Ginkgo  Generated from pipelines/1556235455 branch based on develop. Ginkgo version 1.9.0
A numerical linear algebra library targeting many-core architectures
sparsity_csr.hpp
1 // SPDX-FileCopyrightText: 2017 - 2024 The Ginkgo authors
2 //
3 // SPDX-License-Identifier: BSD-3-Clause
4 
5 #ifndef GKO_PUBLIC_CORE_MATRIX_SPARSITY_CSR_HPP_
6 #define GKO_PUBLIC_CORE_MATRIX_SPARSITY_CSR_HPP_
7 
8 
9 #include <vector>
10 
11 #include <ginkgo/core/base/array.hpp>
12 #include <ginkgo/core/base/lin_op.hpp>
13 #include <ginkgo/core/base/polymorphic_object.hpp>
14 
15 
16 namespace gko {
17 namespace matrix {
18 
19 
20 template <typename ValueType, typename IndexType>
21 class Csr;
22 
23 
24 template <typename ValueType>
25 class Dense;
26 
27 
28 template <typename ValueType, typename IndexType>
29 class Fbcsr;
30 
31 
50 template <typename ValueType = default_precision, typename IndexType = int32>
51 class SparsityCsr : public EnableLinOp<SparsityCsr<ValueType, IndexType>>,
52  public ConvertibleTo<Csr<ValueType, IndexType>>,
53  public ConvertibleTo<Dense<ValueType>>,
54  public ReadableFromMatrixData<ValueType, IndexType>,
55  public WritableToMatrixData<ValueType, IndexType>,
56  public Transposable {
57  friend class EnablePolymorphicObject<SparsityCsr, LinOp>;
58  friend class Csr<ValueType, IndexType>;
59  friend class Dense<ValueType>;
60  friend class Fbcsr<ValueType, IndexType>;
61 
62 public:
65  using ConvertibleTo<Csr<ValueType, IndexType>>::convert_to;
66  using ConvertibleTo<Csr<ValueType, IndexType>>::move_to;
67  using ConvertibleTo<Dense<ValueType>>::convert_to;
68  using ConvertibleTo<Dense<ValueType>>::move_to;
70 
71  using value_type = ValueType;
72  using index_type = IndexType;
73  using transposed_type = SparsityCsr<IndexType, ValueType>;
74  using mat_data = matrix_data<ValueType, IndexType>;
75  using device_mat_data = device_matrix_data<ValueType, IndexType>;
76 
77  void convert_to(Csr<ValueType, IndexType>* result) const override;
78 
79  void move_to(Csr<ValueType, IndexType>* result) override;
80 
81  void convert_to(Dense<ValueType>* result) const override;
82 
83  void move_to(Dense<ValueType>* result) override;
84 
85  void read(const mat_data& data) override;
86 
87  void read(const device_mat_data& data) override;
88 
89  void read(device_mat_data&& data) override;
90 
91  void write(mat_data& data) const override;
92 
93  std::unique_ptr<LinOp> transpose() const override;
94 
95  std::unique_ptr<LinOp> conj_transpose() const override;
96 
106  std::unique_ptr<SparsityCsr> to_adjacency_matrix() const;
107 
111  void sort_by_column_index();
112 
113  /*
114  * Tests if all col_idxs are sorted by column index
115  *
116  * @returns True if all col_idxs are sorted.
117  */
118  bool is_sorted_by_column_index() const;
119 
125  index_type* get_col_idxs() noexcept { return col_idxs_.get_data(); }
126 
134  const index_type* get_const_col_idxs() const noexcept
135  {
136  return col_idxs_.get_const_data();
137  }
138 
144  index_type* get_row_ptrs() noexcept { return row_ptrs_.get_data(); }
145 
153  const index_type* get_const_row_ptrs() const noexcept
154  {
155  return row_ptrs_.get_const_data();
156  }
157 
163  value_type* get_value() noexcept { return value_.get_data(); }
164 
172  const value_type* get_const_value() const noexcept
173  {
174  return value_.get_const_data();
175  }
176 
182  size_type get_num_nonzeros() const noexcept { return col_idxs_.get_size(); }
183 
191  static std::unique_ptr<SparsityCsr> create(
192  std::shared_ptr<const Executor> exec, const dim<2>& size = dim<2>{},
193  size_type num_nonzeros = {});
194 
214  static std::unique_ptr<SparsityCsr> create(
215  std::shared_ptr<const Executor> exec, const dim<2>& size,
216  array<index_type> col_idxs, array<index_type> row_ptrs,
217  value_type value = one<ValueType>());
218 
224  template <typename ColIndexType, typename RowPtrType>
225  GKO_DEPRECATED(
226  "explicitly construct the gko::array argument instead of passing "
227  "initializer lists")
228  static std::unique_ptr<SparsityCsr> create(
229  std::shared_ptr<const Executor> exec, const dim<2>& size,
230  std::initializer_list<ColIndexType> col_idxs,
231  std::initializer_list<RowPtrType> row_ptrs,
232  value_type value = one<ValueType>())
233  {
234  return create(exec, size, array<index_type>{exec, std::move(col_idxs)},
235  array<index_type>{exec, std::move(row_ptrs)}, value);
236  }
237 
245  static std::unique_ptr<SparsityCsr> create(
246  std::shared_ptr<const Executor> exec,
247  std::shared_ptr<const LinOp> matrix);
248 
262  static std::unique_ptr<const SparsityCsr> create_const(
263  std::shared_ptr<const Executor> exec, const dim<2>& size,
264  gko::detail::const_array_view<IndexType>&& col_idxs,
265  gko::detail::const_array_view<IndexType>&& row_ptrs,
266  ValueType value = one<ValueType>())
267  {
268  // cast const-ness away, but return a const object afterwards,
269  // so we can ensure that no modifications take place.
270  return std::unique_ptr<const SparsityCsr>(new SparsityCsr{
271  exec, size, gko::detail::array_const_cast(std::move(col_idxs)),
272  gko::detail::array_const_cast(std::move(row_ptrs)), value});
273  }
274 
280 
287 
292  SparsityCsr(const SparsityCsr&);
293 
300 
301 protected:
302  SparsityCsr(std::shared_ptr<const Executor> exec,
303  const dim<2>& size = dim<2>{}, size_type num_nonzeros = {});
304 
305  SparsityCsr(std::shared_ptr<const Executor> exec, const dim<2>& size,
306  array<index_type> col_idxs, array<index_type> row_ptrs,
307  value_type value = one<ValueType>());
308 
309  SparsityCsr(std::shared_ptr<const Executor> exec,
310  std::shared_ptr<const LinOp> matrix);
311 
312  void apply_impl(const LinOp* b, LinOp* x) const override;
313 
314  void apply_impl(const LinOp* alpha, const LinOp* b, const LinOp* beta,
315  LinOp* x) const override;
316 
317 private:
318  array<index_type> col_idxs_;
319  array<index_type> row_ptrs_;
320  array<value_type> value_;
321 };
322 
323 
324 } // namespace matrix
325 } // namespace gko
326 
327 
328 #endif // GKO_PUBLIC_CORE_MATRIX_SPARSITY_CSR_HPP_
gko::EnablePolymorphicAssignment< ConcreteLinOp >::move_to
void move_to(result_type *result) override
Definition: polymorphic_object.hpp:731
gko::EnablePolymorphicAssignment< ConcreteLinOp >::convert_to
void convert_to(result_type *result) const override
Definition: polymorphic_object.hpp:729
gko::matrix::SparsityCsr::get_const_col_idxs
const index_type * get_const_col_idxs() const noexcept
Returns the column indices of the matrix.
Definition: sparsity_csr.hpp:134
gko::ReadableFromMatrixData::read
virtual void read(const matrix_data< ValueType, IndexType > &data)=0
Reads a matrix from a matrix_data structure.
gko::matrix::SparsityCsr
SparsityCsr is a matrix format which stores only the sparsity pattern of a sparse matrix by compressi...
Definition: csr.hpp:40
gko::size_type
std::size_t size_type
Integral type used for allocation quantities.
Definition: types.hpp:86
gko::matrix::SparsityCsr::transpose
std::unique_ptr< LinOp > transpose() const override
Returns a LinOp representing the transpose of the Transposable object.
gko::matrix::SparsityCsr::get_const_row_ptrs
const index_type * get_const_row_ptrs() const noexcept
Returns the row pointers of the matrix.
Definition: sparsity_csr.hpp:153
gko::matrix::SparsityCsr::get_col_idxs
index_type * get_col_idxs() noexcept
Returns the column indices of the matrix.
Definition: sparsity_csr.hpp:125
gko::matrix::SparsityCsr::create
static std::unique_ptr< SparsityCsr > create(std::shared_ptr< const Executor > exec, const dim< 2 > &size=dim< 2 >{}, size_type num_nonzeros={})
Creates an uninitialized SparsityCsr matrix of the specified size.
gko
The Ginkgo namespace.
Definition: abstract_factory.hpp:20
gko::matrix::SparsityCsr::get_value
value_type * get_value() noexcept
Returns the value stored in the matrix.
Definition: sparsity_csr.hpp:163
gko::array< index_type >
gko::matrix::SparsityCsr::read
void read(const mat_data &data) override
Reads a matrix from a matrix_data structure.
gko::dim< 2 >
gko::matrix::SparsityCsr::get_num_nonzeros
size_type get_num_nonzeros() const noexcept
Returns the number of elements explicitly stored in the matrix.
Definition: sparsity_csr.hpp:182
gko::matrix::SparsityCsr::sort_by_column_index
void sort_by_column_index()
Sorts each row by column index.
gko::array::get_data
value_type * get_data() noexcept
Returns a pointer to the block of memory used to store the elements of the array.
Definition: array.hpp:673
gko::matrix::SparsityCsr::create_const
static std::unique_ptr< const SparsityCsr > create_const(std::shared_ptr< const Executor > exec, const dim< 2 > &size, gko::detail::const_array_view< IndexType > &&col_idxs, gko::detail::const_array_view< IndexType > &&row_ptrs, ValueType value=one< ValueType >())
Creates a constant (immutable) SparsityCsr matrix from constant arrays.
Definition: sparsity_csr.hpp:262
gko::matrix::SparsityCsr::SparsityCsr
SparsityCsr(const SparsityCsr &)
Copy-constructs a SparsityCsr matrix.
gko::Executor
The first step in using the Ginkgo library consists of creating an executor.
Definition: executor.hpp:615
gko::array::get_const_data
const value_type * get_const_data() const noexcept
Returns a constant pointer to the block of memory used to store the elements of the array.
Definition: array.hpp:682
gko::matrix::SparsityCsr::get_row_ptrs
index_type * get_row_ptrs() noexcept
Returns the row pointers of the matrix.
Definition: sparsity_csr.hpp:144
gko::matrix::SparsityCsr::operator=
SparsityCsr & operator=(const SparsityCsr &)
Copy-assigns a SparsityCsr matrix.
gko::array::get_size
size_type get_size() const noexcept
Returns the number of elements in the array.
Definition: array.hpp:656
gko::matrix::SparsityCsr::conj_transpose
std::unique_ptr< LinOp > conj_transpose() const override
Returns a LinOp representing the conjugate transpose of the Transposable object.
gko::matrix::SparsityCsr::get_const_value
const value_type * get_const_value() const noexcept
Returns the value stored in the matrix.
Definition: sparsity_csr.hpp:172
gko::matrix::SparsityCsr::to_adjacency_matrix
std::unique_ptr< SparsityCsr > to_adjacency_matrix() const
Transforms the sparsity matrix to an adjacency matrix.
gko::matrix::SparsityCsr::write
void write(mat_data &data) const override
Writes a matrix to a matrix_data structure.
gko::LinOp::LinOp
LinOp(const LinOp &)=default
Copy-constructs a LinOp.
gko::one
constexpr T one()
Returns the multiplicative identity for T.
Definition: math.hpp:652