[petsc-users] my code runs too slow

[abhyshr at mcs.anl.gov]

Use TSComputeDefaultJacobian instead of SNESComputeDefaultJacobian if you want to use TS objects only. 


> ierr = TSComputeDefaultJacobian(ts,t,CV_Y,&J,&J,&flag,PETSC_NULL);CHKERRQ(ierr); 




> ierr = MatGetColoring(J,MATCOLORINGSL,&iscoloring);CHKERRQ(ierr); 
> ierr = MatFDColoringCreate(J,iscoloring,&matfdcoloring);CHKERRQ(ierr); 
> ierr = ISColoringDestroy(iscoloring);CHKERRQ(ierr); ...you missed this 
> ierr = MatFDColoringSetFunction(matfdcoloring,(PetscErrorCode (*)(void))f,(void*)&appctx);CHKERRQ(ierr); 
> ierr = MatFDColoringSetFromOptions(matfdcoloring);CHKERRQ(ierr); 
> ierr = TSSetRHSJacobian(ts,J,J,TSDefaultComputeJacobianColor,matfdcoloring); 




Shri 

> ----- "Xuan YU" <xxy113 at psu.edu> wrote: 
> > ierr = MatCreateSeqAIJ(PETSC_COMM_SELF,N,N,10,PETSC_NULL,&J);CHKERRQ(ierr); 

ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 
ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 

ierr = SNESComputeJacobian(ts_snes,CV_Y,&J,&J,&flag);CHKERRQ(ierr); 
ierr = MatGetColoring(J,MATCOLORINGSL,&iscoloring);CHKERRQ(ierr); 
ierr = MatFDColoringCreate(J,iscoloring,&matfdcoloring);CHKERRQ(ierr); 
ierr = MatFDColoringSetFunction(matfdcoloring,(PetscErrorCode (*)(void))f,(void*)&appctx);CHKERRQ(ierr); 
ierr = MatFDColoringSetFromOptions(matfdcoloring);CHKERRQ(ierr); 
ierr = TSSetRHSJacobian(ts,J,J,TSDefaultComputeJacobianColor,matfdcoloring); 


> > 
These are the Jacobian related codes. 

> > 

> > 

> > 

> > 

On Jul 7, 2010, at 1:51 PM, Satish Balay wrote: 





total: nonzeros=1830 
> > 

mallocs used during MatSetValues calls =1830 
> > 
> > Looks like you are zero-ing out the non-zero structure - before 
> > assembling the matrix. 
> > 
> > Are you calling MatZeroRows() or MatZeroEntries() or something else - 
> > before assembling the matrix? 
> > 
> > Satish 
> > 
> > On Wed, 7 Jul 2010, Xuan YU wrote: 
> > 
> > 

I made a change: ierr = 
> > 

MatCreateSeqAIJ(PETSC_COMM_SELF,N,N,5,PETSC_NULL,&J);CHKERRQ(ierr); 
> > 


> > 

Time of the code did not change much, and got the info: 
> > 

Matrix Object: 
> > 

type=seqaij, rows=1830, cols=1830 
> > 

total: nonzeros=1830, allocated nonzeros=36600 
> > 

total number of mallocs used during MatSetValues calls =1830 
> > 

not using I-node routines 
> > 


> > 


> > 


> > 

On Jul 7, 2010, at 12:51 PM, Satish Balay wrote: 
> > 


> > 





total: nonzeros=1830, allocated nonzeros=29280 
> > 





total number of mallocs used during MatSetValues calls =1830 
> > 




> > 



There is something wrong with your preallocation or matrix 
> > 



assembly. You should see zero mallocs for efficient assembly. 
> > 




> > 



http://www.mcs.anl.gov/petsc/petsc-as/documentation/faq.html#efficient-assembly 
> > 




> > 



satish 
> > 




> > 




> > 



On Wed, 7 Jul 2010, Xuan YU wrote: 
> > 




> > 





Hi, 
> > 






> > 





I finite difference Jacobian approximation for my TS model. The size of 
> > 





the 
> > 





vector is 1830. I got the following info with(-ts_view): 
> > 






> > 





type: beuler 
> > 





maximum steps=50 
> > 





maximum time=50 
> > 





total number of nonlinear solver iterations=647 
> > 





total number of linear solver iterations=647 
> > 





SNES Object: 
> > 





type: ls 
> > 





line search variant: SNESLineSearchCubic 
> > 





alpha=0.0001, maxstep=1e+08, minlambda=1e-12 
> > 





maximum iterations=50, maximum function evaluations=10000 
> > 





tolerances: relative=1e-08, absolute=1e-50, solution=1e-08 
> > 





total number of linear solver iterations=50 
> > 





total number of function evaluations=51 
> > 





KSP Object: 
> > 





type: gmres 
> > 





GMRES: restart=30, using Classical (unmodified) Gram-Schmidt 
> > 





Orthogonalization with no iterative refinement 
> > 





GMRES: happy breakdown tolerance 1e-30 
> > 





maximum iterations=10000, initial guess is zero 
> > 





tolerances: relative=1e-05, absolute=1e-50, divergence=10000 
> > 





left preconditioning 
> > 





using PRECONDITIONED norm type for convergence test 
> > 





PC Object: 
> > 





type: ilu 
> > 





ILU: out-of-place factorization 
> > 





0 levels of fill 
> > 





tolerance for zero pivot 1e-12 
> > 





using diagonal shift to prevent zero pivot 
> > 





matrix ordering: natural 
> > 





factor fill ratio given 1, needed 1 
> > 





Factored matrix follows: 
> > 





Matrix Object: 
> > 





type=seqaij, rows=1830, cols=1830 
> > 





package used to perform factorization: petsc 
> > 





total: nonzeros=1830, allocated nonzeros=1830 
> > 





total number of mallocs used during MatSetValues calls =0 
> > 





not using I-node routines 
> > 





linear system matrix = precond matrix: 
> > 





Matrix Object: 
> > 





type=seqaij, rows=1830, cols=1830 
> > 





total: nonzeros=1830, allocated nonzeros=29280 
> > 





total number of mallocs used during MatSetValues calls =1830 
> > 





not using I-node routines 
> > 






> > 






> > 





50 output time step takes me 11.877s. So I guess there is something not 
> > 





appropriate with my Jacobian Matrix. Could you please tell me how to speed 
> > 





up 
> > 





my code? 
> > 






> > 





Thanks! 
> > 






> > 





Xuan YU 
> > 





xxy113 at psu.edu 
> > 






> > 






> > 






> > 






> > 




> > 




> > 


> > 

Xuan YU (俞烜) 
> > 

xxy113 at psu.edu 
> > 


> > 


> > 


> > 


> > 
> > 

> > 
> > 
Xuan YU ( 俞烜 ) 
xxy113 at psu.edu 

> > 


> >
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