1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
1155
1156
1157
1158
1159
1160
1161
1162
1163
1164
1165
1166
1167
1168
1169
1170
1171
1172
1173
1174
1175
1176
1177
1178
1179
1180
1181
1182
1183
1184
1185
1186
1187
1188
1189
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
1207
1208
1209
1210
1211
1212
1213
1214
1215
1216
1217
1218
1219
1220
1221
1222
1223
1224
1225
1226
1227
1228
1229
1230
1231
1232
1233
1234
1235
1236
1237
1238
1239
1240
1241
1242
1243
1244
1245
1246
1247
1248
1249
1250
1251
1252
1253
1254
1255
1256
1257
1258
1259
1260
1261
1262
1263
1264
1265
1266
1267
1268
1269
1270
1271
1272
1273
1274
1275
1276
1277
1278
1279
1280
1281
1282
1283
1284
1285
1286
1287
1288
1289
1290
1291
1292
1293
1294
1295
1296
1297
1298
1299
1300
1301
1302
1303
1304
1305
1306
1307
1308
1309
1310
1311
1312
1313
1314
1315
1316
1317
1318
1319
1320
1321
1322
1323
1324
1325
1326
1327
1328
1329
1330
1331
1332
1333
1334
1335
1336
1337
1338
1339
1340
1341
1342
1343
1344
1345
1346
1347
1348
1349
1350
1351
1352
1353
1354
1355
1356
1357
1358
1359
1360
1361
1362
1363
1364
1365
1366
1367
1368
1369
1370
1371
1372
1373
1374
1375
1376
1377
1378
1379
1380
1381
1382
1383
1384
1385
1386
1387
1388
1389
1390
1391
1392
1393
1394
1395
1396
1397
|
//===- SimplifyIntrinsics.cpp -- replace intrinsics with simpler form -----===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
//===----------------------------------------------------------------------===//
/// \file
/// This pass looks for suitable calls to runtime library for intrinsics that
/// can be simplified/specialized and replaces with a specialized function.
///
/// For example, SUM(arr) can be specialized as a simple function with one loop,
/// compared to the three arguments (plus file & line info) that the runtime
/// call has - when the argument is a 1D-array (multiple loops may be needed
// for higher dimension arrays, of course)
///
/// The general idea is that besides making the call simpler, it can also be
/// inlined by other passes that run after this pass, which further improves
/// performance, particularly when the work done in the function is trivial
/// and small in size.
//===----------------------------------------------------------------------===//
#include "flang/Common/Fortran.h"
#include "flang/Optimizer/Builder/BoxValue.h"
#include "flang/Optimizer/Builder/FIRBuilder.h"
#include "flang/Optimizer/Builder/LowLevelIntrinsics.h"
#include "flang/Optimizer/Builder/Todo.h"
#include "flang/Optimizer/Dialect/FIROps.h"
#include "flang/Optimizer/Dialect/FIRType.h"
#include "flang/Optimizer/Dialect/Support/FIRContext.h"
#include "flang/Optimizer/HLFIR/HLFIRDialect.h"
#include "flang/Optimizer/Transforms/Passes.h"
#include "flang/Runtime/entry-names.h"
#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
#include "mlir/IR/Matchers.h"
#include "mlir/IR/Operation.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Transforms/DialectConversion.h"
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
#include "mlir/Transforms/RegionUtils.h"
#include "llvm/Support/Debug.h"
#include "llvm/Support/raw_ostream.h"
#include <llvm/Support/ErrorHandling.h>
#include <mlir/Dialect/Arith/IR/Arith.h>
#include <mlir/IR/BuiltinTypes.h>
#include <mlir/IR/Location.h>
#include <mlir/IR/MLIRContext.h>
#include <mlir/IR/Value.h>
#include <mlir/Support/LLVM.h>
#include <optional>
namespace fir {
#define GEN_PASS_DEF_SIMPLIFYINTRINSICS
#include "flang/Optimizer/Transforms/Passes.h.inc"
} // namespace fir
#define DEBUG_TYPE "flang-simplify-intrinsics"
namespace {
class SimplifyIntrinsicsPass
: public fir::impl::SimplifyIntrinsicsBase<SimplifyIntrinsicsPass> {
using FunctionTypeGeneratorTy =
llvm::function_ref<mlir::FunctionType(fir::FirOpBuilder &)>;
using FunctionBodyGeneratorTy =
llvm::function_ref<void(fir::FirOpBuilder &, mlir::func::FuncOp &)>;
using GenReductionBodyTy = llvm::function_ref<void(
fir::FirOpBuilder &builder, mlir::func::FuncOp &funcOp, unsigned rank,
mlir::Type elementType)>;
public:
/// Generate a new function implementing a simplified version
/// of a Fortran runtime function defined by \p basename name.
/// \p typeGenerator is a callback that generates the new function's type.
/// \p bodyGenerator is a callback that generates the new function's body.
/// The new function is created in the \p builder's Module.
mlir::func::FuncOp getOrCreateFunction(fir::FirOpBuilder &builder,
const mlir::StringRef &basename,
FunctionTypeGeneratorTy typeGenerator,
FunctionBodyGeneratorTy bodyGenerator);
void runOnOperation() override;
void getDependentDialects(mlir::DialectRegistry ®istry) const override;
private:
/// Helper functions to replace a reduction type of call with its
/// simplified form. The actual function is generated using a callback
/// function.
/// \p call is the call to be replaced
/// \p kindMap is used to create FIROpBuilder
/// \p genBodyFunc is the callback that builds the replacement function
void simplifyIntOrFloatReduction(fir::CallOp call,
const fir::KindMapping &kindMap,
GenReductionBodyTy genBodyFunc);
void simplifyLogicalDim0Reduction(fir::CallOp call,
const fir::KindMapping &kindMap,
GenReductionBodyTy genBodyFunc);
void simplifyLogicalDim1Reduction(fir::CallOp call,
const fir::KindMapping &kindMap,
GenReductionBodyTy genBodyFunc);
void simplifyMinMaxlocReduction(fir::CallOp call,
const fir::KindMapping &kindMap, bool isMax);
void simplifyReductionBody(fir::CallOp call, const fir::KindMapping &kindMap,
GenReductionBodyTy genBodyFunc,
fir::FirOpBuilder &builder,
const mlir::StringRef &basename,
mlir::Type elementType);
};
} // namespace
/// Create FirOpBuilder with the provided \p op insertion point
/// and \p kindMap additionally inheriting FastMathFlags from \p op.
static fir::FirOpBuilder
getSimplificationBuilder(mlir::Operation *op, const fir::KindMapping &kindMap) {
fir::FirOpBuilder builder{op, kindMap};
auto fmi = mlir::dyn_cast<mlir::arith::ArithFastMathInterface>(*op);
if (!fmi)
return builder;
// Regardless of what default FastMathFlags are used by FirOpBuilder,
// override them with FastMathFlags attached to the operation.
builder.setFastMathFlags(fmi.getFastMathFlagsAttr().getValue());
return builder;
}
/// Generate function type for the simplified version of RTNAME(Sum) and
/// similar functions with a fir.box<none> type returning \p elementType.
static mlir::FunctionType genNoneBoxType(fir::FirOpBuilder &builder,
const mlir::Type &elementType) {
mlir::Type boxType = fir::BoxType::get(builder.getNoneType());
return mlir::FunctionType::get(builder.getContext(), {boxType},
{elementType});
}
template <typename Op>
Op expectOp(mlir::Value val) {
if (Op op = mlir::dyn_cast_or_null<Op>(val.getDefiningOp()))
return op;
LLVM_DEBUG(llvm::dbgs() << "Didn't find expected " << Op::getOperationName()
<< '\n');
return nullptr;
}
template <typename Op>
static mlir::Value findDefSingle(fir::ConvertOp op) {
if (auto defOp = expectOp<Op>(op->getOperand(0))) {
return defOp.getResult();
}
return {};
}
template <typename... Ops>
static mlir::Value findDef(fir::ConvertOp op) {
mlir::Value defOp;
// Loop over the operation types given to see if any match, exiting once
// a match is found. Cast to void is needed to avoid compiler complaining
// that the result of expression is unused
(void)((defOp = findDefSingle<Ops>(op), (defOp)) || ...);
return defOp;
}
static bool isOperandAbsent(mlir::Value val) {
if (auto op = expectOp<fir::ConvertOp>(val)) {
assert(op->getOperands().size() != 0);
return mlir::isa_and_nonnull<fir::AbsentOp>(
op->getOperand(0).getDefiningOp());
}
return false;
}
static bool isTrueOrNotConstant(mlir::Value val) {
if (auto op = expectOp<mlir::arith::ConstantOp>(val)) {
return !mlir::matchPattern(val, mlir::m_Zero());
}
return true;
}
static bool isZero(mlir::Value val) {
if (auto op = expectOp<fir::ConvertOp>(val)) {
assert(op->getOperands().size() != 0);
if (mlir::Operation *defOp = op->getOperand(0).getDefiningOp())
return mlir::matchPattern(defOp, mlir::m_Zero());
}
return false;
}
static mlir::Value findBoxDef(mlir::Value val) {
if (auto op = expectOp<fir::ConvertOp>(val)) {
assert(op->getOperands().size() != 0);
return findDef<fir::EmboxOp, fir::ReboxOp>(op);
}
return {};
}
static mlir::Value findMaskDef(mlir::Value val) {
if (auto op = expectOp<fir::ConvertOp>(val)) {
assert(op->getOperands().size() != 0);
return findDef<fir::EmboxOp, fir::ReboxOp, fir::AbsentOp>(op);
}
return {};
}
static unsigned getDimCount(mlir::Value val) {
// In order to find the dimensions count, we look for EmboxOp/ReboxOp
// and take the count from its *result* type. Note that in case
// of sliced emboxing the operand and the result of EmboxOp/ReboxOp
// have different types.
// Actually, we can take the box type from the operand of
// the first ConvertOp that has non-opaque box type that we meet
// going through the ConvertOp chain.
if (mlir::Value emboxVal = findBoxDef(val))
if (auto boxTy = emboxVal.getType().dyn_cast<fir::BoxType>())
if (auto seqTy = boxTy.getEleTy().dyn_cast<fir::SequenceType>())
return seqTy.getDimension();
return 0;
}
/// Given the call operation's box argument \p val, discover
/// the element type of the underlying array object.
/// \returns the element type or std::nullopt if the type cannot
/// be reliably found.
/// We expect that the argument is a result of fir.convert
/// with the destination type of !fir.box<none>.
static std::optional<mlir::Type> getArgElementType(mlir::Value val) {
mlir::Operation *defOp;
do {
defOp = val.getDefiningOp();
// Analyze only sequences of convert operations.
if (!mlir::isa<fir::ConvertOp>(defOp))
return std::nullopt;
val = defOp->getOperand(0);
// The convert operation is expected to convert from one
// box type to another box type.
auto boxType = val.getType().cast<fir::BoxType>();
auto elementType = fir::unwrapSeqOrBoxedSeqType(boxType);
if (!elementType.isa<mlir::NoneType>())
return elementType;
} while (true);
}
using BodyOpGeneratorTy = llvm::function_ref<mlir::Value(
fir::FirOpBuilder &, mlir::Location, const mlir::Type &, mlir::Value,
mlir::Value)>;
using InitValGeneratorTy = llvm::function_ref<mlir::Value(
fir::FirOpBuilder &, mlir::Location, const mlir::Type &)>;
using ContinueLoopGenTy = llvm::function_ref<llvm::SmallVector<mlir::Value>(
fir::FirOpBuilder &, mlir::Location, mlir::Value)>;
/// Generate the reduction loop into \p funcOp.
///
/// \p initVal is a function, called to get the initial value for
/// the reduction value
/// \p genBody is called to fill in the actual reduciton operation
/// for example add for SUM, MAX for MAXVAL, etc.
/// \p rank is the rank of the input argument.
/// \p elementType is the type of the elements in the input array,
/// which may be different to the return type.
/// \p loopCond is called to generate the condition to continue or
/// not for IterWhile loops
/// \p unorderedOrInitalLoopCond contains either a boolean or bool
/// mlir constant, and controls the inital value for while loops
/// or if DoLoop is ordered/unordered.
template <typename OP, typename T, int resultIndex>
static void
genReductionLoop(fir::FirOpBuilder &builder, mlir::func::FuncOp &funcOp,
InitValGeneratorTy initVal, ContinueLoopGenTy loopCond,
T unorderedOrInitialLoopCond, BodyOpGeneratorTy genBody,
unsigned rank, mlir::Type elementType, mlir::Location loc) {
mlir::IndexType idxTy = builder.getIndexType();
mlir::Block::BlockArgListType args = funcOp.front().getArguments();
mlir::Value arg = args[0];
mlir::Value zeroIdx = builder.createIntegerConstant(loc, idxTy, 0);
fir::SequenceType::Shape flatShape(rank,
fir::SequenceType::getUnknownExtent());
mlir::Type arrTy = fir::SequenceType::get(flatShape, elementType);
mlir::Type boxArrTy = fir::BoxType::get(arrTy);
mlir::Value array = builder.create<fir::ConvertOp>(loc, boxArrTy, arg);
mlir::Type resultType = funcOp.getResultTypes()[0];
mlir::Value init = initVal(builder, loc, resultType);
llvm::SmallVector<mlir::Value, Fortran::common::maxRank> bounds;
assert(rank > 0 && "rank cannot be zero");
mlir::Value one = builder.createIntegerConstant(loc, idxTy, 1);
// Compute all the upper bounds before the loop nest.
// It is not strictly necessary for performance, since the loop nest
// does not have any store operations and any LICM optimization
// should be able to optimize the redundancy.
for (unsigned i = 0; i < rank; ++i) {
mlir::Value dimIdx = builder.createIntegerConstant(loc, idxTy, i);
auto dims =
builder.create<fir::BoxDimsOp>(loc, idxTy, idxTy, idxTy, array, dimIdx);
mlir::Value len = dims.getResult(1);
// We use C indexing here, so len-1 as loopcount
mlir::Value loopCount = builder.create<mlir::arith::SubIOp>(loc, len, one);
bounds.push_back(loopCount);
}
// Create a loop nest consisting of OP operations.
// Collect the loops' induction variables into indices array,
// which will be used in the innermost loop to load the input
// array's element.
// The loops are generated such that the innermost loop processes
// the 0 dimension.
llvm::SmallVector<mlir::Value, Fortran::common::maxRank> indices;
for (unsigned i = rank; 0 < i; --i) {
mlir::Value step = one;
mlir::Value loopCount = bounds[i - 1];
auto loop = builder.create<OP>(loc, zeroIdx, loopCount, step,
unorderedOrInitialLoopCond,
/*finalCountValue=*/false, init);
init = loop.getRegionIterArgs()[resultIndex];
indices.push_back(loop.getInductionVar());
// Set insertion point to the loop body so that the next loop
// is inserted inside the current one.
builder.setInsertionPointToStart(loop.getBody());
}
// Reverse the indices such that they are ordered as:
// <dim-0-idx, dim-1-idx, ...>
std::reverse(indices.begin(), indices.end());
// We are in the innermost loop: generate the reduction body.
mlir::Type eleRefTy = builder.getRefType(elementType);
mlir::Value addr =
builder.create<fir::CoordinateOp>(loc, eleRefTy, array, indices);
mlir::Value elem = builder.create<fir::LoadOp>(loc, addr);
mlir::Value reductionVal = genBody(builder, loc, elementType, elem, init);
// Generate vector with condition to continue while loop at [0] and result
// from current loop at [1] for IterWhileOp loops, just result at [0] for
// DoLoopOp loops.
llvm::SmallVector<mlir::Value> results = loopCond(builder, loc, reductionVal);
// Unwind the loop nest and insert ResultOp on each level
// to return the updated value of the reduction to the enclosing
// loops.
for (unsigned i = 0; i < rank; ++i) {
auto result = builder.create<fir::ResultOp>(loc, results);
// Proceed to the outer loop.
auto loop = mlir::cast<OP>(result->getParentOp());
results = loop.getResults();
// Set insertion point after the loop operation that we have
// just processed.
builder.setInsertionPointAfter(loop.getOperation());
}
// End of loop nest. The insertion point is after the outermost loop.
// Return the reduction value from the function.
builder.create<mlir::func::ReturnOp>(loc, results[resultIndex]);
}
using MinMaxlocBodyOpGeneratorTy = llvm::function_ref<mlir::Value(
fir::FirOpBuilder &, mlir::Location, const mlir::Type &, mlir::Value,
mlir::Value, llvm::SmallVector<mlir::Value, Fortran::common::maxRank> &)>;
static void genMinMaxlocReductionLoop(
fir::FirOpBuilder &builder, mlir::func::FuncOp &funcOp,
InitValGeneratorTy initVal, MinMaxlocBodyOpGeneratorTy genBody,
unsigned rank, mlir::Type elementType, mlir::Location loc, bool hasMask,
mlir::Type maskElemType, mlir::Value resultArr) {
mlir::IndexType idxTy = builder.getIndexType();
mlir::Block::BlockArgListType args = funcOp.front().getArguments();
mlir::Value arg = args[1];
mlir::Value zeroIdx = builder.createIntegerConstant(loc, idxTy, 0);
fir::SequenceType::Shape flatShape(rank,
fir::SequenceType::getUnknownExtent());
mlir::Type arrTy = fir::SequenceType::get(flatShape, elementType);
mlir::Type boxArrTy = fir::BoxType::get(arrTy);
mlir::Value array = builder.create<fir::ConvertOp>(loc, boxArrTy, arg);
mlir::Type resultElemType = hlfir::getFortranElementType(resultArr.getType());
mlir::Value flagSet = builder.createIntegerConstant(loc, resultElemType, 1);
mlir::Value zero = builder.createIntegerConstant(loc, resultElemType, 0);
mlir::Value flagRef = builder.createTemporary(loc, resultElemType);
builder.create<fir::StoreOp>(loc, zero, flagRef);
mlir::Value mask;
if (hasMask) {
mlir::Type maskTy = fir::SequenceType::get(flatShape, maskElemType);
mlir::Type boxMaskTy = fir::BoxType::get(maskTy);
mask = builder.create<fir::ConvertOp>(loc, boxMaskTy, args[2]);
}
mlir::Value init = initVal(builder, loc, elementType);
llvm::SmallVector<mlir::Value, Fortran::common::maxRank> bounds;
assert(rank > 0 && "rank cannot be zero");
mlir::Value one = builder.createIntegerConstant(loc, idxTy, 1);
// Compute all the upper bounds before the loop nest.
// It is not strictly necessary for performance, since the loop nest
// does not have any store operations and any LICM optimization
// should be able to optimize the redundancy.
for (unsigned i = 0; i < rank; ++i) {
mlir::Value dimIdx = builder.createIntegerConstant(loc, idxTy, i);
auto dims =
builder.create<fir::BoxDimsOp>(loc, idxTy, idxTy, idxTy, array, dimIdx);
mlir::Value len = dims.getResult(1);
// We use C indexing here, so len-1 as loopcount
mlir::Value loopCount = builder.create<mlir::arith::SubIOp>(loc, len, one);
bounds.push_back(loopCount);
}
// Create a loop nest consisting of OP operations.
// Collect the loops' induction variables into indices array,
// which will be used in the innermost loop to load the input
// array's element.
// The loops are generated such that the innermost loop processes
// the 0 dimension.
llvm::SmallVector<mlir::Value, Fortran::common::maxRank> indices;
for (unsigned i = rank; 0 < i; --i) {
mlir::Value step = one;
mlir::Value loopCount = bounds[i - 1];
auto loop =
builder.create<fir::DoLoopOp>(loc, zeroIdx, loopCount, step, false,
/*finalCountValue=*/false, init);
init = loop.getRegionIterArgs()[0];
indices.push_back(loop.getInductionVar());
// Set insertion point to the loop body so that the next loop
// is inserted inside the current one.
builder.setInsertionPointToStart(loop.getBody());
}
// Reverse the indices such that they are ordered as:
// <dim-0-idx, dim-1-idx, ...>
std::reverse(indices.begin(), indices.end());
// We are in the innermost loop: generate the reduction body.
if (hasMask) {
mlir::Type logicalRef = builder.getRefType(maskElemType);
mlir::Value maskAddr =
builder.create<fir::CoordinateOp>(loc, logicalRef, mask, indices);
mlir::Value maskElem = builder.create<fir::LoadOp>(loc, maskAddr);
// fir::IfOp requires argument to be I1 - won't accept logical or any other
// Integer.
mlir::Type ifCompatType = builder.getI1Type();
mlir::Value ifCompatElem =
builder.create<fir::ConvertOp>(loc, ifCompatType, maskElem);
llvm::SmallVector<mlir::Type> resultsTy = {elementType, elementType};
fir::IfOp ifOp = builder.create<fir::IfOp>(loc, elementType, ifCompatElem,
/*withElseRegion=*/true);
builder.setInsertionPointToStart(&ifOp.getThenRegion().front());
}
// Set flag that mask was true at some point
builder.create<fir::StoreOp>(loc, flagSet, flagRef);
mlir::Type eleRefTy = builder.getRefType(elementType);
mlir::Value addr =
builder.create<fir::CoordinateOp>(loc, eleRefTy, array, indices);
mlir::Value elem = builder.create<fir::LoadOp>(loc, addr);
mlir::Value reductionVal =
genBody(builder, loc, elementType, elem, init, indices);
if (hasMask) {
fir::IfOp ifOp =
mlir::dyn_cast<fir::IfOp>(builder.getBlock()->getParentOp());
builder.create<fir::ResultOp>(loc, reductionVal);
builder.setInsertionPointToStart(&ifOp.getElseRegion().front());
builder.create<fir::ResultOp>(loc, init);
reductionVal = ifOp.getResult(0);
builder.setInsertionPointAfter(ifOp);
}
// Unwind the loop nest and insert ResultOp on each level
// to return the updated value of the reduction to the enclosing
// loops.
for (unsigned i = 0; i < rank; ++i) {
auto result = builder.create<fir::ResultOp>(loc, reductionVal);
// Proceed to the outer loop.
auto loop = mlir::cast<fir::DoLoopOp>(result->getParentOp());
reductionVal = loop.getResult(0);
// Set insertion point after the loop operation that we have
// just processed.
builder.setInsertionPointAfter(loop.getOperation());
}
// End of loop nest. The insertion point is after the outermost loop.
if (fir::IfOp ifOp =
mlir::dyn_cast<fir::IfOp>(builder.getBlock()->getParentOp())) {
builder.create<fir::ResultOp>(loc, reductionVal);
builder.setInsertionPointAfter(ifOp);
// Redefine flagSet to escape scope of ifOp
flagSet = builder.createIntegerConstant(loc, resultElemType, 1);
reductionVal = ifOp.getResult(0);
}
// Check for case where array was full of max values.
// flag will be 0 if mask was never true, 1 if mask was true as some point,
// this is needed to avoid catching cases where we didn't access any elements
// e.g. mask=.FALSE.
mlir::Value flagValue =
builder.create<fir::LoadOp>(loc, resultElemType, flagRef);
mlir::Value flagCmp = builder.create<mlir::arith::CmpIOp>(
loc, mlir::arith::CmpIPredicate::eq, flagValue, flagSet);
fir::IfOp ifMaskTrueOp =
builder.create<fir::IfOp>(loc, flagCmp, /*withElseRegion=*/false);
builder.setInsertionPointToStart(&ifMaskTrueOp.getThenRegion().front());
mlir::Value testInit = initVal(builder, loc, elementType);
fir::IfOp ifMinSetOp;
if (elementType.isa<mlir::FloatType>()) {
mlir::Value cmp = builder.create<mlir::arith::CmpFOp>(
loc, mlir::arith::CmpFPredicate::OEQ, testInit, reductionVal);
ifMinSetOp = builder.create<fir::IfOp>(loc, cmp,
/*withElseRegion*/ false);
} else {
mlir::Value cmp = builder.create<mlir::arith::CmpIOp>(
loc, mlir::arith::CmpIPredicate::eq, testInit, reductionVal);
ifMinSetOp = builder.create<fir::IfOp>(loc, cmp,
/*withElseRegion*/ false);
}
builder.setInsertionPointToStart(&ifMinSetOp.getThenRegion().front());
// Load output array with 1s instead of 0s
for (unsigned int i = 0; i < rank; ++i) {
mlir::Type resultRefTy = builder.getRefType(resultElemType);
// mlir::Value one = builder.createIntegerConstant(loc, resultElemType, 1);
mlir::Value index = builder.createIntegerConstant(loc, idxTy, i);
mlir::Value resultElemAddr =
builder.create<fir::CoordinateOp>(loc, resultRefTy, resultArr, index);
builder.create<fir::StoreOp>(loc, flagSet, resultElemAddr);
}
builder.setInsertionPointAfter(ifMaskTrueOp);
// Store newly created output array to the reference passed in
fir::SequenceType::Shape resultShape(1, rank);
mlir::Type outputArrTy = fir::SequenceType::get(resultShape, resultElemType);
mlir::Type outputHeapTy = fir::HeapType::get(outputArrTy);
mlir::Type outputBoxTy = fir::BoxType::get(outputHeapTy);
mlir::Type outputRefTy = builder.getRefType(outputBoxTy);
mlir::Value outputArrNone = args[0];
mlir::Value outputArr =
builder.create<fir::ConvertOp>(loc, outputRefTy, outputArrNone);
// Store nearly created array to output array
builder.create<fir::StoreOp>(loc, resultArr, outputArr);
builder.create<mlir::func::ReturnOp>(loc);
}
static llvm::SmallVector<mlir::Value> nopLoopCond(fir::FirOpBuilder &builder,
mlir::Location loc,
mlir::Value reductionVal) {
return {reductionVal};
}
/// Generate function body of the simplified version of RTNAME(Sum)
/// with signature provided by \p funcOp. The caller is responsible
/// for saving/restoring the original insertion point of \p builder.
/// \p funcOp is expected to be empty on entry to this function.
/// \p rank specifies the rank of the input argument.
static void genRuntimeSumBody(fir::FirOpBuilder &builder,
mlir::func::FuncOp &funcOp, unsigned rank,
mlir::Type elementType) {
// function RTNAME(Sum)<T>x<rank>_simplified(arr)
// T, dimension(:) :: arr
// T sum = 0
// integer iter
// do iter = 0, extent(arr)
// sum = sum + arr[iter]
// end do
// RTNAME(Sum)<T>x<rank>_simplified = sum
// end function RTNAME(Sum)<T>x<rank>_simplified
auto zero = [](fir::FirOpBuilder builder, mlir::Location loc,
mlir::Type elementType) {
if (auto ty = elementType.dyn_cast<mlir::FloatType>()) {
const llvm::fltSemantics &sem = ty.getFloatSemantics();
return builder.createRealConstant(loc, elementType,
llvm::APFloat::getZero(sem));
}
return builder.createIntegerConstant(loc, elementType, 0);
};
auto genBodyOp = [](fir::FirOpBuilder builder, mlir::Location loc,
mlir::Type elementType, mlir::Value elem1,
mlir::Value elem2) -> mlir::Value {
if (elementType.isa<mlir::FloatType>())
return builder.create<mlir::arith::AddFOp>(loc, elem1, elem2);
if (elementType.isa<mlir::IntegerType>())
return builder.create<mlir::arith::AddIOp>(loc, elem1, elem2);
llvm_unreachable("unsupported type");
return {};
};
mlir::Location loc = mlir::UnknownLoc::get(builder.getContext());
builder.setInsertionPointToEnd(funcOp.addEntryBlock());
genReductionLoop<fir::DoLoopOp, bool, 0>(builder, funcOp, zero, nopLoopCond,
false, genBodyOp, rank, elementType,
loc);
}
static void genRuntimeMaxvalBody(fir::FirOpBuilder &builder,
mlir::func::FuncOp &funcOp, unsigned rank,
mlir::Type elementType) {
auto init = [](fir::FirOpBuilder builder, mlir::Location loc,
mlir::Type elementType) {
if (auto ty = elementType.dyn_cast<mlir::FloatType>()) {
const llvm::fltSemantics &sem = ty.getFloatSemantics();
return builder.createRealConstant(
loc, elementType, llvm::APFloat::getLargest(sem, /*Negative=*/true));
}
unsigned bits = elementType.getIntOrFloatBitWidth();
int64_t minInt = llvm::APInt::getSignedMinValue(bits).getSExtValue();
return builder.createIntegerConstant(loc, elementType, minInt);
};
auto genBodyOp = [](fir::FirOpBuilder builder, mlir::Location loc,
mlir::Type elementType, mlir::Value elem1,
mlir::Value elem2) -> mlir::Value {
if (elementType.isa<mlir::FloatType>()) {
// arith.maxf later converted to llvm.intr.maxnum does not work
// correctly for NaNs and -0.0 (see maxnum/minnum pattern matching
// in LLVM's InstCombine pass). Moreover, llvm.intr.maxnum
// for F128 operands is lowered into fmaxl call by LLVM.
// This libm function may not work properly for F128 arguments
// on targets where long double is not F128. It is an LLVM issue,
// but we just use normal select here to resolve all the cases.
auto compare = builder.create<mlir::arith::CmpFOp>(
loc, mlir::arith::CmpFPredicate::OGT, elem1, elem2);
return builder.create<mlir::arith::SelectOp>(loc, compare, elem1, elem2);
}
if (elementType.isa<mlir::IntegerType>())
return builder.create<mlir::arith::MaxSIOp>(loc, elem1, elem2);
llvm_unreachable("unsupported type");
return {};
};
mlir::Location loc = mlir::UnknownLoc::get(builder.getContext());
builder.setInsertionPointToEnd(funcOp.addEntryBlock());
genReductionLoop<fir::DoLoopOp, bool, 0>(builder, funcOp, init, nopLoopCond,
false, genBodyOp, rank, elementType,
loc);
}
static void genRuntimeCountBody(fir::FirOpBuilder &builder,
mlir::func::FuncOp &funcOp, unsigned rank,
mlir::Type elementType) {
auto zero = [](fir::FirOpBuilder builder, mlir::Location loc,
mlir::Type elementType) {
unsigned bits = elementType.getIntOrFloatBitWidth();
int64_t zeroInt = llvm::APInt::getZero(bits).getSExtValue();
return builder.createIntegerConstant(loc, elementType, zeroInt);
};
auto genBodyOp = [](fir::FirOpBuilder builder, mlir::Location loc,
mlir::Type elementType, mlir::Value elem1,
mlir::Value elem2) -> mlir::Value {
auto zero32 = builder.createIntegerConstant(loc, elementType, 0);
auto zero64 = builder.createIntegerConstant(loc, builder.getI64Type(), 0);
auto one64 = builder.createIntegerConstant(loc, builder.getI64Type(), 1);
auto compare = builder.create<mlir::arith::CmpIOp>(
loc, mlir::arith::CmpIPredicate::eq, elem1, zero32);
auto select =
builder.create<mlir::arith::SelectOp>(loc, compare, zero64, one64);
return builder.create<mlir::arith::AddIOp>(loc, select, elem2);
};
// Count always gets I32 for elementType as it converts logical input to
// logical<4> before passing to the function.
mlir::Location loc = mlir::UnknownLoc::get(builder.getContext());
builder.setInsertionPointToEnd(funcOp.addEntryBlock());
genReductionLoop<fir::DoLoopOp, bool, 0>(builder, funcOp, zero, nopLoopCond,
false, genBodyOp, rank, elementType,
loc);
}
static void genRuntimeAnyBody(fir::FirOpBuilder &builder,
mlir::func::FuncOp &funcOp, unsigned rank,
mlir::Type elementType) {
auto zero = [](fir::FirOpBuilder builder, mlir::Location loc,
mlir::Type elementType) {
return builder.createIntegerConstant(loc, elementType, 0);
};
auto genBodyOp = [](fir::FirOpBuilder builder, mlir::Location loc,
mlir::Type elementType, mlir::Value elem1,
mlir::Value elem2) -> mlir::Value {
auto zero = builder.createIntegerConstant(loc, elementType, 0);
return builder.create<mlir::arith::CmpIOp>(
loc, mlir::arith::CmpIPredicate::ne, elem1, zero);
};
auto continueCond = [](fir::FirOpBuilder builder, mlir::Location loc,
mlir::Value reductionVal) {
auto one1 = builder.createIntegerConstant(loc, builder.getI1Type(), 1);
auto eor = builder.create<mlir::arith::XOrIOp>(loc, reductionVal, one1);
llvm::SmallVector<mlir::Value> results = {eor, reductionVal};
return results;
};
mlir::Location loc = mlir::UnknownLoc::get(builder.getContext());
builder.setInsertionPointToEnd(funcOp.addEntryBlock());
mlir::Value ok = builder.createBool(loc, true);
genReductionLoop<fir::IterWhileOp, mlir::Value, 1>(
builder, funcOp, zero, continueCond, ok, genBodyOp, rank, elementType,
loc);
}
static void genRuntimeAllBody(fir::FirOpBuilder &builder,
mlir::func::FuncOp &funcOp, unsigned rank,
mlir::Type elementType) {
auto one = [](fir::FirOpBuilder builder, mlir::Location loc,
mlir::Type elementType) {
return builder.createIntegerConstant(loc, elementType, 1);
};
auto genBodyOp = [](fir::FirOpBuilder builder, mlir::Location loc,
mlir::Type elementType, mlir::Value elem1,
mlir::Value elem2) -> mlir::Value {
auto zero = builder.createIntegerConstant(loc, elementType, 0);
return builder.create<mlir::arith::CmpIOp>(
loc, mlir::arith::CmpIPredicate::ne, elem1, zero);
};
auto continueCond = [](fir::FirOpBuilder builder, mlir::Location loc,
mlir::Value reductionVal) {
llvm::SmallVector<mlir::Value> results = {reductionVal, reductionVal};
return results;
};
mlir::Location loc = mlir::UnknownLoc::get(builder.getContext());
builder.setInsertionPointToEnd(funcOp.addEntryBlock());
mlir::Value ok = builder.createBool(loc, true);
genReductionLoop<fir::IterWhileOp, mlir::Value, 1>(
builder, funcOp, one, continueCond, ok, genBodyOp, rank, elementType,
loc);
}
static mlir::FunctionType genRuntimeMinlocType(fir::FirOpBuilder &builder,
unsigned int rank) {
mlir::Type boxType = fir::BoxType::get(builder.getNoneType());
mlir::Type boxRefType = builder.getRefType(boxType);
return mlir::FunctionType::get(builder.getContext(),
{boxRefType, boxType, boxType}, {});
}
static void genRuntimeMinMaxlocBody(fir::FirOpBuilder &builder,
mlir::func::FuncOp &funcOp, bool isMax,
unsigned rank, int maskRank,
mlir::Type elementType,
mlir::Type maskElemType,
mlir::Type resultElemTy) {
auto init = [isMax](fir::FirOpBuilder builder, mlir::Location loc,
mlir::Type elementType) {
if (auto ty = elementType.dyn_cast<mlir::FloatType>()) {
const llvm::fltSemantics &sem = ty.getFloatSemantics();
return builder.createRealConstant(
loc, elementType, llvm::APFloat::getLargest(sem, /*Negative=*/isMax));
}
unsigned bits = elementType.getIntOrFloatBitWidth();
int64_t initValue = (isMax ? llvm::APInt::getSignedMinValue(bits)
: llvm::APInt::getSignedMaxValue(bits))
.getSExtValue();
return builder.createIntegerConstant(loc, elementType, initValue);
};
mlir::Location loc = mlir::UnknownLoc::get(builder.getContext());
builder.setInsertionPointToEnd(funcOp.addEntryBlock());
mlir::Value mask = funcOp.front().getArgument(2);
// Set up result array in case of early exit / 0 length array
mlir::IndexType idxTy = builder.getIndexType();
mlir::Type resultTy = fir::SequenceType::get(rank, resultElemTy);
mlir::Type resultHeapTy = fir::HeapType::get(resultTy);
mlir::Type resultBoxTy = fir::BoxType::get(resultHeapTy);
mlir::Value returnValue = builder.createIntegerConstant(loc, resultElemTy, 0);
mlir::Value resultArrSize = builder.createIntegerConstant(loc, idxTy, rank);
mlir::Value resultArrInit = builder.create<fir::AllocMemOp>(loc, resultTy);
mlir::Value resultArrShape = builder.create<fir::ShapeOp>(loc, resultArrSize);
mlir::Value resultArr = builder.create<fir::EmboxOp>(
loc, resultBoxTy, resultArrInit, resultArrShape);
mlir::Type resultRefTy = builder.getRefType(resultElemTy);
for (unsigned int i = 0; i < rank; ++i) {
mlir::Value index = builder.createIntegerConstant(loc, idxTy, i);
mlir::Value resultElemAddr =
builder.create<fir::CoordinateOp>(loc, resultRefTy, resultArr, index);
builder.create<fir::StoreOp>(loc, returnValue, resultElemAddr);
}
auto genBodyOp =
[&rank, &resultArr,
isMax](fir::FirOpBuilder builder, mlir::Location loc,
mlir::Type elementType, mlir::Value elem1, mlir::Value elem2,
llvm::SmallVector<mlir::Value, Fortran::common::maxRank> indices)
-> mlir::Value {
mlir::Value cmp;
if (elementType.isa<mlir::FloatType>()) {
cmp = builder.create<mlir::arith::CmpFOp>(
loc,
isMax ? mlir::arith::CmpFPredicate::OGT
: mlir::arith::CmpFPredicate::OLT,
elem1, elem2);
} else if (elementType.isa<mlir::IntegerType>()) {
cmp = builder.create<mlir::arith::CmpIOp>(
loc,
isMax ? mlir::arith::CmpIPredicate::sgt
: mlir::arith::CmpIPredicate::slt,
elem1, elem2);
} else {
llvm_unreachable("unsupported type");
}
fir::IfOp ifOp = builder.create<fir::IfOp>(loc, elementType, cmp,
/*withElseRegion*/ true);
builder.setInsertionPointToStart(&ifOp.getThenRegion().front());
mlir::Type resultElemTy = hlfir::getFortranElementType(resultArr.getType());
mlir::Type returnRefTy = builder.getRefType(resultElemTy);
mlir::IndexType idxTy = builder.getIndexType();
mlir::Value one = builder.createIntegerConstant(loc, resultElemTy, 1);
for (unsigned int i = 0; i < rank; ++i) {
mlir::Value index = builder.createIntegerConstant(loc, idxTy, i);
mlir::Value resultElemAddr =
builder.create<fir::CoordinateOp>(loc, returnRefTy, resultArr, index);
mlir::Value convert =
builder.create<fir::ConvertOp>(loc, resultElemTy, indices[i]);
mlir::Value fortranIndex =
builder.create<mlir::arith::AddIOp>(loc, convert, one);
builder.create<fir::StoreOp>(loc, fortranIndex, resultElemAddr);
}
builder.create<fir::ResultOp>(loc, elem1);
builder.setInsertionPointToStart(&ifOp.getElseRegion().front());
builder.create<fir::ResultOp>(loc, elem2);
builder.setInsertionPointAfter(ifOp);
return ifOp.getResult(0);
};
// if mask is a logical scalar, we can check its value before the main loop
// and either ignore the fact it is there or exit early.
if (maskRank == 0) {
mlir::Type logical = builder.getI1Type();
mlir::IndexType idxTy = builder.getIndexType();
fir::SequenceType::Shape singleElement(1, 1);
mlir::Type arrTy = fir::SequenceType::get(singleElement, logical);
mlir::Type boxArrTy = fir::BoxType::get(arrTy);
mlir::Value array = builder.create<fir::ConvertOp>(loc, boxArrTy, mask);
mlir::Value indx = builder.createIntegerConstant(loc, idxTy, 0);
mlir::Type logicalRefTy = builder.getRefType(logical);
mlir::Value condAddr =
builder.create<fir::CoordinateOp>(loc, logicalRefTy, array, indx);
mlir::Value cond = builder.create<fir::LoadOp>(loc, condAddr);
fir::IfOp ifOp = builder.create<fir::IfOp>(loc, elementType, cond,
/*withElseRegion=*/true);
builder.setInsertionPointToStart(&ifOp.getElseRegion().front());
mlir::Value basicValue;
if (elementType.isa<mlir::IntegerType>()) {
basicValue = builder.createIntegerConstant(loc, elementType, 0);
} else {
basicValue = builder.createRealConstant(loc, elementType, 0);
}
builder.create<fir::ResultOp>(loc, basicValue);
builder.setInsertionPointToStart(&ifOp.getThenRegion().front());
}
// bit of a hack - maskRank is set to -1 for absent mask arg, so don't
// generate high level mask or element by element mask.
bool hasMask = maskRank > 0;
genMinMaxlocReductionLoop(builder, funcOp, init, genBodyOp, rank, elementType,
loc, hasMask, maskElemType, resultArr);
}
/// Generate function type for the simplified version of RTNAME(DotProduct)
/// operating on the given \p elementType.
static mlir::FunctionType genRuntimeDotType(fir::FirOpBuilder &builder,
const mlir::Type &elementType) {
mlir::Type boxType = fir::BoxType::get(builder.getNoneType());
return mlir::FunctionType::get(builder.getContext(), {boxType, boxType},
{elementType});
}
/// Generate function body of the simplified version of RTNAME(DotProduct)
/// with signature provided by \p funcOp. The caller is responsible
/// for saving/restoring the original insertion point of \p builder.
/// \p funcOp is expected to be empty on entry to this function.
/// \p arg1ElementTy and \p arg2ElementTy specify elements types
/// of the underlying array objects - they are used to generate proper
/// element accesses.
static void genRuntimeDotBody(fir::FirOpBuilder &builder,
mlir::func::FuncOp &funcOp,
mlir::Type arg1ElementTy,
mlir::Type arg2ElementTy) {
// function RTNAME(DotProduct)<T>_simplified(arr1, arr2)
// T, dimension(:) :: arr1, arr2
// T product = 0
// integer iter
// do iter = 0, extent(arr1)
// product = product + arr1[iter] * arr2[iter]
// end do
// RTNAME(ADotProduct)<T>_simplified = product
// end function RTNAME(DotProduct)<T>_simplified
auto loc = mlir::UnknownLoc::get(builder.getContext());
mlir::Type resultElementType = funcOp.getResultTypes()[0];
builder.setInsertionPointToEnd(funcOp.addEntryBlock());
mlir::IndexType idxTy = builder.getIndexType();
mlir::Value zero =
resultElementType.isa<mlir::FloatType>()
? builder.createRealConstant(loc, resultElementType, 0.0)
: builder.createIntegerConstant(loc, resultElementType, 0);
mlir::Block::BlockArgListType args = funcOp.front().getArguments();
mlir::Value arg1 = args[0];
mlir::Value arg2 = args[1];
mlir::Value zeroIdx = builder.createIntegerConstant(loc, idxTy, 0);
fir::SequenceType::Shape flatShape = {fir::SequenceType::getUnknownExtent()};
mlir::Type arrTy1 = fir::SequenceType::get(flatShape, arg1ElementTy);
mlir::Type boxArrTy1 = fir::BoxType::get(arrTy1);
mlir::Value array1 = builder.create<fir::ConvertOp>(loc, boxArrTy1, arg1);
mlir::Type arrTy2 = fir::SequenceType::get(flatShape, arg2ElementTy);
mlir::Type boxArrTy2 = fir::BoxType::get(arrTy2);
mlir::Value array2 = builder.create<fir::ConvertOp>(loc, boxArrTy2, arg2);
// This version takes the loop trip count from the first argument.
// If the first argument's box has unknown (at compilation time)
// extent, then it may be better to take the extent from the second
// argument - so that after inlining the loop may be better optimized, e.g.
// fully unrolled. This requires generating two versions of the simplified
// function and some analysis at the call site to choose which version
// is more profitable to call.
// Note that we can assume that both arguments have the same extent.
auto dims =
builder.create<fir::BoxDimsOp>(loc, idxTy, idxTy, idxTy, array1, zeroIdx);
mlir::Value len = dims.getResult(1);
mlir::Value one = builder.createIntegerConstant(loc, idxTy, 1);
mlir::Value step = one;
// We use C indexing here, so len-1 as loopcount
mlir::Value loopCount = builder.create<mlir::arith::SubIOp>(loc, len, one);
auto loop = builder.create<fir::DoLoopOp>(loc, zeroIdx, loopCount, step,
/*unordered=*/false,
/*finalCountValue=*/false, zero);
mlir::Value sumVal = loop.getRegionIterArgs()[0];
// Begin loop code
mlir::OpBuilder::InsertPoint loopEndPt = builder.saveInsertionPoint();
builder.setInsertionPointToStart(loop.getBody());
mlir::Type eleRef1Ty = builder.getRefType(arg1ElementTy);
mlir::Value index = loop.getInductionVar();
mlir::Value addr1 =
builder.create<fir::CoordinateOp>(loc, eleRef1Ty, array1, index);
mlir::Value elem1 = builder.create<fir::LoadOp>(loc, addr1);
// Convert to the result type.
elem1 = builder.create<fir::ConvertOp>(loc, resultElementType, elem1);
mlir::Type eleRef2Ty = builder.getRefType(arg2ElementTy);
mlir::Value addr2 =
builder.create<fir::CoordinateOp>(loc, eleRef2Ty, array2, index);
mlir::Value elem2 = builder.create<fir::LoadOp>(loc, addr2);
// Convert to the result type.
elem2 = builder.create<fir::ConvertOp>(loc, resultElementType, elem2);
if (resultElementType.isa<mlir::FloatType>())
sumVal = builder.create<mlir::arith::AddFOp>(
loc, builder.create<mlir::arith::MulFOp>(loc, elem1, elem2), sumVal);
else if (resultElementType.isa<mlir::IntegerType>())
sumVal = builder.create<mlir::arith::AddIOp>(
loc, builder.create<mlir::arith::MulIOp>(loc, elem1, elem2), sumVal);
else
llvm_unreachable("unsupported type");
builder.create<fir::ResultOp>(loc, sumVal);
// End of loop.
builder.restoreInsertionPoint(loopEndPt);
mlir::Value resultVal = loop.getResult(0);
builder.create<mlir::func::ReturnOp>(loc, resultVal);
}
mlir::func::FuncOp SimplifyIntrinsicsPass::getOrCreateFunction(
fir::FirOpBuilder &builder, const mlir::StringRef &baseName,
FunctionTypeGeneratorTy typeGenerator,
FunctionBodyGeneratorTy bodyGenerator) {
// WARNING: if the function generated here changes its signature
// or behavior (the body code), we should probably embed some
// versioning information into its name, otherwise libraries
// statically linked with older versions of Flang may stop
// working with object files created with newer Flang.
// We can also avoid this by using internal linkage, but
// this may increase the size of final executable/shared library.
std::string replacementName = mlir::Twine{baseName, "_simplified"}.str();
mlir::ModuleOp module = builder.getModule();
// If we already have a function, just return it.
mlir::func::FuncOp newFunc =
fir::FirOpBuilder::getNamedFunction(module, replacementName);
mlir::FunctionType fType = typeGenerator(builder);
if (newFunc) {
assert(newFunc.getFunctionType() == fType &&
"type mismatch for simplified function");
return newFunc;
}
// Need to build the function!
auto loc = mlir::UnknownLoc::get(builder.getContext());
newFunc =
fir::FirOpBuilder::createFunction(loc, module, replacementName, fType);
auto inlineLinkage = mlir::LLVM::linkage::Linkage::LinkonceODR;
auto linkage =
mlir::LLVM::LinkageAttr::get(builder.getContext(), inlineLinkage);
newFunc->setAttr("llvm.linkage", linkage);
// Save the position of the original call.
mlir::OpBuilder::InsertPoint insertPt = builder.saveInsertionPoint();
bodyGenerator(builder, newFunc);
// Now back to where we were adding code earlier...
builder.restoreInsertionPoint(insertPt);
return newFunc;
}
void SimplifyIntrinsicsPass::simplifyIntOrFloatReduction(
fir::CallOp call, const fir::KindMapping &kindMap,
GenReductionBodyTy genBodyFunc) {
// args[1] and args[2] are source filename and line number, ignored.
mlir::Operation::operand_range args = call.getArgs();
const mlir::Value &dim = args[3];
const mlir::Value &mask = args[4];
// dim is zero when it is absent, which is an implementation
// detail in the runtime library.
bool dimAndMaskAbsent = isZero(dim) && isOperandAbsent(mask);
unsigned rank = getDimCount(args[0]);
// Rank is set to 0 for assumed shape arrays, don't simplify
// in these cases
if (!(dimAndMaskAbsent && rank > 0))
return;
mlir::Type resultType = call.getResult(0).getType();
if (!resultType.isa<mlir::FloatType>() &&
!resultType.isa<mlir::IntegerType>())
return;
auto argType = getArgElementType(args[0]);
if (!argType)
return;
assert(*argType == resultType &&
"Argument/result types mismatch in reduction");
mlir::SymbolRefAttr callee = call.getCalleeAttr();
fir::FirOpBuilder builder{getSimplificationBuilder(call, kindMap)};
std::string fmfString{builder.getFastMathFlagsString()};
std::string funcName =
(mlir::Twine{callee.getLeafReference().getValue(), "x"} +
mlir::Twine{rank} +
// We must mangle the generated function name with FastMathFlags
// value.
(fmfString.empty() ? mlir::Twine{} : mlir::Twine{"_", fmfString}))
.str();
simplifyReductionBody(call, kindMap, genBodyFunc, builder, funcName,
resultType);
}
void SimplifyIntrinsicsPass::simplifyLogicalDim0Reduction(
fir::CallOp call, const fir::KindMapping &kindMap,
GenReductionBodyTy genBodyFunc) {
mlir::Operation::operand_range args = call.getArgs();
const mlir::Value &dim = args[3];
unsigned rank = getDimCount(args[0]);
// getDimCount returns a rank of 0 for assumed shape arrays, don't simplify in
// these cases.
if (!(isZero(dim) && rank > 0))
return;
mlir::Value inputBox = findBoxDef(args[0]);
mlir::Type elementType = hlfir::getFortranElementType(inputBox.getType());
mlir::SymbolRefAttr callee = call.getCalleeAttr();
fir::FirOpBuilder builder{getSimplificationBuilder(call, kindMap)};
// Treating logicals as integers makes things a lot easier
fir::LogicalType logicalType = {elementType.dyn_cast<fir::LogicalType>()};
fir::KindTy kind = logicalType.getFKind();
mlir::Type intElementType = builder.getIntegerType(kind * 8);
// Mangle kind into function name as it is not done by default
std::string funcName =
(mlir::Twine{callee.getLeafReference().getValue(), "Logical"} +
mlir::Twine{kind} + "x" + mlir::Twine{rank})
.str();
simplifyReductionBody(call, kindMap, genBodyFunc, builder, funcName,
intElementType);
}
void SimplifyIntrinsicsPass::simplifyLogicalDim1Reduction(
fir::CallOp call, const fir::KindMapping &kindMap,
GenReductionBodyTy genBodyFunc) {
mlir::Operation::operand_range args = call.getArgs();
mlir::SymbolRefAttr callee = call.getCalleeAttr();
mlir::StringRef funcNameBase = callee.getLeafReference().getValue();
unsigned rank = getDimCount(args[0]);
// getDimCount returns a rank of 0 for assumed shape arrays, don't simplify in
// these cases. We check for Dim at the end as some logical functions (Any,
// All) set dim to 1 instead of 0 when the argument is not present.
if (funcNameBase.ends_with("Dim") || !(rank > 0))
return;
mlir::Value inputBox = findBoxDef(args[0]);
mlir::Type elementType = hlfir::getFortranElementType(inputBox.getType());
fir::FirOpBuilder builder{getSimplificationBuilder(call, kindMap)};
// Treating logicals as integers makes things a lot easier
fir::LogicalType logicalType = {elementType.dyn_cast<fir::LogicalType>()};
fir::KindTy kind = logicalType.getFKind();
mlir::Type intElementType = builder.getIntegerType(kind * 8);
// Mangle kind into function name as it is not done by default
std::string funcName =
(mlir::Twine{callee.getLeafReference().getValue(), "Logical"} +
mlir::Twine{kind} + "x" + mlir::Twine{rank})
.str();
simplifyReductionBody(call, kindMap, genBodyFunc, builder, funcName,
intElementType);
}
void SimplifyIntrinsicsPass::simplifyMinMaxlocReduction(
fir::CallOp call, const fir::KindMapping &kindMap, bool isMax) {
mlir::Operation::operand_range args = call.getArgs();
mlir::Value back = args[6];
if (isTrueOrNotConstant(back))
return;
mlir::Value mask = args[5];
mlir::Value maskDef = findMaskDef(mask);
// maskDef is set to NULL when the defining op is not one we accept.
// This tends to be because it is a selectOp, in which case let the
// runtime deal with it.
if (maskDef == NULL)
return;
mlir::SymbolRefAttr callee = call.getCalleeAttr();
mlir::StringRef funcNameBase = callee.getLeafReference().getValue();
unsigned rank = getDimCount(args[1]);
if (funcNameBase.ends_with("Dim") || !(rank > 0))
return;
fir::FirOpBuilder builder{getSimplificationBuilder(call, kindMap)};
mlir::Location loc = call.getLoc();
auto inputBox = findBoxDef(args[1]);
mlir::Type inputType = hlfir::getFortranElementType(inputBox.getType());
if (inputType.isa<fir::CharacterType>())
return;
int maskRank;
fir::KindTy kind = 0;
mlir::Type logicalElemType = builder.getI1Type();
if (isOperandAbsent(mask)) {
maskRank = -1;
} else {
maskRank = getDimCount(mask);
mlir::Type maskElemTy = hlfir::getFortranElementType(maskDef.getType());
fir::LogicalType logicalFirType = {maskElemTy.dyn_cast<fir::LogicalType>()};
kind = logicalFirType.getFKind();
// Convert fir::LogicalType to mlir::Type
logicalElemType = logicalFirType;
}
mlir::Operation *outputDef = args[0].getDefiningOp();
mlir::Value outputAlloc = outputDef->getOperand(0);
mlir::Type outType = hlfir::getFortranElementType(outputAlloc.getType());
std::string fmfString{builder.getFastMathFlagsString()};
std::string funcName =
(mlir::Twine{callee.getLeafReference().getValue(), "x"} +
mlir::Twine{rank} +
(maskRank >= 0
? "_Logical" + mlir::Twine{kind} + "x" + mlir::Twine{maskRank}
: "") +
"_")
.str();
llvm::raw_string_ostream nameOS(funcName);
outType.print(nameOS);
nameOS << '_' << fmfString;
auto typeGenerator = [rank](fir::FirOpBuilder &builder) {
return genRuntimeMinlocType(builder, rank);
};
auto bodyGenerator = [rank, maskRank, inputType, logicalElemType, outType,
isMax](fir::FirOpBuilder &builder,
mlir::func::FuncOp &funcOp) {
genRuntimeMinMaxlocBody(builder, funcOp, isMax, rank, maskRank, inputType,
logicalElemType, outType);
};
mlir::func::FuncOp newFunc =
getOrCreateFunction(builder, funcName, typeGenerator, bodyGenerator);
builder.create<fir::CallOp>(loc, newFunc,
mlir::ValueRange{args[0], args[1], args[5]});
call->dropAllReferences();
call->erase();
}
void SimplifyIntrinsicsPass::simplifyReductionBody(
fir::CallOp call, const fir::KindMapping &kindMap,
GenReductionBodyTy genBodyFunc, fir::FirOpBuilder &builder,
const mlir::StringRef &funcName, mlir::Type elementType) {
mlir::Operation::operand_range args = call.getArgs();
mlir::Type resultType = call.getResult(0).getType();
unsigned rank = getDimCount(args[0]);
mlir::Location loc = call.getLoc();
auto typeGenerator = [&resultType](fir::FirOpBuilder &builder) {
return genNoneBoxType(builder, resultType);
};
auto bodyGenerator = [&rank, &genBodyFunc,
&elementType](fir::FirOpBuilder &builder,
mlir::func::FuncOp &funcOp) {
genBodyFunc(builder, funcOp, rank, elementType);
};
// Mangle the function name with the rank value as "x<rank>".
mlir::func::FuncOp newFunc =
getOrCreateFunction(builder, funcName, typeGenerator, bodyGenerator);
auto newCall =
builder.create<fir::CallOp>(loc, newFunc, mlir::ValueRange{args[0]});
call->replaceAllUsesWith(newCall.getResults());
call->dropAllReferences();
call->erase();
}
void SimplifyIntrinsicsPass::runOnOperation() {
LLVM_DEBUG(llvm::dbgs() << "=== Begin " DEBUG_TYPE " ===\n");
mlir::ModuleOp module = getOperation();
fir::KindMapping kindMap = fir::getKindMapping(module);
module.walk([&](mlir::Operation *op) {
if (auto call = mlir::dyn_cast<fir::CallOp>(op)) {
if (mlir::SymbolRefAttr callee = call.getCalleeAttr()) {
mlir::StringRef funcName = callee.getLeafReference().getValue();
// Replace call to runtime function for SUM when it has single
// argument (no dim or mask argument) for 1D arrays with either
// Integer4 or Real8 types. Other forms are ignored.
// The new function is added to the module.
//
// Prototype for runtime call (from sum.cpp):
// RTNAME(Sum<T>)(const Descriptor &x, const char *source, int line,
// int dim, const Descriptor *mask)
//
if (funcName.starts_with(RTNAME_STRING(Sum))) {
simplifyIntOrFloatReduction(call, kindMap, genRuntimeSumBody);
return;
}
if (funcName.starts_with(RTNAME_STRING(DotProduct))) {
LLVM_DEBUG(llvm::dbgs() << "Handling " << funcName << "\n");
LLVM_DEBUG(llvm::dbgs() << "Call operation:\n"; op->dump();
llvm::dbgs() << "\n");
mlir::Operation::operand_range args = call.getArgs();
const mlir::Value &v1 = args[0];
const mlir::Value &v2 = args[1];
mlir::Location loc = call.getLoc();
fir::FirOpBuilder builder{getSimplificationBuilder(op, kindMap)};
// Stringize the builder's FastMathFlags flags for mangling
// the generated function name.
std::string fmfString{builder.getFastMathFlagsString()};
mlir::Type type = call.getResult(0).getType();
if (!type.isa<mlir::FloatType>() && !type.isa<mlir::IntegerType>())
return;
// Try to find the element types of the boxed arguments.
auto arg1Type = getArgElementType(v1);
auto arg2Type = getArgElementType(v2);
if (!arg1Type || !arg2Type)
return;
// Support only floating point and integer arguments
// now (e.g. logical is skipped here).
if (!arg1Type->isa<mlir::FloatType>() &&
!arg1Type->isa<mlir::IntegerType>())
return;
if (!arg2Type->isa<mlir::FloatType>() &&
!arg2Type->isa<mlir::IntegerType>())
return;
auto typeGenerator = [&type](fir::FirOpBuilder &builder) {
return genRuntimeDotType(builder, type);
};
auto bodyGenerator = [&arg1Type,
&arg2Type](fir::FirOpBuilder &builder,
mlir::func::FuncOp &funcOp) {
genRuntimeDotBody(builder, funcOp, *arg1Type, *arg2Type);
};
// Suffix the function name with the element types
// of the arguments.
std::string typedFuncName(funcName);
llvm::raw_string_ostream nameOS(typedFuncName);
// We must mangle the generated function name with FastMathFlags
// value.
if (!fmfString.empty())
nameOS << '_' << fmfString;
nameOS << '_';
arg1Type->print(nameOS);
nameOS << '_';
arg2Type->print(nameOS);
mlir::func::FuncOp newFunc = getOrCreateFunction(
builder, typedFuncName, typeGenerator, bodyGenerator);
auto newCall = builder.create<fir::CallOp>(loc, newFunc,
mlir::ValueRange{v1, v2});
call->replaceAllUsesWith(newCall.getResults());
call->dropAllReferences();
call->erase();
LLVM_DEBUG(llvm::dbgs() << "Replaced with:\n"; newCall.dump();
llvm::dbgs() << "\n");
return;
}
if (funcName.starts_with(RTNAME_STRING(Maxval))) {
simplifyIntOrFloatReduction(call, kindMap, genRuntimeMaxvalBody);
return;
}
if (funcName.starts_with(RTNAME_STRING(Count))) {
simplifyLogicalDim0Reduction(call, kindMap, genRuntimeCountBody);
return;
}
if (funcName.starts_with(RTNAME_STRING(Any))) {
simplifyLogicalDim1Reduction(call, kindMap, genRuntimeAnyBody);
return;
}
if (funcName.ends_with(RTNAME_STRING(All))) {
simplifyLogicalDim1Reduction(call, kindMap, genRuntimeAllBody);
return;
}
if (funcName.starts_with(RTNAME_STRING(Minloc))) {
simplifyMinMaxlocReduction(call, kindMap, false);
return;
}
if (funcName.starts_with(RTNAME_STRING(Maxloc))) {
simplifyMinMaxlocReduction(call, kindMap, true);
return;
}
}
}
});
LLVM_DEBUG(llvm::dbgs() << "=== End " DEBUG_TYPE " ===\n");
}
void SimplifyIntrinsicsPass::getDependentDialects(
mlir::DialectRegistry ®istry) const {
// LLVM::LinkageAttr creation requires that LLVM dialect is loaded.
registry.insert<mlir::LLVM::LLVMDialect>();
}
std::unique_ptr<mlir::Pass> fir::createSimplifyIntrinsicsPass() {
return std::make_unique<SimplifyIntrinsicsPass>();
}
|