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369 lines
10 KiB
C
369 lines
10 KiB
C
#include <time.h>
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#include <lapack.h>
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#include <lapacke.h>
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#include <mpi.h>
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#include <petscconf.h>
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#include <petscerror.h>
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#include <petscmat.h>
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#include <petscoptions.h>
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#include <petscsys.h>
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#include <petscsystypes.h>
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#include <petsctime.h>
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#include <petscvec.h>
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#include <petscviewer.h>
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#include <petscviewerhdf5.h>
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#include <petscdm.h>
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#include <petscdmda.h>
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#include <petscksp.h>
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#include <petscviewertypes.h>
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#include <stdio.h>
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#include <stdlib.h>
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static char help[] = "Example PETSc program\n\n";
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void swap(double *a, double *b) {
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double t = *a;
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*a = *b;
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*b = t;
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}
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void print_all_hostnames() {
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int rank, size, name_len;
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char proc_name[MPI_MAX_PROCESSOR_NAME];
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MPI_Comm_rank(MPI_COMM_WORLD, &rank);
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MPI_Comm_size(MPI_COMM_WORLD, &size);
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MPI_Get_processor_name(proc_name, &name_len);
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char *all_names = NULL;
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if (rank == 0)
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all_names = malloc(size * MPI_MAX_PROCESSOR_NAME * sizeof(char));
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MPI_Gather(proc_name, MPI_MAX_PROCESSOR_NAME, MPI_CHAR, all_names, MPI_MAX_PROCESSOR_NAME, MPI_CHAR, 0,
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MPI_COMM_WORLD);
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if (rank == 0) {
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for (int i = 0; i < size; i++) {
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printf("Rank %d: %s\n", i, &all_names[i * MPI_MAX_PROCESSOR_NAME]);
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}
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free(all_names);
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}
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}
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PetscErrorCode ArnoldiIteration(Mat A, Vec b, PetscInt n, PetscInt m, Vec *Q, double *h);
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int main(int argc, char **argv) {
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PetscFunctionBeginUser;
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PetscInitialize(&argc, &argv, (char *)0, help);
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print_all_hostnames();
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PetscInt n, l;
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char matrix_name[PETSC_MAX_PATH_LEN];
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PetscBool flg;
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PetscOptionsGetInt(NULL, NULL, "-n", &n, &flg);
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if (!flg)
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n = -1;
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PetscOptionsGetInt(NULL, NULL, "-l", &l, &flg);
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if (!flg)
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l = 10;
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PetscOptionsGetString(NULL, NULL, "-matrix_path", matrix_name, sizeof(matrix_name), &flg);
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if (!flg)
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snprintf(matrix_name, sizeof(matrix_name), "./matrices/laplacian/laplacian-discretization-3d.mat");
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int rank, total;
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MPI_Comm_rank(PETSC_COMM_WORLD, &rank);
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MPI_Comm_size(PETSC_COMM_WORLD, &total);
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char hostname[64];
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PetscCall(PetscGetHostName(hostname, sizeof(hostname)));
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if (rank == 0)
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PetscCall(PetscPrintf(PETSC_COMM_WORLD, "[Arnoldi] Running on %s, rank %d of %d\n", hostname, rank, total));
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PetscLogDouble load_start_time;
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PetscCall(PetscTime(&load_start_time));
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Mat A;
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MatCreate(PETSC_COMM_WORLD, &A);
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PetscViewer v;
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PetscCall(PetscViewerCreate(PETSC_COMM_WORLD, &v));
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PetscCall(PetscViewerSetType(v, PETSCVIEWERHDF5));
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PetscCall(PetscViewerPushFormat(v, PETSC_VIEWER_HDF5_MAT));
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PetscCall(PetscViewerSetFromOptions(v));
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PetscCall(PetscViewerFileSetMode(v, FILE_MODE_READ));
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PetscCall(PetscViewerFileSetName(v, matrix_name));
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PetscCall(MatSetOptionsPrefix(A, "a_"));
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PetscCall(PetscObjectSetName((PetscObject)A, "A"));
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PetscCall(MatLoad(A, v));
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// Print matrix info
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{
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PetscInt m, n;
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MatGetSize(A, &m, &n);
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PetscCall(PetscPrintf(PETSC_COMM_WORLD, "[Arnoldi] Matrix loaded from %s\n", matrix_name));
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PetscCall(PetscPrintf(PETSC_COMM_WORLD, "[Arnoldi] Matrix size: %d x %d\n", m, n));
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}
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MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY);
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MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY);
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PetscLogDouble load_start_end;
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PetscCall(PetscTime(&load_start_end));
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PetscLogDouble load_time = load_start_end - load_start_time;
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if (rank == 0)
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PetscCall(PetscPrintf(PETSC_COMM_WORLD, "[Arnoldi] Load time: %f seconds\n", load_time));
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if (n == -1) {
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MatGetSize(A, &n, NULL);
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}
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Vec b;
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VecCreate(PETSC_COMM_WORLD, &b);
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VecSetSizes(b, PETSC_DECIDE, n);
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VecSetType(b, VECMPI);
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VecSet(b, 1.0);
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// seed random number generator
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// srand((unsigned int)time(NULL));
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// fill b with random values
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// for (PetscInt i = 0; i < n; i++) {
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// double val = (double)rand() / RAND_MAX;
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// VecSetValue(b, i, val, INSERT_VALUES);
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// }
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// VecAssemblyBegin(b);
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// VecAssemblyEnd(b);
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// VecSetValue(b, 0, 1.0, INSERT_VALUES);
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// MatView(A, PETSC_VIEWER_STDOUT_WORLD);
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// VecView(b, PETSC_VIEWER_STDOUT_WORLD);
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// PetscCall(PetscPrintf(PETSC_COMM_WORLD, "[Arnoldi] Allocating memory for Krylov subspace basis\n"));
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Vec *Q;
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PetscMalloc1(l, &Q);
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for (PetscInt i = 0; i < l; i++) {
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VecCreateMPI(PETSC_COMM_WORLD, PETSC_DECIDE, n, &Q[i]);
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}
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// PetscCall(PetscPrintf(PETSC_COMM_WORLD, "[Arnoldi] Constructing Hessenberg matrix\n"));
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// Mat H;
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// PetscCall(MatCreate(PETSC_COMM_SELF, &H));
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// PetscCall(PetscObjectSetName((PetscObject)H, "hessenberg"));
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// PetscCall(MatSetSizes(H, PETSC_DECIDE, PETSC_DECIDE, l + 1, l));
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// PetscCall(MatSetType(H, MATDENSE));
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// PetscCall(MatCreate(PETSC_COMM_WORLD, &H));
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// MatSetType(H, MATMPIAIJ);
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double *h = (double *)malloc((l + 1) * l * sizeof(double));
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for (PetscInt ii = 0; ii < (l + 1) * l; ii++) {
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h[ii] = 0.0;
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}
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// PetscCall(PetscPrintf(PETSC_COMM_WORLD, "[Arnoldi] Starting iteration\n"));
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PetscLogDouble arnoldi_start_time;
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PetscCall(PetscTime(&arnoldi_start_time));
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{
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PetscCall(ArnoldiIteration(A, b, l, n, Q, h));
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}
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PetscLogDouble arnoldi_end_time;
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PetscCall(PetscTime(&arnoldi_end_time));
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PetscLogDouble arnoldi_time = arnoldi_end_time - arnoldi_start_time;
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if (rank == 0)
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PetscCall(PetscPrintf(PETSC_COMM_WORLD, "[Arnoldi] Arnoldi time: %f seconds\n", arnoldi_time));
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// PetscCall(MatSetValue(H, 2, 3, -1, INSERT_VALUES));
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// PetscCall(MatAssemblyBegin(H, MAT_FINAL_ASSEMBLY));
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// PetscCall(MatAssemblyEnd(H, MAT_FINAL_ASSEMBLY));
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// PetscCall(PetscPrintf(PETSC_COMM_WORLD, "[Arnoldi] Done\n"));
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// int rank;
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// PetscCallMPI(MPI_Comm_rank(PETSC_COMM_WORLD, &rank));
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if (rank == 0) {
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// print Hessenberg matrix
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printf("H = \n");
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for (int i = 0; i < l + 1; i++) {
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for (int j = 0; j < l; j++) {
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printf("%.2f\t", h[i * (l + 1) + j]);
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}
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printf("\n");
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}
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double *wr = (double *)malloc(l * sizeof(double));
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double *wi = (double *)malloc(l * sizeof(double));
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double *z = (double *)malloc(l * l * sizeof(double));
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double *work = (double *)malloc(3 * l * sizeof(double));
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int info;
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PetscLogDouble lapack_start_time;
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PetscCall(PetscTime(&lapack_start_time));
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{
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// call LAPACK function "DHSEQR" to compute the eigenvalues of the Hessenberg matrix
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LAPACKE_dhseqr(LAPACK_ROW_MAJOR, 'E', 'I', l, 1, l, h, l + 1, wr, wi, z, l);
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}
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PetscLogDouble lapack_end_time;
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PetscCall(PetscTime(&lapack_end_time));
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PetscLogDouble lapack_time = lapack_end_time - lapack_start_time;
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PetscCall(PetscPrintf(PETSC_COMM_WORLD, "[Arnoldi] LAPACK time: %f seconds\n", lapack_time));
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// print Hessenberg matrix
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printf("H = \n");
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for (int i = 0; i < l + 1; i++) {
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for (int j = 0; j < l; j++) {
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printf("%.2f\t", h[i * (l + 1) + j]);
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}
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printf("\n");
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}
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// sort eigenvalues
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for (int i = 0; i < l; i++) {
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for (int j = i + 1; j < l; j++) {
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if (wr[i] > wr[j]) {
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swap(&wr[i], &wr[j]);
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swap(&wi[i], &wi[j]);
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for (int k = 0; k < l; k++) {
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swap(&z[i * l + k], &z[j * l + k]);
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}
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}
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}
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}
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// print eigenvalues
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printf("Eigenvalues = \n");
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for (int i = 0; i < l; i++) {
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printf("%.3f + %.3f i\n", wr[i], wi[i]);
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}
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}
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// print eigenvectors
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// printf("Eigenvectors = \n");
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// for (int i = 0; i < l; i++) {
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// for (int j = 0; j < l; j++) {
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// printf("%f ", z[i * l + j]);
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// }
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// printf("\n");
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// }
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PetscCall(MatDestroy(&A));
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PetscCall(VecDestroy(&b));
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// PetscCall(MatDestroy(&H));
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PetscFinalize();
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return 0;
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}
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PetscErrorCode ArnoldiIteration(Mat A, Vec b, PetscInt n, PetscInt m, Vec *Q, double *h) {
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PetscFunctionBeginUser;
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int rank;
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MPI_Comm_rank(PETSC_COMM_WORLD, &rank);
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PetscScalar eps = 1e-12;
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Vec q;
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if (rank == 0)
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printf("n = %d, m = %d\n", n, m);
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/*
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eps = 1e-12
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h = np.zeros((n + 1, n))
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Q = np.zeros((A.shape[0], n + 1))
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# Normalize the input vector
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Q[:, 0] = b / np.linalg.norm(b, 2) # Use it as the first Krylov vector
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for k in range(1, n + 1):
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v = np.dot(A, Q[:, k - 1]) # Generate a new candidate vector
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for j in range(k): # Subtract the projections on previous vectors
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h[j, k - 1] = np.dot(Q[:, j].conj(), v)
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v = v - h[j, k - 1] * Q[:, j]
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h[k, k - 1] = np.linalg.norm(v, 2)
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if h[k, k - 1] > eps: # Add the produced vector to the list, unless
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Q[:, k] = v / h[k, k - 1]
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else: # If that happens, stop iterating.
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return Q, h
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*/
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PetscCall(VecDuplicate(b, &q));
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PetscCall(VecCopy(b, q));
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PetscCall(VecNormalize(q, NULL));
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Q[0] = q;
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for (PetscInt k = 1; k < n + 1; k++) {
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if (rank == 0)
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PetscCall(PetscPrintf(PETSC_COMM_WORLD, "[Arnoldi] Iteration %d\n", k));
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Vec v;
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PetscCall(VecDuplicate(b, &v));
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// v = A q_k
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PetscCall(MatMult(A, Q[k - 1], v));
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// Reorthogonalization using modified Gram-Schmidt
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// fill all rows from 0 to k - 1 at column k - 1
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for (PetscInt j = 0; j < k; j++) { // anche solo 3
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PetscScalar h_ij;
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// h_(j, k - 1) = q_j . v
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PetscCall(VecDot(Q[j], v, &h_ij));
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if (rank == 0)
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printf("h[%d, %d] = %f\n", j, k - 1, h_ij);
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h[j * (n + 1) + k - 1] = h_ij;
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// v -= h_ij * q_j
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PetscCall(VecAXPY(v, -h_ij, Q[j]));
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}
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// Normalize:
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// v = v / ||v||
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// h_ij = ||v||
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PetscScalar h_ij;
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PetscCall(VecNorm(v, NORM_2, &h_ij));
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if (rank == 0)
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printf("h[%d, %d] = %f\n", k, k - 1, h_ij);
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h[k * (n + 1) + k - 1] = h_ij;
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// Check for convergence
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if (h_ij > eps) {
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PetscCall(VecNormalize(v, NULL));
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Q[k] = v;
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} else {
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PetscCall(PetscPrintf(PETSC_COMM_WORLD, "[Arnoldi] Early breakdown"));
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break;
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}
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}
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PetscFunctionReturn(PETSC_SUCCESS);
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}
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