From: Wolfgang Bangerth <bangerth@colostate.edu>
Date: Sat, 30 Mar 2024 15:03:26 +0000 (-0600)
Subject: Revert "Align Tensor<rank,dim,Number> to make vectorization possible."
X-Git-Tag: v9.6.0-rc1~423^2~2
X-Git-Url: https://gitweb.dealii.org/cgi-bin/gitweb.cgi?a=commitdiff_plain;h=91d639ccbe11137db0ca5d0b3266bfa2cbe3e6aa;p=dealii.git

Revert "Align Tensor<rank,dim,Number> to make vectorization possible."

This reverts commit d6a65a9b929b1862a78de843ceaa7848e5a588e3.
---

diff --git a/include/deal.II/base/tensor.h b/include/deal.II/base/tensor.h
index 3cba07e361..03c3b5f3f0 100644
--- a/include/deal.II/base/tensor.h
+++ b/include/deal.II/base/tensor.h
@@ -393,55 +393,6 @@ private:
 
 
 
-namespace internal
-{
-  namespace TensorImplementation
-  {
-    /**
-     * Whether or not the 'values' array of Tensor can be treated as (i.e.,
-     * bitcasted to) a vectorized array (of possibly more than 'dim' elements,
-     * where the padding elements would then have to
-     * be ignored by all functions).
-     *
-     * We can store the values as an array that can be casted to VectorizedArray
-     * if we are considering a rank-1 tensor, and if it stores `double` or
-     * `float` values, and if there are at most 4 values -- we do not try to
-     * vectorize the uncommon case of `dim>4`. We also don't consider the case
-     * `dim==1` because in that case vectorization does not provide any benefit.
-     *
-     * Note that this leads to a platform dependent alignment given that
-     * we want to treat the elements as VectorizedArray and that whether
-     * or not a VectorizedArray of sufficiently large size exists depends
-     * on the platform we're on.
-     */
-    template <int rank, int dim, typename Number>
-    constexpr bool can_treat_values_as_vectorized_array =
-      ((rank == 1) &&
-       /* Only if dim==2,3,4 */
-       (dim > 1) && (dim <= 4) &&
-       /* Only for float and double tensors */
-       (std::is_same_v<Number, double> || std::is_same_v<Number, float>)&&
-       /* Only if a VectorizedArray<Number,N> is avaiable where N>=dim
-          (but we only have to consider N=2 or 4 because dim==2,3,4). */
-       (internal::VectorizedArrayWidthSpecifier<Number>::max_width >=
-        (dim <= 2 ? 2 : 4)));
-
-    /**
-     * Compute the alignment to be used for Tensor objects. We align it
-     * by 2 or 4 times the size of the scalar object for rank-1 tensors if
-     * rank-1 tensors can be treated as vectorized arrays (which makes sure that
-     * the higher-rank tensors are then also so aligned). Otherwise, set the
-     * alignment to the alignment of `Number`.
-     */
-    template <int rank, int dim, typename Number>
-    constexpr size_t tensor_alignment =
-      (can_treat_values_as_vectorized_array<1, dim, Number> ?
-         (dim <= 2 ? 2 : 4) * sizeof(Number) :
-         alignof(Number));
-  } // namespace TensorImplementation
-} // namespace internal
-
-
 /**
  * A general tensor class with an arbitrary rank, i.e. with an arbitrary
  * number of indices. The Tensor class provides an indexing operator and a bit
@@ -516,8 +467,7 @@ namespace internal
  * @ingroup geomprimitives
  */
 template <int rank_, int dim, typename Number>
-class alignas(
-  internal::TensorImplementation::tensor_alignment<rank_, dim, Number>) Tensor
+class Tensor
 {
 public:
   static_assert(rank_ >= 1,