Update in-place examples to use refactorization

exanauts · Jul 30, 2024 · 94bbef5 · 94bbef5
1 parent 7403269
commit 94bbef5
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Showing 3 changed files with 9 additions and 9 deletions.
diff --git a/README.md b/README.md
@@ -70,7 +70,7 @@ cudss_set(solver, A_gpu)
 c_cpu = rand(T, n)
 c_gpu = CuVector(c_cpu)
 
-cudss("factorization", solver, x_gpu, c_gpu)
+cudss("refactorization", solver, x_gpu, c_gpu)
 cudss("solve", solver, x_gpu, c_gpu)
 
 r_gpu = c_gpu - A_gpu * x_gpu
@@ -115,7 +115,7 @@ cudss_set(solver, A_gpu)
 C_cpu = rand(T, n, p)
 C_gpu = CuMatrix(C_cpu)
 
-cudss("factorization", solver, X_gpu, C_gpu)
+cudss("refactorization", solver, X_gpu, C_gpu)
 cudss("solve", solver, X_gpu, C_gpu)
 
 R_gpu = C_gpu - ( CuSparseMatrixCSR(A_cpu) + Diagonal(d_gpu) ) * X_gpu
@@ -160,7 +160,7 @@ cudss_set(solver, A_gpu)
 C_cpu = rand(T, n, p)
 C_gpu = CuMatrix(C_cpu)
 
-cudss("factorization", solver, X_gpu, C_gpu)
+cudss("refactorization", solver, X_gpu, C_gpu)
 cudss("solve", solver, X_gpu, C_gpu)
 
 R_gpu = C_gpu - ( CuSparseMatrixCSR(A_cpu) + Diagonal(d_gpu) ) * X_gpu

diff --git a/src/generic.jl b/src/generic.jl
@@ -33,7 +33,7 @@ function LinearAlgebra.lu!(solver::CudssSolver{T}, A::CuSparseMatrixCSR{T,Cint};
   cudss_set(solver, A)
   x = CudssMatrix(T, n)
   b = CudssMatrix(T, n)
-  cudss("factorization", solver, x, b)
+  cudss("refactorization", solver, x, b)
   return solver
 end
 
@@ -80,7 +80,7 @@ function LinearAlgebra.ldlt!(solver::CudssSolver{T}, A::CuSparseMatrixCSR{T,Cint
   cudss_set(solver, A)
   x = CudssMatrix(T, n)
   b = CudssMatrix(T, n)
-  cudss("factorization", solver, x, b)
+  cudss("refactorization", solver, x, b)
   return solver
 end
 
@@ -127,7 +127,7 @@ function LinearAlgebra.cholesky!(solver::CudssSolver{T}, A::CuSparseMatrixCSR{T,
   cudss_set(solver, A)
   x = CudssMatrix(T, n)
   b = CudssMatrix(T, n)
-  cudss("factorization", solver, x, b)
+  cudss("refactorization", solver, x, b)
   return solver
 end
 

diff --git a/test/test_cudss.jl b/test/test_cudss.jl
@@ -154,7 +154,7 @@ function cudss_execution()
         c_cpu = rand(T, n)
         c_gpu = CuVector(c_cpu)
 
-        cudss("factorization", solver, x_gpu, c_gpu)
+        cudss("refactorization", solver, x_gpu, c_gpu)
         cudss("solve", solver, x_gpu, c_gpu)
 
         r_gpu = c_gpu - A_gpu * x_gpu
@@ -198,7 +198,7 @@ function cudss_execution()
           C_cpu = rand(T, n, p)
           C_gpu = CuMatrix(C_cpu)
 
-          cudss("factorization", solver, X_gpu, C_gpu)
+          cudss("refactorization", solver, X_gpu, C_gpu)
           cudss("solve", solver, X_gpu, C_gpu)
 
           R_gpu = C_gpu - ( CuSparseMatrixCSR(A_cpu) + Diagonal(d_gpu) ) * X_gpu
@@ -243,7 +243,7 @@ function cudss_execution()
           C_cpu = rand(T, n, p)
           C_gpu = CuMatrix(C_cpu)
 
-          cudss("factorization", solver, X_gpu, C_gpu)
+          cudss("refactorization", solver, X_gpu, C_gpu)
           cudss("solve", solver, X_gpu, C_gpu)
 
           R_gpu = C_gpu - ( CuSparseMatrixCSR(A_cpu) + Diagonal(d_gpu) ) * X_gpu