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 = 0;
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>
}
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 vectorized lane-reducing statements 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 could be eliminated.
Thanks,
Feng
---
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.
---
gcc/tree-vect-loop.cc | 39 +++++++++++++++++++++++++++++++++++----
gcc/tree-vectorizer.h | 6 ++++++
2 files changed, 41 insertions(+), 4 deletions(-)
diff --git a/gcc/tree-vect-loop.cc b/gcc/tree-vect-loop.cc
index 6d91665a341..c7e13d655d8 100644
--- a/gcc/tree-vect-loop.cc
+++ b/gcc/tree-vect-loop.cc
@@ -8828,9 +8828,9 @@ vect_transform_reduction (loop_vec_info loop_vinfo,
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_v0 = sum_v0; // copy
+ sum_v1 = SAD (s0_v1[i: 0 ~ 7 ], s1_v1[i: 0 ~ 7 ], sum_v1);
+ sum_v2 = SAD (s0_v2[i: 8 ~ 15], s1_v2[i: 8 ~ 15], sum_v2);
sum_v3 = sum_v3; // copy
sum_v0 += n_v0[i: 0 ~ 3 ];
@@ -8838,14 +8838,45 @@ vect_transform_reduction (loop_vec_info loop_vinfo,
sum_v2 += n_v2[i: 8 ~ 11];
sum_v3 += n_v3[i: 12 ~ 15];
}
- */
+
+ Moreover, for a higher instruction parallelism in final vectorized
+ loop, it is considered to make those effective vectorized lane-
+ reducing statements be distributed evenly among all def-use cycles.
+ In the above example, SADs are generated into other cycles rather
+ than that of DOT_PROD. */
unsigned using_ncopies = vec_oprnds[0].length ();
unsigned reduc_ncopies = vec_oprnds[reduc_index].length ();
+ unsigned result_pos = reduc_info->reduc_result_pos;
+
+ reduc_info->reduc_result_pos
+ = (result_pos + using_ncopies) % reduc_ncopies;
+ gcc_assert (result_pos < reduc_ncopies);
for (unsigned i = 0; i < op.num_ops - 1; i++)
{
gcc_assert (vec_oprnds[i].length () == using_ncopies);
vec_oprnds[i].safe_grow_cleared (reduc_ncopies);
+
+ /* Find suitable def-use cycles to generate vectorized statements
+ into, and reorder operands based on the selection. */
+ if (result_pos)
+ {
+ unsigned count = reduc_ncopies - using_ncopies;
+ unsigned start = result_pos - count;
+
+ if ((int) start < 0)
+ {
+ count = result_pos;
+ start = 0;
+ }
+
+ for (unsigned j = using_ncopies; j > start; j--)
+ {
+ unsigned k = j - 1;
+ std::swap (vec_oprnds[i][k], vec_oprnds[i][k + count]);
+ gcc_assert (!vec_oprnds[i][k]);
+ }
+ }
}
}
diff --git a/gcc/tree-vectorizer.h b/gcc/tree-vectorizer.h
index 94736736dcc..64c6571a293 100644
--- a/gcc/tree-vectorizer.h
+++ b/gcc/tree-vectorizer.h
@@ -1402,6 +1402,12 @@ public:
/* The vector type for performing the actual reduction. */
tree reduc_vectype;
+ /* For loop reduction with multiple vectorized results (ncopies > 1), a
+ lane-reducing operation participating in it may not use all of those
+ results, this field specifies result index starting from which any
+ following land-reducing operation would be assigned to. */
+ unsigned int reduc_result_pos;
+
/* If IS_REDUC_INFO is true and if the vector code is performing
N scalar reductions in parallel, this variable gives the initial
scalar values of those N reductions. */
--
2.17.1From 1f2e05a6787eb4449a24a9d6e371ae162855aaff Mon Sep 17 00:00:00 2001
From: Feng Xue <f...@os.amperecomputing.com>
Date: Wed, 29 May 2024 17:28:14 +0800
Subject: [PATCH 8/8] vect: Optimize order of lane-reducing statements 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 = 0;
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>
}
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 vectorized lane-reducing statements 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 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 <f...@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.
---
gcc/tree-vect-loop.cc | 39 +++++++++++++++++++++++++++++++++++----
gcc/tree-vectorizer.h | 6 ++++++
2 files changed, 41 insertions(+), 4 deletions(-)
diff --git a/gcc/tree-vect-loop.cc b/gcc/tree-vect-loop.cc
index 6d91665a341..c7e13d655d8 100644
--- a/gcc/tree-vect-loop.cc
+++ b/gcc/tree-vect-loop.cc
@@ -8828,9 +8828,9 @@ vect_transform_reduction (loop_vec_info loop_vinfo,
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_v0 = sum_v0; // copy
+ sum_v1 = SAD (s0_v1[i: 0 ~ 7 ], s1_v1[i: 0 ~ 7 ], sum_v1);
+ sum_v2 = SAD (s0_v2[i: 8 ~ 15], s1_v2[i: 8 ~ 15], sum_v2);
sum_v3 = sum_v3; // copy
sum_v0 += n_v0[i: 0 ~ 3 ];
@@ -8838,14 +8838,45 @@ vect_transform_reduction (loop_vec_info loop_vinfo,
sum_v2 += n_v2[i: 8 ~ 11];
sum_v3 += n_v3[i: 12 ~ 15];
}
- */
+
+ Moreover, for a higher instruction parallelism in final vectorized
+ loop, it is considered to make those effective vectorized lane-
+ reducing statements be distributed evenly among all def-use cycles.
+ In the above example, SADs are generated into other cycles rather
+ than that of DOT_PROD. */
unsigned using_ncopies = vec_oprnds[0].length ();
unsigned reduc_ncopies = vec_oprnds[reduc_index].length ();
+ unsigned result_pos = reduc_info->reduc_result_pos;
+
+ reduc_info->reduc_result_pos
+ = (result_pos + using_ncopies) % reduc_ncopies;
+ gcc_assert (result_pos < reduc_ncopies);
for (unsigned i = 0; i < op.num_ops - 1; i++)
{
gcc_assert (vec_oprnds[i].length () == using_ncopies);
vec_oprnds[i].safe_grow_cleared (reduc_ncopies);
+
+ /* Find suitable def-use cycles to generate vectorized statements
+ into, and reorder operands based on the selection. */
+ if (result_pos)
+ {
+ unsigned count = reduc_ncopies - using_ncopies;
+ unsigned start = result_pos - count;
+
+ if ((int) start < 0)
+ {
+ count = result_pos;
+ start = 0;
+ }
+
+ for (unsigned j = using_ncopies; j > start; j--)
+ {
+ unsigned k = j - 1;
+ std::swap (vec_oprnds[i][k], vec_oprnds[i][k + count]);
+ gcc_assert (!vec_oprnds[i][k]);
+ }
+ }
}
}
diff --git a/gcc/tree-vectorizer.h b/gcc/tree-vectorizer.h
index 94736736dcc..64c6571a293 100644
--- a/gcc/tree-vectorizer.h
+++ b/gcc/tree-vectorizer.h
@@ -1402,6 +1402,12 @@ public:
/* The vector type for performing the actual reduction. */
tree reduc_vectype;
+ /* For loop reduction with multiple vectorized results (ncopies > 1), a
+ lane-reducing operation participating in it may not use all of those
+ results, this field specifies result index starting from which any
+ following land-reducing operation would be assigned to. */
+ unsigned int reduc_result_pos;
+
/* If IS_REDUC_INFO is true and if the vector code is performing
N scalar reductions in parallel, this variable gives the initial
scalar values of those N reductions. */
--
2.17.1
