On Thu, Jan 16, 2025 at 9:50 PM Zou, Ling via petsc-users < petsc-users@mcs.anl.gov> wrote:
> Hi all, > > > > Does PETSc has some automatic matrix sparsity detection algorithm > available? > > Something like: > https://urldefense.us/v3/__https://docs.sciml.ai/NonlinearSolve/stable/basics/sparsity_detection/__;!!G_uCfscf7eWS!dvR7knTNgJjVsN8MbdkzqHYGMeFeJA5KRmWbLart8sNlv5MD6vaocv12fo_IltMmctrA04DuDQsTXfRFd2UH$ > > <https://urldefense.us/v3/__https://docs.sciml.ai/NonlinearSolve/stable/basics/sparsity_detection/__;!!G_uCfscf7eWS!ccEx6zmuNrVADqtN50hO2N0k4Qs-A70nztAjMLu-JElnjhK5w84BpYC8CAINd6KihSxaS2rx_LgpqUVM49U$> > Sparsity detection would rely on introspection of the user code for ComputeFunction(), which is not possible in C (unless you were to code up your evaluation in some symbolic framework). > The background is that I use finite differencing plus matrix coloring to > (efficiently) get the Jacobian. > > For the matrix coloring part, I color the matrix based on mesh > connectivity and variable dependencies, which is not bad, but just try to > be lazy to even eliminating this part. > This is how the automatic frameworks also work. This is how we compute the sparsity pattern for PetscFE and PetscFV. > A related but different question, how much does PETSc support automatic > differentiation? > > I see some old paper: > > https://ftp.mcs.anl.gov/pub/tech_reports/reports/P922.pdf > > and discussion in the roadmap: > > https://urldefense.us/v3/__https://petsc.org/release/community/roadmap/__;!!G_uCfscf7eWS!dvR7knTNgJjVsN8MbdkzqHYGMeFeJA5KRmWbLart8sNlv5MD6vaocv12fo_IltMmctrA04DuDQsTXRy5JWAw$ > > <https://urldefense.us/v3/__https://petsc.org/release/community/roadmap/__;!!G_uCfscf7eWS!ccEx6zmuNrVADqtN50hO2N0k4Qs-A70nztAjMLu-JElnjhK5w84BpYC8CAINd6KihSxaS2rx_Lgpw6v6hKE$> > > I am thinking that if AD works so I don’t even need to do finite > differencing Jacobian, or have it as another option. > Other people understand that better than I do. Thanks, Matt > Best, > > > > -Ling > -- What most experimenters take for granted before they begin their experiments is infinitely more interesting than any results to which their experiments lead. -- Norbert Wiener https://urldefense.us/v3/__https://www.cse.buffalo.edu/*knepley/__;fg!!G_uCfscf7eWS!dvR7knTNgJjVsN8MbdkzqHYGMeFeJA5KRmWbLart8sNlv5MD6vaocv12fo_IltMmctrA04DuDQsTXfZqhc9B$ <https://urldefense.us/v3/__http://www.cse.buffalo.edu/*knepley/__;fg!!G_uCfscf7eWS!dvR7knTNgJjVsN8MbdkzqHYGMeFeJA5KRmWbLart8sNlv5MD6vaocv12fo_IltMmctrA04DuDQsTXUFmc9QT$ >
