The form is u_t = A(t)u. On Sun, Jan 27, 2019 at 4:24 PM Smith, Barry F. <bsm...@mcs.anl.gov> wrote:
> > > > On Jan 25, 2019, at 4:51 PM, Sajid Ali via petsc-users < > petsc-users@mcs.anl.gov> wrote: > > > > Hi, > > > > If I have a linear time dependent equation I'm trying to solve using TS, > I can use : > > TSSetProblemType(ts,TS_LINEAR); > > TSSetRHSFunction(ts,NULL,TSComputeRHSFunctionLinear,NULL); > > TSSetRHSJacobian(ts,A,A,YourComputeRHSJacobian, &appctx); > > > > If the matrix that's being evaluated by YourComputeRHSJacobian is such > that the non-zero structure stays the same and only the diagonal changes > with time, is there a way to optimize the function so that it doesn't > create the whole matrix from scratch each time ? > > If it is a linear PDE u_t = A u then how can A change with time? It > sounds like it really isn't a linear problem? > > Barry > > > > > Naively I can make a dummy matrix and store the copy from t=0 and change > the diagonal at each iteration but that unnecessarily doubles the memory > consumption, is there a better way? > > > > > > Thank You, > > Sajid Ali > > Applied Physics > > Northwestern University > > -- Sajid Ali Applied Physics Northwestern University
