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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.
psblas3-type-indexed
Salvatore Filippone 13 years ago
parent 6cd3709757
commit 7189e5e1ad
4 changed files with 684 additions and 32 deletions
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179
base/modules/psb_c_base_mat_mod.f90
Unescape Escape View File

@ -601,13 +601,21 @@ module psb_c_base_mat_mod
end interface end interface
! !
! Matrix-vector products. !> Function csmm:
! Y = alpha*A*X + beta*Y !! \brief Product by a dense rank 2 array.
! !!
! vect_mv relies on csmv for those data types !! Compute
! not specifically using the encapsulation to handle !! Y = alpha*op(A)*X + beta*Y
! foreign data. !!
! !! \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 interface
subroutine psb_c_base_csmm(alpha,a,x,beta,y,info,trans) 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 subroutine psb_c_base_csmm
end interface 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 interface
subroutine psb_c_base_csmv(alpha,a,x,beta,y,info,trans) subroutine psb_c_base_csmv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_c_base_sparse_mat, psb_spk_ 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 subroutine psb_c_base_csmv
end interface 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 interface
subroutine psb_c_base_vect_mv(alpha,a,x,beta,y,info,trans) 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 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. ! level, and they take care of the SCALE and D control arguments.
! So the derived classes need to override only the INNER_ methods. ! 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 interface
subroutine psb_c_base_inner_cssm(alpha,a,x,beta,y,info,trans) subroutine psb_c_base_inner_cssm(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_c_base_sparse_mat, psb_spk_ 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 subroutine psb_c_base_inner_cssm
end interface 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 interface
subroutine psb_c_base_inner_cssv(alpha,a,x,beta,y,info,trans) subroutine psb_c_base_inner_cssv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_c_base_sparse_mat, psb_spk_ 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 subroutine psb_c_base_inner_cssv
end interface 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 interface
subroutine psb_c_base_inner_vect_sv(alpha,a,x,beta,y,info,trans) 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 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 subroutine psb_c_base_inner_vect_sv
end interface 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 interface
subroutine psb_c_base_cssm(alpha,a,x,beta,y,info,trans,scale,d) subroutine psb_c_base_cssm(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_c_base_sparse_mat, psb_spk_ 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 subroutine psb_c_base_cssm
end interface 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 interface
subroutine psb_c_base_cssv(alpha,a,x,beta,y,info,trans,scale,d) subroutine psb_c_base_cssv(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_c_base_sparse_mat, psb_spk_ 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(:) complex(psb_spk_), intent(in), optional :: d(:)
end subroutine psb_c_base_cssv end subroutine psb_c_base_cssv
end interface 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 interface
subroutine psb_c_base_vect_cssv(alpha,a,x,beta,y,info,trans,scale,d) 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 import :: psb_ipk_, psb_c_base_sparse_mat, psb_spk_,psb_c_base_vect_type

179
base/modules/psb_d_base_mat_mod.f90
Unescape Escape View File

@ -601,13 +601,21 @@ module psb_d_base_mat_mod
end interface end interface
! !
! Matrix-vector products. !> Function csmm:
! Y = alpha*A*X + beta*Y !! \brief Product by a dense rank 2 array.
! !!
! vect_mv relies on csmv for those data types !! Compute
! not specifically using the encapsulation to handle !! Y = alpha*op(A)*X + beta*Y
! foreign data. !!
! !! \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 interface
subroutine psb_d_base_csmm(alpha,a,x,beta,y,info,trans) 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 subroutine psb_d_base_csmm
end interface 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 interface
subroutine psb_d_base_csmv(alpha,a,x,beta,y,info,trans) subroutine psb_d_base_csmv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_d_base_sparse_mat, psb_dpk_ 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 subroutine psb_d_base_csmv
end interface 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 interface
subroutine psb_d_base_vect_mv(alpha,a,x,beta,y,info,trans) 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 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. ! level, and they take care of the SCALE and D control arguments.
! So the derived classes need to override only the INNER_ methods. ! 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 interface
subroutine psb_d_base_inner_cssm(alpha,a,x,beta,y,info,trans) subroutine psb_d_base_inner_cssm(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_d_base_sparse_mat, psb_dpk_ 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 subroutine psb_d_base_inner_cssm
end interface 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 interface
subroutine psb_d_base_inner_cssv(alpha,a,x,beta,y,info,trans) subroutine psb_d_base_inner_cssv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_d_base_sparse_mat, psb_dpk_ 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 subroutine psb_d_base_inner_cssv
end interface 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 interface
subroutine psb_d_base_inner_vect_sv(alpha,a,x,beta,y,info,trans) 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 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 subroutine psb_d_base_inner_vect_sv
end interface 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 interface
subroutine psb_d_base_cssm(alpha,a,x,beta,y,info,trans,scale,d) subroutine psb_d_base_cssm(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_d_base_sparse_mat, psb_dpk_ 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 subroutine psb_d_base_cssm
end interface 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 interface
subroutine psb_d_base_cssv(alpha,a,x,beta,y,info,trans,scale,d) subroutine psb_d_base_cssv(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_d_base_sparse_mat, psb_dpk_ 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(:) real(psb_dpk_), intent(in), optional :: d(:)
end subroutine psb_d_base_cssv end subroutine psb_d_base_cssv
end interface 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 interface
subroutine psb_d_base_vect_cssv(alpha,a,x,beta,y,info,trans,scale,d) 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 import :: psb_ipk_, psb_d_base_sparse_mat, psb_dpk_,psb_d_base_vect_type

179
base/modules/psb_s_base_mat_mod.f90
Unescape Escape View File

@ -601,13 +601,21 @@ module psb_s_base_mat_mod
end interface end interface
! !
! Matrix-vector products. !> Function csmm:
! Y = alpha*A*X + beta*Y !! \brief Product by a dense rank 2 array.
! !!
! vect_mv relies on csmv for those data types !! Compute
! not specifically using the encapsulation to handle !! Y = alpha*op(A)*X + beta*Y
! foreign data. !!
! !! \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 interface
subroutine psb_s_base_csmm(alpha,a,x,beta,y,info,trans) 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 subroutine psb_s_base_csmm
end interface 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 interface
subroutine psb_s_base_csmv(alpha,a,x,beta,y,info,trans) subroutine psb_s_base_csmv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_s_base_sparse_mat, psb_spk_ 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 subroutine psb_s_base_csmv
end interface 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 interface
subroutine psb_s_base_vect_mv(alpha,a,x,beta,y,info,trans) 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 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. ! level, and they take care of the SCALE and D control arguments.
! So the derived classes need to override only the INNER_ methods. ! 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 interface
subroutine psb_s_base_inner_cssm(alpha,a,x,beta,y,info,trans) subroutine psb_s_base_inner_cssm(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_s_base_sparse_mat, psb_spk_ 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 subroutine psb_s_base_inner_cssm
end interface 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 interface
subroutine psb_s_base_inner_cssv(alpha,a,x,beta,y,info,trans) subroutine psb_s_base_inner_cssv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_s_base_sparse_mat, psb_spk_ 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 subroutine psb_s_base_inner_cssv
end interface 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 interface
subroutine psb_s_base_inner_vect_sv(alpha,a,x,beta,y,info,trans) 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 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 subroutine psb_s_base_inner_vect_sv
end interface 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 interface
subroutine psb_s_base_cssm(alpha,a,x,beta,y,info,trans,scale,d) subroutine psb_s_base_cssm(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_s_base_sparse_mat, psb_spk_ 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 subroutine psb_s_base_cssm
end interface 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 interface
subroutine psb_s_base_cssv(alpha,a,x,beta,y,info,trans,scale,d) subroutine psb_s_base_cssv(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_s_base_sparse_mat, psb_spk_ 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(:) real(psb_spk_), intent(in), optional :: d(:)
end subroutine psb_s_base_cssv end subroutine psb_s_base_cssv
end interface 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 interface
subroutine psb_s_base_vect_cssv(alpha,a,x,beta,y,info,trans,scale,d) 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 import :: psb_ipk_, psb_s_base_sparse_mat, psb_spk_,psb_s_base_vect_type

179
base/modules/psb_z_base_mat_mod.f90
Unescape Escape View File

@ -601,13 +601,21 @@ module psb_z_base_mat_mod
end interface end interface
! !
! Matrix-vector products. !> Function csmm:
! Y = alpha*A*X + beta*Y !! \brief Product by a dense rank 2 array.
! !!
! vect_mv relies on csmv for those data types !! Compute
! not specifically using the encapsulation to handle !! Y = alpha*op(A)*X + beta*Y
! foreign data. !!
! !! \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 interface
subroutine psb_z_base_csmm(alpha,a,x,beta,y,info,trans) 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 subroutine psb_z_base_csmm
end interface 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 interface
subroutine psb_z_base_csmv(alpha,a,x,beta,y,info,trans) subroutine psb_z_base_csmv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_z_base_sparse_mat, psb_dpk_ 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 subroutine psb_z_base_csmv
end interface 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 interface
subroutine psb_z_base_vect_mv(alpha,a,x,beta,y,info,trans) 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 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. ! level, and they take care of the SCALE and D control arguments.
! So the derived classes need to override only the INNER_ methods. ! 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 interface
subroutine psb_z_base_inner_cssm(alpha,a,x,beta,y,info,trans) subroutine psb_z_base_inner_cssm(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_z_base_sparse_mat, psb_dpk_ 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 subroutine psb_z_base_inner_cssm
end interface 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 interface
subroutine psb_z_base_inner_cssv(alpha,a,x,beta,y,info,trans) subroutine psb_z_base_inner_cssv(alpha,a,x,beta,y,info,trans)
import :: psb_ipk_, psb_z_base_sparse_mat, psb_dpk_ 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 subroutine psb_z_base_inner_cssv
end interface 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 interface
subroutine psb_z_base_inner_vect_sv(alpha,a,x,beta,y,info,trans) 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 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 subroutine psb_z_base_inner_vect_sv
end interface 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 interface
subroutine psb_z_base_cssm(alpha,a,x,beta,y,info,trans,scale,d) subroutine psb_z_base_cssm(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_z_base_sparse_mat, psb_dpk_ 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 subroutine psb_z_base_cssm
end interface 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 interface
subroutine psb_z_base_cssv(alpha,a,x,beta,y,info,trans,scale,d) subroutine psb_z_base_cssv(alpha,a,x,beta,y,info,trans,scale,d)
import :: psb_ipk_, psb_z_base_sparse_mat, psb_dpk_ 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(:) complex(psb_dpk_), intent(in), optional :: d(:)
end subroutine psb_z_base_cssv end subroutine psb_z_base_cssv
end interface 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 interface
subroutine psb_z_base_vect_cssv(alpha,a,x,beta,y,info,trans,scale,d) 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 import :: psb_ipk_, psb_z_base_sparse_mat, psb_dpk_,psb_z_base_vect_type

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