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psblas3:

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base/modules/psb_c_base_mat_mod.f90
 base/modules/psb_d_base_mat_mod.f90
 base/modules/psb_s_base_mat_mod.f90
 base/modules/psb_z_base_mat_mod.f90

Updates for doxygen.
This commit is contained in:
Salvatore Filippone
2012-02-22 17:30:29 +00:00
parent 6cd3709757
commit 7189e5e1ad
4 changed files with 684 additions and 32 deletions
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base/modules/psb_c_base_mat_mod.f90
+171 -8
View File
@@ -601,13 +601,21 @@ module psb_c_base_mat_mod
end interface
!
! Matrix-vector products.
! Y = alpha*A*X + beta*Y
!
! vect_mv relies on csmv for those data types
! not specifically using the encapsulation to handle
! foreign data.
!
!> Function csmm:
!! \brief Product by a dense rank 2 array.
!!
!! Compute
!! Y = alpha*op(A)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:,:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:,:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!!
!
interface
subroutine psb_c_base_csmm(alpha,a,x,beta,y,info,trans)
@@ -620,6 +628,22 @@ module psb_c_base_mat_mod
end subroutine psb_c_base_csmm
end interface
!> Function csmv:
!! \brief Product by a dense rank 1 array.
!!
!! Compute
!! Y = alpha*op(A)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!!
!
interface
subroutine psb_c_base_csmv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_c_base_sparse_mat, psb_spk_
@@ -631,6 +655,22 @@ module psb_c_base_mat_mod
end subroutine psb_c_base_csmv
end interface
!> Function vect_mv:
!! \brief Product by an encapsulated array type(psb_c_vect_type)
!!
!! Compute
!! Y = alpha*op(A)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x the input X
!! \param beta Scaling factor for y
!! \param y the input/output Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!!
!
interface
subroutine psb_c_base_vect_mv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_c_base_sparse_mat, psb_spk_, psb_c_base_vect_type
@@ -649,6 +689,26 @@ module psb_c_base_mat_mod
! level, and they take care of the SCALE and D control arguments.
! So the derived classes need to override only the INNER_ methods.
!
!
!> Function cssm:
!! \brief Triangular system solve by a dense rank 2 array.
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! Internal workhorse called by cssm.
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:,:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:,:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!!
!
interface
subroutine psb_c_base_inner_cssm(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_c_base_sparse_mat, psb_spk_
@@ -660,6 +720,29 @@ module psb_c_base_mat_mod
end subroutine psb_c_base_inner_cssm
end interface
!
!> Function cssv:
!! \brief Triangular system solve by a dense rank 1 array.
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! Internal workhorse called by cssv.
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!! \param scale [N] Apply a scaling on Right (R) i.e. ADX
!! or on the Left (L) i.e. DAx
!! \param D(:) [none] Diagonal for scaling.
!!
!
interface
subroutine psb_c_base_inner_cssv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_c_base_sparse_mat, psb_spk_
@@ -671,6 +754,25 @@ module psb_c_base_mat_mod
end subroutine psb_c_base_inner_cssv
end interface
!
!> Function inner_vect_cssv:
!! \brief Triangular system solve by
!! an encapsulated array type(psb_c_vect_type)
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! Internal workhorse called by vect_cssv.
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x the input dense X
!! \param beta Scaling factor for y
!! \param y the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!
interface
subroutine psb_c_base_inner_vect_sv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_c_base_sparse_mat, psb_spk_, psb_c_base_vect_type
@@ -682,6 +784,26 @@ module psb_c_base_mat_mod
end subroutine psb_c_base_inner_vect_sv
end interface
!
!> Function cssm:
!! \brief Triangular system solve by a dense rank 2 array.
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:,:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:,:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!! \param scale [N] Apply a scaling on Right (R) i.e. ADX
!! or on the Left (L) i.e. DAx
!! \param D(:) [none] Diagonal for scaling.
!!
!
interface
subroutine psb_c_base_cssm(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_c_base_sparse_mat, psb_spk_
@@ -694,6 +816,26 @@ module psb_c_base_mat_mod
end subroutine psb_c_base_cssm
end interface
!
!> Function cssv:
!! \brief Triangular system solve by a dense rank 1 array.
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!! \param scale [N] Apply a scaling on Right (R) i.e. ADX
!! or on the Left (L) i.e. DAx
!! \param D(:) [none] Diagonal for scaling.
!!
!
interface
subroutine psb_c_base_cssv(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_c_base_sparse_mat, psb_spk_
@@ -705,7 +847,28 @@ module psb_c_base_mat_mod
complex(psb_spk_), intent(in), optional :: d(:)
end subroutine psb_c_base_cssv
end interface
!
!> Function vect_cssv:
!! \brief Triangular system solve by
!! an encapsulated array type(psb_c_vect_type)
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x the input dense X
!! \param beta Scaling factor for y
!! \param y the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!! \param scale [N] Apply a scaling on Right (R) i.e. ADX
!! or on the Left (L) i.e. DAx
!! \param D [none] Diagonal for scaling.
!!
!
interface
subroutine psb_c_base_vect_cssv(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_c_base_sparse_mat, psb_spk_,psb_c_base_vect_type
base/modules/psb_d_base_mat_mod.f90
+171 -8
View File
@@ -601,13 +601,21 @@ module psb_d_base_mat_mod
end interface
!
! Matrix-vector products.
! Y = alpha*A*X + beta*Y
!
! vect_mv relies on csmv for those data types
! not specifically using the encapsulation to handle
! foreign data.
!
!> Function csmm:
!! \brief Product by a dense rank 2 array.
!!
!! Compute
!! Y = alpha*op(A)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:,:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:,:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!!
!
interface
subroutine psb_d_base_csmm(alpha,a,x,beta,y,info,trans)
@@ -620,6 +628,22 @@ module psb_d_base_mat_mod
end subroutine psb_d_base_csmm
end interface
!> Function csmv:
!! \brief Product by a dense rank 1 array.
!!
!! Compute
!! Y = alpha*op(A)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!!
!
interface
subroutine psb_d_base_csmv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_d_base_sparse_mat, psb_dpk_
@@ -631,6 +655,22 @@ module psb_d_base_mat_mod
end subroutine psb_d_base_csmv
end interface
!> Function vect_mv:
!! \brief Product by an encapsulated array type(psb_d_vect_type)
!!
!! Compute
!! Y = alpha*op(A)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x the input X
!! \param beta Scaling factor for y
!! \param y the input/output Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!!
!
interface
subroutine psb_d_base_vect_mv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_d_base_sparse_mat, psb_dpk_, psb_d_base_vect_type
@@ -649,6 +689,26 @@ module psb_d_base_mat_mod
! level, and they take care of the SCALE and D control arguments.
! So the derived classes need to override only the INNER_ methods.
!
!
!> Function cssm:
!! \brief Triangular system solve by a dense rank 2 array.
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! Internal workhorse called by cssm.
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:,:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:,:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!!
!
interface
subroutine psb_d_base_inner_cssm(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_d_base_sparse_mat, psb_dpk_
@@ -660,6 +720,29 @@ module psb_d_base_mat_mod
end subroutine psb_d_base_inner_cssm
end interface
!
!> Function cssv:
!! \brief Triangular system solve by a dense rank 1 array.
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! Internal workhorse called by cssv.
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!! \param scale [N] Apply a scaling on Right (R) i.e. ADX
!! or on the Left (L) i.e. DAx
!! \param D(:) [none] Diagonal for scaling.
!!
!
interface
subroutine psb_d_base_inner_cssv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_d_base_sparse_mat, psb_dpk_
@@ -671,6 +754,25 @@ module psb_d_base_mat_mod
end subroutine psb_d_base_inner_cssv
end interface
!
!> Function inner_vect_cssv:
!! \brief Triangular system solve by
!! an encapsulated array type(psb_d_vect_type)
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! Internal workhorse called by vect_cssv.
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x the input dense X
!! \param beta Scaling factor for y
!! \param y the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!
interface
subroutine psb_d_base_inner_vect_sv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_d_base_sparse_mat, psb_dpk_, psb_d_base_vect_type
@@ -682,6 +784,26 @@ module psb_d_base_mat_mod
end subroutine psb_d_base_inner_vect_sv
end interface
!
!> Function cssm:
!! \brief Triangular system solve by a dense rank 2 array.
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:,:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:,:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!! \param scale [N] Apply a scaling on Right (R) i.e. ADX
!! or on the Left (L) i.e. DAx
!! \param D(:) [none] Diagonal for scaling.
!!
!
interface
subroutine psb_d_base_cssm(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_d_base_sparse_mat, psb_dpk_
@@ -694,6 +816,26 @@ module psb_d_base_mat_mod
end subroutine psb_d_base_cssm
end interface
!
!> Function cssv:
!! \brief Triangular system solve by a dense rank 1 array.
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!! \param scale [N] Apply a scaling on Right (R) i.e. ADX
!! or on the Left (L) i.e. DAx
!! \param D(:) [none] Diagonal for scaling.
!!
!
interface
subroutine psb_d_base_cssv(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_d_base_sparse_mat, psb_dpk_
@@ -705,7 +847,28 @@ module psb_d_base_mat_mod
real(psb_dpk_), intent(in), optional :: d(:)
end subroutine psb_d_base_cssv
end interface
!
!> Function vect_cssv:
!! \brief Triangular system solve by
!! an encapsulated array type(psb_d_vect_type)
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x the input dense X
!! \param beta Scaling factor for y
!! \param y the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!! \param scale [N] Apply a scaling on Right (R) i.e. ADX
!! or on the Left (L) i.e. DAx
!! \param D [none] Diagonal for scaling.
!!
!
interface
subroutine psb_d_base_vect_cssv(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_d_base_sparse_mat, psb_dpk_,psb_d_base_vect_type
base/modules/psb_s_base_mat_mod.f90
+171 -8
View File
@@ -601,13 +601,21 @@ module psb_s_base_mat_mod
end interface
!
! Matrix-vector products.
! Y = alpha*A*X + beta*Y
!
! vect_mv relies on csmv for those data types
! not specifically using the encapsulation to handle
! foreign data.
!
!> Function csmm:
!! \brief Product by a dense rank 2 array.
!!
!! Compute
!! Y = alpha*op(A)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:,:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:,:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!!
!
interface
subroutine psb_s_base_csmm(alpha,a,x,beta,y,info,trans)
@@ -620,6 +628,22 @@ module psb_s_base_mat_mod
end subroutine psb_s_base_csmm
end interface
!> Function csmv:
!! \brief Product by a dense rank 1 array.
!!
!! Compute
!! Y = alpha*op(A)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!!
!
interface
subroutine psb_s_base_csmv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_s_base_sparse_mat, psb_spk_
@@ -631,6 +655,22 @@ module psb_s_base_mat_mod
end subroutine psb_s_base_csmv
end interface
!> Function vect_mv:
!! \brief Product by an encapsulated array type(psb_s_vect_type)
!!
!! Compute
!! Y = alpha*op(A)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x the input X
!! \param beta Scaling factor for y
!! \param y the input/output Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!!
!
interface
subroutine psb_s_base_vect_mv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_s_base_sparse_mat, psb_spk_, psb_s_base_vect_type
@@ -649,6 +689,26 @@ module psb_s_base_mat_mod
! level, and they take care of the SCALE and D control arguments.
! So the derived classes need to override only the INNER_ methods.
!
!
!> Function cssm:
!! \brief Triangular system solve by a dense rank 2 array.
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! Internal workhorse called by cssm.
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:,:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:,:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!!
!
interface
subroutine psb_s_base_inner_cssm(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_s_base_sparse_mat, psb_spk_
@@ -660,6 +720,29 @@ module psb_s_base_mat_mod
end subroutine psb_s_base_inner_cssm
end interface
!
!> Function cssv:
!! \brief Triangular system solve by a dense rank 1 array.
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! Internal workhorse called by cssv.
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!! \param scale [N] Apply a scaling on Right (R) i.e. ADX
!! or on the Left (L) i.e. DAx
!! \param D(:) [none] Diagonal for scaling.
!!
!
interface
subroutine psb_s_base_inner_cssv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_s_base_sparse_mat, psb_spk_
@@ -671,6 +754,25 @@ module psb_s_base_mat_mod
end subroutine psb_s_base_inner_cssv
end interface
!
!> Function inner_vect_cssv:
!! \brief Triangular system solve by
!! an encapsulated array type(psb_s_vect_type)
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! Internal workhorse called by vect_cssv.
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x the input dense X
!! \param beta Scaling factor for y
!! \param y the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!
interface
subroutine psb_s_base_inner_vect_sv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_s_base_sparse_mat, psb_spk_, psb_s_base_vect_type
@@ -682,6 +784,26 @@ module psb_s_base_mat_mod
end subroutine psb_s_base_inner_vect_sv
end interface
!
!> Function cssm:
!! \brief Triangular system solve by a dense rank 2 array.
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:,:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:,:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!! \param scale [N] Apply a scaling on Right (R) i.e. ADX
!! or on the Left (L) i.e. DAx
!! \param D(:) [none] Diagonal for scaling.
!!
!
interface
subroutine psb_s_base_cssm(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_s_base_sparse_mat, psb_spk_
@@ -694,6 +816,26 @@ module psb_s_base_mat_mod
end subroutine psb_s_base_cssm
end interface
!
!> Function cssv:
!! \brief Triangular system solve by a dense rank 1 array.
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!! \param scale [N] Apply a scaling on Right (R) i.e. ADX
!! or on the Left (L) i.e. DAx
!! \param D(:) [none] Diagonal for scaling.
!!
!
interface
subroutine psb_s_base_cssv(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_s_base_sparse_mat, psb_spk_
@@ -705,7 +847,28 @@ module psb_s_base_mat_mod
real(psb_spk_), intent(in), optional :: d(:)
end subroutine psb_s_base_cssv
end interface
!
!> Function vect_cssv:
!! \brief Triangular system solve by
!! an encapsulated array type(psb_s_vect_type)
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x the input dense X
!! \param beta Scaling factor for y
!! \param y the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!! \param scale [N] Apply a scaling on Right (R) i.e. ADX
!! or on the Left (L) i.e. DAx
!! \param D [none] Diagonal for scaling.
!!
!
interface
subroutine psb_s_base_vect_cssv(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_s_base_sparse_mat, psb_spk_,psb_s_base_vect_type
base/modules/psb_z_base_mat_mod.f90
+171 -8
View File
@@ -601,13 +601,21 @@ module psb_z_base_mat_mod
end interface
!
! Matrix-vector products.
! Y = alpha*A*X + beta*Y
!
! vect_mv relies on csmv for those data types
! not specifically using the encapsulation to handle
! foreign data.
!
!> Function csmm:
!! \brief Product by a dense rank 2 array.
!!
!! Compute
!! Y = alpha*op(A)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:,:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:,:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!!
!
interface
subroutine psb_z_base_csmm(alpha,a,x,beta,y,info,trans)
@@ -620,6 +628,22 @@ module psb_z_base_mat_mod
end subroutine psb_z_base_csmm
end interface
!> Function csmv:
!! \brief Product by a dense rank 1 array.
!!
!! Compute
!! Y = alpha*op(A)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!!
!
interface
subroutine psb_z_base_csmv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_z_base_sparse_mat, psb_dpk_
@@ -631,6 +655,22 @@ module psb_z_base_mat_mod
end subroutine psb_z_base_csmv
end interface
!> Function vect_mv:
!! \brief Product by an encapsulated array type(psb_z_vect_type)
!!
!! Compute
!! Y = alpha*op(A)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x the input X
!! \param beta Scaling factor for y
!! \param y the input/output Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!!
!
interface
subroutine psb_z_base_vect_mv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_z_base_sparse_mat, psb_dpk_, psb_z_base_vect_type
@@ -649,6 +689,26 @@ module psb_z_base_mat_mod
! level, and they take care of the SCALE and D control arguments.
! So the derived classes need to override only the INNER_ methods.
!
!
!> Function cssm:
!! \brief Triangular system solve by a dense rank 2 array.
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! Internal workhorse called by cssm.
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:,:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:,:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!!
!
interface
subroutine psb_z_base_inner_cssm(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_z_base_sparse_mat, psb_dpk_
@@ -660,6 +720,29 @@ module psb_z_base_mat_mod
end subroutine psb_z_base_inner_cssm
end interface
!
!> Function cssv:
!! \brief Triangular system solve by a dense rank 1 array.
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! Internal workhorse called by cssv.
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!! \param scale [N] Apply a scaling on Right (R) i.e. ADX
!! or on the Left (L) i.e. DAx
!! \param D(:) [none] Diagonal for scaling.
!!
!
interface
subroutine psb_z_base_inner_cssv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_z_base_sparse_mat, psb_dpk_
@@ -671,6 +754,25 @@ module psb_z_base_mat_mod
end subroutine psb_z_base_inner_cssv
end interface
!
!> Function inner_vect_cssv:
!! \brief Triangular system solve by
!! an encapsulated array type(psb_z_vect_type)
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! Internal workhorse called by vect_cssv.
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x the input dense X
!! \param beta Scaling factor for y
!! \param y the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!
interface
subroutine psb_z_base_inner_vect_sv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_z_base_sparse_mat, psb_dpk_, psb_z_base_vect_type
@@ -682,6 +784,26 @@ module psb_z_base_mat_mod
end subroutine psb_z_base_inner_vect_sv
end interface
!
!> Function cssm:
!! \brief Triangular system solve by a dense rank 2 array.
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:,:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:,:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!! \param scale [N] Apply a scaling on Right (R) i.e. ADX
!! or on the Left (L) i.e. DAx
!! \param D(:) [none] Diagonal for scaling.
!!
!
interface
subroutine psb_z_base_cssm(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_z_base_sparse_mat, psb_dpk_
@@ -694,6 +816,26 @@ module psb_z_base_mat_mod
end subroutine psb_z_base_cssm
end interface
!
!> Function cssv:
!! \brief Triangular system solve by a dense rank 1 array.
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x(:) the input dense X
!! \param beta Scaling factor for y
!! \param y(:) the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!! \param scale [N] Apply a scaling on Right (R) i.e. ADX
!! or on the Left (L) i.e. DAx
!! \param D(:) [none] Diagonal for scaling.
!!
!
interface
subroutine psb_z_base_cssv(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_z_base_sparse_mat, psb_dpk_
@@ -705,7 +847,28 @@ module psb_z_base_mat_mod
complex(psb_dpk_), intent(in), optional :: d(:)
end subroutine psb_z_base_cssv
end interface
!
!> Function vect_cssv:
!! \brief Triangular system solve by
!! an encapsulated array type(psb_z_vect_type)
!!
!! Compute
!! Y = alpha*op(A^-1)*X + beta*Y
!!
!! \param alpha Scaling factor for Ax
!! \param A the input sparse matrix
!! \param x the input dense X
!! \param beta Scaling factor for y
!! \param y the input/output dense Y
!! \param info return code
!! \param trans [N] Whether to use A (N), its transpose (T)
!! or its conjugate transpose (C)
!! \param scale [N] Apply a scaling on Right (R) i.e. ADX
!! or on the Left (L) i.e. DAx
!! \param D [none] Diagonal for scaling.
!!
!
interface
subroutine psb_z_base_vect_cssv(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_z_base_sparse_mat, psb_dpk_,psb_z_base_vect_type