Inverse_SSE.h
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00001 // This file is part of Eigen, a lightweight C++ template library
00002 // for linear algebra.
00003 //
00004 // Copyright (C) 2001 Intel Corporation
00005 // Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
00006 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
00007 //
00008 // Eigen is free software; you can redistribute it and/or
00009 // modify it under the terms of the GNU Lesser General Public
00010 // License as published by the Free Software Foundation; either
00011 // version 3 of the License, or (at your option) any later version.
00012 //
00013 // Alternatively, you can redistribute it and/or
00014 // modify it under the terms of the GNU General Public License as
00015 // published by the Free Software Foundation; either version 2 of
00016 // the License, or (at your option) any later version.
00017 //
00018 // Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
00019 // WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
00020 // FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
00021 // GNU General Public License for more details.
00022 //
00023 // You should have received a copy of the GNU Lesser General Public
00024 // License and a copy of the GNU General Public License along with
00025 // Eigen. If not, see <http://www.gnu.org/licenses/>.
00026 
00027 // The SSE code for the 4x4 float and double matrix inverse in this file
00028 // comes from the following Intel's library:
00029 // http://software.intel.com/en-us/articles/optimized-matrix-library-for-use-with-the-intel-pentiumr-4-processors-sse2-instructions/
00030 //
00031 // Here is the respective copyright and license statement:
00032 //
00033 //   Copyright (c) 2001 Intel Corporation.
00034 //
00035 // Permition is granted to use, copy, distribute and prepare derivative works
00036 // of this library for any purpose and without fee, provided, that the above
00037 // copyright notice and this statement appear in all copies.
00038 // Intel makes no representations about the suitability of this software for
00039 // any purpose, and specifically disclaims all warranties.
00040 // See LEGAL.TXT for all the legal information.
00041 
00042 #ifndef EIGEN_INVERSE_SSE_H
00043 #define EIGEN_INVERSE_SSE_H
00044 
00045 namespace internal {
00046 
00047 template<typename MatrixType, typename ResultType>
00048 struct compute_inverse_size4<Architecture::SSE, float, MatrixType, ResultType>
00049 {
00050   enum {
00051     MatrixAlignment     = bool(MatrixType::Flags&AlignedBit),
00052     ResultAlignment     = bool(ResultType::Flags&AlignedBit),
00053     StorageOrdersMatch  = (MatrixType::Flags&RowMajorBit) == (ResultType::Flags&RowMajorBit)
00054   };
00055   
00056   static void run(const MatrixType& matrix, ResultType& result)
00057   {
00058     EIGEN_ALIGN16 const  int _Sign_PNNP[4] = { 0x00000000, 0x80000000, 0x80000000, 0x00000000 };
00059 
00060     // Load the full matrix into registers
00061     __m128 _L1 = matrix.template packet<MatrixAlignment>( 0);
00062     __m128 _L2 = matrix.template packet<MatrixAlignment>( 4);
00063     __m128 _L3 = matrix.template packet<MatrixAlignment>( 8);
00064     __m128 _L4 = matrix.template packet<MatrixAlignment>(12);
00065 
00066     // The inverse is calculated using "Divide and Conquer" technique. The
00067     // original matrix is divide into four 2x2 sub-matrices. Since each
00068     // register holds four matrix element, the smaller matrices are
00069     // represented as a registers. Hence we get a better locality of the
00070     // calculations.
00071 
00072     __m128 A, B, C, D; // the four sub-matrices
00073     if(!StorageOrdersMatch)
00074     {
00075       A = _mm_unpacklo_ps(_L1, _L2);
00076       B = _mm_unpacklo_ps(_L3, _L4);
00077       C = _mm_unpackhi_ps(_L1, _L2);
00078       D = _mm_unpackhi_ps(_L3, _L4);
00079     }
00080     else
00081     {
00082       A = _mm_movelh_ps(_L1, _L2);
00083       B = _mm_movehl_ps(_L2, _L1);
00084       C = _mm_movelh_ps(_L3, _L4);
00085       D = _mm_movehl_ps(_L4, _L3);
00086     }
00087 
00088     __m128 iA, iB, iC, iD,                 // partial inverse of the sub-matrices
00089             DC, AB;
00090     __m128 dA, dB, dC, dD;                 // determinant of the sub-matrices
00091     __m128 det, d, d1, d2;
00092     __m128 rd;                             // reciprocal of the determinant
00093 
00094     //  AB = A# * B
00095     AB = _mm_mul_ps(_mm_shuffle_ps(A,A,0x0F), B);
00096     AB = _mm_sub_ps(AB,_mm_mul_ps(_mm_shuffle_ps(A,A,0xA5), _mm_shuffle_ps(B,B,0x4E)));
00097     //  DC = D# * C
00098     DC = _mm_mul_ps(_mm_shuffle_ps(D,D,0x0F), C);
00099     DC = _mm_sub_ps(DC,_mm_mul_ps(_mm_shuffle_ps(D,D,0xA5), _mm_shuffle_ps(C,C,0x4E)));
00100 
00101     //  dA = |A|
00102     dA = _mm_mul_ps(_mm_shuffle_ps(A, A, 0x5F),A);
00103     dA = _mm_sub_ss(dA, _mm_movehl_ps(dA,dA));
00104     //  dB = |B|
00105     dB = _mm_mul_ps(_mm_shuffle_ps(B, B, 0x5F),B);
00106     dB = _mm_sub_ss(dB, _mm_movehl_ps(dB,dB));
00107 
00108     //  dC = |C|
00109     dC = _mm_mul_ps(_mm_shuffle_ps(C, C, 0x5F),C);
00110     dC = _mm_sub_ss(dC, _mm_movehl_ps(dC,dC));
00111     //  dD = |D|
00112     dD = _mm_mul_ps(_mm_shuffle_ps(D, D, 0x5F),D);
00113     dD = _mm_sub_ss(dD, _mm_movehl_ps(dD,dD));
00114 
00115     //  d = trace(AB*DC) = trace(A#*B*D#*C)
00116     d = _mm_mul_ps(_mm_shuffle_ps(DC,DC,0xD8),AB);
00117 
00118     //  iD = C*A#*B
00119     iD = _mm_mul_ps(_mm_shuffle_ps(C,C,0xA0), _mm_movelh_ps(AB,AB));
00120     iD = _mm_add_ps(iD,_mm_mul_ps(_mm_shuffle_ps(C,C,0xF5), _mm_movehl_ps(AB,AB)));
00121     //  iA = B*D#*C
00122     iA = _mm_mul_ps(_mm_shuffle_ps(B,B,0xA0), _mm_movelh_ps(DC,DC));
00123     iA = _mm_add_ps(iA,_mm_mul_ps(_mm_shuffle_ps(B,B,0xF5), _mm_movehl_ps(DC,DC)));
00124 
00125     //  d = trace(AB*DC) = trace(A#*B*D#*C) [continue]
00126     d  = _mm_add_ps(d, _mm_movehl_ps(d, d));
00127     d  = _mm_add_ss(d, _mm_shuffle_ps(d, d, 1));
00128     d1 = _mm_mul_ss(dA,dD);
00129     d2 = _mm_mul_ss(dB,dC);
00130 
00131     //  iD = D*|A| - C*A#*B
00132     iD = _mm_sub_ps(_mm_mul_ps(D,_mm_shuffle_ps(dA,dA,0)), iD);
00133 
00134     //  iA = A*|D| - B*D#*C;
00135     iA = _mm_sub_ps(_mm_mul_ps(A,_mm_shuffle_ps(dD,dD,0)), iA);
00136 
00137     //  det = |A|*|D| + |B|*|C| - trace(A#*B*D#*C)
00138     det = _mm_sub_ss(_mm_add_ss(d1,d2),d);
00139     rd  = _mm_div_ss(_mm_set_ss(1.0f), det);
00140 
00141 //     #ifdef ZERO_SINGULAR
00142 //         rd = _mm_and_ps(_mm_cmpneq_ss(det,_mm_setzero_ps()), rd);
00143 //     #endif
00144 
00145     //  iB = D * (A#B)# = D*B#*A
00146     iB = _mm_mul_ps(D, _mm_shuffle_ps(AB,AB,0x33));
00147     iB = _mm_sub_ps(iB, _mm_mul_ps(_mm_shuffle_ps(D,D,0xB1), _mm_shuffle_ps(AB,AB,0x66)));
00148     //  iC = A * (D#C)# = A*C#*D
00149     iC = _mm_mul_ps(A, _mm_shuffle_ps(DC,DC,0x33));
00150     iC = _mm_sub_ps(iC, _mm_mul_ps(_mm_shuffle_ps(A,A,0xB1), _mm_shuffle_ps(DC,DC,0x66)));
00151 
00152     rd = _mm_shuffle_ps(rd,rd,0);
00153     rd = _mm_xor_ps(rd, _mm_load_ps((float*)_Sign_PNNP));
00154 
00155     //  iB = C*|B| - D*B#*A
00156     iB = _mm_sub_ps(_mm_mul_ps(C,_mm_shuffle_ps(dB,dB,0)), iB);
00157 
00158     //  iC = B*|C| - A*C#*D;
00159     iC = _mm_sub_ps(_mm_mul_ps(B,_mm_shuffle_ps(dC,dC,0)), iC);
00160 
00161     //  iX = iX / det
00162     iA = _mm_mul_ps(rd,iA);
00163     iB = _mm_mul_ps(rd,iB);
00164     iC = _mm_mul_ps(rd,iC);
00165     iD = _mm_mul_ps(rd,iD);
00166 
00167     result.template writePacket<ResultAlignment>( 0, _mm_shuffle_ps(iA,iB,0x77));
00168     result.template writePacket<ResultAlignment>( 4, _mm_shuffle_ps(iA,iB,0x22));
00169     result.template writePacket<ResultAlignment>( 8, _mm_shuffle_ps(iC,iD,0x77));
00170     result.template writePacket<ResultAlignment>(12, _mm_shuffle_ps(iC,iD,0x22));
00171   }
00172 
00173 };
00174 
00175 template<typename MatrixType, typename ResultType>
00176 struct compute_inverse_size4<Architecture::SSE, double, MatrixType, ResultType>
00177 {
00178   enum {
00179     MatrixAlignment = bool(MatrixType::Flags&AlignedBit),
00180     ResultAlignment = bool(ResultType::Flags&AlignedBit),
00181     StorageOrdersMatch  = (MatrixType::Flags&RowMajorBit) == (ResultType::Flags&RowMajorBit)
00182   };
00183   static void run(const MatrixType& matrix, ResultType& result)
00184   {
00185     const __m128d _Sign_NP = _mm_castsi128_pd(_mm_set_epi32(0x0,0x0,0x80000000,0x0));
00186     const __m128d _Sign_PN = _mm_castsi128_pd(_mm_set_epi32(0x80000000,0x0,0x0,0x0));
00187 
00188     // The inverse is calculated using "Divide and Conquer" technique. The
00189     // original matrix is divide into four 2x2 sub-matrices. Since each
00190     // register of the matrix holds two element, the smaller matrices are
00191     // consisted of two registers. Hence we get a better locality of the
00192     // calculations.
00193 
00194     // the four sub-matrices
00195     __m128d A1, A2, B1, B2, C1, C2, D1, D2;
00196     
00197     if(StorageOrdersMatch)
00198     {
00199       A1 = matrix.template packet<MatrixAlignment>( 0); B1 = matrix.template packet<MatrixAlignment>( 2);
00200       A2 = matrix.template packet<MatrixAlignment>( 4); B2 = matrix.template packet<MatrixAlignment>( 6);
00201       C1 = matrix.template packet<MatrixAlignment>( 8); D1 = matrix.template packet<MatrixAlignment>(10);
00202       C2 = matrix.template packet<MatrixAlignment>(12); D2 = matrix.template packet<MatrixAlignment>(14);
00203     }
00204     else
00205     {
00206       __m128d tmp;
00207       A1 = matrix.template packet<MatrixAlignment>( 0); C1 = matrix.template packet<MatrixAlignment>( 2);
00208       A2 = matrix.template packet<MatrixAlignment>( 4); C2 = matrix.template packet<MatrixAlignment>( 6);
00209       tmp = A1;
00210       A1 = _mm_unpacklo_pd(A1,A2);
00211       A2 = _mm_unpackhi_pd(tmp,A2);
00212       tmp = C1;
00213       C1 = _mm_unpacklo_pd(C1,C2);
00214       C2 = _mm_unpackhi_pd(tmp,C2);
00215       
00216       B1 = matrix.template packet<MatrixAlignment>( 8); D1 = matrix.template packet<MatrixAlignment>(10);
00217       B2 = matrix.template packet<MatrixAlignment>(12); D2 = matrix.template packet<MatrixAlignment>(14);
00218       tmp = B1;
00219       B1 = _mm_unpacklo_pd(B1,B2);
00220       B2 = _mm_unpackhi_pd(tmp,B2);
00221       tmp = D1;
00222       D1 = _mm_unpacklo_pd(D1,D2);
00223       D2 = _mm_unpackhi_pd(tmp,D2);
00224     }
00225     
00226     __m128d iA1, iA2, iB1, iB2, iC1, iC2, iD1, iD2,     // partial invese of the sub-matrices
00227             DC1, DC2, AB1, AB2;
00228     __m128d dA, dB, dC, dD;     // determinant of the sub-matrices
00229     __m128d det, d1, d2, rd;
00230 
00231     //  dA = |A|
00232     dA = _mm_shuffle_pd(A2, A2, 1);
00233     dA = _mm_mul_pd(A1, dA);
00234     dA = _mm_sub_sd(dA, _mm_shuffle_pd(dA,dA,3));
00235     //  dB = |B|
00236     dB = _mm_shuffle_pd(B2, B2, 1);
00237     dB = _mm_mul_pd(B1, dB);
00238     dB = _mm_sub_sd(dB, _mm_shuffle_pd(dB,dB,3));
00239 
00240     //  AB = A# * B
00241     AB1 = _mm_mul_pd(B1, _mm_shuffle_pd(A2,A2,3));
00242     AB2 = _mm_mul_pd(B2, _mm_shuffle_pd(A1,A1,0));
00243     AB1 = _mm_sub_pd(AB1, _mm_mul_pd(B2, _mm_shuffle_pd(A1,A1,3)));
00244     AB2 = _mm_sub_pd(AB2, _mm_mul_pd(B1, _mm_shuffle_pd(A2,A2,0)));
00245 
00246     //  dC = |C|
00247     dC = _mm_shuffle_pd(C2, C2, 1);
00248     dC = _mm_mul_pd(C1, dC);
00249     dC = _mm_sub_sd(dC, _mm_shuffle_pd(dC,dC,3));
00250     //  dD = |D|
00251     dD = _mm_shuffle_pd(D2, D2, 1);
00252     dD = _mm_mul_pd(D1, dD);
00253     dD = _mm_sub_sd(dD, _mm_shuffle_pd(dD,dD,3));
00254 
00255     //  DC = D# * C
00256     DC1 = _mm_mul_pd(C1, _mm_shuffle_pd(D2,D2,3));
00257     DC2 = _mm_mul_pd(C2, _mm_shuffle_pd(D1,D1,0));
00258     DC1 = _mm_sub_pd(DC1, _mm_mul_pd(C2, _mm_shuffle_pd(D1,D1,3)));
00259     DC2 = _mm_sub_pd(DC2, _mm_mul_pd(C1, _mm_shuffle_pd(D2,D2,0)));
00260 
00261     //  rd = trace(AB*DC) = trace(A#*B*D#*C)
00262     d1 = _mm_mul_pd(AB1, _mm_shuffle_pd(DC1, DC2, 0));
00263     d2 = _mm_mul_pd(AB2, _mm_shuffle_pd(DC1, DC2, 3));
00264     rd = _mm_add_pd(d1, d2);
00265     rd = _mm_add_sd(rd, _mm_shuffle_pd(rd, rd,3));
00266 
00267     //  iD = C*A#*B
00268     iD1 = _mm_mul_pd(AB1, _mm_shuffle_pd(C1,C1,0));
00269     iD2 = _mm_mul_pd(AB1, _mm_shuffle_pd(C2,C2,0));
00270     iD1 = _mm_add_pd(iD1, _mm_mul_pd(AB2, _mm_shuffle_pd(C1,C1,3)));
00271     iD2 = _mm_add_pd(iD2, _mm_mul_pd(AB2, _mm_shuffle_pd(C2,C2,3)));
00272 
00273     //  iA = B*D#*C
00274     iA1 = _mm_mul_pd(DC1, _mm_shuffle_pd(B1,B1,0));
00275     iA2 = _mm_mul_pd(DC1, _mm_shuffle_pd(B2,B2,0));
00276     iA1 = _mm_add_pd(iA1, _mm_mul_pd(DC2, _mm_shuffle_pd(B1,B1,3)));
00277     iA2 = _mm_add_pd(iA2, _mm_mul_pd(DC2, _mm_shuffle_pd(B2,B2,3)));
00278 
00279     //  iD = D*|A| - C*A#*B
00280     dA = _mm_shuffle_pd(dA,dA,0);
00281     iD1 = _mm_sub_pd(_mm_mul_pd(D1, dA), iD1);
00282     iD2 = _mm_sub_pd(_mm_mul_pd(D2, dA), iD2);
00283 
00284     //  iA = A*|D| - B*D#*C;
00285     dD = _mm_shuffle_pd(dD,dD,0);
00286     iA1 = _mm_sub_pd(_mm_mul_pd(A1, dD), iA1);
00287     iA2 = _mm_sub_pd(_mm_mul_pd(A2, dD), iA2);
00288 
00289     d1 = _mm_mul_sd(dA, dD);
00290     d2 = _mm_mul_sd(dB, dC);
00291 
00292     //  iB = D * (A#B)# = D*B#*A
00293     iB1 = _mm_mul_pd(D1, _mm_shuffle_pd(AB2,AB1,1));
00294     iB2 = _mm_mul_pd(D2, _mm_shuffle_pd(AB2,AB1,1));
00295     iB1 = _mm_sub_pd(iB1, _mm_mul_pd(_mm_shuffle_pd(D1,D1,1), _mm_shuffle_pd(AB2,AB1,2)));
00296     iB2 = _mm_sub_pd(iB2, _mm_mul_pd(_mm_shuffle_pd(D2,D2,1), _mm_shuffle_pd(AB2,AB1,2)));
00297 
00298     //  det = |A|*|D| + |B|*|C| - trace(A#*B*D#*C)
00299     det = _mm_add_sd(d1, d2);
00300     det = _mm_sub_sd(det, rd);
00301 
00302     //  iC = A * (D#C)# = A*C#*D
00303     iC1 = _mm_mul_pd(A1, _mm_shuffle_pd(DC2,DC1,1));
00304     iC2 = _mm_mul_pd(A2, _mm_shuffle_pd(DC2,DC1,1));
00305     iC1 = _mm_sub_pd(iC1, _mm_mul_pd(_mm_shuffle_pd(A1,A1,1), _mm_shuffle_pd(DC2,DC1,2)));
00306     iC2 = _mm_sub_pd(iC2, _mm_mul_pd(_mm_shuffle_pd(A2,A2,1), _mm_shuffle_pd(DC2,DC1,2)));
00307 
00308     rd = _mm_div_sd(_mm_set_sd(1.0), det);
00309 //     #ifdef ZERO_SINGULAR
00310 //         rd = _mm_and_pd(_mm_cmpneq_sd(det,_mm_setzero_pd()), rd);
00311 //     #endif
00312     rd = _mm_shuffle_pd(rd,rd,0);
00313 
00314     //  iB = C*|B| - D*B#*A
00315     dB = _mm_shuffle_pd(dB,dB,0);
00316     iB1 = _mm_sub_pd(_mm_mul_pd(C1, dB), iB1);
00317     iB2 = _mm_sub_pd(_mm_mul_pd(C2, dB), iB2);
00318 
00319     d1 = _mm_xor_pd(rd, _Sign_PN);
00320     d2 = _mm_xor_pd(rd, _Sign_NP);
00321 
00322     //  iC = B*|C| - A*C#*D;
00323     dC = _mm_shuffle_pd(dC,dC,0);
00324     iC1 = _mm_sub_pd(_mm_mul_pd(B1, dC), iC1);
00325     iC2 = _mm_sub_pd(_mm_mul_pd(B2, dC), iC2);
00326 
00327     result.template writePacket<ResultAlignment>( 0, _mm_mul_pd(_mm_shuffle_pd(iA2, iA1, 3), d1));     // iA# / det
00328     result.template writePacket<ResultAlignment>( 4, _mm_mul_pd(_mm_shuffle_pd(iA2, iA1, 0), d2));
00329     result.template writePacket<ResultAlignment>( 2, _mm_mul_pd(_mm_shuffle_pd(iB2, iB1, 3), d1));     // iB# / det
00330     result.template writePacket<ResultAlignment>( 6, _mm_mul_pd(_mm_shuffle_pd(iB2, iB1, 0), d2));
00331     result.template writePacket<ResultAlignment>( 8, _mm_mul_pd(_mm_shuffle_pd(iC2, iC1, 3), d1));     // iC# / det
00332     result.template writePacket<ResultAlignment>(12, _mm_mul_pd(_mm_shuffle_pd(iC2, iC1, 0), d2));
00333     result.template writePacket<ResultAlignment>(10, _mm_mul_pd(_mm_shuffle_pd(iD2, iD1, 3), d1));     // iD# / det
00334     result.template writePacket<ResultAlignment>(14, _mm_mul_pd(_mm_shuffle_pd(iD2, iD1, 0), d2));
00335   }
00336 };
00337 
00338 }
00339 
00340 #endif // EIGEN_INVERSE_SSE_H


libicr
Author(s): Robert Krug
autogenerated on Mon Jan 6 2014 11:32:51