Use page locked memory in BlockSparseMatrix
If using CUDA_SPARSE for an iterative solve on the GPU,
allocate the values array in BlockSparseMatrix to make copying
to the GPU faster.
Change-Id: I63c1d2512babd74fc275b277ac8c3eabf3ec1144
diff --git a/internal/ceres/block_jacobian_writer.cc b/internal/ceres/block_jacobian_writer.cc
index 29fe688..f74d64d 100644
--- a/internal/ceres/block_jacobian_writer.cc
+++ b/internal/ceres/block_jacobian_writer.cc
@@ -125,7 +125,7 @@
BlockJacobianWriter::BlockJacobianWriter(const Evaluator::Options& options,
Program* program)
- : program_(program) {
+ : options_(options), program_(program) {
CHECK_GE(options.num_eliminate_blocks, 0)
<< "num_eliminate_blocks must be greater than 0.";
@@ -207,7 +207,8 @@
std::sort(row->cells.begin(), row->cells.end(), CellLessThan);
}
- return std::make_unique<BlockSparseMatrix>(bs);
+ return std::make_unique<BlockSparseMatrix>(
+ bs, options_.sparse_linear_algebra_library_type == CUDA_SPARSE);
}
} // namespace ceres::internal
diff --git a/internal/ceres/block_jacobian_writer.h b/internal/ceres/block_jacobian_writer.h
index 7f5c50b..61f69b3 100644
--- a/internal/ceres/block_jacobian_writer.h
+++ b/internal/ceres/block_jacobian_writer.h
@@ -74,6 +74,7 @@
}
private:
+ Evaluator::Options options_;
Program* program_;
// Stores the position of each residual / parameter jacobian.
diff --git a/internal/ceres/block_sparse_matrix.cc b/internal/ceres/block_sparse_matrix.cc
index b3d4efd..ab1d746 100644
--- a/internal/ceres/block_sparse_matrix.cc
+++ b/internal/ceres/block_sparse_matrix.cc
@@ -46,6 +46,10 @@
#include "ceres/triplet_sparse_matrix.h"
#include "glog/logging.h"
+#ifndef CERES_NO_CUDA
+#include "cuda_runtime.h"
+#endif
+
namespace ceres::internal {
namespace {
@@ -171,8 +175,9 @@
} // namespace
BlockSparseMatrix::BlockSparseMatrix(
- CompressedRowBlockStructure* block_structure)
- : num_rows_(0),
+ CompressedRowBlockStructure* block_structure, bool use_page_locked_memory)
+ : use_page_locked_memory_(use_page_locked_memory),
+ num_rows_(0),
num_cols_(0),
num_nonzeros_(0),
block_structure_(block_structure) {
@@ -202,12 +207,15 @@
CHECK_GE(num_nonzeros_, 0);
VLOG(2) << "Allocating values array with " << num_nonzeros_ * sizeof(double)
<< " bytes."; // NOLINT
- values_ = std::make_unique<double[]>(num_nonzeros_);
+
+ values_ = AllocateValues(num_nonzeros_);
max_num_nonzeros_ = num_nonzeros_;
CHECK(values_ != nullptr);
AddTransposeBlockStructure();
}
+BlockSparseMatrix::~BlockSparseMatrix() { FreeValues(values_); }
+
void BlockSparseMatrix::AddTransposeBlockStructure() {
if (transpose_block_structure_ == nullptr) {
transpose_block_structure_ = CreateTranspose(*block_structure_);
@@ -215,11 +223,11 @@
}
void BlockSparseMatrix::SetZero() {
- std::fill(values_.get(), values_.get() + num_nonzeros_, 0.0);
+ std::fill(values_, values_ + num_nonzeros_, 0.0);
}
void BlockSparseMatrix::SetZero(ContextImpl* context, int num_threads) {
- ParallelSetZero(context, num_threads, values_.get(), num_nonzeros_);
+ ParallelSetZero(context, num_threads, values_, num_nonzeros_);
}
void BlockSparseMatrix::RightMultiplyAndAccumulate(const double* x,
@@ -234,7 +242,7 @@
CHECK(x != nullptr);
CHECK(y != nullptr);
- const auto values = values_.get();
+ const auto values = values_;
const auto block_structure = block_structure_.get();
const auto num_row_blocks = block_structure->rows.size();
@@ -282,7 +290,7 @@
}
auto transpose_bs = transpose_block_structure_.get();
- const auto values = values_.get();
+ const auto values = values_;
const int num_col_blocks = transpose_bs->rows.size();
if (!num_col_blocks) {
return;
@@ -330,7 +338,7 @@
int col_block_size = block_structure_->cols[col_block_id].size;
int col_block_pos = block_structure_->cols[col_block_id].position;
MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
- values_.get() + cell.position,
+ values_ + cell.position,
row_block_size,
col_block_size,
x + row_block_pos,
@@ -350,7 +358,7 @@
int col_block_size = block_structure_->cols[col_block_id].size;
int col_block_pos = block_structure_->cols[col_block_id].position;
const MatrixRef m(
- values_.get() + cell.position, row_block_size, col_block_size);
+ values_ + cell.position, row_block_size, col_block_size);
VectorRef(x + col_block_pos, col_block_size) += m.colwise().squaredNorm();
}
}
@@ -370,7 +378,7 @@
ParallelSetZero(context, num_threads, x, num_cols_);
auto transpose_bs = transpose_block_structure_.get();
- const auto values = values_.get();
+ const auto values = values_;
const int num_col_blocks = transpose_bs->rows.size();
ParallelFor(
context,
@@ -401,8 +409,7 @@
int col_block_id = cell.block_id;
int col_block_size = block_structure_->cols[col_block_id].size;
int col_block_pos = block_structure_->cols[col_block_id].position;
- MatrixRef m(
- values_.get() + cell.position, row_block_size, col_block_size);
+ MatrixRef m(values_ + cell.position, row_block_size, col_block_size);
m *= ConstVectorRef(scale + col_block_pos, col_block_size).asDiagonal();
}
}
@@ -420,7 +427,7 @@
CHECK(scale != nullptr);
auto transpose_bs = transpose_block_structure_.get();
- auto values = values_.get();
+ auto values = values_;
const int num_col_blocks = transpose_bs->rows.size();
ParallelFor(
context,
@@ -500,7 +507,7 @@
int col_block_pos = block_structure_->cols[col_block_id].position;
int jac_pos = cell.position;
m.block(row_block_pos, col_block_pos, row_block_size, col_block_size) +=
- MatrixRef(values_.get() + jac_pos, row_block_size, col_block_size);
+ MatrixRef(values_ + jac_pos, row_block_size, col_block_size);
}
}
}
@@ -643,15 +650,15 @@
}
if (num_nonzeros_ > max_num_nonzeros_) {
- auto new_values = std::make_unique<double[]>(num_nonzeros_);
- std::copy_n(values_.get(), old_num_nonzeros, new_values.get());
- values_ = std::move(new_values);
+ double* old_values = values_;
+ values_ = AllocateValues(num_nonzeros_);
+ std::copy_n(old_values, old_num_nonzeros, values_);
max_num_nonzeros_ = num_nonzeros_;
+ FreeValues(old_values);
}
- std::copy(m.values(),
- m.values() + m.num_nonzeros(),
- values_.get() + old_num_nonzeros);
+ std::copy(
+ m.values(), m.values() + m.num_nonzeros(), values_ + old_num_nonzeros);
if (transpose_block_structure_ == nullptr) {
return;
@@ -796,4 +803,39 @@
return transpose;
}
+double* BlockSparseMatrix::AllocateValues(int size) {
+ if (!use_page_locked_memory_) {
+ return new double[size];
+ }
+
+#ifndef CERES_NO_CUDA
+
+ double* values = nullptr;
+ CHECK_EQ(cudaSuccess,
+ cudaHostAlloc(&values, sizeof(double) * size, cudaHostAllocDefault));
+ return values;
+#else
+ LOG(FATAL) << "Page locked memory requested when CUDA is not available. "
+ << "This is a Ceres bug; please contact the developers!";
+ return nullptr;
+#endif
+};
+
+void BlockSparseMatrix::FreeValues(double* values) {
+ if (!use_page_locked_memory_) {
+ delete values;
+ values = nullptr;
+ return;
+ }
+
+#ifndef CERES_NO_CUDA
+ CHECK_EQ(cudaSuccess, cudaFreeHost(values));
+#else
+ LOG(FATAL) << "Page locked memory requested when CUDA is not available. "
+ << "This is a Ceres bug; please contact the developers!";
+#endif
+
+ values = nullptr;
+};
+
} // namespace ceres::internal
diff --git a/internal/ceres/block_sparse_matrix.h b/internal/ceres/block_sparse_matrix.h
index 55f1cc4..0d99e15 100644
--- a/internal/ceres/block_sparse_matrix.h
+++ b/internal/ceres/block_sparse_matrix.h
@@ -65,7 +65,9 @@
//
// TODO(sameeragarwal): Add a function which will validate legal
// CompressedRowBlockStructure objects.
- explicit BlockSparseMatrix(CompressedRowBlockStructure* block_structure);
+ explicit BlockSparseMatrix(CompressedRowBlockStructure* block_structure,
+ bool use_page_locked_memory = false);
+ ~BlockSparseMatrix();
BlockSparseMatrix(const BlockSparseMatrix&) = delete;
void operator=(const BlockSparseMatrix&) = delete;
@@ -114,8 +116,8 @@
int num_rows() const final { return num_rows_; }
int num_cols() const final { return num_cols_; }
int num_nonzeros() const final { return num_nonzeros_; }
- const double* values() const final { return values_.get(); }
- double* mutable_values() final { return values_.get(); }
+ const double* values() const final { return values_; }
+ double* mutable_values() final { return values_; }
// clang-format on
void ToTripletSparseMatrix(TripletSparseMatrix* matrix) const;
@@ -158,11 +160,15 @@
const RandomMatrixOptions& options, std::mt19937& prng);
private:
+ double* AllocateValues(int size);
+ void FreeValues(double* values);
+
+ const bool use_page_locked_memory_;
int num_rows_;
int num_cols_;
int num_nonzeros_;
int max_num_nonzeros_;
- std::unique_ptr<double[]> values_;
+ double* values_;
std::unique_ptr<CompressedRowBlockStructure> block_structure_;
std::unique_ptr<CompressedRowBlockStructure> transpose_block_structure_;
};