[Ipopt] Computing the jacobians and hessians for IPOPT in single precision

Daniel Arteaga daniel.arteaga at upf.edu
Thu Jul 26 05:31:35 EDT 2018

Hi all,

We are using automatic differentiation with Tensorflow to compute the
derivatives (jacobians and hessians) for IPOPT. Tensorflow can only compute
such derivatives in single precision.

We were finding some issues with the stability of the minimization, and we
were wondering if using single precision derivatives could be the root

Do you think it is acceptable to compute derivatives with single precision?
Function evaluations are still computed with double precision.

Thank you very much,

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