! { dg-do compile } ! { dg-require-effective-target vect_double } ! { dg-options "-O3 --param vect-max-peeling-for-alignment=0 -fpredictive-commoning -fdump-tree-pcom-details -std=legacy" } ! { dg-additional-options "-mprefer-avx128" { target { i?86-*-* x86_64-*-* } } } ! { dg-additional-options "-mzarch" { target { s390*-*-* } } } ******* RESID COMPUTES THE RESIDUAL: R = V - AU * * THIS SIMPLE IMPLEMENTATION COSTS 27A + 4M PER RESULT, WHERE * A AND M DENOTE THE COSTS OF ADDITION (OR SUBTRACTION) AND * MULTIPLICATION, RESPECTIVELY. BY USING SEVERAL TWO-DIMENSIONAL * BUFFERS ONE CAN REDUCE THIS COST TO 13A + 4M IN THE GENERAL * CASE, OR 10A + 3M WHEN THE COEFFICIENT A(1) IS ZERO. * SUBROUTINE RESID(U,V,R,N,A) INTEGER N REAL*8 U(N,N,N),V(N,N,N),R(N,N,N),A(0:3) INTEGER I3, I2, I1 C DO 600 I3=2,N-1 DO 600 I2=2,N-1 DO 600 I1=2,N-1 600 R(I1,I2,I3)=V(I1,I2,I3) > -A(0)*( U(I1, I2, I3 ) ) > -A(1)*( U(I1-1,I2, I3 ) + U(I1+1,I2, I3 ) > + U(I1, I2-1,I3 ) + U(I1, I2+1,I3 ) > + U(I1, I2, I3-1) + U(I1, I2, I3+1) ) > -A(2)*( U(I1-1,I2-1,I3 ) + U(I1+1,I2-1,I3 ) > + U(I1-1,I2+1,I3 ) + U(I1+1,I2+1,I3 ) > + U(I1, I2-1,I3-1) + U(I1, I2+1,I3-1) > + U(I1, I2-1,I3+1) + U(I1, I2+1,I3+1) > + U(I1-1,I2, I3-1) + U(I1-1,I2, I3+1) > + U(I1+1,I2, I3-1) + U(I1+1,I2, I3+1) ) > -A(3)*( U(I1-1,I2-1,I3-1) + U(I1+1,I2-1,I3-1) > + U(I1-1,I2+1,I3-1) + U(I1+1,I2+1,I3-1) > + U(I1-1,I2-1,I3+1) + U(I1+1,I2-1,I3+1) > + U(I1-1,I2+1,I3+1) + U(I1+1,I2+1,I3+1) ) C RETURN END ! we want to check that predictive commoning did something on the ! vectorized loop. If vector factor is 2, the vectorized loop can ! be predictive commoned, we check if predictive commoning PHI node ! is created with vector(2) type. ! { dg-final { scan-tree-dump "Executing predictive commoning without unrolling" "pcom" { xfail vect_variable_length } } } ! { dg-final { scan-tree-dump "vectp_u.*__lsm.* = PHI <.*vectp_u.*__lsm" "pcom" { xfail vect_variable_length } } }