<div dir="ltr">Sure, it would be nice to do the comparison.<div><br></div><div>Thanks in advance,</div><div><br></div><div>Johnoel</div></div><div class="gmail_extra"><br><div class="gmail_quote">On Mon, Sep 15, 2014 at 9:19 AM, dave fournier <span dir="ltr"><<a href="mailto:davef@otter-rsch.com" target="_blank">davef@otter-rsch.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">
  
    
  
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    <div>On 09/15/2014 12:14 PM, Johnoel Ancheta
      wrote:<br>
      <br>
      If you wan t I have code to call the Openblas version as well as a
      blocked version which stores the relevant matrices in<br>
      blocks as recommended by Dongarra et al  (but it does not seem to
      be worth the effort).<br>
      <br>
      <br>
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      <div dir="ltr">Thanks Dave!  I'll provide feedback after
        testing...
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      <div class="gmail_extra"><br>
        <div class="gmail_quote">On Mon, Sep 15, 2014 at 9:03 AM, otter
          <span dir="ltr"><<a href="mailto:otter@otter-rsch.com" target="_blank">otter@otter-rsch.com</a>></span>
          wrote:<br>
          <blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">After much
            pain I have produced a C++ version of the LU decomposition
            which<br>
            is suitable for producing adjoint code for ADMB and perhaps
            cppad. (Don't know what adjoint<br>
            code for cppad is as yet!)  This code is about 25 times
            faster than the current<br>
            ADMB code for a 2,000 x 2,000 matrix and about 4 times
            slower than the Openblas<br>
            code which contains optimized assembler and Fortrash.  Any
            suggestion for improvements<br>
            would be welcome.  Per usual I will hold my breath.<br>
            <br>
            <br>
            <br>
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    </blockquote>
    <br>
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