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Diffstat (limited to 'gcc/testsuite/g77.f-torture/compile/980310-3.f')
| -rw-r--r-- | gcc/testsuite/g77.f-torture/compile/980310-3.f | 259 |
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diff --git a/gcc/testsuite/g77.f-torture/compile/980310-3.f b/gcc/testsuite/g77.f-torture/compile/980310-3.f deleted file mode 100644 index ddfb4c4bb9f..00000000000 --- a/gcc/testsuite/g77.f-torture/compile/980310-3.f +++ /dev/null @@ -1,259 +0,0 @@ -c -c This demonstrates a problem with g77 and pic on x86 where -c egcs 1.0.1 and earlier will generate bogus assembler output. -c unfortunately, gas accepts the bogus acssembler output and -c generates code that almost works. -c - - -C Date: Wed, 17 Dec 1997 23:20:29 +0000 -C From: Joao Cardoso <jcardoso@inescn.pt> -C To: egcs-bugs@cygnus.com -C Subject: egcs-1.0 f77 bug on OSR5 -C When trying to compile the Fortran file that I enclose bellow, -C I got an assembler error: -C -C ./g77 -B./ -fpic -O -c scaleg.f -C /usr/tmp/cca002D8.s:123:syntax error at ( -C -C ./g77 -B./ -fpic -O0 -c scaleg.f -C /usr/tmp/cca002EW.s:246:invalid operand combination: leal -C -C Compiling without the -fpic flag runs OK. - - subroutine scaleg (n,ma,a,mb,b,low,igh,cscale,cperm,wk) -c -c *****parameters: - integer igh,low,ma,mb,n - double precision a(ma,n),b(mb,n),cperm(n),cscale(n),wk(n,6) -c -c *****local variables: - integer i,ir,it,j,jc,kount,nr,nrp2 - double precision alpha,basl,beta,cmax,coef,coef2,coef5,cor, - * ew,ewc,fi,fj,gamma,pgamma,sum,t,ta,tb,tc -c -c *****fortran functions: - double precision dabs, dlog10, dsign -c float -c -c *****subroutines called: -c none -c -c --------------------------------------------------------------- -c -c *****purpose: -c scales the matrices a and b in the generalized eigenvalue -c problem a*x = (lambda)*b*x such that the magnitudes of the -c elements of the submatrices of a and b (as specified by low -c and igh) are close to unity in the least squares sense. -c ref.: ward, r. c., balancing the generalized eigenvalue -c problem, siam j. sci. stat. comput., vol. 2, no. 2, june 1981, -c 141-152. -c -c *****parameter description: -c -c on input: -c -c ma,mb integer -c row dimensions of the arrays containing matrices -c a and b respectively, as declared in the main calling -c program dimension statement; -c -c n integer -c order of the matrices a and b; -c -c a real(ma,n) -c contains the a matrix of the generalized eigenproblem -c defined above; -c -c b real(mb,n) -c contains the b matrix of the generalized eigenproblem -c defined above; -c -c low integer -c specifies the beginning -1 for the rows and -c columns of a and b to be scaled; -c -c igh integer -c specifies the ending -1 for the rows and columns -c of a and b to be scaled; -c -c cperm real(n) -c work array. only locations low through igh are -c referenced and altered by this subroutine; -c -c wk real(n,6) -c work array that must contain at least 6*n locations. -c only locations low through igh, n+low through n+igh, -c ..., 5*n+low through 5*n+igh are referenced and -c altered by this subroutine. -c -c on output: -c -c a,b contain the scaled a and b matrices; -c -c cscale real(n) -c contains in its low through igh locations the integer -c exponents of 2 used for the column scaling factors. -c the other locations are not referenced; -c -c wk contains in its low through igh locations the integer -c exponents of 2 used for the row scaling factors. -c -c *****algorithm notes: -c none. -c -c *****history: -c written by r. c. ward....... -c modified 8/86 by bobby bodenheimer so that if -c sum = 0 (corresponding to the case where the matrix -c doesn't need to be scaled) the routine returns. -c -c --------------------------------------------------------------- -c - if (low .eq. igh) go to 410 - do 210 i = low,igh - wk(i,1) = 0.0d0 - wk(i,2) = 0.0d0 - wk(i,3) = 0.0d0 - wk(i,4) = 0.0d0 - wk(i,5) = 0.0d0 - wk(i,6) = 0.0d0 - cscale(i) = 0.0d0 - cperm(i) = 0.0d0 - 210 continue -c -c compute right side vector in resulting linear equations -c - basl = dlog10(2.0d0) - do 240 i = low,igh - do 240 j = low,igh - tb = b(i,j) - ta = a(i,j) - if (ta .eq. 0.0d0) go to 220 - ta = dlog10(dabs(ta)) / basl - 220 continue - if (tb .eq. 0.0d0) go to 230 - tb = dlog10(dabs(tb)) / basl - 230 continue - wk(i,5) = wk(i,5) - ta - tb - wk(j,6) = wk(j,6) - ta - tb - 240 continue - nr = igh-low+1 - coef = 1.0d0/float(2*nr) - coef2 = coef*coef - coef5 = 0.5d0*coef2 - nrp2 = nr+2 - beta = 0.0d0 - it = 1 -c -c start generalized conjugate gradient iteration -c - 250 continue - ew = 0.0d0 - ewc = 0.0d0 - gamma = 0.0d0 - do 260 i = low,igh - gamma = gamma + wk(i,5)*wk(i,5) + wk(i,6)*wk(i,6) - ew = ew + wk(i,5) - ewc = ewc + wk(i,6) - 260 continue - gamma = coef*gamma - coef2*(ew**2 + ewc**2) - + - coef5*(ew - ewc)**2 - if (it .ne. 1) beta = gamma / pgamma - t = coef5*(ewc - 3.0d0*ew) - tc = coef5*(ew - 3.0d0*ewc) - do 270 i = low,igh - wk(i,2) = beta*wk(i,2) + coef*wk(i,5) + t - cperm(i) = beta*cperm(i) + coef*wk(i,6) + tc - 270 continue -c -c apply matrix to vector -c - do 300 i = low,igh - kount = 0 - sum = 0.0d0 - do 290 j = low,igh - if (a(i,j) .eq. 0.0d0) go to 280 - kount = kount+1 - sum = sum + cperm(j) - 280 continue - if (b(i,j) .eq. 0.0d0) go to 290 - kount = kount+1 - sum = sum + cperm(j) - 290 continue - wk(i,3) = float(kount)*wk(i,2) + sum - 300 continue - do 330 j = low,igh - kount = 0 - sum = 0.0d0 - do 320 i = low,igh - if (a(i,j) .eq. 0.0d0) go to 310 - kount = kount+1 - sum = sum + wk(i,2) - 310 continue - if (b(i,j) .eq. 0.0d0) go to 320 - kount = kount+1 - sum = sum + wk(i,2) - 320 continue - wk(j,4) = float(kount)*cperm(j) + sum - 330 continue - sum = 0.0d0 - do 340 i = low,igh - sum = sum + wk(i,2)*wk(i,3) + cperm(i)*wk(i,4) - 340 continue - if(sum.eq.0.0d0) return - alpha = gamma / sum -c -c determine correction to current iterate -c - cmax = 0.0d0 - do 350 i = low,igh - cor = alpha * wk(i,2) - if (dabs(cor) .gt. cmax) cmax = dabs(cor) - wk(i,1) = wk(i,1) + cor - cor = alpha * cperm(i) - if (dabs(cor) .gt. cmax) cmax = dabs(cor) - cscale(i) = cscale(i) + cor - 350 continue - if (cmax .lt. 0.5d0) go to 370 - do 360 i = low,igh - wk(i,5) = wk(i,5) - alpha*wk(i,3) - wk(i,6) = wk(i,6) - alpha*wk(i,4) - 360 continue - pgamma = gamma - it = it+1 - if (it .le. nrp2) go to 250 -c -c end generalized conjugate gradient iteration -c - 370 continue - do 380 i = low,igh - ir = wk(i,1) + dsign(0.5d0,wk(i,1)) - wk(i,1) = ir - jc = cscale(i) + dsign(0.5d0,cscale(i)) - cscale(i) = jc - 380 continue -c -c scale a and b -c - do 400 i = 1,igh - ir = wk(i,1) - fi = 2.0d0**ir - if (i .lt. low) fi = 1.0d0 - do 400 j =low,n - jc = cscale(j) - fj = 2.0d0**jc - if (j .le. igh) go to 390 - if (i .lt. low) go to 400 - fj = 1.0d0 - 390 continue - a(i,j) = a(i,j)*fi*fj - b(i,j) = b(i,j)*fi*fj - 400 continue - 410 continue - return -c -c last line of scaleg -c - end |