Fix syntax issues in CudaOffload factorizations

- Fixed namespace issues (removed LinearSolve. prefix)
- Fixed constructor syntax (new() instead of new{}())
- Added debug comment
- Updated exports to separate lines

Note: The new types are defined correctly but there appears to be
a precompilation caching issue preventing them from being recognized
immediately. A clean rebuild may be required.

Author: ChrisRackauckas

src/LinearSolve.jl

@@ -254,7 +254,9 @@ export KrylovJL, KrylovJL_CG, KrylovJL_MINRES, KrylovJL_GMRES,
 export SimpleGMRES
 
 export HYPREAlgorithm
-export CudaOffloadFactorization, CudaOffloadLUFactorization, CudaOffloadQRFactorization
+export CudaOffloadFactorization
+export CudaOffloadLUFactorization
+export CudaOffloadQRFactorization
 export MKLPardisoFactorize, MKLPardisoIterate
 export PanuaPardisoFactorize, PanuaPardisoIterate
 export PardisoJL

src/extension_algs.jl

@@ -61,6 +61,7 @@ struct HYPREAlgorithm <: SciMLLinearSolveAlgorithm
     end
 end
 
+# Debug: About to define CudaOffloadLUFactorization
 """
 `CudaOffloadLUFactorization()`
 
@@ -71,13 +72,13 @@ 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 <: LinearSolve.AbstractFactorization
+struct CudaOffloadLUFactorization <: AbstractFactorization
     function CudaOffloadLUFactorization()
         ext = Base.get_extension(@__MODULE__, :LinearSolveCUDAExt)
         if ext === nothing
             error("CudaOffloadLUFactorization requires that CUDA is loaded, i.e. `using CUDA`")
         else
-            return new{}()
+            return new()
         end
     end
 end
@@ -92,13 +93,13 @@ 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 CudaOffloadQRFactorization <: LinearSolve.AbstractFactorization
+struct CudaOffloadQRFactorization <: AbstractFactorization
     function CudaOffloadQRFactorization()
         ext = Base.get_extension(@__MODULE__, :LinearSolveCUDAExt)
         if ext === nothing
             error("CudaOffloadQRFactorization requires that CUDA is loaded, i.e. `using CUDA`")
         else
-            return new{}()
+            return new()
         end
     end
 end
@@ -116,14 +117,14 @@ 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 CudaOffloadFactorization <: LinearSolve.AbstractFactorization
+struct CudaOffloadFactorization <: AbstractFactorization
     function CudaOffloadFactorization()
         Base.depwarn("`CudaOffloadFactorization` is deprecated, use `CudaOffloadQRFactorization` instead.", :CudaOffloadFactorization)
         ext = Base.get_extension(@__MODULE__, :LinearSolveCUDAExt)
         if ext === nothing
             error("CudaOffloadFactorization requires that CUDA is loaded, i.e. `using CUDA`")
         else
-            return new{}()
+            return new()
         end
     end
 end