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Remove the rotating kernel. It was only useful on some ARM CPUs (Qualcomm Krait) that are not as ubiquitous today as they were when I introduced it.
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e617711306
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6136f4fdd4
@ -860,80 +860,6 @@ protected:
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conj_helper<ResPacket,ResPacket,false,ConjRhs> cj;
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};
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// helper for the rotating kernel below
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template <typename GebpKernel, bool UseRotatingKernel = GebpKernel::UseRotatingKernel>
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struct PossiblyRotatingKernelHelper
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{
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// default implementation, not rotating
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typedef typename GebpKernel::Traits Traits;
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typedef typename Traits::RhsScalar RhsScalar;
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typedef typename Traits::RhsPacket RhsPacket;
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typedef typename Traits::AccPacket AccPacket;
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const Traits& traits;
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PossiblyRotatingKernelHelper(const Traits& t) : traits(t) {}
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template <size_t K, size_t Index>
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void loadOrRotateRhs(RhsPacket& to, const RhsScalar* from) const
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{
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traits.loadRhs(from + (Index+4*K)*Traits::RhsProgress, to);
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}
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void unrotateResult(AccPacket&,
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AccPacket&,
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AccPacket&,
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AccPacket&)
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{
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}
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};
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// rotating implementation
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template <typename GebpKernel>
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struct PossiblyRotatingKernelHelper<GebpKernel, true>
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{
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typedef typename GebpKernel::Traits Traits;
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typedef typename Traits::RhsScalar RhsScalar;
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typedef typename Traits::RhsPacket RhsPacket;
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typedef typename Traits::AccPacket AccPacket;
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const Traits& traits;
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PossiblyRotatingKernelHelper(const Traits& t) : traits(t) {}
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template <size_t K, size_t Index>
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void loadOrRotateRhs(RhsPacket& to, const RhsScalar* from) const
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{
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if (Index == 0) {
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to = pload<RhsPacket>(from + 4*K*Traits::RhsProgress);
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} else {
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EIGEN_ASM_COMMENT("Do not reorder code, we're very tight on registers");
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to = protate<1>(to);
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}
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}
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void unrotateResult(AccPacket& res0,
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AccPacket& res1,
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AccPacket& res2,
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AccPacket& res3)
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{
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PacketBlock<AccPacket> resblock;
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resblock.packet[0] = res0;
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resblock.packet[1] = res1;
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resblock.packet[2] = res2;
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resblock.packet[3] = res3;
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ptranspose(resblock);
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resblock.packet[3] = protate<1>(resblock.packet[3]);
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resblock.packet[2] = protate<2>(resblock.packet[2]);
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resblock.packet[1] = protate<3>(resblock.packet[1]);
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ptranspose(resblock);
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res0 = resblock.packet[0];
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res1 = resblock.packet[1];
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res2 = resblock.packet[2];
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res3 = resblock.packet[3];
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}
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};
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/* optimized GEneral packed Block * packed Panel product kernel
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*
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* Mixing type logic: C += A * B
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@ -967,16 +893,6 @@ struct gebp_kernel
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ResPacketSize = Traits::ResPacketSize
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};
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static const bool UseRotatingKernel =
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EIGEN_ARCH_ARM &&
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internal::is_same<LhsScalar, float>::value &&
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internal::is_same<RhsScalar, float>::value &&
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internal::is_same<ResScalar, float>::value &&
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Traits::LhsPacketSize == 4 &&
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Traits::RhsPacketSize == 4 &&
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Traits::ResPacketSize == 4;
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EIGEN_DONT_INLINE
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void operator()(const DataMapper& res, const LhsScalar* blockA, const RhsScalar* blockB,
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Index rows, Index depth, Index cols, ResScalar alpha,
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@ -1009,9 +925,7 @@ void gebp_kernel<LhsScalar,RhsScalar,Index,DataMapper,mr,nr,ConjugateLhs,Conjuga
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// This corresponds to 3*LhsProgress x nr register blocks.
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// Usually, make sense only with FMA
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if(mr>=3*Traits::LhsProgress)
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{
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PossiblyRotatingKernelHelper<gebp_kernel> possiblyRotatingKernelHelper(traits);
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{
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// Here, the general idea is to loop on each largest micro horizontal panel of the lhs (3*Traits::LhsProgress x depth)
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// and on each largest micro vertical panel of the rhs (depth * nr).
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// Blocking sizes, i.e., 'depth' has been computed so that the micro horizontal panel of the lhs fit in L1.
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@ -1074,19 +988,19 @@ void gebp_kernel<LhsScalar,RhsScalar,Index,DataMapper,mr,nr,ConjugateLhs,Conjuga
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traits.loadLhs(&blA[(0+3*K)*LhsProgress], A0); \
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traits.loadLhs(&blA[(1+3*K)*LhsProgress], A1); \
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traits.loadLhs(&blA[(2+3*K)*LhsProgress], A2); \
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possiblyRotatingKernelHelper.template loadOrRotateRhs<K, 0>(B_0, blB); \
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traits.loadRhs(blB + (0+4*K)*Traits::RhsProgress, B_0); \
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traits.madd(A0, B_0, C0, T0); \
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traits.madd(A1, B_0, C4, T0); \
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traits.madd(A2, B_0, C8, B_0); \
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possiblyRotatingKernelHelper.template loadOrRotateRhs<K, 1>(B_0, blB); \
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traits.loadRhs(blB + (1+4*K)*Traits::RhsProgress, B_0); \
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traits.madd(A0, B_0, C1, T0); \
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traits.madd(A1, B_0, C5, T0); \
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traits.madd(A2, B_0, C9, B_0); \
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possiblyRotatingKernelHelper.template loadOrRotateRhs<K, 2>(B_0, blB); \
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traits.loadRhs(blB + (2+4*K)*Traits::RhsProgress, B_0); \
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traits.madd(A0, B_0, C2, T0); \
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traits.madd(A1, B_0, C6, T0); \
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traits.madd(A2, B_0, C10, B_0); \
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possiblyRotatingKernelHelper.template loadOrRotateRhs<K, 3>(B_0, blB); \
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traits.loadRhs(blB + (3+4*K)*Traits::RhsProgress, B_0); \
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traits.madd(A0, B_0, C3 , T0); \
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traits.madd(A1, B_0, C7, T0); \
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traits.madd(A2, B_0, C11, B_0); \
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@ -1120,10 +1034,6 @@ void gebp_kernel<LhsScalar,RhsScalar,Index,DataMapper,mr,nr,ConjugateLhs,Conjuga
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#undef EIGEN_GEBP_ONESTEP
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possiblyRotatingKernelHelper.unrotateResult(C0, C1, C2, C3);
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possiblyRotatingKernelHelper.unrotateResult(C4, C5, C6, C7);
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possiblyRotatingKernelHelper.unrotateResult(C8, C9, C10, C11);
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ResPacket R0, R1, R2;
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ResPacket alphav = pset1<ResPacket>(alpha);
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