subroutine vconvx(n,a,b,c,d)
      dimension a(n,n),b(n),c(n),d(*)
c there are four loops that i use to test some of the more interesting
c aspects of a vectorizing compiler
c
c loop 1 
c
c setting a matrix to its identity element  (from sandia lab benchmark)
c
      do 20, i = 1,n
         do 10, j = 1,n
            a(i,j) = 0
   10    continue
         a(i,i) = 1
   20 continue
c
c the best results are:
c 1)loop distribution, vectorizing the inner and outer loops
c 2)loop interchange on the innermost loop
c
c
c loop 2
c
c scalar expansion (forward assignment substitution) and using the last element
c calculated outside the loop  (without directives). many dusty decks.
c
      do 30, i = 1,n
         x = c(i) + b(i)
         c(i) = c(i) +.5
         b(i) = x-.5
   30 continue
      print *, x
c the best results vectorize without directives or modifying the code by
c replacing x with x(i)  for all 3 occurrneces of x
c
c loop 3
c
c this example test partial vectorization
c for the creation of vector of indices.
c this example came from the VAST manual on constructs that DO NOT vectorize.
c
      j =1
      do 40, i= 1,n
         j = j*2
         d(j) = 1
   40 continue
c
c the best results are partial vectorization with the net effect being the 
c loops being compiled as
c
c temp(1)=1
c do i= 2,n
c temp(i) = temp(i-1)*2 (actually temp(i-1)+temp(i-1))
c enddo
c 
c do i= 1,n
c d(temp(i)) =1
c enddo
c
c loop 4
c
c tests scalar expansion.  came from a benchmark to test the scalar speed of
c the machine.  since no vectors were defined
c
      q = 1.
      do 50, i = 1,n
         q = .995*q
   50 continue
c
c the best results are fully vectorized. the compiler expands .995 into a
c vector of .995 and does a product reduction on the vector of .995
c this one fooled everybody.  vectorization without vectors.
      return
      end

.