diff options
-rw-r--r-- | Eigen/src/Core/GeneralProduct.h | 32 | ||||
-rw-r--r-- | Eigen/src/Core/products/GeneralMatrixVector.h | 246 | ||||
-rw-r--r-- | Eigen/src/Core/products/TriangularMatrixVector.h | 46 | ||||
-rw-r--r-- | Eigen/src/Core/products/TriangularSolverVector.h | 24 | ||||
-rw-r--r-- | Eigen/src/Core/util/BlasUtil.h | 47 |
5 files changed, 228 insertions, 167 deletions
diff --git a/Eigen/src/Core/GeneralProduct.h b/Eigen/src/Core/GeneralProduct.h index 7179eb124..9d3d5562c 100644 --- a/Eigen/src/Core/GeneralProduct.h +++ b/Eigen/src/Core/GeneralProduct.h @@ -11,7 +11,7 @@ #ifndef EIGEN_GENERAL_PRODUCT_H #define EIGEN_GENERAL_PRODUCT_H -namespace Eigen { +namespace Eigen { /** \class GeneralProduct * \ingroup Core_Module @@ -257,7 +257,7 @@ class GeneralProduct<Lhs, Rhs, OuterProduct> : public ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs> { template<typename T> struct IsRowMajor : internal::conditional<(int(T::Flags)&RowMajorBit), internal::true_type, internal::false_type>::type {}; - + public: EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct) @@ -266,7 +266,7 @@ class GeneralProduct<Lhs, Rhs, OuterProduct> EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value), YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) } - + struct set { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() = src; } }; struct add { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() += src; } }; struct sub { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() -= src; } }; @@ -277,12 +277,12 @@ class GeneralProduct<Lhs, Rhs, OuterProduct> dst.const_cast_derived() += m_scale * src; } }; - + template<typename Dest> inline void evalTo(Dest& dest) const { internal::outer_product_selector_run(*this, dest, set(), IsRowMajor<Dest>()); } - + template<typename Dest> inline void addTo(Dest& dest) const { internal::outer_product_selector_run(*this, dest, add(), IsRowMajor<Dest>()); @@ -436,12 +436,12 @@ template<> struct gemv_selector<OnTheRight,ColMajor,true> bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0)); bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible; - + RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha); ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(), evalToDest ? dest.data() : static_dest.data()); - + if(!evalToDest) { #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN @@ -457,11 +457,13 @@ template<> struct gemv_selector<OnTheRight,ColMajor,true> MappedDest(actualDestPtr, dest.size()) = dest; } + typedef const_blas_data_mapper<LhsScalar,Index,ColMajor> LhsMapper; + typedef const_blas_data_mapper<RhsScalar,Index,RowMajor> RhsMapper; general_matrix_vector_product - <Index,LhsScalar,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run( + <Index,LhsScalar,LhsMapper,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run( actualLhs.rows(), actualLhs.cols(), - actualLhs.data(), actualLhs.outerStride(), - actualRhs.data(), actualRhs.innerStride(), + LhsMapper(actualLhs.data(), actualLhs.outerStride()), + RhsMapper(actualRhs.data(), actualRhs.innerStride()), actualDestPtr, 1, compatibleAlpha); @@ -516,11 +518,13 @@ template<> struct gemv_selector<OnTheRight,RowMajor,true> Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs; } + typedef const_blas_data_mapper<LhsScalar,Index,RowMajor> LhsMapper; + typedef const_blas_data_mapper<RhsScalar,Index,ColMajor> RhsMapper; general_matrix_vector_product - <Index,LhsScalar,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run( + <Index,LhsScalar,LhsMapper,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsMapper,RhsBlasTraits::NeedToConjugate>::run( actualLhs.rows(), actualLhs.cols(), - actualLhs.data(), actualLhs.outerStride(), - actualRhsPtr, 1, + LhsMapper(actualLhs.data(), actualLhs.outerStride()), + RhsMapper(actualRhsPtr, 1), dest.data(), dest.innerStride(), actualAlpha); } @@ -594,7 +598,7 @@ MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const #ifdef EIGEN_DEBUG_PRODUCT internal::product_type<Derived,OtherDerived>::debug(); #endif - + return Product<Derived, OtherDerived>(derived(), other.derived()); } #else diff --git a/Eigen/src/Core/products/GeneralMatrixVector.h b/Eigen/src/Core/products/GeneralMatrixVector.h index 340c51394..7dfa48bfb 100644 --- a/Eigen/src/Core/products/GeneralMatrixVector.h +++ b/Eigen/src/Core/products/GeneralMatrixVector.h @@ -10,7 +10,7 @@ #ifndef EIGEN_GENERAL_MATRIX_VECTOR_H #define EIGEN_GENERAL_MATRIX_VECTOR_H -namespace Eigen { +namespace Eigen { namespace internal { @@ -48,17 +48,17 @@ namespace internal { * // we currently fall back to the NoneAligned case * * The same reasoning apply for the transposed case. - * + * * The last case (PacketSize>4) could probably be improved by generalizing the FirstAligned case, but since we do not support AVX yet... * One might also wonder why in the EvenAligned case we perform unaligned loads instead of using the aligned-loads plus re-alignment * strategy as in the FirstAligned case. The reason is that we observed that unaligned loads on a 8 byte boundary are not too slow * compared to unaligned loads on a 4 byte boundary. * */ -template<typename Index, typename LhsScalar, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs, int Version> -struct general_matrix_vector_product<Index,LhsScalar,ColMajor,ConjugateLhs,RhsScalar,ConjugateRhs,Version> +template<typename Index, typename LhsScalar, typename LhsMapper, bool ConjugateLhs, typename RhsScalar, typename RhsMapper, bool ConjugateRhs, int Version> +struct general_matrix_vector_product<Index,LhsScalar,LhsMapper,ColMajor,ConjugateLhs,RhsScalar,RhsMapper,ConjugateRhs,Version> { -typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar; + typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar; enum { Vectorizable = packet_traits<LhsScalar>::Vectorizable && packet_traits<RhsScalar>::Vectorizable @@ -78,17 +78,17 @@ typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::type ResPacket; EIGEN_DONT_INLINE static void run( Index rows, Index cols, - const LhsScalar* lhs, Index lhsStride, - const RhsScalar* rhs, Index rhsIncr, + const LhsMapper& lhs, + const RhsMapper& rhs, ResScalar* res, Index resIncr, RhsScalar alpha); }; -template<typename Index, typename LhsScalar, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs, int Version> -EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,ColMajor,ConjugateLhs,RhsScalar,ConjugateRhs,Version>::run( +template<typename Index, typename LhsScalar, typename LhsMapper, bool ConjugateLhs, typename RhsScalar, typename RhsMapper, bool ConjugateRhs, int Version> +EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,LhsMapper,ColMajor,ConjugateLhs,RhsScalar,RhsMapper,ConjugateRhs,Version>::run( Index rows, Index cols, - const LhsScalar* lhs, Index lhsStride, - const RhsScalar* rhs, Index rhsIncr, + const LhsMapper& lhs, + const RhsMapper& rhs, ResScalar* res, Index resIncr, RhsScalar alpha) { @@ -97,14 +97,16 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,ColMajor,Co #ifdef _EIGEN_ACCUMULATE_PACKETS #error _EIGEN_ACCUMULATE_PACKETS has already been defined #endif - #define _EIGEN_ACCUMULATE_PACKETS(A0,A13,A2) \ + #define _EIGEN_ACCUMULATE_PACKETS(Alignment0,Alignment13,Alignment2) \ pstore(&res[j], \ padd(pload<ResPacket>(&res[j]), \ padd( \ - padd(pcj.pmul(EIGEN_CAT(ploa , A0)<LhsPacket>(&lhs0[j]), ptmp0), \ - pcj.pmul(EIGEN_CAT(ploa , A13)<LhsPacket>(&lhs1[j]), ptmp1)), \ - padd(pcj.pmul(EIGEN_CAT(ploa , A2)<LhsPacket>(&lhs2[j]), ptmp2), \ - pcj.pmul(EIGEN_CAT(ploa , A13)<LhsPacket>(&lhs3[j]), ptmp3)) ))) + padd(pcj.pmul(lhs0.template load<LhsPacket, Alignment0>(j), ptmp0), \ + pcj.pmul(lhs1.template load<LhsPacket, Alignment13>(j), ptmp1)), \ + padd(pcj.pmul(lhs2.template load<LhsPacket, Alignment2>(j), ptmp2), \ + pcj.pmul(lhs3.template load<LhsPacket, Alignment13>(j), ptmp3)) ))) + + typedef typename LhsMapper::VectorMapper LhsScalars; conj_helper<LhsScalar,RhsScalar,ConjugateLhs,ConjugateRhs> cj; conj_helper<LhsPacket,RhsPacket,ConjugateLhs,ConjugateRhs> pcj; @@ -118,7 +120,9 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,ColMajor,Co const Index ResPacketAlignedMask = ResPacketSize-1; // const Index PeelAlignedMask = ResPacketSize*peels-1; const Index size = rows; - + + const Index lhsStride = lhs.stride(); + // How many coeffs of the result do we have to skip to be aligned. // Here we assume data are at least aligned on the base scalar type. Index alignedStart = internal::first_aligned(res,size); @@ -131,12 +135,12 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,ColMajor,Co : FirstAligned; // we cannot assume the first element is aligned because of sub-matrices - const Index lhsAlignmentOffset = internal::first_aligned(lhs,size); + const Index lhsAlignmentOffset = lhs.firstAligned(size); // find how many columns do we have to skip to be aligned with the result (if possible) Index skipColumns = 0; // if the data cannot be aligned (TODO add some compile time tests when possible, e.g. for floats) - if( (size_t(lhs)%sizeof(LhsScalar)) || (size_t(res)%sizeof(ResScalar)) ) + if( (lhsAlignmentOffset < 0) || (size_t(res)%sizeof(ResScalar)) ) { alignedSize = 0; alignedStart = 0; @@ -149,7 +153,7 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,ColMajor,Co } else if (LhsPacketSize>1) { - eigen_internal_assert(size_t(lhs+lhsAlignmentOffset)%sizeof(LhsPacket)==0 || size<LhsPacketSize); + // eigen_internal_assert(size_t(firstLhs+lhsAlignmentOffset)%sizeof(LhsPacket)==0 || size<LhsPacketSize); while (skipColumns<LhsPacketSize && alignedStart != ((lhsAlignmentOffset + alignmentStep*skipColumns)%LhsPacketSize)) @@ -166,10 +170,10 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,ColMajor,Co // note that the skiped columns are processed later. } - eigen_internal_assert( (alignmentPattern==NoneAligned) + /* eigen_internal_assert( (alignmentPattern==NoneAligned) || (skipColumns + columnsAtOnce >= cols) || LhsPacketSize > size - || (size_t(lhs+alignedStart+lhsStride*skipColumns)%sizeof(LhsPacket))==0); + || (size_t(firstLhs+alignedStart+lhsStride*skipColumns)%sizeof(LhsPacket))==0);*/ } else if(Vectorizable) { @@ -178,20 +182,20 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,ColMajor,Co alignmentPattern = AllAligned; } - Index offset1 = (FirstAligned && alignmentStep==1?3:1); - Index offset3 = (FirstAligned && alignmentStep==1?1:3); + const Index offset1 = (FirstAligned && alignmentStep==1?3:1); + const Index offset3 = (FirstAligned && alignmentStep==1?1:3); Index columnBound = ((cols-skipColumns)/columnsAtOnce)*columnsAtOnce + skipColumns; for (Index i=skipColumns; i<columnBound; i+=columnsAtOnce) { - RhsPacket ptmp0 = pset1<RhsPacket>(alpha*rhs[i*rhsIncr]), - ptmp1 = pset1<RhsPacket>(alpha*rhs[(i+offset1)*rhsIncr]), - ptmp2 = pset1<RhsPacket>(alpha*rhs[(i+2)*rhsIncr]), - ptmp3 = pset1<RhsPacket>(alpha*rhs[(i+offset3)*rhsIncr]); + RhsPacket ptmp0 = pset1<RhsPacket>(alpha*rhs(i, 0)), + ptmp1 = pset1<RhsPacket>(alpha*rhs(i+offset1, 0)), + ptmp2 = pset1<RhsPacket>(alpha*rhs(i+2, 0)), + ptmp3 = pset1<RhsPacket>(alpha*rhs(i+offset3, 0)); // this helps a lot generating better binary code - const LhsScalar *lhs0 = lhs + i*lhsStride, *lhs1 = lhs + (i+offset1)*lhsStride, - *lhs2 = lhs + (i+2)*lhsStride, *lhs3 = lhs + (i+offset3)*lhsStride; + const LhsScalars lhs0 = lhs.getVectorMapper(0, i+0), lhs1 = lhs.getVectorMapper(0, i+offset1), + lhs2 = lhs.getVectorMapper(0, i+2), lhs3 = lhs.getVectorMapper(0, i+offset3); if (Vectorizable) { @@ -199,10 +203,10 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,ColMajor,Co // process initial unaligned coeffs for (Index j=0; j<alignedStart; ++j) { - res[j] = cj.pmadd(lhs0[j], pfirst(ptmp0), res[j]); - res[j] = cj.pmadd(lhs1[j], pfirst(ptmp1), res[j]); - res[j] = cj.pmadd(lhs2[j], pfirst(ptmp2), res[j]); - res[j] = cj.pmadd(lhs3[j], pfirst(ptmp3), res[j]); + res[j] = cj.pmadd(lhs0(j), pfirst(ptmp0), res[j]); + res[j] = cj.pmadd(lhs1(j), pfirst(ptmp1), res[j]); + res[j] = cj.pmadd(lhs2(j), pfirst(ptmp2), res[j]); + res[j] = cj.pmadd(lhs3(j), pfirst(ptmp3), res[j]); } if (alignedSize>alignedStart) @@ -211,11 +215,11 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,ColMajor,Co { case AllAligned: for (Index j = alignedStart; j<alignedSize; j+=ResPacketSize) - _EIGEN_ACCUMULATE_PACKETS(d,d,d); + _EIGEN_ACCUMULATE_PACKETS(Aligned,Aligned,Aligned); break; case EvenAligned: for (Index j = alignedStart; j<alignedSize; j+=ResPacketSize) - _EIGEN_ACCUMULATE_PACKETS(d,du,d); + _EIGEN_ACCUMULATE_PACKETS(Aligned,Unaligned,Aligned); break; case FirstAligned: { @@ -225,28 +229,28 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,ColMajor,Co LhsPacket A00, A01, A02, A03, A10, A11, A12, A13; ResPacket T0, T1; - A01 = pload<LhsPacket>(&lhs1[alignedStart-1]); - A02 = pload<LhsPacket>(&lhs2[alignedStart-2]); - A03 = pload<LhsPacket>(&lhs3[alignedStart-3]); + A01 = lhs1.template load<LhsPacket, Aligned>(alignedStart-1); + A02 = lhs2.template load<LhsPacket, Aligned>(alignedStart-2); + A03 = lhs3.template load<LhsPacket, Aligned>(alignedStart-3); for (; j<peeledSize; j+=peels*ResPacketSize) { - A11 = pload<LhsPacket>(&lhs1[j-1+LhsPacketSize]); palign<1>(A01,A11); - A12 = pload<LhsPacket>(&lhs2[j-2+LhsPacketSize]); palign<2>(A02,A12); - A13 = pload<LhsPacket>(&lhs3[j-3+LhsPacketSize]); palign<3>(A03,A13); + A11 = lhs1.template load<LhsPacket, Aligned>(j-1+LhsPacketSize); palign<1>(A01,A11); + A12 = lhs2.template load<LhsPacket, Aligned>(j-2+LhsPacketSize); palign<2>(A02,A12); + A13 = lhs3.template load<LhsPacket, Aligned>(j-3+LhsPacketSize); palign<3>(A03,A13); - A00 = pload<LhsPacket>(&lhs0[j]); - A10 = pload<LhsPacket>(&lhs0[j+LhsPacketSize]); + A00 = lhs0.template load<LhsPacket, Aligned>(j); + A10 = lhs0.template load<LhsPacket, Aligned>(j+LhsPacketSize); T0 = pcj.pmadd(A00, ptmp0, pload<ResPacket>(&res[j])); T1 = pcj.pmadd(A10, ptmp0, pload<ResPacket>(&res[j+ResPacketSize])); T0 = pcj.pmadd(A01, ptmp1, T0); - A01 = pload<LhsPacket>(&lhs1[j-1+2*LhsPacketSize]); palign<1>(A11,A01); + A01 = lhs1.template load<LhsPacket, Aligned>(j-1+2*LhsPacketSize); palign<1>(A11,A01); T0 = pcj.pmadd(A02, ptmp2, T0); - A02 = pload<LhsPacket>(&lhs2[j-2+2*LhsPacketSize]); palign<2>(A12,A02); + A02 = lhs2.template load<LhsPacket, Aligned>(j-2+2*LhsPacketSize); palign<2>(A12,A02); T0 = pcj.pmadd(A03, ptmp3, T0); pstore(&res[j],T0); - A03 = pload<LhsPacket>(&lhs3[j-3+2*LhsPacketSize]); palign<3>(A13,A03); + A03 = lhs3.template load<LhsPacket, Aligned>(j-3+2*LhsPacketSize); palign<3>(A13,A03); T1 = pcj.pmadd(A11, ptmp1, T1); T1 = pcj.pmadd(A12, ptmp2, T1); T1 = pcj.pmadd(A13, ptmp3, T1); @@ -254,12 +258,12 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,ColMajor,Co } } for (; j<alignedSize; j+=ResPacketSize) - _EIGEN_ACCUMULATE_PACKETS(d,du,du); + _EIGEN_ACCUMULATE_PACKETS(Aligned,Unaligned,Unaligned); break; } default: for (Index j = alignedStart; j<alignedSize; j+=ResPacketSize) - _EIGEN_ACCUMULATE_PACKETS(du,du,du); + _EIGEN_ACCUMULATE_PACKETS(Unaligned,Unaligned,Unaligned); break; } } @@ -268,10 +272,10 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,ColMajor,Co /* process remaining coeffs (or all if there is no explicit vectorization) */ for (Index j=alignedSize; j<size; ++j) { - res[j] = cj.pmadd(lhs0[j], pfirst(ptmp0), res[j]); - res[j] = cj.pmadd(lhs1[j], pfirst(ptmp1), res[j]); - res[j] = cj.pmadd(lhs2[j], pfirst(ptmp2), res[j]); - res[j] = cj.pmadd(lhs3[j], pfirst(ptmp3), res[j]); + res[j] = cj.pmadd(lhs0(j), pfirst(ptmp0), res[j]); + res[j] = cj.pmadd(lhs1(j), pfirst(ptmp1), res[j]); + res[j] = cj.pmadd(lhs2(j), pfirst(ptmp2), res[j]); + res[j] = cj.pmadd(lhs3(j), pfirst(ptmp3), res[j]); } } @@ -282,27 +286,27 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,ColMajor,Co { for (Index k=start; k<end; ++k) { - RhsPacket ptmp0 = pset1<RhsPacket>(alpha*rhs[k*rhsIncr]); - const LhsScalar* lhs0 = lhs + k*lhsStride; + RhsPacket ptmp0 = pset1<RhsPacket>(alpha*rhs(k, 0)); + const LhsScalars lhs0 = lhs.getVectorMapper(0, k); if (Vectorizable) { /* explicit vectorization */ // process first unaligned result's coeffs for (Index j=0; j<alignedStart; ++j) - res[j] += cj.pmul(lhs0[j], pfirst(ptmp0)); + res[j] += cj.pmul(lhs0(j), pfirst(ptmp0)); // process aligned result's coeffs - if ((size_t(lhs0+alignedStart)%sizeof(LhsPacket))==0) + if (lhs0.template aligned<LhsPacket>(alignedStart)) for (Index i = alignedStart;i<alignedSize;i+=ResPacketSize) - pstore(&res[i], pcj.pmadd(pload<LhsPacket>(&lhs0[i]), ptmp0, pload<ResPacket>(&res[i]))); + pstore(&res[i], pcj.pmadd(lhs0.template load<LhsPacket, Aligned>(i), ptmp0, pload<ResPacket>(&res[i]))); else for (Index i = alignedStart;i<alignedSize;i+=ResPacketSize) - pstore(&res[i], pcj.pmadd(ploadu<LhsPacket>(&lhs0[i]), ptmp0, pload<ResPacket>(&res[i]))); + pstore(&res[i], pcj.pmadd(lhs0.template load<LhsPacket, Unaligned>(i), ptmp0, pload<ResPacket>(&res[i]))); } // process remaining scalars (or all if no explicit vectorization) for (Index i=alignedSize; i<size; ++i) - res[i] += cj.pmul(lhs0[i], pfirst(ptmp0)); + res[i] += cj.pmul(lhs0(i), pfirst(ptmp0)); } if (skipColumns) { @@ -326,8 +330,8 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,ColMajor,Co * - alpha is always a complex (or converted to a complex) * - no vectorization */ -template<typename Index, typename LhsScalar, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs, int Version> -struct general_matrix_vector_product<Index,LhsScalar,RowMajor,ConjugateLhs,RhsScalar,ConjugateRhs,Version> +template<typename Index, typename LhsScalar, typename LhsMapper, bool ConjugateLhs, typename RhsScalar, typename RhsMapper, bool ConjugateRhs, int Version> +struct general_matrix_vector_product<Index,LhsScalar,LhsMapper,RowMajor,ConjugateLhs,RhsScalar,RhsMapper,ConjugateRhs,Version> { typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar; @@ -346,67 +350,69 @@ typedef typename packet_traits<ResScalar>::type _ResPacket; typedef typename conditional<Vectorizable,_LhsPacket,LhsScalar>::type LhsPacket; typedef typename conditional<Vectorizable,_RhsPacket,RhsScalar>::type RhsPacket; typedef typename conditional<Vectorizable,_ResPacket,ResScalar>::type ResPacket; - + EIGEN_DONT_INLINE static void run( Index rows, Index cols, - const LhsScalar* lhs, Index lhsStride, - const RhsScalar* rhs, Index rhsIncr, + const LhsMapper& lhs, + const RhsMapper& rhs, ResScalar* res, Index resIncr, ResScalar alpha); }; -template<typename Index, typename LhsScalar, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs, int Version> -EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,RowMajor,ConjugateLhs,RhsScalar,ConjugateRhs,Version>::run( +template<typename Index, typename LhsScalar, typename LhsMapper, bool ConjugateLhs, typename RhsScalar, typename RhsMapper, bool ConjugateRhs, int Version> +EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,LhsMapper,RowMajor,ConjugateLhs,RhsScalar,RhsMapper,ConjugateRhs,Version>::run( Index rows, Index cols, - const LhsScalar* lhs, Index lhsStride, - const RhsScalar* rhs, Index rhsIncr, + const LhsMapper& lhs, + const RhsMapper& rhs, ResScalar* res, Index resIncr, ResScalar alpha) { - EIGEN_UNUSED_VARIABLE(rhsIncr); - eigen_internal_assert(rhsIncr==1); - + eigen_internal_assert(rhs.stride()==1); + #ifdef _EIGEN_ACCUMULATE_PACKETS #error _EIGEN_ACCUMULATE_PACKETS has already been defined #endif - #define _EIGEN_ACCUMULATE_PACKETS(A0,A13,A2) {\ - RhsPacket b = pload<RhsPacket>(&rhs[j]); \ - ptmp0 = pcj.pmadd(EIGEN_CAT(ploa,A0) <LhsPacket>(&lhs0[j]), b, ptmp0); \ - ptmp1 = pcj.pmadd(EIGEN_CAT(ploa,A13)<LhsPacket>(&lhs1[j]), b, ptmp1); \ - ptmp2 = pcj.pmadd(EIGEN_CAT(ploa,A2) <LhsPacket>(&lhs2[j]), b, ptmp2); \ - ptmp3 = pcj.pmadd(EIGEN_CAT(ploa,A13)<LhsPacket>(&lhs3[j]), b, ptmp3); } + #define _EIGEN_ACCUMULATE_PACKETS(Alignment0,Alignment13,Alignment2) {\ + RhsPacket b = rhs.getVectorMapper(j, 0).template load<RhsPacket, Aligned>(0); \ + ptmp0 = pcj.pmadd(lhs0.template load<LhsPacket, Alignment0>(j), b, ptmp0); \ + ptmp1 = pcj.pmadd(lhs1.template load<LhsPacket, Alignment13>(j), b, ptmp1); \ + ptmp2 = pcj.pmadd(lhs2.template load<LhsPacket, Alignment2>(j), b, ptmp2); \ + ptmp3 = pcj.pmadd(lhs3.template load<LhsPacket, Alignment13>(j), b, ptmp3); } conj_helper<LhsScalar,RhsScalar,ConjugateLhs,ConjugateRhs> cj; conj_helper<LhsPacket,RhsPacket,ConjugateLhs,ConjugateRhs> pcj; + typedef typename LhsMapper::VectorMapper LhsScalars; + enum { AllAligned=0, EvenAligned=1, FirstAligned=2, NoneAligned=3 }; const Index rowsAtOnce = 4; const Index peels = 2; const Index RhsPacketAlignedMask = RhsPacketSize-1; const Index LhsPacketAlignedMask = LhsPacketSize-1; -// const Index PeelAlignedMask = RhsPacketSize*peels-1; const Index depth = cols; + const Index lhsStride = lhs.stride(); // How many coeffs of the result do we have to skip to be aligned. // Here we assume data are at least aligned on the base scalar type // if that's not the case then vectorization is discarded, see below. - Index alignedStart = internal::first_aligned(rhs, depth); + Index alignedStart = rhs.firstAligned(depth); Index alignedSize = RhsPacketSize>1 ? alignedStart + ((depth-alignedStart) & ~RhsPacketAlignedMask) : 0; const Index peeledSize = alignedSize - RhsPacketSize*peels - RhsPacketSize + 1; const Index alignmentStep = LhsPacketSize>1 ? (LhsPacketSize - lhsStride % LhsPacketSize) & LhsPacketAlignedMask : 0; Index alignmentPattern = alignmentStep==0 ? AllAligned - : alignmentStep==(LhsPacketSize/2) ? EvenAligned - : FirstAligned; + : alignmentStep==(LhsPacketSize/2) ? EvenAligned + : FirstAligned; // we cannot assume the first element is aligned because of sub-matrices - const Index lhsAlignmentOffset = internal::first_aligned(lhs,depth); + const Index lhsAlignmentOffset = lhs.firstAligned(depth); + const Index rhsAlignmentOffset = rhs.firstAligned(rows); // find how many rows do we have to skip to be aligned with rhs (if possible) Index skipRows = 0; // if the data cannot be aligned (TODO add some compile time tests when possible, e.g. for floats) - if( (sizeof(LhsScalar)!=sizeof(RhsScalar)) || (size_t(lhs)%sizeof(LhsScalar)) || (size_t(rhs)%sizeof(RhsScalar)) ) + if( (sizeof(LhsScalar)!=sizeof(RhsScalar)) || (lhsAlignmentOffset < 0) || (rhsAlignmentOffset < 0) ) { alignedSize = 0; alignedStart = 0; @@ -418,7 +424,7 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,RowMajor,Co } else if (LhsPacketSize>1) { - eigen_internal_assert(size_t(lhs+lhsAlignmentOffset)%sizeof(LhsPacket)==0 || depth<LhsPacketSize); + // eigen_internal_assert(size_t(firstLhs+lhsAlignmentOffset)%sizeof(LhsPacket)==0 || depth<LhsPacketSize); while (skipRows<LhsPacketSize && alignedStart != ((lhsAlignmentOffset + alignmentStep*skipRows)%LhsPacketSize)) @@ -434,11 +440,11 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,RowMajor,Co skipRows = (std::min)(skipRows,Index(rows)); // note that the skiped columns are processed later. } - eigen_internal_assert( alignmentPattern==NoneAligned + /* eigen_internal_assert( alignmentPattern==NoneAligned || LhsPacketSize==1 || (skipRows + rowsAtOnce >= rows) || LhsPacketSize > depth - || (size_t(lhs+alignedStart+lhsStride*skipRows)%sizeof(LhsPacket))==0); + || (size_t(firstLhs+alignedStart+lhsStride*skipRows)%sizeof(LhsPacket))==0);*/ } else if(Vectorizable) { @@ -447,8 +453,8 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,RowMajor,Co alignmentPattern = AllAligned; } - Index offset1 = (FirstAligned && alignmentStep==1?3:1); - Index offset3 = (FirstAligned && alignmentStep==1?1:3); + const Index offset1 = (FirstAligned && alignmentStep==1?3:1); + const Index offset3 = (FirstAligned && alignmentStep==1?1:3); Index rowBound = ((rows-skipRows)/rowsAtOnce)*rowsAtOnce + skipRows; for (Index i=skipRows; i<rowBound; i+=rowsAtOnce) @@ -457,8 +463,8 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,RowMajor,Co ResScalar tmp1 = ResScalar(0), tmp2 = ResScalar(0), tmp3 = ResScalar(0); // this helps the compiler generating good binary code - const LhsScalar *lhs0 = lhs + i*lhsStride, *lhs1 = lhs + (i+offset1)*lhsStride, - *lhs2 = lhs + (i+2)*lhsStride, *lhs3 = lhs + (i+offset3)*lhsStride; + const LhsScalars lhs0 = lhs.getVectorMapper(i+0, 0), lhs1 = lhs.getVectorMapper(i+offset1, 0), + lhs2 = lhs.getVectorMapper(i+2, 0), lhs3 = lhs.getVectorMapper(i+offset3, 0); if (Vectorizable) { @@ -470,9 +476,9 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,RowMajor,Co // FIXME this loop get vectorized by the compiler ! for (Index j=0; j<alignedStart; ++j) { - RhsScalar b = rhs[j]; - tmp0 += cj.pmul(lhs0[j],b); tmp1 += cj.pmul(lhs1[j],b); - tmp2 += cj.pmul(lhs2[j],b); tmp3 += cj.pmul(lhs3[j],b); + RhsScalar b = rhs(j, 0); + tmp0 += cj.pmul(lhs0(j),b); tmp1 += cj.pmul(lhs1(j),b); + tmp2 += cj.pmul(lhs2(j),b); tmp3 += cj.pmul(lhs3(j),b); } if (alignedSize>alignedStart) @@ -481,11 +487,11 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,RowMajor,Co { case AllAligned: for (Index j = alignedStart; j<alignedSize; j+=RhsPacketSize) - _EIGEN_ACCUMULATE_PACKETS(d,d,d); + _EIGEN_ACCUMULATE_PACKETS(Aligned,Aligned,Aligned); break; case EvenAligned: for (Index j = alignedStart; j<alignedSize; j+=RhsPacketSize) - _EIGEN_ACCUMULATE_PACKETS(d,du,d); + _EIGEN_ACCUMULATE_PACKETS(Aligned,Unaligned,Aligned); break; case FirstAligned: { @@ -499,39 +505,39 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,RowMajor,Co * than basic unaligned loads. */ LhsPacket A01, A02, A03, A11, A12, A13; - A01 = pload<LhsPacket>(&lhs1[alignedStart-1]); - A02 = pload<LhsPacket>(&lhs2[alignedStart-2]); - A03 = pload<LhsPacket>(&lhs3[alignedStart-3]); + A01 = lhs1.template load<LhsPacket, Aligned>(alignedStart-1); + A02 = lhs2.template load<LhsPacket, Aligned>(alignedStart-2); + A03 = lhs3.template load<LhsPacket, Aligned>(alignedStart-3); for (; j<peeledSize; j+=peels*RhsPacketSize) { - RhsPacket b = pload<RhsPacket>(&rhs[j]); - A11 = pload<LhsPacket>(&lhs1[j-1+LhsPacketSize]); palign<1>(A01,A11); - A12 = pload<LhsPacket>(&lhs2[j-2+LhsPacketSize]); palign<2>(A02,A12); - A13 = pload<LhsPacket>(&lhs3[j-3+LhsPacketSize]); palign<3>(A03,A13); + RhsPacket b = rhs.getVectorMapper(j, 0).template load<RhsPacket, Aligned>(0); + A11 = lhs1.template load<LhsPacket, Aligned>(j-1+LhsPacketSize); palign<1>(A01,A11); + A12 = lhs2.template load<LhsPacket, Aligned>(j-2+LhsPacketSize); palign<2>(A02,A12); + A13 = lhs3.template load<LhsPacket, Aligned>(j-3+LhsPacketSize); palign<3>(A03,A13); - ptmp0 = pcj.pmadd(pload<LhsPacket>(&lhs0[j]), b, ptmp0); + ptmp0 = pcj.pmadd(lhs0.template load<LhsPacket, Aligned>(j), b, ptmp0); ptmp1 = pcj.pmadd(A01, b, ptmp1); - A01 = pload<LhsPacket>(&lhs1[j-1+2*LhsPacketSize]); palign<1>(A11,A01); + A01 = lhs1.template load<LhsPacket, Aligned>(j-1+2*LhsPacketSize); palign<1>(A11,A01); ptmp2 = pcj.pmadd(A02, b, ptmp2); - A02 = pload<LhsPacket>(&lhs2[j-2+2*LhsPacketSize]); palign<2>(A12,A02); + A02 = lhs2.template load<LhsPacket, Aligned>(j-2+2*LhsPacketSize); palign<2>(A12,A02); ptmp3 = pcj.pmadd(A03, b, ptmp3); - A03 = pload<LhsPacket>(&lhs3[j-3+2*LhsPacketSize]); palign<3>(A13,A03); + A03 = lhs3.template load<LhsPacket, Aligned>(j-3+2*LhsPacketSize); palign<3>(A13,A03); - b = pload<RhsPacket>(&rhs[j+RhsPacketSize]); - ptmp0 = pcj.pmadd(pload<LhsPacket>(&lhs0[j+LhsPacketSize]), b, ptmp0); + b = rhs.getVectorMapper(j+RhsPacketSize, 0).template load<RhsPacket, Aligned>(0); + ptmp0 = pcj.pmadd(lhs0.template load<LhsPacket, Aligned>(j+LhsPacketSize), b, ptmp0); ptmp1 = pcj.pmadd(A11, b, ptmp1); ptmp2 = pcj.pmadd(A12, b, ptmp2); ptmp3 = pcj.pmadd(A13, b, ptmp3); } } for (; j<alignedSize; j+=RhsPacketSize) - _EIGEN_ACCUMULATE_PACKETS(d,du,du); + _EIGEN_ACCUMULATE_PACKETS(Aligned,Unaligned,Unaligned); break; } default: for (Index j = alignedStart; j<alignedSize; j+=RhsPacketSize) - _EIGEN_ACCUMULATE_PACKETS(du,du,du); + _EIGEN_ACCUMULATE_PACKETS(Unaligned,Unaligned,Unaligned); break; } tmp0 += predux(ptmp0); @@ -545,9 +551,9 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,RowMajor,Co // FIXME this loop get vectorized by the compiler ! for (Index j=alignedSize; j<depth; ++j) { - RhsScalar b = rhs[j]; - tmp0 += cj.pmul(lhs0[j],b); tmp1 += cj.pmul(lhs1[j],b); - tmp2 += cj.pmul(lhs2[j],b); tmp3 += cj.pmul(lhs3[j],b); + RhsScalar b = rhs(j, 0); + tmp0 += cj.pmul(lhs0(j),b); tmp1 += cj.pmul(lhs1(j),b); + tmp2 += cj.pmul(lhs2(j),b); tmp3 += cj.pmul(lhs3(j),b); } res[i*resIncr] += alpha*tmp0; res[(i+offset1)*resIncr] += alpha*tmp1; @@ -564,28 +570,28 @@ EIGEN_DONT_INLINE void general_matrix_vector_product<Index,LhsScalar,RowMajor,Co { EIGEN_ALIGN_DEFAULT ResScalar tmp0 = ResScalar(0); ResPacket ptmp0 = pset1<ResPacket>(tmp0); - const LhsScalar* lhs0 = lhs + i*lhsStride; + const LhsScalars lhs0 = lhs.getVectorMapper(i, 0); // process first unaligned result's coeffs // FIXME this loop get vectorized by the compiler ! for (Index j=0; j<alignedStart; ++j) - tmp0 += cj.pmul(lhs0[j], rhs[j]); + tmp0 += cj.pmul(lhs0(j), rhs(j, 0)); if (alignedSize>alignedStart) { // process aligned rhs coeffs - if ((size_t(lhs0+alignedStart)%sizeof(LhsPacket))==0) + if (lhs0.template aligned<LhsPacket>(alignedStart)) for (Index j = alignedStart;j<alignedSize;j+=RhsPacketSize) - ptmp0 = pcj.pmadd(pload<LhsPacket>(&lhs0[j]), pload<RhsPacket>(&rhs[j]), ptmp0); + ptmp0 = pcj.pmadd(lhs0.template load<LhsPacket, Aligned>(j), rhs.getVectorMapper(j, 0).template load<RhsPacket, Aligned>(0), ptmp0); else for (Index j = alignedStart;j<alignedSize;j+=RhsPacketSize) - ptmp0 = pcj.pmadd(ploadu<LhsPacket>(&lhs0[j]), pload<RhsPacket>(&rhs[j]), ptmp0); + ptmp0 = pcj.pmadd(lhs0.template load<LhsPacket, Unaligned>(j), rhs.getVectorMapper(j, 0).template load<RhsPacket, Aligned>(0), ptmp0); tmp0 += predux(ptmp0); } // process remaining scalars // FIXME this loop get vectorized by the compiler ! for (Index j=alignedSize; j<depth; ++j) - tmp0 += cj.pmul(lhs0[j], rhs[j]); + tmp0 += cj.pmul(lhs0(j), rhs(j, 0)); res[i*resIncr] += alpha*tmp0; } if (skipRows) diff --git a/Eigen/src/Core/products/TriangularMatrixVector.h b/Eigen/src/Core/products/TriangularMatrixVector.h index 817768481..d33e3f409 100644 --- a/Eigen/src/Core/products/TriangularMatrixVector.h +++ b/Eigen/src/Core/products/TriangularMatrixVector.h @@ -10,7 +10,7 @@ #ifndef EIGEN_TRIANGULARMATRIXVECTOR_H #define EIGEN_TRIANGULARMATRIXVECTOR_H -namespace Eigen { +namespace Eigen { namespace internal { @@ -43,7 +43,7 @@ EIGEN_DONT_INLINE void triangular_matrix_vector_product<Index,Mode,LhsScalar,Con typedef Map<const Matrix<LhsScalar,Dynamic,Dynamic,ColMajor>, 0, OuterStride<> > LhsMap; const LhsMap lhs(_lhs,rows,cols,OuterStride<>(lhsStride)); typename conj_expr_if<ConjLhs,LhsMap>::type cjLhs(lhs); - + typedef Map<const Matrix<RhsScalar,Dynamic,1>, 0, InnerStride<> > RhsMap; const RhsMap rhs(_rhs,cols,InnerStride<>(rhsIncr)); typename conj_expr_if<ConjRhs,RhsMap>::type cjRhs(rhs); @@ -51,6 +51,9 @@ EIGEN_DONT_INLINE void triangular_matrix_vector_product<Index,Mode,LhsScalar,Con typedef Map<Matrix<ResScalar,Dynamic,1> > ResMap; ResMap res(_res,rows); + typedef const_blas_data_mapper<LhsScalar,Index,ColMajor> LhsMapper; + typedef const_blas_data_mapper<RhsScalar,Index,RowMajor> RhsMapper; + for (Index pi=0; pi<size; pi+=PanelWidth) { Index actualPanelWidth = (std::min)(PanelWidth, size-pi); @@ -68,19 +71,19 @@ EIGEN_DONT_INLINE void triangular_matrix_vector_product<Index,Mode,LhsScalar,Con if (r>0) { Index s = IsLower ? pi+actualPanelWidth : 0; - general_matrix_vector_product<Index,LhsScalar,ColMajor,ConjLhs,RhsScalar,ConjRhs,BuiltIn>::run( + general_matrix_vector_product<Index,LhsScalar,LhsMapper,ColMajor,ConjLhs,RhsScalar,RhsMapper,ConjRhs,BuiltIn>::run( r, actualPanelWidth, - &lhs.coeffRef(s,pi), lhsStride, - &rhs.coeffRef(pi), rhsIncr, + LhsMapper(&lhs.coeffRef(s,pi), lhsStride), + RhsMapper(&rhs.coeffRef(pi), rhsIncr), &res.coeffRef(s), resIncr, alpha); } } if((!IsLower) && cols>size) { - general_matrix_vector_product<Index,LhsScalar,ColMajor,ConjLhs,RhsScalar,ConjRhs>::run( + general_matrix_vector_product<Index,LhsScalar,LhsMapper,ColMajor,ConjLhs,RhsScalar,RhsMapper,ConjRhs>::run( rows, cols-size, - &lhs.coeffRef(0,size), lhsStride, - &rhs.coeffRef(size), rhsIncr, + LhsMapper(&lhs.coeffRef(0,size), lhsStride), + RhsMapper(&rhs.coeffRef(size), rhsIncr), _res, resIncr, alpha); } } @@ -118,7 +121,10 @@ EIGEN_DONT_INLINE void triangular_matrix_vector_product<Index,Mode,LhsScalar,Con typedef Map<Matrix<ResScalar,Dynamic,1>, 0, InnerStride<> > ResMap; ResMap res(_res,rows,InnerStride<>(resIncr)); - + + typedef const_blas_data_mapper<LhsScalar,Index,RowMajor> LhsMapper; + typedef const_blas_data_mapper<RhsScalar,Index,RowMajor> RhsMapper; + for (Index pi=0; pi<diagSize; pi+=PanelWidth) { Index actualPanelWidth = (std::min)(PanelWidth, diagSize-pi); @@ -136,19 +142,19 @@ EIGEN_DONT_INLINE void triangular_matrix_vector_product<Index,Mode,LhsScalar,Con if (r>0) { Index s = IsLower ? 0 : pi + actualPanelWidth; - general_matrix_vector_product<Index,LhsScalar,RowMajor,ConjLhs,RhsScalar,ConjRhs,BuiltIn>::run( + general_matrix_vector_product<Index,LhsScalar,LhsMapper,RowMajor,ConjLhs,RhsScalar,RhsMapper,ConjRhs,BuiltIn>::run( actualPanelWidth, r, - &lhs.coeffRef(pi,s), lhsStride, - &rhs.coeffRef(s), rhsIncr, + LhsMapper(&lhs.coeffRef(pi,s), lhsStride), + RhsMapper(&rhs.coeffRef(s), rhsIncr), &res.coeffRef(pi), resIncr, alpha); } } if(IsLower && rows>diagSize) { - general_matrix_vector_product<Index,LhsScalar,RowMajor,ConjLhs,RhsScalar,ConjRhs>::run( + general_matrix_vector_product<Index,LhsScalar,LhsMapper,RowMajor,ConjLhs,RhsScalar,RhsMapper,ConjRhs>::run( rows-diagSize, cols, - &lhs.coeffRef(diagSize,0), lhsStride, - &rhs.coeffRef(0), rhsIncr, + LhsMapper(&lhs.coeffRef(diagSize,0), lhsStride), + RhsMapper(&rhs.coeffRef(0), rhsIncr), &res.coeffRef(diagSize), resIncr, alpha); } } @@ -184,7 +190,7 @@ struct TriangularProduct<Mode,true,Lhs,false,Rhs,true> template<typename Dest> void scaleAndAddTo(Dest& dst, const Scalar& alpha) const { eigen_assert(dst.rows()==m_lhs.rows() && dst.cols()==m_rhs.cols()); - + internal::trmv_selector<(int(internal::traits<Lhs>::Flags)&RowMajorBit) ? RowMajor : ColMajor>::run(*this, dst, alpha); } }; @@ -211,7 +217,7 @@ struct TriangularProduct<Mode,false,Lhs,true,Rhs,false> namespace internal { // TODO: find a way to factorize this piece of code with gemv_selector since the logic is exactly the same. - + template<> struct trmv_selector<ColMajor> { template<int Mode, typename Lhs, typename Rhs, typename Dest> @@ -247,7 +253,7 @@ template<> struct trmv_selector<ColMajor> bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0)); bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible; - + RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha); ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(), @@ -267,7 +273,7 @@ template<> struct trmv_selector<ColMajor> else MappedDest(actualDestPtr, dest.size()) = dest; } - + internal::triangular_matrix_vector_product <Index,Mode, LhsScalar, LhsBlasTraits::NeedToConjugate, @@ -327,7 +333,7 @@ template<> struct trmv_selector<RowMajor> #endif Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs; } - + internal::triangular_matrix_vector_product <Index,Mode, LhsScalar, LhsBlasTraits::NeedToConjugate, diff --git a/Eigen/src/Core/products/TriangularSolverVector.h b/Eigen/src/Core/products/TriangularSolverVector.h index ce4d10088..b994759b2 100644 --- a/Eigen/src/Core/products/TriangularSolverVector.h +++ b/Eigen/src/Core/products/TriangularSolverVector.h @@ -10,7 +10,7 @@ #ifndef EIGEN_TRIANGULAR_SOLVER_VECTOR_H #define EIGEN_TRIANGULAR_SOLVER_VECTOR_H -namespace Eigen { +namespace Eigen { namespace internal { @@ -25,7 +25,7 @@ struct triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheRight, Mode, Co >::run(size, _lhs, lhsStride, rhs); } }; - + // forward and backward substitution, row-major, rhs is a vector template<typename LhsScalar, typename RhsScalar, typename Index, int Mode, bool Conjugate> struct triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheLeft, Mode, Conjugate, RowMajor> @@ -37,6 +37,10 @@ struct triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheLeft, Mode, Con { typedef Map<const Matrix<LhsScalar,Dynamic,Dynamic,RowMajor>, 0, OuterStride<> > LhsMap; const LhsMap lhs(_lhs,size,size,OuterStride<>(lhsStride)); + + typedef const_blas_data_mapper<LhsScalar,Index,RowMajor> LhsMapper; + typedef const_blas_data_mapper<RhsScalar,Index,ColMajor> RhsMapper; + typename internal::conditional< Conjugate, const CwiseUnaryOp<typename internal::scalar_conjugate_op<LhsScalar>,LhsMap>, @@ -58,10 +62,10 @@ struct triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheLeft, Mode, Con Index startRow = IsLower ? pi : pi-actualPanelWidth; Index startCol = IsLower ? 0 : pi; - general_matrix_vector_product<Index,LhsScalar,RowMajor,Conjugate,RhsScalar,false>::run( + general_matrix_vector_product<Index,LhsScalar,LhsMapper,RowMajor,Conjugate,RhsScalar,RhsMapper,false>::run( actualPanelWidth, r, - &lhs.coeffRef(startRow,startCol), lhsStride, - rhs + startCol, 1, + LhsMapper(&lhs.coeffRef(startRow,startCol), lhsStride), + RhsMapper(rhs + startCol, 1), rhs + startRow, 1, RhsScalar(-1)); } @@ -72,7 +76,7 @@ struct triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheLeft, Mode, Con Index s = IsLower ? pi : i+1; if (k>0) rhs[i] -= (cjLhs.row(i).segment(s,k).transpose().cwiseProduct(Map<const Matrix<RhsScalar,Dynamic,1> >(rhs+s,k))).sum(); - + if(!(Mode & UnitDiag)) rhs[i] /= cjLhs(i,i); } @@ -91,6 +95,8 @@ struct triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheLeft, Mode, Con { typedef Map<const Matrix<LhsScalar,Dynamic,Dynamic,ColMajor>, 0, OuterStride<> > LhsMap; const LhsMap lhs(_lhs,size,size,OuterStride<>(lhsStride)); + typedef const_blas_data_mapper<LhsScalar,Index,ColMajor> LhsMapper; + typedef const_blas_data_mapper<RhsScalar,Index,ColMajor> RhsMapper; typename internal::conditional<Conjugate, const CwiseUnaryOp<typename internal::scalar_conjugate_op<LhsScalar>,LhsMap>, const LhsMap& @@ -122,10 +128,10 @@ struct triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheLeft, Mode, Con // let's directly call the low level product function because: // 1 - it is faster to compile // 2 - it is slighlty faster at runtime - general_matrix_vector_product<Index,LhsScalar,ColMajor,Conjugate,RhsScalar,false>::run( + general_matrix_vector_product<Index,LhsScalar,LhsMapper,ColMajor,Conjugate,RhsScalar,RhsMapper,false>::run( r, actualPanelWidth, - &lhs.coeffRef(endBlock,startBlock), lhsStride, - rhs+startBlock, 1, + LhsMapper(&lhs.coeffRef(endBlock,startBlock), lhsStride), + RhsMapper(rhs+startBlock, 1), rhs+endBlock, 1, RhsScalar(-1)); } } diff --git a/Eigen/src/Core/util/BlasUtil.h b/Eigen/src/Core/util/BlasUtil.h index 25a62d528..c4881b8da 100644 --- a/Eigen/src/Core/util/BlasUtil.h +++ b/Eigen/src/Core/util/BlasUtil.h @@ -34,7 +34,9 @@ template< int ResStorageOrder> struct general_matrix_matrix_product; -template<typename Index, typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs, int Version=Specialized> +template<typename Index, + typename LhsScalar, typename LhsMapper, int LhsStorageOrder, bool ConjugateLhs, + typename RhsScalar, typename RhsMapper, bool ConjugateRhs, int Version=Specialized> struct general_matrix_vector_product; @@ -118,13 +120,35 @@ template<typename Scalar> struct get_factor<Scalar,typename NumTraits<Scalar>::R }; +template<typename Scalar, typename Index> +class BlasVectorMapper { + public: + EIGEN_ALWAYS_INLINE BlasVectorMapper(Scalar *data) : m_data(data) {} + + EIGEN_ALWAYS_INLINE Scalar operator()(Index i) const { + return m_data[i]; + } + template <typename Packet, int AlignmentType> + EIGEN_ALWAYS_INLINE Packet load(Index i) const { + return ploadt<Packet, AlignmentType>(m_data + i); + } + + template <typename Packet> + bool aligned(Index i) const { + return (size_t(m_data+i)%sizeof(Packet))==0; + } + + protected: + Scalar* m_data; +}; + template<typename Scalar, typename Index, int AlignmentType> -class MatrixLinearMapper { +class BlasLinearMapper { public: typedef typename packet_traits<Scalar>::type Packet; typedef typename packet_traits<Scalar>::half HalfPacket; - EIGEN_ALWAYS_INLINE MatrixLinearMapper(Scalar *data) : m_data(data) {} + EIGEN_ALWAYS_INLINE BlasLinearMapper(Scalar *data) : m_data(data) {} EIGEN_ALWAYS_INLINE void prefetch(int i) const { internal::prefetch(&operator()(i)); @@ -157,7 +181,8 @@ class blas_data_mapper { typedef typename packet_traits<Scalar>::type Packet; typedef typename packet_traits<Scalar>::half HalfPacket; - typedef MatrixLinearMapper<Scalar, Index, AlignmentType> LinearMapper; + typedef BlasLinearMapper<Scalar, Index, AlignmentType> LinearMapper; + typedef BlasVectorMapper<Scalar, Index> VectorMapper; EIGEN_ALWAYS_INLINE blas_data_mapper(Scalar* data, Index stride) : m_data(data), m_stride(stride) {} @@ -170,6 +195,11 @@ class blas_data_mapper { return LinearMapper(&operator()(i, j)); } + EIGEN_ALWAYS_INLINE VectorMapper getVectorMapper(Index i, Index j) const { + return VectorMapper(&operator()(i, j)); + } + + EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Scalar& operator()(Index i, Index j) const { return m_data[StorageOrder==RowMajor ? j + i*m_stride : i + j*m_stride]; @@ -193,6 +223,15 @@ class blas_data_mapper { return pgather<Scalar, SubPacket>(&operator()(i, j), m_stride); } + const Index stride() const { return m_stride; } + + Index firstAligned(Index size) const { + if (size_t(m_data)%sizeof(Scalar)) { + return -1; + } + return internal::first_aligned(m_data, size); + } + protected: Scalar* EIGEN_RESTRICT m_data; const Index m_stride; |