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C
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C Parallel Sparse BLAS version 2.2
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C (C) Copyright 2006/2007/2008
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C Salvatore Filippone University of Rome Tor Vergata
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C Alfredo Buttari University of Rome Tor Vergata
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C
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C Redistribution and use in source and binary forms, with or without
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C modification, are permitted provided that the following conditions
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C are met:
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C 1. Redistributions of source code must retain the above copyright
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C notice, this list of conditions and the following disclaimer.
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C 2. Redistributions in binary form must reproduce the above copyright
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C notice, this list of conditions, and the following disclaimer in the
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C documentation and/or other materials provided with the distribution.
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C 3. The name of the PSBLAS group or the names of its contributors may
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C not be used to endorse or promote products derived from this
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C software without specific written permission.
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C
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C THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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C ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
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C TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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C PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE PSBLAS GROUP OR ITS CONTRIBUTORS
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C BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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C CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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C SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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C INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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C CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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C ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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C POSSIBILITY OF SUCH DAMAGE.
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C
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C
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***********************************************************************
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* DSRMV modified for SPARKER
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* *
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* FUNCTION: Driver for routines performing one of the sparse *
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* matrix vector operations *
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* *
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* y = alpha*op(A)*x + beta*y *
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* *
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* where op(A) is one of: *
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* *
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* op(A) = A or op(A) = A' or *
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* op(A) = lower or upper part of A *
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* *
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* alpha and beta are scalars. *
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* The data structure of the matrix is related *
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* to the scalar computer. *
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* This is an internal routine called by: *
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* DSMMV *
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* *
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* ENTRY-POINT = DSRMV *
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* INPUT = *
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* *
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* *
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* SYMBOLIC NAME: TRANS *
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* POSITION: PARAMETER NO 1. *
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* ATTRIBUTES: CHARACTER*1 *
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* VALUES: 'N' 'T' 'L' 'U' *
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* DESCRIPTION: Specifies the form of op(A) to be used in the *
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* matrix vector multiplications as follows: *
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* *
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* TRANS = 'N' , op( A ) = A. *
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* *
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* TRANS = 'T' , op( A ) = A'. *
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* *
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* TRANS = 'L' or 'U', op( A ) = lower or *
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* upper part of A *
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* *
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* SYMBOLIC NAME: DIAG *
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* POSITION: PARAMETER NO 2. *
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* ATTRIBUTES: CHARACTER*1 *
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* VALUES: 'N' 'U' *
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* DESCRIPTION: *
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* Specifies whether or not the matrix A has *
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* unit diagonal as follows: *
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* *
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* DIAG = 'N' A is not assumed *
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* to have unit diagonal *
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* *
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* DIAG = 'U' A is assumed *
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* to have unit diagonal. *
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* *
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* WARNING: it is the caller's responsibility *
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* to ensure that if the matrix has unit *
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* diagonal, there are no elements of the *
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* diagonal are stored in the arrays AS and JA. *
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* *
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* SYMBOLIC NAME: M *
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* POSITION: PARAMETER NO 3. *
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* ATTRIBUTES: INTEGER*4. *
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* VALUES: M >= 0 *
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* DESCRIPTION: Number of rows of the matrix op(A). *
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* *
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* SYMBOLIC NAME: N *
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* POSITION: PARAMETER NO 4. *
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* ATTRIBUTES: INTEGER*4. *
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* VALUES: N >= 0 *
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* DESCRIPTION: Number of columns of the matrix op(A) *
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* *
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* SYMBOLIC NAME: ALPHA *
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* POSITION: PARAMETER NO 5. *
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* ATTRIBUTES: REAL*8. *
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* VALUES: any. *
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* DESCRIPTION: Specifies the scalar alpha. *
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* *
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* *
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* SYMBOLIC NAME: AS *
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* POSITION: PARAMETER NO 6. *
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* ATTRIBUTES: REAL*8: ARRAY(IA(M+1)-1) *
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* VALUES: ANY *
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* DESCRIPTION: Array containing the non zero coefficients of *
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* the sparse matrix op(A). *
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* *
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* SYMBOLIC NAME: JA *
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* POSITION: PARAMETER NO 7. *
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* ATTRIBUTES: INTEGER*4: ARRAY(IA(M+1)-1) *
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* VALUES: 0 < JA(I) <= M *
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* DESCRIPTION: Array containing the column number of the *
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* nonzero coefficients stored in array AS. *
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* *
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* SYMBOLIC NAME: IA *
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* POSITION: PARAMETER NO 8. *
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* ATTRIBUTES: INTEGER*4: ARRAY(*) *
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* VALUES: IA(I) > 0 *
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* DESCRIPTION: Contains the pointers for the beginning of *
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* each rows. *
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* *
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* *
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* SYMBOLIC NAME: X *
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* POSITION: PARAMETER NO 9. *
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* ATTRIBUTES: REAL*8 ARRAY(N) (or ARRAY(M) when op(A) = A') *
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* VALUES: any. *
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* DESCRIPTION: Contains the values of the vector to be *
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* multiplied by the matrix A. *
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* *
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* SYMBOLIC NAME: BETA *
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* POSITION: PARAMETER NO 10. *
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* ATTRIBUTES: REAL*8. *
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* VALUES: any. *
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* DESCRIPTION: Specifies the scalar beta. *
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* *
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* SYMBOLIC NAME: Y *
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* POSITION: PARAMETER NO 11. *
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* ATTRIBUTES: REAL*8 ARRAY(M) (or ARRAY(N) when op(A) = A') *
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* VALUES: any. *
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* DESCRIPTION: Contains the values of the vector to be *
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* updated by the matrix-vector multiplication. *
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* *
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* SYMBOLIC NAME: WORK *
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* POSITION: PARAMETER NO 12. *
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* ATTRIBUTES: REAL*8 ARRAY(M) (or ARRAY(N) when op(A) = A') *
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* VALUES: any. *
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* DESCRIPTION: Work area available to the program. It is used *
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* only when TRANS = 'T'. *
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* *
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* OUTPUT = *
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* *
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* *
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* SYMBOLIC NAME: Y *
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* POSITION: PARAMETER NO 11. *
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* ATTRIBUTES: REAL*8 ARRAY(M) (or ARRAY(N) when op(A) = A') *
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* VALUES: any. *
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* DESCRIPTION: Contains the values of the vector *
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* updated by the matrix-vector multiplication. *
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* *
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* *
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***********************************************************************
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SUBROUTINE DCSRMV4(TRANS,DIAG,M,N,ALPHA,AS,JA,IA,X,LDX,
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+ BETA,Y,LDY, WORK,LWORK,IERROR)
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use psb_const_mod
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use psb_string_mod
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integer nb
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parameter (nb=4)
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C .. Parameters ..
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real(psb_dpk_) ONE, ZERO
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PARAMETER (ONE=1.0D0,ZERO=0.0D0)
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C .. Scalar Arguments ..
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real(psb_dpk_) ALPHA, BETA
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INTEGER M, N,LWORK,IERROR,ldx,ldy
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CHARACTER DIAG, TRANS
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C .. Array Arguments ..
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real(psb_dpk_) AS(*), WORK(*), X(LDX,NB), Y(LDY,NB)
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INTEGER IA(*), JA(*)
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C .. Local Scalars ..
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real(psb_dpk_) ACC(nb)
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INTEGER I, J, K, NCOLA, NROWA
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LOGICAL SYM, TRA, UNI
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C .. Executable Statements ..
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C
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IERROR = 0
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UNI = (psb_toupper(DIAG).EQ.'U')
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TRA = (psb_toupper(TRANS).EQ.'T')
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C Symmetric matrix upper or lower
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SYM = ((psb_toupper(TRANS).EQ.'L').OR.
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+ (psb_toupper(TRANS).EQ.'U'))
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C
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if ( .not. tra) then
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nrowa = m
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ncola = n
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else if (tra) then
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nrowa = n
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ncola = m
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end if !(....tra)
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if (alpha.eq.zero) then
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if (beta.eq.zero) then
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do i = 1, m
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y(i,1:nb) = zero
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enddo
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else
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do 20 i = 1, m
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y(i,1:nb) = beta*y(i,1:nb)
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20 continue
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endif
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return
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end if
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c
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if (sym) then
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if (uni) then
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c
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c ......Symmetric with unitary diagonal.......
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C ....OK!!
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C To be optimized
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if (beta.ne.zero) then
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do i = 1, m
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C
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C Product for diagonal elements
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c
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y(i,1:nb) = beta*y(i,1:nb) + alpha*x(i,1:nb)
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enddo
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else
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do i = 1, m
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y(i,1:nb) = alpha*x(i,1:nb)
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enddo
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endif
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C Product for other elements
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do 80 i = 1, m
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acc = zero
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do 60 j = ia(i), ia(i+1) - 1
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k = ja(j)
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y(k,1:nb) = y(k,1:nb) + alpha*as(j)*x(i,1:nb)
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acc(1:nb) = acc(1:nb) + as(j)*x(k,1:nb)
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60 continue
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y(i,1:nb) = y(i,1:nb) + alpha*acc(1:nb)
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80 continue
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C
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else if ( .not. uni) then
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C
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C Check if matrix is lower or upper
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C
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if (trans.eq.'L') then
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C
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C LOWER CASE: diagonal element is the last element of row
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C ....OK!
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if (beta.ne.zero) then
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do 100 i = 1, m
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y(i,1:nb) = beta*y(i,1:nb)
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100 continue
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else
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do i = 1, m
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y(i,1:nb) = zero
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enddo
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endif
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do 140 i = 1, m
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acc = zero
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do 120 j = ia(i), ia(i+1) - 1 ! it was -2
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K = ja(j)
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C
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C To be optimized
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C
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if (k.ne.i) then !for symmetric element
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y(k,1:nb) = y(k,1:nb) + alpha*as(j)*x(i,1:nb)
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endif
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acc(1:nb) = acc(1:nb) + as(j)*x(k,1:nb)
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120 continue
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y(i,1:nb) = y(i,1:nb) + alpha*acc(1:nb)
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140 continue
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else ! ....Trans<>L
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C
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C UPPER CASE
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C ....OK!!
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C
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if (beta.ne.zero) then
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do 160 i = 1, m
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y(i,1:nb) = beta*y(i,1:nb)
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160 continue
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else
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do i = 1, m
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y(i,1:nb) = zero
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enddo
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endif
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do 200 i = 1, m
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acc = zero
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do 180 j = ia(i) , ia(i+1) - 1 ! removed +1
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k = ja(j)
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C
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C To be optimized
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C
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if (k.ne.i) then
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y(k,1:nb) = y(k,1:nb) + alpha*as(j)*x(i,1:nb)
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endif
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acc(1:nb) = acc(1:nb) + as(j)*x(k,1:nb)
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180 continue
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y(i,1:nb) = y(i,1:nb) + alpha*acc(1:nb)
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200 continue
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end if ! ......TRANS=='L'
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end if ! ......Not UNI
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c
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else if ( .not. tra) then !......NOT SYM
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if ( .not. uni) then
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C
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C .......General Not Unit, No Traspose
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C
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if (beta == zero) then
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if (alpha==one) then
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do i = 1, m
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acc = zero
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do j = ia(i), ia(i+1) - 1
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acc = acc + as(j)*x(ja(j),1:nb)
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enddo
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y(i,1:nb) = acc
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enddo
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else if (alpha==-one) then
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do i = 1, m
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acc = zero
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do j = ia(i), ia(i+1) - 1
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acc = acc - as(j)*x(ja(j),1:nb)
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enddo
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y(i,1:nb) = acc
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enddo
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else
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do i = 1, m
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acc = zero
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do j = ia(i), ia(i+1) - 1
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acc = acc + as(j)*x(ja(j),1:nb)
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enddo
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y(i,1:nb) = alpha*acc
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enddo
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endif
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else if (beta==one) then
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if (alpha==one) then
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do i = 1, m
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acc = y(i,1:nb)
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do j = ia(i), ia(i+1) - 1
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acc = acc + as(j)*x(ja(j),1:nb)
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enddo
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y(i,1:nb) = acc
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enddo
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else if (alpha==-one) then
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do i = 1, m
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acc = y(i,1:nb)
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do j = ia(i), ia(i+1) - 1
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acc = acc - as(j)*x(ja(j),1:nb)
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enddo
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y(i,1:nb) = acc
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enddo
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else
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do i = 1, m
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acc = zero
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do j = ia(i), ia(i+1) - 1
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acc = acc + as(j)*x(ja(j),1:nb)
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enddo
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y(i,1:nb) = alpha*acc + y(i,1:nb)
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enddo
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endif
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else if (beta==-one) then
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if (alpha==one) then
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do i = 1, m
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acc = -y(i,1:nb)
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do j = ia(i), ia(i+1) - 1
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acc = acc + as(j)*x(ja(j),1:nb)
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enddo
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y(i,1:nb) = acc
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enddo
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else if (alpha==-one) then
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do i = 1, m
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acc = -y(i,1:nb)
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do j = ia(i), ia(i+1) - 1
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acc = acc - as(j)*x(ja(j),1:nb)
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enddo
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y(i,1:nb) = acc
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enddo
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else
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do i = 1, m
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acc = zero
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do j = ia(i), ia(i+1) - 1
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acc = acc + as(j)*x(ja(j),1:nb)
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enddo
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y(i,1:nb) = alpha*acc - y(i,1:nb)
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enddo
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endif
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else
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if (alpha==one) then
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do i = 1, m
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acc = zero
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do j = ia(i), ia(i+1) - 1
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acc = acc + as(j)*x(ja(j),1:nb)
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enddo
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y(i,1:nb) = acc + beta*y(i,1:nb)
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enddo
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else if (alpha==-one) then
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do i = 1, m
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acc = zero
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do j = ia(i), ia(i+1) - 1
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acc = acc - as(j)*x(ja(j),1:nb)
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enddo
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y(i,1:nb) = acc + beta*y(i,1:nb)
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enddo
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else
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do i = 1, m
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acc = zero
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do j = ia(i), ia(i+1) - 1
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acc = acc + as(j)*x(ja(j),1:nb)
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enddo
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y(i,1:nb) = alpha*acc + beta*y(i,1:nb)
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enddo
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endif
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end if
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c
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else if (uni) then
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c
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if (beta.ne.zero) then
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do 280 i = 1, m
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acc(1:nb) = zero
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do 260 j = ia(i), ia(i+1) - 1
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acc(1:nb) = acc(1:nb) + as(j)*x(ja(j),1:nb)
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260 continue
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y(i,1:nb) = alpha*(acc(1:nb)+x(i,1:nb)) + beta*y(i,1:nb)
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280 continue
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else !(beta.eq.zero)
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|
do i = 1, m
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|
|
acc(1:nb) = zero
|
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|
|
do j = ia(i), ia(i+1) - 1
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|
|
|
acc(1:nb) = acc(1:nb) + as(j)*x(ja(j),1:nb)
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|
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|
enddo
|
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|
|
y(i,1:nb) = alpha*(acc(1:nb)+x(i,1:nb))
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|
enddo
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|
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|
endif
|
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|
|
end if !....End Testing on UNI
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|
|
C
|
|
|
|
|
else if (tra) then !....Else on SYM (swapped M and N)
|
|
|
|
|
C
|
|
|
|
|
if ( .not. uni) then
|
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|
|
|
c
|
|
|
|
|
if (beta.ne.zero) then
|
|
|
|
|
do 300 i = 1, m
|
|
|
|
|
y(i,1:nb) = beta*y(i,1:nb)
|
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|
|
|
300 continue
|
|
|
|
|
else !(BETA.EQ.ZERO)
|
|
|
|
|
do i = 1, m
|
|
|
|
|
y(i,1:nb) = zero
|
|
|
|
|
enddo
|
|
|
|
|
endif
|
|
|
|
|
c
|
|
|
|
|
else if (uni) then
|
|
|
|
|
c
|
|
|
|
|
|
|
|
|
|
if (beta.ne.zero) then
|
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|
|
|
do 320 i = 1, m
|
|
|
|
|
y(i,1:nb) = beta*y(i,1:nb) + alpha*x(i,1:nb)
|
|
|
|
|
320 continue
|
|
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|
|
else !(BETA.EQ.ZERO)
|
|
|
|
|
do i = 1, m
|
|
|
|
|
y(i,1:nb) = alpha*x(i,1:nb)
|
|
|
|
|
enddo
|
|
|
|
|
endif
|
|
|
|
|
|
|
|
|
|
c
|
|
|
|
|
end if !....UNI
|
|
|
|
|
C
|
|
|
|
|
if (alpha.eq.one) then
|
|
|
|
|
c
|
|
|
|
|
do 360 i = 1, n
|
|
|
|
|
do 340 j = ia(i), ia(i+1) - 1
|
|
|
|
|
k = ja(j)
|
|
|
|
|
y(k,1:nb) = y(k,1:nb) + as(j)*x(i,1:nb)
|
|
|
|
|
340 continue
|
|
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|
|
360 continue
|
|
|
|
|
c
|
|
|
|
|
else if (alpha.eq.-one) then
|
|
|
|
|
c
|
|
|
|
|
do 400 i = 1, n
|
|
|
|
|
do 380 j = ia(i), ia(i+1) - 1
|
|
|
|
|
k = ja(j)
|
|
|
|
|
y(k,1:nb) = y(k,1:nb) - as(j)*x(i,1:nb)
|
|
|
|
|
380 continue
|
|
|
|
|
400 continue
|
|
|
|
|
c
|
|
|
|
|
else !.....Else on TRA
|
|
|
|
|
C
|
|
|
|
|
C This work array is used for efficiency
|
|
|
|
|
C
|
|
|
|
|
if (lwork.lt.n) then
|
|
|
|
|
ierror = 60
|
|
|
|
|
work(1) = dble(n)
|
|
|
|
|
return
|
|
|
|
|
endif
|
|
|
|
|
c$$$ do 420 i = 1, n
|
|
|
|
|
c$$$ work(i) = alpha*x(i,1:4)
|
|
|
|
|
c$$$ 420 continue
|
|
|
|
|
c$$$C
|
|
|
|
|
c$$$ DO 460 I = 1, n
|
|
|
|
|
c$$$ DO 440 J = IA(I), IA(I+1) - 1
|
|
|
|
|
c$$$ K = JA(J)
|
|
|
|
|
c$$$ Y(K) = Y(K) + AS(J)*WORK(I)
|
|
|
|
|
c$$$ 440 CONTINUE
|
|
|
|
|
c$$$ 460 CONTINUE
|
|
|
|
|
c
|
|
|
|
|
end if !.....end testing on alpha
|
|
|
|
|
|
|
|
|
|
end if !.....end testing on sym
|
|
|
|
|
c
|
|
|
|
|
return
|
|
|
|
|
c
|
|
|
|
|
c end of dsrmv
|
|
|
|
|
c
|
|
|
|
|
end
|
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|
