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Copy pathparallelize.patch
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197 lines (192 loc) · 8.63 KB
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diff --git a/Eigen/src/Core/products/GeneralBlockPanelKernel.h b/Eigen/src/Core/products/GeneralBlockPanelKernel.h
index 922cbf92e..869a76077 100644
--- a/Eigen/src/Core/products/GeneralBlockPanelKernel.h
+++ b/Eigen/src/Core/products/GeneralBlockPanelKernel.h
@@ -1500,22 +1500,24 @@ EIGEN_DONT_INLINE void gebp_kernel<LhsScalar, RhsScalar, Index, DataMapper, mr,
for (Index i1 = 0; i1 < peeled_mc3; i1 += actual_panel_rows) {
const Index actual_panel_end = (std::min)(i1 + actual_panel_rows, peeled_mc3);
EIGEN_IF_CONSTEXPR (nr >= 8) {
- for (Index j2 = 0; j2 < packet_cols8; j2 += 8) {
+ tbb::parallel_for(Index(0), packet_cols8 / 8, [&](Index j2) {
+ j2 *= 8;
for (Index i = i1; i < actual_panel_end; i += 3 * LhsProgress) {
micro_panel(fix<3>, fix<8>, traits, i, j2);
}
- }
+ });
}
- for (Index j2 = packet_cols8; j2 < packet_cols4; j2 += 4) {
+ tbb::parallel_for(packet_cols8 / 4, packet_cols4 / 4, [&](Index j2) {
+ j2 *= 4;
for (Index i = i1; i < actual_panel_end; i += 3 * LhsProgress) {
micro_panel(fix<3>, fix<4>, traits, i, j2);
}
- }
- for (Index j2 = packet_cols4; j2 < cols; j2++) {
+ });
+ tbb::parallel_for(packet_cols4, cols, [&](Index j2) {
for (Index i = i1; i < actual_panel_end; i += 3 * LhsProgress) {
micro_panel(fix<3>, fix<1>, traits, i, j2);
}
- }
+ });
}
}
@@ -1531,22 +1533,24 @@ EIGEN_DONT_INLINE void gebp_kernel<LhsScalar, RhsScalar, Index, DataMapper, mr,
for (Index i1 = peeled_mc3; i1 < peeled_mc2; i1 += actual_panel_rows) {
Index actual_panel_end = (std::min)(i1 + actual_panel_rows, peeled_mc2);
EIGEN_IF_CONSTEXPR (nr >= 8) {
- for (Index j2 = 0; j2 < packet_cols8; j2 += 8) {
+ tbb::parallel_for(Index(0), packet_cols8 / 8, [&](Index j2) {
+ j2 *= 8;
for (Index i = i1; i < actual_panel_end; i += 2 * LhsProgress) {
micro_panel(fix<2>, fix<8>, traits, i, j2);
}
- }
+ });
}
- for (Index j2 = packet_cols8; j2 < packet_cols4; j2 += 4) {
+ tbb::parallel_for(packet_cols8 / 4, packet_cols4 / 4, [&](Index j2) {
+ j2 *= 4;
for (Index i = i1; i < actual_panel_end; i += 2 * LhsProgress) {
micro_panel(fix<2>, fix<4>, traits, i, j2);
}
- }
- for (Index j2 = packet_cols4; j2 < cols; j2++) {
+ });
+ tbb::parallel_for(packet_cols4, cols, [&](Index j2) {
for (Index i = i1; i < actual_panel_end; i += 2 * LhsProgress) {
micro_panel(fix<2>, fix<1>, traits, i, j2);
}
- }
+ });
}
}
@@ -1554,16 +1558,16 @@ EIGEN_DONT_INLINE void gebp_kernel<LhsScalar, RhsScalar, Index, DataMapper, mr,
EIGEN_IF_CONSTEXPR (mr >= 1 * Traits::LhsProgress) {
for (Index i = peeled_mc2; i < peeled_mc1; i += LhsProgress) {
EIGEN_IF_CONSTEXPR (nr >= 8) {
- for (Index j2 = 0; j2 < packet_cols8; j2 += 8) {
+ tbb::parallel_for(Index(0), packet_cols8 / 8, [&](Index j2) {
+ j2 *= 8;
micro_panel(fix<1>, fix<8>, traits, i, j2);
- }
+ });
}
- for (Index j2 = packet_cols8; j2 < packet_cols4; j2 += 4) {
+ tbb::parallel_for(packet_cols8 / 4, packet_cols4 / 4, [&](Index j2) {
+ j2 *= 4;
micro_panel(fix<1>, fix<4>, traits, i, j2);
- }
- for (Index j2 = packet_cols4; j2 < cols; j2++) {
- micro_panel(fix<1>, fix<1>, traits, i, j2);
- }
+ });
+ tbb::parallel_for(packet_cols4, cols, [&](Index j2) { micro_panel(fix<1>, fix<1>, traits, i, j2); });
}
}
diff --git a/Eigen/src/Core/products/GeneralMatrixVector.h b/Eigen/src/Core/products/GeneralMatrixVector.h
index 2c972382c..d2b07ea64 100644
--- a/Eigen/src/Core/products/GeneralMatrixVector.h
+++ b/Eigen/src/Core/products/GeneralMatrixVector.h
@@ -225,7 +225,21 @@ general_matrix_vector_product<Index, LhsScalar, LhsMapper, ColMajor, ConjugateLh
for (Index j2 = 0; j2 < cols; j2 += block_cols) {
Index jend = numext::mini(j2 + block_cols, cols);
Index i = 0;
- for (; i < n8; i += ResPacketSize * 8) process_rows<8>(i, j2, jend, lhs, rhs, res, palpha, pcj);
+ for (; i < n8; i += ResPacketSize * 8)
+ for (auto x = 0; x < 8; ++x) {
+ const auto offset = i + ResPacketSize * x;
+ pstoreu(res + offset, pmadd(tbb::parallel_deterministic_reduce(
+ tbb::blocked_range<Index>(j2, jend), pzero(ResPacket{}),
+ [&](const tbb::blocked_range<Index>& r, ResPacket running_total) {
+ for (auto j = r.begin(); j < r.end(); ++j)
+ running_total += pcj.pmul(
+ lhs.template load<LhsPacket, LhsAlignment>(i + LhsPacketSize * x, j),
+ pset1<RhsPacket>(rhs(j, 0)));
+ return running_total;
+ },
+ std::plus<>()),
+ palpha, ploadu<ResPacket>(res + offset)));
+ }
if (i < n4) {
process_rows<4>(i, j2, jend, lhs, rhs, res, palpha, pcj);
i += ResPacketSize * 4;
diff --git a/Eigen/src/SVD/BDCSVDImpl.h b/Eigen/src/SVD/BDCSVDImpl.h
index dd50a6806..e8b93b9a3 100644
--- a/Eigen/src/SVD/BDCSVDImpl.h
+++ b/Eigen/src/SVD/BDCSVDImpl.h
@@ -371,6 +371,16 @@ typename bdcsvd_impl<RealScalar_>::RealScalar bdcsvd_impl<RealScalar_>::secularE
const IndicesRef& perm,
const ArrayRef& diagShifted,
RealScalar shift) {
+ return tbb::parallel_deterministic_reduce(
+ tbb::blocked_range<Index>(Index(0), perm.size()), RealScalar(1),
+ [&](const tbb::blocked_range<Index>& r, RealScalar running_total) {
+ for (auto i = r.begin(); i < r.end(); ++i) {
+ const Index j = perm(i);
+ running_total += (col0(j) / (diagShifted(j) - mu)) * (col0(j) / (diag(j) + shift + mu));
+ }
+ return running_total;
+ },
+ std::plus<>());
Index m = perm.size();
RealScalar res = Literal(1);
for (Index i = 0; i < m; ++i) {
@@ -606,6 +616,8 @@ template <typename RealScalar_>
void bdcsvd_impl<RealScalar_>::computeSingVecs(const ArrayRef& zhat, const ArrayRef& diag, const IndicesRef& perm,
const VectorType& singVals, const ArrayRef& shifts, const ArrayRef& mus,
MatrixXr& U, MatrixXr& V) {
+ static tbb::affinity_partitioner ap;
+
Index n = zhat.size();
Index m = perm.size();
@@ -615,27 +627,33 @@ void bdcsvd_impl<RealScalar_>::computeSingVecs(const ArrayRef& zhat, const Array
if (m_compV) V.col(k) = VectorType::Unit(n, k);
} else {
U.col(k).setZero();
- for (Index l = 0; l < m; ++l) {
- Index i = perm(l);
- RealScalar diff = diag(i) - shifts(k);
- EIGEN_OPTIMIZATION_BARRIER(diff)
- diff -= mus(k);
- EIGEN_OPTIMIZATION_BARRIER(diff)
- U(i, k) = zhat(i) / diff / ((diag(i) + singVals[k]));
- }
+ tbb::parallel_for(
+ Index(0), m,
+ [&](const Index l) {
+ Index i = perm(l);
+ RealScalar diff = diag(i) - shifts(k);
+ EIGEN_OPTIMIZATION_BARRIER(diff)
+ diff -= mus(k);
+ EIGEN_OPTIMIZATION_BARRIER(diff)
+ U(i, k) = zhat(i) / diff / ((diag(i) + singVals[k]));
+ },
+ ap);
U(n, k) = Literal(0);
U.col(k).normalize();
if (m_compV) {
V.col(k).setZero();
- for (Index l = 1; l < m; ++l) {
- Index i = perm(l);
- RealScalar diff = diag(i) - shifts(k);
- EIGEN_OPTIMIZATION_BARRIER(diff)
- diff -= mus(k);
- EIGEN_OPTIMIZATION_BARRIER(diff)
- V(i, k) = diag(i) * zhat(i) / diff / ((diag(i) + singVals[k]));
- }
+ tbb::parallel_for(
+ Index(1), m,
+ [&](const Index l) {
+ Index i = perm(l);
+ RealScalar diff = diag(i) - shifts(k);
+ EIGEN_OPTIMIZATION_BARRIER(diff)
+ diff -= mus(k);
+ EIGEN_OPTIMIZATION_BARRIER(diff)
+ V(i, k) = diag(i) * zhat(i) / diff / ((diag(i) + singVals[k]));
+ },
+ ap);
V(0, k) = Literal(-1);
V.col(k).normalize();
}