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@ -255,20 +255,11 @@ EIGEN_DEVICE_FUNC EIGEN_DONT_INLINE void general_matrix_vector_product<Index,Lhs
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conj_helper<LhsScalar,RhsScalar,ConjugateLhs,ConjugateRhs> cj;
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conj_helper<LhsPacket,RhsPacket,ConjugateLhs,ConjugateRhs> pcj;
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// TODO: fine tune the following heuristic. The rationale is that if the
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// matrix is very large, processing multiple rows at once might be counter
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// productive wrt cache.
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#if EIGEN_ARCH_ARM_OR_ARM64
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// This threshold was empirically determined using a Pixel2.
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// The little cores are a lot more sensitive to this number
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// than the big cores.
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const Index cache_threshold = 1024;
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#else
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const Index cache_threshold = 1024 * 256;
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#endif
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const Index row_bytes = lhs.stride() * sizeof(LhsScalar);
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const Index n8 = (8 * row_bytes > cache_threshold) ? 0 : (rows - 7);
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// TODO: fine tune the following heuristic. The rationale is that if the matrix is very large,
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// processing 8 rows at once might be counter productive wrt cache.
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const Index n8 = lhs.stride()*sizeof(LhsScalar)>32000 ? 0 : rows-7;
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const Index n4 = rows-3;
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const Index n2 = rows-1;
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// TODO: for padded aligned inputs, we could enable aligned reads
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enum { LhsAlignment = Unaligned };
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@ -329,9 +320,6 @@ EIGEN_DEVICE_FUNC EIGEN_DONT_INLINE void general_matrix_vector_product<Index,Lhs
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res[(i+6)*resIncr] += alpha*cc6;
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res[(i+7)*resIncr] += alpha*cc7;
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}
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if (i == rows) return;
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const Index n4 = (4 * row_bytes > cache_threshold) ? 0 : (rows - 3);
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for(; i<n4; i+=4)
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{
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ResPacket c0 = pset1<ResPacket>(ResScalar(0)),
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@ -367,9 +355,6 @@ EIGEN_DEVICE_FUNC EIGEN_DONT_INLINE void general_matrix_vector_product<Index,Lhs
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res[(i+2)*resIncr] += alpha*cc2;
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res[(i+3)*resIncr] += alpha*cc3;
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}
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if (i == rows) return;
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const Index n2 = (2 * row_bytes > cache_threshold) ? 0 : (rows - 1);
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for(; i<n2; i+=2)
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{
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ResPacket c0 = pset1<ResPacket>(ResScalar(0)),
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