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cgsarkar3.f90
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!integration with DDSCAT
!changed subroutine names by adding 90 at the end
SUBROUTINE gacg90ver2(cx,cy,n,cxsc,mxcxsc,matvec, cmatvec, cg)
USE ddprecision, ONLY : wp
use cgmodule
implicit none
type (cgstruct) cg
! Purpose: GACG --- generalized augumented conjugate gradient method
! for unsymmetric case
! History: 1988 (TKS); original version
! 92/06/09 (PJF); re-written using "BLAS"-type style
! 92/09/11 (TLS); Removed unnecessary zeroing.
! .. Parameters ..
! .. Scalar Arguments ..
REAL (wp) ::epsilon_err
INTEGER :: iter, maxit, n, alloc_error, dealloc_error,ioerr
! .. Array Arguments ..
COMPLEX (wp) :: cx(n), cy(n)
integer mxcxsc
complex(wp),target:: cxsc(n,8)
! .. Local Scalars ..
REAL (wp) :: ak, ay, bk, bw2, q2, sk, sk2
! .. Local Arrays ..
COMPLEX (wp), pointer :: cbq(:), cbw(:), cq(:), cw(:)
! .. External Functions ..
! .. External Subroutines ..
EXTERNAL matvec, cmatvec
! .. Intrinsic Functions ..
INTRINSIC conjg, sqrt
maxit=cg%maxit
epsilon_err=cg%epsilon_err
ioerr=cg%ioerr
if(n*8 .gt. mxcxsc) &
stop 'stop in sarkar routine gacg90ver2 n*8> mxcxsc not enough memory'
cbq => cxsc(:,1)
cbw => cxsc(:,3)
cq => cxsc(:,5)
cw => cxsc(:,7)
! allocate(cbq(2*n), cbw(2*n), cq(2*n), cw(2*n),STAT=alloc_error)
! IF (alloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)') &
! 'Allocation Error Detected in conjugate gradient gacg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' gacg '
! END IF
iter = 0
ay=2._wp*dot_product(cy(1:n),cy(1:n))
! CALL prod(n,'u',cx,'u',cq)
call matvec(cx,cq,n)
! CALL prod(n,'c',cx,'u',cq(n+1))
call cmatvec(cx,cq(n+1),n)
!
cq(1:n) = cy(1:n) - cq(1:n)
cq(n+1:2*n) = conjg(cy(1:n)) - cq(n+1:2*n)
cw(1:n) = cq(1:n)
cw(n+1:2*n) = cq(n+1:2*n)
! CALL prod(n,'u',cq(n+1),'u',cbq)
call matvec(cq(n+1),cbq,n)
cbq(n+1:2*n)=cmplx(0.0_wp,0.0_wp,kind=wp)
! CALL prod(n,'c',cq,'u',cbq(n+1))
call matvec(cq,cbq(n+1),n)
!
sk = 2.0_wp*sum(cbq(1:n)*conjg(cq(1:n)))
cbw(1:2*n) = cbq(1:2*n)
bw2=dot_product(cbw(1:2*n),cbw(1:2*n))
30 CONTINUE
ak = sk/bw2
cx(1:n)=cx(1:n)+ak*cw(n+1:2*n)
cq(1:2*n)=cq(1:2*n)-ak*cbw(1:2*n)
q2=dot_product(cq(1:2*n),cq(1:2*n))
if(cg%print.eq.'print')WRITE (*,fmt=*) &
'sqrt(q2/ay)= ', iter, sqrt(q2/ay)
cg%itno=iter
IF ((sqrt(q2/ay)).LT.epsilon_err) GO TO 50
! CALL prod(n,'u',cq(n+1),'u',cbq)
call matvec(cq(n+1),cbq,n)
! CALL prod(n,'c',cq,'u',cbq(n+1))
call cmatvec(cq,cbq(n+1),n)
!
sk2 = 2.0_wp*sum(cbq(1:n)*conjg(cq(1:n)))
bk = sk2/sk
! Warning there are differences in results (very small) when the code is run in
! double precision two times. First time we use section 1, which is "fortran 77"
! construct with do loops. Second time I run section 2 which is "fortran 90"
! type construct. I do not know what is the problem. This problems is not
! occuring if the code is run in single precision. One would think that there
! should not be any difference.
! PJF
!section 1
! DO i = 1, 2*n
! cw(i) = cq(i) + bk*cw(i)
! cbw(i) = cbq(i) + bk*cbw(i)
! END DO
! section 2
cw(1:2*n) = cq(1:2*n) + bk*cw(1:2*n)
cbw(1:2*n) = cbq(1:2*n) + bk*cbw(1:2*n)
bw2=dot_product(cbw(1:2*n),cbw(1:2*n))
sk = sk2
iter = iter + 1
IF (iter.GT.maxit) GO TO 50
GO TO 30
50 CONTINUE
! deallocate(cbq, cbw, cq, cw,STAT=dealloc_error)
! IF (dealloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)') &
! 'Deallcation Error Detected in conjugate gradient gacg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' gacg '
! END IF
RETURN
END SUBROUTINE gacg90ver2
SUBROUTINE gbicg90ver2(cx,cy,n,cxsc,mxcxsc,matvec, cmatvec, cg)
USE ddprecision, ONLY : wp
use cgmodule
implicit none
type (cgstruct) cg
! Purpose: GBICG --- generalized bi-conjugate gradient
! History: 1988 (TKS); original version
! 92/06/09 (PJF); re-written using "BLAS"-type style
! 92/09/11 (TLS); Removed unnecessary zeroing.
! .. Parameters ..
! .. Scalar Arguments ..
REAL (wp) ::epsilon_err
INTEGER :: iter, maxit, n, alloc_error, dealloc_error,ioerr
! .. Array Arguments ..
COMPLEX (wp) :: cx(n), cy(n)
! .. Local Scalars ..
COMPLEX (wp) :: cak, cbk, csk, csk2
REAL (wp) :: ay, ek
INTEGER :: i
integer mxcxsc
complex(wp),target:: cxsc(n,6)
! .. Local Arrays ..
COMPLEX (wp),pointer :: cap(:), caw(:), cp(:), cq(:), cr(:), cw(:)
! .. External Functions ..
! .. External Subroutines ..
EXTERNAL matvec, cmatvec
! .. Intrinsic Functions ..
INTRINSIC conjg, sqrt
maxit=cg%maxit
epsilon_err=cg%epsilon_err
ioerr=cg%ioerr
if(n*6 .gt. mxcxsc) &
stop 'stop in sarkar routine gbicg90ver2 n*6> mxcxsc not enough memory'
cap => cxsc(:,1)
caw => cxsc(:,2)
cp => cxsc(:,3)
cq => cxsc(:,4)
cr => cxsc(:,5)
cw => cxsc(:,6)
! allocate(cap(n), caw(n), cp(n), cq(n), cr(n), cw(n),STAT=alloc_error)
! IF (alloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)')
! 'Allocation Error Detected in conjugate gradient gbicg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' gbicg '
! END IF
iter = 0._wp
ay=dot_product(cy(1:n),cy(1:n))
! CALL prod(n,'u',cx,'u',cr)
call matvec(cx,cr,n)
csk = (0._wp,0._wp)
cr(1:n) = cy(1:n) - cr(1:n)
cq(1:n) = conjg(cr(1:n))
cw(1:n) = cq(1:n)
cp(1:n) = cr(1:n)
csk= sum(cr(1:n)*cr(1:n))
20 CONTINUE
! CALL prod(n,'c',cw,'u',caw)
call cmatvec(cw,caw,n)
! CALL prod(n,'u',cp,'u',cap)
call matvec(cp,cap,n)
cak = sum(cap(1:n)*conjg(cw(1:n)))
cak = csk/cak
cx(1:n)=cx(1:n)+cak*cp(1:n)
cr(1:n)=cr(1:n)-cak*cap(1:n)
cq(1:n)=cq(1:n)-conjg(cak)*caw(1:n)
csk2 = sum(cr(1:n)*conjg(cq(1:n)))
ek=dot_product(cr(1:n),cr(1:n))
if(cg%print.eq.'print') WRITE (*,fmt=*) 'sqrt(ek/ay)= ', iter, sqrt(ek/ay)
cg%itno=iter
IF ((sqrt(ek/ay)).LT.epsilon_err) GO TO 40
cbk = csk2/csk
cp(1:n) = cr(1:n) + cbk*cp(1:n)
cw(1:n) = cq(1:n) + conjg(cbk)*cw(1:n)
csk = csk2
iter = iter + 1
IF (iter.GT.maxit) GO TO 40
GO TO 20
40 CONTINUE
! deallocate(cap, caw, cp, cq, cr, cw, STAT=dealloc_error)
! IF (dealloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)')
! 'Deallcation Error Detected in conjugate gradient gbicg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' gbicg '
! END IF
RETURN
END SUBROUTINE gbicg90ver2
SUBROUTINE gmcg90ver2(cx,cy,n,cxsc,mxcxsc,matvec, cmatvec, cg)
USE ddprecision, ONLY : wp
use cgmodule
implicit none
type (cgstruct) cg
! Purpose: GMCG --- modified conjugate method for unsymmetric complex
! matrices
! History: 1988 (TKS); original version
! 92/06/09 (PJF); re-written using "BLAS"-type style
! 92/09/11 (TLS); Removed unnecessary zeroing.
! .. Parameters ..
! .. Scalar Arguments ..
REAL (wp) ::epsilon_err
INTEGER :: iter, maxit, n, alloc_error, dealloc_error,ioerr
! .. Array Arguments ..
COMPLEX (wp) :: cx(n), cy(n)
! .. Local Scalars ..
REAL (wp) :: ak, ay, bk, bk2, q2, w2
integer mxcxsc
complex(wp),target:: cxsc(n,8)
! .. Local Arrays ..
COMPLEX (wp), pointer :: cbw(:), cq(:), cw(:), cxh(:), cz(:)
! .. External Functions ..
! .. External Subroutines ..
EXTERNAL matvec, cmatvec
! .. Intrinsic Functions ..
INTRINSIC conjg, sqrt
maxit=cg%maxit
epsilon_err=cg%epsilon_err
ioerr=cg%ioerr
if(n*8 .gt. mxcxsc) &
stop 'stop in sarkar routine gmcg90ver2 n*8> mxcxsc not enough memory'
cbw => cxsc(:,1)
cq => cxsc(:,3)
cw => cxsc(:,5)
cxh => cxsc(:,7)
cz => cxsc(:,8)
! allocate(cbw(2*n), cq(2*n), cw(2*n), cxh(n), cz(n),STAT=alloc_error)
! IF (alloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)') &
! 'Allocation Error Detected in conjugate gradient gmcg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' gmcg '
! END IF
iter = 0
cz(1:n) = cx(1:n)
cxh(1:n) = cx(1:n)
ay=2._wp*dot_product(cy(1:n),cy(1:n))
! CALL prod(n,'u',cx,'u',cq)
call matvec(cx,cq,n)
! CALL prod(n,'c',cz,'u',cq(n+1))
call cmatvec(cz,cq(n+1),n)
!
cq(1:n) = cy(1:n) - cq(1:n)
cq(n+1:2*n) = conjg(cy(1:n)) - cq(n+1:2*n)
cw(1:n) = cq(1:n)
cw(n+1:2*n) = cq(n+1:2*n)
w2=dot_product(cw(1:2*n),cw(1:2*n))
30 CONTINUE
! CALL prod(n,'u',cw(n+1),'u',cbw)
call matvec(cw(n+1),cbw,n)
! CALL prod(n,'c',cw,'u',cbw(n+1))
call cmatvec(cw,cbw(n+1),n)
!
ak = 2.0_wp*sum(cbw(1:n)*conjg(cw(1:n)))
IF (ak.EQ.0._wp) THEN
PRINT *, ' gmcg. ak = 0 '
STOP
END IF
ak = w2/ak
cx(1:n)=cx(1:n)+ak*cw(n+1:2*n)
cz(1:n)=cz(1:n)+ak*cw(1:n)
cq(1:2*n)=cq(1:2*n)-ak*cbw(1:2*n)
q2=dot_product(cq(1:2*n),cq(1:2*n))
bk = q2/w2
bk2 = 1._wp + bk
cxh(1:n) = (cx(1:n)+bk*cxh(1:n))/bk2
cw(1:2*n) = (cq(1:2*n)+bk*cw(1:2*n))/bk2
w2=dot_product(cw(1:2*n),cw(1:2*n))
if(cg%print.eq.'print') &
WRITE (*,fmt=*) 'sqrt(w2/ay)= ', iter, sqrt(w2/ay)
cg%itno=iter
IF ((sqrt(w2/ay)).LT.epsilon_err) GO TO 60
iter = iter + 1
IF (iter.GT.maxit) GO TO 60
GO TO 30
60 CONTINUE
cx(1:n) = cxh(1:n)
! deallocate(cbw, cq, cw, cxh, cz, STAT=dealloc_error)
! IF (dealloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)') 'Deallcation Error Detected in conjugate gradient gmcg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' gmcg '
! END IF
RETURN
END SUBROUTINE gmcg90ver2
SUBROUTINE rcg90ver2(cx,cy,n,cxsc,mxcxsc,matvec, cmatvec, cg)
USE ddprecision, ONLY : wp
use cgmodule
implicit none
type (cgstruct) cg
! Purpose: RCG --- residual minimized; the residuals are minimized
! at each iteration, no scaling is introduced.
! History: 1988 (TKS); original version
! 92/06/09 (PJF); re-written using "BLAS"-type style
! 92/09/11 (TLS); Removed unnecessary zeroing.
! Warning there are differences in results (very small) when the code is run in
! double precision two times. First time we use section 1, which is "fortran 77"
! construct with do loops. Second time I run section 2 which is "fortran 90"
! type construct. I do not know what is the problem. This problems is not
! occuring if the code is run in single precision. One would think that there
! should not be any difference.
! PJF
! .. Parameters ..
! .. Scalar Arguments ..
REAL (wp) ::epsilon_err
INTEGER :: iter, maxit, n, alloc_error, dealloc_error,ioerr
! .. Array Arguments ..
COMPLEX (wp) :: cx(n), cy(n)
! .. Local Scalars ..
REAL (wp) :: ak, ay, ek, qk, sk, sk2
integer mxcxsc
complex(wp),target:: cxsc(n,3)
! .. Local Arrays ..
COMPLEX (wp), pointer :: cp(:), cprod(:), cr(:)
! .. External Functions ..
! .. External Subroutines ..
EXTERNAL matvec, cmatvec
! .. Intrinsic Functions ..
INTRINSIC sqrt
maxit=cg%maxit
epsilon_err=cg%epsilon_err
ioerr=cg%ioerr
if(n*3 .gt. mxcxsc) &
stop 'stop in sarkar routine rcg90ver2 n*3> mxcxsc not enough memory'
cp => cxsc(:,1)
cprod => cxsc(:,2)
cr => cxsc(:,3)
! allocate(cp(n), cprod(n), cr(n),STAT=alloc_error)
! IF (alloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)') &
! 'Allocation Error Detected in conjugate gradient rcg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' rcg '
! END IF
iter = 0
ay=dot_product(cy(1:n),cy(1:n))
! CALL prod(n,'u',cx,'u',cprod)
call matvec(cx,cprod,n)
cr(1:n) = cy(1:n) - cprod(1:n)
! CALL prod(n,'c',cr,'u',cp)
call cmatvec(cr,cp,n)
sk=dot_product(cp(1:n),cp(1:n))
20 CONTINUE
! CALL prod(n,'u',cp,'u',cprod)
call matvec(cp,cprod,n)
ak=dot_product(cprod(1:n),cprod(1:n))
ak = sk/ak
cx(1:n)=cx(1:n)+ak*cp(1:n)
cr(1:n)=cr(1:n)-ak*cprod(1:n)
ek=dot_product(cr(1:n),cr(1:n))
if(cg%print.eq.'print')WRITE (*,fmt=*) 'sqrt(ek/ay)= ', iter, sqrt(ek/ay)
cg%itno=iter
IF ((sqrt(ek/ay)).LT.epsilon_err) GO TO 40
! CALL prod(n,'c',cr,'u',cprod)
call cmatvec(cr,cprod,n)
!
sk2=dot_product(cprod(1:n),cprod(1:n))
qk = sk2/sk
cp(1:n) = cprod(1:n) + qk*cp(1:n)
iter = iter + 1
sk = sk2
IF (iter.GT.maxit) GO TO 40
GO TO 20
40 CONTINUE
! deallocate(cp, cprod, cr, STAT=dealloc_error)
! IF (dealloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)') &
! 'Deallcation Error Detected in conjugate gradient rcg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' rcg '
! END IF
RETURN
END SUBROUTINE rcg90ver2
SUBROUTINE sacg90ver2(cx,cy,n,cxsc,mxcxsc,matvec, cg)
USE ddprecision, ONLY : wp
use cgmodule
implicit none
type (cgstruct) cg
! Purpose: SACG --- augumented conjugate gradient method for symmetric
! case.
! History: 1988 (TKS); original version
! 92/06/09 (PJF); re-written using "BLAS"-type style
! 92/09/11 (TLS); Removed unnecessary zeroing.
! Warning there are differences in results (very small) when the code is run in
! double precision two times. First time we use section 1, which is "fortran 77"
! construct with do loops. Second time I run section 2 which is "fortran 90"
! type construct. I do not know what is the problem. This problems is not
! occuring if the code is run in single precision. One would think that there
! should not be any difference.
! PJF
! .. Parameters ..
! .. Scalar Arguments ..
REAL (wp) ::epsilon_err
INTEGER :: iter, maxit, n, alloc_error, dealloc_error,ioerr
! .. Array Arguments ..
COMPLEX (wp) :: cx(n), cy(n)
integer mxcxsc
complex(wp),target:: cxsc(n,4)
! .. Local Scalars ..
REAL (wp) :: ak, ap2, ay, bk, r2, sk, sk2
! .. Local Arrays ..
COMPLEX (wp), pointer :: cap(:), car(:), cp(:), cr(:)
! .. External Functions ..
! .. External Subroutines ..
EXTERNAL matvec
! .. Intrinsic Functions ..
INTRINSIC sqrt
maxit=cg%maxit
epsilon_err=cg%epsilon_err
ioerr=cg%ioerr
if(n*4 .gt. mxcxsc) &
stop 'stop in sarkar routine sacg90ver2 n*4> mxcxsc not enough memory'
cap => cxsc(:,1)
car => cxsc(:,2)
cp => cxsc(:,3)
cr => cxsc(:,4)
! allocate(cap(n), car(n), cp(n), cr(n),STAT=alloc_error)
! IF (alloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)') &
! 'Allocation Error Detected in conjugate gradient sacg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' sacg '
! END IF
iter = 0
ay=dot_product(cy(1:n),cy(1:n))
! CALL prod(n,'u',cx,'u',cr)
call matvec(cx,cr,n)
cr(1:n) = cy(1:n) - cr(1:n)
cp(1:n) = cr(1:n)
! CALL prod(n,'u',cr,'c',car)
call matvec(conjg(cr),car,n)
!
sk = sum(car(1:n)*conjg(cr(1:n)))
cap(1:n) = car(1:n)
ap2=dot_product(cap(1:n),cap(1:n))
30 CONTINUE
ak = sk/ap2
cx(1:n)=cx(1:n)+ak*conjg(cp(1:n))
cr(1:n)=cr(1:n)-ak*cap(1:n)
r2=dot_product(cr(1:n),cr(1:n))
car(1:n)=cmplx(0.0_wp,0.0_wp,kind=wp)
if(cg%print.eq.'print')WRITE (*,fmt=*) 'sqrt(r2/ay)= ', iter, sqrt(r2/ay)
cg%itno=iter
IF ((sqrt(r2/ay)).LT.epsilon_err) GO TO 50
! CALL prod(n,'u',cr,'c',car)
call matvec(conjg(cr),car,n)
!
sk2 = sum(car(1:n)*conjg(cr(1:n)))
bk = sk2/sk
cp(1:n) = cr(1:n) + bk*cp(1:n)
cap(1:n) = car(1:n) + bk*cap(1:n)
ap2=dot_product(cap(1:n),cap(1:n))
sk = sk2
iter = iter + 1
IF (iter.GT.maxit) GO TO 50
GO TO 30
50 CONTINUE
! deallocate(cap, car, cp, cr, STAT=dealloc_error)
! IF (dealloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)') &
! 'Deallcation Error Detected in conjugate gradient sacg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' sacg '
! END IF
RETURN
END SUBROUTINE sacg90ver2
SUBROUTINE sbicg90ver2(cx,cy,n,cxsc,mxcxsc,matvec, cg)
USE ddprecision, ONLY : wp
use cgmodule
implicit none
type (cgstruct) cg
! Purpose: SBICG --- simplified biconjugate gradient method specialized
! to symmetric matrices
! History: 1988 (TKS); original version
! 92/06/09 (PJF); re-written using "BLAS"-type style
! 92/09/11 (TLS); Removed unnecessary zeroing.
! 13.01.10 (BTD); added CMSGNM variable and call to WRIMSG
! to report progress in DDSCAT standard way...
! .. Parameters ..
! .. Scalar Arguments ..
CHARACTER :: CMSGNM*70
REAL (wp) :: epsilon_err, time
INTEGER :: iter, maxit, n, alloc_error, dealloc_error,ioerr
! .. Array Arguments ..
COMPLEX (wp) :: cx(n), cy(n)
! .. Local Scalars ..
COMPLEX (wp) :: cak, cbk, csk, csk2
REAL (wp) :: ay, ek
integer mxcxsc
complex(wp),target:: cxsc(n,3)
! .. Local Arrays ..
COMPLEX (wp), pointer :: cap(:), cp(:), cr(:)
! .. External Functions ..
! .. External Subroutines ..
EXTERNAL matvec
! .. Intrinsic Functions ..
INTRINSIC sqrt
maxit=cg%maxit
epsilon_err=cg%epsilon_err
ioerr=cg%ioerr
if(n*3 .gt. mxcxsc) &
stop 'stop in sarkar routine sbicgver2 n*3 > mxcxsc not enough memory'
cap => cxsc(:,1)
cp => cxsc(:,2)
cr => cxsc(:,3)
! allocate(cap(n), cp(n), cr(n),STAT=alloc_error)
! IF (alloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)') &
! 'Allocation Error Detected in conjugate gradient sbicg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' sbicg '
! END IF
iter = 0
ay=dot_product(cy(1:n),cy(1:n))
! CALL prod(n,'u',cx,'u',cr)
call matvec(cx,cr,n)
cr(1:n) = cy(1:n) - cr(1:n)
cp(1:n) = cr(1:n)
csk = sum(cr(1:n)*cr(1:n))
20 CONTINUE
! CALL prod(n,'u',cp,'u',cap)
call matvec(cp,cap,n)
cak = sum(cap(1:n)*cp(1:n))
cak = csk/cak
cx(1:n)=cx(1:n)+cak*cp(1:n)
cr(1:n)=cr(1:n)-cak*cap(1:n)
csk2 = sum(cr(1:n)*cr(1:n))
ek=dot_product(cr(1:n),cr(1:n))
IF(CG%PRINT.EQ.'print')THEN
WRITE(CMSGNM,FMT='(A,I8,A,1P,E10.3)') &
'IT=',ITER,' f.err=',SQRT(EK/AY)
CALL WRIMSG('SBICGM',CMSGNM)
! WRITE (*,fmt=*) 'sqrt(ek/ay)= ', iter, sqrt(ek/ay)
ENDIF
cg%itno=iter
IF ((sqrt(ek/ay)).LT.epsilon_err) GO TO 40
cbk = csk2/csk
cp(1:n) = cr(1:n) + cbk*cp(1:n)
csk = csk2
iter = iter + 1
IF (iter.GT.maxit) GO TO 40
GO TO 20
40 CONTINUE
! deallocate(cap, cp, cr, STAT=dealloc_error)
! IF (dealloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)') 'Deallcation Error Detected in conjugate gradient sbicg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' sbicg '
! END IF
RETURN
END SUBROUTINE sbicg90ver2
SUBROUTINE smcg90ver2(cx,cy,n,cxsc,mxcxsc,matvec, cg)
USE ddprecision, ONLY : wp
use cgmodule
implicit none
type (cgstruct) cg
! Purpose: SMCG --- modified conjugate gradient method for symmetric
! case.
! History: 1988 (TKS); original version
! 92/06/09 (PJF); re-written using "BLAS"-type style
! 92/09/11 (TLS); Removed unnecessary zeroing.
! .. Parameters ..
! .. Scalar Arguments ..
REAL (wp) ::epsilon_err
INTEGER :: iter, maxit, n, alloc_error, dealloc_error,ioerr
! .. Array Arguments ..
COMPLEX (wp) :: cx(n), cy(n)
! .. Local Scalars ..
REAL (wp) :: ak, ay, bk, bk2, p2, r2
integer mxcxsc
complex(wp),target:: cxsc(n,4)
! .. Local Arrays ..
COMPLEX (wp), pointer :: cap(:), cp(:), cr(:), cxh(:)
! .. External Functions ..
! .. External Subroutines ..
EXTERNAL matvec
! .. Intrinsic Functions ..
INTRINSIC sqrt
maxit=cg%maxit
epsilon_err=cg%epsilon_err
ioerr=cg%ioerr
if(n*4 .gt. mxcxsc) stop 'stop in sarkar routine smcg90ver2 n*4> mxcxsc not enough memory'
cap => cxsc(:,1)
cp => cxsc(:,2)
cr => cxsc(:,3)
cxh => cxsc(:,4)
! allocate(cap(n), cp(n), cr(n), cxh(n),STAT=alloc_error)
! IF (alloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)') 'Allocation Error Detected in conjugate gradient smcg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' smcg '
! END IF
iter = 0
cxh(1:n) = cx(1:n)
ay=dot_product(cy(1:n),cy(1:n))
! CALL prod(n,'u',cx,'u',cr)
call matvec(cx,cr,n)
cr(1:n) = cy(1:n) - cr(1:n)
cp(1:n) = cr(1:n)
p2=dot_product(cp(1:n),cp(1:n))
30 CONTINUE
! CALL prod(n,'u',cp,'c',cap)
call matvec(conjg(cp),cap,n)
!
ak = sum(cap(1:n)*conjg(cp(1:n)))
ak = p2/ak
cx(1:n)=cx(1:n)+ak*conjg(cp(1:n))
cr(1:n)=cr(1:n)-ak*cap(1:n)
r2=dot_product(cr(1:n),cr(1:n))
bk = r2/p2
bk2 = 1._wp + bk
cxh(1:n) = (cx(1:n)+bk*cxh(1:n))/bk2
cp(1:n) = (cr(1:n)+bk*cp(1:n))/bk2
p2=dot_product(cp(1:n),cp(1:n))
if(cg%print.eq.'print') WRITE (*,fmt=*) 'sqrt(p2/ay)= ', iter, sqrt(p2/ay)
cg%itno=iter
IF ((sqrt(p2/ay)).LT.epsilon_err) GO TO 60
iter = iter + 1
IF (iter.GT.maxit) GO TO 60
GO TO 30
60 CONTINUE
cx(1:n) = cxh(1:n)
! deallocate(cap, cp, cr, cxh, STAT=dealloc_error)
! IF (dealloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)') 'Deallcation Error Detected in conjugate gradient smcg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' smcg '
! END IF
RETURN
END SUBROUTINE smcg90ver2
SUBROUTINE srcg90ver2(cx,cy,n,cxsc,mxcxsc,matvec, cg)
USE ddprecision, ONLY : wp
use cgmodule
implicit none
type (cgstruct) cg
! Purpose: SRCG --- search directions scaled at each iteration
! and the residuals are minimized
! History: 1988 (TKS); original version
! 92/06/09 (PJF); re-written using "BLAS"-type style
! 92/09/11 (TLS); Removed unnecessary zeroing.
! .. Parameters ..
! .. Scalar Arguments ..
REAL (wp) ::epsilon_err
INTEGER :: iter, maxit, n, alloc_error, dealloc_error,ioerr
! .. Array Arguments ..
COMPLEX (wp) :: cx(n), cy(n)
integer mxcxsc
complex(wp),target:: cxsc(n,3)
! .. Local Scalars ..
REAL (wp) :: ak, ay, ek, sk
! .. Local Arrays ..
COMPLEX (wp), pointer :: cp(:), cprod(:), cr(:)
! .. External Functions ..
! .. External Subroutines ..
EXTERNAL matvec, cmatvec
! .. Intrinsic Functions ..
INTRINSIC sqrt
maxit=cg%maxit
epsilon_err=cg%epsilon_err
ioerr=cg%ioerr
if(n*3 .gt. mxcxsc) stop 'stop in sarkar routine srcg90ver2 n*3> mxcxsc not enough memory'
cp => cxsc(:,1)
cprod => cxsc(:,2)
cr => cxsc(:,3)
! allocate(cp(n), cprod(n), cr(n),STAT=alloc_error)
! IF (alloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)') 'Allocation Error Detected in conjugate gradient srcg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' srcg '
! END IF
iter = 0
ay=dot_product(cy(1:n),cy(1:n))
! CALL prod(n,'u',cx,'u',cprod)
call matvec(cx,cprod,n)
cr(1:n) = cy(1:n) - cprod(1:n)
! CALL prod(n,'c',cr,'u',cprod)
call cmatvec(cr,cprod,n)
!
sk=dot_product(cprod(1:n),cprod(1:n))
cp(1:n) = cprod(1:n)/sk
30 CONTINUE
! CALL prod(n,'u',cp,'u',cprod)
call matvec(cp,cprod,n)
ak=dot_product(cprod(1:n),cprod(1:n))
ak = 1._wp/ak
cx(1:n)=cx(1:n)+ak*cp(1:n)
cr(1:n)=cr(1:n)-ak*cprod(1:n)
ek=dot_product(cr(1:n),cr(1:n))
if(cg%print.eq.'print') WRITE (*,fmt=*) 'sqrt(ek/ay)= ', iter, sqrt(ek/ay)
cg%itno=iter
IF ((sqrt(ek/ay)).LT.epsilon_err) GO TO 40
! CALL prod(n,'c',cr,'u',cprod)
call cmatvec(cr,cprod,n)
!
sk=dot_product(cprod(1:n),cprod(1:n))
cp(1:n)=cp(1:n)+(1._wp/sk)*cprod(1:n)
iter = iter + 1
IF (iter.GT.maxit) GO TO 40
GO TO 30
40 CONTINUE
! deallocate(cp, cprod, cr, STAT=dealloc_error)
! IF (dealloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)') 'Deallcation Error Detected in conjugate gradient srcg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' srcg '
! END IF
RETURN
END SUBROUTINE srcg90ver2
SUBROUTINE xcg90ver2(cx,cy,n,cxsc,mxcxsc,matvec, cmatvec, cg)
USE ddprecision, ONLY : wp
use cgmodule
implicit none
type (cgstruct) cg
! Purpose: XCG --- the error between the true solution and the
! approximate solution is minimized at each iteration
! History: 1988 (TKS); original version
! 92/06/09 (PJF); re-written using "BLAS"-type style
! 92/09/11 (TLS); Removed unnecessary zeroing.
! Warning there are differences in results (very small) when the code is run in double precision
! two times. First time we use section 1, which is "fortran 77" construct with do loops. Second time I run
! section 2 which is "fortran 90" type construct. I do not know what is the problem. This problems is not
! occuring if the code is run in single precision. One would think that there should not be any difference.
! PJF
! .. Parameters ..
! .. Scalar Arguments ..
REAL (wp) ::epsilon_err
INTEGER :: iter, maxit, n, alloc_error, dealloc_error,ioerr
! .. Array Arguments ..
COMPLEX (wp) :: cx(n), cy(n)
! .. Local Scalars ..
REAL (wp) :: ak, ay, qk, sk, sk2
integer mxcxsc
complex(wp),target:: cxsc(n,3)
! .. Local Arrays ..
COMPLEX (wp), pointer :: cp(:), cprod(:), cr(:)
! .. External Functions ..
! .. External Subroutines ..
EXTERNAL matvec, cmatvec
! .. Intrinsic Functions ..
INTRINSIC sqrt
maxit=cg%maxit
epsilon_err=cg%epsilon_err
ioerr=cg%ioerr
if(n*3 .gt. mxcxsc) stop 'stop in sarkar routine xcg90ver2 n*3> mxcxsc not enough memory'
cp => cxsc(:,1)
cprod => cxsc(:,2)
cr => cxsc(:,3)
! allocate(cp(n), cprod(n), cr(n),STAT=alloc_error)
! IF (alloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)') 'Allocation Error Detected in conjugate gradient xcg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' xcg '
! END IF
iter = 0
ay=dot_product(cy(1:n),cy(1:n))
! CALL prod(n,'u',cx,'u',cprod)
call matvec(cx,cprod,n)
cr(1:n) = cy(1:n) - cprod(1:n)
sk=dot_product(cr(1:n),cr(1:n))
! CALL prod(n,'c',cr,'u',cp)
call cmatvec(cr,cp,n)
!
20 CONTINUE
! CALL prod(n,'u',cp,'u',cprod)
call matvec(cp,cprod,n)
ak=dot_product(cp(1:n),cp(1:n))
ak = sk/ak
cx(1:n)=cx(1:n)+ak*cp(1:n)
cr(1:n)=cr(1:n)-ak*cprod(1:n)
sk2=dot_product(cr(1:n),cr(1:n))
if(cg%print.eq.'print') WRITE (*,fmt=*) 'sqrt(sk2/ay)= ', iter, sqrt(sk2/ay)
cg%itno=iter
IF ((sqrt(sk2/ay)).LT.epsilon_err) GO TO 40
! CALL prod(n,'c',cr,'u',cprod)
call cmatvec(cr,cprod,n)
qk = sk2/sk
cp(1:n) = cprod(1:n) + qk*cp(1:n)
iter = iter + 1
sk = sk2
IF (iter.GT.maxit) GO TO 40
GO TO 20
40 CONTINUE
! deallocate(cp, cprod, cr, STAT=dealloc_error)
! IF (dealloc_error/=0) THEN
! WRITE (ioerr,fmt='(a)') 'Deallcation Error Detected in conjugate gradient xcg'
! WRITE (ioerr,fmt='(''Aborting'')')
! stop ' xcg '
! END IF
RETURN
END SUBROUTINE xcg90ver2