Moved warning prints from cusparseSolver to BdaBridge. Moved solving logic from BdaBridge to cusparseSolver. Added cusparseSolverStatus enum.

opm/simulators/linalg/bda/BdaBridge.cpp

@@ -20,6 +20,8 @@
 #include <config.h>
 #include <memory>
 
+#include <opm/common/OpmLog/OpmLog.hpp>
+
 #include <opm/simulators/linalg/bda/BdaBridge.hpp>
 #include <opm/simulators/linalg/bda/BdaResult.hpp>
 
@@ -91,7 +93,7 @@ int checkZeroDiagonal(BridgeMatrix& mat) {
 // if only_vals, do not convert rowPointers and colIndices
 // sparsity pattern should stay the same due to matrix-add-well-contributions
 template <class BridgeMatrix>
-void convertMatrixBsr(BridgeMatrix& mat, std::vector<double> &h_vals, std::vector<int> &h_rows, std::vector<int> &h_cols, int dim, bool only_vals) {
+void convertMatrixBsr(BridgeMatrix& mat, std::vector<double> &h_vals, std::vector<int> &h_rows, std::vector<int> &h_cols, int dim) {
 	int sum_nnzs = 0;
 	int nnz = mat.nonzeroes()*dim*dim;
 
@@ -99,7 +101,7 @@ void convertMatrixBsr(BridgeMatrix& mat, std::vector<double> &h_vals, std::vecto
 	memcpy(h_vals.data(), &(mat[0][0][0][0]), sizeof(double)*nnz);
 
 	// convert colIndices and rowPointers
-	if(only_vals == false){
+	if(h_rows.size() == 0){
 		h_rows.emplace_back(0);
 			for(typename BridgeMatrix::const_iterator r = mat.begin(); r != mat.end(); ++r){
 				int size_row = 0;
@@ -160,13 +162,11 @@ void BdaBridge::solve_system(BridgeMatrix *mat, BridgeVector &b, InverseOperator
 		checkZeroDiagonal(*mat);
 #endif
 
-		bool initialized = backend->isInitialized();
-
 #if PRINT_TIMERS_BRIDGE
 		Dune::Timer t;
 #endif
 
-		convertMatrixBsr(*mat, h_vals, h_rows, h_cols, dim, initialized);
+		convertMatrixBsr(*mat, h_vals, h_rows, h_cols, dim);
 		convertBlockVectorToArray(b, h_b);
 
 #if PRINT_TIMERS_BRIDGE
@@ -176,17 +176,23 @@ void BdaBridge::solve_system(BridgeMatrix *mat, BridgeVector &b, InverseOperator
 		/////////////////////////
 		// actually solve
 
-		if(initialized == false){
-			backend->initialize(N, nnz, dim);
-			backend->copy_system_to_gpu(h_vals.data(), h_rows.data(), h_cols.data(), h_b.data());
-			backend->analyse_matrix();
-		}else{
-			backend->update_system_on_gpu(h_vals.data(), h_b.data());
-		}
-		backend->reset_prec_on_gpu();
-		if(backend->create_preconditioner()){
-			backend->solve_system(result);
+		typedef cusparseSolverBackend::cusparseSolverStatus cusparseSolverStatus;
+
+		cusparseSolverStatus status = backend->solve_system(N, nnz, dim, h_vals.data(), h_rows.data(), h_cols.data(), h_b.data(), result);
+		switch(status){
+		case cusparseSolverStatus::CUSPARSE_SOLVER_SUCCESS:
+			//OpmLog::info("cusparseSolver converged");
+			break;
+		case cusparseSolverStatus::CUSPARSE_SOLVER_ANALYSIS_FAILED:
+			OpmLog::warning("cusparseSolver could not analyse level information of matrix, perhaps there is still a 0.0 on the diagonal of a block on the diagonal");
+			break;
+		case cusparseSolverStatus::CUSPARSE_SOLVER_CREATE_PRECONDITIONER_FAILED:
+			OpmLog::warning("cusparseSolver could not create preconditioner, perhaps there is still a 0.0 on the diagonal of a block on the diagonal");
+			break;
+		default:
+			OpmLog::warning("cusparseSolver returned unknown status code");
 		}
+
 		res.iterations = result.iterations;
 		res.reduction = result.reduction;
 		res.converged = result.converged;

opm/simulators/linalg/bda/cusparseSolverBackend.cu

@@ -55,8 +55,7 @@ namespace Opm
 		finalize();
 	}
 
-	// return true iff converged
-	bool cusparseSolverBackend::gpu_pbicgstab(BdaResult& res){
+	void cusparseSolverBackend::gpu_pbicgstab(BdaResult& res){
 		double t_total1, t_total2;
 		int n = N;
 		double rho = 1.0, rhop;
@@ -163,7 +162,6 @@ namespace Opm
 		if(verbosity > 0){
 			printf("=== converged: %d, conv_rate: %.2f, time: %f, time per iteration: %f, iterations: %.1f\n", res.converged, res.conv_rate, res.elapsed, res.elapsed/it, it);
 		}
-		return res.converged;
 	}
 
 
@@ -308,7 +306,7 @@ namespace Opm
 	}
 
 
-	void cusparseSolverBackend::analyse_matrix(){
+	bool cusparseSolverBackend::analyse_matrix(){
 
 		int d_bufferSize_M, d_bufferSize_L, d_bufferSize_U, d_bufferSize;
 		double t1, t2;
@@ -367,9 +365,7 @@ namespace Opm
 		int structural_zero;
 		cusparseStatus_t status = cusparseXbsrilu02_zeroPivot(cusparseHandle, info_M, &structural_zero);
 		if(CUSPARSE_STATUS_ZERO_PIVOT == status){
-			fprintf(stderr, "ERROR block U(%d,%d) is not invertible\n", structural_zero, structural_zero);
-			fprintf(stderr, "cusparse fails when a block has a 0.0 on its diagonal, these should be replaced in BdaBridge::checkZeroDiagonal()\n");
-			exit(1);
+			return false;
 		}
 
 		// analysis of ilu apply
@@ -388,6 +384,7 @@ namespace Opm
 			printf("cusparseSolver::analyse_matrix(): %f s\n", t2-t1);
 		}
 
+		return true;
 	} // end analyse_matrix()
 
 	bool cusparseSolverBackend::create_preconditioner(){
@@ -407,8 +404,6 @@ namespace Opm
 		// cusparseXbsrilu02_zeroPivot() calls cudaDeviceSynchronize()
 		cusparseStatus_t status = cusparseXbsrilu02_zeroPivot(cusparseHandle, info_M, &structural_zero);
 		if(CUSPARSE_STATUS_ZERO_PIVOT == status){
-			fprintf(stderr, "WARNING block U(%d,%d) is not invertible\n", structural_zero, structural_zero);
-			fprintf(stderr, "cusparse fails when a block has a 0.0 on its diagonal, these should be replaced in BdaBridge::checkZeroDiagonal()\n");
 			return false;
 		}
 
@@ -421,13 +416,11 @@ namespace Opm
 	} // end create_preconditioner()
 
 
-	// return true iff converged
-	bool cusparseSolverBackend::solve_system(BdaResult &res){
+	void cusparseSolverBackend::solve_system(BdaResult &res){
 		// actually solve
-		bool converged = gpu_pbicgstab(res);
+		gpu_pbicgstab(res);
 		cudaStreamSynchronize(stream);
 		cudaCheckLastError("Something went wrong during the GPU solve");
-		return converged;
 	} // end solve_system()
 
 
@@ -454,9 +447,29 @@ namespace Opm
 	} // end post_process()
 
 
-	bool cusparseSolverBackend::isInitialized(){
-		return initialized;
-	}
+	typedef cusparseSolverBackend::cusparseSolverStatus cusparseSolverStatus;
+
+    cusparseSolverStatus cusparseSolverBackend::solve_system(int N, int nnz, int dim, double *vals, int *rows, int *cols, double *b, BdaResult &res){    	
+		if(initialized == false){
+			initialize(N, nnz, dim);
+			copy_system_to_gpu(vals, rows, cols, b);
+		}else{
+			update_system_on_gpu(vals, b);
+		}
+		if(analysis_done == false){
+			if(!analyse_matrix()){
+				return cusparseSolverStatus::CUSPARSE_SOLVER_ANALYSIS_FAILED;
+			}
+		}
+		reset_prec_on_gpu();
+		if(create_preconditioner()){
+			solve_system(res);
+		}else{
+			return cusparseSolverStatus::CUSPARSE_SOLVER_CREATE_PRECONDITIONER_FAILED;
+		}
+		return cusparseSolverStatus::CUSPARSE_SOLVER_SUCCESS;
+    }
+
 
 }
 

opm/simulators/linalg/bda/cusparseSolverBackend.hpp

@@ -58,6 +58,7 @@ private:
     int BLOCK_SIZE;
 
     bool initialized = false;
+    bool analysis_done = false;
 
     // verbosity
     // 0: print nothing during solves, only when initializing
@@ -67,14 +68,8 @@ private:
 
     int verbosity = 0;
 
-public:
 
-    cusparseSolverBackend(int linear_solver_verbosity, int maxit, double tolerance);
-
-    ~cusparseSolverBackend();
-
-    // return true iff converged
-    bool gpu_pbicgstab(BdaResult& res);
+    void gpu_pbicgstab(BdaResult& res);
 
     void initialize(int N, int nnz, int dim);
 
@@ -87,17 +82,29 @@ public:
 
     void reset_prec_on_gpu();
 
-    void analyse_matrix();
+    bool analyse_matrix();
 
     bool create_preconditioner();
 
-    // return true iff converged
-    bool solve_system(BdaResult &res);
+    void solve_system(BdaResult &res);
+
+public:
+
+    enum class cusparseSolverStatus {
+      CUSPARSE_SOLVER_SUCCESS,
+      CUSPARSE_SOLVER_ANALYSIS_FAILED,
+      CUSPARSE_SOLVER_CREATE_PRECONDITIONER_FAILED,
+      CUSPARSE_SOLVER_UNKNOWN_ERROR
+    };
+
+    cusparseSolverBackend(int linear_solver_verbosity, int maxit, double tolerance);
+
+    ~cusparseSolverBackend();
+
+    cusparseSolverStatus solve_system(int N, int nnz, int dim, double *vals, int *rows, int *cols, double *b, BdaResult &res);
 
     void post_process(double *x);
 
-    bool isInitialized();
-
 }; // end class cusparseSolverBackend
 
 }