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Restore the initial ordering of dimensions before applying the pattern matching 

Dimensions of band nodes can be implicitly permuted by the algorithm applied
during the schedule generation.

For example, in case of the following matrix-matrix multiplication,

for (i = 0; i < 1024; i++)
  for (k = 0; k < 1024; k++)
    for (j = 0; j < 1024; j++)
      C[i][j] += A[i][k] * B[k][j];

it can produce the following schedule tree

domain: "{ Stmt_for_body6[i0, i1, i2] : 0 <= i0 <= 1023 and 0 <= i1 <= 1023 and
                                        0 <= i2 <= 1023 }"
child:
  schedule: "[{ Stmt_for_body6[i0, i1, i2] -> [(i0)] },
              { Stmt_for_body6[i0, i1, i2] -> [(i1)] },
              { Stmt_for_body6[i0, i1, i2] -> [(i2)] }]"
  permutable: 1
  coincident: [ 1, 1, 0 ]

The current implementation of the pattern matching optimizations relies on the
initial ordering of dimensions. Otherwise, it can produce the miscompilation
(e.g., [1]).

This patch helps to restore the initial ordering of dimensions by recreating
the band node when the corresponding conditions are satisfied.

Refs.:

[1] - https://bugs.llvm.org/show_bug.cgi?id=32500

Reviewed-by: Michael Kruse <llvm@meinersbur.de>

Differential Revision: https://reviews.llvm.org/D31741

llvm-svn: 299662
This commit is contained in:
Roman Gareev 2017-04-06 17:09:54 +00:00
parent d3115972bf
commit e0d466342b
2 changed files with 162 additions and 1 deletions
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40
polly/lib/Transform/ScheduleOptimizer.cpp
View File

@ -1268,6 +1268,38 @@ static isl_schedule_node *markInterIterationAliasFree(isl_schedule_node *Node,
return isl_schedule_node_child(isl_schedule_node_insert_mark(Node, Id), 0);
}
/// Restore the initial ordering of dimensions of the band node
///
/// In case the band node represents all the dimensions of the iteration
/// domain, recreate the band node to restore the initial ordering of the
/// dimensions.
///
/// @param Node The band node to be modified.
/// @return The modified schedule node.
namespace {
isl::schedule_node getBandNodeWithOriginDimOrder(isl::schedule_node Node) {
assert(isl_schedule_node_get_type(Node.keep()) == isl_schedule_node_band);
if (isl_schedule_node_get_type(Node.child(0).keep()) !=
isl_schedule_node_leaf)
return Node;
auto Domain = isl::manage(isl_schedule_node_get_universe_domain(Node.keep()));
assert(isl_union_set_n_set(Domain.keep()) == 1);
if (isl_schedule_node_get_schedule_depth(Node.keep()) != 0 ||
(isl::set(isl::manage(Domain.copy())).dim(isl::dim::set) !=
isl_schedule_node_band_n_member(Node.keep())))
return Node;
Node = isl::manage(isl_schedule_node_delete(Node.take()));
auto PartialSchedulePwAff =
isl::manage(isl_union_set_identity_union_pw_multi_aff(Domain.take()));
auto PartialScheduleMultiPwAff =
isl::multi_union_pw_aff(PartialSchedulePwAff);
PartialScheduleMultiPwAff = isl::manage(isl_multi_union_pw_aff_reset_tuple_id(
PartialScheduleMultiPwAff.take(), isl_dim_set));
return isl::manage(isl_schedule_node_insert_partial_schedule(
Node.take(), PartialScheduleMultiPwAff.take()));
}
} // namespace
__isl_give isl_schedule_node *ScheduleTreeOptimizer::optimizeMatMulPattern(
__isl_take isl_schedule_node *Node, const llvm::TargetTransformInfo *TTI,
MatMulInfoTy &MMI) {
@ -1277,6 +1309,7 @@ __isl_give isl_schedule_node *ScheduleTreeOptimizer::optimizeMatMulPattern(
assert(DimOutNum > 2 && "In case of the matrix multiplication the loop nest "
"and, consequently, the corresponding scheduling "
"functions have at least three dimensions.");
Node = getBandNodeWithOriginDimOrder(isl::manage(Node)).take();
Node = permuteBandNodeDimensions(Node, MMI.i, DimOutNum - 3);
int NewJ = MMI.j == DimOutNum - 3 ? MMI.i : MMI.j;
int NewK = MMI.k == DimOutNum - 3 ? MMI.i : MMI.k;
@ -1304,7 +1337,12 @@ bool ScheduleTreeOptimizer::isMatrMultPattern(
MatMulInfoTy &MMI) {
auto *PartialSchedule =
isl_schedule_node_band_get_partial_schedule_union_map(Node);
if (isl_schedule_node_band_n_member(Node) < 3 ||
Node = isl_schedule_node_child(Node, 0);
auto LeafType = isl_schedule_node_get_type(Node);
Node = isl_schedule_node_parent(Node);
if (LeafType != isl_schedule_node_leaf ||
isl_schedule_node_band_n_member(Node) < 3 ||
isl_schedule_node_get_schedule_depth(Node) != 0 ||
isl_union_map_n_map(PartialSchedule) != 1) {
isl_union_map_free(PartialSchedule);
return false;

123
polly/test/ScheduleOptimizer/pattern-matching-based-opts_4.ll Normal file
View File

@ -0,0 +1,123 @@
; RUN: opt %loadPolly -polly-opt-isl -polly-pattern-matching-based-opts=true \
; RUN: -debug < %s 2>&1| FileCheck %s
; RUN: opt %loadPolly -polly-opt-isl -polly-pattern-matching-based-opts=true \
; RUN: -polly-target-throughput-vector-fma=1 \
; RUN: -polly-target-latency-vector-fma=8 \
; RUN: -polly-target-1st-cache-level-size=32768 \
; RUN: -polly-target-vector-register-bitwidth=256 \
; RUN: -polly-target-2nd-cache-level-size=262144 -polly-ast \
; RUN: -analyze < %s | FileCheck %s --check-prefix=PATTERN-MATCHING-OPTS
; REQUIRES: asserts
;
; C := A * B + C
; Check that the pattern matching optimizations can detect different
; permutations of GEMM loop and produce the correct ISL AST. In this case,
; dimensions of band nodes can be implicitly permuted by the algorithm
; applied during the schedule generation. It should be taken into the
; account during the pattern matching optimizations.
; for (i = 0; i < _PB_NI; i++)
; for (k = 0; k < _PB_NK; ++k)
; for (j = 0; j < _PB_NJ; j++)
; C[i][j] += A[i][k] * B[k][j];
;
; CHECK: The matrix multiplication pattern was detected
;
; PATTERN-MATCHING-OPTS: // 1st level tiling - Tiles
; PATTERN-MATCHING-OPTS-NEXT: for (int c1 = 0; c1 <= 3; c1 += 1) {
; PATTERN-MATCHING-OPTS-NEXT: for (int c3 = 256 * c1; c3 <= 256 * c1 + 255; c3 += 1)
; PATTERN-MATCHING-OPTS-NEXT: for (int c4 = 0; c4 <= 1023; c4 += 1)
; PATTERN-MATCHING-OPTS-NEXT: CopyStmt_0(0, c3, c4);
; PATTERN-MATCHING-OPTS-NEXT: for (int c2 = 0; c2 <= 10; c2 += 1) {
; PATTERN-MATCHING-OPTS-NEXT: for (int c3 = 96 * c2; c3 <= min(1023, 96 * c2 + 95); c3 += 1)
; PATTERN-MATCHING-OPTS-NEXT: for (int c4 = 256 * c1; c4 <= 256 * c1 + 255; c4 += 1)
; PATTERN-MATCHING-OPTS-NEXT: CopyStmt_1(c3, c4, 0);
; PATTERN-MATCHING-OPTS-NEXT: // 1st level tiling - Points
; PATTERN-MATCHING-OPTS-NEXT: // Register tiling - Tiles
; PATTERN-MATCHING-OPTS-NEXT: for (int c3 = 0; c3 <= 127; c3 += 1)
; PATTERN-MATCHING-OPTS-NEXT: for (int c4 = 0; c4 <= min(23, -24 * c2 + 255); c4 += 1)
; PATTERN-MATCHING-OPTS-NEXT: for (int c5 = 0; c5 <= 255; c5 += 1) {
; PATTERN-MATCHING-OPTS-NEXT: // Register tiling - Points
; PATTERN-MATCHING-OPTS-NEXT: {
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 256 * c1 + c5, 8 * c3);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 256 * c1 + c5, 8 * c3 + 1);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 256 * c1 + c5, 8 * c3 + 2);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 256 * c1 + c5, 8 * c3 + 3);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 256 * c1 + c5, 8 * c3 + 4);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 256 * c1 + c5, 8 * c3 + 5);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 256 * c1 + c5, 8 * c3 + 6);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 256 * c1 + c5, 8 * c3 + 7);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 256 * c1 + c5, 8 * c3);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 256 * c1 + c5, 8 * c3 + 1);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 256 * c1 + c5, 8 * c3 + 2);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 256 * c1 + c5, 8 * c3 + 3);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 256 * c1 + c5, 8 * c3 + 4);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 256 * c1 + c5, 8 * c3 + 5);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 256 * c1 + c5, 8 * c3 + 6);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 256 * c1 + c5, 8 * c3 + 7);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 256 * c1 + c5, 8 * c3);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 256 * c1 + c5, 8 * c3 + 1);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 256 * c1 + c5, 8 * c3 + 2);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 256 * c1 + c5, 8 * c3 + 3);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 256 * c1 + c5, 8 * c3 + 4);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 256 * c1 + c5, 8 * c3 + 5);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 256 * c1 + c5, 8 * c3 + 6);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 256 * c1 + c5, 8 * c3 + 7);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 256 * c1 + c5, 8 * c3);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 256 * c1 + c5, 8 * c3 + 1);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 256 * c1 + c5, 8 * c3 + 2);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 256 * c1 + c5, 8 * c3 + 3);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 256 * c1 + c5, 8 * c3 + 4);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 256 * c1 + c5, 8 * c3 + 5);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 256 * c1 + c5, 8 * c3 + 6);
; PATTERN-MATCHING-OPTS-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 256 * c1 + c5, 8 * c3 + 7);
; PATTERN-MATCHING-OPTS-NEXT: }
; PATTERN-MATCHING-OPTS-NEXT: }
; PATTERN-MATCHING-OPTS-NEXT: }
; PATTERN-MATCHING-OPTS-NEXT: }
;
target datalayout = "e-m:e-i64:64-f80:128-n8:16:32:64-S128"
target triple = "x86_64-unknown-unknown"
define internal void @kernel_gemm(i32 %ni, i32 %nj, i32 %nk, double %alpha, double %beta, [1024 x double]* %C, [1024 x double]* %A, [1024 x double]* %B) {
entry:
br label %entry.split
entry.split: ; preds = %entry
br label %for.cond1.preheader
for.cond1.preheader: ; preds = %for.inc20, %entry.split
%indvars.iv41 = phi i64 [ 0, %entry.split ], [ %indvars.iv.next42, %for.inc20 ]
br label %for.cond4.preheader
for.cond4.preheader: ; preds = %for.inc17, %for.cond1.preheader
%indvars.iv38 = phi i64 [ 0, %for.cond1.preheader ], [ %indvars.iv.next39, %for.inc17 ]
br label %for.body6
for.body6: ; preds = %for.body6, %for.cond4.preheader
%indvars.iv = phi i64 [ 0, %for.cond4.preheader ], [ %indvars.iv.next, %for.body6 ]
%arrayidx8 = getelementptr inbounds [1024 x double], [1024 x double]* %A, i64 %indvars.iv41, i64 %indvars.iv38
%tmp = load double, double* %arrayidx8, align 8
%arrayidx12 = getelementptr inbounds [1024 x double], [1024 x double]* %B, i64 %indvars.iv38, i64 %indvars.iv
%tmp1 = load double, double* %arrayidx12, align 8
%mul = fmul double %tmp, %tmp1
%arrayidx16 = getelementptr inbounds [1024 x double], [1024 x double]* %C, i64 %indvars.iv41, i64 %indvars.iv
%tmp2 = load double, double* %arrayidx16, align 8
%add = fadd double %tmp2, %mul
store double %add, double* %arrayidx16, align 8
%indvars.iv.next = add nuw nsw i64 %indvars.iv, 1
%exitcond = icmp ne i64 %indvars.iv.next, 1024
br i1 %exitcond, label %for.body6, label %for.inc17
for.inc17: ; preds = %for.body6
%indvars.iv.next39 = add nuw nsw i64 %indvars.iv38, 1
%exitcond40 = icmp ne i64 %indvars.iv.next39, 1024
br i1 %exitcond40, label %for.cond4.preheader, label %for.inc20
for.inc20: ; preds = %for.inc17
%indvars.iv.next42 = add nuw nsw i64 %indvars.iv41, 1
%exitcond43 = icmp ne i64 %indvars.iv.next42, 1024
br i1 %exitcond43, label %for.cond1.preheader, label %for.end22
for.end22: ; preds = %for.inc20
ret void
}