source: pacpussensors/trunk/Vislab/lib3dv/eigen/Eigen/src/Core/products/SelfadjointMatrixVector.h@ 136

Last change on this file since 136 was 136, checked in by ldecherf, 7 years ago

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1// This file is part of Eigen, a lightweight C++ template library
2// for linear algebra.
3//
4// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
5//
6// This Source Code Form is subject to the terms of the Mozilla
7// Public License v. 2.0. If a copy of the MPL was not distributed
8// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
9
10#ifndef EIGEN_SELFADJOINT_MATRIX_VECTOR_H
11#define EIGEN_SELFADJOINT_MATRIX_VECTOR_H
12
13namespace Eigen {
14
15namespace internal {
16
17/* Optimized selfadjoint matrix * vector product:
18 * This algorithm processes 2 columns at onces that allows to both reduce
19 * the number of load/stores of the result by a factor 2 and to reduce
20 * the instruction dependency.
21 */
22
23template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs, int Version=Specialized>
24struct selfadjoint_matrix_vector_product;
25
26template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs, int Version>
27struct selfadjoint_matrix_vector_product
28
29{
30static EIGEN_DONT_INLINE void run(
31 Index size,
32 const Scalar* lhs, Index lhsStride,
33 const Scalar* _rhs, Index rhsIncr,
34 Scalar* res,
35 Scalar alpha);
36};
37
38template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs, int Version>
39EIGEN_DONT_INLINE void selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,Version>::run(
40 Index size,
41 const Scalar* lhs, Index lhsStride,
42 const Scalar* _rhs, Index rhsIncr,
43 Scalar* res,
44 Scalar alpha)
45{
46 typedef typename packet_traits<Scalar>::type Packet;
47 const Index PacketSize = sizeof(Packet)/sizeof(Scalar);
48
49 enum {
50 IsRowMajor = StorageOrder==RowMajor ? 1 : 0,
51 IsLower = UpLo == Lower ? 1 : 0,
52 FirstTriangular = IsRowMajor == IsLower
53 };
54
55 conj_helper<Scalar,Scalar,NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, IsRowMajor), ConjugateRhs> cj0;
56 conj_helper<Scalar,Scalar,NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, !IsRowMajor), ConjugateRhs> cj1;
57 conj_helper<Scalar,Scalar,NumTraits<Scalar>::IsComplex, ConjugateRhs> cjd;
58
59 conj_helper<Packet,Packet,NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, IsRowMajor), ConjugateRhs> pcj0;
60 conj_helper<Packet,Packet,NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, !IsRowMajor), ConjugateRhs> pcj1;
61
62 Scalar cjAlpha = ConjugateRhs ? numext::conj(alpha) : alpha;
63
64 // FIXME this copy is now handled outside product_selfadjoint_vector, so it could probably be removed.
65 // if the rhs is not sequentially stored in memory we copy it to a temporary buffer,
66 // this is because we need to extract packets
67 ei_declare_aligned_stack_constructed_variable(Scalar,rhs,size,rhsIncr==1 ? const_cast<Scalar*>(_rhs) : 0);
68 if (rhsIncr!=1)
69 {
70 const Scalar* it = _rhs;
71 for (Index i=0; i<size; ++i, it+=rhsIncr)
72 rhs[i] = *it;
73 }
74
75 Index bound = (std::max)(Index(0),size-8) & 0xfffffffe;
76 if (FirstTriangular)
77 bound = size - bound;
78
79 for (Index j=FirstTriangular ? bound : 0;
80 j<(FirstTriangular ? size : bound);j+=2)
81 {
82 const Scalar* EIGEN_RESTRICT A0 = lhs + j*lhsStride;
83 const Scalar* EIGEN_RESTRICT A1 = lhs + (j+1)*lhsStride;
84
85 Scalar t0 = cjAlpha * rhs[j];
86 Packet ptmp0 = pset1<Packet>(t0);
87 Scalar t1 = cjAlpha * rhs[j+1];
88 Packet ptmp1 = pset1<Packet>(t1);
89
90 Scalar t2(0);
91 Packet ptmp2 = pset1<Packet>(t2);
92 Scalar t3(0);
93 Packet ptmp3 = pset1<Packet>(t3);
94
95 size_t starti = FirstTriangular ? 0 : j+2;
96 size_t endi = FirstTriangular ? j : size;
97 size_t alignedStart = (starti) + internal::first_aligned(&res[starti], endi-starti);
98 size_t alignedEnd = alignedStart + ((endi-alignedStart)/(PacketSize))*(PacketSize);
99
100 // TODO make sure this product is a real * complex and that the rhs is properly conjugated if needed
101 res[j] += cjd.pmul(numext::real(A0[j]), t0);
102 res[j+1] += cjd.pmul(numext::real(A1[j+1]), t1);
103 if(FirstTriangular)
104 {
105 res[j] += cj0.pmul(A1[j], t1);
106 t3 += cj1.pmul(A1[j], rhs[j]);
107 }
108 else
109 {
110 res[j+1] += cj0.pmul(A0[j+1],t0);
111 t2 += cj1.pmul(A0[j+1], rhs[j+1]);
112 }
113
114 for (size_t i=starti; i<alignedStart; ++i)
115 {
116 res[i] += t0 * A0[i] + t1 * A1[i];
117 t2 += numext::conj(A0[i]) * rhs[i];
118 t3 += numext::conj(A1[i]) * rhs[i];
119 }
120 // Yes this an optimization for gcc 4.3 and 4.4 (=> huge speed up)
121 // gcc 4.2 does this optimization automatically.
122 const Scalar* EIGEN_RESTRICT a0It = A0 + alignedStart;
123 const Scalar* EIGEN_RESTRICT a1It = A1 + alignedStart;
124 const Scalar* EIGEN_RESTRICT rhsIt = rhs + alignedStart;
125 Scalar* EIGEN_RESTRICT resIt = res + alignedStart;
126 for (size_t i=alignedStart; i<alignedEnd; i+=PacketSize)
127 {
128 Packet A0i = ploadu<Packet>(a0It); a0It += PacketSize;
129 Packet A1i = ploadu<Packet>(a1It); a1It += PacketSize;
130 Packet Bi = ploadu<Packet>(rhsIt); rhsIt += PacketSize; // FIXME should be aligned in most cases
131 Packet Xi = pload <Packet>(resIt);
132
133 Xi = pcj0.pmadd(A0i,ptmp0, pcj0.pmadd(A1i,ptmp1,Xi));
134 ptmp2 = pcj1.pmadd(A0i, Bi, ptmp2);
135 ptmp3 = pcj1.pmadd(A1i, Bi, ptmp3);
136 pstore(resIt,Xi); resIt += PacketSize;
137 }
138 for (size_t i=alignedEnd; i<endi; i++)
139 {
140 res[i] += cj0.pmul(A0[i], t0) + cj0.pmul(A1[i],t1);
141 t2 += cj1.pmul(A0[i], rhs[i]);
142 t3 += cj1.pmul(A1[i], rhs[i]);
143 }
144
145 res[j] += alpha * (t2 + predux(ptmp2));
146 res[j+1] += alpha * (t3 + predux(ptmp3));
147 }
148 for (Index j=FirstTriangular ? 0 : bound;j<(FirstTriangular ? bound : size);j++)
149 {
150 const Scalar* EIGEN_RESTRICT A0 = lhs + j*lhsStride;
151
152 Scalar t1 = cjAlpha * rhs[j];
153 Scalar t2(0);
154 // TODO make sure this product is a real * complex and that the rhs is properly conjugated if needed
155 res[j] += cjd.pmul(numext::real(A0[j]), t1);
156 for (Index i=FirstTriangular ? 0 : j+1; i<(FirstTriangular ? j : size); i++)
157 {
158 res[i] += cj0.pmul(A0[i], t1);
159 t2 += cj1.pmul(A0[i], rhs[i]);
160 }
161 res[j] += alpha * t2;
162 }
163}
164
165} // end namespace internal
166
167/***************************************************************************
168* Wrapper to product_selfadjoint_vector
169***************************************************************************/
170
171namespace internal {
172template<typename Lhs, int LhsMode, typename Rhs>
173struct traits<SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,0,true> >
174 : traits<ProductBase<SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,0,true>, Lhs, Rhs> >
175{};
176}
177
178template<typename Lhs, int LhsMode, typename Rhs>
179struct SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,0,true>
180 : public ProductBase<SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,0,true>, Lhs, Rhs >
181{
182 EIGEN_PRODUCT_PUBLIC_INTERFACE(SelfadjointProductMatrix)
183
184 enum {
185 LhsUpLo = LhsMode&(Upper|Lower)
186 };
187
188 SelfadjointProductMatrix(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) {}
189
190 template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
191 {
192 typedef typename Dest::Scalar ResScalar;
193 typedef typename Base::RhsScalar RhsScalar;
194 typedef Map<Matrix<ResScalar,Dynamic,1>, Aligned> MappedDest;
195
196 eigen_assert(dest.rows()==m_lhs.rows() && dest.cols()==m_rhs.cols());
197
198 typename internal::add_const_on_value_type<ActualLhsType>::type lhs = LhsBlasTraits::extract(m_lhs);
199 typename internal::add_const_on_value_type<ActualRhsType>::type rhs = RhsBlasTraits::extract(m_rhs);
200
201 Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs)
202 * RhsBlasTraits::extractScalarFactor(m_rhs);
203
204 enum {
205 EvalToDest = (Dest::InnerStrideAtCompileTime==1),
206 UseRhs = (_ActualRhsType::InnerStrideAtCompileTime==1)
207 };
208
209 internal::gemv_static_vector_if<ResScalar,Dest::SizeAtCompileTime,Dest::MaxSizeAtCompileTime,!EvalToDest> static_dest;
210 internal::gemv_static_vector_if<RhsScalar,_ActualRhsType::SizeAtCompileTime,_ActualRhsType::MaxSizeAtCompileTime,!UseRhs> static_rhs;
211
212 ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
213 EvalToDest ? dest.data() : static_dest.data());
214
215 ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,rhs.size(),
216 UseRhs ? const_cast<RhsScalar*>(rhs.data()) : static_rhs.data());
217
218 if(!EvalToDest)
219 {
220 #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
221 int size = dest.size();
222 EIGEN_DENSE_STORAGE_CTOR_PLUGIN
223 #endif
224 MappedDest(actualDestPtr, dest.size()) = dest;
225 }
226
227 if(!UseRhs)
228 {
229 #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
230 int size = rhs.size();
231 EIGEN_DENSE_STORAGE_CTOR_PLUGIN
232 #endif
233 Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, rhs.size()) = rhs;
234 }
235
236
237 internal::selfadjoint_matrix_vector_product<Scalar, Index, (internal::traits<_ActualLhsType>::Flags&RowMajorBit) ? RowMajor : ColMajor, int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>::run
238 (
239 lhs.rows(), // size
240 &lhs.coeffRef(0,0), lhs.outerStride(), // lhs info
241 actualRhsPtr, 1, // rhs info
242 actualDestPtr, // result info
243 actualAlpha // scale factor
244 );
245
246 if(!EvalToDest)
247 dest = MappedDest(actualDestPtr, dest.size());
248 }
249};
250
251namespace internal {
252template<typename Lhs, typename Rhs, int RhsMode>
253struct traits<SelfadjointProductMatrix<Lhs,0,true,Rhs,RhsMode,false> >
254 : traits<ProductBase<SelfadjointProductMatrix<Lhs,0,true,Rhs,RhsMode,false>, Lhs, Rhs> >
255{};
256}
257
258template<typename Lhs, typename Rhs, int RhsMode>
259struct SelfadjointProductMatrix<Lhs,0,true,Rhs,RhsMode,false>
260 : public ProductBase<SelfadjointProductMatrix<Lhs,0,true,Rhs,RhsMode,false>, Lhs, Rhs >
261{
262 EIGEN_PRODUCT_PUBLIC_INTERFACE(SelfadjointProductMatrix)
263
264 enum {
265 RhsUpLo = RhsMode&(Upper|Lower)
266 };
267
268 SelfadjointProductMatrix(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) {}
269
270 template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
271 {
272 // let's simply transpose the product
273 Transpose<Dest> destT(dest);
274 SelfadjointProductMatrix<Transpose<const Rhs>, int(RhsUpLo)==Upper ? Lower : Upper, false,
275 Transpose<const Lhs>, 0, true>(m_rhs.transpose(), m_lhs.transpose()).scaleAndAddTo(destT, alpha);
276 }
277};
278
279} // end namespace Eigen
280
281#endif // EIGEN_SELFADJOINT_MATRIX_VECTOR_H
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