Add BLISLUFactorization, CudaOffloadLUFactorization, and MetalLUFactorization to default solver choices

ext/LinearSolveCUDAExt.jl

@@ -38,11 +38,13 @@ end
 function SciMLBase.solve!(cache::LinearSolve.LinearCache, alg::CudaOffloadLUFactorization;
         kwargs...)
     if cache.isfresh
+        cacheval = LinearSolve.@get_cacheval(cache, :CudaOffloadLUFactorization)
         fact = lu(CUDA.CuArray(cache.A))
         cache.cacheval = fact
         cache.isfresh = false
     end
-    y = Array(ldiv!(CUDA.CuArray(cache.u), cache.cacheval, CUDA.CuArray(cache.b)))
+    fact = LinearSolve.@get_cacheval(cache, :CudaOffloadLUFactorization)
+    y = Array(ldiv!(CUDA.CuArray(cache.u), fact, CUDA.CuArray(cache.b)))
     cache.u .= y
     SciMLBase.build_linear_solution(alg, y, nothing, cache)
 end

src/LinearSolve.jl

@@ -275,6 +275,9 @@ EnumX.@enumx DefaultAlgorithmChoice begin
     QRFactorizationPivoted
     KrylovJL_CRAIGMR
     KrylovJL_LSMR
+    BLISLUFactorization
+    CudaOffloadLUFactorization
+    MetalLUFactorization
 end
 
 # Autotune preference constants - loaded once at package import time
@@ -296,12 +299,17 @@ function is_algorithm_available(alg::DefaultAlgorithmChoice.T)
         return appleaccelerate_isavailable()  # Available on macOS with Accelerate
     elseif alg === DefaultAlgorithmChoice.RFLUFactorization
         return userecursivefactorization(nothing)  # Requires RecursiveFactorization extension
+    elseif alg === DefaultAlgorithmChoice.BLISLUFactorization
+        return useblis()  # Available if BLIS extension is loaded
+    elseif alg === DefaultAlgorithmChoice.CudaOffloadLUFactorization
+        return usecuda()  # Available if CUDA extension is loaded
+    elseif alg === DefaultAlgorithmChoice.MetalLUFactorization
+        return usemetal()  # Available if Metal extension is loaded
     else
         # For extension-dependent algorithms not explicitly handled above,
         # we cannot easily check availability without trying to use them.
         # For now, assume they're not available in the default selection.
-        # This includes FastLU, BLIS, CUDA, Metal, etc. which would require
-        # specific extension checks.
+        # This includes other extensions that might be added in the future.
         return false
     end
 end
@@ -399,6 +407,17 @@ isopenblas() = IS_OPENBLAS[]
 const HAS_APPLE_ACCELERATE = Ref(false)
 appleaccelerate_isavailable() = HAS_APPLE_ACCELERATE[]
 
+# Extension availability checking functions
+useblis() = Base.get_extension(@__MODULE__, :LinearSolveBLISExt) !== nothing
+usecuda() = Base.get_extension(@__MODULE__, :LinearSolveCUDAExt) !== nothing
+
+# Metal is only available on Apple platforms
+@static if !Sys.isapple()
+    usemetal() = false
+else
+    usemetal() = Base.get_extension(@__MODULE__, :LinearSolveMetalExt) !== nothing
+end
+
 PrecompileTools.@compile_workload begin
     A = rand(4, 4)
     b = rand(4)

src/default.jl

@@ -1,6 +1,6 @@
 needs_concrete_A(alg::DefaultLinearSolver) = true
 mutable struct DefaultLinearSolverInit{T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12,
-    T13, T14, T15, T16, T17, T18, T19, T20, T21}
+    T13, T14, T15, T16, T17, T18, T19, T20, T21, T22, T23, T24}
     LUFactorization::T1
     QRFactorization::T2
     DiagonalFactorization::T3
@@ -22,6 +22,9 @@ mutable struct DefaultLinearSolverInit{T1, T2, T3, T4, T5, T6, T7, T8, T9, T10,
     QRFactorizationPivoted::T19
     KrylovJL_CRAIGMR::T20
     KrylovJL_LSMR::T21
+    BLISLUFactorization::T22
+    CudaOffloadLUFactorization::T23
+    MetalLUFactorization::T24
 end
 
 @generated function __setfield!(cache::DefaultLinearSolverInit, alg::DefaultLinearSolver, v)
@@ -422,6 +425,12 @@ function algchoice_to_alg(alg::Symbol)
         KrylovJL_CRAIGMR()
     elseif alg === :KrylovJL_LSMR
         KrylovJL_LSMR()
+    elseif alg === :BLISLUFactorization
+        BLISLUFactorization(throwerror = false)
+    elseif alg === :CudaOffloadLUFactorization
+        CudaOffloadLUFactorization(throwerror = false)
+    elseif alg === :MetalLUFactorization
+        MetalLUFactorization(throwerror = false)
     else
         error("Algorithm choice symbol $alg not allowed in the default")
     end
@@ -526,6 +535,66 @@ end
                     error("Default algorithm calling solve on RecursiveFactorization without the package being loaded. This shouldn't happen.")
                 end
 
+                sol = SciMLBase.solve!(cache, $(algchoice_to_alg(alg)), args...; kwargs...)
+                if sol.retcode === ReturnCode.Failure && alg.safetyfallback
+                    ## TODO: Add verbosity logging here about using the fallback
+                    sol = SciMLBase.solve!(
+                        cache, QRFactorization(ColumnNorm()), args...; kwargs...)
+                    SciMLBase.build_linear_solution(alg, sol.u, sol.resid, sol.cache;
+                        retcode = sol.retcode,
+                        iters = sol.iters, stats = sol.stats)
+                else
+                    SciMLBase.build_linear_solution(alg, sol.u, sol.resid, sol.cache;
+                        retcode = sol.retcode,
+                        iters = sol.iters, stats = sol.stats)
+                end
+            end
+        elseif alg == Symbol(DefaultAlgorithmChoice.BLISLUFactorization)
+            newex = quote
+                if !useblis()
+                    error("Default algorithm calling solve on BLISLUFactorization without the extension being loaded. This shouldn't happen.")
+                end
+
+                sol = SciMLBase.solve!(cache, $(algchoice_to_alg(alg)), args...; kwargs...)
+                if sol.retcode === ReturnCode.Failure && alg.safetyfallback
+                    ## TODO: Add verbosity logging here about using the fallback
+                    sol = SciMLBase.solve!(
+                        cache, QRFactorization(ColumnNorm()), args...; kwargs...)
+                    SciMLBase.build_linear_solution(alg, sol.u, sol.resid, sol.cache;
+                        retcode = sol.retcode,
+                        iters = sol.iters, stats = sol.stats)
+                else
+                    SciMLBase.build_linear_solution(alg, sol.u, sol.resid, sol.cache;
+                        retcode = sol.retcode,
+                        iters = sol.iters, stats = sol.stats)
+                end
+            end
+        elseif alg == Symbol(DefaultAlgorithmChoice.CudaOffloadLUFactorization)
+            newex = quote
+                if !usecuda()
+                    error("Default algorithm calling solve on CudaOffloadLUFactorization without CUDA.jl being loaded. This shouldn't happen.")
+                end
+
+                sol = SciMLBase.solve!(cache, $(algchoice_to_alg(alg)), args...; kwargs...)
+                if sol.retcode === ReturnCode.Failure && alg.safetyfallback
+                    ## TODO: Add verbosity logging here about using the fallback
+                    sol = SciMLBase.solve!(
+                        cache, QRFactorization(ColumnNorm()), args...; kwargs...)
+                    SciMLBase.build_linear_solution(alg, sol.u, sol.resid, sol.cache;
+                        retcode = sol.retcode,
+                        iters = sol.iters, stats = sol.stats)
+                else
+                    SciMLBase.build_linear_solution(alg, sol.u, sol.resid, sol.cache;
+                        retcode = sol.retcode,
+                        iters = sol.iters, stats = sol.stats)
+                end
+            end
+        elseif alg == Symbol(DefaultAlgorithmChoice.MetalLUFactorization)
+            newex = quote
+                if !usemetal()
+                    error("Default algorithm calling solve on MetalLUFactorization without Metal.jl being loaded. This shouldn't happen.")
+                end
+
                 sol = SciMLBase.solve!(cache, $(algchoice_to_alg(alg)), args...; kwargs...)
                 if sol.retcode === ReturnCode.Failure && alg.safetyfallback
                     ## TODO: Add verbosity logging here about using the fallback

src/extension_algs.jl

@@ -73,9 +73,9 @@ Requires a sufficiently large `A` to overcome the data transfer costs.
     Using this solver requires adding the package CUDA.jl, i.e. `using CUDA`
 """
 struct CudaOffloadLUFactorization <: AbstractFactorization
-    function CudaOffloadLUFactorization()
+    function CudaOffloadLUFactorization(; throwerror = true)
         ext = Base.get_extension(@__MODULE__, :LinearSolveCUDAExt)
-        if ext === nothing
+        if ext === nothing && throwerror
             error("CudaOffloadLUFactorization requires that CUDA is loaded, i.e. `using CUDA`")
         else
             return new()
@@ -610,16 +610,78 @@ A wrapper over the IterativeSolvers.jl MINRES.
 function IterativeSolversJL_MINRES end
 
 """
+    MetalLUFactorization()
+
+A wrapper over Apple's Metal GPU library for LU factorization. Direct calls to Metal 
+in a way that pre-allocates workspace to avoid allocations and automatically offloads 
+to the GPU. This solver is optimized for Metal-capable Apple Silicon Macs.
+
+## Requirements
+Using this solver requires that Metal.jl is loaded: `using Metal`
+
+## Performance Notes
+- Most efficient for large dense matrices where GPU acceleration benefits outweigh transfer costs
+- Automatically manages GPU memory and transfers
+- Particularly effective on Apple Silicon Macs with unified memory
+
+## Example
 ```julia
-MetalLUFactorization()
+using Metal
+alg = MetalLUFactorization()
+sol = solve(prob, alg)
 ```
+"""
+struct MetalLUFactorization <: AbstractFactorization 
+    function MetalLUFactorization(; throwerror = true)
+        @static if !Sys.isapple()
+            if throwerror
+                error("MetalLUFactorization is only available on Apple platforms")
+            else
+                return new()
+            end
+        else
+            ext = Base.get_extension(@__MODULE__, :LinearSolveMetalExt)
+            if ext === nothing && throwerror
+                error("MetalLUFactorization requires that Metal.jl is loaded, i.e. `using Metal`")
+            else
+                return new()
+            end
+        end
+    end
+end
 
-A wrapper over Apple's Metal GPU library. Direct calls to Metal in a way that pre-allocates workspace
-to avoid allocations and automatically offloads to the GPU.
 """
-struct MetalLUFactorization <: AbstractFactorization end
+    BLISLUFactorization()
+
+An LU factorization implementation using the BLIS (BLAS-like Library Instantiation Software) 
+framework. BLIS provides high-performance dense linear algebra kernels optimized for various 
+CPU architectures.
 
-struct BLISLUFactorization <: AbstractFactorization end
+## Requirements
+Using this solver requires that blis_jll is available and the BLIS extension is loaded.
+The solver will be automatically available when conditions are met.
+
+## Performance Notes
+- Optimized for modern CPU architectures with BLIS-specific optimizations
+- May provide better performance than standard BLAS on certain processors
+- Best suited for dense matrices with Float32, Float64, ComplexF32, or ComplexF64 elements
+
+## Example
+```julia
+alg = BLISLUFactorization()
+sol = solve(prob, alg)
+```
+"""
+struct BLISLUFactorization <: AbstractFactorization 
+    function BLISLUFactorization(; throwerror = true)
+        ext = Base.get_extension(@__MODULE__, :LinearSolveBLISExt)
+        if ext === nothing && throwerror
+            error("BLISLUFactorization requires that the BLIS extension is loaded and blis_jll is available")
+        else
+            return new()
+        end
+    end
+end
 
 """
 `CUSOLVERRFFactorization(; symbolic = :RF, reuse_symbolic = true)`

src/factorization.jl

@@ -1203,6 +1203,23 @@ function init_cacheval(::CliqueTreesFactorization, ::StaticArray, b, u, Pl, Pr,
     nothing
 end
 
+# Fallback init_cacheval for extension-based algorithms when extensions aren't loaded
+# These return nothing since the actual implementations are in the extensions
+function init_cacheval(::BLISLUFactorization, A, b, u, Pl, Pr,
+        maxiters::Int, abstol, reltol, verbose::Bool, assumptions::OperatorAssumptions)
+    nothing
+end
+
+function init_cacheval(::CudaOffloadLUFactorization, A, b, u, Pl, Pr,
+        maxiters::Int, abstol, reltol, verbose::Bool, assumptions::OperatorAssumptions)
+    nothing
+end
+
+function init_cacheval(::MetalLUFactorization, A, b, u, Pl, Pr,
+        maxiters::Int, abstol, reltol, verbose::Bool, assumptions::OperatorAssumptions)
+    nothing
+end
+
 for alg in vcat(InteractiveUtils.subtypes(AbstractDenseFactorization),
     InteractiveUtils.subtypes(AbstractSparseFactorization))
     @eval function init_cacheval(alg::$alg, A::MatrixOperator, b, u, Pl, Pr,

src/preferences.jl

@@ -22,11 +22,11 @@ function _string_to_algorithm_choice(algorithm_name::Union{String, Nothing})
     elseif algorithm_name == "FastLUFactorization"
         return DefaultAlgorithmChoice.LUFactorization  # Map to standard LU (FastLapack extension)
     elseif algorithm_name == "BLISLUFactorization"
-        return DefaultAlgorithmChoice.LUFactorization  # Map to standard LU (BLIS extension)
+        return DefaultAlgorithmChoice.BLISLUFactorization  # Now supported as a separate choice
     elseif algorithm_name == "CudaOffloadLUFactorization"
-        return DefaultAlgorithmChoice.LUFactorization  # Map to standard LU (CUDA extension)
+        return DefaultAlgorithmChoice.CudaOffloadLUFactorization  # Now supported as a separate choice
     elseif algorithm_name == "MetalLUFactorization"
-        return DefaultAlgorithmChoice.LUFactorization  # Map to standard LU (Metal extension)
+        return DefaultAlgorithmChoice.MetalLUFactorization  # Now supported as a separate choice
     elseif algorithm_name == "AMDGPUOffloadLUFactorization"
         return DefaultAlgorithmChoice.LUFactorization  # Map to standard LU (AMDGPU extension)
     else

test/nopre/jet.jl

@@ -63,7 +63,8 @@ end
 
     # CUDA/Metal factorizations (only test if CUDA/Metal are loaded)
     # CudaOffloadFactorization requires CUDA to be loaded, skip if not available
-    if @isdefined(MetalLUFactorization)
+    # Metal is only available on Apple platforms
+    if Sys.isapple() && @isdefined(MetalLUFactorization)
         JET.@test_opt solve(prob, MetalLUFactorization()) broken=true
     end
     if @isdefined(BLISLUFactorization)

test_new_solvers.jl

@@ -0,0 +1,86 @@
+using Pkg
+Pkg.activate(".")
+using LinearSolve
+using Test
+using LinearAlgebra
+
+# Test that the new algorithm choices are available in the enum
+@testset "New Algorithm Choices" begin
+    choices = Symbol.(instances(LinearSolve.DefaultAlgorithmChoice.T))
+    println("Available choices: ", choices)
+    @test :BLISLUFactorization in choices
+    @test :CudaOffloadLUFactorization in choices
+    @test :MetalLUFactorization in choices
+end
+
+# Test that availability checking functions exist
+@testset "Availability Functions" begin
+    # These should return false since the extensions aren't loaded
+    @test LinearSolve.useblis() == false
+    @test LinearSolve.usecuda() == false
+    @test LinearSolve.usemetal() == false
+
+    # Test that is_algorithm_available correctly reports availability
+    @test LinearSolve.is_algorithm_available(LinearSolve.DefaultAlgorithmChoice.BLISLUFactorization) == false
+    @test LinearSolve.is_algorithm_available(LinearSolve.DefaultAlgorithmChoice.CudaOffloadLUFactorization) == false
+    @test LinearSolve.is_algorithm_available(LinearSolve.DefaultAlgorithmChoice.MetalLUFactorization) == false
+end
+
+# Test that the algorithms can be instantiated without extensions (with throwerror=false)
+@testset "Algorithm Instantiation" begin
+    # These should work with throwerror=false
+    alg1 = LinearSolve.BLISLUFactorization(throwerror=false)
+    @test alg1 isa LinearSolve.BLISLUFactorization
+
+    alg2 = LinearSolve.CudaOffloadLUFactorization(throwerror=false)
+    @test alg2 isa LinearSolve.CudaOffloadLUFactorization
+
+    # Metal is only available on Apple platforms
+    if Sys.isapple()
+        alg3 = LinearSolve.MetalLUFactorization(throwerror=false)
+        @test alg3 isa LinearSolve.MetalLUFactorization
+    else
+        # On non-Apple platforms, it should still not error with throwerror=false
+        alg3 = LinearSolve.MetalLUFactorization(throwerror=false)
+        @test alg3 isa LinearSolve.MetalLUFactorization
+    end
+
+    # These should throw errors with throwerror=true (default)
+    @test_throws ErrorException LinearSolve.BLISLUFactorization()
+    @test_throws ErrorException LinearSolve.CudaOffloadLUFactorization()
+
+    # Metal error message depends on platform
+    if Sys.isapple()
+        @test_throws ErrorException LinearSolve.MetalLUFactorization()
+    else
+        # On non-Apple platforms, should error with platform message
+        @test_throws ErrorException LinearSolve.MetalLUFactorization()
+    end
+end
+
+# Test that preferences system recognizes the new algorithms
+@testset "Preferences Support" begin
+    # Test that the preference string mapping works
+    alg = LinearSolve._string_to_algorithm_choice("BLISLUFactorization")
+    @test alg === LinearSolve.DefaultAlgorithmChoice.BLISLUFactorization
+
+    alg = LinearSolve._string_to_algorithm_choice("CudaOffloadLUFactorization")
+    @test alg === LinearSolve.DefaultAlgorithmChoice.CudaOffloadLUFactorization
+
+    alg = LinearSolve._string_to_algorithm_choice("MetalLUFactorization")
+    @test alg === LinearSolve.DefaultAlgorithmChoice.MetalLUFactorization
+end
+
+# Test basic solve still works with DefaultLinearSolver
+@testset "Default Solver Still Works" begin
+    A = rand(10, 10)
+    b = rand(10)
+    prob = LinearProblem(A, b)
+
+    # Should use default solver and work fine
+    sol = solve(prob)
+    @test sol.retcode == ReturnCode.Success
+    @test norm(A * sol.u - b) < 1e-10
+end
+
+println("All tests passed!")