1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra. Eigen itself is part of the KDE project.
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla
7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed
8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include "main.h"
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// using namespace Eigen;
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> bool areApprox(const Scalar* a, const Scalar* b, int size)
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<size; ++i)
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if (!ei_isApprox(a[i],b[i])) return false;
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  return true;
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define CHECK_CWISE(REFOP, POP) { \
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<PacketSize; ++i) \
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ref[i] = REFOP(data1[i], data1[i+PacketSize]); \
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  ei_pstore(data2, POP(ei_pload(data1), ei_pload(data1+PacketSize))); \
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(areApprox(ref, data2, PacketSize) && #POP); \
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define REF_ADD(a,b) ((a)+(b))
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define REF_SUB(a,b) ((a)-(b))
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define REF_MUL(a,b) ((a)*(b))
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define REF_DIV(a,b) ((a)/(b))
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace std {
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<> const complex<float>& min(const complex<float>& a, const complex<float>& b)
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ return a.real() < b.real() ? a : b; }
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<> const complex<float>& max(const complex<float>& a, const complex<float>& b)
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ return a.real() < b.real() ? b : a; }
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> void packetmath()
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename ei_packet_traits<Scalar>::type Packet;
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const int PacketSize = ei_packet_traits<Scalar>::size;
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const int size = PacketSize*4;
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_ALIGN_128 Scalar data1[ei_packet_traits<Scalar>::size*4];
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_ALIGN_128 Scalar data2[ei_packet_traits<Scalar>::size*4];
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_ALIGN_128 Packet packets[PacketSize*2];
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_ALIGN_128 Scalar ref[ei_packet_traits<Scalar>::size*4];
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<size; ++i)
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    data1[i] = ei_random<Scalar>();
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    data2[i] = ei_random<Scalar>();
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  ei_pstore(data2, ei_pload(data1));
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(areApprox(data1, data2, PacketSize) && "aligned load/store");
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int offset=0; offset<PacketSize; ++offset)
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ei_pstore(data2, ei_ploadu(data1+offset));
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY(areApprox(data1+offset, data2, PacketSize) && "ei_ploadu");
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int offset=0; offset<PacketSize; ++offset)
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ei_pstoreu(data2+offset, ei_pload(data1));
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY(areApprox(data1, data2+offset, PacketSize) && "ei_pstoreu");
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int offset=0; offset<PacketSize; ++offset)
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    packets[0] = ei_pload(data1);
77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    packets[1] = ei_pload(data1+PacketSize);
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         if (offset==0) ei_palign<0>(packets[0], packets[1]);
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    else if (offset==1) ei_palign<1>(packets[0], packets[1]);
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    else if (offset==2) ei_palign<2>(packets[0], packets[1]);
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    else if (offset==3) ei_palign<3>(packets[0], packets[1]);
82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ei_pstore(data2, packets[0]);
83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (int i=0; i<PacketSize; ++i)
85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      ref[i] = data1[i+offset];
86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    typedef Matrix<Scalar, PacketSize, 1> Vector;
88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY(areApprox(ref, data2, PacketSize) && "ei_palign");
89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CHECK_CWISE(REF_ADD,  ei_padd);
92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CHECK_CWISE(REF_SUB,  ei_psub);
93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CHECK_CWISE(REF_MUL,  ei_pmul);
94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  #ifndef EIGEN_VECTORIZE_ALTIVEC
95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if (!ei_is_same_type<Scalar,int>::ret)
96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CHECK_CWISE(REF_DIV,  ei_pdiv);
97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  #endif
98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CHECK_CWISE(std::min, ei_pmin);
99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CHECK_CWISE(std::max, ei_pmax);
100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<PacketSize; ++i)
102c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ref[i] = data1[0];
103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  ei_pstore(data2, ei_pset1(data1[0]));
104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(areApprox(ref, data2, PacketSize) && "ei_pset1");
105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(ei_isApprox(data1[0], ei_pfirst(ei_pload(data1))) && "ei_pfirst");
107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  ref[0] = 0;
109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<PacketSize; ++i)
110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ref[0] += data1[i];
111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(ei_isApprox(ref[0], ei_predux(ei_pload(data1))) && "ei_predux");
112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int j=0; j<PacketSize; ++j)
114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ref[j] = 0;
116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (int i=0; i<PacketSize; ++i)
117c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      ref[j] += data1[i+j*PacketSize];
118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    packets[j] = ei_pload(data1+j*PacketSize);
119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  ei_pstore(data2, ei_preduxp(packets));
121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(areApprox(ref, data2, PacketSize) && "ei_preduxp");
122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid test_eigen2_packetmath()
125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for(int i = 0; i < g_repeat; i++) {
127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_1( packetmath<float>() );
128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_2( packetmath<double>() );
129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_3( packetmath<int>() );
130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_4( packetmath<std::complex<float> >() );
131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
133