| // 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 |
| // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE |
| // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR |
| // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF |
| // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS |
| // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN |
| // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) |
| // 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> |
| |
| #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 |
