1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifndef EIGEN_BENCH_UTIL_H
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define EIGEN_BENCH_UTIL_H
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <Eigen/Core>
6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include "BenchTimer.h"
7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathusing namespace std;
9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathusing namespace Eigen;
10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <boost/preprocessor/repetition/enum_params.hpp>
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <boost/preprocessor/repetition.hpp>
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <boost/preprocessor/seq.hpp>
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <boost/preprocessor/array.hpp>
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <boost/preprocessor/arithmetic.hpp>
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <boost/preprocessor/comparison.hpp>
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <boost/preprocessor/punctuation.hpp>
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <boost/preprocessor/punctuation/comma.hpp>
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <boost/preprocessor/stringize.hpp>
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> void initMatrix_random(MatrixType& mat) __attribute__((noinline));
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> void initMatrix_random(MatrixType& mat)
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  mat.setRandom();// = MatrixType::random(mat.rows(), mat.cols());
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> void initMatrix_identity(MatrixType& mat) __attribute__((noinline));
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename MatrixType> void initMatrix_identity(MatrixType& mat)
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  mat.setIdentity();
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifndef __INTEL_COMPILER
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define DISABLE_SSE_EXCEPTIONS()  { \
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  int aux; \
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  asm( \
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  "stmxcsr   %[aux]           \n\t" \
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  "orl       $32832, %[aux]   \n\t" \
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  "ldmxcsr   %[aux]           \n\t" \
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  : : [aux] "m" (aux)); \
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#else
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define DISABLE_SSE_EXCEPTIONS()
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifdef BENCH_GMM
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <gmm/gmm.h>
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate <typename EigenMatrixType, typename GmmMatrixType>
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid eiToGmm(const EigenMatrixType& src, GmmMatrixType& dst)
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  dst.resize(src.rows(),src.cols());
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int j=0; j<src.cols(); ++j)
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (int i=0; i<src.rows(); ++i)
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      dst(i,j) = src.coeff(i,j);
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifdef BENCH_GSL
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <gsl/gsl_matrix.h>
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <gsl/gsl_linalg.h>
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <gsl/gsl_eigen.h>
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate <typename EigenMatrixType>
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid eiToGsl(const EigenMatrixType& src, gsl_matrix** dst)
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int j=0; j<src.cols(); ++j)
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (int i=0; i<src.rows(); ++i)
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      gsl_matrix_set(*dst, i, j, src.coeff(i,j));
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#ifdef BENCH_UBLAS
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <boost/numeric/ublas/matrix.hpp>
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <boost/numeric/ublas/vector.hpp>
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate <typename EigenMatrixType, typename UblasMatrixType>
76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid eiToUblas(const EigenMatrixType& src, UblasMatrixType& dst)
77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  dst.resize(src.rows(),src.cols());
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int j=0; j<src.cols(); ++j)
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (int i=0; i<src.rows(); ++i)
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      dst(i,j) = src.coeff(i,j);
82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate <typename EigenType, typename UblasType>
84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid eiToUblasVec(const EigenType& src, UblasType& dst)
85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  dst.resize(src.size());
87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int j=0; j<src.size(); ++j)
88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      dst[j] = src.coeff(j);
89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif
91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#endif // EIGEN_BENCH_UTIL_H
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