1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
|
/*
Genome-wide Efficient Mixed Model Association (GEMMA)
Copyright (C) 2011-2017, Xiang Zhou
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include <iostream>
#include <cmath>
#include <vector>
#include "gsl/gsl_vector.h"
#include "gsl/gsl_matrix.h"
#include "gsl/gsl_linalg.h"
#include "Eigen/Dense"
using namespace std;
using namespace Eigen;
// On two different clusters, compare eigen vs lapack/gsl:
//
// dgemm, 5x or 0.5x faster or slower than lapack, 5x or 4x faster than gsl
// dgemv, 20x or 4x faster than gsl,
// eigen, 1x or 0.3x slower than lapack
// invert, 20x or 10x faster than lapack
//
void eigenlib_dgemm (const char *TransA, const char *TransB,
const double alpha, const gsl_matrix *A,
const gsl_matrix *B, const double beta,
gsl_matrix *C) {
Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic> >
A_mat(A->data, A->size1, A->size2, OuterStride<Dynamic>(A->tda) );
Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic> >
B_mat(B->data, B->size1, B->size2, OuterStride<Dynamic>(B->tda) );
Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic> >
C_mat(C->data, C->size1, C->size2, OuterStride<Dynamic>(C->tda) );
if (*TransA=='N' || *TransA=='n') {
if (*TransB=='N' || *TransB=='n') {
C_mat=alpha*A_mat*B_mat+beta*C_mat;
} else {
C_mat=alpha*A_mat*B_mat.transpose()+beta*C_mat;
}
} else {
if (*TransB=='N' || *TransB=='n') {
C_mat=alpha*A_mat.transpose()*B_mat+beta*C_mat;
} else {
C_mat=alpha*A_mat.transpose()*B_mat.transpose()+beta*C_mat;
}
}
return;
}
void eigenlib_dgemv (const char *TransA, const double alpha,
const gsl_matrix *A, const gsl_vector *x,
const double beta, gsl_vector *y) {
Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic> >
A_mat(A->data, A->size1, A->size2, OuterStride<Dynamic>(A->tda) );
Map<Matrix<double, Dynamic, 1>, 0, InnerStride<Dynamic> >
x_vec(x->data, x->size, InnerStride<Dynamic>(x->stride) );
Map<Matrix<double, Dynamic, 1>, 0, InnerStride<Dynamic> >
y_vec(y->data, y->size, InnerStride<Dynamic>(y->stride) );
if (*TransA=='N' || *TransA=='n') {
y_vec=alpha*A_mat*x_vec+beta*y_vec;
} else {
y_vec=alpha*A_mat.transpose()*x_vec+beta*y_vec;
}
return;
}
void eigenlib_invert(gsl_matrix *A) {
Map<Matrix<double, Dynamic, Dynamic, RowMajor> >
A_mat(A->data, A->size1, A->size2);
A_mat=A_mat.inverse();
return;
}
void eigenlib_dsyr (const double alpha, const gsl_vector *b, gsl_matrix *A) {
Map<Matrix<double, Dynamic, Dynamic, RowMajor> >
A_mat(A->data, A->size1, A->size2);
Map<Matrix<double, Dynamic, 1>, 0, OuterStride<Dynamic> >
b_vec(b->data, b->size, OuterStride<Dynamic>(b->stride) );
A_mat=alpha*b_vec*b_vec.transpose()+A_mat;
return;
}
void eigenlib_eigensymm (const gsl_matrix *G, gsl_matrix *U,
gsl_vector *eval) {
Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic> >
G_mat(G->data, G->size1, G->size2, OuterStride<Dynamic>(G->tda) );
Map<Matrix<double, Dynamic, Dynamic, RowMajor>, 0, OuterStride<Dynamic> >
U_mat(U->data, U->size1, U->size2, OuterStride<Dynamic>(U->tda) );
Map<Matrix<double, Dynamic, 1>, 0, OuterStride<Dynamic> >
eval_vec(eval->data, eval->size, OuterStride<Dynamic>(eval->stride) );
SelfAdjointEigenSolver<MatrixXd> es(G_mat);
if (es.info() != Success)
abort();
eval_vec=es.eigenvalues();
U_mat=es.eigenvectors();
return;
}
|
