[petsc-users] Adaptive controllers in TS
Hi all I'm trying to find out what is the adaptive controller scheme used in the Runge-Kutta time stepping algorithm. Basically I want to know the function that determines the next time step. I see that the next time step is set with the function TSAdaptChoose(), which calls the pointer function (*choose)() within the structure _TSAdaptOps, but where is this set? I need to know this for an adjoint analysis to calculate gradients. I was wondering if there is an example of such analysis with the TS structure. I've seen that the RK source file includes a funciton to interpolate the solution, something that is necessary in an adjoint analysis, hence my question about the example. Thanks Miguel -- *Miguel Angel Salazar de Troya* Graduate Research Assistant Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign (217) 550-2360 salaz...@illinois.edu
Re: [petsc-users] Adaptive controllers in TS
Miguel Angel Salazar de Troya salazardetr...@gmail.com writes: Hi all I'm trying to find out what is the adaptive controller scheme used in the Runge-Kutta time stepping algorithm. Basically I want to know the function that determines the next time step. I see that the next time step is set with the function TSAdaptChoose(), which calls the pointer function (*choose)() within the structure _TSAdaptOps, but where is this set? via TSAdaptSetType. The default will be TSAdaptChoose_Basic (adaptbasic.c). You can find this information easily by running in a debugger. I need to know this for an adjoint analysis to calculate gradients. I was wondering if there is an example of such analysis with the TS structure. I've seen that the RK source file includes a funciton to interpolate the solution, something that is necessary in an adjoint analysis, hence my question about the example. Interpolation arises for continuous adjoints. Be aware that if you want consistent gradients, you'll want a discrete adjoint, which integrates backward in time using the adjoint RK method. The stages of the adjoint RK method coincide with the forward method, so no interpolation is needed. Hong (Cc'd) is developing an example that can integrate discrete adjoint equations and we intend to eventually incorporate that functionality into the library. pgp9KxFGrhL_8.pgp Description: PGP signature
[petsc-users] Check Array and String Bounds in PETSc
Hi All, How can I avoid array bounds error when using PETSc. I have to debug my codes so I compiled the codes with option Check Array and String Bounds. But this results into array bounds error when I need to use ltog, as shown below. call DMGetLocalToGlobalMapping(dmda_flow%da,ltogm,ierr) call ISLocalToGlobalMappingGetIndices(ltogm,ltog,idltog,ierr) Exactly the aforementioned two lines work fine and the bug is in somewhere else. But the debug process just stops at the codes when ltog is used. How can avoid this? Thanks, Danyang
Re: [petsc-users] Check Array and String Bounds in PETSc
On Sun, Oct 19, 2014 at 6:38 PM, Danyang Su danyang...@gmail.com wrote: Hi All, How can I avoid array bounds error when using PETSc. I have to debug my codes so I compiled the codes with option Check Array and String Bounds. But this results into array bounds error when I need to use ltog, as shown below. call DMGetLocalToGlobalMapping(dmda_flow%da,ltogm,ierr) call ISLocalToGlobalMappingGetIndices(ltogm,ltog,idltog,ierr) Exactly the aforementioned two lines work fine and the bug is in somewhere else. But the debug process just stops at the codes when ltog is used. How can avoid this? Something else is wrong with the code. Neither of those routines does array lookup. Matt Thanks, Danyang -- What most experimenters take for granted before they begin their experiments is infinitely more interesting than any results to which their experiments lead. -- Norbert Wiener
Re: [petsc-users] Check Array and String Bounds in PETSc
Use ISLocalToGlobalMappingGetIndicesF90() On Oct 19, 2014, at 6:38 PM, Danyang Su danyang...@gmail.com wrote: Hi All, How can I avoid array bounds error when using PETSc. I have to debug my codes so I compiled the codes with option Check Array and String Bounds. But this results into array bounds error when I need to use ltog, as shown below. call DMGetLocalToGlobalMapping(dmda_flow%da,ltogm,ierr) call ISLocalToGlobalMappingGetIndices(ltogm,ltog,idltog,ierr) Exactly the aforementioned two lines work fine and the bug is in somewhere else. But the debug process just stops at the codes when ltog is used. How can avoid this? Thanks, Danyang
Re: [petsc-users] Adaptive controllers in TS
Thanks for your response I'm struggling with this problem because the literature is not clear for me on how to calculate the discrete adjoint with adaptive time stepping algorithms. They cover the details when automatic differentiation tools are used. They mention that because the time step depend on the solution, it also depends on the parameter. Hence, there are terms that represent the derivative of the time step w.r.t. the parameters. What it is confusing is that they mention these terms must be removed. I don't understand this. I'm planning to hard-code the discrete adjoint problem (and use the TS if possible). I know this might not be the place to ask this. Maybe Hong can help me here. Miguel On Sun, Oct 19, 2014 at 1:41 PM, Jed Brown j...@jedbrown.org wrote: Miguel Angel Salazar de Troya salazardetr...@gmail.com writes: Hi all I'm trying to find out what is the adaptive controller scheme used in the Runge-Kutta time stepping algorithm. Basically I want to know the function that determines the next time step. I see that the next time step is set with the function TSAdaptChoose(), which calls the pointer function (*choose)() within the structure _TSAdaptOps, but where is this set? via TSAdaptSetType. The default will be TSAdaptChoose_Basic (adaptbasic.c). You can find this information easily by running in a debugger. I need to know this for an adjoint analysis to calculate gradients. I was wondering if there is an example of such analysis with the TS structure. I've seen that the RK source file includes a funciton to interpolate the solution, something that is necessary in an adjoint analysis, hence my question about the example. Interpolation arises for continuous adjoints. Be aware that if you want consistent gradients, you'll want a discrete adjoint, which integrates backward in time using the adjoint RK method. The stages of the adjoint RK method coincide with the forward method, so no interpolation is needed. Hong (Cc'd) is developing an example that can integrate discrete adjoint equations and we intend to eventually incorporate that functionality into the library. -- *Miguel Angel Salazar de Troya* Graduate Research Assistant Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign (217) 550-2360 salaz...@illinois.edu
