codegen_cuda.cc 96.7 KB
Newer Older
1
2
3
4
5
6
/*!
 * \file target/codegen.cc
 */

#include "codegen_cuda.h"
#include <tvm/arith/analyzer.h>
7
#include <tvm/ffi/function.h>
8
#include <tvm/tir/index_map.h>
9
10
11
12
13
14
15
16
#include <tvm/tir/op.h>

#include <cmath>
#include <string>
#include <utility>
#include <vector>

#include "../op/builtin.h"
17
#include "./ptx.h"
18
#include "arith/pattern_match.h"
19
20
21

namespace tvm {
namespace codegen {
22
using namespace tvm::tl::codegen;
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
struct CUDAMath {
  std::string operator()(DataType t, std::string name) const {
    if (t.is_float()) {
      switch (t.bits()) {
      case 64:
        return name;
      case 32:
        return name + 'f';
      case 16: {
        if (name == "fabs") {
          return "__habs";
        } else if (name == "round") {
          return "hrint";
        } else {
          return "h" + name;
        }
      }
      default:
        return "";
      }
    } else if (t.is_bfloat16()) {
      if (name == "fabs") {
        return "__habs";
      } else if (name == "round") {
        return "hrint";
      } else {
        return "h" + name;
      }
    } else if (t.is_int() || t.is_uint()) {
      switch (t.bits()) {
      case 32:
        return "__" + name;
      case 64:
        return "__" + name + "ll";
      default:
        return "";
      }
    }
    return "";
  }
};

struct CUDAFastMath : public CUDAMath {
  std::string operator()(DataType t, std::string name) const {
    if (t.is_float() && t.bits() == 32) {
      return "__" + name + 'f';
    } else {
      return CUDAMath::operator()(t, name);
    }
    return "";
  }
};

struct CUDAFastMathTan : public CUDAMath {
  std::string operator()(DataType t, std::string name) const {
    if (t.is_float()) {
      switch (t.bits()) {
      case 64:
        return name;
      // `__tanf` seems to produce some values too deviant from numpy tan
      // version. So, let's use just `tanf` instead.
      case 32:
        return name + 'f';
      case 16:
        return 'h' + name;
      default:
        return "";
      }
    }
    return "";
  }
};

97
98
99
100
101
102
103
104
105
106
107
108
struct CUDAIEEEMath {
  std::string operator()(DataType t, std::string name,
                         std::string rounding_mode) const {
    if (t.is_float() && t.bits() == 32) {
      return "__" + name + "_" + rounding_mode;
    } else if (t.is_float() && t.bits() == 64) {
      return "__d" + name + "_" + rounding_mode;
    }
    return "";
  }
};

109
110
111
112
113
114
115
116
117
118
119
120
121
122
static std::string GetFP8Type(DataType type) {
  std::stringstream stream;
  int32_t lanes = type.lanes();
  std::string vec;
  if (type.is_scalar()) {
    vec = "";
  } else if (lanes == 2) {
    vec = "_2";
  } else if (lanes == 4) {
    vec = "_4";
  } else if (lanes == 8) {
    vec = "_8";
  } else if (lanes == 16) {
    vec = "_16";
123
124
  } else if (lanes == 32) {
    vec = "_32";
125
  } else {
126
127
128
    LOG(FATAL)
        << "Only support scalar and vector types of width (2, 4, 8, 16, 32) "
           "for FP8";
129
  }
130
131
  if (type.is_float8_e4m3fn() || type.is_float8_e4m3fnuz() ||
      type.is_float8_e4m3()) {
132
    stream << "fp8_e4" << vec << "_t";
133
134
  } else if (type.is_float8_e5m2() || type.is_float8_e5m2fnuz() ||
             type.is_float8_e5m2()) {
135
136
    stream << "fp8_e5" << vec << "_t";
  } else {
137
    LOG(FATAL) << "Unsupported FP8 type in CUDA codegen but got " << type;
138
139
140
141
  }
  return stream.str();
}

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
std::string GetFP6Type(DataType type) {
  std::stringstream stream;
  int32_t lanes = type.lanes();
  std::string vec;
  if (type.is_scalar()) {
    vec = "";
  } else if (lanes == 2) {
    vec = "x2";
  } else if (lanes == 4) {
    vec = "x4";
  } else if (lanes == 8) {
    vec = "x8";
  } else if (lanes == 16) {
    vec = "x16";
  } else {
    LOG(FATAL)
        << "Only support scalar and vector types of width (2, 4) for FP6";
  }
  stream << "__nv_fp6";
  std::string suffix;
  if (type.code() == DataType::kFloat6_e2m3fn) {
    suffix = "_e2m3";
  } else if (type.code() == DataType::kFloat6_e3m2fn) {
    suffix = "_e3m2";
  } else {
    LOG(FATAL) << "Unsupported FP6 type in CUDA codegen";
  }
  stream << vec << suffix;
  return stream.str();
}

std::string GetFP4Type(DataType type) {
  std::stringstream stream;
  int32_t lanes = type.lanes();
  std::string vec;
  if (type.is_scalar()) {
    vec = "";
  } else if (lanes == 2) {
    vec = "x2";
  } else if (lanes == 4) {
    vec = "x4";
  } else if (lanes == 8) {
    vec = "x8";
  } else if (lanes == 16) {
    vec = "x16";
  } else {
    LOG(FATAL)
        << "Only support scalar and vector types of width (2, 4) for FP4";
  }
  stream << "__nv_fp4";
  std::string suffix;
  if (type.code() == DataType::kFloat4_e2m1fn) {
    suffix = "_e2m1";
  } else {
    LOG(FATAL) << "Unsupported FP4 type in CUDA codegen";
  }
  stream << vec << suffix;
  return stream.str();
}

202
203
CodeGenTileLangCUDA::CodeGenTileLangCUDA() {
  restrict_keyword_ = "__restrict__";
204
205
206
207
208
  vid_global_barrier_state_ =
      name_supply_->FreshName(runtime::symbol::tvm_global_barrier_state);
  vid_global_barrier_expect_ = name_supply_->FreshName("__barrier_expect");
  ICHECK_EQ(vid_global_barrier_state_,
            runtime::symbol::tvm_global_barrier_state);
209
}
210

211
212
213
void CodeGenTileLangCUDA::PrintFuncPrefix(std::ostream &os) {
  os << "extern \"C\" __global__ ";
}
214
215

class LaunchConfigExtractor : public tir::StmtVisitor {
216
217
private:
  void VisitStmt_(const AttrStmtNode *op) final {
218
219
    if (op->attr_key == tir::attr::thread_extent) {
      IterVar iv = Downcast<IterVar>(op->node);
220
221
      if (iv->var->name_hint == "threadIdx.x" ||
          iv->thread_tag == "threadIdx.x") {
222
        threadIdx_x_ext = op->value;
223
224
      } else if (iv->var->name_hint == "threadIdx.y" ||
                 iv->thread_tag == "threadIdx.y") {
225
        threadIdx_y_ext = op->value;
226
227
      } else if (iv->var->name_hint == "threadIdx.z" ||
                 iv->thread_tag == "threadIdx.z") {
228
229
230
231
232
233
        threadIdx_z_ext = op->value;
      }
    }
    StmtVisitor::VisitStmt_(op);
  }

234
public:
235
236
237
238
239
  PrimExpr threadIdx_x_ext = Integer(1);
  PrimExpr threadIdx_y_ext = Integer(1);
  PrimExpr threadIdx_z_ext = Integer(1);
};

240
void CodeGenTileLangCUDA::PrintExtraAttrs(const PrimFunc &f) {
241
242
243
  LaunchConfigExtractor extractor;
  extractor(f->body);
  arith::Analyzer analyzer;
244
245
246
247
248
  PrimExpr threadIdx_ext =
      analyzer.Simplify(extractor.threadIdx_x_ext * extractor.threadIdx_y_ext *
                        extractor.threadIdx_z_ext);
  if (const IntImmNode *const threadIdx_ext_int =
          threadIdx_ext.as<IntImmNode>()) {
249
    if (threadIdx_ext_int->value == 1) {
250
251
      // unable to extract the number of threads per block, hence directly
      // return
252
253
      return;
    }
254
    stream << " __launch_bounds__(" << threadIdx_ext_int->value << ", 1)";
255
256
257
258
259
260
261
  }
}

std::string CodeGenTileLangCUDA::Finish() {
  if (need_mma_h_) {
    decl_stream << "#include <mma.h>\n";
  }
262
263
264
265
266
267
268
269
  if (enable_fp8_) {
    decl_stream << "#include <tl_templates/cuda/cuda_fp8.h>\n";
  }

  if (need_math_constants_h_) {
    decl_stream << "#include <math_constants.h>\n";
  }

270
271
272
273
  if (need_cooperative_groups_) {
    decl_stream << "#include <cooperative_groups.h>\n";
  }

274
  decl_stream << "#include <tl_templates/cuda/gemm.h>\n";
275
276
277
  if (enable_sparse_gemm_) {
    decl_stream << "#include <tl_templates/cuda/gemm_sp.h>\n";
  }
278
279
280
281
  decl_stream << "#include <tl_templates/cuda/copy.h>\n";
  decl_stream << "#include <tl_templates/cuda/reduce.h>\n";
  decl_stream << "#include <tl_templates/cuda/ldsm.h>\n";
  decl_stream << "#include <tl_templates/cuda/threadblock_swizzle.h>\n";
282
  decl_stream << "#include <tl_templates/cuda/debug.h>\n";
283
284
285
  decl_stream << "#ifdef ENABLE_BF16\n";
  decl_stream << "#include <tl_templates/cuda/cuda_bf16_fallbacks.cuh>\n";
  decl_stream << "#endif\n";
286
287

  if (need_global_barrier_) {
288
289
    decl_stream << "__device__ unsigned " << vid_global_barrier_state_
                << " = 0;\n";
290
  }
291
  decl_stream << "\n";
292

293
294
295
  return CodeGenC::Finish();
}

296
void CodeGenTileLangCUDA::VisitStmt_(const tir::ForNode *op) {
297
298
299
300
  if (op->kind == tir::ForKind::kUnrolled) {
    PrintIndent();
    stream << "#pragma unroll\n";
  }
301
302
  std::string extent =
      PrintExpr(arith::Analyzer().Simplify(op->extent + op->min));
303
304
305
306
307
  PrintIndent();
  std::string vid = AllocVarID(op->loop_var.get());
  std::string start = PrintExpr(op->min);
  stream << "for (";
  PrintType(op->loop_var.dtype(), stream);
308
309
  stream << ' ' << vid << " = " << start << "; " << vid << " < " << extent
         << "; ++" << vid << ") {\n";
310
311
312
313
314
315
316
  int for_scope = BeginScope();
  PrintStmt(op->body);
  this->EndScope(for_scope);
  PrintIndent();
  stream << "}\n";
}

317
void CodeGenTileLangCUDA::BindThreadIndex(const IterVar &iv) {
318
  ICHECK(!var_idmap_.count(iv->var.get()));
319
320
  var_idmap_[iv->var.get()] =
      CastFromTo(iv->thread_tag, DataType::UInt(32), iv->var.dtype());
321
322
}

323
void CodeGenTileLangCUDA::PrintType(DataType t, std::ostream &os) { // NOLINT(*)
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
  int lanes = t.lanes();
  if (t.is_handle()) {
    ICHECK(t.is_scalar()) << "do not yet support vector types";
    os << "void*";
    return;
  }

  if (t.is_void()) {
    os << "void";
    return;
  }

  if (t == tl::cuTensorMapType()) {
    os << "CUtensorMap";
    return;
  }

  bool fail = false;
  if (t.is_float()) {
    switch (t.bits()) {
344
    case 16:
345
      enable_fp16_ = true;
346
347
348
349
350
351
352
353
354
355
356
357
358
359
      if (t.is_scalar()) {
        os << "half_t";
      } else if (lanes <= 8) {
        // Emit CUDA code to access fp16 vector elements.
        //
        // half4 is stored as uint2
        //
        // h4.x is emitted as *(half2*)(&(u2.x)).x
        // h4.y is emitted as *(half2*)(&(u2.x)).y
        // h4.z is emitted as *(half2*)(&(u2.y)).x
        // h4.w is emitted as *(half2*)(&(u2.y)).y
        //
        ICHECK_EQ(lanes % 2, 0) << "only support even lane for half type";
        os << "uint" << lanes / 2;
360
361
362
363
      } else if (lanes <= 16) {
        ICHECK_EQ(lanes % 4, 0) << "only support (mod 4 = 0) lanes for half "
                                   "type of more than 8 lanes";
        os << "ulonglong" << lanes / 4;
364
      } else {
365
        fail = true;
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
      }
      break;
    case 32:
      if (lanes <= 4) {
        os << "float";
      } else if (lanes <= 8) {
        // Emit CUDA code to access fp32 vector elements for 4 < lanes <= 8.
        //
        // float8 is stored as ulonglong4
        //
        // f8.v1 is emitted as *(float2*)(&(ul4.x)).x
        // f8.v2 is emitted as *(float2*)(&(ul4.x)).y
        //
        ICHECK_EQ(lanes % 2, 0)
            << "only support even lane for float type with lanes > 4";
        os << "ulonglong" << lanes / 2;
      } else {
        fail = true;
      }
      break;
    case 64:
      os << "double";
      break;
    default:
      fail = true;
      break;
392
    }
393
394
395
396
    if (!fail && (t.is_scalar() || t.bits() == 16))
      return;
    if (!fail && (lanes > 4 && lanes <= 8 && t.bits() == 32))
      return;
397
398
399
400
401
    if (!fail && (lanes >= 2 && lanes <= 4)) {
      os << lanes;
      return;
    }
  } else if (t.is_bfloat16()) {
402
    enable_bf16_ = true;
403
404
405
406
407
    if (t.is_scalar()) {
      os << "bfloat16_t";
    } else if (lanes <= 8) {
      ICHECK_EQ(lanes % 2, 0) << "only support even lane for half type";
      os << "uint" << lanes / 2;
408
409
410
411
    } else if (lanes <= 16) {
      ICHECK_EQ(lanes % 4, 0) << "only support (mod 4 = 0) lanes for half type "
                                 "of more than 8 lanes";
      os << "ulonglong" << lanes / 4;
412
413
414
    } else {
      fail = true;
    }
415
416
    if (!fail)
      return;
417
  } else if (t.is_float8()) {
418
419
420
    enable_fp8_ = true;
    os << GetFP8Type(t);
    return;
421
422
423
424
425
426
427
428
429
430
431
432
  } else if (t.is_float6()) {
    enable_fp6_ = true;
    if (t.lanes() <= 4) {
      os << GetFP6Type(t);
    }
    return;
  } else if (t.is_float4()) {
    enable_fp4_ = true;
    if (t.lanes() <= 4) {
      os << GetFP4Type(t);
    }
    return;
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
  } else if (t == DataType::Bool()) {
    os << "bool";
    return;
  } else if (t.is_vector_bool()) {
    // CUDA does not support bool vectors.
    // Use ushort vectors to represent instead.
    int n = t.lanes();
    if (n <= 4) {
      os << "ushort" << n;
      return;
    }
  } else if (t.is_uint() || t.is_int()) {
    if (t.is_uint()) {
      os << "u";
    }
    switch (t.bits()) {
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
    case 1: {
      if (t.is_scalar()) {
        os << "int";
        return;
      } else if (t.lanes() == 8) {
        os << "int8_t";
        return;
      } else if (t.lanes() == 16) {
        os << "int16_t";
        return;
      } else if (t.lanes() == 32) {
        os << "int";
        return;
      } else {
        LOG(FATAL) << "Cannot convert type " << t << " to CUDA type!";
464
      }
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
    }
    case 4: {
      if (t.is_scalar()) {
        os << "int";
        return;
      } else if (t.lanes() == 4) {
        os << "int16_t";
        return;
      } else if (t.lanes() == 8) {
        // directly 8 4-bit int in integer.
        os << "int";
        return;
      } else if (t.lanes() == 16) {
        os << "int2";
        return;
      } else if (t.lanes() == 32) {
        os << "int4";
        return;
      } else if (t.lanes() == 64) {
        os << "int8";
        return;
      } else {
        LOG(FATAL) << "Cannot convert type " << t << " to CUDA type!";
488
      }
489
490
491
492
    }
    case 8: {
      if (t.lanes() == 4) {
        // directly 4 8 bit int in integer.
493
        enable_int8_ = true;
494
495
496
497
498
499
500

        // We use int for int8x4 instead of char4 because using char4 is
        // likely to produce extra instructions to pack four int8 elements
        // into 32-bit data.
        os << "int";
        return;
      } else if (t.lanes() == 8) {
501
        enable_int8_ = true;
502
503
504
        os << "int2";
        return;
      } else if (t.lanes() == 16) {
505
        enable_int8_ = true;
506
507
        os << "int4";
        return;
508
509
510
511
      } else if (t.lanes() == 32) {
        enable_int8_ = true;
        os << "longlong4";
        return;
512
513
      } else if (!t.is_uint() && t.is_scalar()) {
        os << "signed char";
514
        break;
515
516
      } else {
        os << "char";
517
518
        break;
      }
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
    }
    case 16: {
      if (t.is_scalar()) {
        os << "short";
      } else if (t.lanes() <= 4) {
        os << "short" << lanes;
      } else if (t.lanes() <= 8) {
        // Emit CUDA code to access int16 vector elements.
        //
        // short4 is stored as int2
        //
        // s4.x is emitted as *(short2*)(&(i2.x)).x
        // s4.y is emitted as *(short2*)(&(i2.x)).y
        // s4.z is emitted as *(short2*)(&(i2.y)).x
        // s4.w is emitted as *(short2*)(&(i2.y)).y
        //
        ICHECK_EQ(t.lanes() % 2, 0)
            << "only support even lane for shorT type with lanes > 4";
        os << "int" << t.lanes() / 2;
      } else {
        fail = true;
      }
      if (!fail) {
542
543
        return;
      }
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
      break;
    }
    case 32: {
      if (t.is_scalar()) {
        os << "int";
      } else if (t.lanes() <= 4) {
        os << "int" << t.lanes();
      } else if (t.lanes() <= 8) {
        // Emit CUDA code to access int32 vector elements for 4 < lanes <= 8.
        //
        // int8 is stored as longlong4
        //
        // i8.v1 is emitted as *(int2*)(&(l4.x)).x
        // i8.v2 is emitted as *(int2*)(&(l4.x)).y
        //
        ICHECK_EQ(lanes % 2, 0)
            << "only support even lane for int32 type with lanes > 4";
        os << "longlong" << lanes / 2;
      } else {
563
        fail = true;
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
      }
      if (!fail) {
        return;
      }
      break;
    }
    case 64: {
      if (t.is_scalar()) {
        os << "int64_t";
      } else if (t.lanes() == 2) {
        os << "longlong2";
      } else if (t.lanes() == 3) {
        os << "longlong3";
      } else if (t.lanes() == 4) {
        os << "longlong4";
579
580
      } else {
        fail = true;
581
      }
582
583
584
585
      if (!fail) {
        return;
      }
      break;
586
587
588
589
    }
    default:
      fail = true;
      break;
590
591
592
593
594
595
596
597
598
599
600
601
    }
    if (!fail && lanes == 1) {
      return;
    }
    if (!fail && (lanes >= 2 && lanes <= 4)) {
      os << lanes;
      return;
    }
  }
  LOG(FATAL) << "Cannot convert type " << t << " to CUDA type";
}

602
603
604
void CodeGenTileLangCUDA::PrintVecBinaryOp(const std::string &op, DataType t,
                                           PrimExpr lhs, PrimExpr rhs,
                                           std::ostream &os) { // NOLINT(*)
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
  // Declare the result.
  std::string sret = name_supply_->FreshName("_");
  this->PrintIndent();
  this->PrintType(t, stream);
  stream << ' ' << sret << ";\n";
  int ssa_scope = BeginScope();
  {
    // Unpack into individual ops.
    std::string vlhs = SSAGetID(PrintExpr(lhs), lhs.dtype());
    std::string vrhs = SSAGetID(PrintExpr(rhs), rhs.dtype());

    for (int i = 0, lanes = t.lanes(); i < lanes; ++i) {
      std::ostringstream value_temp;
      if (isalpha(op[0])) {
        value_temp << op << "(";
        PrintVecElemLoad(vlhs, lhs.dtype(), i, value_temp);
        value_temp << ", ";
        PrintVecElemLoad(vrhs, rhs.dtype(), i, value_temp);
        value_temp << ")";
      } else {
        value_temp << "(";
        PrintVecElemLoad(vlhs, lhs.dtype(), i, value_temp);
        value_temp << op;
        PrintVecElemLoad(vrhs, rhs.dtype(), i, value_temp);
        value_temp << ")";
      }
      PrintVecElemStore(sret, t, i, value_temp.str());
    }
  }
  EndScope(ssa_scope);
  os << sret;
}

638
639
640
void CodeGenTileLangCUDA::PrintVecElemLoad(const std::string &vec, DataType t,
                                           int i,
                                           std::ostream &os) { // NOLINT(*)
641
642
643
644
645
646
  if (t.is_scalar()) {
    os << vec;
    return;
  }

  static const char access[] = {'x', 'y', 'z', 'w'};
647
  ICHECK(i >= 0 && i < 256 / t.bits());
648
649
650
651
  if (t.bits() == 8 && (t.is_int() || t.is_uint())) {
    std::string type_name = t.is_int() ? "char" : "unsigned char";
    if (t.lanes() == 2 || t.lanes() == 3) {
      os << vec << "." << access[i % t.lanes()];
652
    } else if (t.lanes() <= 16) {
653
654
      std::string ac = t.lanes() == 4 ? vec : (vec + "." + access[i / 4]);
      os << "((" << type_name << ")(" << ac << " >> " << i % 4 * 8 << "))";
655
656
657
658
    } else {
      ICHECK(t.lanes() == 32);
      std::string ac = vec + "." + access[i / 8];
      os << "((" << type_name << ")(" << ac << " >> " << i % 8 * 8 << "))";
659
660
    }
  } else if (t.is_float16()) {
661
662
663
664
665
666
667
    if (t.lanes() <= 8) {
      os << "((half2*)(&(" << vec << "." << access[i / 2] << ")))->"
         << access[i % 2];
    } else {
      os << "(((half2*)(&(" << vec << "." << access[i / 4] << "))) + "
         << (i / 2 % 2) << ")->" << access[i % 2];
    }
668
  } else if (t.is_bfloat16()) {
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
    if (t.lanes() <= 8) {
      os << "((nv_bfloat162*)(&(" << vec << "." << access[i / 2] << ")))->"
         << access[i % 2];
    } else {
      os << "(((nv_bfloat162*)(&(" << vec << "." << access[i / 4] << "))) + "
         << (i / 2 % 2) << ")->" << access[i % 2];
    }
  } else if (t.is_float8()) {
    os << vec;
    // fp8_e5_32_t
    if (t.lanes() >= 32)
      os << "." << access[i / 16];
    // fp8_e5_16_t
    if (t.lanes() >= 16)
      os << "." << access[(i % 16) / 8];
    // fp8_e5_8_t
    if (t.lanes() >= 8)
      os << "." << access[(i % 8) / 4];
    // fp8_e5_4_t or fp8_e5_2_t
    os << "." << access[i % 4];
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
  } else if (t.lanes() > 4 && t.lanes() <= 8) {
    std::string type_name;
    if (t.bits() == 16) {
      if (t.is_int()) {
        type_name = "short";
      } else if (t.is_uint()) {
        type_name = "ushort";
      }
    } else if (t.bits() == 32) {
      if (t.is_int()) {
        type_name = "int";
      } else if (t.is_uint()) {
        type_name = "uint";
      } else if (t.is_float()) {
        type_name = "float";
      }
    }
    ICHECK(!type_name.empty());
707
708
    os << "((" << type_name << "2*)(&(" << vec << "." << access[i / 2]
       << ")))->" << access[i % 2];
709
710
711
712
713
  } else {
    os << vec << "." << access[i];
  }
}

714
715
void CodeGenTileLangCUDA::PrintVecElemStore(const std::string &vec, DataType t,
                                            int i, const std::string &value) {
716
717
  this->PrintIndent();
  static const char access[] = {'x', 'y', 'z', 'w'};
718
  ICHECK(i >= 0 && i < 256 / t.bits());
719
720
  if (t.bits() == 8 && (t.is_int() || t.is_uint())) {
    if (t.lanes() == 2 || t.lanes() == 3) {
721
722
      stream << vec << '.' << access[i % t.lanes()] << "="
             << "(" << value << ");\n";
723
    } else if (t.lanes() <= 16) {
724
725
726
727
728
729
730
      std::string ac = t.lanes() == 4 ? vec : (vec + "." + access[i / 4]);
      stream << ac << "=";
      // Do not read the first undef lane.
      if (i != 0) {
        stream << ac << " & ~(0x000000ff << " << i % 4 * 8 << ") |";
      }
      stream << "(" << value << " << " << i % 4 * 8 << ");\n";
731
732
733
734
735
736
737
738
739
    } else {
      ICHECK(t.lanes() == 32);
      std::string ac = vec + "." + access[i / 8];
      stream << ac << "=";
      // Do not read the first undef lane.
      if (i != 0) {
        stream << ac << " & ~(0x000000ff << " << i % 8 * 8 << ") |";
      }
      stream << "(" << value << " << " << i % 8 * 8 << ");\n";
740
741
    }
  } else if (t.is_float16()) {
742
743
744
745
746
747
748
749
    if (t.lanes() <= 8) {
      stream << "((half2*)(&(" << vec << "." << access[i / 2] << ")))->"
             << access[i % 2] << " = " << value << ";\n";
    } else {
      stream << "(((half2*)(&(" << vec << "." << access[i / 4] << "))) + "
             << (i / 2 % 2) << ")->" << access[i % 2] << " = " << value
             << ";\n";
    }
750
  } else if (t.is_bfloat16()) {
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
    if (t.lanes() <= 8) {
      stream << "((nv_bfloat162*)(&(" << vec << "." << access[i / 2] << ")))->"
             << access[i % 2] << " = " << value << ";\n";
    } else {
      stream << "(((nv_bfloat162*)(&(" << vec << "." << access[i / 4]
             << "))) + " << (i / 2 % 2) << ")->" << access[i % 2] << " = "
             << value << ";\n";
    }
  } else if (t.is_float8()) {
    stream << vec;
    // fp8_e5_32_t
    if (t.lanes() >= 32)
      stream << "." << access[i / 16];
    // fp8_e5_16_t
    if (t.lanes() >= 16)
      stream << "." << access[(i % 16) / 8];
    // fp8_e5_8_t
    if (t.lanes() >= 8)
      stream << "." << access[(i % 8) / 4];
    // fp8_e5_4_t or fp8_e5_2_t
    stream << "." << access[i % 4] << " = " << value << ";\n";
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
  } else if (t.lanes() > 4 && t.lanes() <= 8) {
    std::string type_name;
    if (t.bits() == 16) {
      if (t.is_int()) {
        type_name = "short";
      } else if (t.is_uint()) {
        type_name = "ushort";
      }
    } else if (t.bits() == 32) {
      if (t.is_int()) {
        type_name = "int";
      } else if (t.is_uint()) {
        type_name = "uint";
      } else if (t.is_float()) {
        type_name = "float";
      }
    }
    ICHECK(!type_name.empty());
790
791
    stream << "((" << type_name << "2*)(&(" << vec << "." << access[i / 2]
           << ")))->" << access[i % 2] << " = " << value << ";\n";
792
793
794
795
796
  } else {
    stream << vec << "." << access[i] << " = " << value << ";\n";
  }
}

797
void CodeGenTileLangCUDA::PrintStorageSync(const CallNode *op) {
798
799
  auto args = op->args;
  const std::string &sync = args[0].as<StringImmNode>()->value;
800
801
802
803
  if (sync == "warp") {
    // DO nothing.
  } else if (sync == "shared" || sync == "shared.dyn") {
    this->PrintIndent();
804
805
806
807
808
809
810
811
812
813
814
815
816
817
    if (args.size() == 1) {
      this->stream << "__syncthreads();\n";
    } else if (args.size() == 2) {
      auto barrier_id = args[1].as<IntImmNode>()->value;
      this->stream << "tl::__sync_thread_partial<" << barrier_id << ">();\n";
    } else if (args.size() == 3) {
      auto barrier_id = args[1].as<IntImmNode>()->value;
      auto thread_count = args[2].as<IntImmNode>()->value;
      this->stream << "tl::__sync_thread_partial<" << barrier_id << ", "
                   << thread_count << ">();\n";
    } else {
      LOG(FATAL) << "Invalid number of arguments for storage sync: "
                 << args.size();
    }
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
  } else if (sync == "global") {
    if (!need_global_barrier_) {
      need_global_barrier_ = true;
    }
    // global synchronizer
    std::string is_load = PrintExpr(op->args[1]);
    std::string num_blocks = PrintExpr(op->args[2]);
    this->PrintIndent();
    // In theory only threadfence is needed
    // but we observed problems with only threadfence
    this->stream << "__threadfence_system();\n";
    this->PrintIndent();
    this->stream << "if (" << is_load << ") {\n";
    int wb = this->BeginScope();
    this->PrintIndent();
    this->stream << "atomicAdd(&" << vid_global_barrier_state_ << ", 1);\n";
    this->PrintIndent();
    std::string ptr = name_supply_->FreshName("pf");
    this->stream << "volatile unsigned* " << ptr << " = &"
                 << vid_global_barrier_state_ << ";\n";
    this->PrintIndent();
    this->stream << vid_global_barrier_expect_ << " += " << num_blocks << ";\n";
    this->PrintIndent();
    this->stream << "while (" << ptr << "[0] < " << vid_global_barrier_expect_
                 << ");\n";
    this->EndScope(wb);
    this->PrintIndent();
    this->stream << "}\n";
    this->PrintIndent();
    this->stream << "__syncthreads();\n";
848
849
850
  }
}

851
852
853
854
855
void CodeGenTileLangCUDA::PrintStorageScope(const std::string &scope,
                                            std::ostream &os) { // NOLINT(*)
  ICHECK_NE(scope, "global")
      << "Cannot allocate global memory when targeting CUDA. You must pass "
         "all global arrays as input instead";
856
  if (scope == "shared" || scope == "shared.barrier") {
857
858
859
860
861
862
    os << "__shared__ ";
  } else if (scope == "shared.dyn") {
    os << "extern __shared__ __align__(1024) ";
  }
}

863
864
865
866
std::string CodeGenTileLangCUDA::CastFromTo(std::string value, DataType from,
                                            DataType target) {
  if (from == target)
    return value;
867
868
869
870
  std::ostringstream os;
  os << "((";
  this->PrintType(target, os);
  os << ")";
871
872
  if (from.is_float16() && (target.is_int() || target.is_uint()) &&
      target.bits() == 8) {
873
874
875
876
877
878
    os << "(";
    if (target.is_uint()) {
      os << "u";
    }
    os << "int)";
  }
879
880
881
  if ((from.is_float16() || from.is_bfloat16()) && target.is_float8()) {
    os << "(float)";
  }
882
883
884
885
  os << value << ")";
  return os.str();
}

886
void CodeGenTileLangCUDA::VisitExpr_(const CastNode *op, std::ostream &os) {
887
888
889
890
891
  DataType from_ty = op->value.dtype();
  DataType target_ty = op->dtype;
  ICHECK_EQ(target_ty.lanes(), from_ty.lanes());

  // Emit simple C-style type conversion.
892
893
  if (from_ty.is_scalar())
    return CodeGenC::VisitExpr_(op, os);
894
895
896
897
898
899
900

  // We could emit make_float4 like calls, but the emitted code looks
  // too compact to read. Emit this as vectorized unary ops.
  std::string sret = name_supply_->FreshName("_");
  this->PrintIndent();
  this->PrintType(target_ty, stream);
  stream << ' ' << sret << ";\n";
901
902
903
904
905
906
  std::string src = SSAGetID(PrintExpr(op->value), from_ty);

  // Handle bfloat16 special cases with supported ops
  bool used_bf16_op = false;
  if (from_ty.is_bfloat16() || target_ty.is_bfloat16()) {
    std::ostringstream func_name;
907
    if (from_ty.is_bfloat16()) {
908
      func_name << "bf16";
909
    } else if (from_ty.is_float()) {
910
      func_name << "float";
911
912
    }
    if (from_ty.lanes() > 1) {
913
      func_name << from_ty.lanes();
914
    }
915
    func_name << "2";
916
    if (target_ty.is_bfloat16()) {
917
      func_name << "bf16";
918
    } else if (target_ty.is_float()) {
919
      func_name << "float";
920
    } else if (target_ty == DataType::Int(16)) {
921
      func_name << "int16";
922
923
    }
    if (target_ty.lanes() > 1) {
924
      func_name << target_ty.lanes();
925
    }
926
927
928
929
930
931
932

    auto fname = func_name.str();
    if (bf16_supported_ops_.count(fname)) {
      used_bf16_op = true;
      stream << "#ifdef ENABLE_BF16\n";
      PrintIndent();
      stream << "reinterpret_cast<";
933
      if (target_ty.is_bfloat16()) {
934
        stream << "__nv_bfloat16";
935
      } else {
936
        PrintType(target_ty.element_of(), stream);
937
938
      }
      if (target_ty.lanes() > 1) {
939
        stream << target_ty.lanes();
940
      }
941
942
      stream << " &>(" << sret << ") = fastertransformer::" << fname
             << "(reinterpret_cast<";
943
      if (from_ty.is_bfloat16()) {
944
        stream << "__nv_bfloat16";
945
      } else {
946
        PrintType(from_ty.element_of(), stream);
947
948
      }
      if (from_ty.lanes() > 1) {
949
        stream << from_ty.lanes();
950
      }
951
952
      stream << " const &>(" << src << "));\n";
      stream << "#else\n";
953
954
    }
  }
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969

  // Fallback: elementwise cast
  for (int i = 0, lanes = from_ty.lanes(); i < lanes; ++i) {
    std::ostringstream val;
    val << "(";
    PrintType(target_ty.element_of(), val);
    val << ")(";
    PrintVecElemLoad(src, from_ty, i, val);
    val << ")";
    PrintVecElemStore(sret, target_ty, i, val.str());
  }

  if (used_bf16_op) {
    stream << "#endif\n";
  }
970
971
972
  os << sret;
}

973
974
975
976
void CodeGenTileLangCUDA::PrintCallExtern(Type ret_type, String global_symbol,
                                          const Array<PrimExpr> &args,
                                          bool skip_first_arg,
                                          std::ostream &os) { // NOLINT(*)
977
  DataType ret_dtype = GetRuntimeDataType(ret_type);
978
  if (ret_dtype.is_fixed_length_vector()) {
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
    //
    // Emit an unsupported vector call
    //
    // v = intrin_f((float4*)A[0], (float4*)B[0])
    //
    // as
    //
    // float4 __ret;
    // {
    //   float4 __arg0 = ((float4*)A)[0];
    //   float4 __arg1 = ((float4*)B)[0];
    //   __ret.x = intrin_f(__arg0.x, __arg1.x);
    //   __ret.y = intrin_f(__arg0.y, __arg1.y);
    //   __ret.z = intrin_f(__arg0.z, __arg1.z);
    //   __ret.w = intrin_f(__arg0.w, __arg1.w);
    // }
    // v = __ret;
    //
    // Declare the result vector.
    std::string sret = name_supply_->FreshName("_");
    this->PrintIndent();
    this->PrintType(ret_dtype, stream);
    stream << ' ' << sret << ";\n";
    {
      // Load arguments.
      std::vector<std::string> sargs;
      size_t arg_begin = static_cast<size_t>(skip_first_arg);
      for (size_t i = arg_begin; i < args.size(); ++i) {
        std::string val = SSAGetID(PrintExpr(args[i]), args[i].dtype());
        sargs.push_back(std::move(val));
      }

      // Emit a scalar call for each lane.
      for (int i = 0; i < ret_dtype.lanes(); ++i) {
        std::ostringstream scall;
        scall << global_symbol << "(";
        for (size_t j = 0; j < sargs.size(); ++j) {
1016
1017
          if (j > 0)
            scall << ", ";
1018
1019
1020
1021
1022
1023
1024
1025
          PrintVecElemLoad(sargs[j], args[arg_begin + j].dtype(), i, scall);
        }
        scall << ")";
        PrintVecElemStore(sret, ret_dtype, i, scall.str());
      }
    }
    os << sret;
  } else {
1026
1027
    CodeGenC::PrintCallExtern(ret_type, global_symbol, args, skip_first_arg,
                              os);
1028
1029
1030
1031
  }
}

// Print a reference expression to a buffer.
1032
1033
1034
1035
std::string CodeGenTileLangCUDA::GetBufferRef(DataType t,
                                              const BufferNode *buffer,
                                              PrimExpr index) {
  const VarNode *buffer_var = buffer->data.get();
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
  std::ostringstream os;
  std::string vid = GetVarID(buffer_var);
  std::string scope;
  if (alloc_storage_scope_.count(buffer_var)) {
    scope = alloc_storage_scope_.at(buffer_var);
  }
  // bool is_vol = IsVolatile(buffer_var);
  // always false for tl cutlass backend.
  bool is_vol = false;

  auto ptr_cast = [this, is_vol, scope](DataType pointed_to) {
    std::ostringstream ptr_os;
    ptr_os << "(";
    if (is_vol) {
      ptr_os << "volatile ";
    }
    if (!scope.empty() && IsScopePartOfType()) {
      PrintStorageScope(scope, ptr_os);
    }
    PrintType(pointed_to, ptr_os);
    ptr_os << "*)";
    return ptr_os.str();
  };

  DataType buffer_element_dtype = buffer->dtype;

  std::string buffer_str = vid;
  if (!HandleTypeMatch(buffer_var, buffer_element_dtype) || is_vol) {
    std::stringstream temp;
    temp << "(" << ptr_cast(buffer_element_dtype) << vid << ")";
    buffer_str = temp.str();
  }
1068
1069
1070
  if (scope.empty()) {
    scope = GetPtrStorageScope(buffer->data);
  }
1071
  if (scope == "local.var" || scope == "local.descriptor") {
1072
1073
1074
    os << vid;
    return os.str();
  }
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
  std::string index_str = PrintExpr(index);
  if (t.bits() == 4 || (t.bits() == 1 && t.is_int())) {
    // This is a special case, because CodegenCUDA::PrintType()
    // returns "int" for bool and for 4-bit integers. In most cases,
    // we divide by the number of lanes to determine the index.
    // However, the backing type for scalar int4 and scalar bool is
    // int32.  Therefore, we need to divide by the ratio of their
    // sizes in that case.
    int div_factor = (t.lanes() == 1) ? (32 / t.bits()) : t.lanes();

    os << "*("
       << "(" << ptr_cast(t) << vid << ")"
       << " + " << index_str << " / " << div_factor << ")";
  } else if (t == buffer_element_dtype) {
    os << buffer_str << "[" << index_str << "]";
  } else {
    os << "*" << ptr_cast(t) << "(" << buffer_str << " + " << index_str << ")";
  }

  return os.str();
}

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
std::string CodeGenTileLangCUDA::GetVecLoad(DataType t,
                                            const BufferNode *buffer,
                                            PrimExpr base) {
  const VarNode *buffer_var = buffer->data.get();
  std::string scope;
  if (alloc_storage_scope_.count(buffer_var)) {
    scope = alloc_storage_scope_.at(buffer_var);
  }
  if (scope.empty()) {
    scope = GetPtrStorageScope(buffer->data);
  }

  if (scope != "global" || t.bits() * t.lanes() <= 128) {
    return this->CodeGenC::GetVecLoad(t, buffer, base);
  }
  ICHECK_EQ(t.bits() * t.lanes(), 256)
      << "Unsupported vector load size: " << t.bits() * t.lanes();
  auto buffer_ref = this->GetBufferRef(t, buffer, base);
  std::ostringstream os;
  os << "tl::ld_global_256(&(" << buffer_ref << "))";
  return os.str();
}

void CodeGenTileLangCUDA::PrintVecStore(const BufferNode *buffer, DataType t,
                                        PrimExpr base,
                                        const std::string &value) {
  const VarNode *buffer_var = buffer->data.get();
  std::string scope;
  if (alloc_storage_scope_.count(buffer_var)) {
    scope = alloc_storage_scope_.at(buffer_var);
  }
  if (scope.empty()) {
    scope = GetPtrStorageScope(buffer->data);
  }

  if (scope != "global" || t.bits() * t.lanes() <= 128) {
    this->CodeGenC::PrintVecStore(buffer, t, base, value);
    return;
  }
  ICHECK_EQ(t.bits() * t.lanes(), 256)
      << "Unsupported vector load size: " << t.bits() * t.lanes();
  auto buffer_ref = this->GetBufferRef(t, buffer, base);
  this->PrintIndent();
  this->stream << "tl::st_global_256(&(" << buffer_ref << "), " << value
               << ");\n";
}

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
/**
 * @brief Emit CUDA/TensorLib-specific code for a call expression.
 *
 * This visitor handles CallNode intrinsics and builtins that require emitting
 * CUDA/TL-specific code (inline PTX/ASM sequences, TensorLanguage runtime
 * calls, WMMA/TMA helpers, barriers, cp.async primitives, index-map based
 * stores, reinterpret/packing helpers, and various mma/ldmatrix patterns). The
 * function writes the generated code to the provided output stream and falls
 * back to the C codegen for unrecognized calls.
 *
 * The method recognizes and emits code for (non-exhaustive): cp.async and its
 * commit/wait variants, tma_load/store and im2col variants, ptX
 * ldmatrix/stmatrix helpers, mbarrier APIs, cooperative grid sync, WMMA/legacy
 * MMA intrinsics (fill/load/store/mma/bmma/ptx_mma/ptx_mma_sp), low-level PTX
 * asm helpers (ldg32, cp_async bulk/init/arrive/wait barriers), reinterpret
 * paths for special small-float encodings (e.g., float4 e2m1fn), tl::tl_gemm
 * and related external calls, and other TL runtime calls.
 *
 * Side effects:
 * - Emits to `os` and the internal codegen output stream.
 * - May set internal feature flags (e.g., need_cooperative_groups_,
 * need_mma_h_, need_cast_smem_ptr_to_int_, enable_sparse_gemm_).
 * - May open/close SSA scopes and mutate internal variable mappings.
 * - May call LOG(FATAL) / CHECK / ICHECK on invalid or unsupported argument
 *   patterns.
 *
 * @param op The call node to generate code for; the function inspects op->op
 *           and op->args to determine the appropriate emission.
 * @param os  Output stream to receive expression-level output when the caller
 *            expects an expression result (some paths write directly to the
 *            member stream instead).
 */
1176
void CodeGenTileLangCUDA::VisitExpr_(const CallNode *op, std::ostream &os) {
1177
1178
  auto print_extern_call_stmt = [&](std::string name, size_t start = 0,
                                    size_t end = 0) {
1179
1180
1181
1182
    // Cache context into a private ss, otherwise the let node may generate
    // within the function call arguments.
    std::ostringstream ss;

1183
1184
    for (size_t i = start; i < op->args.size() - end; i++) {
      if (i > start)
1185
1186
        ss << ", ";
      ss << this->PrintExpr(op->args[i]);
1187
    }
1188
1189
1190
1191

    this->PrintIndent();
    this->stream << name << "(";
    this->stream << ss.str();
1192
1193
    this->stream << ");\n";
  };
1194
1195
1196
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
  auto print_mbarrier_obj = [&](PrimExpr barrier_id) {
    std::ostringstream ss;
    if (barrier_id.as<IntImmNode>()) {
      // incase the barrier_id is an integer, we need to print the barrier_id as
      // an integer
      ss << mbarrier_name_ << "[" << barrier_id << "]";
    } else {
      // otherwise may be a T.get_mbarrier() call or BufferLoad Node
      // we need to print the barrier_id as a string
      ss << this->PrintExpr(barrier_id);
    }
    return ss.str();
  };
1207
1208
1209
1210
1211
1212
  if (op->op.same_as(builtin::ptx_cp_async())) {
    std::string dst = this->PrintExpr(op->args[0]);
    std::string dst_offset = this->PrintExpr(op->args[1]);
    std::string src = this->PrintExpr(op->args[2]);
    std::string src_offset = this->PrintExpr(op->args[3]);
    std::string size = this->PrintExpr(op->args[4]);
1213
1214
    // use size of argument list to indicate whether or not to use predicated
    // cp.async
1215
1216
    if (op->args.size() == 5) {
      this->PrintIndent();
1217
1218
      this->stream << "tl::cp_async_gs<" << size << ">(" << dst << "+"
                   << dst_offset << ", " << src << "+" << src_offset << ");\n";
1219
1220
1221
    } else {
      std::string condition = this->PrintExpr(op->args[5]);
      this->PrintIndent();
1222
1223
1224
      this->stream << "tl::cp_async_gs_conditional<" << size << ">(" << dst
                   << "+" << dst_offset << ", " << src << "+" << src_offset
                   << ", " << condition << ");\n";
1225
1226
1227
1228
1229
1230
1231
1232
1233
1234
    }
  } else if (op->op.same_as(builtin::ptx_commit_group())) {
    print_extern_call_stmt("tl::cp_async_commit");
  } else if (op->op.same_as(builtin::ptx_wait_group())) {
    int n = Downcast<IntImm>(op->args[0])->value;
    std::string func_name = "tl::cp_async_wait<" + std::to_string(n) + ">";
    print_extern_call_stmt(func_name, 1);
  } else if (op->op.same_as(builtin::create_barriers())) {
    this->PrintIndent();
    int barrier_count = Downcast<IntImm>(op->args[0])->value;
1235
1236
    auto mbarrier_storage_name = mbarrier_name_ + "_mem";
    this->stream << "__shared__ uint64_t " << mbarrier_storage_name << "["
1237
                 << barrier_count << "];\n";
1238
1239
1240
    this->PrintIndent();
    this->stream << "auto " << mbarrier_name_ << " = reinterpret_cast<"
                 << mbarrier_dtype_ << "*>(" << mbarrier_storage_name << ");\n";
1241
  } else if (op->op.same_as(tl::get_mbarrier())) {
1242
    ICHECK_EQ(op->args.size(), 1);
1243
    std::string barrier_id = this->PrintExpr(op->args[0]);
1244
    os << mbarrier_name_ + "[" + barrier_id + "]";
1245
  } else if (op->op.same_as(builtin::ptx_arrive_barrier())) {
1246
1247
1248
1249
1250
1251
1252
1253
1254
1255
1256
1257
1258
1259
1260
    if (op->args.size() == 1) {
      this->PrintIndent();
      auto mbarrier_obj = print_mbarrier_obj(op->args[0]);
      this->stream << mbarrier_obj << ".arrive();\n";
    } else if (op->args.size() == 3) {
      this->PrintIndent();
      auto mbarrier_obj = print_mbarrier_obj(op->args[0]);
      auto cta_id = this->PrintExpr(op->args[1]);
      auto pred = this->PrintExpr(op->args[2]);
      this->stream << mbarrier_obj << ".arrive(" << cta_id << ", " << pred
                   << ");\n";
    } else {
      LOG(FATAL) << "Invalid parameter  for tl::arrive_barrier "
                 << op->args.size();
    }
1261
  } else if (op->op.same_as(builtin::ptx_init_barrier_thread_count())) {
1262
1263
1264
1265
1266
    ICHECK_EQ(op->args.size(), 2);
    this->PrintIndent();
    auto mbarrier_obj = print_mbarrier_obj(op->args[0]);
    auto arrive_count = this->PrintExpr(op->args[1]);
    this->stream << mbarrier_obj << ".init(" << arrive_count << ");\n";
1267
  } else if (op->op.same_as(builtin::ptx_arrive_barrier_expect_tx())) {
1268
1269
1270
1271
1272
1273
1274
1275
1276
1277
1278
1279
1280
1281
1282
1283
1284
1285
1286
    if (op->args.size() == 2) {
      this->PrintIndent();
      auto mbarrier_obj = print_mbarrier_obj(op->args[0]);
      auto transaction_bytes = this->PrintExpr(op->args[1]);
      this->stream << mbarrier_obj << ".arrive_and_expect_tx("
                   << transaction_bytes << ");\n";
    } else if (op->args.size() == 4) {
      this->PrintIndent();
      auto mbarrier_obj = print_mbarrier_obj(op->args[0]);
      auto transaction_bytes = this->PrintExpr(op->args[1]);
      auto cta_id = this->PrintExpr(op->args[2]);
      auto pred = this->PrintExpr(op->args[3]);
      this->stream << mbarrier_obj << ".arrive_and_expect_tx("
                   << transaction_bytes << ", " << cta_id << ", " << pred
                   << ");\n";
    } else {
      LOG(FATAL) << "Invalid parameter  for tl::arrive_barrier_expect_tx "
                 << op->args.size();
    }
1287
1288
  } else if (op->op.same_as(builtin::ptx_cp_async_barrier())) {
    print_extern_call_stmt("tl::mbarrier_cp_async_arrive");
1289
1290
  } else if (op->op.same_as(tl::ptx_fence_barrier_init())) {
    print_extern_call_stmt("tl::fence_barrier_init");
1291
1292
  } else if (op->op.same_as(tl::ptx_cp_async_barrier_noinc())) {
    print_extern_call_stmt("tl::mbarrier_cp_async_arrive_noinc");
1293
  } else if (op->op.same_as(tl::mbarrier_expect_tx())) {
1294
1295
1296
1297
1298
1299
    ICHECK_EQ(op->args.size(), 2);
    this->PrintIndent();
    auto mbarrier_obj = print_mbarrier_obj(op->args[0]);
    auto transaction_bytes = this->PrintExpr(op->args[1]);
    this->stream << mbarrier_obj << ".expect_transaction(" << transaction_bytes
                 << ");\n";
1300
  } else if (op->op.same_as(tl::mbarrier_wait_parity())) {
1301
1302
1303
1304
1305
    ICHECK_EQ(op->args.size(), 2);
    this->PrintIndent();
    auto mbarrier_obj = print_mbarrier_obj(op->args[0]);
    auto phase = this->PrintExpr(op->args[1]);
    this->stream << mbarrier_obj << ".wait(" << phase << ");\n";
1306
1307
1308
1309
  } else if (op->op.same_as(tl::ptx_init_tensor_memory())) {
    print_extern_call_stmt("tl::tmem_allocate");
  } else if (op->op.same_as(tl::ptx_deallocate_tensor_memory())) {
    print_extern_call_stmt("tl::tmem_deallocate");
1310
1311
  } else if (op->op.same_as(tl::no_set_max_nreg())) {
    return;
1312
  } else if (op->op.same_as(tl::tma_load())) {
1313
    std::ostringstream ss;
1314
    ICHECK_GE(op->args.size(), 2);
1315
1316
1317
    auto eviction_policy =
        this->eviction_policy_names_
            [op->args[op->args.size() - 1].as<IntImmNode>()->value];
1318
1319
1320
1321
1322
1323
    // Simplify the code by using the default eviction policy
    if (eviction_policy != "EVICT_NORMAL") {
      ss << "tl::tma_load<tl::CacheHintSm90::" << eviction_policy << ">(";
    } else {
      ss << "tl::tma_load(";
    }
1324
    auto desc = op->args[0];
1325
    ss << this->PrintExpr(desc) << ", ";
1326
    ss << print_mbarrier_obj(op->args[1]) << ", ";
1327
    for (size_t i = 2; i < op->args.size() - 1; i++) {
1328
      if (i > 2)
1329
1330
        ss << ", ";
      ss << this->PrintExpr(op->args[i]);
1331
    }
1332
1333
1334
    ss << ");\n";
    this->PrintIndent();
    this->stream << ss.str();
1335
  } else if (op->op.same_as(tl::tma_load_im2col())) {
1336
    std::stringstream ss;
1337
1338
1339
1340
1341
1342
1343
1344
    auto eviction_policy =
        this->eviction_policy_names_
            [op->args[op->args.size() - 1].as<IntImmNode>()->value];
    if (eviction_policy != "EVICT_NORMAL") {
      ss << "tl::tma_load_im2col<tl::CacheHintSm90::" << eviction_policy << ">";
    } else {
      ss << "tl::tma_load_im2col";
    }
1345
    print_extern_call_stmt(ss.str(), 0, 1);
1346
  } else if (op->op.same_as(tl::tma_store())) {
1347
    std::stringstream ss;
1348
1349
1350
1351
1352
1353
1354
1355
    auto eviction_policy =
        this->eviction_policy_names_
            [op->args[op->args.size() - 1].as<IntImmNode>()->value];
    if (eviction_policy != "EVICT_NORMAL") {
      ss << "tl::tma_store<tl::CacheHintSm90::" << eviction_policy << ">";
    } else {
      ss << "tl::tma_store";
    }
1356
    print_extern_call_stmt(ss.str(), 0, 1);
1357
  } else if (op->op.same_as(tl::ptx_ldmatrix())) {
1358
1359
1360
    int trans = Downcast<IntImm>(op->args[0])->value;
    int num = Downcast<IntImm>(op->args[1])->value;
    std::string func_name = "tl::ptx_ldmatrix_x" + std::to_string(num);
1361
1362
    if (trans == 1)
      func_name += "_trans";
1363
    print_extern_call_stmt(func_name, 2);
1364
  } else if (op->op.same_as(tl::ptx_stmatrix())) {
1365
1366
1367
    int trans = Downcast<IntImm>(op->args[0])->value;
    int num = Downcast<IntImm>(op->args[1])->value;
    std::string func_name = "tl::ptx_stmatrix_x" + std::to_string(num);
1368
1369
    if (trans == 1)
      func_name += "_trans";
1370
    print_extern_call_stmt(func_name, 2);
1371
  } else if (op->op.same_as(tl::fence_proxy_async())) {
1372
    print_extern_call_stmt("tl::fence_proxy_async");
1373
  } else if (op->op.same_as(tl::tma_store_arrive())) {
1374
    print_extern_call_stmt("tl::tma_store_arrive");
1375
  } else if (op->op.same_as(tl::tma_store_wait())) {
1376
    print_extern_call_stmt("tl::tma_store_wait<0>");
1377
  } else if (op->op.same_as(tl::set_max_nreg())) {
1378
1379
1380
    this->PrintIndent();
    int nreg = Downcast<IntImm>(op->args[0])->value;
    int is_inc = Downcast<IntImm>(op->args[1])->value;
1381
1382
    std::string func_name =
        is_inc ? "tl::warpgroup_reg_alloc" : "tl::warpgroup_reg_dealloc";
1383
    this->stream << func_name << "<" << std::to_string(nreg) << ">();\n";
1384
  } else if (op->op.same_as(tl::wait_wgmma())) {
1385
1386
1387
    this->PrintIndent();
    int num_mma = Downcast<IntImm>(op->args[0])->value;
    this->stream << "tl::wait_wgmma<" << std::to_string(num_mma) << ">();\n";
1388
  } else if (op->op.same_as(tl::pack_b16())) {
1389
1390
    os << "__pack_half2(" << this->PrintExpr(op->args[0]) << ", "
       << this->PrintExpr(op->args[1]) << ")";
1391
1392
1393
  } else if (op->op.same_as(tl::sync_grid())) {
    this->need_cooperative_groups_ = true;
    this->PrintIndent();
1394
1395
1396
1397
    this->stream << "cooperative_groups::grid_group grid = "
                    "cooperative_groups::this_grid();\n";
    this->PrintIndent();
    this->stream << "grid.sync();\n";
1398
1399
1400
  } else if (op->op.same_as(tl::loop_break())) {
    this->PrintIndent();
    this->stream << "break;\n";
1401
1402
1403
1404
1405
1406
1407
1408
1409
1410
1411
1412
1413
1414
1415
1416
1417
1418
1419
1420
1421
1422
1423
1424
1425
1426
1427
1428
1429
1430
1431
1432
1433
  } else if (op->op.same_as(builtin::tvm_fill_fragment())) {
    need_mma_h_ = true;
    ICHECK_EQ(op->args.size(), 6U);
    os << "nvcuda::wmma::fill_fragment(";
    this->PrintExpr(op->args[0], os);
    os << "[";
    this->PrintExpr(op->args[4], os);
    os << "], ";
    this->PrintExpr(op->args[5], os);
    os << ")";
  } else if (op->op.same_as(builtin::tvm_load_matrix_sync())) {
    need_mma_h_ = true;
    ICHECK_EQ(op->args.size(), 8U);
    os << "nvcuda::wmma::load_matrix_sync(";
    this->PrintExpr(op->args[0], os);
    os << "[";
    this->PrintExpr(op->args[4], os);
    os << "], ";
    this->PrintExpr(op->args[5], os);
    os << ", ";
    this->PrintExpr(op->args[6], os);
    os << ")";
  } else if (op->op.same_as(builtin::tvm_store_matrix_sync())) {
    need_mma_h_ = true;
    ICHECK_EQ(op->args.size(), 8U);
    os << "nvcuda::wmma::store_matrix_sync(";
    this->PrintExpr(op->args[5], os);
    os << ", ";
    this->PrintExpr(op->args[0], os);
    os << "[";
    this->PrintExpr(op->args[4], os);
    os << "], ";
    this->PrintExpr(op->args[6], os);
1434
    if (const StringImmNode *str = op->args[7].as<StringImmNode>()) {
1435
1436
1437
1438
1439
1440
1441
1442
1443
1444
1445
1446
1447
1448
1449
1450
1451
1452
1453
1454
1455
1456
1457
1458
1459
1460
1461
1462
1463
1464
1465
1466
1467
1468
1469
1470
1471
1472
1473
1474
1475
1476
1477
1478
1479
1480
1481
1482
1483
1484
1485
1486
1487
1488
      os << ", nvcuda::wmma::mem_" << str->value;
    } else {
      LOG(FATAL) << "Invalid parameters";
    }
    os << ")";
  } else if (op->op.same_as(builtin::tvm_mma_sync())) {
    need_mma_h_ = true;
    ICHECK_EQ(op->args.size(), 8U);
    os << "nvcuda::wmma::mma_sync(";
    for (int i = 0; i < 4; ++i) {
      this->PrintExpr(op->args[i * 2], os);
      os << "[";
      this->PrintExpr(op->args[i * 2 + 1], os);
      os << "]" << ((i < 3) ? ", " : ")");
    }
  } else if (op->op.same_as(builtin::tvm_bmma_sync())) {
    need_mma_h_ = true;
    ICHECK_EQ(op->args.size(), 8U);
    os << "nvcuda::wmma::bmma_sync(";
    for (int i = 0; i < 4; ++i) {
      this->PrintExpr(op->args[i * 2], os);
      os << "[";
      this->PrintExpr(op->args[i * 2 + 1], os);
      os << "]" << ((i < 3) ? ", " : ")");
    }
  } else if (op->op.same_as(builtin::ptx_mma())) {
    // arg 0: shape: mXnXkX
    // arg 1: A layout: row/col
    // arg 2: B layout: row/col
    // arg 3: A precision: fp16, fp64, ...
    // arg 4: B precision: fp16, fp64, ...
    // arg 5: C precision: fp32, fp64, ...
    // arg 6: A multiplicand
    // arg 7: A multiplicand index
    // arg 8: B multiplicand
    // arg 9: B multiplicand index
    // arg 10: C accumulator
    // arg 11: C accumulator index
    // arg 12: saturate
    // arg 13: (optional) 1-bit operator (xor or and)
    ICHECK(op->args.size() == 13U || op->args.size() == 14U);
    std::string shape = Downcast<StringImm>(op->args[0])->value;
    std::string A_layout = Downcast<StringImm>(op->args[1])->value;
    std::string B_layout = Downcast<StringImm>(op->args[2])->value;
    std::string A_dtype = Downcast<StringImm>(op->args[3])->value;
    std::string B_dtype = Downcast<StringImm>(op->args[4])->value;
    std::string C_dtype = Downcast<StringImm>(op->args[5])->value;
    std::string a_ref = this->PrintExpr(op->args[6]);
    std::string a_bias = this->PrintExpr(op->args[7]);
    std::string b_ref = this->PrintExpr(op->args[8]);
    std::string b_bias = this->PrintExpr(op->args[9]);
    std::string c_ref = this->PrintExpr(op->args[10]);
    std::string c_bias = this->PrintExpr(op->args[11]);
    bool saturate = Downcast<Bool>(op->args[12])->value;
1489
1490
1491
1492
1493
    std::string bit_op =
        op->args.size() > 13 ? Downcast<StringImm>(op->args[13])->value : "";
    std::string asm_code = PrintMMAAssembly(
        shape, A_layout, B_layout, A_dtype, B_dtype, C_dtype, a_ref, a_bias,
        b_ref, b_bias, c_ref, c_bias, "", "", "", bit_op, false, saturate);
1494
    this->PrintIndent();
1495
1496
1497
1498
1499
1500
1501
1502
1503
1504
1505
1506
1507
1508
1509
1510
1511
1512
1513
1514
1515
1516
1517
1518
1519
1520
1521
1522
1523
1524
1525
1526
1527
1528
1529
    this->stream << asm_code;
  } else if (op->op.same_as(builtin::ptx_mma_sp())) {
    // arg 0: shape: mXnXkX
    // arg 1: A layout: row/col
    // arg 2: B layout: row/col
    // arg 3: A precision: fp16, fp32, ...
    // arg 4: B precision: fp16, fp32, ...
    // arg 5: C precision: fp16, fp32, ...
    // arg 6: A multiplicand pointer
    // arg 7: A multiplicand index
    // arg 8: B multiplicand pointer
    // arg 9: B multiplicand index
    // arg 10: C accumulator pointer
    // arg 11: C accumulator index
    // arg 12: metadata
    // arg 13: metadata index
    // arg 14: sparse_selector
    // arg 15: saturate
    ICHECK_EQ(op->args.size(), 16U);
    std::string shape = Downcast<StringImm>(op->args[0])->value;
    std::string A_layout = Downcast<StringImm>(op->args[1])->value;
    std::string B_layout = Downcast<StringImm>(op->args[2])->value;
    std::string A_dtype = Downcast<StringImm>(op->args[3])->value;
    std::string B_dtype = Downcast<StringImm>(op->args[4])->value;
    std::string C_dtype = Downcast<StringImm>(op->args[5])->value;
    std::string a_ref = this->PrintExpr(op->args[6]);
    std::string a_offset = this->PrintExpr(op->args[7]);
    std::string b_ref = this->PrintExpr(op->args[8]);
    std::string b_offset = this->PrintExpr(op->args[9]);
    std::string c_ref = this->PrintExpr(op->args[10]);
    std::string c_offset = this->PrintExpr(op->args[11]);
    std::string metadata = this->PrintExpr(op->args[12]);
    std::string metadata_offset = this->PrintExpr(op->args[13]);
    std::string sparse_selector = this->PrintExpr(op->args[14]);
    bool saturate = Downcast<Bool>(op->args[15])->value;
1530
    this->PrintIndent();
1531
    std::string asm_code = PrintMMAAssembly(
1532
1533
1534
        shape, A_layout, B_layout, A_dtype, B_dtype, C_dtype, a_ref, a_offset,
        b_ref, b_offset, c_ref, c_offset, metadata, metadata_offset,
        sparse_selector, "", true, saturate);
1535
    this->stream << asm_code;
1536
1537
1538
1539
1540
1541
1542
1543
1544
1545
1546
1547
1548
1549
1550
1551
1552
1553
1554
1555
1556
1557
1558
1559
1560
1561
1562
1563
1564
1565
1566
1567
1568
1569
1570
1571
1572
1573
1574
1575
1576
1577
1578
1579
1580
1581
1582
1583
1584
1585
1586
1587
1588
1589
1590
1591
1592
1593
1594
1595
1596
1597
1598
1599
1600
1601
1602
1603
1604
1605
1606
1607
1608
1609
1610
1611
1612
1613
1614
1615
1616
1617
1618
1619
1620
1621
1622
1623
1624
1625
1626
1627
1628
1629
1630
1631
1632
1633
1634
  } else if (op->op.same_as(tl::ptx_wgmma_ss())) {
    // arg 0: dtype
    // arg 1: shape
    // arg 2: A_layout
    // arg 3: B_layout
    // arg 4: A_dtype
    // arg 5: B_dtype
    // arg 6: C_dtype
    // arg 7: multiplicand_a
    // arg 8: multiplicand_b
    // arg 9: accumulator
    // arg 10: saturate
    ICHECK_EQ(op->args.size(), 15U) << "ptx_wgmma_ss args is " << op->args;
    std::string shape = Downcast<StringImm>(op->args[0])->value;
    bool a_is_k_major = Downcast<Bool>(op->args[1])->value;
    bool b_is_k_major = Downcast<Bool>(op->args[2])->value;
    std::string A_dtype = Downcast<StringImm>(op->args[3])->value;
    std::string B_dtype = Downcast<StringImm>(op->args[4])->value;
    std::string C_dtype = Downcast<StringImm>(op->args[5])->value;
    std::string a_desc = this->PrintExpr(op->args[6]);
    std::string A_offset = this->PrintExpr(op->args[7]);
    std::string b_desc = this->PrintExpr(op->args[8]);
    std::string B_offset = this->PrintExpr(op->args[9]);
    std::string c_ref = this->PrintExpr(op->args[10]);
    std::string c_offset = this->PrintExpr(op->args[11]);
    bool scale_out = Downcast<Bool>(op->args[12])->value;
    bool scale_in_a = Downcast<Bool>(op->args[13])->value;
    bool scale_in_b = Downcast<Bool>(op->args[14])->value;

    const bool a_is_shared = true;
    this->PrintIndent();
    std::string asm_code = PrintWGMMAAssembly(
        shape, a_is_k_major, b_is_k_major, A_dtype, B_dtype, C_dtype, a_desc,
        A_offset, b_desc, B_offset, c_ref, c_offset, scale_out, scale_in_a,
        scale_in_b, a_is_shared, "", "", "", false);
    auto [m, n, k] = tl::codegen::ptx::ParseMMAShape(shape);
    std::string wgmma_asm_code =
        "tl::wgmma_ss<(AType), (BType), (CType), (M), (N), (K), (tnspA), "
        "(tnspB), (scaleA), (scaleB)>(uint64_t((desc_a) + (A_offset)), "
        "uint64_t((desc_b) + (B_offset)), ((uint32_t*)((C))), (scale_out));\n";
    // replace patterns
    tl::codegen::Replacer replacer;
    replacer.register_rule("(AType)",
                           tl::codegen::ptx::DTypeEnumToString(A_dtype));
    replacer.register_rule("(BType)",
                           tl::codegen::ptx::DTypeEnumToString(B_dtype));
    replacer.register_rule("(CType)",
                           tl::codegen::ptx::DTypeEnumToString(C_dtype));
    replacer.register_rule("(M)", std::to_string(m));
    replacer.register_rule("(N)", std::to_string(n));
    replacer.register_rule("(K)", std::to_string(k));
    replacer.register_rule("(tnspA)", a_is_k_major ? "false" : "true");
    replacer.register_rule("(tnspB)", b_is_k_major ? "false" : "true");
    replacer.register_rule("(scaleA)", scale_in_a ? "1" : "-1");
    replacer.register_rule("(scaleB)", scale_in_b ? "1" : "-1");
    replacer.register_rule("(desc_a)", a_desc);
    replacer.register_rule("(A_offset)", A_offset);
    replacer.register_rule("(desc_b)", b_desc);
    replacer.register_rule("(B_offset)", B_offset);
    replacer.register_rule("(C)", c_ref + " + " + c_offset);
    replacer.register_rule("(scale_out)", scale_out ? "true" : "false");
    wgmma_asm_code = replacer.rewrite(wgmma_asm_code);
    this->stream << wgmma_asm_code;
  } else if (op->op.same_as(tl::ptx_wgmma_rs())) {
    // arg 0: dtype
    // arg 1: shape
    // arg 2: A_layout
    // arg 3: B_layout
    // arg 4: A_dtype
    // arg 5: B_dtype
    // arg 6: C_dtype
    // arg 7: multiplicand_a
    // arg 8: multiplicand_b
    // arg 9: accumulator
    // arg 10: saturate
    ICHECK_EQ(op->args.size(), 15U) << "ptx_wgmma_rs args is " << op->args;
    std::string shape = Downcast<StringImm>(op->args[0])->value;
    bool A_layout = Downcast<Bool>(op->args[1])->value;
    bool B_layout = Downcast<Bool>(op->args[2])->value;
    std::string A_dtype = Downcast<StringImm>(op->args[3])->value;
    std::string B_dtype = Downcast<StringImm>(op->args[4])->value;
    std::string C_dtype = Downcast<StringImm>(op->args[5])->value;
    std::string a_ref = this->PrintExpr(op->args[6]);
    std::string A_offset = this->PrintExpr(op->args[7]);
    std::string b_desc = this->PrintExpr(op->args[8]);
    std::string B_offset = this->PrintExpr(op->args[9]);
    std::string c_ref = this->PrintExpr(op->args[10]);
    std::string c_offset = this->PrintExpr(op->args[11]);
    bool scale_out = Downcast<Bool>(op->args[12])->value;
    bool scale_in_a = Downcast<Bool>(op->args[13])->value;
    bool scale_in_b = Downcast<Bool>(op->args[14])->value;

    const bool a_is_shared = false;
    this->PrintIndent();
    std::string asm_code = PrintWGMMAAssembly(
        shape, A_layout, B_layout, A_dtype, B_dtype, C_dtype, a_ref, A_offset,
        b_desc, B_offset, c_ref, c_offset, scale_out, scale_in_a, scale_in_b,
        a_is_shared, "", "", "", false);
    this->stream << asm_code;
1635
1636
1637
1638
1639
1640
1641
  } else if (op->op.same_as(builtin::ptx_ldmatrix())) {
    // arg 0: whether the matrix is loaded in column major format or not.
    // arg 1: number of matrices to load.
    // arg 2: The data type in the matrix, .b16 is the only accepted data type.
    // arg 3: pointer to local buffer.
    // arg 4: The offset of the element to store in the local buffer.
    // arg 5: pointer to the shared memory buffer to load.
1642
1643
    // arg 6: The offset of the start element of the row to load in shared
    // memory.
1644
1645
1646
1647
1648
1649
1650
1651
    ICHECK_EQ(op->args.size(), 7U);
    bool trans = Downcast<Bool>(op->args[0])->value;
    int num = Downcast<Integer>(op->args[1])->value;
    std::string type = Downcast<StringImm>(op->args[2])->value;
    std::string local_ptr = this->PrintExpr(op->args[3]);
    std::string local_elem_offset = this->PrintExpr(op->args[4]);
    std::string smem_ptr = this->PrintExpr(op->args[5]);
    if (trans && op->dtype.bits() == 8) {
1652
1653
      // Since ldmatrix assumes that a matrix element is 16 bit, it cannot
      // properly transpose an int8 matrix.
1654
1655
1656
1657
      std::string smem_stride = this->PrintExpr(op->args[6]);
      ICHECK(num == 4);
      os << "for (int i = 0; i < 16; ++i) {\n";
      os << local_ptr << "[" + local_elem_offset + " + i] = " << smem_ptr
1658
1659
1660
1661
         << "[(i % 8) / 4 * " + smem_stride +
                " * 16 + (threadIdx.x % 4) * 4 * " + smem_stride +
                "+ (i % 4) * " + smem_stride +
                " + threadIdx.x / 4 +  (i / 8) * 8];\n";
1662
1663
1664
      os << "}\n";
    } else {
      std::string smem_elem_offset = this->PrintExpr(op->args[6]);
1665
1666
1667
1668
1669
1670
      std::string func_name = "tl::ptx_ldmatrix_x" + std::to_string(num);
      if (trans == 1)
        func_name += "_trans";
      this->PrintIndent();
      this->stream << func_name << "(" << smem_ptr << " + " << smem_elem_offset
                   << ", " << local_ptr << " + " << local_elem_offset << ");\n";
1671
1672
1673
1674
1675
1676
1677
1678
1679
    }
  } else if (op->op.same_as(builtin::mma_store())) {
    int m = Downcast<Integer>(op->args[0])->value;
    int n = Downcast<Integer>(op->args[1])->value;
    std::string dst = this->PrintExpr(op->args[2]);
    std::string src = this->PrintExpr(op->args[3]);
    std::string src_offset = this->PrintExpr(op->args[4]);
    PrimExpr stride = op->args[5];

1680
1681
    ICHECK(m == 16 && n == 16)
        << "Only m == 16 && n == 16 case supported for now";
1682

1683
1684
1685
1686
1687
    // Each thread in a warp holds a certain number of elements of an MMA
    // output. For example, if we compute a 16x16 tile using MMA, each thread
    // holds 8 elements in its registers. So conceptually, a warp memory is
    // organized as a 32x8 block. A map from a 16x16 tile to a 32x8 block of
    // memory is specified by the index map below.
1688

1689
1690
    // To store the 32x8 output back to a 16x16 tile in shared or global memory,
    // we invert this map to determine the output location for each 8 element.
1691

1692
1693
    const auto index_map_func = ffi::Function::GetGlobal(
        "tir.index_map.shared_16x16_to_mma_32x8_layout");
1694

1695
1696
1697
    IndexMap index_map;
    if (!index_map_func) {
      Var i, j;
1698

1699
      // The index map is defined as follows:
1700
1701
1702
1703
1704
      index_map = IndexMap(
          {i, j}, {4 * FloorMod(i, 8) + FloorDiv(FloorMod(j, 8), 2),
                   4 * FloorDiv(j, 8) + FloorDiv(i, 8) * 2 + FloorMod(j, 2)});
    } else {
      index_map = IndexMap::FromFunc(2, *index_map_func);
1705
1706
1707
1708
1709
1710
1711
    }

    arith::Analyzer analyzer;
    auto inverse_index_map =
        index_map.Inverse({Range(0, m), Range(0, n)}, &analyzer);
    auto indices_16x16 = inverse_index_map->final_indices;

1712
1713
1714
    // "//" and "%" in the index map are translated to FloorDiv/Mod, but the
    // plain Div/Mod are fine. FloorDiv/Mod are supposed to be lowered before
    // they reach codegen, so manually replace them to the plain ones here.
1715
    class LowerFloorDivMod : public ExprMutator {
1716
1717
    public:
      PrimExpr VisitExpr_(const FloorDivNode *op) {
1718
1719
        return tir::Div(this->VisitExpr(op->a), this->VisitExpr(op->b));
      }
1720
      PrimExpr VisitExpr_(const FloorModNode *op) {
1721
1722
1723
1724
        return tir::Mod(this->VisitExpr(op->a), this->VisitExpr(op->b));
      }
    };

1725
1726
    auto dst_ind =
        LowerFloorDivMod()(indices_16x16[0] * stride + indices_16x16[1]);
1727
1728
1729
1730
1731
1732
1733
1734
1735

    var_idmap_[inverse_index_map->initial_indices[0].get()] = "threadIdx.x";
    var_idmap_[inverse_index_map->initial_indices[1].get()] = "local_id";
    if (op->dtype.bits() == 16) {
      os << "for (int local_id = 0; local_id < 8; local_id+=2) {\n";
      os << "*((uint *)&" << dst << "[" + this->PrintExpr(dst_ind) + "])"
         << " = "
         << "*((uint *)&" << src << "[" << src_offset << " + local_id]);\n";
      os << "}\n";
1736
    } else {
1737
1738
1739
1740
1741
1742
1743
1744
1745
1746
1747
1748
1749
1750
1751
1752
1753
1754
1755
1756
1757
      os << "for (int local_id = 0; local_id < 8; ++local_id) {\n";
      os << dst << "[" + this->PrintExpr(dst_ind) + "]"
         << " = " << src << "[" << src_offset << " + local_id];\n";
      os << "}\n";
    }

  } else if (op->op.same_as(builtin::mma_fill())) {
    std::string num_elem = this->PrintExpr(op->args[0]);
    std::string dst = this->PrintExpr(op->args[1]);
    std::string dst_offset = this->PrintExpr(op->args[2]);

    os << "for (int i = 0; i < " << num_elem << "; ++i) {\n";
    os << dst << "[" << dst_offset << " + i] = 0.0;";
    os << "}\n";
  } else if (op->op.same_as(builtin::ptx_cp_async())) {
    std::string dst = this->PrintExpr(op->args[0]);
    std::string dst_offset = this->PrintExpr(op->args[1]);
    std::string src = this->PrintExpr(op->args[2]);
    std::string src_offset = this->PrintExpr(op->args[3]);
    std::string size = this->PrintExpr(op->args[4]);
    need_cast_smem_ptr_to_int_ = true;
1758
1759
    // use size of argument list to indicate whether or not to use predicated
    // cp.async
1760
    if (op->args.size() == 5) {
1761
1762
      this->stream << PrintCpAsyncAssembly(dst, dst_offset, src, src_offset,
                                           size);
1763
    } else {
1764
1765
      this->stream << PrintPredicatedCpAsyncAssembly(
          dst, dst_offset, src, src_offset, size, this->PrintExpr(op->args[5]));
1766
1767
1768
1769
1770
1771
1772
1773
1774
1775
    }
  } else if (op->op.same_as(builtin::ptx_cp_async_bulk())) {
    need_cast_smem_ptr_to_int_ = true;
    std::string dst = this->PrintExpr(op->args[0]);
    std::string dst_offset = this->PrintExpr(op->args[1]);
    std::string src = this->PrintExpr(op->args[2]);
    std::string src_offset = this->PrintExpr(op->args[3]);
    std::string size = this->PrintExpr(op->args[4]);
    int barrier_id = Downcast<IntImm>(op->args[5])->value;
    CHECK(barrier_id < barrier_count_);
1776
1777
1778
1779
    std::string barrier =
        barrier_name_ + "[" + std::to_string(barrier_id) + "]";
    this->stream << PrintCpAsyncBulkAsm(dst, dst_offset, src, src_offset, size,
                                        barrier);
1780
1781
1782
1783
  } else if (op->op.same_as(builtin::ptx_commit_group())) {
    this->stream << "__asm__ __volatile__(\"cp.async.commit_group;\");\n\n";
  } else if (op->op.same_as(builtin::ptx_wait_group())) {
    int n = Downcast<IntImm>(op->args[0])->value;
1784
1785
    this->stream << "__asm__ __volatile__(\"cp.async.wait_group " << n
                 << ";\");\n\n";
1786
1787
1788
1789
  } else if (op->op.same_as(builtin::ptx_init_barrier_thread_count())) {
    need_cast_smem_ptr_to_int_ = true;
    int barrier_id = Downcast<IntImm>(op->args[0])->value;
    CHECK(barrier_id < barrier_count_);
1790
1791
    std::string barrier =
        barrier_name_ + "[" + std::to_string(barrier_id) + "]";
1792
1793
1794
1795
1796
1797
    std::string thread_count = this->PrintExpr(op->args[1]);
    this->stream << PrintInitBarrierThreadCountAsm(barrier, thread_count);
  } else if (op->op.same_as(builtin::ptx_arrive_barrier())) {
    need_cast_smem_ptr_to_int_ = true;
    int barrier_id = Downcast<IntImm>(op->args[0])->value;
    CHECK(barrier_id < barrier_count_);
1798
1799
    std::string barrier =
        barrier_name_ + "[" + std::to_string(barrier_id) + "]";
1800
1801
1802
1803
1804
    this->stream << PrintArriveBarrierAsm(barrier);
  } else if (op->op.same_as(builtin::ptx_arrive_barrier_expect_tx())) {
    need_cast_smem_ptr_to_int_ = true;
    int barrier_id = Downcast<IntImm>(op->args[0])->value;
    CHECK(barrier_id < barrier_count_);
1805
1806
    std::string barrier =
        barrier_name_ + "[" + std::to_string(barrier_id) + "]";
1807
1808
1809
1810
1811
1812
    std::string byte_count = this->PrintExpr(op->args[1]);
    this->stream << PrintArriveBarrierExpectTxAsm(barrier, byte_count);
  } else if (op->op.same_as(builtin::ptx_wait_barrier())) {
    need_cast_smem_ptr_to_int_ = true;
    int barrier_id = Downcast<IntImm>(op->args[0])->value;
    CHECK(barrier_id < barrier_count_);
1813
1814
    std::string barrier =
        barrier_name_ + "[" + std::to_string(barrier_id) + "]";
1815
1816
1817
1818
1819
1820
1821
1822
1823
1824
1825
1826
1827
1828
1829
1830
1831
    this->stream << PrintWaitBarrierAsm(barrier);
  } else if (op->op.same_as(builtin::ptx_ldg32())) {
    /*
    asm volatile (
        "{.reg .pred p;\n"
        " setp.ne.b32 p, %2, 0;\n"
        // " @p ld.global.nc.f32 %0, [%1];}\n"t
        " @p ld.global.nc.L2::128B.f32 %0, [%1];}\n"
        : "=f"(reg)
        : "l"(addr), "r"((int)guard)
    );
    */

    // get local
    std::string reg = this->PrintExpr(op->args[0]);
    // get guard
    std::string guard = this->PrintExpr(op->args[1]);
1832
    const BufferLoadNode *addr_buffer = op->args[2].as<BufferLoadNode>();
1833
1834
1835
1836
1837
1838
1839
1840
1841
1842
1843
    std::string global_addr = this->PrintExpr(addr_buffer->indices[0]);
    std::string global_buffer = this->PrintExpr(addr_buffer->buffer->data);
    std::string local_addr = this->PrintExpr(op->args[3]);
    this->stream << "asm volatile (\n";
    this->stream << "\"{.reg .pred p;\\n\"\n";
    this->stream << "\" setp.ne.b32 p, %2, 0;\\n\"\n";
    this->stream << "\" @!p mov.b32 %0, 0;\\n\"\n";
    this->stream << "\" @p ld.global.nc.f32 %0, [%1];}\\n\"\n";
    // stream << "\" @p ld.global.nc.L2::128B.f32 %0, [%1];}\\n\"\n" ;
    stream << ": \"=f\"(" << reg << "[" << local_addr << "]"
           << ")\n";
1844
1845
    stream << ": \"l\"((void*)(" << global_buffer << "+" << global_addr
           << ")), \"r\"((int)" << guard << ")\n";
1846
    stream << ");\n";
1847
1848
1849
1850
1851
1852
1853
1854
1855
1856
1857
1858
1859
1860
1861
1862
1863
1864
1865
1866
1867
1868
1869
1870
1871
1872
1873
1874
1875
1876
1877
1878
1879
1880
1881
1882
1883
1884
1885
1886
1887
1888
1889
1890
1891
1892
1893
1894
1895
1896
1897
1898
1899
1900
1901
1902
1903
1904
1905
1906
1907
1908
1909
1910
1911
1912
1913
1914
1915
1916
1917
1918
1919
1920
1921
1922
1923
1924
1925
1926
1927
1928
1929
1930
1931
1932
1933
1934
1935
1936
1937
1938
1939
1940
  } else if (op->op.same_as(builtin::reinterpret())) {
    DataType tgt_dtype = op->dtype;
    DataType src_dtype = op->args[0]->dtype;
    PrimExpr value = op->args[0];

    // Handle float4_e2m1fn reinterpret
    if (!src_dtype.is_float4_e2m1fn() && !tgt_dtype.is_float4_e2m1fn()) {
      return CodeGenC::VisitExpr_(op, os);
    }
    if (src_dtype == tgt_dtype || tgt_dtype.lanes() * tgt_dtype.bits() ==
                                      src_dtype.lanes() * src_dtype.bits()) {
      return CodeGenC::VisitExpr_(op, os);
    }
    CHECK_EQ(tgt_dtype.lanes(), src_dtype.lanes())
        << "E2M1 float4 reinterpret expects source and target to have the same "
           "number of lanes. "
        << "Source dtype: " << src_dtype << ", Target dtype: " << tgt_dtype;
    CHECK_EQ(tgt_dtype.bytes(), src_dtype.bytes())
        << "E2M1 float4 reinterpret expects source and target to have the same "
           "number of bytes. "
        << "Source dtype: " << src_dtype << ", Target dtype: " << tgt_dtype;

    int lanes = tgt_dtype.lanes();

    int ssa_scope = BeginScope();
    if (lanes == 1) {
      // The case of lane=1 is same as the normal reinterpret,
      // except that we allow the src and dst dtype to have different number of
      // bits.
      std::string rhs = SSAGetID(PrintExpr(value), src_dtype);
      os << "(*(";
      this->PrintType(tgt_dtype, os);
      os << " *)(&(" << rhs << ")))";
    } else if (lanes == 2) {
      if (tgt_dtype.is_float4_e2m1fn()) {
        // We view the source as an uint16, and then extract bits of two fp4
        // numbers, and finally reinterpret the result as fp4x2.
        value =
            tir::Call(DataType::UInt(16), tir::builtin::reinterpret(), {value});
        tir::Var temp_var("temp_var", DataType::UInt(16));
        value =
            tir::Let(temp_var, value,
                     tir::Cast(DataType::UInt(8),
                               (temp_var & IntImm(DataType::UInt(16), 0xF)) |
                                   ((temp_var >> 4) &
                                    IntImm(DataType::UInt(16), 0xF0))));
      } else {
        value = tir::Cast(
            DataType::UInt(16),
            tir::Call(DataType::UInt(8), tir::builtin::reinterpret(), {value}));
        tir::Var temp_var("temp_var", DataType::UInt(16));
        value =
            tir::Let(temp_var, value,
                     (temp_var & IntImm(DataType::UInt(16), 0xF)) |
                         ((temp_var & IntImm(DataType::UInt(16), 0xF0)) << 4));
      }
      os << PrintExpr(
          tir::Call(tgt_dtype, tir::builtin::reinterpret(), {value}));
    } else if (lanes == 4) {
      if (tgt_dtype.is_float4_e2m1fn()) {
        // We view the source as an uint32, and then extract bits of four fp4
        // numbers, and finally reinterpret the result as fp4x4.
        value =
            tir::Call(DataType::UInt(32), tir::builtin::reinterpret(), {value});
        tir::Var temp_var("temp_var", DataType::UInt(32));
        value = tir::Let(
            temp_var, value,
            tir::Cast(
                DataType::UInt(16),
                (temp_var & IntImm(DataType::UInt(32), 0xF)) |
                    ((temp_var >> 4) & IntImm(DataType::UInt(32), 0xF0)) |
                    ((temp_var >> 8) & IntImm(DataType::UInt(32), 0xF00)) |
                    ((temp_var >> 12) & IntImm(DataType::UInt(32), 0xF000))));
      } else {
        value = tir::Cast(DataType::UInt(32),
                          tir::Call(DataType::UInt(16),
                                    tir::builtin::reinterpret(), {value}));
        tir::Var temp_var("temp_var", DataType::UInt(32));
        value = tir::Let(
            temp_var, value,
            (temp_var & IntImm(DataType::UInt(32), 0xF)) |
                ((temp_var & IntImm(DataType::UInt(32), 0xF0)) << 4) |
                ((temp_var & IntImm(DataType::UInt(32), 0xF00)) << 8) |
                ((temp_var & IntImm(DataType::UInt(32), 0xF000)) << 12));
      }
      os << PrintExpr(
          tir::Call(tgt_dtype, tir::builtin::reinterpret(), {value}));
    } else {
      LOG(FATAL) << "Invalid number of lanes for float4_e2m1fn reinterpret: "
                 << lanes;
    }
    EndScope(ssa_scope);
  } else if (op->op.same_as(builtin::thread_return())) {
    os << "return";
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
  } else if (op->op.same_as(tl::tl_gemm())) {
    ICHECK(op->args.size() == 4) << "tl_gemm expects 4 arguments <op_instance, "
                                    "A_ptr, B_ptr, C_ptr>, but got "
                                 << op->args.size();
    auto op_instance = Downcast<StringImm>(op->args[0]);
    this->PrintCallExtern(GetType(GetRef<PrimExpr>(op)), op_instance->value,
                          op->args, true, os);
  } else if (op->op.same_as(tl::tl_gemm_sp())) {
    ICHECK(op->args.size() == 5)
        << "tl_gemm_sp expects 5 arguments <op_instance, A_ptr, B_ptr, C_ptr, "
           "E_ptr>, but got "
        << op->args.size();
    auto op_instance = Downcast<StringImm>(op->args[0]);
    enable_sparse_gemm_ = true;
    this->PrintCallExtern(GetType(GetRef<PrimExpr>(op)), op_instance->value,
                          op->args, true, os);
1957
1958
  } else if (op->op.same_as(tl::tl_shuffle_elect())) {
    os << "tl::tl_shuffle_elect<" << PrintExpr(op->args[0]) << ">()";
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
  } else if (op->op.same_as(tl::initialize_descriptor())) {
    ICHECK(op->args.size() == 5)
        << "tl_initialize_descriptor expects 5 arguments but got "
        << op->args.size();
    auto descriptor = op->args[0];
    auto start_address = op->args[1];
    auto layout_type = op->args[2];
    auto leading_byte_offset = op->args[3];
    auto stride_byte_offset = op->args[4];
    os << "tl::initialize_descriptor<" << PrintExpr(layout_type) << ", "
       << PrintExpr(leading_byte_offset) << ", "
       << PrintExpr(stride_byte_offset) << ">(" << PrintExpr(descriptor) << ", "
       << PrintExpr(start_address) << ")";
  } else if (op->op.same_as(tl::increase_descriptor_offset())) {
    ICHECK(op->args.size() == 2)
        << "tl_increase_descriptor_offset expects 2 arguments but got "
        << op->args.size();
    auto descriptor = op->args[0];
    auto offset = op->args[1];
    os << "tl::increase_descriptor_offset<int>(" << PrintExpr(descriptor)
       << ", " << PrintExpr(offset) << ")";
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
  } else if (op->op.same_as(tl::__exp())) {
    CUDAFastMath math_func;
    std::string func_name = math_func(op->dtype, "exp");
    os << func_name << "(" << PrintExpr(op->args[0]) << ")";
  } else if (op->op.same_as(tl::__exp10())) {
    CUDAFastMath math_func;
    std::string func_name = math_func(op->dtype, "exp10");
    os << func_name << "(" << PrintExpr(op->args[0]) << ")";
  } else if (op->op.same_as(tl::__log())) {
    CUDAFastMath math_func;
    std::string func_name = math_func(op->dtype, "log");
    os << func_name << "(" << PrintExpr(op->args[0]) << ")";
  } else if (op->op.same_as(tl::__log2())) {
    CUDAFastMath math_func;
    std::string func_name = math_func(op->dtype, "log2");
    os << func_name << "(" << PrintExpr(op->args[0]) << ")";
  } else if (op->op.same_as(tl::__log10())) {
    CUDAFastMath math_func;
    std::string func_name = math_func(op->dtype, "log10");
    os << func_name << "(" << PrintExpr(op->args[0]) << ")";
  } else if (op->op.same_as(tl::__tan())) {
    CUDAFastMath math_func;
    std::string func_name = math_func(op->dtype, "tan");
    os << func_name << "(" << PrintExpr(op->args[0]) << ")";
  } else if (op->op.same_as(tl::__cos())) {
    CUDAFastMath math_func;
    std::string func_name = math_func(op->dtype, "cos");
    os << func_name << "(" << PrintExpr(op->args[0]) << ")";
  } else if (op->op.same_as(tl::__sin())) {
    CUDAFastMath math_func;
    std::string func_name = math_func(op->dtype, "sin");
    os << func_name << "(" << PrintExpr(op->args[0]) << ")";
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
2041
2042
2043
2044
2045
2046
2047
2048
2049
2050
2051
2052
2053
2054
2055
  } else if (op->op.same_as(tl::ieee_add())) {
    CUDAIEEEMath math_func;
    std::string rounding_mode = Downcast<StringImm>(op->args[2])->value;
    std::string func_name = math_func(op->dtype, "fadd", rounding_mode);
    os << func_name << "(" << PrintExpr(op->args[0]) << ", "
       << PrintExpr(op->args[1]) << ")";
  } else if (op->op.same_as(tl::ieee_sub())) {
    CUDAIEEEMath math_func;
    std::string rounding_mode = Downcast<StringImm>(op->args[2])->value;
    std::string func_name = math_func(op->dtype, "fsub", rounding_mode);
    os << func_name << "(" << PrintExpr(op->args[0]) << ", "
       << PrintExpr(op->args[1]) << ")";
  } else if (op->op.same_as(tl::ieee_mul())) {
    CUDAIEEEMath math_func;
    std::string rounding_mode = Downcast<StringImm>(op->args[2])->value;
    std::string func_name = math_func(op->dtype, "fmul", rounding_mode);
    os << func_name << "(" << PrintExpr(op->args[0]) << ", "
       << PrintExpr(op->args[1]) << ")";
  } else if (op->op.same_as(tl::ieee_fmaf())) {
    CUDAIEEEMath math_func;
    std::string rounding_mode = Downcast<StringImm>(op->args[3])->value;
    std::string func_name = math_func(op->dtype, "fmaf", rounding_mode);
    os << func_name << "(" << PrintExpr(op->args[0]) << ", "
       << PrintExpr(op->args[1]) << ", " << PrintExpr(op->args[2]) << ")";
  } else if (op->op.same_as(tl::ieee_frcp())) {
    CUDAIEEEMath math_func;
    std::string rounding_mode = Downcast<StringImm>(op->args[1])->value;
    std::string func_name = math_func(op->dtype, "frcp", rounding_mode);
    os << func_name << "(" << PrintExpr(op->args[0]) << ")";
  } else if (op->op.same_as(tl::ieee_fsqrt())) {
    CUDAIEEEMath math_func;
    std::string rounding_mode = Downcast<StringImm>(op->args[1])->value;
    std::string func_name = math_func(op->dtype, "fsqrt", rounding_mode);
    os << func_name << "(" << PrintExpr(op->args[0]) << ")";
  } else if (op->op.same_as(tl::ieee_frsqrt())) {
    CUDAIEEEMath math_func;
    std::string func_name = math_func(op->dtype, "frsqrt", "rn");
    os << func_name << "(" << PrintExpr(op->args[0]) << ")";
  } else if (op->op.same_as(tl::ieee_fdiv())) {
    CUDAIEEEMath math_func;
    std::string rounding_mode = Downcast<StringImm>(op->args[2])->value;
    std::string func_name = math_func(op->dtype, "fdiv", rounding_mode);
    os << func_name << "(" << PrintExpr(op->args[0]) << ", "
       << PrintExpr(op->args[1]) << ")";
2056
2057
2058
2059
2060
  } else {
    CodeGenC::VisitExpr_(op, os);
  }
}

2061
void CodeGenTileLangCUDA::VisitStmt_(const AttrStmtNode *op) {
2062
  if (op->attr_key == tir::attr::fragment_shape) {
2063
2064
    const VarNode *buffer = op->node.as<VarNode>();
    const StringImmNode *shape_str = op->value.as<StringImmNode>();
2065
2066
    fragment_shapes[buffer] = shape_str->value;
  } else if (op->attr_key == tir::attr::fragment_layout) {
2067
2068
    const VarNode *buffer = op->node.as<VarNode>();
    const StringImmNode *layout_str = op->value.as<StringImmNode>();
2069
2070
    fragment_layouts[buffer] = layout_str->value;
  } else if (op->attr_key == tir::attr::async_commit_queue_scope) {
2071
2072
2073
    const IntImmNode *queue_id = op->value.as<IntImmNode>();
    ICHECK(queue_id && queue_id->value == 0)
        << "For CUDA, the index of an async queue must be 0.";
2074
2075
2076
2077
2078
2079
2080
    this->VisitStmt(op->body);
    auto commit_group = Call(DataType::Void(), builtin::ptx_commit_group(), {});
    this->VisitExpr(commit_group, this->stream);
    return;
  } else if (op->attr_key == tir::attr::async_wait_queue_scope) {
    auto wait_attrs = GetAsyncWaitAttributes(op);
    auto queue_id = wait_attrs.first.as<IntImmNode>();
2081
2082
    ICHECK(queue_id && queue_id->value == 0)
        << "For CUDA, the index of an async queue must be 0.";
2083
    auto wait_cnt = wait_attrs.second;
2084
2085
    auto wait_group =
        Call(DataType::Void(), builtin::ptx_wait_group(), {wait_cnt});
2086
2087
2088
2089
2090
2091
2092
    this->VisitExpr(wait_group, this->stream);
    auto inner = op->body.as<AttrStmtNode>();
    ICHECK(inner);
    this->VisitStmt(inner->body);
    return;
  } else if (op->attr_key == "threadblock_swizzle_pattern") {
    this->PrintIndent();
2093
    const StringImmNode *pattern = op->value.as<StringImmNode>();
2094
2095
2096
2097
2098
2099
2100
2101
    ICHECK(pattern);
    this->stream << "const dim3 blockIdx = " << pattern->value << "();\n";
    this->VisitStmt(op->body);
    return;
  }
  CodeGenC::VisitStmt_(op);
}

2102
void CodeGenTileLangCUDA::VisitStmt_(const AllocateNode *op) {
2103
2104
2105
2106
  ICHECK(!is_zero(op->condition));
  std::string vid = AllocVarID(op->buffer_var.get());
  this->PrintIndent();
  std::string scope = GetPtrStorageScope(op->buffer_var);
2107
  const VarNode *buffer = op->buffer_var.as<VarNode>();
2108
2109
  if (scope.find("wmma.") == 0) {
    if (scope == "wmma.matrix_a" || scope == "wmma.matrix_b") {
2110
2111
2112
2113
      ICHECK(op->dtype == DataType::Float(16) ||
             op->dtype == DataType::Int(8) || op->dtype == DataType::UInt(8) ||
             op->dtype == DataType::Int(4) || op->dtype == DataType::UInt(4) ||
             op->dtype == DataType::Int(1) || op->dtype == DataType::BFloat(16))
2114
2115
2116
          << "Matrix_a and matrix_b only support half or char or unsigned char "
          << "or uint4 or int4 or int1 type for now";
    } else {
2117
2118
      ICHECK(op->dtype == DataType::Float(16) ||
             op->dtype == DataType::Float(32) || op->dtype == DataType::Int(32))
2119
2120
2121
          << "Accumulator only support half, float and int type for now";
    }
    PrintWmmaScope(scope, op->dtype, buffer, stream);
2122
2123
  } else if (scope == "local.descriptor") {
    stream << "tl::GmmaDescriptor " << vid << ";\n";
2124
  } else {
2125
2126
2127
2128
2129
2130
2131
2132
    PrintStorageScope(scope, stream);
    PrintType(op->dtype, stream);
  }

  if (scope == "shared.dyn") {
    stream << ' ' << vid << "[];\n";
  } else {
    size_t constant_size = op->ConstantAllocationSize();
2133
    ICHECK_GT(constant_size, 0)
2134
2135
        << "Can only handle constant size stack allocation for now, but get "
        << constant_size << " for " << op->buffer_var->name_hint;
2136
2137
2138
2139
2140
2141
2142
2143
    if (scope.find("wmma.") == 0) {
      constant_size = GetWmmaFragmentSize(scope, buffer, constant_size);
    }
    if ((op->dtype == DataType::Int(4) || op->dtype == DataType::UInt(4) ||
         op->dtype == DataType::Int(1)) &&
        scope == "shared") {
      constant_size = constant_size / (32 / op->dtype.bits());
    }
2144
2145
    if (scope == "shared") {
      stream << ' ' << vid << '[' << constant_size << "];\n";
2146
2147
2148
2149
2150
2151
    } else if (scope == "shared.barrier") {
      auto v_id_mem = vid + "_mem";
      stream << ' ' << v_id_mem << "[" << constant_size << "];\n";
      PrintIndent();
      stream << "auto " << vid << " = reinterpret_cast<" << mbarrier_dtype_
             << "*>(" << v_id_mem << ");\n";
2152
2153
2154
2155
2156
    } else if (scope == "local") {
      stream << ' ' << vid << '[' << constant_size << "];\n";
    } else if (scope == "local.var") {
      stream << ' ' << vid << " = " << PrintExpr(tir::make_const(op->dtype, 0))
             << ";\n";
2157
    } else if (scope != "local.descriptor") {
2158
2159
      ICHECK(false) << "Unsupported scope: " << scope;
    }
2160
2161
2162
2163
2164
2165
  }

  RegisterHandleType(op->buffer_var.get(), op->dtype);
  this->PrintStmt(op->body);
}

2166
2167
2168
2169
2170
2171
2172
2173
2174
2175
2176
2177
2178
2179
2180
2181
2182
2183
void CodeGenTileLangCUDA::VisitStmt_(const EvaluateNode *op) {
  if (is_const_int(op->value))
    return;
  const CallNode *call = op->value.as<CallNode>();
  if (call && call->op.same_as(builtin::tvm_global_barrier_kinit())) {
    PrintIndent();
    stream << "__shared__ unsigned " << vid_global_barrier_expect_ << ";\n";
    PrintIndent();
    stream << "if (threadIdx.x == 0) {\n";
    PrintIndent();
    stream << "  " << vid_global_barrier_expect_ << " = 0;\n";
    PrintIndent();
    stream << "}\n";
  } else {
    CodeGenC::VisitStmt_(op);
  }
}

2184
void CodeGenTileLangCUDA::VisitExpr_(const RampNode *op, std::ostream &os) {
2185
  int lanes = static_cast<int>(Downcast<IntImm>(op->lanes)->value);
2186
2187
  CHECK_LE(lanes, 4) << "Translate Ramp Node " << GetRef<Ramp>(op) << " with "
                     << lanes << " lanes is not allowed.";
2188
2189
2190
2191
2192
2193
  os << "(make_";
  PrintType(op->dtype, os);
  os << "(";
  for (int i = 0; i < lanes; i++) {
    os << "(" << PrintExpr(op->base) << ")"
       << "+(" << PrintExpr(op->stride) << "*" << i << ")";
2194
2195
    if (i != lanes - 1)
      os << ", ";
2196
2197
2198
2199
  }
  os << "))";
}

2200
2201
2202
2203
2204
2205
2206
2207
2208
2209
2210
2211
2212
void CodeGenTileLangCUDA::VisitExpr_(const BufferLoadNode *op,
                                     std::ostream &os) { // NOLINT(*)
  ICHECK_EQ(op->indices.size(), 1)
      << "Load from non-flat memory not supported.";
  ICHECK(!op->predicate.defined())
      << "Predicated buffer load is not supported.";

  DataType value_dtype = op->dtype;
  PrimExpr index = op->indices[0];
  Var buffer_var = op->buffer->data;
  DataType element_dtype = op->buffer->dtype;

  int lanes = op->dtype.lanes();
2213
  // declare type.
2214
2215
2216
2217
2218
2219
2220
2221
2222
2223
2224
2225
2226
2227
2228
2229
2230
2231
2232
2233
2234
2235
2236
2237
2238
2239
2240
2241
2242
2243
2244
2245
2246
2247
2248
2249
2250
2251
2252
2253
2254
2255
2256
2257
2258
2259
2260
2261
2262
2263
2264
2265
2266
2267
2268
2269
  if (value_dtype.lanes() == element_dtype.lanes()) {
    std::string ref = GetBufferRef(op->dtype, op->buffer.get(), index);
    HandleVolatileLoads(ref, op, os);
  } else {
    bool can_vector_load = false;
    arith::PVar<PrimExpr> base;
    if (arith::ramp(base, 1, op->dtype.lanes()).Match(index)) {
      const RampNode *ramp = index.as<RampNode>();
      ICHECK(ramp);
      can_vector_load = true;
      // arith::ModularSet me = arith::Analyzer().modular_set(ramp->base);
      // The condition: {k * coeff + base} divisible by the alignment for any k
      // if (me->coeff % op->dtype.lanes() == 0 && me->base % op->dtype.lanes()
      // == 0) {
      //   can_vector_load = true;
      // }
    }

    if (value_dtype.is_float4_e2m1fn() && lanes != 1) {
      // A float4_e2m1fn element has 4 bits, which is an incomplete byte.
      // So we cannot vector load it.
      can_vector_load = false;
    }
    if (can_vector_load) {
      std::string ref = GetVecLoad(op->dtype, op->buffer.get(), base.Eval());
      HandleVolatileLoads(ref, op, os);
    } else {
      std::ostringstream svalue_expr;
      std::string sindex = SSAGetID(PrintExpr(index), index.dtype());
      std::string vid = GetVarID(buffer_var.get());
      DataType elem_type = op->dtype.element_of();
      for (int i = 0; i < lanes; ++i) {
        std::ostringstream value_temp;
        if (!HandleTypeMatch(buffer_var.get(), elem_type)) {
          value_temp << "((";
          if (buffer_var.get()->dtype.is_handle()) {
            auto it = alloc_storage_scope_.find(buffer_var.get());
            if (it != alloc_storage_scope_.end()) {
              PrintStorageScope(it->second, value_temp);
            }
          }
          PrintType(elem_type, value_temp);
          value_temp << "*)" << vid << ')';
        } else {
          value_temp << vid;
        }
        value_temp << '[';
        PrintVecElemLoad(sindex, index.dtype(), i, value_temp);
        value_temp << ']';
        PrintVecElemLoadExpr(op->dtype, i, value_temp.str(), svalue_expr);
      }
      os << svalue_expr.str();
    }
  }
}

2270
2271
void CodeGenTileLangCUDA::VisitExpr_(const BroadcastNode *op,
                                     std::ostream &os) { // NOLINT(*)
2272
  int lanes = static_cast<int>(Downcast<IntImm>(op->lanes)->value);
2273
2274
2275
2276
2277
2278
2279
2280
2281
2282
2283
2284
2285
2286
2287
2288
2289
2290
2291
2292
2293
2294
2295
2296
2297
2298
2299
  if ((op->dtype.is_int() || op->dtype.is_uint()) && op->dtype.bits() == 8) {
    if (lanes == 4) {
      // make_int8x4
      const int64_t *p = as_const_int(op->value);
      ICHECK(p);
      int64_t v = *p & 0xFF;
      v = (v << 24) | (v << 16) | (v << 8) | v;
      if (op->dtype.is_uint()) {
        os << "(uint)" << v;
      } else {
        os << "(int)" << v;
      }
      return;
    } else if (lanes == 32) {
      // make_int8x32
      const int64_t *p = as_const_int(op->value);
      ICHECK(p);
      int64_t v = *p & 0xFF;
      v = (v << 24) | (v << 16) | (v << 8) | v;
      if (op->dtype.is_uint()) {
        os << "make_ulonglong4(" << v << ", " << v << ", " << v << ", " << v
           << ")";
      } else {
        os << "make_longlong4(" << v << ", " << v << ", " << v << ", " << v
           << ")";
      }
      return;
2300
2301
2302
2303
2304
2305
2306
2307
    }
  }

  if (op->dtype.is_float16()) {
    std::string v = PrintExpr(op->value);
    os << "make_";
    PrintType(op->dtype, os);
    os << '(';
2308
2309
2310
2311
2312
2313
2314
2315
2316
2317
2318
2319
2320
    if (lanes <= 8) {
      for (int i = 0; i < lanes / 2; ++i) {
        if (i != 0)
          os << ", ";
        os << "__pack_half2(" << v << ", " << v << ")";
      }
    } else {
      for (int i = 0; i < lanes / 4; ++i) {
        if (i != 0)
          os << ", ";
        os << "tl::pack_float16x4(" << v << ", " << v << ", " << v << ", " << v
           << ")";
      }
2321
2322
2323
2324
2325
2326
2327
2328
2329
2330
    }
    os << ')';
    return;
  }

  if (op->dtype.is_bfloat16()) {
    std::string v = PrintExpr(op->value);
    os << "make_";
    PrintType(op->dtype, os);
    os << '(';
2331
2332
2333
2334
2335
2336
2337
2338
2339
2340
2341
2342
2343
    if (lanes <= 8) {
      for (int i = 0; i < lanes / 2; ++i) {
        if (i != 0)
          os << ", ";
        os << "__pack_nv_bfloat162(" << v << ", " << v << ")";
      }
    } else {
      for (int i = 0; i < lanes / 4; ++i) {
        if (i != 0)
          os << ", ";
        os << "tl::pack_bfloat16x4(" << v << ", " << v << ", " << v << ", " << v
           << ")";
      }
2344
2345
2346
2347
2348
    }
    os << ')';
    return;
  }

2349
2350
  if (op->dtype.is_float() && op->dtype.bits() == 32 &&
      op->dtype.lanes() == 8) {
2351
2352
2353
    std::string v = PrintExpr(op->value);
    os << "make_ulonglong4(";
    for (int i = 0; i < 4; ++i) {
2354
2355
      if (i != 0)
        os << ", ";
2356
2357
2358
2359
2360
2361
2362
2363
      os << "*(unsigned long long*)&make_float2(" << v << ", " << v << ")";
    }
    os << ')';
    return;
  }

  if ((op->dtype.is_int() || op->dtype.is_uint()) && op->dtype.bits() == 4) {
    bool fail = false;
2364
    const int64_t *p = as_const_int(op->value);
2365
2366
2367
2368
2369
2370
2371
2372
2373
2374
2375
    ICHECK(p);
    int64_t v = *p & 0xF;

    if (lanes == 4) {
      v = (v << 12) | (v << 8) | (v << 4) | v;
      if (op->dtype.is_uint()) {
        os << "(uint16_t)" << v;
      } else {
        os << "(int16_t)" << v;
      }
    } else {
2376
2377
      v = (v << 28) | (v << 24) | (v << 20) | (v << 16) | (v << 12) | (v << 8) |
          (v << 4) | v;
2378
2379
2380
2381
2382
2383
2384
2385
2386
2387
2388
      if (lanes == 8) {
        if (op->dtype.is_uint()) {
          os << "(uint)" << v;
        } else {
          os << "(int)" << v;
        }
      } else if (lanes == 16 || lanes == 32) {
        os << "make_";
        PrintType(op->dtype, os);
        os << '(';
        for (int i = 0; i < lanes / 8; ++i) {
2389
2390
          if (i != 0)
            os << ", ";
2391
2392
2393
2394
2395
2396
2397
2398
2399
2400
2401
2402
2403
2404
2405
2406
2407
2408
2409
2410
2411
2412
          if (op->dtype.is_uint()) {
            os << "(uint)" << v;
          } else {
            os << "(int)" << v;
          }
        }
        os << ')';
      } else {
        fail = true;
      }
    }

    if (!fail) {
      return;
    }
  }

  std::string v = PrintExpr(op->value);
  os << "make_";
  PrintType(op->dtype, os);
  os << '(';
  for (int i = 0; i < lanes; ++i) {
2413
2414
    if (i != 0)
      os << ", ";
2415
2416
2417
2418
2419
    os << v;
  }
  os << ')';
}

2420
2421
inline void PrintConst(const FloatImmNode *op, std::ostream &os,
                       CodeGenTileLangCUDA *p) { // NOLINT(*)
2422
2423
2424
  // Type code is kBFloat
  if (op->dtype.is_bfloat16()) {
    os << "bfloat16_t";
2425
2426
2427
    os << '(' << std::hexfloat << op->value << 'f';
    os << "/*" << std::scientific << op->value << "*/";
    os << ')';
2428
2429
    return;
  }
2430
2431
2432
  // Type code is kFloat8_e5m2 or kE4M4Float
  if (op->dtype.is_float8() || op->dtype.is_float4()) {
    p->PrintType(op->dtype, os);
2433
2434
2435
    os << '(' << std::hexfloat << op->value << 'f';
    os << "/*" << std::scientific << op->value << "*/";
    os << ')';
2436
2437
    return;
  }
2438
2439
  // Type code is kFloat
  switch (op->dtype.bits()) {
2440
2441
2442
2443
2444
2445
  case 64:
  case 32: {
    std::ostringstream temp;
    if (std::isinf(op->value)) {
      if (op->value < 0) {
        temp << "-";
2446
      }
2447
      temp << ((op->dtype.bits() == 32) ? "CUDART_INF_F" : "CUDART_INF");
2448
      p->need_math_constants_h_ = true;
2449
2450
    } else if (std::isnan(op->value)) {
      temp << ((op->dtype.bits() == 32) ? "CUDART_NAN_F" : "CUDART_NAN");
2451
      p->need_math_constants_h_ = true;
2452
    } else {
2453
      temp << std::hexfloat << op->value;
2454
2455
      if (op->dtype.bits() == 32)
        temp << 'f';
2456
      temp << "/*" << std::scientific << op->value << "*/";
2457
    }
2458
2459
2460
2461
2462
2463
2464
2465
2466
2467
2468
2469
2470
    p->MarkConst(temp.str());
    os << temp.str();
    break;
  }
  case 16: {
    os << "half_t" << '(';
    FloatImm const_f32 = FloatImm(DataType::Float(32), op->value);
    PrintConst(const_f32.get(), os, p);
    os << ')';
    break;
  }
  default:
    LOG(FATAL) << "Bad bit-width for float: " << op->dtype << "\n";
2471
2472
2473
  }
}

2474
2475
void CodeGenTileLangCUDA::VisitExpr_(const FloatImmNode *op,
                                     std::ostream &os) { // NOLINT(*)
2476
2477
2478
  PrintConst(op, os, this);
}

2479
2480
2481
void CodeGenTileLangCUDA::PrintWmmaScope(const std::string &scope, DataType t,
                                         const VarNode *variable,
                                         std::ostream &os) {
2482
2483
  std::stringstream type;
  PrintType(t, type);
2484
2485
  ICHECK(fragment_shapes.count(variable))
      << "Cannot find shape of the wmma fragment " << variable->name_hint;
2486
2487
2488
2489
2490
2491
2492
2493
2494
2495
2496
2497
2498
2499
2500
2501
2502
2503
2504
2505
2506
2507
  std::string shape_str = fragment_shapes.at(variable);
  if ((t.is_int() || t.is_uint()) && t.bits() < 8 && t.lanes() == 1) {
    type.str(std::string());
    if (t.is_int()) {
      if (t.bits() == 4) {
        type << "nvcuda::wmma::experimental::precision::s4";
      } else if (t.bits() == 1) {
        type << "nvcuda::wmma::experimental::precision::b1";
      } else {
        LOG(FATAL) << "Unhandled integer type for wmma fragment!";
      }
    } else if (t.is_uint()) {
      if (t.bits() == 4) {
        type << "nvcuda::wmma::experimental::precision::u4";
      } else {
        LOG(FATAL) << "Unhandled integer type for wmma fragment!";
      }
    }
  }
  if (scope == "wmma.matrix_a") {
    std::string layout_str = fragment_layouts[variable];
    ICHECK_NE(layout_str, "") << "Layout must be defined for matrix_a";
2508
2509
    os << "nvcuda::wmma::fragment<nvcuda::wmma::matrix_a, " << shape_str << ", "
       << type.str() << ", nvcuda::wmma::" << layout_str << ">";
2510
2511
2512
  } else if (scope == "wmma.matrix_b") {
    std::string layout_str = fragment_layouts[variable];
    ICHECK_NE(layout_str, "") << "Layout must be defined for matrix_b";
2513
2514
    os << "nvcuda::wmma::fragment<nvcuda::wmma::matrix_b, " << shape_str << ", "
       << type.str() << ", nvcuda::wmma::" << layout_str << ">";
2515
  } else if (scope == "wmma.accumulator") {
2516
2517
    os << "nvcuda::wmma::fragment<nvcuda::wmma::accumulator, " << shape_str
       << ", " << type.str() << ">";
2518
2519
2520
  }
}

2521
2522
int32_t CodeGenTileLangCUDA::GetWmmaFragmentSize(const std::string &scope,
                                                 const VarNode *variable,
2523
                                                 int32_t size) {
2524
2525
  ICHECK(fragment_shapes.count(variable))
      << "Cannot find shape of the wmma fragment " << variable->name_hint;
2526
2527
2528
2529
2530
2531
2532
2533
  std::string shape_str = fragment_shapes.at(variable);
  std::pair<int32_t, int32_t> dim = GetWmmaFragmentDimSize(shape_str, scope);
  if (dim.first * dim.second != 0)
    return size / dim.first / dim.second;
  else
    return 0;
}

2534
2535
2536
void CodeGenTileLangCUDA::HandleVolatileLoads(const std::string &value,
                                              const BufferLoadNode *op,
                                              std::ostream &os) {
2537
2538
2539
  // Cast away volatile qualifier for fp16 types. That is, only loads and
  // stores are volatile. The loaded objects are not marked as volatile.
  //
2540
2541
  if ((op->dtype.is_float16() || op->dtype.is_bfloat16()) &&
      IsVolatile(op->buffer->data.get())) {
2542
2543
2544
2545
2546
2547
2548
2549
    os << "(";
    PrintType(op->dtype, os);
    os << ")(" << value << ")";
  } else {
    os << value;
  }
}

2550
2551
2552
void CodeGenTileLangCUDA::PrintVecElemLoadExpr(DataType t, int i,
                                               const std::string &value,
                                               std::ostream &os) {
2553
2554
2555
2556
2557
2558
  ICHECK_GT(t.lanes(), 1);
  if (t.bits() == 8 && (t.is_int() || t.is_uint())) {
    if (!(t.lanes() == 2 || t.lanes() == 3)) {
      if (i != 0) {
        os << "|";
      }
2559
2560
      os << "((0x000000ff << " << i * 8 << ") & (" << value << " << " << i * 8
         << "))";
2561
2562
2563
2564
2565
2566
2567
2568
2569
2570
2571
2572
2573
2574
2575
2576
2577
2578
2579
2580
2581
2582
2583
2584
2585
2586
2587
2588
2589
2590
2591
2592
2593
2594
2595
2596
2597
2598
2599
2600
2601
2602
2603
2604
2605
2606
2607
2608
2609
2610
2611
2612
2613
2614
2615
2616
      return;
    }
  }

  if (t.is_float16()) {
    if (i == 0) {
      os << "make_";
      PrintType(t, os);
      os << '(';
    }
    if (i % 2 == 0) {
      os << "__pack_half2(" << value;
    } else {
      os << "," << value << ")";
      if (i != t.lanes() - 1) {
        os << ",";
      } else {
        os << ")";
      }
    }
    return;
  }

  if (t.is_bfloat16()) {
    if (i == 0) {
      os << "make_";
      PrintType(t, os);
      os << '(';
    }
    if (i % 2 == 0) {
      os << "__pack_bfloat162(" << value;
    } else {
      os << "," << value << ")";
      if (i != t.lanes() - 1) {
        os << ",";
      } else {
        os << ")";
      }
    }
    return;
  }

  if (i == 0) {
    os << "make_";
    PrintType(t, os);
    os << "(";
  }
  os << value;
  if (i != t.lanes() - 1) {
    os << ",";
  } else {
    os << ")";
  }
  return;
}

2617
2618
2619
2620
2621
2622
2623
2624
2625
2626
2627
2628
2629
2630
2631
2632
2633
2634
2635
2636
2637
2638
2639
2640
2641
2642
2643
2644
2645
2646
2647
2648
2649
2650
2651
2652
2653
2654
2655
2656
2657
2658
2659
2660
2661
2662
2663
2664
2665
2666
2667
2668
2669
2670
2671
2672
2673
2674
2675
2676
2677
2678
2679
2680
2681
2682
void CodeGenTileLangCUDA::PrintFunctionSignature(const String &function_name,
                                                 const PrimFunc &func,
                                                 std::ostream &os) {
  PrintFuncPrefix(os);
  CodeGenC::PrintType(func->ret_type, os);
  CodeGenC::PrintExtraAttrs(func, os);
  bool no_alias = func->HasNonzeroAttr(tir::attr::kNoAlias);
  os << " " << function_name << "(";
  for (size_t i = 0; i < func->params.size(); ++i) {
    tir::Var v = func->params[i];
    std::string vid = AllocVarID(v.get());

    if (i > 0) {
      os << ", ";
    }

    if (v.dtype().is_handle()) {
      // work around for grid constant parameters.
      if (auto *ptr = v->type_annotation.as<PointerTypeNode>()) {
        if (ptr->storage_scope == "grid_constant") {
          os << "__grid_constant__ const ";
          CodeGenC::PrintType(ptr->element_type, os);
          os << ' ' << vid;
          continue;
        }
      }

      auto it = alloc_storage_scope_.find(v.get());
      if (it != alloc_storage_scope_.end()) {
        PrintStorageScope(it->second, os);
      }

      CodeGenC::PrintType(GetType(v), os);
      if (auto *ptr = v->type_annotation.as<PointerTypeNode>()) {
        if (auto *prim = ptr->element_type.as<PrimTypeNode>()) {
          RegisterHandleType(v.get(), prim->dtype);
        }
      }

      if (no_alias) {
        PrintRestrict(v, os);
      }
    } else {
      CodeGenC::PrintType(GetType(v), os);
    }
    os << ' ' << vid;
  }
  os << ")";

  // Register handle data type
  // TODO(tvm-team): consider simply keep type info in the
  // type annotation(via a normalizing rewriting).
  for (const auto &param : func->params) {
    if (auto *ptr = param->type_annotation.as<PointerTypeNode>()) {
      if (auto *prim = ptr->element_type.as<PrimTypeNode>()) {
        RegisterHandleType(param.get(), prim->dtype);
      }
    }
  }
}

void CodeGenTileLangCUDA::AddFunction(const GlobalVar &gvar,
                                      const PrimFunc &f) {
  // If the function has already been forward-declared, this is a
  // no-op.
  CodeGenC::DeclareFunction(gvar, f);
2683
2684
2685
2686
2687
2688
2689
2690
2691
2692
2693
2694
  // clear previous generated state.
  this->InitFuncState(f);
  // reserve keywords
  ReserveKeywordsAsUnique();

  auto global_symbol = f->GetAttr<String>(tvm::attr::kGlobalSymbol);
  ICHECK(global_symbol.defined())
      << "CodeGenC: Expect PrimFunc to have the global_symbol attribute";
  bool no_alias = f->HasNonzeroAttr(tir::attr::kNoAlias);

  this->PrintFuncPrefix(stream);
  CodeGenC::PrintType(f->ret_type, stream);
2695
2696
  this->PrintExtraAttrs(f);

2697
2698
2699
2700
2701
  this->stream << " " << static_cast<std::string>(global_symbol.value()) << "(";

  for (size_t i = 0; i < f->params.size(); ++i) {
    tir::Var v = f->params[i];
    std::string vid = AllocVarID(v.get());
2702
2703
    if (i != 0)
      stream << ", ";
2704
2705
    if (v.dtype().is_handle()) {
      // work around for grid constant parameters.
2706
      if (auto *ptr = v->type_annotation.as<PointerTypeNode>()) {
2707
2708
2709
2710
2711
2712
2713
2714
2715
2716
2717
2718
2719
2720
        if (ptr->storage_scope == "grid_constant") {
          stream << "__grid_constant__ const ";
          CodeGenC::PrintType(ptr->element_type, stream);
          stream << ' ' << vid;
          continue;
        }
      }

      auto it = alloc_storage_scope_.find(v.get());
      if (it != alloc_storage_scope_.end()) {
        PrintStorageScope(it->second, stream);
      }

      CodeGenC::PrintType(GetType(v), stream);
2721
2722
      if (auto *ptr = v->type_annotation.as<PointerTypeNode>()) {
        if (auto *prim = ptr->element_type.as<PrimTypeNode>()) {
2723
2724
2725
2726
2727
2728
2729
2730
2731
2732
2733
2734
2735
2736
2737
2738
2739
2740
2741
2742
2743
          RegisterHandleType(v.get(), prim->dtype);
        }
      }

      if (no_alias) {
        PrintRestrict(v, stream);
      }
    } else {
      CodeGenC::PrintType(GetType(v), stream);
    }
    stream << ' ' << vid;
  }
  stream << ") {\n";
  this->PreFunctionBody(f);
  int func_scope = this->BeginScope();
  this->PrintStmt(f->body);
  this->EndScope(func_scope);
  this->PrintIndent();
  this->stream << "}\n\n";
}

2744
2745
} // namespace codegen
} // namespace tvm