<div dir="ltr">Hi,<div><br></div><div style>I am looking for a way to roughly estimate the required memory size when using an in-core linear solver (ma27, ma57, etc.) with ipopt, and required disk storage size when using an out-of core linear solver (ma77).</div>
<div style><br></div><div style>If:</div><div style>number of variables = n</div><div style>number of equality constraints = m</div><div style>number of inequality constraints = k</div><div style>number of nonzero in constraint jacobian = j</div>
<div style>number of nonzero in lagrangian hessian = h</div><div style><br></div><div style>Is it correct that when using the "exact" hessian, the dominant memory requirement arises from the search direction matrix, and it is a dense (n+m)*(n+m) matrix? Or is it more involved than this?</div>
<div style><br></div><div style>How many of these matrices are stored during the execution?</div><div style><br></div><div style>Is there any difference in size when using an out-of-core linear solver other than the fact that the matrix is now stored on disk?</div>
<div style><br></div><div style>What about the "limited-memory case"?</div><div style><br></div><div style><br></div><div style>Thanks in advance for your help.</div><div style><br></div><div style>PS: For my problem the values are roughly as follows:</div>
<div style>n = 1M</div><div style>m = 50K</div><div style>k = 0</div><div style>j = 1M</div><div style>h = 500K</div><div><br clear="all"><div><br></div>-- <br>Mehmet Ersin Yumer
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