vect: Optimize order of lane-reducing operations in loop def-use cycles

vect: Optimize order of lane-reducing operations in loop def-use cycles

When transforming multiple lane-reducing operations in a loop reduction chain,
originally, corresponding vectorized statements are generated into def-use
cycles starting from 0. The def-use cycle with smaller index, would contain
more statements, which means more instruction dependency. For example:

   int sum = 1;
   for (i)
     {
       sum += d0[i] * d1[i];      // dot-prod <vector(16) char>
       sum += w[i];               // widen-sum <vector(16) char>
       sum += abs(s0[i] - s1[i]); // sad <vector(8) short>
       sum += n[i];               // normal <vector(4) int>
     }

Original transformation result:

   for (i / 16)
     {
       sum_v0 = DOT_PROD (d0_v0[i: 0 ~ 15], d1_v0[i: 0 ~ 15], sum_v0);
       sum_v1 = sum_v1;  // copy
       sum_v2 = sum_v2;  // copy
       sum_v3 = sum_v3;  // copy

       sum_v0 = WIDEN_SUM (w_v0[i: 0 ~ 15], sum_v0);
       sum_v1 = sum_v1;  // copy
       sum_v2 = sum_v2;  // copy
       sum_v3 = sum_v3;  // copy

       sum_v0 = SAD (s0_v0[i: 0 ~ 7 ], s1_v0[i: 0 ~ 7 ], sum_v0);
       sum_v1 = SAD (s0_v1[i: 8 ~ 15], s1_v1[i: 8 ~ 15], sum_v1);
       sum_v2 = sum_v2;  // copy
       sum_v3 = sum_v3;  // copy

       ...
     }

For a higher instruction parallelism in final vectorized loop, an optimal
means is to make those effective vector lane-reducing ops be distributed
evenly among all def-use cycles. Transformed as the below, DOT_PROD,
WIDEN_SUM and SADs are generated into disparate cycles, instruction
dependency among them could be eliminated.

   for (i / 16)
     {
       sum_v0 = DOT_PROD (d0_v0[i: 0 ~ 15], d1_v0[i: 0 ~ 15], sum_v0);
       sum_v1 = sum_v1;  // copy
       sum_v2 = sum_v2;  // copy
       sum_v3 = sum_v3;  // copy

       sum_v0 = sum_v0;  // copy
       sum_v1 = WIDEN_SUM (w_v1[i: 0 ~ 15], sum_v1);
       sum_v2 = sum_v2;  // copy
       sum_v3 = sum_v3;  // copy

       sum_v0 = sum_v0;  // copy
       sum_v1 = sum_v1;  // copy
       sum_v2 = SAD (s0_v2[i: 0 ~ 7 ], s1_v2[i: 0 ~ 7 ], sum_v2);
       sum_v3 = SAD (s0_v3[i: 8 ~ 15], s1_v3[i: 8 ~ 15], sum_v3);

       ...
     }

2024-03-22 Feng Xue <fxue@os.amperecomputing.com>

gcc/
	PR tree-optimization/114440
	* tree-vectorizer.h (struct _stmt_vec_info): Add a new field
	reduc_result_pos.
	* tree-vect-loop.cc (vect_transform_reduction): Generate lane-reducing
	statements in an optimized order.