PETSc的解决与KSP导向线性系统(PETSc solving linear system wit

2019-07-29 15:46发布

我开始使用的PETSc库来解决线性方程系统并行。 我已经安装了所有的软件包,构建和运行成功的PETSc / src目录/ KSP / KSP /例子/教程/文件夹中的例子,例如ex.c

但我不明白怎么填矩阵A,从文件中读取它们例如X的B中。

在这里,我提供ex2.c文件中的代码:

/* Program usage:  mpiexec -n <procs> ex2 [-help] [all PETSc options] */ 

static char help[] = "Solves a linear system in parallel with KSP.\n\
Input parameters include:\n\
  -random_exact_sol : use a random exact solution vector\n\
  -view_exact_sol   : write exact solution vector to stdout\n\
  -m <mesh_x>       : number of mesh points in x-direction\n\
  -n <mesh_n>       : number of mesh points in y-direction\n\n";

/*T
   Concepts: KSP^basic parallel example;
   Concepts: KSP^Laplacian, 2d
   Concepts: Laplacian, 2d
   Processors: n
T*/

/* 
  Include "petscksp.h" so that we can use KSP solvers.  Note that this file
  automatically includes:
     petscsys.h       - base PETSc routines   petscvec.h - vectors
     petscmat.h - matrices
     petscis.h     - index sets            petscksp.h - Krylov subspace methods
     petscviewer.h - viewers               petscpc.h  - preconditioners
*/
#include <C:\PETSC\include\petscksp.h>

#undef __FUNCT__
#define __FUNCT__ "main"
int main(int argc,char **args)
{
  Vec            x,b,u;  /* approx solution, RHS, exact solution */
  Mat            A;        /* linear system matrix */
  KSP            ksp;     /* linear solver context */
  PetscRandom    rctx;     /* random number generator context */
  PetscReal      norm;     /* norm of solution error */
  PetscInt       i,j,Ii,J,Istart,Iend,m = 8,n = 7,its;
  PetscErrorCode ierr;
  PetscBool      flg = PETSC_FALSE;
  PetscScalar    v;
#if defined(PETSC_USE_LOG)
  PetscLogStage  stage;
#endif

  PetscInitialize(&argc,&args,(char *)0,help);
  ierr = PetscOptionsGetInt(PETSC_NULL,"-m",&m,PETSC_NULL);CHKERRQ(ierr);
  ierr = PetscOptionsGetInt(PETSC_NULL,"-n",&n,PETSC_NULL);CHKERRQ(ierr);
  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 
         Compute the matrix and right-hand-side vector that define
         the linear system, Ax = b.
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  /* 
     Create parallel matrix, specifying only its global dimensions.
     When using MatCreate(), the matrix format can be specified at
     runtime. Also, the parallel partitioning of the matrix is
     determined by PETSc at runtime.

     Performance tuning note:  For problems of substantial size,
     preallocation of matrix memory is crucial for attaining good 
     performance. See the matrix chapter of the users manual for details.
  */
  ierr = MatCreate(PETSC_COMM_WORLD,&A);CHKERRQ(ierr);
  ierr = MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,m*n,m*n);CHKERRQ(ierr);
  ierr = MatSetFromOptions(A);CHKERRQ(ierr);
  ierr = MatMPIAIJSetPreallocation(A,5,PETSC_NULL,5,PETSC_NULL);CHKERRQ(ierr);
  ierr = MatSeqAIJSetPreallocation(A,5,PETSC_NULL);CHKERRQ(ierr);

  /* 
     Currently, all PETSc parallel matrix formats are partitioned by
     contiguous chunks of rows across the processors.  Determine which
     rows of the matrix are locally owned. 
  */
  ierr = MatGetOwnershipRange(A,&Istart,&Iend);CHKERRQ(ierr);

  /* 
     Set matrix elements for the 2-D, five-point stencil in parallel.
      - Each processor needs to insert only elements that it owns
        locally (but any non-local elements will be sent to the
        appropriate processor during matrix assembly). 
      - Always specify global rows and columns of matrix entries.

     Note: this uses the less common natural ordering that orders first
     all the unknowns for x = h then for x = 2h etc; Hence you see J = Ii +- n
     instead of J = I +- m as you might expect. The more standard ordering
     would first do all variables for y = h, then y = 2h etc.

   */
  ierr = PetscLogStageRegister("Assembly", &stage);CHKERRQ(ierr);
  ierr = PetscLogStagePush(stage);CHKERRQ(ierr);
  for (Ii=Istart; Ii<Iend; Ii++) { 
    v = -1.0; i = Ii/n; j = Ii - i*n;  
    if (i>0)   {J = Ii - n; ierr = MatSetValues(A,1,&Ii,1,&J,&v,INSERT_VALUES);CHKERRQ(ierr);}
    if (i<m-1) {J = Ii + n; ierr = MatSetValues(A,1,&Ii,1,&J,&v,INSERT_VALUES);CHKERRQ(ierr);}
    if (j>0)   {J = Ii - 1; ierr = MatSetValues(A,1,&Ii,1,&J,&v,INSERT_VALUES);CHKERRQ(ierr);}
    if (j<n-1) {J = Ii + 1; ierr = MatSetValues(A,1,&Ii,1,&J,&v,INSERT_VALUES);CHKERRQ(ierr);}
    v = 4.0; ierr = MatSetValues(A,1,&Ii,1,&Ii,&v,INSERT_VALUES);CHKERRQ(ierr);
  }

  /* 
     Assemble matrix, using the 2-step process:
       MatAssemblyBegin(), MatAssemblyEnd()
     Computations can be done while messages are in transition
     by placing code between these two statements.
  */
  ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
  ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
  ierr = PetscLogStagePop();CHKERRQ(ierr);

  /* A is symmetric. Set symmetric flag to enable ICC/Cholesky preconditioner */
  ierr = MatSetOption(A,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr);

  /* 
     Create parallel vectors.
      - We form 1 vector from scratch and then duplicate as needed.
      - When using VecCreate(), VecSetSizes and VecSetFromOptions()
        in this example, we specify only the
        vector's global dimension; the parallel partitioning is determined
        at runtime. 
      - When solving a linear system, the vectors and matrices MUST
        be partitioned accordingly.  PETSc automatically generates
        appropriately partitioned matrices and vectors when MatCreate()
        and VecCreate() are used with the same communicator.  
      - The user can alternatively specify the local vector and matrix
        dimensions when more sophisticated partitioning is needed
        (replacing the PETSC_DECIDE argument in the VecSetSizes() statement
        below).
  */
  ierr = VecCreate(PETSC_COMM_WORLD,&u);CHKERRQ(ierr);
  ierr = VecSetSizes(u,PETSC_DECIDE,m*n);CHKERRQ(ierr);
  ierr = VecSetFromOptions(u);CHKERRQ(ierr);
  ierr = VecDuplicate(u,&b);CHKERRQ(ierr); 
  ierr = VecDuplicate(b,&x);CHKERRQ(ierr);

  /* 
     Set exact solution; then compute right-hand-side vector.
     By default we use an exact solution of a vector with all
     elements of 1.0;  Alternatively, using the runtime option
     -random_sol forms a solution vector with random components.
  */
  ierr = PetscOptionsGetBool(PETSC_NULL,"-random_exact_sol",&flg,PETSC_NULL);CHKERRQ(ierr);
  if (flg) {
    ierr = PetscRandomCreate(PETSC_COMM_WORLD,&rctx);CHKERRQ(ierr);
    ierr = PetscRandomSetFromOptions(rctx);CHKERRQ(ierr);
    ierr = VecSetRandom(u,rctx);CHKERRQ(ierr);
    ierr = PetscRandomDestroy(&rctx);CHKERRQ(ierr);
  } else {
    ierr = VecSet(u,1.0);CHKERRQ(ierr);
  }
  ierr = MatMult(A,u,b);CHKERRQ(ierr);

  /*
     View the exact solution vector if desired
  */
  flg  = PETSC_FALSE;
  ierr = PetscOptionsGetBool(PETSC_NULL,"-view_exact_sol",&flg,PETSC_NULL);CHKERRQ(ierr);
  if (flg) {ierr = VecView(u,PETSC_VIEWER_STDOUT_WORLD);CHKERRQ(ierr);}

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 
                Create the linear solver and set various options
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

  /* 
     Create linear solver context
  */
  ierr = KSPCreate(PETSC_COMM_WORLD,&ksp);CHKERRQ(ierr);

  /* 
     Set operators. Here the matrix that defines the linear system
     also serves as the preconditioning matrix.
  */
  ierr = KSPSetOperators(ksp,A,A,DIFFERENT_NONZERO_PATTERN);CHKERRQ(ierr);

  /* 
     Set linear solver defaults for this problem (optional).
     - By extracting the KSP and PC contexts from the KSP context,
       we can then directly call any KSP and PC routines to set
       various options.
     - The following two statements are optional; all of these
       parameters could alternatively be specified at runtime via
       KSPSetFromOptions().  All of these defaults can be
       overridden at runtime, as indicated below.
  */
  ierr = KSPSetTolerances(ksp,1.e-2/((m+1)*(n+1)),1.e-50,PETSC_DEFAULT,
                          PETSC_DEFAULT);CHKERRQ(ierr);

  /* 
    Set runtime options, e.g.,
        -ksp_type <type> -pc_type <type> -ksp_monitor -ksp_rtol <rtol>
    These options will override those specified above as long as
    KSPSetFromOptions() is called _after_ any other customization
    routines.
  */
  ierr = KSPSetFromOptions(ksp);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 
                      Solve the linear system
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

  ierr = KSPSolve(ksp,b,x);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 
                      Check solution and clean up
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

  /* 
     Check the error
  */
  ierr = VecAXPY(x,-1.0,u);CHKERRQ(ierr);
  ierr = VecNorm(x,NORM_2,&norm);CHKERRQ(ierr);
  ierr = KSPGetIterationNumber(ksp,&its);CHKERRQ(ierr);
  /* Scale the norm */
  /*  norm *= sqrt(1.0/((m+1)*(n+1))); */

  /*
     Print convergence information.  PetscPrintf() produces a single 
     print statement from all processes that share a communicator.
     An alternative is PetscFPrintf(), which prints to a file.
  */
  ierr = PetscPrintf(PETSC_COMM_WORLD,"Norm of error %A iterations %D\n",
                     norm,its);CHKERRQ(ierr);

  /*
     Free work space.  All PETSc objects should be destroyed when they
     are no longer needed.
  */
  ierr = KSPDestroy(&ksp);CHKERRQ(ierr);
  ierr = VecDestroy(&u);CHKERRQ(ierr);  ierr = VecDestroy(&x);CHKERRQ(ierr);
  ierr = VecDestroy(&b);CHKERRQ(ierr);  ierr = MatDestroy(&A);CHKERRQ(ierr);

  /*
     Always call PetscFinalize() before exiting a program.  This routine
       - finalizes the PETSc libraries as well as MPI
       - provides summary and diagnostic information if certain runtime
         options are chosen (e.g., -log_summary). 
  */
  ierr = PetscFinalize();
  return 0;
}

是否有人知道如何实例中填写自己的矩阵?

Answer 1:

是啊,这可有点令人生畏当你开始。 还有在这个过程中的一个很好的步行通过这个 ACTS从2006年的教程; 在上市辅导 PETSc的网页上通常都相当不错。

这样做的关键部分是:

  ierr = MatCreate(PETSC_COMM_WORLD,&A);CHKERRQ(ierr);

实际创建的PETSc矩阵对象, Mat A ;

  ierr = MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,m*n,m*n);CHKERRQ(ierr);

设置大小; 这里,基质是m*nxm*n ,因为它是用于在操作的模版mxn 2D网格

  ierr = MatSetFromOptions(A);CHKERRQ(ierr);

这只是需要,你可能会在运行时已提供,并将其应用到矩阵,如果你想控制一个是如何设置的任何PETSc的命令行选项; 否则,你可能只是,有例如,使用MatCreateMPIAIJ()来创建它作为一个AIJ格式矩阵(默认), MatCreateMPIDense() ,如果它要成为一个密集矩阵。

  ierr = MatMPIAIJSetPreallocation(A,5,PETSC_NULL,5,PETSC_NULL);CHKERRQ(ierr);
  ierr = MatSeqAIJSetPreallocation(A,5,PETSC_NULL);CHKERRQ(ierr);

现在,我们已经得到了一个AIJ矩阵,这些电话只是预先分配的稀疏矩阵,假设每排5个非零。 这是性能。 请注意,无论是MPI和Seq函数必须被调用,以确保这个工程既1个处理器和多处理器; 这似乎总是怪异的是,但你去那里。

好了,现在该矩阵的所有设置,这里就是我们开始进入该事项的实际肉。

首先,我们发现这个特别的进程拥有哪些行。 分布是按行,这是典型的稀疏矩阵的良好分布。

  ierr = MatGetOwnershipRange(A,&Istart,&Iend);CHKERRQ(ierr);

所以这个电话后,每个处理器都有自己的ISTART和IEND的版本,它的这颗处理器的作业来更新行,起价只有 IEND结束之前结束ISTART,因为你在这看到的循环:

  for (Ii=Istart; Ii<Iend; Ii++) { 
    v = -1.0; i = Ii/n; j = Ii - i*n;  

好了,如果我们在排操作Ii ,这相当于网格位置(i,j)其中i = Ii/nj = Ii % n 。 例如,网格位置(i,j)对应于行Ii = i*n + j 。 说得通?

我要去,因为他们是非常重要的在这里带出的if语句,但他们只是在处理边界值,它们使事情更加复杂。

在该行,将有在对角线上一个4,并且在列-1s对应于(i-1,j)(i+1,j)(i,j-1)(i,j+1) 假设我们没有去关闭网格对于这些(例如,结束1 < i < m-11 < j < n-1这意味着

    J = Ii - n; ierr = MatSetValues(A,1,&Ii,1,&J,&v,INSERT_VALUES);CHKERRQ(ierr);
    J = Ii + n; ierr = MatSetValues(A,1,&Ii,1,&J,&v,INSERT_VALUES);CHKERRQ(ierr);
    J = Ii - 1; ierr = MatSetValues(A,1,&Ii,1,&J,&v,INSERT_VALUES);CHKERRQ(ierr);
    J = Ii + 1; ierr = MatSetValues(A,1,&Ii,1,&J,&v,INSERT_VALUES);CHKERRQ(ierr);

    v = 4.0; ierr = MatSetValues(A,1,&Ii,1,&Ii,&v,INSERT_VALUES);CHKERRQ(ierr);
  }

该if语句我拿出只是避免如果他们不存在设置这些值,以及CHKERRQ宏刚打印出一个有用的错误,如果ierr != 0 ,如设定值调用失败(因为我们试图建立一个无效的值) 。

现在,我们已经设置局部值; 在MatAssembly通话开始沟通,以确保任何必要的值的处理器之间交换。 如果您有任何不相关的工作要做,它可以卡之间的开始和结束,试图重叠通信和计算:

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

现在,你就大功告成了,可以打电话给你解算器。

因此,一个典型的工作流程是:

  • 创建矩阵( MatCreate
  • 设置其大小( MatSetSizes
  • 设置各种选项的矩阵( MatSetFromOptions是一个不错的选择,而不是硬编码的东西)
  • 为稀疏矩阵,设置预分配为每行非零的数目合理猜测; 可以用一个单一的值来完成(如在此),或与表示每行的非零(在这里与填充的数量的阵列PETSC_NULL ):( MatMPIAIJSetPreallocationMatSeqAIJSetPreallocation
  • 找出哪些行是你的责任:( MatGetOwnershipRange
  • 设置的值(调用MatSetValues或者每值一次,或传递值的块; INSERT_VALUES设置新的元素, ADD_VALUES递增任何现有的元件)
  • 然后做组件( MatAssemblyBeginMatAssemblyEnd )。

其他较为复杂的情况下是可能的。



文章来源: PETSc solving linear system with ksp guide