gcc/libgomp/testsuite/libgomp.c/scan-20.c
Jakub Jelinek fab2f61dc1 vectorizer: Fix up -fsimd-cost-model= handling
>	* testsuite/libgomp.c++/scan-10.C: Add option -fvect-cost-model=cheap.

I don't think this is the right thing to do.
This just means that at some point between 2013 when -fsimd-cost-model has
been introduced and now -fsimd-cost-model= option at least partially stopped
working properly.
As documented, -fsimd-cost-model= overrides the -fvect-cost-model= setting
for OpenMP simd loops (loop->force_vectorize is true) if specified differently
from default.
In tree-vectorizer.h we have:
static inline bool
unlimited_cost_model (loop_p loop)
{
  if (loop != NULL && loop->force_vectorize
      && flag_simd_cost_model != VECT_COST_MODEL_DEFAULT)
    return flag_simd_cost_model == VECT_COST_MODEL_UNLIMITED;
  return (flag_vect_cost_model == VECT_COST_MODEL_UNLIMITED);
}
and use it in various places, but we also just use flag_vect_cost_model
in lots of places (and in one spot use flag_simd_cost_model, not sure if
we are sure it is a force_vectorize loop or what).

So, IMHO we should change the above inline function to
loop_cost_model and let it return the cost model and then just
reimplement unlimited_cost_model as
return loop_cost_model (loop) == VECT_COST_MODEL_UNLIMITED;
and then adjust the direct uses of the flag and revert these changes.

2021-10-12  Jakub Jelinek  <jakub@redhat.com>

gcc/
	* tree-vectorizer.h (loop_cost_model): New function.
	(unlimited_cost_model): Use it.
	* tree-vect-loop.c (vect_analyze_loop_costing): Use loop_cost_model
	call instead of flag_vect_cost_model.
	* tree-vect-data-refs.c (vect_enhance_data_refs_alignment): Likewise.
	(vect_prune_runtime_alias_test_list): Likewise.  Also use it instead
	of flag_simd_cost_model.
gcc/testsuite/
	* gcc.dg/gomp/simd-2.c: Remove option -fvect-cost-model=cheap.
	* gcc.dg/gomp/simd-3.c: Likewise.
libgomp/
	* testsuite/libgomp.c/scan-11.c: Remove option -fvect-cost-model=cheap.
	* testsuite/libgomp.c/scan-12.c: Likewise.
	* testsuite/libgomp.c/scan-13.c: Likewise.
	* testsuite/libgomp.c/scan-14.c: Likewise.
	* testsuite/libgomp.c/scan-15.c: Likewise.
	* testsuite/libgomp.c/scan-16.c: Likewise.
	* testsuite/libgomp.c/scan-17.c: Likewise.
	* testsuite/libgomp.c/scan-18.c: Likewise.
	* testsuite/libgomp.c/scan-19.c: Likewise.
	* testsuite/libgomp.c/scan-20.c: Likewise.
	* testsuite/libgomp.c/scan-21.c: Likewise.
	* testsuite/libgomp.c/scan-22.c: Likewise.
	* testsuite/libgomp.c++/scan-9.C: Likewise.
	* testsuite/libgomp.c++/scan-10.C: Likewise.
	* testsuite/libgomp.c++/scan-11.C: Likewise.
	* testsuite/libgomp.c++/scan-12.C: Likewise.
	* testsuite/libgomp.c++/scan-13.C: Likewise.
	* testsuite/libgomp.c++/scan-14.C: Likewise.
	* testsuite/libgomp.c++/scan-15.C: Likewise.
	* testsuite/libgomp.c++/scan-16.C: Likewise.
2021-10-12 09:28:10 +02:00

121 lines
2.6 KiB
C

/* { dg-require-effective-target size32plus } */
/* { dg-additional-options "-O2 -fopenmp -fdump-tree-vect-details" } */
/* { dg-additional-options "-msse2" { target sse2_runtime } } */
/* { dg-additional-options "-mavx" { target avx_runtime } } */
/* { dg-final { scan-tree-dump-times "vectorized \[2-6] loops" 2 "vect" { target sse2_runtime } } } */
extern void abort (void);
int r, a[1024], b[1024], x, y, z;
__attribute__((noipa)) void
foo (int *a, int *b)
{
#pragma omp for simd reduction (inscan, +:r) lastprivate (conditional: z) firstprivate (x) private (y) simdlen(1)
for (int i = 0; i < 1024; i++)
{
{ b[i] = r; if ((i & 1) == 0 && i < 937) z = r; }
#pragma omp scan exclusive(r)
{ y = a[i]; r += y + x + 12; }
}
}
__attribute__((noipa)) int
bar (void)
{
int s = 0;
#pragma omp parallel
#pragma omp for simd reduction (inscan, +:s) firstprivate (x) private (y) lastprivate (z) if (0)
for (int i = 0; i < 1024; i++)
{
{ y = s; b[i] = y + x + 12; }
#pragma omp scan exclusive(s)
{ y = 2 * a[i]; s += y; z = y; }
}
return s;
}
__attribute__((noipa)) void
baz (int *a, int *b)
{
#pragma omp parallel for simd reduction (inscan, +:r) firstprivate (x) lastprivate (x)
for (int i = 0; i < 1024; i++)
{
b[i] = r;
#pragma omp scan exclusive(r)
{ r += a[i]; if (i == 1023) x = 29; }
}
}
__attribute__((noipa)) int
qux (void)
{
int s = 0;
#pragma omp parallel for simd reduction (inscan, +:s) lastprivate (conditional: x, y)
for (int i = 0; i < 1024; i++)
{
{ b[i] = s; if ((a[i] & 1) == 0 && i < 829) y = a[i]; }
#pragma omp scan exclusive(s)
{ s += 2 * a[i]; if ((a[i] & 1) == 1 && i < 825) x = a[i]; }
}
return s;
}
int
main ()
{
int s = 0;
x = -12;
for (int i = 0; i < 1024; ++i)
{
a[i] = i;
b[i] = -1;
asm ("" : "+g" (i));
}
#pragma omp parallel
foo (a, b);
if (r != 1024 * 1023 / 2 || x != -12 || z != b[936])
abort ();
for (int i = 0; i < 1024; ++i)
{
if (b[i] != s)
abort ();
else
b[i] = 25;
s += i;
}
if (bar () != 1024 * 1023 || x != -12 || z != 2 * 1023)
abort ();
s = 0;
for (int i = 0; i < 1024; ++i)
{
if (b[i] != s)
abort ();
else
b[i] = -1;
s += 2 * i;
}
r = 0;
baz (a, b);
if (r != 1024 * 1023 / 2 || x != 29)
abort ();
s = 0;
for (int i = 0; i < 1024; ++i)
{
if (b[i] != s)
abort ();
else
b[i] = -25;
s += i;
}
if (qux () != 1024 * 1023 || x != 823 || y != 828)
abort ();
s = 0;
for (int i = 0; i < 1024; ++i)
{
if (b[i] != s)
abort ();
s += 2 * i;
}
return 0;
}