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    <div class="moz-cite-prefix">Assuming its not down to a bug in the
      Ipopt code, it could be any number of factors:<br>
      1) Does the BLAS library used support reproducibility, and is this
      enabled with the correct link line etc.<br>
      2) Does the sparse linear solver support reproducibility, is this
      enabled?<br>
      3) Is the memory alignment of all arrays consistent - can result
      in different portions of loops being addressed with AVX vs x87 FP
      that can give different answers.<br>
      <br>
      One thing to try might be to recompile everything you can with AVX
      (vectorization) disabled to force everything through the x87 path,
      and disable any unsafe floating point optimization flags. If this
      fixes the problem, at least you have a starting point.<br>
      <br>
      Jonathan.<br>
      <br>
      On 09/01/14 11:16, Roberto Verdelli wrote:<br>
    </div>
    <blockquote
cite="mid:CAF-yftUUodfyOFLW0Xu_T+KviAe-ewD0Vsyuk3qkE01cNbFpiA@mail.gmail.com"
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                      <div>Hi,<br>
                        <br>
                        I did some testing and I noticed that it also
                        happens with the tutorial problem written on the
                        ipopt website.<br>
                        <br>
                      </div>
                      My code looks like this:<br>
                      <br>
                      int main(int argv, char* argc[]){<br>
                      <br>
                      &nbsp;&nbsp;&nbsp; for(int i = 0; i &lt; 15; i++)<br>
                      &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; loop();<br>
                      <br>
                      }<br>
                      <br>
                    </div>
                    int loop(){<br>
                    <br>
                    // Create a new instance of your nlp <br>
                    //&nbsp; (use a SmartPtr, not raw)<br>
                    SmartPtr&lt;TNLP&gt; mynlp = new
                    hs071_nlp(/*a,b,c,d*/);<br>
                    <br>
                    // Create a new instance of IpoptApplication<br>
                    ...<br>
                    <br>
                    <br>
                  </div>
                  The function called 'loop' contains the tutorial ipopt
                  problem.<br>
                </div>
                If I lower the tolerance to 1e-3 (which shouldn't be a
                problem because if the algorithm is deterministic two
                consecutive runs should look the same, independently
                from the tolerance) I get this results:<br>
              </div>
              <div>iterations<br>
              </div>
              1.Objective...............:&nbsp; 1.7014117428683792e-007&nbsp;&nbsp;
              1.7014117428683793e+001<br>
              2.Objective...............:&nbsp; 1.7014117428684237e-007&nbsp;&nbsp;
              1.7014117428684237e+001<br>
              3.Objective...............:&nbsp; 1.7014117428684237e-007&nbsp;&nbsp;
              1.7014117428684237e+001<br>
              4.Objective...............:&nbsp; 1.7014117428684237e-007&nbsp;&nbsp;
              1.7014117428684237e+001<br>
              <br>
              <br>
            </div>
            Why the first iteration is different?<br>
            <br>
            <br>
          </div>
          Kind regards,<br>
        </div>
        Roberto.<br>
      </div>
      <br>
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      <br>
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    <br>
  
<br>
<p>-- 
<BR>Scanned by iCritical.
</p><br>
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