ViennaCL - The Vienna Computing Library  1.7.1
Free open-source GPU-accelerated linear algebra and solver library.
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blas2_host.cpp
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1 /* =========================================================================
2  Copyright (c) 2010-2014, Institute for Microelectronics,
3  Institute for Analysis and Scientific Computing,
4  TU Wien.
5  Portions of this software are copyright by UChicago Argonne, LLC.
6 
7  -----------------
8  ViennaCL - The Vienna Computing Library
9  -----------------
10 
11  Project Head: Karl Rupp rupp@iue.tuwien.ac.at
12 
13  (A list of authors and contributors can be found in the PDF manual)
14 
15  License: MIT (X11), see file LICENSE in the base directory
16 ============================================================================= */
17 
18 // include necessary system headers
19 #include <iostream>
20 
21 #include "viennacl.hpp"
22 #include "viennacl_private.hpp"
23 
24 //include basic scalar and vector types of ViennaCL
25 #include "viennacl/scalar.hpp"
26 #include "viennacl/vector.hpp"
27 
28 #include "viennacl/vector.hpp"
29 #include "viennacl/matrix.hpp"
30 #include "viennacl/linalg/direct_solve.hpp"
31 #include "viennacl/linalg/prod.hpp"
32 
33 
34 // xGEMV
35 
36 VIENNACL_EXPORTED_FUNCTION ViennaCLStatus ViennaCLHostSgemv(ViennaCLBackend /*backend*/,
37  ViennaCLOrder order, ViennaCLTranspose transA,
38  ViennaCLInt m, ViennaCLInt n, float alpha, float *A, ViennaCLInt offA_row, ViennaCLInt offA_col, ViennaCLInt incA_row, ViennaCLInt incA_col, ViennaCLInt lda,
39  float *x, ViennaCLInt offx, ViennaCLInt incx,
40  float beta,
41  float *y, ViennaCLInt offy, ViennaCLInt incy)
42 {
43  typedef viennacl::vector_base<float>::size_type size_type;
44  typedef viennacl::vector_base<float>::size_type difference_type;
45 
46  viennacl::vector_base<float> v1(x, viennacl::MAIN_MEMORY, size_type(n), size_type(offx), difference_type(incx));
47  viennacl::vector_base<float> v2(y, viennacl::MAIN_MEMORY, size_type(m), size_type(offy), difference_type(incy));
48  viennacl::matrix_base<float> mat(A, viennacl::MAIN_MEMORY,
49  size_type(m), size_type(offA_row), difference_type(incA_row), size_type(m),
50  size_type(n), size_type(offA_col), difference_type(incA_col), size_type(lda), order == ViennaCLRowMajor);
51  v2 *= beta;
52  if (transA == ViennaCLTrans)
53  v2 += alpha * viennacl::linalg::prod(viennacl::trans(mat), v1);
54  else
55  v2 += alpha * viennacl::linalg::prod(mat, v1);
56 
57  return ViennaCLSuccess;
58 }
59 
60 VIENNACL_EXPORTED_FUNCTION ViennaCLStatus ViennaCLHostDgemv(ViennaCLBackend /*backend*/,
61  ViennaCLOrder order, ViennaCLTranspose transA,
62  ViennaCLInt m, ViennaCLInt n, double alpha, double *A, ViennaCLInt offA_row, ViennaCLInt offA_col, ViennaCLInt incA_row, ViennaCLInt incA_col, ViennaCLInt lda,
63  double *x, ViennaCLInt offx, ViennaCLInt incx,
64  double beta,
65  double *y, ViennaCLInt offy, ViennaCLInt incy)
66 {
67  typedef viennacl::vector_base<double>::size_type size_type;
68  typedef viennacl::vector_base<double>::size_type difference_type;
69 
70  viennacl::vector_base<double> v1(x, viennacl::MAIN_MEMORY, size_type(n), size_type(offx), difference_type(incx));
71  viennacl::vector_base<double> v2(y, viennacl::MAIN_MEMORY, size_type(m), size_type(offy), difference_type(incy));
72  viennacl::matrix_base<double> mat(A, viennacl::MAIN_MEMORY,
73  size_type(m), size_type(offA_row), difference_type(incA_row), size_type(m),
74  size_type(n), size_type(offA_col), difference_type(incA_col), size_type(lda), order == ViennaCLRowMajor);
75  v2 *= beta;
76  if (transA == ViennaCLTrans)
77  v2 += alpha * viennacl::linalg::prod(viennacl::trans(mat), v1);
78  else
79  v2 += alpha * viennacl::linalg::prod(mat, v1);
80 
81  return ViennaCLSuccess;
82 }
83 
84 
85 
86 // xTRSV
87 
88 VIENNACL_EXPORTED_FUNCTION ViennaCLStatus ViennaCLHostStrsv(ViennaCLBackend /*backend*/,
89  ViennaCLUplo uplo, ViennaCLOrder order, ViennaCLTranspose transA, ViennaCLDiag diag,
90  ViennaCLInt n, float *A, ViennaCLInt offA_row, ViennaCLInt offA_col, ViennaCLInt incA_row, ViennaCLInt incA_col, ViennaCLInt lda,
91  float *x, ViennaCLInt offx, ViennaCLInt incx)
92 {
93  typedef viennacl::vector_base<float>::size_type size_type;
94  typedef viennacl::vector_base<float>::size_type difference_type;
95 
96  viennacl::vector_base<float> v(x, viennacl::MAIN_MEMORY, size_type(n), size_type(offx), difference_type(incx));
97  viennacl::matrix_base<float> mat(A, viennacl::MAIN_MEMORY,
98  size_type(n), size_type(offA_row), difference_type(incA_row), size_type(n),
99  size_type(n), size_type(offA_col), difference_type(incA_col), size_type(lda), order == ViennaCLRowMajor);
100  if (transA == ViennaCLTrans)
101  {
102  if (uplo == ViennaCLUpper)
103  if (diag == ViennaCLUnit)
104  viennacl::linalg::inplace_solve(viennacl::trans(mat), v, viennacl::linalg::unit_upper_tag());
105  else
106  viennacl::linalg::inplace_solve(viennacl::trans(mat), v, viennacl::linalg::upper_tag());
107  else
108  if (diag == ViennaCLUnit)
109  viennacl::linalg::inplace_solve(viennacl::trans(mat), v, viennacl::linalg::unit_lower_tag());
110  else
111  viennacl::linalg::inplace_solve(viennacl::trans(mat), v, viennacl::linalg::lower_tag());
112  }
113  else
114  {
115  if (uplo == ViennaCLUpper)
116  if (diag == ViennaCLUnit)
117  viennacl::linalg::inplace_solve(mat, v, viennacl::linalg::unit_upper_tag());
118  else
119  viennacl::linalg::inplace_solve(mat, v, viennacl::linalg::upper_tag());
120  else
121  if (diag == ViennaCLUnit)
122  viennacl::linalg::inplace_solve(mat, v, viennacl::linalg::unit_lower_tag());
123  else
124  viennacl::linalg::inplace_solve(mat, v, viennacl::linalg::lower_tag());
125  }
126 
127  return ViennaCLSuccess;
128 }
129 
130 VIENNACL_EXPORTED_FUNCTION ViennaCLStatus ViennaCLHostDtrsv(ViennaCLBackend /*backend*/,
131  ViennaCLUplo uplo, ViennaCLOrder order, ViennaCLTranspose transA, ViennaCLDiag diag,
132  ViennaCLInt n, double *A, ViennaCLInt offA_row, ViennaCLInt offA_col, ViennaCLInt incA_row, ViennaCLInt incA_col, ViennaCLInt lda,
133  double *x, ViennaCLInt offx, ViennaCLInt incx)
134 {
135  typedef viennacl::vector_base<double>::size_type size_type;
136  typedef viennacl::vector_base<double>::size_type difference_type;
137 
138  viennacl::vector_base<double> v(x, viennacl::MAIN_MEMORY, size_type(n), size_type(offx), difference_type(incx));
139  viennacl::matrix_base<double> mat(A, viennacl::MAIN_MEMORY,
140  size_type(n), size_type(offA_row), difference_type(incA_row), size_type(n),
141  size_type(n), size_type(offA_col), difference_type(incA_col), size_type(lda), order == ViennaCLRowMajor);
142  if (transA == ViennaCLTrans)
143  {
144  if (uplo == ViennaCLUpper)
145  if (diag == ViennaCLUnit)
146  viennacl::linalg::inplace_solve(viennacl::trans(mat), v, viennacl::linalg::unit_upper_tag());
147  else
148  viennacl::linalg::inplace_solve(viennacl::trans(mat), v, viennacl::linalg::upper_tag());
149  else
150  if (diag == ViennaCLUnit)
151  viennacl::linalg::inplace_solve(viennacl::trans(mat), v, viennacl::linalg::unit_lower_tag());
152  else
153  viennacl::linalg::inplace_solve(viennacl::trans(mat), v, viennacl::linalg::lower_tag());
154  }
155  else
156  {
157  if (uplo == ViennaCLUpper)
158  if (diag == ViennaCLUnit)
159  viennacl::linalg::inplace_solve(mat, v, viennacl::linalg::unit_upper_tag());
160  else
161  viennacl::linalg::inplace_solve(mat, v, viennacl::linalg::upper_tag());
162  else
163  if (diag == ViennaCLUnit)
164  viennacl::linalg::inplace_solve(mat, v, viennacl::linalg::unit_lower_tag());
165  else
166  viennacl::linalg::inplace_solve(mat, v, viennacl::linalg::lower_tag());
167  }
168 
169  return ViennaCLSuccess;
170 }
171 
172 
173 
174 // xGER
175 
176 VIENNACL_EXPORTED_FUNCTION ViennaCLStatus ViennaCLHostSger(ViennaCLBackend /*backend*/,
177  ViennaCLOrder order,
178  ViennaCLInt m, ViennaCLInt n,
179  float alpha,
180  float *x, ViennaCLInt offx, ViennaCLInt incx,
181  float *y, ViennaCLInt offy, ViennaCLInt incy,
182  float *A, ViennaCLInt offA_row, ViennaCLInt offA_col, ViennaCLInt incA_row, ViennaCLInt incA_col, ViennaCLInt lda)
183 {
184  typedef viennacl::vector_base<float>::size_type size_type;
185  typedef viennacl::vector_base<float>::size_type difference_type;
186 
187  viennacl::vector_base<float> v1(x, viennacl::MAIN_MEMORY, size_type(n), size_type(offx), difference_type(incx));
188  viennacl::vector_base<float> v2(y, viennacl::MAIN_MEMORY, size_type(m), size_type(offy), difference_type(incy));
189  viennacl::matrix_base<float> mat(A, viennacl::MAIN_MEMORY,
190  size_type(m), size_type(offA_row), difference_type(incA_row), size_type(m),
191  size_type(n), size_type(offA_col), difference_type(incA_col), size_type(lda), order == ViennaCLRowMajor);
192 
193  mat += alpha * viennacl::linalg::outer_prod(v1, v2);
194 
195  return ViennaCLSuccess;
196 }
197 
198 VIENNACL_EXPORTED_FUNCTION ViennaCLStatus ViennaCLHostDger(ViennaCLBackend /*backend*/,
199  ViennaCLOrder order,
200  ViennaCLInt m, ViennaCLInt n,
201  double alpha,
202  double *x, ViennaCLInt offx, ViennaCLInt incx,
203  double *y, ViennaCLInt offy, ViennaCLInt incy,
204  double *A, ViennaCLInt offA_row, ViennaCLInt offA_col, ViennaCLInt incA_row, ViennaCLInt incA_col, ViennaCLInt lda)
205 {
206  typedef viennacl::vector_base<double>::size_type size_type;
207  typedef viennacl::vector_base<double>::size_type difference_type;
208 
209  viennacl::vector_base<double> v1(x, viennacl::MAIN_MEMORY, size_type(n), size_type(offx), difference_type(incx));
210  viennacl::vector_base<double> v2(y, viennacl::MAIN_MEMORY, size_type(m), size_type(offy), difference_type(incy));
211  viennacl::matrix_base<double> mat(A, viennacl::MAIN_MEMORY,
212  size_type(m), size_type(offA_row), difference_type(incA_row), size_type(m),
213  size_type(n), size_type(offA_col), difference_type(incA_col), size_type(lda), order == ViennaCLRowMajor);
214 
215  mat += alpha * viennacl::linalg::outer_prod(v1, v2);
216 
217  return ViennaCLSuccess;
218 }
219 
viennacl::linalg::inplace_solve
void inplace_solve(const matrix_base< NumericT > &A, matrix_base< NumericT > &B, SolverTagT)
Direct inplace solver for triangular systems with multiple right hand sides, i.e. A \ B (MATLAB notat...
Definition: direct_solve.hpp:217
ViennaCLTranspose
ViennaCLTranspose
Definition: viennacl.hpp:68
viennacl::trans
viennacl::enable_if< viennacl::is_any_sparse_matrix< M1 >::value, matrix_expression< const M1, const M1, op_trans > >::type trans(const M1 &mat)
Returns an expression template class representing a transposed matrix.
Definition: sparse_matrix_operations.hpp:376
ViennaCLBackend_impl
Generic backend for CUDA, OpenCL, host-based stuff.
Definition: viennacl_private.hpp:54
ViennaCLHostSger
VIENNACL_EXPORTED_FUNCTION ViennaCLStatus ViennaCLHostSger(ViennaCLBackend, ViennaCLOrder order, ViennaCLInt m, ViennaCLInt n, float alpha, float *x, ViennaCLInt offx, ViennaCLInt incx, float *y, ViennaCLInt offy, ViennaCLInt incy, float *A, ViennaCLInt offA_row, ViennaCLInt offA_col, ViennaCLInt incA_row, ViennaCLInt incA_col, ViennaCLInt lda)
Definition: blas2_host.cpp:176
prod.hpp
Generic interface for matrix-vector and matrix-matrix products. See viennacl/linalg/vector_operations...
matrix.hpp
Implementation of the dense matrix class.
viennacl::linalg::lower_tag
A tag class representing a lower triangular matrix.
Definition: forwards.h:849
viennacl::matrix_base< float >
ViennaCLDiag
ViennaCLDiag
Definition: viennacl.hpp:82
ViennaCLStatus
ViennaCLStatus
Definition: viennacl.hpp:97
ViennaCLHostSgemv
VIENNACL_EXPORTED_FUNCTION ViennaCLStatus ViennaCLHostSgemv(ViennaCLBackend, ViennaCLOrder order, ViennaCLTranspose transA, ViennaCLInt m, ViennaCLInt n, float alpha, float *A, ViennaCLInt offA_row, ViennaCLInt offA_col, ViennaCLInt incA_row, ViennaCLInt incA_col, ViennaCLInt lda, float *x, ViennaCLInt offx, ViennaCLInt incx, float beta, float *y, ViennaCLInt offy, ViennaCLInt incy)
Definition: blas2_host.cpp:36
ViennaCLMatrix_impl::order
ViennaCLOrder order
Definition: viennacl_private.hpp:117
VIENNACL_EXPORTED_FUNCTION
#define VIENNACL_EXPORTED_FUNCTION
Definition: viennacl.hpp:40
v1
viennacl::vector< float > v1
Definition: global_variables.cpp:60
ViennaCLHostDtrsv
VIENNACL_EXPORTED_FUNCTION ViennaCLStatus ViennaCLHostDtrsv(ViennaCLBackend, ViennaCLUplo uplo, ViennaCLOrder order, ViennaCLTranspose transA, ViennaCLDiag diag, ViennaCLInt n, double *A, ViennaCLInt offA_row, ViennaCLInt offA_col, ViennaCLInt incA_row, ViennaCLInt incA_col, ViennaCLInt lda, double *x, ViennaCLInt offx, ViennaCLInt incx)
Definition: blas2_host.cpp:130
viennacl::linalg::prod
VectorT prod(std::vector< std::vector< T, A1 >, A2 > const &matrix, VectorT const &vector)
Definition: prod.hpp:102
viennacl_private.hpp
ViennaCLUplo
ViennaCLUplo
Definition: viennacl.hpp:75
viennacl::linalg::upper_tag
A tag class representing an upper triangular matrix.
Definition: forwards.h:854
ViennaCLOrder
ViennaCLOrder
Definition: viennacl.hpp:61
ViennaCLHostDger
VIENNACL_EXPORTED_FUNCTION ViennaCLStatus ViennaCLHostDger(ViennaCLBackend, ViennaCLOrder order, ViennaCLInt m, ViennaCLInt n, double alpha, double *x, ViennaCLInt offx, ViennaCLInt incx, double *y, ViennaCLInt offy, ViennaCLInt incy, double *A, ViennaCLInt offA_row, ViennaCLInt offA_col, ViennaCLInt incA_row, ViennaCLInt incA_col, ViennaCLInt lda)
Definition: blas2_host.cpp:198
viennacl::vector_base< float >
ViennaCLInt
int ViennaCLInt
Definition: viennacl.hpp:48
viennacl::diag
vector_expression< const matrix_base< NumericT >, const int, op_matrix_diag > diag(const matrix_base< NumericT > &A, int k=0)
Definition: matrix.hpp:895
ViennaCLHostStrsv
VIENNACL_EXPORTED_FUNCTION ViennaCLStatus ViennaCLHostStrsv(ViennaCLBackend, ViennaCLUplo uplo, ViennaCLOrder order, ViennaCLTranspose transA, ViennaCLDiag diag, ViennaCLInt n, float *A, ViennaCLInt offA_row, ViennaCLInt offA_col, ViennaCLInt incA_row, ViennaCLInt incA_col, ViennaCLInt lda, float *x, ViennaCLInt offx, ViennaCLInt incx)
Definition: blas2_host.cpp:88
direct_solve.hpp
Implementations of dense direct solvers are found here.
viennacl::linalg::outer_prod
viennacl::matrix_expression< const vector_base< NumericT >, const vector_base< NumericT >, op_prod > outer_prod(const vector_base< NumericT > &vec1, const vector_base< NumericT > &vec2)
Returns a proxy class for the operation mat += vec1 * vec2^T, i.e. a rank 1 update.
Definition: matrix_operations.hpp:840
v2
viennacl::vector< int > v2
Definition: global_variables.cpp:61
vector.hpp
The vector type with operator-overloads and proxy classes is defined here. Linear algebra operations ...
viennacl::linalg::unit_lower_tag
A tag class representing a lower triangular matrix with unit diagonal.
Definition: forwards.h:859
ViennaCLHostDgemv
VIENNACL_EXPORTED_FUNCTION ViennaCLStatus ViennaCLHostDgemv(ViennaCLBackend, ViennaCLOrder order, ViennaCLTranspose transA, ViennaCLInt m, ViennaCLInt n, double alpha, double *A, ViennaCLInt offA_row, ViennaCLInt offA_col, ViennaCLInt incA_row, ViennaCLInt incA_col, ViennaCLInt lda, double *x, ViennaCLInt offx, ViennaCLInt incx, double beta, double *y, ViennaCLInt offy, ViennaCLInt incy)
Definition: blas2_host.cpp:60
scalar.hpp
Implementation of the ViennaCL scalar class.
viennacl::linalg::unit_upper_tag
A tag class representing an upper triangular matrix with unit diagonal.
Definition: forwards.h:864
viennacl::vector_base::size_type
SizeT size_type
Definition: vector_def.hpp:112