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A numerical linear algebra library targeting many-core architectures
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sellp.hpp
1// SPDX-FileCopyrightText: 2017 - 2025 The Ginkgo authors
2//
3// SPDX-License-Identifier: BSD-3-Clause
4
5#ifndef GKO_PUBLIC_CORE_MATRIX_SELLP_HPP_
6#define GKO_PUBLIC_CORE_MATRIX_SELLP_HPP_
7
8
9#include <ginkgo/core/base/array.hpp>
10#include <ginkgo/core/base/lin_op.hpp>
11
12
13namespace gko {
14namespace matrix {
15
16
17constexpr int default_slice_size = 64;
18constexpr int default_stride_factor = 1;
19
20
21template <typename ValueType>
22class Dense;
23
24template <typename ValueType, typename IndexType>
25class Csr;
26
42template <typename ValueType = default_precision, typename IndexType = int32>
43class Sellp
44 : public EnableLinOp<Sellp<ValueType, IndexType>>,
45 public ConvertibleTo<Sellp<next_precision<ValueType>, IndexType>>,
46#if GINKGO_ENABLE_HALF || GINKGO_ENABLE_BFLOAT16
47 public ConvertibleTo<Sellp<next_precision<ValueType, 2>, IndexType>>,
48#endif
49#if GINKGO_ENABLE_HALF && GINKGO_ENABLE_BFLOAT16
50 public ConvertibleTo<Sellp<next_precision<ValueType, 3>, IndexType>>,
51#endif
52 public ConvertibleTo<Dense<ValueType>>,
53 public ConvertibleTo<Csr<ValueType, IndexType>>,
54 public DiagonalExtractable<ValueType>,
55 public ReadableFromMatrixData<ValueType, IndexType>,
56 public WritableToMatrixData<ValueType, IndexType>,
58 remove_complex<Sellp<ValueType, IndexType>>> {
59 friend class EnablePolymorphicObject<Sellp, LinOp>;
60 friend class Dense<ValueType>;
61 friend class Csr<ValueType, IndexType>;
62 friend class Sellp<to_complex<ValueType>, IndexType>;
63
64public:
65 using EnableLinOp<Sellp>::convert_to;
66 using EnableLinOp<Sellp>::move_to;
67 using ConvertibleTo<
68 Sellp<next_precision<ValueType>, IndexType>>::convert_to;
69 using ConvertibleTo<Sellp<next_precision<ValueType>, IndexType>>::move_to;
70 using ConvertibleTo<Dense<ValueType>>::convert_to;
71 using ConvertibleTo<Dense<ValueType>>::move_to;
74 using ReadableFromMatrixData<ValueType, IndexType>::read;
75
76 using value_type = ValueType;
77 using index_type = IndexType;
78 using mat_data = matrix_data<ValueType, IndexType>;
79 using device_mat_data = device_matrix_data<ValueType, IndexType>;
80 using absolute_type = remove_complex<Sellp>;
81
82 friend class Sellp<previous_precision<ValueType>, IndexType>;
83
84 void convert_to(
85 Sellp<next_precision<ValueType>, IndexType>* result) const override;
86
87 void move_to(Sellp<next_precision<ValueType>, IndexType>* result) override;
88
89#if GINKGO_ENABLE_HALF || GINKGO_ENABLE_BFLOAT16
90 friend class Sellp<previous_precision<ValueType, 2>, IndexType>;
91 using ConvertibleTo<
92 Sellp<next_precision<ValueType, 2>, IndexType>>::convert_to;
93 using ConvertibleTo<
94 Sellp<next_precision<ValueType, 2>, IndexType>>::move_to;
95
96 void convert_to(
97 Sellp<next_precision<ValueType, 2>, IndexType>* result) const override;
98
99 void move_to(
100 Sellp<next_precision<ValueType, 2>, IndexType>* result) override;
101#endif
102
103#if GINKGO_ENABLE_HALF && GINKGO_ENABLE_BFLOAT16
104 friend class Sellp<previous_precision<ValueType, 3>, IndexType>;
105 using ConvertibleTo<
106 Sellp<next_precision<ValueType, 3>, IndexType>>::convert_to;
107 using ConvertibleTo<
108 Sellp<next_precision<ValueType, 3>, IndexType>>::move_to;
109
110 void convert_to(
111 Sellp<next_precision<ValueType, 3>, IndexType>* result) const override;
112
113 void move_to(
114 Sellp<next_precision<ValueType, 3>, IndexType>* result) override;
115#endif
116
117 void convert_to(Dense<ValueType>* other) const override;
118
119 void move_to(Dense<ValueType>* other) override;
120
121 void convert_to(Csr<ValueType, IndexType>* other) const override;
122
123 void move_to(Csr<ValueType, IndexType>* other) override;
124
125 void read(const mat_data& data) override;
126
127 void read(const device_mat_data& data) override;
128
129 void read(device_mat_data&& data) override;
130
131 void write(mat_data& data) const override;
132
133 std::unique_ptr<Diagonal<ValueType>> extract_diagonal() const override;
134
135 std::unique_ptr<absolute_type> compute_absolute() const override;
136
138
144 value_type* get_values() noexcept { return values_.get_data(); }
145
153 const value_type* get_const_values() const noexcept
154 {
155 return values_.get_const_data();
156 }
157
163 index_type* get_col_idxs() noexcept { return col_idxs_.get_data(); }
164
172 const index_type* get_const_col_idxs() const noexcept
173 {
174 return col_idxs_.get_const_data();
175 }
176
183 {
184 return slice_lengths_.get_data();
185 }
186
194 const size_type* get_const_slice_lengths() const noexcept
195 {
196 return slice_lengths_.get_const_data();
197 }
198
204 size_type* get_slice_sets() noexcept { return slice_sets_.get_data(); }
205
213 const size_type* get_const_slice_sets() const noexcept
214 {
215 return slice_sets_.get_const_data();
216 }
217
223 size_type get_slice_size() const noexcept { return slice_size_; }
224
230 size_type get_stride_factor() const noexcept { return stride_factor_; }
231
237 size_type get_total_cols() const noexcept
238 {
239 return values_.get_size() / slice_size_;
240 }
241
248 {
249 return values_.get_size();
250 }
251
264 value_type& val_at(size_type row, size_type slice_set,
265 size_type idx) noexcept
266 {
267 return values_.get_data()[this->linearize_index(row, slice_set, idx)];
268 }
269
273 value_type val_at(size_type row, size_type slice_set,
274 size_type idx) const noexcept
275 {
276 return values_
277 .get_const_data()[this->linearize_index(row, slice_set, idx)];
278 }
279
292 index_type& col_at(size_type row, size_type slice_set,
293 size_type idx) noexcept
294 {
295 return this->get_col_idxs()[this->linearize_index(row, slice_set, idx)];
296 }
297
301 index_type col_at(size_type row, size_type slice_set,
302 size_type idx) const noexcept
303 {
304 return this
305 ->get_const_col_idxs()[this->linearize_index(row, slice_set, idx)];
306 }
307
318 static std::unique_ptr<Sellp> create(std::shared_ptr<const Executor> exec,
319 const dim<2>& size = {},
320 size_type total_cols = 0);
321
334 static std::unique_ptr<Sellp> create(std::shared_ptr<const Executor> exec,
335 const dim<2>& size,
336 size_type slice_size,
337 size_type stride_factor,
338 size_type total_cols);
339
345
352
357 Sellp(const Sellp&);
358
365
366protected:
367 Sellp(std::shared_ptr<const Executor> exec, const dim<2>& size = {},
368 size_type total_cols = {});
369
370 Sellp(std::shared_ptr<const Executor> exec, const dim<2>& size,
371 size_type slice_size, size_type stride_factor, size_type total_cols);
372
373 void apply_impl(const LinOp* b, LinOp* x) const override;
374
375 void apply_impl(const LinOp* alpha, const LinOp* b, const LinOp* beta,
376 LinOp* x) const override;
377
378 size_type linearize_index(size_type row, size_type slice_set,
379 size_type col) const noexcept
380 {
381 return (slice_set + col) * slice_size_ + row;
382 }
383
384private:
385 array<value_type> values_;
386 array<index_type> col_idxs_;
387 array<size_type> slice_lengths_;
388 array<size_type> slice_sets_;
389 size_type slice_size_;
390 size_type stride_factor_;
391};
392
393
394} // namespace matrix
395} // namespace gko
396
397
398#endif // GKO_PUBLIC_CORE_MATRIX_SELLP_HPP_
ConvertibleTo interface is used to mark that the implementer can be converted to the object of Result...
Definition polymorphic_object.hpp:479
The diagonal of a LinOp implementing this interface can be extracted.
Definition lin_op.hpp:743
The EnableAbsoluteComputation mixin provides the default implementations of compute_absolute_linop an...
Definition lin_op.hpp:794
The EnableLinOp mixin can be used to provide sensible default implementations of the majority of the ...
Definition lin_op.hpp:879
This mixin inherits from (a subclass of) PolymorphicObject and provides a base implementation of a ne...
Definition polymorphic_object.hpp:668
Definition lin_op.hpp:117
A LinOp implementing this interface can read its data from a matrix_data structure.
Definition lin_op.hpp:605
A LinOp implementing this interface can write its data to a matrix_data structure.
Definition lin_op.hpp:660
This type is a device-side equivalent to matrix_data.
Definition device_matrix_data.hpp:36
CSR is a matrix format which stores only the nonzero coefficients by compressing each row of the matr...
Definition csr.hpp:126
Dense is a matrix format which explicitly stores all values of the matrix.
Definition dense.hpp:120
size_type get_slice_size() const noexcept
Returns the size of a slice.
Definition sellp.hpp:223
value_type & val_at(size_type row, size_type slice_set, size_type idx) noexcept
Returns the idx-th non-zero element of the row-th row with slice_set slice set.
Definition sellp.hpp:264
static std::unique_ptr< Sellp > create(std::shared_ptr< const Executor > exec, const dim< 2 > &size, size_type slice_size, size_type stride_factor, size_type total_cols)
Creates an uninitialized Sellp matrix of the specified size.
index_type & col_at(size_type row, size_type slice_set, size_type idx) noexcept
Returns the idx-th column index of the row-th row with slice_set slice set.
Definition sellp.hpp:292
Sellp(const Sellp &)
Copy-assigns a Sellp matrix.
std::unique_ptr< absolute_type > compute_absolute() const override
Gets the AbsoluteLinOp.
value_type * get_values() noexcept
Returns the values of the matrix.
Definition sellp.hpp:144
Sellp & operator=(Sellp &&)
Move-assigns a Sellp matrix.
size_type get_stride_factor() const noexcept
Returns the stride factor(t) of SELL-P.
Definition sellp.hpp:230
const size_type * get_const_slice_sets() const noexcept
Returns the offsets of slices.
Definition sellp.hpp:213
index_type * get_col_idxs() noexcept
Returns the column indexes of the matrix.
Definition sellp.hpp:163
size_type get_total_cols() const noexcept
Returns the total column number.
Definition sellp.hpp:237
index_type col_at(size_type row, size_type slice_set, size_type idx) const noexcept
Returns the idx-th column index of the row-th row with slice_set slice set.
Definition sellp.hpp:301
size_type * get_slice_lengths() noexcept
Returns the lengths(columns) of slices.
Definition sellp.hpp:182
Sellp & operator=(const Sellp &)
Copy-assigns a Sellp matrix.
void compute_absolute_inplace() override
Compute absolute inplace on each element.
static std::unique_ptr< Sellp > create(std::shared_ptr< const Executor > exec, const dim< 2 > &size={}, size_type total_cols=0)
Creates an uninitialized Sellp matrix of the specified size.
size_type * get_slice_sets() noexcept
Returns the offsets of slices.
Definition sellp.hpp:204
size_type get_num_stored_elements() const noexcept
Returns the number of elements explicitly stored in the matrix.
Definition sellp.hpp:247
value_type val_at(size_type row, size_type slice_set, size_type idx) const noexcept
Returns the idx-th non-zero element of the row-th row with slice_set slice set.
Definition sellp.hpp:273
const index_type * get_const_col_idxs() const noexcept
Returns the column indexes of the matrix.
Definition sellp.hpp:172
Sellp(Sellp &&)
Move-assigns a Sellp matrix.
std::unique_ptr< Diagonal< ValueType > > extract_diagonal() const override
Extracts the diagonal entries of the matrix into a vector.
const size_type * get_const_slice_lengths() const noexcept
Returns the lengths(columns) of slices.
Definition sellp.hpp:194
const value_type * get_const_values() const noexcept
Returns the values of the matrix.
Definition sellp.hpp:153
The matrix namespace.
Definition dense_cache.hpp:24
The Ginkgo namespace.
Definition abstract_factory.hpp:20
typename detail::remove_complex_s< T >::type remove_complex
Obtain the type which removed the complex of complex/scalar type or the template parameter of class b...
Definition math.hpp:264
typename detail::to_complex_s< T >::type to_complex
Obtain the type which adds the complex of complex/scalar type or the template parameter of class by a...
Definition math.hpp:283
std::size_t size_type
Integral type used for allocation quantities.
Definition types.hpp:90
typename detail::find_precision_impl< T, -step >::type previous_precision
Obtains the previous move type of T in the singly-linked precision corresponding bfloat16/half.
Definition math.hpp:473
typename detail::find_precision_impl< T, step >::type next_precision
Obtains the next move type of T in the singly-linked precision corresponding bfloat16/half.
Definition math.hpp:466
A type representing the dimensions of a multidimensional object.
Definition dim.hpp:26
This structure is used as an intermediate data type to store a sparse matrix.
Definition matrix_data.hpp:126