<p>Eigen or Intel MKL (if you're on Intel) with OpenMP should help.</p>
<p> <a href="http://eigen.tuxfamily.org/dox-devel/GettingStarted.html">http://eigen.tuxfamily.org/dox-devel/GettingStarted.html</a><br>
<br>
<a href="http://software.intel.com/en-us/intel-mkl">http://software.intel.com/en-us/intel-mkl</a></p>
<p> <a href="http://openmp.org/wp/">http://openmp.org/wp/</a></p>
<div class="gmail_quote">On Mar 8, 2013 11:35 AM, "Jeff Hubbs" <<a href="mailto:jhubbslist@att.net">jhubbslist@att.net</a>> wrote:<br type="attribution"><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
My *practical* experience has a hole in it when it comes to developing software to efficiently use multiple cores in a machine.<br>
<br>
If I'm writing code in the likes of C++, Python, or Fortran (acknowledging that I've got a range of programming paradigms there) and let's say that I'm subtracting two 2-D arrays of floating point numbers from one another element-wise, how is it that the operation gets blown across multiple CPU cores in an efficient way, if at all? Bear in mind that if this is done in Fortran, it's done in a pair of nested do-loops so unless the compiler is really smart, that becomes a serial operation.<br>
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