Merge pull request #238 from DilumAluthge/dpa/use-gpl-libs

Use `Preferences` to toggle precompilation of code that requires GPL dependencies

Author: ChrisRackauckas

Project.toml

@@ -13,6 +13,7 @@ KLU = "ef3ab10e-7fda-4108-b977-705223b18434"
 Krylov = "ba0b0d4f-ebba-5204-a429-3ac8c609bfb7"
 KrylovKit = "0b1a1467-8014-51b9-945f-bf0ae24f4b77"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+Preferences = "21216c6a-2e73-6563-6e65-726566657250"
 RecursiveFactorization = "f2c3362d-daeb-58d1-803e-2bc74f2840b4"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
@@ -31,6 +32,7 @@ IterativeSolvers = "0.9.2"
 KLU = "0.3.0, 0.4"
 Krylov = "0.9"
 KrylovKit = "0.5, 0.6"
+Preferences = "1"
 RecursiveFactorization = "0.2.8"
 Reexport = "1"
 SciMLBase = "1.68"

src/LinearSolve.jl

@@ -15,6 +15,7 @@ using KLU
 using FastLapackInterface
 using DocStringExtensions
 import GPUArraysCore
+import Preferences
 
 # wrap
 import Krylov
@@ -38,6 +39,8 @@ needs_concrete_A(alg::AbstractSolveFunction) = false
 
 # Code
 
+const INCLUDE_SPARSE = Preferences.@load_preference("include_sparse", Base.USE_GPL_LIBS)
+
 include("common.jl")
 include("factorization.jl")
 include("simplelu.jl")
@@ -47,6 +50,10 @@ include("solve_function.jl")
 include("default.jl")
 include("init.jl")
 
+@static if INCLUDE_SPARSE
+    include("factorization_sparse.jl")
+end
+
 const IS_OPENBLAS = Ref(true)
 isopenblas() = IS_OPENBLAS[]
 
@@ -60,12 +67,17 @@ SnoopPrecompile.@precompile_all_calls begin
     sol = solve(prob, LUFactorization())
     sol = solve(prob, RFLUFactorization())
     sol = solve(prob, KrylovJL_GMRES())
+end
 
-    A = sprand(4, 4, 0.3) + I
-    prob = LinearProblem(A, b)
-    sol = solve(prob)
-    sol = solve(prob, KLUFactorization())
-    sol = solve(prob, UMFPACKFactorization())
+@static if INCLUDE_SPARSE
+    SnoopPrecompile.@precompile_all_calls begin
+        A = sprand(4, 4, 0.3) + I
+        b = rand(4)
+        prob = LinearProblem(A, b)
+        sol = solve(prob)
+        sol = solve(prob, KLUFactorization())
+        sol = solve(prob, UMFPACKFactorization())
+    end
 end
 
 export LUFactorization, SVDFactorization, QRFactorization, GenericFactorization,

src/default.jl

@@ -34,11 +34,17 @@ function defaultalg(A::SymTridiagonal, b, ::OperatorAssumptions{true})
     GenericFactorization(; fact_alg = ldlt!)
 end
 
-function defaultalg(A::SparseMatrixCSC, b, ::OperatorAssumptions{true})
-    if length(b) <= 10_000
-        KLUFactorization()
-    else
-        UMFPACKFactorization()
+@static if INCLUDE_SPARSE
+    function defaultalg(A::SparseMatrixCSC, b, ::OperatorAssumptions{true})
+        if length(b) <= 10_000
+            KLUFactorization()
+        else
+            UMFPACKFactorization()
+        end
+    end
+else
+    function defaultalg(A::SparseMatrixCSC, b, ::OperatorAssumptions{true})
+        KrylovJL_GMRES()
     end
 end
 

src/factorization.jl

@@ -5,14 +5,6 @@ function _ldiv!(x::Vector, A::Factorization, b::Vector)
     ldiv!(A, x)
 end
 
-# Specialize QR for the non-square case
-# Missing ldiv! definitions: https://github.com/JuliaSparse/SparseArrays.jl/issues/242
-function _ldiv!(x::Vector,
-                A::Union{SparseArrays.QR, LinearAlgebra.QRCompactWY,
-                         SuiteSparse.SPQR.QRSparse}, b::Vector)
-    x .= A \ b
-end
-
 function SciMLBase.solve(cache::LinearCache, alg::AbstractFactorization; kwargs...)
     if cache.isfresh
         fact = do_factorization(alg, cache.A, cache.b, cache.u)

src/factorization_sparse.jl

@@ -0,0 +1,7 @@
+# Specialize QR for the non-square case
+# Missing ldiv! definitions: https://github.com/JuliaSparse/SparseArrays.jl/issues/242
+function _ldiv!(x::Vector,
+                A::Union{SparseArrays.QR, LinearAlgebra.QRCompactWY,
+                         SuiteSparse.SPQR.QRSparse}, b::Vector)
+    x .= A \ b
+end