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Hi,</div>
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I am used to developing python extension modules written in fortran (f2py) or C++ for compute intensive tasks. The algorithm I am facing now cannot be tackled with auto-vectorization. Since I had good experience in performance of Vc libraries, I wanted to give
this a try. I briefly describe the setting below</div>
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I am using a recent python version (3.6) and Numpy 1.15 from Anaconda. Numpy provides nicely aligned 64-byte aligned arrays. Using the tools of <a href="https://github.com/mdboom/numpy-boost" class="">https://github.com/mdboom/numpy-boost</a> to pass Numpy
arrays to c++ functions. Inside these functions I have a pointer to the memory allocated by the Numpy array, how can I used the Vc machinery on this memory? In all examples I have seen the memory is allocated in the C++ code. Is there a way to cast a raw pointer
to (well aligned) memory to sth that is understood by Vc?</div>
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Many thanks in advance</div>
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Bert</div>
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Kindest regards,</div>
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Dr [Engel]bert Tijskens - HPC Analyst/Consultant</div>
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Flemish Supercomputer Center</div>
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University of Antwerp / Computational mathematics</div>
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++32 3 265 3879, ++32 494 664408</div>
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