| // Ceres Solver - A fast non-linear least squares minimizer | |
| // Copyright 2023 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 | |
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| // 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: joydeepb@cs.utexas.edu (Joydeep Biswas) | |
| // | |
| // A simple CUDA vector class. | |
| // This include must come before any #ifndef check on Ceres compile options. | |
| // clang-format off | |
| #include "ceres/internal/config.h" | |
| // clang-format on | |
| #include <math.h> | |
| #include "absl/log/check.h" | |
| #include "ceres/context_impl.h" | |
| #include "ceres/internal/export.h" | |
| #include "ceres/types.h" | |
| #ifndef CERES_NO_CUDA | |
| #include "ceres/cuda_buffer.h" | |
| #include "ceres/cuda_kernels_vector_ops.h" | |
| #include "ceres/cuda_vector.h" | |
| #include "cublas_v2.h" | |
| namespace ceres::internal { | |
| CudaVector::CudaVector(ContextImpl* context, int size) | |
| : context_(context), data_(context, size) { | |
| DCHECK_NE(context, nullptr); | |
| DCHECK(context->IsCudaInitialized()); | |
| Resize(size); | |
| } | |
| CudaVector::CudaVector(CudaVector&& other) | |
| : num_rows_(other.num_rows_), | |
| context_(other.context_), | |
| data_(std::move(other.data_)), | |
| descr_(other.descr_) { | |
| other.num_rows_ = 0; | |
| other.descr_ = nullptr; | |
| } | |
| CudaVector& CudaVector::operator=(const CudaVector& other) { | |
| if (this != &other) { | |
| Resize(other.num_rows()); | |
| data_.CopyFromGPUArray(other.data_.data(), num_rows_); | |
| } | |
| return *this; | |
| } | |
| void CudaVector::DestroyDescriptor() { | |
| if (descr_ != nullptr) { | |
| CHECK_EQ(cusparseDestroyDnVec(descr_), CUSPARSE_STATUS_SUCCESS); | |
| descr_ = nullptr; | |
| } | |
| } | |
| CudaVector::~CudaVector() { DestroyDescriptor(); } | |
| void CudaVector::Resize(int size) { | |
| data_.Reserve(size); | |
| num_rows_ = size; | |
| DestroyDescriptor(); | |
| CHECK_EQ(cusparseCreateDnVec(&descr_, num_rows_, data_.data(), CUDA_R_64F), | |
| CUSPARSE_STATUS_SUCCESS); | |
| } | |
| double CudaVector::Dot(const CudaVector& x) const { | |
| double result = 0; | |
| CHECK_EQ(cublasDdot(context_->cublas_handle_, | |
| num_rows_, | |
| data_.data(), | |
| 1, | |
| x.data(), | |
| 1, | |
| &result), | |
| CUBLAS_STATUS_SUCCESS) | |
| << "CuBLAS cublasDdot failed."; | |
| return result; | |
| } | |
| double CudaVector::Norm() const { | |
| double result = 0; | |
| CHECK_EQ(cublasDnrm2( | |
| context_->cublas_handle_, num_rows_, data_.data(), 1, &result), | |
| CUBLAS_STATUS_SUCCESS) | |
| << "CuBLAS cublasDnrm2 failed."; | |
| return result; | |
| } | |
| void CudaVector::CopyFromCpu(const double* x) { | |
| data_.CopyFromCpu(x, num_rows_); | |
| } | |
| void CudaVector::CopyFromCpu(const Vector& x) { | |
| if (x.rows() != num_rows_) { | |
| Resize(x.rows()); | |
| } | |
| CopyFromCpu(x.data()); | |
| } | |
| void CudaVector::CopyTo(Vector* x) const { | |
| CHECK(x != nullptr); | |
| x->resize(num_rows_); | |
| data_.CopyToCpu(x->data(), num_rows_); | |
| } | |
| void CudaVector::CopyTo(double* x) const { | |
| CHECK(x != nullptr); | |
| data_.CopyToCpu(x, num_rows_); | |
| } | |
| void CudaVector::SetZero() { | |
| // Allow empty vector to be zeroed | |
| if (num_rows_ == 0) return; | |
| CHECK(data_.data() != nullptr); | |
| CudaSetZeroFP64(data_.data(), num_rows_, context_->DefaultStream()); | |
| } | |
| void CudaVector::Axpby(double a, const CudaVector& x, double b) { | |
| if (&x == this) { | |
| Scale(a + b); | |
| return; | |
| } | |
| CHECK_EQ(num_rows_, x.num_rows_); | |
| if (b != 1.0) { | |
| // First scale y by b. | |
| CHECK_EQ( | |
| cublasDscal(context_->cublas_handle_, num_rows_, &b, data_.data(), 1), | |
| CUBLAS_STATUS_SUCCESS) | |
| << "CuBLAS cublasDscal failed."; | |
| } | |
| // Then add a * x to y. | |
| CHECK_EQ(cublasDaxpy(context_->cublas_handle_, | |
| num_rows_, | |
| &a, | |
| x.data(), | |
| 1, | |
| data_.data(), | |
| 1), | |
| CUBLAS_STATUS_SUCCESS) | |
| << "CuBLAS cublasDaxpy failed."; | |
| } | |
| void CudaVector::DtDxpy(const CudaVector& D, const CudaVector& x) { | |
| CudaDtDxpy( | |
| data_.data(), D.data(), x.data(), num_rows_, context_->DefaultStream()); | |
| } | |
| void CudaVector::Scale(double s) { | |
| CHECK_EQ( | |
| cublasDscal(context_->cublas_handle_, num_rows_, &s, data_.data(), 1), | |
| CUBLAS_STATUS_SUCCESS) | |
| << "CuBLAS cublasDscal failed."; | |
| } | |
| } // namespace ceres::internal | |
| #endif // CERES_NO_CUDA |