[petsc-dev] Discussion about time-dependent optimization moved from PR

[Stefano Zampini]

Jed,

have you thought about how to fix this?

https://lists.mcs.anl.gov/pipermail/petsc-dev/2017-October/021387.html

2017-10-16 11:26 GMT+03:00 Stefano Zampini <stefano.zampini at gmail.com>:

>
>
>>
>> Yeah, but they are sparse quadratures.  That's sort of how Stefano has
>> implemented it, though the concept should be generalized and
>> fixtime=PETSC_MIN_REAL is not a nice way to denote an integral.
>>
>>
> My quadrature implementation is very primitive: it is just function
> sampling and trapezoidal rule.
> Having fixtime=PETSC_MIN_REAL is just a simple way to have both kind of
> objectives under the same API, and I'm open to suggestions.
>
>
>> >> Both methods need the Jacobian of the DAE wrt the parameters: H
>> >> TSAdjointSetRHSJacobian(), S TSSetGradientDAE()
>> >>
>> >
>> > Here I understand Stefano to be using DAE in the following sense:
>> Suppose
>> > my continuous problem is a Partial Differential-Algebraic Equation
>> (PDAE).
>> > Then after discretizing in space, which I would call Method of Lines, I
>> am
>> > left with a Differential-Algebraic Equation (DAE) in time.
>>
>> Yeah, but the method isn't very useful in that context.  Fortunately,
>> TSCreateAdjointTS() is an interface that makes it easy to replace the
>> adjoint of the spatially-discretized operator with the discretization of
>> the adjoint (i.e., call TSSetComputeRHSJacobian(tsadj, ...)).
>>
>
> Wait, you are mixing two "Jacobians here", and this is why I prefer to
> call gradient one of them
> The one (let's call it J_m) you set with  TSSetGradientDAE() (and
> TSAdjointSetRHSJacobian(), bad name) is needed by the quadrature rule for
> \int J_m^T L . The one that instead you can set via TSSetComputeRHSJacobian(tsadj,
> aJ...)). is for the adjoint DAE, i.e. Ldot  = L^T * aJ
>
>
>
> --
> Stefano
>



-- 
Stefano
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