Difference between revisions of "3.4"

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</source>
 
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* Versatile API for sub-matrices, slices, and indexed views.
 
* Versatile API for sub-matrices, slices, and indexed views.
 +
* Reshaped
 +
* Vectorization of partial-reductions along outer-dimension, e.g.: colmajor.rowwise().mean()
 
* Generalization of the CUDA support to CUDA/HIP for AMD gpus.
 
* Generalization of the CUDA support to CUDA/HIP for AMD gpus.
 
* Add MSA (MIPS) vectorization engine
 
* Add MSA (MIPS) vectorization engine
 +
* AVX512 is enabled by default when enabled on compiler side.

Revision as of 21:42, 9 October 2018

Raw dump of the main novelties and improvements that will be part of the 3.4 release compared to the 3.3 branch:

  • Speed up evaluation of HouseholderSequence to a dense matrix, e.g.,
    MatrixXd Q = A.qr().householderQ();
  • Versatile API for sub-matrices, slices, and indexed views.
  • Reshaped
  • Vectorization of partial-reductions along outer-dimension, e.g.: colmajor.rowwise().mean()
  • Generalization of the CUDA support to CUDA/HIP for AMD gpus.
  • Add MSA (MIPS) vectorization engine
  • AVX512 is enabled by default when enabled on compiler side.