add test for CuSparseMatrixCSR + Cholesky

Author: hexaeder

test/gpu/cuda.jl

@@ -1,7 +1,66 @@
 using LinearSolve, CUDA, LinearAlgebra, SparseArrays, StableRNGs
-using CUDA.CUSPARSE, CUDSS
+using CUDA.CUSPARSE
 using Test
 
+@testset "Test default solver choice for CuSparse" begin
+    b = Float64[1, 2, 3, 4]
+    b_gpu = CUDA.adapt(CuArray, b)
+
+    A = Float64[1 1 0 0
+                0 1 1 0
+                0 0 3 1
+                0 0 0 4]
+    A_gpu_csr = CUDA.CUSPARSE.CuSparseMatrixCSR(sparse(A))
+    A_gpu_csc = CUDA.CUSPARSE.CuSparseMatrixCSC(sparse(A))
+    prob_csr = LinearProblem(A_gpu_csr, b_gpu)
+    prob_csc = LinearProblem(A_gpu_csc, b_gpu)
+
+    A_sym = Float64[1 1 0 0
+                    1 0 0 2
+                    0 0 3 0
+                    0 2 0 0]
+    A_gpu_sym_csr = CUDA.CUSPARSE.CuSparseMatrixCSR(sparse(A_sym))
+    A_gpu_sym_csc = CUDA.CUSPARSE.CuSparseMatrixCSC(sparse(A_sym))
+    prob_sym_csr = LinearProblem(A_gpu_sym_csr, b_gpu)
+    prob_sym_csc = LinearProblem(A_gpu_sym_csc, b_gpu)
+
+    @testset "Test without CUDSS loaded" begin
+        # assert CuDSS is not loaded yet
+        @test !LinearSolve.cudss_loaded(A_gpu_csr)
+        # csr fallback to krylov
+        alg = solve(prob_csr).alg
+        @test alg.alg == LinearSolve.DefaultAlgorithmChoice.KrylovJL_GMRES
+        # csc fallback to krylov
+        alg = solve(prob_csc).alg
+        @test alg.alg == LinearSolve.DefaultAlgorithmChoice.KrylovJL_GMRES
+        # csr symmetric fallback to krylov
+        alg = solve(prob_sym_csr).alg
+        @test alg.alg == LinearSolve.DefaultAlgorithmChoice.KrylovJL_GMRES
+        # csc symmetric fallback to krylov
+        alg = solve(prob_sym_csc).alg
+        @test alg.alg == LinearSolve.DefaultAlgorithmChoice.KrylovJL_GMRES
+    end
+
+    # after loading CUDSS, it should fall back tu LU factorization
+    using CUDSS
+
+    @testset "Test with CUDSS loaded" begin
+        @test LinearSolve.cudss_loaded(A_gpu_csr)
+        # csr uses LU
+        alg = solve(prob_csr).alg
+        @test alg.alg == LinearSolve.DefaultAlgorithmChoice.LUFactorization
+        # csc fallback to krylov
+        alg = solve(prob_csc).alg
+        @test alg.alg == LinearSolve.DefaultAlgorithmChoice.KrylovJL_GMRES
+        # csr symmetric uses LU/cholesky
+        alg = solve(prob_sym_csr).alg
+        @test alg.alg == LinearSolve.DefaultAlgorithmChoice.LUFactorization
+        # csc symetric fallback to krylov
+        alg = solve(prob_sym_csc).alg
+        @test alg.alg == LinearSolve.DefaultAlgorithmChoice.KrylovJL_GMRES
+    end
+end
+
 CUDA.allowscalar(false)
 
 n = 8
@@ -96,9 +155,9 @@ end
 @testset "CUDSS" begin
     T = Float32
     n = 100
-    A_cpu = sprand(T, n, n, 0.05) + I
+    A_cpu = sprand(rng, T, n, n, 0.05) + I
     x_cpu = zeros(T, n)
-    b_cpu = rand(T, n)
+    b_cpu = rand(rng, T, n)
 
     A_gpu_csr = CuSparseMatrixCSR(A_cpu)
     b_gpu = CuVector(b_cpu)