El mar, 4 mar 2025 a la(s) 4:25 p.m., Pierre Jolivet (pie...@joliv.et) escribió:
> > > On 4 Mar 2025, at 11:17 PM, Emmanuel Ayala <juan...@gmail.com> wrote: > > > Well, I just tested the configuration with --download-f2cblaslapack > --download-blis > and the direct solver cholesky with mumps becomes 10x faster :D > > > If your problem is big enough (and 700k unknowns should be by far big > enough), you should turn on BLR (block low-rank) which will give both > performance boost and memory savings. > But a good BLAS is mandatory indeed. > Thanks for the advice, I will try it. Regards. > > Thanks, > Pierre > > Thanks! > > El mar, 4 mar 2025 a la(s) 3:21 p.m., Emmanuel Ayala (juan...@gmail.com) > escribió: > >> Thanks for the notes. >> >> El mar, 4 mar 2025 a la(s) 2:22 p.m., Barry Smith (bsm...@petsc.dev) >> escribió: >> >>> >>> >>> > On Mar 4, 2025, at 2:02 PM, Emmanuel Ayala <juan...@gmail.com> wrote: >>> > >>> > Hello everyone. >>> > >>> > I'm trying to solve a linear system (which comes from 3D FEM with >>> structured DM mesh) with a direct solver. I configured petsc installation >>> with mumps (–download-mumps –download-scalapack –download-parmetis >>> –download-metis, --download-hwloc, without ptscotch) and I have the >>> following functions: >>> > >>> > // K is the stiffness matrix, assembly correctly >>> > // U is the solution vector >>> > // RHS is the right hand side of the linear equation >>> > >>> > Mat Kfactor; >>> > >>> > ierr = MatGetFactor(K,MATSOLVERMUMPS, MAT_FACTOR_CHOLESKY, >>> &Kfactor); CHKERRQ(ierr); >>> > ierr = MatCholeskyFactorSymbolic(Kfactor,K,0,0); CHKERRQ(ierr); >>> > ierr = MatCholeskyFactorNumeric(Kfactor,K,0); CHKERRQ(ierr); >>> > ierr = MatSolve(Kfactor,RHS,U); >>> >>> >>> Note 1) these four lines of code above are not needed if you use are >>> using KSPSolve to solve the system. The options below will trigger this. >>> > >>> > and run with options: >>> > -pc_type cholesky -pc_factor_mat_solver_type mumps >>> -mat_mumps_icntl_1 1 -mat_mumps_icntl_13 0 -mat_mumps_icntl_28 2 >>> -mat_mumps_icntl_29 2 >>> >> OK. I'm solving sepparetelly the direct solver and the iterative one. >> >>> >>> Note 2) it is imperative you use a good BLAS library and optimization >>> when using mumps. Do not use --download-blaslapack (or friends) and use >>> --with-debugging=0 in the configure option). >>> >> Right. I configured it with --with-debugging=0 and >> --download-fblaslapack. *So, which is a good BLAS library?* from petsc: >> ...One can use --download-f2cblaslapack --download-blis... >> >>> >>> Note 3) If you are running sequentially (no MPI) then also ensure you >>> have --with-openmp in your configure options and set an appropriate value >>> for the number of OpenMP threads when you run your program. >>> >> I'm running with MPI . >> >> Regards. >> >>> >>> >>> > >>> > PROBLEM: >>> > I got the correct solution, but the function MatCholeskyFactorNumeric( >>> ) takes too much time to be completed. MatCholeskyFactorSymbolic() and >>> MatSolve() are very fast. The test uses a square K matrix of 700k dofs, and >>> the MatCholeskyFactorNumeric() takes around 14 minutes, while an iterative >>> solver (KSPCG/PCJACOBI) takes 5 seconds to get the solution. Any >>> suggestions? >>> > >>> > Thanks in advance. >>> >>> >
