| /petsc/src/mat/utils/ |
| H A D | getcolv.c | 115 PetscErrorCode MatGetColumnSumsRealPart(Mat A, PetscReal sums[]) in MatGetColumnSumsRealPart() argument
118 PetscCall(MatGetColumnReductions(A, REDUCTION_SUM_REALPART, sums)); in MatGetColumnSumsRealPart()
139 PetscErrorCode MatGetColumnSumsImaginaryPart(Mat A, PetscReal sums[]) in MatGetColumnSumsImaginaryPart() argument
142 PetscCall(MatGetColumnReductions(A, REDUCTION_SUM_IMAGINARYPART, sums)); in MatGetColumnSumsImaginaryPart()
163 PetscErrorCode MatGetColumnSums(Mat A, PetscScalar sums[]) in MatGetColumnSums() argument
172 PetscCall(MatGetColumnSumsRealPart(A, sums)); in MatGetColumnSums()
175 PetscCall(PetscArrayzero(sums, n)); in MatGetColumnSums()
178 for (i = 0; i < n; i++) sums[i] = work[i]; in MatGetColumnSums()
180 for (i = 0; i < n; i++) sums[i] += work[i] * PETSC_i; in MatGetColumnSums()
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| /petsc/src/mat/tests/output/ |
| H A D | ex9_1.out | 7 matrix information (global sums):
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| /petsc/src/vec/is/is/utils/ |
| H A D | iscoloring.c | 519 PetscInt n, *starts = NULL, *sums = NULL, *lsizes = NULL, *newi = NULL; in ISPartitioningToNumbering() local
548 PetscCall(PetscMalloc3(np, &lsizes, np, &starts, np, &sums)); in ISPartitioningToNumbering()
551 PetscCallMPI(MPIU_Allreduce(lsizes, sums, np, MPIU_INT, MPI_SUM, comm)); in ISPartitioningToNumbering()
555 sums[i] += sums[i - 1]; in ISPartitioningToNumbering()
556 starts[i] += sums[i - 1]; in ISPartitioningToNumbering()
564 PetscCall(PetscFree3(lsizes, starts, sums)); in ISPartitioningToNumbering()
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| /petsc/src/ksp/ksp/tutorials/output/ |
| H A D | ex55_hypre_device.out | 36 Maximum row sums 0.9
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| H A D | ex55_hypre_device_alt.out | 34 Maximum row sums 0.9
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| H A D | ex49_hypre_nullspace_alt.out | 29 Maximum row sums 0.9
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| H A D | ex49_hypre_nullspace.out | 30 Maximum row sums 0.9
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| /petsc/src/ksp/ksp/tests/output/ |
| H A D | ex3_hypre.out | 22 Maximum row sums 0.9
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| H A D | ex3_hypre_alt.out | 22 Maximum row sums 0.9
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| /petsc/src/ksp/pc/tests/output/ |
| H A D | ex10_1.out | 13 Maximum row sums 1.
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| /petsc/src/mat/impls/kaij/ |
| H A D | kaij.c | 658 PetscScalar *y, *sums; in MatMultAdd_SeqKAIJ() local
680 sums = y + p * i; in MatMultAdd_SeqKAIJ()
682 for (k = 0; k < p; k++) sums[k] += v[jrow + j] * x[q * idx[jrow + j] + k]; in MatMultAdd_SeqKAIJ()
690 sums = y + p * i; in MatMultAdd_SeqKAIJ()
693 for (l = 0; l < q; l++) sums[k] += v[jrow + j] * t[k + l * p] * x[q * idx[jrow + j] + l]; in MatMultAdd_SeqKAIJ()
705 sums = y + p * i; in MatMultAdd_SeqKAIJ()
709 for (k = 0; k < p; k++) sums[k] += s[k + j * p] * bx[j]; in MatMultAdd_SeqKAIJ()
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| /petsc/src/mat/impls/maij/ |
| H A D | maij.c | 349 PetscScalar *y, *sums; in MatMult_SeqMAIJ_N() local
364 sums = y + dof * i; in MatMult_SeqMAIJ_N()
366 for (k = 0; k < dof; k++) sums[k] += v[jrow] * x[dof * idx[jrow] + k]; in MatMult_SeqMAIJ_N()
382 PetscScalar *y, *sums; in MatMultAdd_SeqMAIJ_N() local
397 sums = y + dof * i; in MatMultAdd_SeqMAIJ_N()
399 for (k = 0; k < dof; k++) sums[k] += v[jrow] * x[dof * idx[jrow] + k]; in MatMultAdd_SeqMAIJ_N()
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| /petsc/src/vec/vec/utils/ |
| H A D | vinv.c | 615 PetscErrorCode VecStrideSumAll(Vec v, PetscScalar sums[]) in VecStrideSumAll() argument
625 PetscAssertPointer(sums, 2); in VecStrideSumAll()
638 PetscCallMPI(MPIU_Allreduce(local_sums, sums, ibs, MPIU_SCALAR, MPIU_SUM, comm)); in VecStrideSumAll()
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| /petsc/src/mat/impls/baij/mpi/ |
| H A D | mpibaij.c | 756 PetscReal *sums; in MatNorm_MPIBAIJ() local
757 PetscCall(PetscMalloc1(bs, &sums)); in MatNorm_MPIBAIJ()
760 for (row = 0; row < bs; row++) sums[row] = 0.0; in MatNorm_MPIBAIJ()
766 sums[row] += PetscAbsScalar(*v); in MatNorm_MPIBAIJ()
776 sums[row] += PetscAbsScalar(*v); in MatNorm_MPIBAIJ()
782 if (sums[row] > sum) sum = sums[row]; in MatNorm_MPIBAIJ()
786 PetscCall(PetscFree(sums)); in MatNorm_MPIBAIJ()
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| /petsc/src/ksp/pc/impls/bddc/ |
| H A D | bddcschurs.c | 1155 PetscScalar *array, sum = 0., one = 1., *sums; in PCBDDCSubSchursSetUp() local
1160 PetscCall(PetscCalloc1(benign_n, &sums)); in PCBDDCSubSchursSetUp()
1170 for (j = 0; j < nz - 1; j++) sums[k] -= AIIm1_data[idxs[j] + sizeA * i]; in PCBDDCSubSchursSetUp()
1188 sum = sums[k]; in PCBDDCSubSchursSetUp()
1209 PetscCall(PetscFree(sums)); in PCBDDCSubSchursSetUp()
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| H A D | bddcprivate.c | 4967 PetscScalar *sums; in PCBDDCSetUpCorrection() local
4971 PetscCall(PetscMalloc1(n_vertices, &sums)); in PCBDDCSetUpCorrection()
4980 sums[j] = 0.; in PCBDDCSetUpCorrection()
4981 for (PetscInt k = 0; k < nz; k++) sums[j] += marr[idxs_zero[k] + j * n_R]; in PCBDDCSetUpCorrection()
4986 …; k++) PetscCall(MatSetValue(*coarse_submat, idx_V[idxs[j]], idx_V[k], val * sums[k], ADD_VALUES)); in PCBDDCSetUpCorrection()
4991 PetscCall(PetscFree(sums)); in PCBDDCSetUpCorrection()
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| /petsc/doc/changes/ |
| H A D | 316.md | 129 …`MatGetColumnSumsRealPart()`, `MatGetColumnSumsImaginaryPart()` to compute sums over matrix columns
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| /petsc/share/petsc/matlab/ |
| H A D | laplacian.m | 72 % conditions using tensor sums of 1D Laplacians. For more information on
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| /petsc/doc/manual/ |
| H A D | ts.md | 1101 …, the lumped mass matrix is diagonal (e.g., computed via collocated quadrature or row sums of $M$).
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| H A D | tao.md | 2447 Optimization Using No Derivatives for sums of Squares) algorithm
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