| // Ceres Solver - A fast non-linear least squares minimizer | |
| // Copyright 2022 Google Inc. All rights reserved. | |
| // http://ceres-solver.org/ | |
| // | |
| // Redistribution and use in source and binary forms, with or without | |
| // modification, are permitted provided that the following conditions are met: | |
| // | |
| // * Redistributions of source code must retain the above copyright notice, | |
| // this list of conditions and the following disclaimer. | |
| // * Redistributions in binary form must reproduce the above copyright notice, | |
| // this list of conditions and the following disclaimer in the documentation | |
| // and/or other materials provided with the distribution. | |
| // * Neither the name of Google Inc. nor the names of its contributors may be | |
| // used to endorse or promote products derived from this software without | |
| // specific prior written permission. | |
| // | |
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" | |
| // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE | |
| // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE | |
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| // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE | |
| // POSSIBILITY OF SUCH DAMAGE. | |
| // | |
| // Author: sameeragarwal@google.com (Sameer Agarwal) | |
| #include "ceres/dense_cholesky.h" | |
| #include <algorithm> | |
| #include <memory> | |
| #include <string> | |
| #include <vector> | |
| #include "ceres/internal/config.h" | |
| #ifndef CERES_NO_CUDA | |
| #include "ceres/context_impl.h" | |
| #include "cuda_runtime.h" | |
| #include "cusolverDn.h" | |
| #endif // CERES_NO_CUDA | |
| #ifndef CERES_NO_LAPACK | |
| // C interface to the LAPACK Cholesky factorization and triangular solve. | |
| extern "C" void dpotrf_( | |
| const char* uplo, const int* n, double* a, const int* lda, int* info); | |
| extern "C" void dpotrs_(const char* uplo, | |
| const int* n, | |
| const int* nrhs, | |
| const double* a, | |
| const int* lda, | |
| double* b, | |
| const int* ldb, | |
| int* info); | |
| #endif | |
| namespace ceres { | |
| namespace internal { | |
| DenseCholesky::~DenseCholesky() = default; | |
| std::unique_ptr<DenseCholesky> DenseCholesky::Create( | |
| const LinearSolver::Options& options) { | |
| std::unique_ptr<DenseCholesky> dense_cholesky; | |
| switch (options.dense_linear_algebra_library_type) { | |
| case EIGEN: | |
| dense_cholesky = std::make_unique<EigenDenseCholesky>(); | |
| break; | |
| case LAPACK: | |
| #ifndef CERES_NO_LAPACK | |
| dense_cholesky = std::make_unique<LAPACKDenseCholesky>(); | |
| break; | |
| #else | |
| LOG(FATAL) << "Ceres was compiled without support for LAPACK."; | |
| #endif | |
| case CUDA: | |
| #ifndef CERES_NO_CUDA | |
| dense_cholesky = CUDADenseCholesky::Create(options); | |
| break; | |
| #else | |
| LOG(FATAL) << "Ceres was compiled without support for CUDA."; | |
| #endif | |
| default: | |
| LOG(FATAL) << "Unknown dense linear algebra library type : " | |
| << DenseLinearAlgebraLibraryTypeToString( | |
| options.dense_linear_algebra_library_type); | |
| } | |
| return dense_cholesky; | |
| } | |
| LinearSolverTerminationType DenseCholesky::FactorAndSolve( | |
| int num_cols, | |
| double* lhs, | |
| const double* rhs, | |
| double* solution, | |
| std::string* message) { | |
| LinearSolverTerminationType termination_type = | |
| Factorize(num_cols, lhs, message); | |
| if (termination_type == LINEAR_SOLVER_SUCCESS) { | |
| termination_type = Solve(rhs, solution, message); | |
| } | |
| return termination_type; | |
| } | |
| LinearSolverTerminationType EigenDenseCholesky::Factorize( | |
| int num_cols, double* lhs, std::string* message) { | |
| Eigen::Map<Eigen::MatrixXd> m(lhs, num_cols, num_cols); | |
| llt_ = std::make_unique<LLTType>(m); | |
| if (llt_->info() != Eigen::Success) { | |
| *message = "Eigen failure. Unable to perform dense Cholesky factorization."; | |
| return LINEAR_SOLVER_FAILURE; | |
| } | |
| *message = "Success."; | |
| return LINEAR_SOLVER_SUCCESS; | |
| } | |
| LinearSolverTerminationType EigenDenseCholesky::Solve(const double* rhs, | |
| double* solution, | |
| std::string* message) { | |
| if (llt_->info() != Eigen::Success) { | |
| *message = "Eigen failure. Unable to perform dense Cholesky factorization."; | |
| return LINEAR_SOLVER_FAILURE; | |
| } | |
| VectorRef(solution, llt_->cols()) = | |
| llt_->solve(ConstVectorRef(rhs, llt_->cols())); | |
| *message = "Success."; | |
| return LINEAR_SOLVER_SUCCESS; | |
| } | |
| #ifndef CERES_NO_LAPACK | |
| LinearSolverTerminationType LAPACKDenseCholesky::Factorize( | |
| int num_cols, double* lhs, std::string* message) { | |
| lhs_ = lhs; | |
| num_cols_ = num_cols; | |
| const char uplo = 'L'; | |
| int info = 0; | |
| dpotrf_(&uplo, &num_cols_, lhs_, &num_cols_, &info); | |
| if (info < 0) { | |
| termination_type_ = LINEAR_SOLVER_FATAL_ERROR; | |
| LOG(FATAL) << "Congratulations, you found a bug in Ceres. " | |
| << "Please report it. " | |
| << "LAPACK::dpotrf fatal error. " | |
| << "Argument: " << -info << " is invalid."; | |
| } else if (info > 0) { | |
| termination_type_ = LINEAR_SOLVER_FAILURE; | |
| *message = StringPrintf( | |
| "LAPACK::dpotrf numerical failure. " | |
| "The leading minor of order %d is not positive definite.", | |
| info); | |
| } else { | |
| termination_type_ = LINEAR_SOLVER_SUCCESS; | |
| *message = "Success."; | |
| } | |
| return termination_type_; | |
| } | |
| LinearSolverTerminationType LAPACKDenseCholesky::Solve(const double* rhs, | |
| double* solution, | |
| std::string* message) { | |
| const char uplo = 'L'; | |
| const int nrhs = 1; | |
| int info = 0; | |
| std::copy_n(rhs, num_cols_, solution); | |
| dpotrs_( | |
| &uplo, &num_cols_, &nrhs, lhs_, &num_cols_, solution, &num_cols_, &info); | |
| if (info < 0) { | |
| termination_type_ = LINEAR_SOLVER_FATAL_ERROR; | |
| LOG(FATAL) << "Congratulations, you found a bug in Ceres. " | |
| << "Please report it. " | |
| << "LAPACK::dpotrs fatal error. " | |
| << "Argument: " << -info << " is invalid."; | |
| } | |
| *message = "Success"; | |
| termination_type_ = LINEAR_SOLVER_SUCCESS; | |
| return termination_type_; | |
| } | |
| #endif // CERES_NO_LAPACK | |
| #ifndef CERES_NO_CUDA | |
| bool CUDADenseCholesky::Init(ContextImpl* context, std::string* message) { | |
| if (!context->InitCUDA(message)) { | |
| return false; | |
| } | |
| cusolver_handle_ = context->cusolver_handle_; | |
| stream_ = context->stream_; | |
| error_.Reserve(1); | |
| *message = "CUDADenseCholesky::Init Success."; | |
| return true; | |
| } | |
| LinearSolverTerminationType CUDADenseCholesky::Factorize(int num_cols, | |
| double* lhs, | |
| std::string* message) { | |
| factorize_result_ = LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR; | |
| lhs_.Reserve(num_cols * num_cols); | |
| num_cols_ = num_cols; | |
| lhs_.CopyToGpuAsync(lhs, num_cols * num_cols, stream_); | |
| int device_workspace_size = 0; | |
| if (cusolverDnDpotrf_bufferSize(cusolver_handle_, | |
| CUBLAS_FILL_MODE_LOWER, | |
| num_cols, | |
| lhs_.data(), | |
| num_cols, | |
| &device_workspace_size) != | |
| CUSOLVER_STATUS_SUCCESS) { | |
| *message = "cuSolverDN::cusolverDnDpotrf_bufferSize failed."; | |
| return LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR; | |
| } | |
| device_workspace_.Reserve(device_workspace_size); | |
| if (cusolverDnDpotrf(cusolver_handle_, | |
| CUBLAS_FILL_MODE_LOWER, | |
| num_cols, | |
| lhs_.data(), | |
| num_cols, | |
| reinterpret_cast<double*>(device_workspace_.data()), | |
| device_workspace_.size(), | |
| error_.data()) != CUSOLVER_STATUS_SUCCESS) { | |
| *message = "cuSolverDN::cusolverDnDpotrf failed."; | |
| return LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR; | |
| } | |
| if (cudaDeviceSynchronize() != cudaSuccess || | |
| cudaStreamSynchronize(stream_) != cudaSuccess) { | |
| *message = "Cuda device synchronization failed."; | |
| return LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR; | |
| } | |
| int error = 0; | |
| error_.CopyToHost(&error, 1); | |
| if (error < 0) { | |
| LOG(FATAL) << "Congratulations, you found a bug in Ceres - " | |
| << "please report it. " | |
| << "cuSolverDN::cusolverDnXpotrf fatal error. " | |
| << "Argument: " << -error << " is invalid."; | |
| // The following line is unreachable, but return failure just to be | |
| // pedantic, since the compiler does not know that. | |
| return LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR; | |
| } else if (error > 0) { | |
| *message = StringPrintf( | |
| "cuSolverDN::cusolverDnDpotrf numerical failure. " | |
| "The leading minor of order %d is not positive definite.", | |
| error); | |
| factorize_result_ = LinearSolverTerminationType::LINEAR_SOLVER_FAILURE; | |
| return LinearSolverTerminationType::LINEAR_SOLVER_FAILURE; | |
| } | |
| *message = "Success"; | |
| factorize_result_ = LinearSolverTerminationType::LINEAR_SOLVER_SUCCESS; | |
| return LinearSolverTerminationType::LINEAR_SOLVER_SUCCESS; | |
| } | |
| LinearSolverTerminationType CUDADenseCholesky::Solve(const double* rhs, | |
| double* solution, | |
| std::string* message) { | |
| if (factorize_result_ != LinearSolverTerminationType::LINEAR_SOLVER_SUCCESS) { | |
| *message = "Factorize did not complete succesfully previously."; | |
| return factorize_result_; | |
| } | |
| rhs_.CopyToGpuAsync(rhs, num_cols_, stream_); | |
| if (cusolverDnDpotrs(cusolver_handle_, | |
| CUBLAS_FILL_MODE_LOWER, | |
| num_cols_, | |
| 1, | |
| lhs_.data(), | |
| num_cols_, | |
| rhs_.data(), | |
| num_cols_, | |
| error_.data()) != CUSOLVER_STATUS_SUCCESS) { | |
| *message = "cuSolverDN::cusolverDnDpotrs failed."; | |
| return LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR; | |
| } | |
| if (cudaDeviceSynchronize() != cudaSuccess || | |
| cudaStreamSynchronize(stream_) != cudaSuccess) { | |
| *message = "Cuda device synchronization failed."; | |
| return LinearSolverTerminationType::LINEAR_SOLVER_FATAL_ERROR; | |
| } | |
| int error = 0; | |
| error_.CopyToHost(&error, 1); | |
| if (error != 0) { | |
| LOG(FATAL) << "Congratulations, you found a bug in Ceres. " | |
| << "Please report it." | |
| << "cuSolverDN::cusolverDnDpotrs fatal error. " | |
| << "Argument: " << -error << " is invalid."; | |
| } | |
| rhs_.CopyToHost(solution, num_cols_); | |
| *message = "Success"; | |
| return LinearSolverTerminationType::LINEAR_SOLVER_SUCCESS; | |
| } | |
| std::unique_ptr<CUDADenseCholesky> CUDADenseCholesky::Create( | |
| const LinearSolver::Options& options) { | |
| if (options.dense_linear_algebra_library_type != CUDA) { | |
| // The user called the wrong factory method. | |
| return nullptr; | |
| } | |
| auto cuda_dense_cholesky = | |
| std::unique_ptr<CUDADenseCholesky>(new CUDADenseCholesky()); | |
| std::string cuda_error; | |
| if (cuda_dense_cholesky->Init(options.context, &cuda_error)) { | |
| return cuda_dense_cholesky; | |
| } | |
| // Initialization failed, destroy the object (done automatically) and return a | |
| // nullptr. | |
| LOG(ERROR) << "CUDADenseCholesky::Init failed: " << cuda_error; | |
| return nullptr; | |
| } | |
| #endif // CERES_NO_CUDA | |
| } // namespace internal | |
| } // namespace ceres |