{Int, Nothing, ext.Pardiso.Solver}
-                @assert T2 <: Union{Int, Nothing, ext.Pardiso.MatrixType}
-                return new{T1, T2}(nprocs, solver_type, matrix_type, iparm, dparm)
-            end
+```
+
+A generic method using MKL Pardiso. Specifying `solver_type` is required.
+
+!!! note
+
+    Using this solver requires adding the package Pardiso.jl, i.e. `using Pardiso`
+
+## Keyword Arguments
+
+For the definition of the keyword arguments, see the Pardiso.jl documentation.
+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.
+"""
+struct PardisoJL{T1, T2} <: LinearSolve.SciMLLinearSolveAlgorithm
+    nprocs::Union{Int, Nothing}
+    solver_type::T1
+    matrix_type::T2
+    iparm::Union{Vector{Tuple{Int, Int}}, Nothing}
+    dparm::Union{Vector{Tuple{Int, Int}}, Nothing}
+
+    function PardisoJL(; nprocs::Union{Int, Nothing} = nothing,
+        solver_type = nothing,
+        matrix_type = nothing,
+        iparm::Union{Vector{Tuple{Int, Int}}, Nothing} = nothing,
+        dparm::Union{Vector{Tuple{Int, Int}}, Nothing} = nothing)
+        ext = Base.get_extension(@__MODULE__, :LinearSolvePardisoExt)
+        if ext === nothing
+            error("PardisoJL requires that Pardiso is loaded, i.e. `using Pardiso`")
+        else
+            T1 = typeof(solver_type)
+            T2 = typeof(matrix_type)
+            @assert T1 <: Union{Int, Nothing, ext.Pardiso.Solver}
+            @assert T2 <: Union{Int, Nothing, ext.Pardiso.MatrixType}
+            return new{T1, T2}(nprocs, solver_type, matrix_type, iparm, dparm)
         end
     end
-else
-    """
-    ```julia
-    PardisoJL(; nprocs::Union{Int, Nothing} = nothing,
-                solver_type = nothing,
-                matrix_type = nothing,
-                iparm::Union{Vector{Tuple{Int, Int}}, Nothing} = nothing,
-                dparm::Union{Vector{Tuple{Int, Int}}, Nothing} = nothing)
-    ```
-
-    A generic method using MKL Pardiso. Specifying `solver_type` is required.
-
-    !!! note
-
-        Using this solver requires adding the package Pardiso.jl, i.e. `using Pardiso`
-
-    ## Keyword Arguments
-
-    For the definition of the keyword arguments, see the Pardiso.jl documentation.
-    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.
-    """
-    Base.@kwdef struct PardisoJL <: LinearSolve.SciMLLinearSolveAlgorithm
-        nprocs::Union{Int, Nothing} = nothing
-        solver_type::Any = nothing
-        matrix_type::Any = nothing
-        iparm::Union{Vector{Tuple{Int, Int}}, Nothing} = nothing
-        dparm::Union{Vector{Tuple{Int, Int}}, Nothing} = nothing
-    end
 end
 
 """