RE: relation of numerical error to gfortran?

Hi Tong, The general issue of floating point instability is generally a problem for models that are hard to fit (3 days with full parallelization sounds hard to fit). It’s discussed in the intro7.pdf document in section I.70, “Stable Model Development for Monte Carlo Methods”. Given that you’re using SAEM, it seems like there could be a division by zero or near zero when trying to choose the next point to estimate and the values are going toward infinity or negative infinity. I’ve experienced this in the past with problems that are not well-defined around the OFV minimum. For instance, if a parameter has a near-flat derivative in the likelihood surface, it can cause these issues. It's not a specific problem to changing from Intel Fortran to gfortran; it could have happened with almost any platform change (changing operating system, changing compiler, changing operating system or compiler version, changing architecture [AMD vs Intel], and even changing architectures within a brand [Intel i9 vs Xeon, for instance]). In my experience, usually this points to a model that’s not well-defined. I would try to slowly build up the model—either in fixing parameters, fitting the model, and add the parameters back one-by-one to see which parameter estimation causes the estimation to slow down dramatically or to cause the problem. Or, subset your data: start with one study and build up from there; occasionally, trying to identify a problem individual or problem study and see if a different parameterization could help with that data (e.g. do you need a different residual error for Phase 1 vs Phase 2 studies?). Thanks, Bill *From:* [email protected] <[email protected]> *On Behalf Of *Tong Lu *Sent:* Thursday, March 31, 2022 5:43 PM *To:* [email protected] *Subject:* [NMusers] relation of numerical error to gfortran? Hello All, Has anyone experienced numerical errors when using NONMEM with gfortran but not intel fortran? We have a complex PKPD model which gave us strage individual fitting with NM7.5.1 (compiled by gfortran) but not NM7.4.3 (compiled with intel fortran). When using NM7.5.1, there is an unexpected & abrupt change of the time profile in some individuals, which is likely caused by the issue of numerical integration. This is a model with a large percent of BLQ, and has an extremely long run time (3 day with full parallelization). We used NOHABORT in SAEM estimation. Somehow we failed to install NM7.5.1 and PsN 5.2.6 properly on our linux cluster (CentOS) when using intel fortran. Thus no apple-to-apple comparison can be made (NM 7.5.1 by gfortran v.s. NM 7.5.1 by intel fortran). I am wondering if you have experienced cases where gfortran gave an issue but intel fortran is ok, for the same NONMEM version. The changes made in NM7.5.1 could also be related to this issue. Any thoughts or experience around this could also be very helpful. Thanks a lot for your insights Best, Tong