reference, declarationdefinition
definition → references, declarations, derived classes, virtual overrides
reference to multiple definitions → definitions
unreferenced
    1
    2
    3
    4
    5
    6
    7
    8
    9
   10
   11
   12
   13
   14
   15
   16
   17
   18
   19
   20
   21
   22
   23
   24
   25
   26
   27
   28
   29
   30
   31
   32
   33
   34
   35
   36
   37
   38
   39
   40
   41
   42
   43
   44
   45
   46
   47
   48
   49
   50
   51
   52
   53
   54
   55
   56
   57
   58
   59
   60
   61
   62
   63
   64
   65
   66
   67
   68
   69
   70
   71
   72
   73
   74
   75
   76
   77
   78
   79
   80
   81
   82
   83
   84
   85
   86
   87
   88
   89
   90
   91
   92
   93
   94
   95
   96
   97
   98
   99
  100
  101
  102
  103
  104
  105
  106
  107
  108
  109
  110
  111
  112
  113
  114
  115
  116
  117
  118
  119
  120
  121
  122
  123
  124
  125
  126
  127
  128
  129
  130
  131
  132
  133
  134
  135
  136
  137
  138
  139
  140
  141
  142
  143
  144
  145
  146
  147
  148
  149
  150
  151
  152
  153
  154
  155
  156
  157
  158
  159
  160
  161
  162
  163
  164
  165
  166
  167
  168
  169
  170
  171
  172
  173
  174
  175
  176
  177
  178
  179
  180
  181
  182
  183
  184
  185
  186
  187
  188
  189
  190
  191
  192
  193
  194
  195
  196
  197
  198
  199
  200
  201
  202
  203
  204
  205
  206
  207
  208
  209
  210
  211
  212
  213
  214
  215
  216
  217
  218
  219
  220
  221
  222
  223
  224
  225
  226
  227
  228
  229
  230
  231
  232
  233
  234
  235
  236
  237
  238
  239
  240
  241
  242
  243
  244
  245
  246
  247
  248
  249
  250
  251
  252
  253
  254
  255
  256
  257
  258
  259
  260
  261
  262
  263
  264
  265
  266
  267
  268
  269
  270
  271
  272
  273
  274
  275
  276
  277
  278
  279
  280
  281
  282
  283
  284
  285
  286
  287
  288
  289
  290
  291
  292
  293
  294
  295
  296
  297
  298
  299
  300
  301
  302
  303
  304
  305
  306
  307
  308
  309
  310
  311
  312
  313
  314
  315
  316
  317
  318
  319
  320
  321
  322
  323
  324
  325
  326
  327
  328
  329
  330
  331
  332
  333
  334
  335
  336
  337
  338
  339
  340
  341
  342
  343
  344
  345
  346
  347
  348
  349
  350
  351
  352
  353
  354
  355
  356
  357
  358
  359
  360
  361
  362
  363
  364
  365
  366
  367
  368
  369
  370
  371
  372
  373
  374
  375
  376
  377
  378
  379
  380
  381
  382
  383
  384
  385
  386
  387
  388
  389
  390
  391
  392
  393
  394
  395
  396
  397
  398
  399
  400
  401
  402
  403
  404
  405
  406
  407
  408
  409
  410
  411
  412
  413
  414
  415
  416
  417
  418
  419
  420
  421
  422
  423
  424
  425
  426
  427
  428
  429
  430
  431
  432
  433
  434
  435
  436
  437
  438
  439
  440
  441
  442
  443
  444
  445
  446
  447
  448
  449
  450
  451
  452
  453
  454
  455
  456
  457
  458
  459
  460
  461
  462
  463
  464
  465
  466
  467
  468
  469
  470
  471
  472
  473
  474
  475
  476
  477
  478
  479
  480
  481
  482
  483
  484
  485
  486
  487
  488
  489
  490
  491
  492
  493
  494
  495
  496
  497
  498
  499
  500
  501
  502
  503
  504
  505
  506
  507
  508
  509
  510
  511
  512
  513
  514
  515
  516
  517
  518
  519
  520
  521
  522
  523
  524
  525
  526
  527
  528
  529
  530
  531
  532
  533
  534
  535
  536
  537
  538
  539
  540
  541
  542
  543
  544
  545
  546
  547
  548
  549
  550
  551
  552
  553
  554
  555
  556
  557
  558
  559
  560
  561
  562
  563
  564
  565
  566
  567
  568
  569
  570
  571
  572
  573
  574
  575
  576
  577
  578
  579
  580
  581
  582
  583
  584
  585
  586
  587
  588
  589
  590
  591
  592
  593
  594
  595
  596
  597
  598
  599
  600
  601
  602
  603
  604
  605
  606
  607
  608
  609
  610
  611
  612
  613
  614
  615
  616
  617
  618
  619
  620
  621
  622
  623
  624
  625
  626
  627
  628
  629
  630
  631
  632
  633
  634
  635
  636
  637
  638
  639
  640
  641
  642
  643
  644
  645
  646
  647
  648
  649
  650
  651
  652
  653
  654
  655
  656
  657
  658
  659
  660
  661
  662
  663
  664
  665
  666
  667
  668
  669
  670
  671
  672
  673
  674
  675
  676
  677
  678
  679
  680
  681
  682
  683
  684
  685
  686
  687
  688
  689
  690
  691
  692
  693
  694
  695
  696
  697
  698
  699
  700
  701
  702
  703
  704
  705
  706
  707
  708
  709
  710
  711
  712
  713
  714
  715
  716
  717
  718
  719
  720
  721
  722
  723
  724
  725
  726
  727
  728
  729
  730
  731
  732
  733
  734
  735
  736
  737
  738
  739
  740
  741
  742
  743
  744
  745
  746
  747
  748
  749
  750
  751
  752
  753
  754
  755
  756
  757
  758
  759
  760
  761
  762
  763
  764
  765
  766
  767
  768
  769
  770
  771
  772
  773
  774
  775
  776
  777
  778
  779
  780
  781
  782
  783
  784
  785
  786
  787
  788
  789
  790
  791
  792
  793
  794
  795
  796
  797
  798
  799
  800
  801
  802
  803
  804
  805
  806
  807
  808
  809
  810
  811
  812
  813
  814
  815
  816
  817
  818
  819
  820
  821
  822
  823
  824
  825
  826
  827
  828
  829
  830
  831
  832
  833
  834
  835
  836
  837
  838
  839
  840
  841
  842
  843
  844
  845
  846
  847
  848
  849
  850
  851
  852
  853
  854
  855
  856
  857
  858
  859
  860
  861
  862
  863
  864
  865
  866
  867
  868
  869
  870
  871
  872
  873
  874
  875
  876
  877
  878
  879
  880
  881
  882
  883
  884
  885
  886
  887
  888
  889
  890
  891
  892
  893
  894
  895
  896
  897
  898
  899
  900
  901
  902
  903
  904
  905
  906
  907
  908
  909
  910
  911
  912
  913
  914
  915
  916
  917
  918
  919
  920
  921
  922
  923
  924
  925
  926
  927
  928
  929
  930
  931
  932
  933
  934
  935
  936
  937
  938
  939
  940
  941
  942
  943
  944
  945
  946
  947
  948
  949
  950
  951
  952
  953
  954
  955
  956
  957
  958
  959
  960
  961
  962
  963
  964
  965
  966
  967
  968
  969
  970
  971
  972
  973
  974
  975
  976
  977
  978
  979
  980
  981
  982
  983
  984
  985
  986
  987
  988
  989
  990
  991
  992
  993
  994
  995
  996
  997
  998
  999
 1000
 1001
 1002
 1003
 1004
 1005
 1006
 1007
 1008
 1009
 1010
 1011
 1012
 1013
 1014
 1015
 1016
 1017
 1018
 1019
 1020
 1021
 1022
 1023
 1024
 1025
 1026
 1027
 1028
 1029
 1030
 1031
 1032
 1033
 1034
 1035
 1036
 1037
 1038
 1039
 1040
 1041
 1042
 1043
 1044
 1045
 1046
 1047
 1048
 1049
 1050
 1051
 1052
 1053
 1054
 1055
 1056
 1057
 1058
 1059
 1060
 1061
 1062
 1063
 1064
 1065
 1066
 1067
 1068
 1069
 1070
 1071
 1072
 1073
 1074
 1075
 1076
 1077
 1078
 1079
 1080
 1081
 1082
 1083
 1084
 1085
 1086
 1087
 1088
 1089
 1090
 1091
 1092
 1093
 1094
 1095
 1096
 1097
 1098
 1099
 1100
 1101
 1102
 1103
 1104
 1105
 1106
 1107
 1108
 1109
 1110
 1111
 1112
 1113
 1114
 1115
 1116
 1117
 1118
 1119
 1120
 1121
 1122
 1123
 1124
 1125
 1126
 1127
 1128
 1129
 1130
 1131
 1132
 1133
 1134
 1135
 1136
 1137
 1138
 1139
 1140
 1141
 1142
 1143
 1144
 1145
 1146
 1147
 1148
 1149
 1150
 1151
 1152
 1153
 1154
 1155
 1156
 1157
 1158
 1159
 1160
 1161
 1162
 1163
 1164
 1165
 1166
 1167
 1168
 1169
 1170
 1171
 1172
 1173
 1174
 1175
 1176
 1177
 1178
 1179
 1180
 1181
 1182
 1183
 1184
 1185
 1186
 1187
 1188
 1189
 1190
 1191
 1192
 1193
 1194
 1195
 1196
 1197
 1198
 1199
 1200
 1201
 1202
 1203
 1204
 1205
 1206
 1207
 1208
 1209
 1210
 1211
 1212
 1213
 1214
 1215
 1216
 1217
 1218
 1219
 1220
 1221
 1222
 1223
 1224
 1225
 1226
 1227
 1228
 1229
 1230
 1231
 1232
 1233
 1234
 1235
 1236
 1237
 1238
 1239
 1240
 1241
 1242
 1243
 1244
 1245
 1246
 1247
 1248
 1249
 1250
 1251
 1252
 1253
 1254
 1255
 1256
 1257
 1258
 1259
 1260
 1261
 1262
 1263
 1264
 1265
 1266
 1267
 1268
 1269
 1270
 1271
 1272
 1273
 1274
 1275
 1276
 1277
 1278
 1279
 1280
 1281
 1282
 1283
 1284
 1285
 1286
 1287
 1288
 1289
 1290
 1291
 1292
 1293
 1294
 1295
 1296
 1297
 1298
 1299
 1300
 1301
 1302
 1303
 1304
 1305
 1306
 1307
 1308
 1309
 1310
 1311
 1312
 1313
 1314
 1315
 1316
 1317
 1318
 1319
 1320
 1321
 1322
 1323
 1324
 1325
 1326
 1327
 1328
 1329
 1330
 1331
 1332
 1333
 1334
 1335
 1336
 1337
 1338
 1339
 1340
 1341
 1342
 1343
 1344
 1345
 1346
 1347
 1348
 1349
 1350
 1351
 1352
 1353
 1354
 1355
 1356
 1357
 1358
 1359
 1360
 1361
 1362
 1363
 1364
 1365
 1366
 1367
 1368
 1369
 1370
 1371
 1372
 1373
 1374
 1375
 1376
 1377
 1378
 1379
 1380
 1381
 1382
 1383
 1384
 1385
 1386
 1387
 1388
 1389
 1390
 1391
 1392
 1393
 1394
 1395
 1396
 1397
 1398
 1399
 1400
 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
 1434
 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
 1489
 1490
 1491
 1492
 1493
 1494
 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
 1530
 1531
 1532
 1533
 1534
 1535
 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
 1635
 1636
 1637
 1638
 1639
 1640
 1641
 1642
 1643
 1644
 1645
 1646
 1647
 1648
 1649
 1650
 1651
 1652
 1653
 1654
 1655
 1656
 1657
 1658
 1659
 1660
 1661
 1662
 1663
 1664
 1665
 1666
 1667
 1668
 1669
 1670
 1671
 1672
 1673
 1674
 1675
 1676
 1677
 1678
 1679
 1680
 1681
 1682
 1683
 1684
 1685
 1686
 1687
 1688
 1689
 1690
 1691
 1692
 1693
 1694
 1695
 1696
 1697
 1698
 1699
 1700
 1701
 1702
 1703
 1704
 1705
 1706
 1707
 1708
 1709
 1710
 1711
 1712
 1713
 1714
 1715
 1716
 1717
 1718
 1719
 1720
 1721
 1722
 1723
 1724
 1725
 1726
 1727
 1728
 1729
 1730
 1731
 1732
 1733
 1734
 1735
 1736
 1737
 1738
 1739
 1740
 1741
 1742
 1743
 1744
 1745
 1746
 1747
 1748
 1749
 1750
 1751
 1752
 1753
 1754
 1755
 1756
 1757
 1758
 1759
 1760
 1761
 1762
 1763
 1764
 1765
 1766
 1767
 1768
 1769
 1770
 1771
 1772
 1773
 1774
 1775
 1776
 1777
 1778
 1779
 1780
 1781
 1782
 1783
 1784
 1785
 1786
 1787
 1788
 1789
 1790
 1791
 1792
 1793
 1794
 1795
 1796
 1797
 1798
 1799
 1800
 1801
 1802
 1803
 1804
 1805
 1806
 1807
 1808
 1809
 1810
 1811
 1812
 1813
 1814
 1815
 1816
 1817
 1818
 1819
 1820
 1821
 1822
 1823
 1824
 1825
 1826
 1827
 1828
 1829
 1830
 1831
 1832
 1833
 1834
 1835
 1836
 1837
 1838
 1839
 1840
 1841
 1842
 1843
 1844
 1845
 1846
 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
 1941
 1942
 1943
 1944
 1945
 1946
 1947
 1948
 1949
 1950
 1951
 1952
 1953
 1954
 1955
 1956
 1957
 1958
 1959
 1960
 1961
 1962
 1963
 1964
 1965
 1966
 1967
 1968
 1969
 1970
 1971
 1972
 1973
 1974
 1975
 1976
 1977
 1978
 1979
 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
 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
 2056
 2057
 2058
 2059
 2060
 2061
 2062
 2063
 2064
 2065
 2066
 2067
 2068
 2069
 2070
 2071
 2072
 2073
 2074
 2075
 2076
 2077
 2078
 2079
 2080
 2081
 2082
 2083
 2084
 2085
 2086
 2087
 2088
 2089
 2090
 2091
 2092
 2093
 2094
 2095
 2096
 2097
 2098
 2099
 2100
 2101
 2102
 2103
 2104
 2105
 2106
 2107
 2108
 2109
 2110
 2111
 2112
 2113
 2114
 2115
 2116
 2117
 2118
 2119
 2120
 2121
 2122
 2123
 2124
 2125
 2126
 2127
 2128
 2129
 2130
 2131
 2132
 2133
 2134
 2135
 2136
 2137
 2138
 2139
 2140
 2141
 2142
 2143
 2144
 2145
 2146
 2147
 2148
 2149
 2150
 2151
 2152
 2153
 2154
 2155
 2156
 2157
 2158
 2159
 2160
 2161
 2162
 2163
 2164
 2165
 2166
 2167
 2168
 2169
 2170
 2171
 2172
 2173
 2174
 2175
 2176
 2177
 2178
 2179
 2180
 2181
 2182
 2183
 2184
 2185
 2186
 2187
 2188
 2189
 2190
 2191
 2192
 2193
 2194
 2195
 2196
 2197
 2198
 2199
 2200
 2201
 2202
 2203
 2204
 2205
 2206
 2207
 2208
 2209
 2210
 2211
 2212
 2213
 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
 2270
 2271
 2272
 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
 2300
 2301
 2302
 2303
 2304
 2305
 2306
 2307
 2308
 2309
 2310
 2311
 2312
 2313
 2314
 2315
 2316
 2317
 2318
 2319
 2320
 2321
 2322
 2323
 2324
 2325
 2326
 2327
 2328
 2329
 2330
 2331
 2332
 2333
 2334
 2335
 2336
 2337
 2338
 2339
 2340
 2341
 2342
 2343
 2344
 2345
 2346
 2347
 2348
 2349
 2350
 2351
 2352
 2353
 2354
 2355
 2356
 2357
 2358
 2359
 2360
 2361
 2362
 2363
 2364
 2365
 2366
 2367
 2368
 2369
 2370
 2371
 2372
 2373
 2374
 2375
 2376
 2377
 2378
 2379
 2380
 2381
 2382
 2383
 2384
 2385
 2386
 2387
 2388
 2389
 2390
 2391
 2392
 2393
 2394
 2395
 2396
 2397
 2398
 2399
 2400
 2401
 2402
 2403
 2404
 2405
 2406
 2407
 2408
 2409
 2410
 2411
 2412
 2413
 2414
 2415
 2416
 2417
 2418
 2419
 2420
 2421
 2422
 2423
 2424
 2425
 2426
 2427
 2428
 2429
 2430
 2431
 2432
 2433
 2434
 2435
 2436
 2437
 2438
 2439
 2440
 2441
 2442
 2443
 2444
 2445
 2446
 2447
 2448
 2449
 2450
 2451
 2452
 2453
 2454
 2455
 2456
 2457
 2458
 2459
 2460
 2461
 2462
 2463
 2464
 2465
 2466
 2467
 2468
 2469
 2470
 2471
 2472
 2473
 2474
 2475
 2476
 2477
 2478
 2479
 2480
 2481
 2482
 2483
 2484
 2485
 2486
 2487
 2488
 2489
 2490
 2491
 2492
 2493
 2494
 2495
 2496
 2497
 2498
 2499
 2500
 2501
 2502
 2503
 2504
 2505
 2506
 2507
 2508
 2509
 2510
 2511
 2512
 2513
 2514
 2515
 2516
 2517
 2518
 2519
 2520
 2521
 2522
 2523
 2524
 2525
 2526
 2527
 2528
 2529
 2530
 2531
 2532
 2533
 2534
 2535
 2536
 2537
 2538
 2539
 2540
 2541
 2542
 2543
 2544
 2545
 2546
 2547
 2548
 2549
 2550
 2551
 2552
 2553
 2554
 2555
 2556
 2557
 2558
 2559
 2560
 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
 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
 2683
 2684
 2685
 2686
 2687
 2688
 2689
 2690
 2691
 2692
 2693
 2694
 2695
 2696
 2697
 2698
 2699
 2700
 2701
 2702
 2703
 2704
 2705
 2706
 2707
 2708
 2709
 2710
 2711
 2712
 2713
 2714
 2715
 2716
 2717
 2718
 2719
 2720
 2721
 2722
 2723
 2724
 2725
 2726
 2727
 2728
 2729
 2730
 2731
 2732
 2733
 2734
 2735
 2736
 2737
 2738
 2739
 2740
 2741
 2742
 2743
 2744
 2745
 2746
 2747
 2748
 2749
 2750
 2751
 2752
 2753
 2754
 2755
 2756
 2757
 2758
 2759
 2760
 2761
 2762
 2763
 2764
 2765
 2766
 2767
 2768
 2769
 2770
 2771
 2772
 2773
 2774
 2775
 2776
 2777
 2778
 2779
 2780
 2781
 2782
 2783
 2784
 2785
 2786
 2787
 2788
 2789
 2790
 2791
 2792
 2793
 2794
 2795
 2796
 2797
 2798
 2799
 2800
 2801
 2802
 2803
 2804
 2805
 2806
 2807
 2808
 2809
 2810
 2811
 2812
 2813
 2814
 2815
 2816
 2817
 2818
 2819
 2820
 2821
 2822
 2823
 2824
 2825
 2826
 2827
 2828
 2829
 2830
 2831
 2832
 2833
 2834
 2835
 2836
 2837
 2838
 2839
 2840
 2841
 2842
 2843
 2844
 2845
 2846
 2847
 2848
 2849
 2850
 2851
 2852
 2853
 2854
 2855
 2856
 2857
 2858
 2859
 2860
 2861
 2862
 2863
 2864
 2865
 2866
 2867
 2868
 2869
 2870
 2871
 2872
 2873
 2874
 2875
 2876
 2877
 2878
 2879
 2880
 2881
 2882
 2883
 2884
 2885
 2886
 2887
 2888
 2889
 2890
 2891
 2892
 2893
 2894
 2895
 2896
 2897
 2898
 2899
 2900
 2901
 2902
 2903
 2904
 2905
 2906
 2907
 2908
 2909
 2910
 2911
 2912
 2913
 2914
 2915
 2916
 2917
 2918
 2919
 2920
 2921
 2922
 2923
 2924
 2925
 2926
 2927
 2928
 2929
 2930
 2931
 2932
 2933
 2934
 2935
 2936
 2937
 2938
 2939
 2940
 2941
 2942
 2943
 2944
 2945
 2946
 2947
 2948
 2949
 2950
 2951
 2952
 2953
 2954
 2955
 2956
 2957
 2958
 2959
 2960
 2961
 2962
 2963
 2964
 2965
 2966
 2967
 2968
 2969
 2970
 2971
 2972
 2973
 2974
 2975
 2976
 2977
 2978
 2979
 2980
 2981
 2982
 2983
 2984
 2985
 2986
 2987
 2988
 2989
 2990
 2991
 2992
 2993
 2994
 2995
 2996
 2997
 2998
 2999
 3000
 3001
 3002
 3003
 3004
 3005
 3006
 3007
 3008
 3009
 3010
 3011
 3012
 3013
 3014
 3015
 3016
 3017
 3018
 3019
 3020
 3021
 3022
 3023
 3024
 3025
 3026
 3027
 3028
 3029
 3030
 3031
 3032
 3033
 3034
 3035
 3036
 3037
 3038
 3039
 3040
 3041
 3042
 3043
 3044
 3045
 3046
 3047
 3048
 3049
 3050
 3051
 3052
 3053
 3054
 3055
 3056
 3057
 3058
 3059
 3060
 3061
 3062
 3063
 3064
 3065
 3066
 3067
 3068
 3069
 3070
 3071
 3072
 3073
 3074
 3075
 3076
 3077
 3078
 3079
 3080
 3081
 3082
 3083
 3084
 3085
 3086
 3087
 3088
 3089
 3090
 3091
 3092
 3093
 3094
 3095
 3096
 3097
 3098
 3099
 3100
 3101
 3102
 3103
 3104
 3105
 3106
 3107
 3108
 3109
 3110
 3111
 3112
 3113
 3114
 3115
 3116
 3117
 3118
 3119
 3120
 3121
 3122
 3123
 3124
 3125
 3126
 3127
 3128
 3129
 3130
 3131
 3132
 3133
 3134
 3135
 3136
 3137
 3138
 3139
 3140
 3141
 3142
 3143
 3144
 3145
 3146
 3147
 3148
 3149
 3150
 3151
 3152
 3153
 3154
 3155
 3156
 3157
 3158
 3159
 3160
 3161
 3162
 3163
 3164
 3165
 3166
 3167
 3168
 3169
 3170
 3171
 3172
 3173
 3174
 3175
 3176
 3177
 3178
 3179
 3180
 3181
 3182
 3183
 3184
 3185
 3186
 3187
 3188
 3189
 3190
 3191
 3192
 3193
 3194
 3195
 3196
 3197
 3198
 3199
 3200
 3201
 3202
 3203
 3204
 3205
 3206
 3207
 3208
 3209
 3210
 3211
 3212
 3213
 3214
 3215
 3216
 3217
 3218
 3219
 3220
 3221
 3222
 3223
 3224
 3225
 3226
 3227
 3228
 3229
 3230
 3231
 3232
 3233
 3234
 3235
 3236
 3237
 3238
 3239
 3240
 3241
 3242
 3243
 3244
 3245
 3246
 3247
 3248
 3249
 3250
 3251
 3252
 3253
 3254
 3255
 3256
 3257
 3258
 3259
 3260
 3261
 3262
 3263
 3264
 3265
 3266
 3267
 3268
 3269
 3270
 3271
 3272
 3273
 3274
 3275
 3276
 3277
 3278
 3279
 3280
 3281
 3282
 3283
 3284
 3285
 3286
 3287
 3288
 3289
 3290
 3291
 3292
 3293
 3294
 3295
 3296
 3297
 3298
 3299
 3300
 3301
 3302
 3303
 3304
 3305
 3306
 3307
 3308
 3309
 3310
 3311
 3312
 3313
 3314
 3315
 3316
 3317
 3318
 3319
 3320
 3321
 3322
 3323
 3324
 3325
 3326
 3327
 3328
 3329
 3330
 3331
 3332
 3333
 3334
 3335
 3336
 3337
 3338
 3339
 3340
 3341
 3342
 3343
 3344
 3345
 3346
 3347
 3348
 3349
 3350
 3351
 3352
 3353
 3354
 3355
 3356
 3357
 3358
 3359
 3360
 3361
 3362
 3363
 3364
 3365
 3366
 3367
 3368
 3369
 3370
 3371
 3372
 3373
 3374
 3375
 3376
 3377
 3378
 3379
 3380
 3381
 3382
 3383
 3384
 3385
 3386
 3387
 3388
 3389
 3390
 3391
 3392
 3393
 3394
 3395
 3396
 3397
 3398
 3399
 3400
 3401
 3402
 3403
 3404
 3405
 3406
 3407
 3408
 3409
 3410
 3411
 3412
 3413
 3414
 3415
 3416
 3417
 3418
 3419
 3420
 3421
 3422
 3423
 3424
 3425
 3426
 3427
 3428
 3429
 3430
 3431
 3432
 3433
 3434
 3435
 3436
 3437
 3438
 3439
 3440
 3441
 3442
 3443
 3444
 3445
 3446
 3447
 3448
 3449
 3450
 3451
 3452
 3453
 3454
 3455
 3456
 3457
 3458
 3459
 3460
 3461
 3462
 3463
 3464
 3465
 3466
 3467
 3468
 3469
 3470
 3471
 3472
 3473
 3474
 3475
 3476
 3477
 3478
 3479
 3480
 3481
 3482
 3483
 3484
 3485
 3486
 3487
 3488
 3489
 3490
 3491
 3492
 3493
 3494
 3495
 3496
 3497
 3498
 3499
 3500
 3501
 3502
 3503
 3504
 3505
 3506
 3507
 3508
 3509
 3510
 3511
 3512
 3513
 3514
 3515
 3516
 3517
 3518
 3519
 3520
 3521
 3522
 3523
 3524
 3525
 3526
 3527
 3528
 3529
 3530
 3531
 3532
 3533
 3534
 3535
 3536
 3537
 3538
 3539
 3540
 3541
 3542
 3543
 3544
 3545
 3546
 3547
 3548
 3549
 3550
 3551
 3552
 3553
 3554
 3555
 3556
 3557
 3558
 3559
 3560
 3561
 3562
 3563
 3564
 3565
 3566
 3567
 3568
 3569
 3570
 3571
 3572
 3573
 3574
 3575
 3576
 3577
 3578
 3579
 3580
 3581
 3582
 3583
 3584
 3585
 3586
 3587
 3588
 3589
 3590
 3591
 3592
 3593
 3594
 3595
 3596
 3597
 3598
 3599
 3600
 3601
 3602
 3603
 3604
 3605
 3606
 3607
 3608
 3609
 3610
 3611
 3612
 3613
 3614
 3615
 3616
 3617
 3618
 3619
 3620
 3621
 3622
 3623
 3624
 3625
//===------ PPCGCodeGeneration.cpp - Polly Accelerator Code Generation. ---===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
//
// Take a scop created by ScopInfo and map it to GPU code using the ppcg
// GPU mapping strategy.
//
//===----------------------------------------------------------------------===//

#include "polly/CodeGen/PPCGCodeGeneration.h"
#include "polly/CodeGen/CodeGeneration.h"
#include "polly/CodeGen/IslAst.h"
#include "polly/CodeGen/IslNodeBuilder.h"
#include "polly/CodeGen/PerfMonitor.h"
#include "polly/CodeGen/Utils.h"
#include "polly/DependenceInfo.h"
#include "polly/LinkAllPasses.h"
#include "polly/Options.h"
#include "polly/ScopDetection.h"
#include "polly/ScopInfo.h"
#include "polly/Support/SCEVValidator.h"
#include "llvm/ADT/PostOrderIterator.h"
#include "llvm/Analysis/TargetTransformInfo.h"
#include "llvm/IR/LegacyPassManager.h"
#include "llvm/IR/Verifier.h"
#include "llvm/IRReader/IRReader.h"
#include "llvm/Linker/Linker.h"
#include "llvm/Support/SourceMgr.h"
#include "llvm/Support/TargetRegistry.h"
#include "llvm/Target/TargetMachine.h"
#include "llvm/Transforms/IPO/PassManagerBuilder.h"
#include "llvm/Transforms/Utils/BasicBlockUtils.h"
#include "isl/union_map.h"

extern "C" {
#include "ppcg/cuda.h"
#include "ppcg/gpu.h"
#include "ppcg/ppcg.h"
}

#include "llvm/Support/Debug.h"

using namespace polly;
using namespace llvm;

#define DEBUG_TYPE "polly-codegen-ppcg"

static cl::opt<bool> DumpSchedule("polly-acc-dump-schedule",
                                  cl::desc("Dump the computed GPU Schedule"),
                                  cl::Hidden, cl::init(false), cl::ZeroOrMore,
                                  cl::cat(PollyCategory));

static cl::opt<bool>
    DumpCode("polly-acc-dump-code",
             cl::desc("Dump C code describing the GPU mapping"), cl::Hidden,
             cl::init(false), cl::ZeroOrMore, cl::cat(PollyCategory));

static cl::opt<bool> DumpKernelIR("polly-acc-dump-kernel-ir",
                                  cl::desc("Dump the kernel LLVM-IR"),
                                  cl::Hidden, cl::init(false), cl::ZeroOrMore,
                                  cl::cat(PollyCategory));

static cl::opt<bool> DumpKernelASM("polly-acc-dump-kernel-asm",
                                   cl::desc("Dump the kernel assembly code"),
                                   cl::Hidden, cl::init(false), cl::ZeroOrMore,
                                   cl::cat(PollyCategory));

static cl::opt<bool> FastMath("polly-acc-fastmath",
                              cl::desc("Allow unsafe math optimizations"),
                              cl::Hidden, cl::init(false), cl::ZeroOrMore,
                              cl::cat(PollyCategory));
static cl::opt<bool> SharedMemory("polly-acc-use-shared",
                                  cl::desc("Use shared memory"), cl::Hidden,
                                  cl::init(false), cl::ZeroOrMore,
                                  cl::cat(PollyCategory));
static cl::opt<bool> PrivateMemory("polly-acc-use-private",
                                   cl::desc("Use private memory"), cl::Hidden,
                                   cl::init(false), cl::ZeroOrMore,
                                   cl::cat(PollyCategory));

bool polly::PollyManagedMemory;
static cl::opt<bool, true>
    XManagedMemory("polly-acc-codegen-managed-memory",
                   cl::desc("Generate Host kernel code assuming"
                            " that all memory has been"
                            " declared as managed memory"),
                   cl::location(PollyManagedMemory), cl::Hidden,
                   cl::init(false), cl::ZeroOrMore, cl::cat(PollyCategory));

static cl::opt<bool>
    FailOnVerifyModuleFailure("polly-acc-fail-on-verify-module-failure",
                              cl::desc("Fail and generate a backtrace if"
                                       " verifyModule fails on the GPU "
                                       " kernel module."),
                              cl::Hidden, cl::init(false), cl::ZeroOrMore,
                              cl::cat(PollyCategory));

static cl::opt<std::string> CUDALibDevice(
    "polly-acc-libdevice", cl::desc("Path to CUDA libdevice"), cl::Hidden,
    cl::init("/usr/local/cuda/nvvm/libdevice/libdevice.compute_20.10.ll"),
    cl::ZeroOrMore, cl::cat(PollyCategory));

static cl::opt<std::string>
    CudaVersion("polly-acc-cuda-version",
                cl::desc("The CUDA version to compile for"), cl::Hidden,
                cl::init("sm_30"), cl::ZeroOrMore, cl::cat(PollyCategory));

static cl::opt<int>
    MinCompute("polly-acc-mincompute",
               cl::desc("Minimal number of compute statements to run on GPU."),
               cl::Hidden, cl::init(10 * 512 * 512));

extern bool polly::PerfMonitoring;

/// Return  a unique name for a Scop, which is the scop region with the
/// function name.
std::string getUniqueScopName(const Scop *S) {
  return "Scop Region: " + S->getNameStr() +
         " | Function: " + std::string(S->getFunction().getName());
}

/// Used to store information PPCG wants for kills. This information is
/// used by live range reordering.
///
/// @see computeLiveRangeReordering
/// @see GPUNodeBuilder::createPPCGScop
/// @see GPUNodeBuilder::createPPCGProg
struct MustKillsInfo {
  /// Collection of all kill statements that will be sequenced at the end of
  /// PPCGScop->schedule.
  ///
  /// The nodes in `KillsSchedule` will be merged using `isl_schedule_set`
  /// which merges schedules in *arbitrary* order.
  /// (we don't care about the order of the kills anyway).
  isl::schedule KillsSchedule;
  /// Map from kill statement instances to scalars that need to be
  /// killed.
  ///
  /// We currently derive kill information for:
  ///  1. phi nodes. PHI nodes are not alive outside the scop and can
  ///     consequently all be killed.
  ///  2. Scalar arrays that are not used outside the Scop. This is
  ///     checked by `isScalarUsesContainedInScop`.
  /// [params] -> { [Stmt_phantom[] -> ref_phantom[]] -> scalar_to_kill[] }
  isl::union_map TaggedMustKills;

  /// Tagged must kills stripped of the tags.
  /// [params] -> { Stmt_phantom[]  -> scalar_to_kill[] }
  isl::union_map MustKills;

  MustKillsInfo() : KillsSchedule(nullptr) {}
};

/// Check if SAI's uses are entirely contained within Scop S.
/// If a scalar is used only with a Scop, we are free to kill it, as no data
/// can flow in/out of the value any more.
/// @see computeMustKillsInfo
static bool isScalarUsesContainedInScop(const Scop &S,
                                        const ScopArrayInfo *SAI) {
  assert(SAI->isValueKind() && "this function only deals with scalars."
                               " Dealing with arrays required alias analysis");

  const Region &R = S.getRegion();
  for (User *U : SAI->getBasePtr()->users()) {
    Instruction *I = dyn_cast<Instruction>(U);
    assert(I && "invalid user of scop array info");
    if (!R.contains(I))
      return false;
  }
  return true;
}

/// Compute must-kills needed to enable live range reordering with PPCG.
///
/// @params S The Scop to compute live range reordering information
/// @returns live range reordering information that can be used to setup
/// PPCG.
static MustKillsInfo computeMustKillsInfo(const Scop &S) {
  const isl::space ParamSpace = S.getParamSpace();
  MustKillsInfo Info;

  // 1. Collect all ScopArrayInfo that satisfy *any* of the criteria:
  //      1.1 phi nodes in scop.
  //      1.2 scalars that are only used within the scop
  SmallVector<isl::id, 4> KillMemIds;
  for (ScopArrayInfo *SAI : S.arrays()) {
    if (SAI->isPHIKind() ||
        (SAI->isValueKind() && isScalarUsesContainedInScop(S, SAI)))
      KillMemIds.push_back(isl::manage(SAI->getBasePtrId().release()));
  }

  Info.TaggedMustKills = isl::union_map::empty(ParamSpace);
  Info.MustKills = isl::union_map::empty(ParamSpace);

  // Initialising KillsSchedule to `isl_set_empty` creates an empty node in the
  // schedule:
  //     - filter: "[control] -> { }"
  // So, we choose to not create this to keep the output a little nicer,
  // at the cost of some code complexity.
  Info.KillsSchedule = nullptr;

  for (isl::id &ToKillId : KillMemIds) {
    isl::id KillStmtId = isl::id::alloc(
        S.getIslCtx(),
        std::string("SKill_phantom_").append(ToKillId.get_name()), nullptr);

    // NOTE: construction of tagged_must_kill:
    // 2. We need to construct a map:
    //     [param] -> { [Stmt_phantom[] -> ref_phantom[]] -> scalar_to_kill[] }
    // To construct this, we use `isl_map_domain_product` on 2 maps`:
    // 2a. StmtToScalar:
    //         [param] -> { Stmt_phantom[] -> scalar_to_kill[] }
    // 2b. PhantomRefToScalar:
    //         [param] -> { ref_phantom[] -> scalar_to_kill[] }
    //
    // Combining these with `isl_map_domain_product` gives us
    // TaggedMustKill:
    //     [param] -> { [Stmt[] -> phantom_ref[]] -> scalar_to_kill[] }

    // 2a. [param] -> { Stmt[] -> scalar_to_kill[] }
    isl::map StmtToScalar = isl::map::universe(ParamSpace);
    StmtToScalar = StmtToScalar.set_tuple_id(isl::dim::in, isl::id(KillStmtId));
    StmtToScalar = StmtToScalar.set_tuple_id(isl::dim::out, isl::id(ToKillId));

    isl::id PhantomRefId = isl::id::alloc(
        S.getIslCtx(), std::string("ref_phantom") + ToKillId.get_name(),
        nullptr);

    // 2b. [param] -> { phantom_ref[] -> scalar_to_kill[] }
    isl::map PhantomRefToScalar = isl::map::universe(ParamSpace);
    PhantomRefToScalar =
        PhantomRefToScalar.set_tuple_id(isl::dim::in, PhantomRefId);
    PhantomRefToScalar =
        PhantomRefToScalar.set_tuple_id(isl::dim::out, ToKillId);

    // 2. [param] -> { [Stmt[] -> phantom_ref[]] -> scalar_to_kill[] }
    isl::map TaggedMustKill = StmtToScalar.domain_product(PhantomRefToScalar);
    Info.TaggedMustKills = Info.TaggedMustKills.unite(TaggedMustKill);

    // 2. [param] -> { Stmt[] -> scalar_to_kill[] }
    Info.MustKills = Info.TaggedMustKills.domain_factor_domain();

    // 3. Create the kill schedule of the form:
    //     "[param] -> { Stmt_phantom[] }"
    // Then add this to Info.KillsSchedule.
    isl::space KillStmtSpace = ParamSpace;
    KillStmtSpace = KillStmtSpace.set_tuple_id(isl::dim::set, KillStmtId);
    isl::union_set KillStmtDomain = isl::set::universe(KillStmtSpace);

    isl::schedule KillSchedule = isl::schedule::from_domain(KillStmtDomain);
    if (Info.KillsSchedule)
      Info.KillsSchedule = isl::manage(
          isl_schedule_set(Info.KillsSchedule.release(), KillSchedule.copy()));
    else
      Info.KillsSchedule = KillSchedule;
  }

  return Info;
}

/// Create the ast expressions for a ScopStmt.
///
/// This function is a callback for to generate the ast expressions for each
/// of the scheduled ScopStmts.
static __isl_give isl_id_to_ast_expr *pollyBuildAstExprForStmt(
    void *StmtT, __isl_take isl_ast_build *Build_C,
    isl_multi_pw_aff *(*FunctionIndex)(__isl_take isl_multi_pw_aff *MPA,
                                       isl_id *Id, void *User),
    void *UserIndex,
    isl_ast_expr *(*FunctionExpr)(isl_ast_expr *Expr, isl_id *Id, void *User),
    void *UserExpr) {

  ScopStmt *Stmt = (ScopStmt *)StmtT;

  if (!Stmt || !Build_C)
    return NULL;

  isl::ast_build Build = isl::manage_copy(Build_C);
  isl::ctx Ctx = Build.get_ctx();
  isl::id_to_ast_expr RefToExpr = isl::id_to_ast_expr::alloc(Ctx, 0);

  Stmt->setAstBuild(Build);

  for (MemoryAccess *Acc : *Stmt) {
    isl::map AddrFunc = Acc->getAddressFunction();
    AddrFunc = AddrFunc.intersect_domain(Stmt->getDomain());

    isl::id RefId = Acc->getId();
    isl::pw_multi_aff PMA = isl::pw_multi_aff::from_map(AddrFunc);

    isl::multi_pw_aff MPA = isl::multi_pw_aff(PMA);
    MPA = MPA.coalesce();
    MPA = isl::manage(FunctionIndex(MPA.release(), RefId.get(), UserIndex));

    isl::ast_expr Access = Build.access_from(MPA);
    Access = isl::manage(FunctionExpr(Access.release(), RefId.get(), UserExpr));
    RefToExpr = RefToExpr.set(RefId, Access);
  }

  return RefToExpr.release();
}

/// Given a LLVM Type, compute its size in bytes,
static int computeSizeInBytes(const Type *T) {
  int bytes = T->getPrimitiveSizeInBits() / 8;
  if (bytes == 0)
    bytes = T->getScalarSizeInBits() / 8;
  return bytes;
}

/// Generate code for a GPU specific isl AST.
///
/// The GPUNodeBuilder augments the general existing IslNodeBuilder, which
/// generates code for general-purpose AST nodes, with special functionality
/// for generating GPU specific user nodes.
///
/// @see GPUNodeBuilder::createUser
class GPUNodeBuilder : public IslNodeBuilder {
public:
  GPUNodeBuilder(PollyIRBuilder &Builder, ScopAnnotator &Annotator,
                 const DataLayout &DL, LoopInfo &LI, ScalarEvolution &SE,
                 DominatorTree &DT, Scop &S, BasicBlock *StartBlock,
                 gpu_prog *Prog, GPURuntime Runtime, GPUArch Arch)
      : IslNodeBuilder(Builder, Annotator, DL, LI, SE, DT, S, StartBlock),
        Prog(Prog), Runtime(Runtime), Arch(Arch) {
    getExprBuilder().setIDToSAI(&IDToSAI);
  }

  /// Create after-run-time-check initialization code.
  void initializeAfterRTH();

  /// Finalize the generated scop.
  virtual void finalize();

  /// Track if the full build process was successful.
  ///
  /// This value is set to false, if throughout the build process an error
  /// occurred which prevents us from generating valid GPU code.
  bool BuildSuccessful = true;

  /// The maximal number of loops surrounding a sequential kernel.
  unsigned DeepestSequential = 0;

  /// The maximal number of loops surrounding a parallel kernel.
  unsigned DeepestParallel = 0;

  /// Return the name to set for the ptx_kernel.
  std::string getKernelFuncName(int Kernel_id);

private:
  /// A vector of array base pointers for which a new ScopArrayInfo was created.
  ///
  /// This vector is used to delete the ScopArrayInfo when it is not needed any
  /// more.
  std::vector<Value *> LocalArrays;

  /// A map from ScopArrays to their corresponding device allocations.
  std::map<ScopArrayInfo *, Value *> DeviceAllocations;

  /// The current GPU context.
  Value *GPUContext;

  /// The set of isl_ids allocated in the kernel
  std::vector<isl_id *> KernelIds;

  /// A module containing GPU code.
  ///
  /// This pointer is only set in case we are currently generating GPU code.
  std::unique_ptr<Module> GPUModule;

  /// The GPU program we generate code for.
  gpu_prog *Prog;

  /// The GPU Runtime implementation to use (OpenCL or CUDA).
  GPURuntime Runtime;

  /// The GPU Architecture to target.
  GPUArch Arch;

  /// Class to free isl_ids.
  class IslIdDeleter {
  public:
    void operator()(__isl_take isl_id *Id) { isl_id_free(Id); };
  };

  /// A set containing all isl_ids allocated in a GPU kernel.
  ///
  /// By releasing this set all isl_ids will be freed.
  std::set<std::unique_ptr<isl_id, IslIdDeleter>> KernelIDs;

  IslExprBuilder::IDToScopArrayInfoTy IDToSAI;

  /// Create code for user-defined AST nodes.
  ///
  /// These AST nodes can be of type:
  ///
  ///   - ScopStmt:      A computational statement (TODO)
  ///   - Kernel:        A GPU kernel call (TODO)
  ///   - Data-Transfer: A GPU <-> CPU data-transfer
  ///   - In-kernel synchronization
  ///   - In-kernel memory copy statement
  ///
  /// @param UserStmt The ast node to generate code for.
  virtual void createUser(__isl_take isl_ast_node *UserStmt);

  virtual void createFor(__isl_take isl_ast_node *Node);

  enum DataDirection { HOST_TO_DEVICE, DEVICE_TO_HOST };

  /// Create code for a data transfer statement
  ///
  /// @param TransferStmt The data transfer statement.
  /// @param Direction The direction in which to transfer data.
  void createDataTransfer(__isl_take isl_ast_node *TransferStmt,
                          enum DataDirection Direction);

  /// Find llvm::Values referenced in GPU kernel.
  ///
  /// @param Kernel The kernel to scan for llvm::Values
  ///
  /// @returns A tuple, whose:
  ///          - First element contains the set of values referenced by the
  ///            kernel
  ///          - Second element contains the set of functions referenced by the
  ///             kernel. All functions in the set satisfy
  ///             `isValidFunctionInKernel`.
  ///          - Third element contains loops that have induction variables
  ///            which are used in the kernel, *and* these loops are *neither*
  ///            in the scop, nor do they immediately surroung the Scop.
  ///            See [Code generation of induction variables of loops outside
  ///            Scops]
  std::tuple<SetVector<Value *>, SetVector<Function *>, SetVector<const Loop *>,
             isl::space>
  getReferencesInKernel(ppcg_kernel *Kernel);

  /// Compute the sizes of the execution grid for a given kernel.
  ///
  /// @param Kernel The kernel to compute grid sizes for.
  ///
  /// @returns A tuple with grid sizes for X and Y dimension
  std::tuple<Value *, Value *> getGridSizes(ppcg_kernel *Kernel);

  /// Get the managed array pointer for sending host pointers to the device.
  /// \note
  /// This is to be used only with managed memory
  Value *getManagedDeviceArray(gpu_array_info *Array, ScopArrayInfo *ArrayInfo);

  /// Compute the sizes of the thread blocks for a given kernel.
  ///
  /// @param Kernel The kernel to compute thread block sizes for.
  ///
  /// @returns A tuple with thread block sizes for X, Y, and Z dimensions.
  std::tuple<Value *, Value *, Value *> getBlockSizes(ppcg_kernel *Kernel);

  /// Store a specific kernel launch parameter in the array of kernel launch
  /// parameters.
  ///
  /// @param Parameters The list of parameters in which to store.
  /// @param Param      The kernel launch parameter to store.
  /// @param Index      The index in the parameter list, at which to store the
  ///                   parameter.
  void insertStoreParameter(Instruction *Parameters, Instruction *Param,
                            int Index);

  /// Create kernel launch parameters.
  ///
  /// @param Kernel        The kernel to create parameters for.
  /// @param F             The kernel function that has been created.
  /// @param SubtreeValues The set of llvm::Values referenced by this kernel.
  ///
  /// @returns A stack allocated array with pointers to the parameter
  ///          values that are passed to the kernel.
  Value *createLaunchParameters(ppcg_kernel *Kernel, Function *F,
                                SetVector<Value *> SubtreeValues);

  /// Create declarations for kernel variable.
  ///
  /// This includes shared memory declarations.
  ///
  /// @param Kernel        The kernel definition to create variables for.
  /// @param FN            The function into which to generate the variables.
  void createKernelVariables(ppcg_kernel *Kernel, Function *FN);

  /// Add CUDA annotations to module.
  ///
  /// Add a set of CUDA annotations that declares the maximal block dimensions
  /// that will be used to execute the CUDA kernel. This allows the NVIDIA
  /// PTX compiler to bound the number of allocated registers to ensure the
  /// resulting kernel is known to run with up to as many block dimensions
  /// as specified here.
  ///
  /// @param M         The module to add the annotations to.
  /// @param BlockDimX The size of block dimension X.
  /// @param BlockDimY The size of block dimension Y.
  /// @param BlockDimZ The size of block dimension Z.
  void addCUDAAnnotations(Module *M, Value *BlockDimX, Value *BlockDimY,
                          Value *BlockDimZ);

  /// Create GPU kernel.
  ///
  /// Code generate the kernel described by @p KernelStmt.
  ///
  /// @param KernelStmt The ast node to generate kernel code for.
  void createKernel(__isl_take isl_ast_node *KernelStmt);

  /// Generate code that computes the size of an array.
  ///
  /// @param Array The array for which to compute a size.
  Value *getArraySize(gpu_array_info *Array);

  /// Generate code to compute the minimal offset at which an array is accessed.
  ///
  /// The offset of an array is the minimal array location accessed in a scop.
  ///
  /// Example:
  ///
  ///   for (long i = 0; i < 100; i++)
  ///     A[i + 42] += ...
  ///
  ///   getArrayOffset(A) results in 42.
  ///
  /// @param Array The array for which to compute the offset.
  /// @returns An llvm::Value that contains the offset of the array.
  Value *getArrayOffset(gpu_array_info *Array);

  /// Prepare the kernel arguments for kernel code generation
  ///
  /// @param Kernel The kernel to generate code for.
  /// @param FN     The function created for the kernel.
  void prepareKernelArguments(ppcg_kernel *Kernel, Function *FN);

  /// Create kernel function.
  ///
  /// Create a kernel function located in a newly created module that can serve
  /// as target for device code generation. Set the Builder to point to the
  /// start block of this newly created function.
  ///
  /// @param Kernel The kernel to generate code for.
  /// @param SubtreeValues The set of llvm::Values referenced by this kernel.
  /// @param SubtreeFunctions The set of llvm::Functions referenced by this
  ///                         kernel.
  void createKernelFunction(ppcg_kernel *Kernel,
                            SetVector<Value *> &SubtreeValues,
                            SetVector<Function *> &SubtreeFunctions);

  /// Create the declaration of a kernel function.
  ///
  /// The kernel function takes as arguments:
  ///
  ///   - One i8 pointer for each external array reference used in the kernel.
  ///   - Host iterators
  ///   - Parameters
  ///   - Other LLVM Value references (TODO)
  ///
  /// @param Kernel The kernel to generate the function declaration for.
  /// @param SubtreeValues The set of llvm::Values referenced by this kernel.
  ///
  /// @returns The newly declared function.
  Function *createKernelFunctionDecl(ppcg_kernel *Kernel,
                                     SetVector<Value *> &SubtreeValues);

  /// Insert intrinsic functions to obtain thread and block ids.
  ///
  /// @param The kernel to generate the intrinsic functions for.
  void insertKernelIntrinsics(ppcg_kernel *Kernel);

  /// Insert function calls to retrieve the SPIR group/local ids.
  ///
  /// @param Kernel The kernel to generate the function calls for.
  /// @param SizeTypeIs64Bit Whether size_t of the openCl device is 64bit.
  void insertKernelCallsSPIR(ppcg_kernel *Kernel, bool SizeTypeIs64bit);

  /// Setup the creation of functions referenced by the GPU kernel.
  ///
  /// 1. Create new function declarations in GPUModule which are the same as
  /// SubtreeFunctions.
  ///
  /// 2. Populate IslNodeBuilder::ValueMap with mappings from
  /// old functions (that come from the original module) to new functions
  /// (that are created within GPUModule). That way, we generate references
  /// to the correct function (in GPUModule) in BlockGenerator.
  ///
  /// @see IslNodeBuilder::ValueMap
  /// @see BlockGenerator::GlobalMap
  /// @see BlockGenerator::getNewValue
  /// @see GPUNodeBuilder::getReferencesInKernel.
  ///
  /// @param SubtreeFunctions The set of llvm::Functions referenced by
  ///                         this kernel.
  void setupKernelSubtreeFunctions(SetVector<Function *> SubtreeFunctions);

  /// Create a global-to-shared or shared-to-global copy statement.
  ///
  /// @param CopyStmt The copy statement to generate code for
  void createKernelCopy(ppcg_kernel_stmt *CopyStmt);

  /// Create code for a ScopStmt called in @p Expr.
  ///
  /// @param Expr The expression containing the call.
  /// @param KernelStmt The kernel statement referenced in the call.
  void createScopStmt(isl_ast_expr *Expr, ppcg_kernel_stmt *KernelStmt);

  /// Create an in-kernel synchronization call.
  void createKernelSync();

  /// Create a PTX assembly string for the current GPU kernel.
  ///
  /// @returns A string containing the corresponding PTX assembly code.
  std::string createKernelASM();

  /// Remove references from the dominator tree to the kernel function @p F.
  ///
  /// @param F The function to remove references to.
  void clearDominators(Function *F);

  /// Remove references from scalar evolution to the kernel function @p F.
  ///
  /// @param F The function to remove references to.
  void clearScalarEvolution(Function *F);

  /// Remove references from loop info to the kernel function @p F.
  ///
  /// @param F The function to remove references to.
  void clearLoops(Function *F);

  /// Check if the scop requires to be linked with CUDA's libdevice.
  bool requiresCUDALibDevice();

  /// Link with the NVIDIA libdevice library (if needed and available).
  void addCUDALibDevice();

  /// Finalize the generation of the kernel function.
  ///
  /// Free the LLVM-IR module corresponding to the kernel and -- if requested --
  /// dump its IR to stderr.
  ///
  /// @returns The Assembly string of the kernel.
  std::string finalizeKernelFunction();

  /// Finalize the generation of the kernel arguments.
  ///
  /// This function ensures that not-read-only scalars used in a kernel are
  /// stored back to the global memory location they are backed with before
  /// the kernel terminates.
  ///
  /// @params Kernel The kernel to finalize kernel arguments for.
  void finalizeKernelArguments(ppcg_kernel *Kernel);

  /// Create code that allocates memory to store arrays on device.
  void allocateDeviceArrays();

  /// Create code to prepare the managed device pointers.
  void prepareManagedDeviceArrays();

  /// Free all allocated device arrays.
  void freeDeviceArrays();

  /// Create a call to initialize the GPU context.
  ///
  /// @returns A pointer to the newly initialized context.
  Value *createCallInitContext();

  /// Create a call to get the device pointer for a kernel allocation.
  ///
  /// @param Allocation The Polly GPU allocation
  ///
  /// @returns The device parameter corresponding to this allocation.
  Value *createCallGetDevicePtr(Value *Allocation);

  /// Create a call to free the GPU context.
  ///
  /// @param Context A pointer to an initialized GPU context.
  void createCallFreeContext(Value *Context);

  /// Create a call to allocate memory on the device.
  ///
  /// @param Size The size of memory to allocate
  ///
  /// @returns A pointer that identifies this allocation.
  Value *createCallAllocateMemoryForDevice(Value *Size);

  /// Create a call to free a device array.
  ///
  /// @param Array The device array to free.
  void createCallFreeDeviceMemory(Value *Array);

  /// Create a call to copy data from host to device.
  ///
  /// @param HostPtr A pointer to the host data that should be copied.
  /// @param DevicePtr A device pointer specifying the location to copy to.
  void createCallCopyFromHostToDevice(Value *HostPtr, Value *DevicePtr,
                                      Value *Size);

  /// Create a call to copy data from device to host.
  ///
  /// @param DevicePtr A pointer to the device data that should be copied.
  /// @param HostPtr A host pointer specifying the location to copy to.
  void createCallCopyFromDeviceToHost(Value *DevicePtr, Value *HostPtr,
                                      Value *Size);

  /// Create a call to synchronize Host & Device.
  /// \note
  /// This is to be used only with managed memory.
  void createCallSynchronizeDevice();

  /// Create a call to get a kernel from an assembly string.
  ///
  /// @param Buffer The string describing the kernel.
  /// @param Entry  The name of the kernel function to call.
  ///
  /// @returns A pointer to a kernel object
  Value *createCallGetKernel(Value *Buffer, Value *Entry);

  /// Create a call to free a GPU kernel.
  ///
  /// @param GPUKernel THe kernel to free.
  void createCallFreeKernel(Value *GPUKernel);

  /// Create a call to launch a GPU kernel.
  ///
  /// @param GPUKernel  The kernel to launch.
  /// @param GridDimX   The size of the first grid dimension.
  /// @param GridDimY   The size of the second grid dimension.
  /// @param GridBlockX The size of the first block dimension.
  /// @param GridBlockY The size of the second block dimension.
  /// @param GridBlockZ The size of the third block dimension.
  /// @param Parameters A pointer to an array that contains itself pointers to
  ///                   the parameter values passed for each kernel argument.
  void createCallLaunchKernel(Value *GPUKernel, Value *GridDimX,
                              Value *GridDimY, Value *BlockDimX,
                              Value *BlockDimY, Value *BlockDimZ,
                              Value *Parameters);
};

std::string GPUNodeBuilder::getKernelFuncName(int Kernel_id) {
  return "FUNC_" + S.getFunction().getName().str() + "_SCOP_" +
         std::to_string(S.getID()) + "_KERNEL_" + std::to_string(Kernel_id);
}

void GPUNodeBuilder::initializeAfterRTH() {
  BasicBlock *NewBB = SplitBlock(Builder.GetInsertBlock(),
                                 &*Builder.GetInsertPoint(), &DT, &LI);
  NewBB->setName("polly.acc.initialize");
  Builder.SetInsertPoint(&NewBB->front());

  GPUContext = createCallInitContext();

  if (!PollyManagedMemory)
    allocateDeviceArrays();
  else
    prepareManagedDeviceArrays();
}

void GPUNodeBuilder::finalize() {
  if (!PollyManagedMemory)
    freeDeviceArrays();

  createCallFreeContext(GPUContext);
  IslNodeBuilder::finalize();
}

void GPUNodeBuilder::allocateDeviceArrays() {
  assert(!PollyManagedMemory &&
         "Managed memory will directly send host pointers "
         "to the kernel. There is no need for device arrays");
  isl_ast_build *Build = isl_ast_build_from_context(S.getContext().release());

  for (int i = 0; i < Prog->n_array; ++i) {
    gpu_array_info *Array = &Prog->array[i];
    auto *ScopArray = (ScopArrayInfo *)Array->user;
    std::string DevArrayName("p_dev_array_");
    DevArrayName.append(Array->name);

    Value *ArraySize = getArraySize(Array);
    Value *Offset = getArrayOffset(Array);
    if (Offset)
      ArraySize = Builder.CreateSub(
          ArraySize,
          Builder.CreateMul(Offset,
                            Builder.getInt64(ScopArray->getElemSizeInBytes())));
    const SCEV *SizeSCEV = SE.getSCEV(ArraySize);
    // It makes no sense to have an array of size 0. The CUDA API will
    // throw an error anyway if we invoke `cuMallocManaged` with size `0`. We
    // choose to be defensive and catch this at the compile phase. It is
    // most likely that we are doing something wrong with size computation.
    if (SizeSCEV->isZero()) {
      errs() << getUniqueScopName(&S)
             << " has computed array size 0: " << *ArraySize
             << " | for array: " << *(ScopArray->getBasePtr())
             << ". This is illegal, exiting.\n";
      report_fatal_error("array size was computed to be 0");
    }

    Value *DevArray = createCallAllocateMemoryForDevice(ArraySize);
    DevArray->setName(DevArrayName);
    DeviceAllocations[ScopArray] = DevArray;
  }

  isl_ast_build_free(Build);
}

void GPUNodeBuilder::prepareManagedDeviceArrays() {
  assert(PollyManagedMemory &&
         "Device array most only be prepared in managed-memory mode");
  for (int i = 0; i < Prog->n_array; ++i) {
    gpu_array_info *Array = &Prog->array[i];
    ScopArrayInfo *ScopArray = (ScopArrayInfo *)Array->user;
    Value *HostPtr;

    if (gpu_array_is_scalar(Array))
      HostPtr = BlockGen.getOrCreateAlloca(ScopArray);
    else
      HostPtr = ScopArray->getBasePtr();
    HostPtr = getLatestValue(HostPtr);

    Value *Offset = getArrayOffset(Array);
    if (Offset) {
      HostPtr = Builder.CreatePointerCast(
          HostPtr, ScopArray->getElementType()->getPointerTo());
      HostPtr = Builder.CreateGEP(HostPtr, Offset);
    }

    HostPtr = Builder.CreatePointerCast(HostPtr, Builder.getInt8PtrTy());
    DeviceAllocations[ScopArray] = HostPtr;
  }
}

void GPUNodeBuilder::addCUDAAnnotations(Module *M, Value *BlockDimX,
                                        Value *BlockDimY, Value *BlockDimZ) {
  auto AnnotationNode = M->getOrInsertNamedMetadata("nvvm.annotations");

  for (auto &F : *M) {
    if (F.getCallingConv() != CallingConv::PTX_Kernel)
      continue;

    Value *V[] = {BlockDimX, BlockDimY, BlockDimZ};

    Metadata *Elements[] = {
        ValueAsMetadata::get(&F),   MDString::get(M->getContext(), "maxntidx"),
        ValueAsMetadata::get(V[0]), MDString::get(M->getContext(), "maxntidy"),
        ValueAsMetadata::get(V[1]), MDString::get(M->getContext(), "maxntidz"),
        ValueAsMetadata::get(V[2]),
    };
    MDNode *Node = MDNode::get(M->getContext(), Elements);
    AnnotationNode->addOperand(Node);
  }
}

void GPUNodeBuilder::freeDeviceArrays() {
  assert(!PollyManagedMemory && "Managed memory does not use device arrays");
  for (auto &Array : DeviceAllocations)
    createCallFreeDeviceMemory(Array.second);
}

Value *GPUNodeBuilder::createCallGetKernel(Value *Buffer, Value *Entry) {
  const char *Name = "polly_getKernel";
  Module *M = Builder.GetInsertBlock()->getParent()->getParent();
  Function *F = M->getFunction(Name);

  // If F is not available, declare it.
  if (!F) {
    GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage;
    std::vector<Type *> Args;
    Args.push_back(Builder.getInt8PtrTy());
    Args.push_back(Builder.getInt8PtrTy());
    FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false);
    F = Function::Create(Ty, Linkage, Name, M);
  }

  return Builder.CreateCall(F, {Buffer, Entry});
}

Value *GPUNodeBuilder::createCallGetDevicePtr(Value *Allocation) {
  const char *Name = "polly_getDevicePtr";
  Module *M = Builder.GetInsertBlock()->getParent()->getParent();
  Function *F = M->getFunction(Name);

  // If F is not available, declare it.
  if (!F) {
    GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage;
    std::vector<Type *> Args;
    Args.push_back(Builder.getInt8PtrTy());
    FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false);
    F = Function::Create(Ty, Linkage, Name, M);
  }

  return Builder.CreateCall(F, {Allocation});
}

void GPUNodeBuilder::createCallLaunchKernel(Value *GPUKernel, Value *GridDimX,
                                            Value *GridDimY, Value *BlockDimX,
                                            Value *BlockDimY, Value *BlockDimZ,
                                            Value *Parameters) {
  const char *Name = "polly_launchKernel";
  Module *M = Builder.GetInsertBlock()->getParent()->getParent();
  Function *F = M->getFunction(Name);

  // If F is not available, declare it.
  if (!F) {
    GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage;
    std::vector<Type *> Args;
    Args.push_back(Builder.getInt8PtrTy());
    Args.push_back(Builder.getInt32Ty());
    Args.push_back(Builder.getInt32Ty());
    Args.push_back(Builder.getInt32Ty());
    Args.push_back(Builder.getInt32Ty());
    Args.push_back(Builder.getInt32Ty());
    Args.push_back(Builder.getInt8PtrTy());
    FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false);
    F = Function::Create(Ty, Linkage, Name, M);
  }

  Builder.CreateCall(F, {GPUKernel, GridDimX, GridDimY, BlockDimX, BlockDimY,
                         BlockDimZ, Parameters});
}

void GPUNodeBuilder::createCallFreeKernel(Value *GPUKernel) {
  const char *Name = "polly_freeKernel";
  Module *M = Builder.GetInsertBlock()->getParent()->getParent();
  Function *F = M->getFunction(Name);

  // If F is not available, declare it.
  if (!F) {
    GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage;
    std::vector<Type *> Args;
    Args.push_back(Builder.getInt8PtrTy());
    FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false);
    F = Function::Create(Ty, Linkage, Name, M);
  }

  Builder.CreateCall(F, {GPUKernel});
}

void GPUNodeBuilder::createCallFreeDeviceMemory(Value *Array) {
  assert(!PollyManagedMemory &&
         "Managed memory does not allocate or free memory "
         "for device");
  const char *Name = "polly_freeDeviceMemory";
  Module *M = Builder.GetInsertBlock()->getParent()->getParent();
  Function *F = M->getFunction(Name);

  // If F is not available, declare it.
  if (!F) {
    GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage;
    std::vector<Type *> Args;
    Args.push_back(Builder.getInt8PtrTy());
    FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false);
    F = Function::Create(Ty, Linkage, Name, M);
  }

  Builder.CreateCall(F, {Array});
}

Value *GPUNodeBuilder::createCallAllocateMemoryForDevice(Value *Size) {
  assert(!PollyManagedMemory &&
         "Managed memory does not allocate or free memory "
         "for device");
  const char *Name = "polly_allocateMemoryForDevice";
  Module *M = Builder.GetInsertBlock()->getParent()->getParent();
  Function *F = M->getFunction(Name);

  // If F is not available, declare it.
  if (!F) {
    GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage;
    std::vector<Type *> Args;
    Args.push_back(Builder.getInt64Ty());
    FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false);
    F = Function::Create(Ty, Linkage, Name, M);
  }

  return Builder.CreateCall(F, {Size});
}

void GPUNodeBuilder::createCallCopyFromHostToDevice(Value *HostData,
                                                    Value *DeviceData,
                                                    Value *Size) {
  assert(!PollyManagedMemory &&
         "Managed memory does not transfer memory between "
         "device and host");
  const char *Name = "polly_copyFromHostToDevice";
  Module *M = Builder.GetInsertBlock()->getParent()->getParent();
  Function *F = M->getFunction(Name);

  // If F is not available, declare it.
  if (!F) {
    GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage;
    std::vector<Type *> Args;
    Args.push_back(Builder.getInt8PtrTy());
    Args.push_back(Builder.getInt8PtrTy());
    Args.push_back(Builder.getInt64Ty());
    FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false);
    F = Function::Create(Ty, Linkage, Name, M);
  }

  Builder.CreateCall(F, {HostData, DeviceData, Size});
}

void GPUNodeBuilder::createCallCopyFromDeviceToHost(Value *DeviceData,
                                                    Value *HostData,
                                                    Value *Size) {
  assert(!PollyManagedMemory &&
         "Managed memory does not transfer memory between "
         "device and host");
  const char *Name = "polly_copyFromDeviceToHost";
  Module *M = Builder.GetInsertBlock()->getParent()->getParent();
  Function *F = M->getFunction(Name);

  // If F is not available, declare it.
  if (!F) {
    GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage;
    std::vector<Type *> Args;
    Args.push_back(Builder.getInt8PtrTy());
    Args.push_back(Builder.getInt8PtrTy());
    Args.push_back(Builder.getInt64Ty());
    FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false);
    F = Function::Create(Ty, Linkage, Name, M);
  }

  Builder.CreateCall(F, {DeviceData, HostData, Size});
}

void GPUNodeBuilder::createCallSynchronizeDevice() {
  assert(PollyManagedMemory && "explicit synchronization is only necessary for "
                               "managed memory");
  const char *Name = "polly_synchronizeDevice";
  Module *M = Builder.GetInsertBlock()->getParent()->getParent();
  Function *F = M->getFunction(Name);

  // If F is not available, declare it.
  if (!F) {
    GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage;
    FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), false);
    F = Function::Create(Ty, Linkage, Name, M);
  }

  Builder.CreateCall(F);
}

Value *GPUNodeBuilder::createCallInitContext() {
  const char *Name;

  switch (Runtime) {
  case GPURuntime::CUDA:
    Name = "polly_initContextCUDA";
    break;
  case GPURuntime::OpenCL:
    Name = "polly_initContextCL";
    break;
  }

  Module *M = Builder.GetInsertBlock()->getParent()->getParent();
  Function *F = M->getFunction(Name);

  // If F is not available, declare it.
  if (!F) {
    GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage;
    std::vector<Type *> Args;
    FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false);
    F = Function::Create(Ty, Linkage, Name, M);
  }

  return Builder.CreateCall(F, {});
}

void GPUNodeBuilder::createCallFreeContext(Value *Context) {
  const char *Name = "polly_freeContext";
  Module *M = Builder.GetInsertBlock()->getParent()->getParent();
  Function *F = M->getFunction(Name);

  // If F is not available, declare it.
  if (!F) {
    GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage;
    std::vector<Type *> Args;
    Args.push_back(Builder.getInt8PtrTy());
    FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false);
    F = Function::Create(Ty, Linkage, Name, M);
  }

  Builder.CreateCall(F, {Context});
}

/// Check if one string is a prefix of another.
///
/// @param String The string in which to look for the prefix.
/// @param Prefix The prefix to look for.
static bool isPrefix(std::string String, std::string Prefix) {
  return String.find(Prefix) == 0;
}

Value *GPUNodeBuilder::getArraySize(gpu_array_info *Array) {
  isl::ast_build Build = isl::ast_build::from_context(S.getContext());
  Value *ArraySize = ConstantInt::get(Builder.getInt64Ty(), Array->size);

  if (!gpu_array_is_scalar(Array)) {
    isl::multi_pw_aff ArrayBound = isl::manage_copy(Array->bound);

    isl::pw_aff OffsetDimZero = ArrayBound.get_pw_aff(0);
    isl::ast_expr Res = Build.expr_from(OffsetDimZero);

    for (unsigned int i = 1; i < Array->n_index; i++) {
      isl::pw_aff Bound_I = ArrayBound.get_pw_aff(i);
      isl::ast_expr Expr = Build.expr_from(Bound_I);
      Res = Res.mul(Expr);
    }

    Value *NumElements = ExprBuilder.create(Res.release());
    if (NumElements->getType() != ArraySize->getType())
      NumElements = Builder.CreateSExt(NumElements, ArraySize->getType());
    ArraySize = Builder.CreateMul(ArraySize, NumElements);
  }
  return ArraySize;
}

Value *GPUNodeBuilder::getArrayOffset(gpu_array_info *Array) {
  if (gpu_array_is_scalar(Array))
    return nullptr;

  isl::ast_build Build = isl::ast_build::from_context(S.getContext());

  isl::set Min = isl::manage_copy(Array->extent).lexmin();

  isl::set ZeroSet = isl::set::universe(Min.get_space());

  for (long i = 0, n = Min.dim(isl::dim::set); i < n; i++)
    ZeroSet = ZeroSet.fix_si(isl::dim::set, i, 0);

  if (Min.is_subset(ZeroSet)) {
    return nullptr;
  }

  isl::ast_expr Result = isl::ast_expr::from_val(isl::val(Min.get_ctx(), 0));

  for (long i = 0, n = Min.dim(isl::dim::set); i < n; i++) {
    if (i > 0) {
      isl::pw_aff Bound_I =
          isl::manage(isl_multi_pw_aff_get_pw_aff(Array->bound, i - 1));
      isl::ast_expr BExpr = Build.expr_from(Bound_I);
      Result = Result.mul(BExpr);
    }
    isl::pw_aff DimMin = Min.dim_min(i);
    isl::ast_expr MExpr = Build.expr_from(DimMin);
    Result = Result.add(MExpr);
  }

  return ExprBuilder.create(Result.release());
}

Value *GPUNodeBuilder::getManagedDeviceArray(gpu_array_info *Array,
                                             ScopArrayInfo *ArrayInfo) {
  assert(PollyManagedMemory && "Only used when you wish to get a host "
                               "pointer for sending data to the kernel, "
                               "with managed memory");
  std::map<ScopArrayInfo *, Value *>::iterator it;
  it = DeviceAllocations.find(ArrayInfo);
  assert(it != DeviceAllocations.end() &&
         "Device array expected to be available");
  return it->second;
}

void GPUNodeBuilder::createDataTransfer(__isl_take isl_ast_node *TransferStmt,
                                        enum DataDirection Direction) {
  assert(!PollyManagedMemory && "Managed memory needs no data transfers");
  isl_ast_expr *Expr = isl_ast_node_user_get_expr(TransferStmt);
  isl_ast_expr *Arg = isl_ast_expr_get_op_arg(Expr, 0);
  isl_id *Id = isl_ast_expr_get_id(Arg);
  auto Array = (gpu_array_info *)isl_id_get_user(Id);
  auto ScopArray = (ScopArrayInfo *)(Array->user);

  Value *Size = getArraySize(Array);
  Value *Offset = getArrayOffset(Array);
  Value *DevPtr = DeviceAllocations[ScopArray];

  Value *HostPtr;

  if (gpu_array_is_scalar(Array))
    HostPtr = BlockGen.getOrCreateAlloca(ScopArray);
  else
    HostPtr = ScopArray->getBasePtr();
  HostPtr = getLatestValue(HostPtr);

  if (Offset) {
    HostPtr = Builder.CreatePointerCast(
        HostPtr, ScopArray->getElementType()->getPointerTo());
    HostPtr = Builder.CreateGEP(HostPtr, Offset);
  }

  HostPtr = Builder.CreatePointerCast(HostPtr, Builder.getInt8PtrTy());

  if (Offset) {
    Size = Builder.CreateSub(
        Size, Builder.CreateMul(
                  Offset, Builder.getInt64(ScopArray->getElemSizeInBytes())));
  }

  if (Direction == HOST_TO_DEVICE)
    createCallCopyFromHostToDevice(HostPtr, DevPtr, Size);
  else
    createCallCopyFromDeviceToHost(DevPtr, HostPtr, Size);

  isl_id_free(Id);
  isl_ast_expr_free(Arg);
  isl_ast_expr_free(Expr);
  isl_ast_node_free(TransferStmt);
}

void GPUNodeBuilder::createUser(__isl_take isl_ast_node *UserStmt) {
  isl_ast_expr *Expr = isl_ast_node_user_get_expr(UserStmt);
  isl_ast_expr *StmtExpr = isl_ast_expr_get_op_arg(Expr, 0);
  isl_id *Id = isl_ast_expr_get_id(StmtExpr);
  isl_id_free(Id);
  isl_ast_expr_free(StmtExpr);

  const char *Str = isl_id_get_name(Id);
  if (!strcmp(Str, "kernel")) {
    createKernel(UserStmt);
    if (PollyManagedMemory)
      createCallSynchronizeDevice();
    isl_ast_expr_free(Expr);
    return;
  }
  if (!strcmp(Str, "init_device")) {
    initializeAfterRTH();
    isl_ast_node_free(UserStmt);
    isl_ast_expr_free(Expr);
    return;
  }
  if (!strcmp(Str, "clear_device")) {
    finalize();
    isl_ast_node_free(UserStmt);
    isl_ast_expr_free(Expr);
    return;
  }
  if (isPrefix(Str, "to_device")) {
    if (!PollyManagedMemory)
      createDataTransfer(UserStmt, HOST_TO_DEVICE);
    else
      isl_ast_node_free(UserStmt);

    isl_ast_expr_free(Expr);
    return;
  }

  if (isPrefix(Str, "from_device")) {
    if (!PollyManagedMemory) {
      createDataTransfer(UserStmt, DEVICE_TO_HOST);
    } else {
      isl_ast_node_free(UserStmt);
    }
    isl_ast_expr_free(Expr);
    return;
  }

  isl_id *Anno = isl_ast_node_get_annotation(UserStmt);
  struct ppcg_kernel_stmt *KernelStmt =
      (struct ppcg_kernel_stmt *)isl_id_get_user(Anno);
  isl_id_free(Anno);

  switch (KernelStmt->type) {
  case ppcg_kernel_domain:
    createScopStmt(Expr, KernelStmt);
    isl_ast_node_free(UserStmt);
    return;
  case ppcg_kernel_copy:
    createKernelCopy(KernelStmt);
    isl_ast_expr_free(Expr);
    isl_ast_node_free(UserStmt);
    return;
  case ppcg_kernel_sync:
    createKernelSync();
    isl_ast_expr_free(Expr);
    isl_ast_node_free(UserStmt);
    return;
  }

  isl_ast_expr_free(Expr);
  isl_ast_node_free(UserStmt);
}

void GPUNodeBuilder::createFor(__isl_take isl_ast_node *Node) {
  createForSequential(isl::manage(Node), false);
}

void GPUNodeBuilder::createKernelCopy(ppcg_kernel_stmt *KernelStmt) {
  isl_ast_expr *LocalIndex = isl_ast_expr_copy(KernelStmt->u.c.local_index);
  LocalIndex = isl_ast_expr_address_of(LocalIndex);
  Value *LocalAddr = ExprBuilder.create(LocalIndex);
  isl_ast_expr *Index = isl_ast_expr_copy(KernelStmt->u.c.index);
  Index = isl_ast_expr_address_of(Index);
  Value *GlobalAddr = ExprBuilder.create(Index);

  if (KernelStmt->u.c.read) {
    LoadInst *Load = Builder.CreateLoad(GlobalAddr, "shared.read");
    Builder.CreateStore(Load, LocalAddr);
  } else {
    LoadInst *Load = Builder.CreateLoad(LocalAddr, "shared.write");
    Builder.CreateStore(Load, GlobalAddr);
  }
}

void GPUNodeBuilder::createScopStmt(isl_ast_expr *Expr,
                                    ppcg_kernel_stmt *KernelStmt) {
  auto Stmt = (ScopStmt *)KernelStmt->u.d.stmt->stmt;
  isl_id_to_ast_expr *Indexes = KernelStmt->u.d.ref2expr;

  LoopToScevMapT LTS;
  LTS.insert(OutsideLoopIterations.begin(), OutsideLoopIterations.end());

  createSubstitutions(Expr, Stmt, LTS);

  if (Stmt->isBlockStmt())
    BlockGen.copyStmt(*Stmt, LTS, Indexes);
  else
    RegionGen.copyStmt(*Stmt, LTS, Indexes);
}

void GPUNodeBuilder::createKernelSync() {
  Module *M = Builder.GetInsertBlock()->getParent()->getParent();
  const char *SpirName = "__gen_ocl_barrier_global";

  Function *Sync;

  switch (Arch) {
  case GPUArch::SPIR64:
  case GPUArch::SPIR32:
    Sync = M->getFunction(SpirName);

    // If Sync is not available, declare it.
    if (!Sync) {
      GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage;
      std::vector<Type *> Args;
      FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false);
      Sync = Function::Create(Ty, Linkage, SpirName, M);
      Sync->setCallingConv(CallingConv::SPIR_FUNC);
    }
    break;
  case GPUArch::NVPTX64:
    Sync = Intrinsic::getDeclaration(M, Intrinsic::nvvm_barrier0);
    break;
  }

  Builder.CreateCall(Sync, {});
}

/// Collect llvm::Values referenced from @p Node
///
/// This function only applies to isl_ast_nodes that are user_nodes referring
/// to a ScopStmt. All other node types are ignore.
///
/// @param Node The node to collect references for.
/// @param User A user pointer used as storage for the data that is collected.
///
/// @returns isl_bool_true if data could be collected successfully.
isl_bool collectReferencesInGPUStmt(__isl_keep isl_ast_node *Node, void *User) {
  if (isl_ast_node_get_type(Node) != isl_ast_node_user)
    return isl_bool_true;

  isl_ast_expr *Expr = isl_ast_node_user_get_expr(Node);
  isl_ast_expr *StmtExpr = isl_ast_expr_get_op_arg(Expr, 0);
  isl_id *Id = isl_ast_expr_get_id(StmtExpr);
  const char *Str = isl_id_get_name(Id);
  isl_id_free(Id);
  isl_ast_expr_free(StmtExpr);
  isl_ast_expr_free(Expr);

  if (!isPrefix(Str, "Stmt"))
    return isl_bool_true;

  Id = isl_ast_node_get_annotation(Node);
  auto *KernelStmt = (ppcg_kernel_stmt *)isl_id_get_user(Id);
  auto Stmt = (ScopStmt *)KernelStmt->u.d.stmt->stmt;
  isl_id_free(Id);

  addReferencesFromStmt(Stmt, User, false /* CreateScalarRefs */);

  return isl_bool_true;
}

/// A list of functions that are available in NVIDIA's libdevice.
const std::set<std::string> CUDALibDeviceFunctions = {
    "exp",      "expf",      "expl",      "cos", "cosf", "sqrt", "sqrtf",
    "copysign", "copysignf", "copysignl", "log", "logf", "powi", "powif"};

// A map from intrinsics to their corresponding libdevice functions.
const std::map<std::string, std::string> IntrinsicToLibdeviceFunc = {
    {"llvm.exp.f64", "exp"},
    {"llvm.exp.f32", "expf"},
    {"llvm.powi.f64", "powi"},
    {"llvm.powi.f32", "powif"}};

/// Return the corresponding CUDA libdevice function name @p Name.
/// Note that this function will try to convert instrinsics in the list
/// IntrinsicToLibdeviceFunc into libdevice functions.
/// This is because some intrinsics such as `exp`
/// are not supported by the NVPTX backend.
/// If this restriction of the backend is lifted, we should refactor our code
/// so that we use intrinsics whenever possible.
///
/// Return "" if we are not compiling for CUDA.
std::string getCUDALibDeviceFuntion(StringRef Name) {
  auto It = IntrinsicToLibdeviceFunc.find(Name);
  if (It != IntrinsicToLibdeviceFunc.end())
    return getCUDALibDeviceFuntion(It->second);

  if (CUDALibDeviceFunctions.count(Name))
    return ("__nv_" + Name).str();

  return "";
}

/// Check if F is a function that we can code-generate in a GPU kernel.
static bool isValidFunctionInKernel(llvm::Function *F, bool AllowLibDevice) {
  assert(F && "F is an invalid pointer");
  // We string compare against the name of the function to allow
  // all variants of the intrinsic "llvm.sqrt.*", "llvm.fabs", and
  // "llvm.copysign".
  const StringRef Name = F->getName();

  if (AllowLibDevice && getCUDALibDeviceFuntion(Name).length() > 0)
    return true;

  return F->isIntrinsic() &&
         (Name.startswith("llvm.sqrt") || Name.startswith("llvm.fabs") ||
          Name.startswith("llvm.copysign"));
}

/// Do not take `Function` as a subtree value.
///
/// We try to take the reference of all subtree values and pass them along
/// to the kernel from the host. Taking an address of any function and
/// trying to pass along is nonsensical. Only allow `Value`s that are not
/// `Function`s.
static bool isValidSubtreeValue(llvm::Value *V) { return !isa<Function>(V); }

/// Return `Function`s from `RawSubtreeValues`.
static SetVector<Function *>
getFunctionsFromRawSubtreeValues(SetVector<Value *> RawSubtreeValues,
                                 bool AllowCUDALibDevice) {
  SetVector<Function *> SubtreeFunctions;
  for (Value *It : RawSubtreeValues) {
    Function *F = dyn_cast<Function>(It);
    if (F) {
      assert(isValidFunctionInKernel(F, AllowCUDALibDevice) &&
             "Code should have bailed out by "
             "this point if an invalid function "
             "were present in a kernel.");
      SubtreeFunctions.insert(F);
    }
  }
  return SubtreeFunctions;
}

std::tuple<SetVector<Value *>, SetVector<Function *>, SetVector<const Loop *>,
           isl::space>
GPUNodeBuilder::getReferencesInKernel(ppcg_kernel *Kernel) {
  SetVector<Value *> SubtreeValues;
  SetVector<const SCEV *> SCEVs;
  SetVector<const Loop *> Loops;
  isl::space ParamSpace = isl::space(S.getIslCtx(), 0, 0).params();
  SubtreeReferences References = {
      LI,         SE, S, ValueMap, SubtreeValues, SCEVs, getBlockGenerator(),
      &ParamSpace};

  for (const auto &I : IDToValue)
    SubtreeValues.insert(I.second);

  // NOTE: this is populated in IslNodeBuilder::addParameters
  // See [Code generation of induction variables of loops outside Scops].
  for (const auto &I : OutsideLoopIterations)
    SubtreeValues.insert(cast<SCEVUnknown>(I.second)->getValue());

  isl_ast_node_foreach_descendant_top_down(
      Kernel->tree, collectReferencesInGPUStmt, &References);

  for (const SCEV *Expr : SCEVs) {
    findValues(Expr, SE, SubtreeValues);
    findLoops(Expr, Loops);
  }

  Loops.remove_if([this](const Loop *L) {
    return S.contains(L) || L->contains(S.getEntry());
  });

  for (auto &SAI : S.arrays())
    SubtreeValues.remove(SAI->getBasePtr());

  isl_space *Space = S.getParamSpace().release();
  for (long i = 0, n = isl_space_dim(Space, isl_dim_param); i < n; i++) {
    isl_id *Id = isl_space_get_dim_id(Space, isl_dim_param, i);
    assert(IDToValue.count(Id));
    Value *Val = IDToValue[Id];
    SubtreeValues.remove(Val);
    isl_id_free(Id);
  }
  isl_space_free(Space);

  for (long i = 0, n = isl_space_dim(Kernel->space, isl_dim_set); i < n; i++) {
    isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i);
    assert(IDToValue.count(Id));
    Value *Val = IDToValue[Id];
    SubtreeValues.remove(Val);
    isl_id_free(Id);
  }

  // Note: { ValidSubtreeValues, ValidSubtreeFunctions } partitions
  // SubtreeValues. This is important, because we should not lose any
  // SubtreeValues in the process of constructing the
  // "ValidSubtree{Values, Functions} sets. Nor should the set
  // ValidSubtree{Values, Functions} have any common element.
  auto ValidSubtreeValuesIt =
      make_filter_range(SubtreeValues, isValidSubtreeValue);
  SetVector<Value *> ValidSubtreeValues(ValidSubtreeValuesIt.begin(),
                                        ValidSubtreeValuesIt.end());

  bool AllowCUDALibDevice = Arch == GPUArch::NVPTX64;

  SetVector<Function *> ValidSubtreeFunctions(
      getFunctionsFromRawSubtreeValues(SubtreeValues, AllowCUDALibDevice));

  // @see IslNodeBuilder::getReferencesInSubtree
  SetVector<Value *> ReplacedValues;
  for (Value *V : ValidSubtreeValues) {
    auto It = ValueMap.find(V);
    if (It == ValueMap.end())
      ReplacedValues.insert(V);
    else
      ReplacedValues.insert(It->second);
  }
  return std::make_tuple(ReplacedValues, ValidSubtreeFunctions, Loops,
                         ParamSpace);
}

void GPUNodeBuilder::clearDominators(Function *F) {
  DomTreeNode *N = DT.getNode(&F->getEntryBlock());
  std::vector<BasicBlock *> Nodes;
  for (po_iterator<DomTreeNode *> I = po_begin(N), E = po_end(N); I != E; ++I)
    Nodes.push_back(I->getBlock());

  for (BasicBlock *BB : Nodes)
    DT.eraseNode(BB);
}

void GPUNodeBuilder::clearScalarEvolution(Function *F) {
  for (BasicBlock &BB : *F) {
    Loop *L = LI.getLoopFor(&BB);
    if (L)
      SE.forgetLoop(L);
  }
}

void GPUNodeBuilder::clearLoops(Function *F) {
  SmallSet<Loop *, 1> WorkList;
  for (BasicBlock &BB : *F) {
    Loop *L = LI.getLoopFor(&BB);
    if (L)
      WorkList.insert(L);
  }
  for (auto *L : WorkList)
    LI.erase(L);
}

std::tuple<Value *, Value *> GPUNodeBuilder::getGridSizes(ppcg_kernel *Kernel) {
  std::vector<Value *> Sizes;
  isl::ast_build Context = isl::ast_build::from_context(S.getContext());

  isl::multi_pw_aff GridSizePwAffs = isl::manage_copy(Kernel->grid_size);
  for (long i = 0; i < Kernel->n_grid; i++) {
    isl::pw_aff Size = GridSizePwAffs.get_pw_aff(i);
    isl::ast_expr GridSize = Context.expr_from(Size);
    Value *Res = ExprBuilder.create(GridSize.release());
    Res = Builder.CreateTrunc(Res, Builder.getInt32Ty());
    Sizes.push_back(Res);
  }

  for (long i = Kernel->n_grid; i < 3; i++)
    Sizes.push_back(ConstantInt::get(Builder.getInt32Ty(), 1));

  return std::make_tuple(Sizes[0], Sizes[1]);
}

std::tuple<Value *, Value *, Value *>
GPUNodeBuilder::getBlockSizes(ppcg_kernel *Kernel) {
  std::vector<Value *> Sizes;

  for (long i = 0; i < Kernel->n_block; i++) {
    Value *Res = ConstantInt::get(Builder.getInt32Ty(), Kernel->block_dim[i]);
    Sizes.push_back(Res);
  }

  for (long i = Kernel->n_block; i < 3; i++)
    Sizes.push_back(ConstantInt::get(Builder.getInt32Ty(), 1));

  return std::make_tuple(Sizes[0], Sizes[1], Sizes[2]);
}

void GPUNodeBuilder::insertStoreParameter(Instruction *Parameters,
                                          Instruction *Param, int Index) {
  Value *Slot = Builder.CreateGEP(
      Parameters, {Builder.getInt64(0), Builder.getInt64(Index)});
  Value *ParamTyped = Builder.CreatePointerCast(Param, Builder.getInt8PtrTy());
  Builder.CreateStore(ParamTyped, Slot);
}

Value *
GPUNodeBuilder::createLaunchParameters(ppcg_kernel *Kernel, Function *F,
                                       SetVector<Value *> SubtreeValues) {
  const int NumArgs = F->arg_size();
  std::vector<int> ArgSizes(NumArgs);

  // If we are using the OpenCL Runtime, we need to add the kernel argument
  // sizes to the end of the launch-parameter list, so OpenCL can determine
  // how big the respective kernel arguments are.
  // Here we need to reserve adequate space for that.
  Type *ArrayTy;
  if (Runtime == GPURuntime::OpenCL)
    ArrayTy = ArrayType::get(Builder.getInt8PtrTy(), 2 * NumArgs);
  else
    ArrayTy = ArrayType::get(Builder.getInt8PtrTy(), NumArgs);

  BasicBlock *EntryBlock =
      &Builder.GetInsertBlock()->getParent()->getEntryBlock();
  auto AddressSpace = F->getParent()->getDataLayout().getAllocaAddrSpace();
  std::string Launch = "polly_launch_" + std::to_string(Kernel->id);
  Instruction *Parameters = new AllocaInst(
      ArrayTy, AddressSpace, Launch + "_params", EntryBlock->getTerminator());

  int Index = 0;
  for (long i = 0; i < Prog->n_array; i++) {
    if (!ppcg_kernel_requires_array_argument(Kernel, i))
      continue;

    isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set);
    const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl::manage(Id));

    if (Runtime == GPURuntime::OpenCL)
      ArgSizes[Index] = SAI->getElemSizeInBytes();

    Value *DevArray = nullptr;
    if (PollyManagedMemory) {
      DevArray = getManagedDeviceArray(&Prog->array[i],
                                       const_cast<ScopArrayInfo *>(SAI));
    } else {
      DevArray = DeviceAllocations[const_cast<ScopArrayInfo *>(SAI)];
      DevArray = createCallGetDevicePtr(DevArray);
    }
    assert(DevArray != nullptr && "Array to be offloaded to device not "
                                  "initialized");
    Value *Offset = getArrayOffset(&Prog->array[i]);

    if (Offset) {
      DevArray = Builder.CreatePointerCast(
          DevArray, SAI->getElementType()->getPointerTo());
      DevArray = Builder.CreateGEP(DevArray, Builder.CreateNeg(Offset));
      DevArray = Builder.CreatePointerCast(DevArray, Builder.getInt8PtrTy());
    }
    Value *Slot = Builder.CreateGEP(
        Parameters, {Builder.getInt64(0), Builder.getInt64(Index)});

    if (gpu_array_is_read_only_scalar(&Prog->array[i])) {
      Value *ValPtr = nullptr;
      if (PollyManagedMemory)
        ValPtr = DevArray;
      else
        ValPtr = BlockGen.getOrCreateAlloca(SAI);

      assert(ValPtr != nullptr && "ValPtr that should point to a valid object"
                                  " to be stored into Parameters");
      Value *ValPtrCast =
          Builder.CreatePointerCast(ValPtr, Builder.getInt8PtrTy());
      Builder.CreateStore(ValPtrCast, Slot);
    } else {
      Instruction *Param =
          new AllocaInst(Builder.getInt8PtrTy(), AddressSpace,
                         Launch + "_param_" + std::to_string(Index),
                         EntryBlock->getTerminator());
      Builder.CreateStore(DevArray, Param);
      Value *ParamTyped =
          Builder.CreatePointerCast(Param, Builder.getInt8PtrTy());
      Builder.CreateStore(ParamTyped, Slot);
    }
    Index++;
  }

  int NumHostIters = isl_space_dim(Kernel->space, isl_dim_set);

  for (long i = 0; i < NumHostIters; i++) {
    isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i);
    Value *Val = IDToValue[Id];
    isl_id_free(Id);

    if (Runtime == GPURuntime::OpenCL)
      ArgSizes[Index] = computeSizeInBytes(Val->getType());

    Instruction *Param =
        new AllocaInst(Val->getType(), AddressSpace,
                       Launch + "_param_" + std::to_string(Index),
                       EntryBlock->getTerminator());
    Builder.CreateStore(Val, Param);
    insertStoreParameter(Parameters, Param, Index);
    Index++;
  }

  int NumVars = isl_space_dim(Kernel->space, isl_dim_param);

  for (long i = 0; i < NumVars; i++) {
    isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i);
    Value *Val = IDToValue[Id];
    if (ValueMap.count(Val))
      Val = ValueMap[Val];
    isl_id_free(Id);

    if (Runtime == GPURuntime::OpenCL)
      ArgSizes[Index] = computeSizeInBytes(Val->getType());

    Instruction *Param =
        new AllocaInst(Val->getType(), AddressSpace,
                       Launch + "_param_" + std::to_string(Index),
                       EntryBlock->getTerminator());
    Builder.CreateStore(Val, Param);
    insertStoreParameter(Parameters, Param, Index);
    Index++;
  }

  for (auto Val : SubtreeValues) {
    if (Runtime == GPURuntime::OpenCL)
      ArgSizes[Index] = computeSizeInBytes(Val->getType());

    Instruction *Param =
        new AllocaInst(Val->getType(), AddressSpace,
                       Launch + "_param_" + std::to_string(Index),
                       EntryBlock->getTerminator());
    Builder.CreateStore(Val, Param);
    insertStoreParameter(Parameters, Param, Index);
    Index++;
  }

  if (Runtime == GPURuntime::OpenCL) {
    for (int i = 0; i < NumArgs; i++) {
      Value *Val = ConstantInt::get(Builder.getInt32Ty(), ArgSizes[i]);
      Instruction *Param =
          new AllocaInst(Builder.getInt32Ty(), AddressSpace,
                         Launch + "_param_size_" + std::to_string(i),
                         EntryBlock->getTerminator());
      Builder.CreateStore(Val, Param);
      insertStoreParameter(Parameters, Param, Index);
      Index++;
    }
  }

  auto Location = EntryBlock->getTerminator();
  return new BitCastInst(Parameters, Builder.getInt8PtrTy(),
                         Launch + "_params_i8ptr", Location);
}

void GPUNodeBuilder::setupKernelSubtreeFunctions(
    SetVector<Function *> SubtreeFunctions) {
  for (auto Fn : SubtreeFunctions) {
    const std::string ClonedFnName = Fn->getName();
    Function *Clone = GPUModule->getFunction(ClonedFnName);
    if (!Clone)
      Clone =
          Function::Create(Fn->getFunctionType(), GlobalValue::ExternalLinkage,
                           ClonedFnName, GPUModule.get());
    assert(Clone && "Expected cloned function to be initialized.");
    assert(ValueMap.find(Fn) == ValueMap.end() &&
           "Fn already present in ValueMap");
    ValueMap[Fn] = Clone;
  }
}
void GPUNodeBuilder::createKernel(__isl_take isl_ast_node *KernelStmt) {
  isl_id *Id = isl_ast_node_get_annotation(KernelStmt);
  ppcg_kernel *Kernel = (ppcg_kernel *)isl_id_get_user(Id);
  isl_id_free(Id);
  isl_ast_node_free(KernelStmt);

  if (Kernel->n_grid > 1)
    DeepestParallel =
        std::max(DeepestParallel, isl_space_dim(Kernel->space, isl_dim_set));
  else
    DeepestSequential =
        std::max(DeepestSequential, isl_space_dim(Kernel->space, isl_dim_set));

  Value *BlockDimX, *BlockDimY, *BlockDimZ;
  std::tie(BlockDimX, BlockDimY, BlockDimZ) = getBlockSizes(Kernel);

  SetVector<Value *> SubtreeValues;
  SetVector<Function *> SubtreeFunctions;
  SetVector<const Loop *> Loops;
  isl::space ParamSpace;
  std::tie(SubtreeValues, SubtreeFunctions, Loops, ParamSpace) =
      getReferencesInKernel(Kernel);

  // Add parameters that appear only in the access function to the kernel
  // space. This is important to make sure that all isl_ids are passed as
  // parameters to the kernel, even though we may not have all parameters
  // in the context to improve compile time.
  Kernel->space = isl_space_align_params(Kernel->space, ParamSpace.release());

  assert(Kernel->tree && "Device AST of kernel node is empty");

  Instruction &HostInsertPoint = *Builder.GetInsertPoint();
  IslExprBuilder::IDToValueTy HostIDs = IDToValue;
  ValueMapT HostValueMap = ValueMap;
  BlockGenerator::AllocaMapTy HostScalarMap = ScalarMap;
  ScalarMap.clear();
  BlockGenerator::EscapeUsersAllocaMapTy HostEscapeMap = EscapeMap;
  EscapeMap.clear();

  // Create for all loops we depend on values that contain the current loop
  // iteration. These values are necessary to generate code for SCEVs that
  // depend on such loops. As a result we need to pass them to the subfunction.
  for (const Loop *L : Loops) {
    const SCEV *OuterLIV = SE.getAddRecExpr(SE.getUnknown(Builder.getInt64(0)),
                                            SE.getUnknown(Builder.getInt64(1)),
                                            L, SCEV::FlagAnyWrap);
    Value *V = generateSCEV(OuterLIV);
    OutsideLoopIterations[L] = SE.getUnknown(V);
    SubtreeValues.insert(V);
  }

  createKernelFunction(Kernel, SubtreeValues, SubtreeFunctions);
  setupKernelSubtreeFunctions(SubtreeFunctions);

  create(isl_ast_node_copy(Kernel->tree));

  finalizeKernelArguments(Kernel);
  Function *F = Builder.GetInsertBlock()->getParent();
  if (Arch == GPUArch::NVPTX64)
    addCUDAAnnotations(F->getParent(), BlockDimX, BlockDimY, BlockDimZ);
  clearDominators(F);
  clearScalarEvolution(F);
  clearLoops(F);

  IDToValue = HostIDs;

  ValueMap = std::move(HostValueMap);
  ScalarMap = std::move(HostScalarMap);
  EscapeMap = std::move(HostEscapeMap);
  IDToSAI.clear();
  Annotator.resetAlternativeAliasBases();
  for (auto &BasePtr : LocalArrays)
    S.invalidateScopArrayInfo(BasePtr, MemoryKind::Array);
  LocalArrays.clear();

  std::string ASMString = finalizeKernelFunction();
  Builder.SetInsertPoint(&HostInsertPoint);
  Value *Parameters = createLaunchParameters(Kernel, F, SubtreeValues);

  std::string Name = getKernelFuncName(Kernel->id);
  Value *KernelString = Builder.CreateGlobalStringPtr(ASMString, Name);
  Value *NameString = Builder.CreateGlobalStringPtr(Name, Name + "_name");
  Value *GPUKernel = createCallGetKernel(KernelString, NameString);

  Value *GridDimX, *GridDimY;
  std::tie(GridDimX, GridDimY) = getGridSizes(Kernel);

  createCallLaunchKernel(GPUKernel, GridDimX, GridDimY, BlockDimX, BlockDimY,
                         BlockDimZ, Parameters);
  createCallFreeKernel(GPUKernel);

  for (auto Id : KernelIds)
    isl_id_free(Id);

  KernelIds.clear();
}

/// Compute the DataLayout string for the NVPTX backend.
///
/// @param is64Bit Are we looking for a 64 bit architecture?
static std::string computeNVPTXDataLayout(bool is64Bit) {
  std::string Ret = "";

  if (!is64Bit) {
    Ret += "e-p:32:32:32-i1:8:8-i8:8:8-i16:16:16-i32:32:32-i64:64:"
           "64-i128:128:128-f32:32:32-f64:64:64-v16:16:16-v32:32:32-v64:64:"
           "64-v128:128:128-n16:32:64";
  } else {
    Ret += "e-p:64:64:64-i1:8:8-i8:8:8-i16:16:16-i32:32:32-i64:64:"
           "64-i128:128:128-f32:32:32-f64:64:64-v16:16:16-v32:32:32-v64:64:"
           "64-v128:128:128-n16:32:64";
  }

  return Ret;
}

/// Compute the DataLayout string for a SPIR kernel.
///
/// @param is64Bit Are we looking for a 64 bit architecture?
static std::string computeSPIRDataLayout(bool is64Bit) {
  std::string Ret = "";

  if (!is64Bit) {
    Ret += "e-p:32:32:32-i1:8:8-i8:8:8-i16:16:16-i32:32:32-i64:64:"
           "64-i128:128:128-f32:32:32-f64:64:64-v16:16:16-v24:32:32-v32:32:"
           "32-v48:64:64-v64:64:64-v96:128:128-v128:128:128-v192:"
           "256:256-v256:256:256-v512:512:512-v1024:1024:1024";
  } else {
    Ret += "e-p:64:64:64-i1:8:8-i8:8:8-i16:16:16-i32:32:32-i64:64:"
           "64-i128:128:128-f32:32:32-f64:64:64-v16:16:16-v24:32:32-v32:32:"
           "32-v48:64:64-v64:64:64-v96:128:128-v128:128:128-v192:"
           "256:256-v256:256:256-v512:512:512-v1024:1024:1024";
  }

  return Ret;
}

Function *
GPUNodeBuilder::createKernelFunctionDecl(ppcg_kernel *Kernel,
                                         SetVector<Value *> &SubtreeValues) {
  std::vector<Type *> Args;
  std::string Identifier = getKernelFuncName(Kernel->id);

  std::vector<Metadata *> MemoryType;

  for (long i = 0; i < Prog->n_array; i++) {
    if (!ppcg_kernel_requires_array_argument(Kernel, i))
      continue;

    if (gpu_array_is_read_only_scalar(&Prog->array[i])) {
      isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set);
      const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl::manage(Id));
      Args.push_back(SAI->getElementType());
      MemoryType.push_back(
          ConstantAsMetadata::get(ConstantInt::get(Builder.getInt32Ty(), 0)));
    } else {
      static const int UseGlobalMemory = 1;
      Args.push_back(Builder.getInt8PtrTy(UseGlobalMemory));
      MemoryType.push_back(
          ConstantAsMetadata::get(ConstantInt::get(Builder.getInt32Ty(), 1)));
    }
  }

  int NumHostIters = isl_space_dim(Kernel->space, isl_dim_set);

  for (long i = 0; i < NumHostIters; i++) {
    Args.push_back(Builder.getInt64Ty());
    MemoryType.push_back(
        ConstantAsMetadata::get(ConstantInt::get(Builder.getInt32Ty(), 0)));
  }

  int NumVars = isl_space_dim(Kernel->space, isl_dim_param);

  for (long i = 0; i < NumVars; i++) {
    isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i);
    Value *Val = IDToValue[Id];
    isl_id_free(Id);
    Args.push_back(Val->getType());
    MemoryType.push_back(
        ConstantAsMetadata::get(ConstantInt::get(Builder.getInt32Ty(), 0)));
  }

  for (auto *V : SubtreeValues) {
    Args.push_back(V->getType());
    MemoryType.push_back(
        ConstantAsMetadata::get(ConstantInt::get(Builder.getInt32Ty(), 0)));
  }

  auto *FT = FunctionType::get(Builder.getVoidTy(), Args, false);
  auto *FN = Function::Create(FT, Function::ExternalLinkage, Identifier,
                              GPUModule.get());

  std::vector<Metadata *> EmptyStrings;

  for (unsigned int i = 0; i < MemoryType.size(); i++) {
    EmptyStrings.push_back(MDString::get(FN->getContext(), ""));
  }

  if (Arch == GPUArch::SPIR32 || Arch == GPUArch::SPIR64) {
    FN->setMetadata("kernel_arg_addr_space",
                    MDNode::get(FN->getContext(), MemoryType));
    FN->setMetadata("kernel_arg_name",
                    MDNode::get(FN->getContext(), EmptyStrings));
    FN->setMetadata("kernel_arg_access_qual",
                    MDNode::get(FN->getContext(), EmptyStrings));
    FN->setMetadata("kernel_arg_type",
                    MDNode::get(FN->getContext(), EmptyStrings));
    FN->setMetadata("kernel_arg_type_qual",
                    MDNode::get(FN->getContext(), EmptyStrings));
    FN->setMetadata("kernel_arg_base_type",
                    MDNode::get(FN->getContext(), EmptyStrings));
  }

  switch (Arch) {
  case GPUArch::NVPTX64:
    FN->setCallingConv(CallingConv::PTX_Kernel);
    break;
  case GPUArch::SPIR32:
  case GPUArch::SPIR64:
    FN->setCallingConv(CallingConv::SPIR_KERNEL);
    break;
  }

  auto Arg = FN->arg_begin();
  for (long i = 0; i < Kernel->n_array; i++) {
    if (!ppcg_kernel_requires_array_argument(Kernel, i))
      continue;

    Arg->setName(Kernel->array[i].array->name);

    isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set);
    const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl::manage_copy(Id));
    Type *EleTy = SAI->getElementType();
    Value *Val = &*Arg;
    SmallVector<const SCEV *, 4> Sizes;
    isl_ast_build *Build =
        isl_ast_build_from_context(isl_set_copy(Prog->context));
    Sizes.push_back(nullptr);
    for (long j = 1, n = Kernel->array[i].array->n_index; j < n; j++) {
      isl_ast_expr *DimSize = isl_ast_build_expr_from_pw_aff(
          Build, isl_multi_pw_aff_get_pw_aff(Kernel->array[i].array->bound, j));
      auto V = ExprBuilder.create(DimSize);
      Sizes.push_back(SE.getSCEV(V));
    }
    const ScopArrayInfo *SAIRep =
        S.getOrCreateScopArrayInfo(Val, EleTy, Sizes, MemoryKind::Array);
    LocalArrays.push_back(Val);

    isl_ast_build_free(Build);
    KernelIds.push_back(Id);
    IDToSAI[Id] = SAIRep;
    Arg++;
  }

  for (long i = 0; i < NumHostIters; i++) {
    isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i);
    Arg->setName(isl_id_get_name(Id));
    IDToValue[Id] = &*Arg;
    KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id));
    Arg++;
  }

  for (long i = 0; i < NumVars; i++) {
    isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i);
    Arg->setName(isl_id_get_name(Id));
    Value *Val = IDToValue[Id];
    ValueMap[Val] = &*Arg;
    IDToValue[Id] = &*Arg;
    KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id));
    Arg++;
  }

  for (auto *V : SubtreeValues) {
    Arg->setName(V->getName());
    ValueMap[V] = &*Arg;
    Arg++;
  }

  return FN;
}

void GPUNodeBuilder::insertKernelIntrinsics(ppcg_kernel *Kernel) {
  Intrinsic::ID IntrinsicsBID[2];
  Intrinsic::ID IntrinsicsTID[3];

  switch (Arch) {
  case GPUArch::SPIR64:
  case GPUArch::SPIR32:
    llvm_unreachable("Cannot generate NVVM intrinsics for SPIR");
  case GPUArch::NVPTX64:
    IntrinsicsBID[0] = Intrinsic::nvvm_read_ptx_sreg_ctaid_x;
    IntrinsicsBID[1] = Intrinsic::nvvm_read_ptx_sreg_ctaid_y;

    IntrinsicsTID[0] = Intrinsic::nvvm_read_ptx_sreg_tid_x;
    IntrinsicsTID[1] = Intrinsic::nvvm_read_ptx_sreg_tid_y;
    IntrinsicsTID[2] = Intrinsic::nvvm_read_ptx_sreg_tid_z;
    break;
  }

  auto addId = [this](__isl_take isl_id *Id, Intrinsic::ID Intr) mutable {
    std::string Name = isl_id_get_name(Id);
    Module *M = Builder.GetInsertBlock()->getParent()->getParent();
    Function *IntrinsicFn = Intrinsic::getDeclaration(M, Intr);
    Value *Val = Builder.CreateCall(IntrinsicFn, {});
    Val = Builder.CreateIntCast(Val, Builder.getInt64Ty(), false, Name);
    IDToValue[Id] = Val;
    KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id));
  };

  for (int i = 0; i < Kernel->n_grid; ++i) {
    isl_id *Id = isl_id_list_get_id(Kernel->block_ids, i);
    addId(Id, IntrinsicsBID[i]);
  }

  for (int i = 0; i < Kernel->n_block; ++i) {
    isl_id *Id = isl_id_list_get_id(Kernel->thread_ids, i);
    addId(Id, IntrinsicsTID[i]);
  }
}

void GPUNodeBuilder::insertKernelCallsSPIR(ppcg_kernel *Kernel,
                                           bool SizeTypeIs64bit) {
  const char *GroupName[3] = {"__gen_ocl_get_group_id0",
                              "__gen_ocl_get_group_id1",
                              "__gen_ocl_get_group_id2"};

  const char *LocalName[3] = {"__gen_ocl_get_local_id0",
                              "__gen_ocl_get_local_id1",
                              "__gen_ocl_get_local_id2"};
  IntegerType *SizeT =
      SizeTypeIs64bit ? Builder.getInt64Ty() : Builder.getInt32Ty();

  auto createFunc = [this](const char *Name, __isl_take isl_id *Id,
                           IntegerType *SizeT) mutable {
    Module *M = Builder.GetInsertBlock()->getParent()->getParent();
    Function *FN = M->getFunction(Name);

    // If FN is not available, declare it.
    if (!FN) {
      GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage;
      std::vector<Type *> Args;
      FunctionType *Ty = FunctionType::get(SizeT, Args, false);
      FN = Function::Create(Ty, Linkage, Name, M);
      FN->setCallingConv(CallingConv::SPIR_FUNC);
    }

    Value *Val = Builder.CreateCall(FN, {});
    if (SizeT == Builder.getInt32Ty())
      Val = Builder.CreateIntCast(Val, Builder.getInt64Ty(), false, Name);
    IDToValue[Id] = Val;
    KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id));
  };

  for (int i = 0; i < Kernel->n_grid; ++i)
    createFunc(GroupName[i], isl_id_list_get_id(Kernel->block_ids, i), SizeT);

  for (int i = 0; i < Kernel->n_block; ++i)
    createFunc(LocalName[i], isl_id_list_get_id(Kernel->thread_ids, i), SizeT);
}

void GPUNodeBuilder::prepareKernelArguments(ppcg_kernel *Kernel, Function *FN) {
  auto Arg = FN->arg_begin();
  for (long i = 0; i < Kernel->n_array; i++) {
    if (!ppcg_kernel_requires_array_argument(Kernel, i))
      continue;

    isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set);
    const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl::manage_copy(Id));
    isl_id_free(Id);

    if (SAI->getNumberOfDimensions() > 0) {
      Arg++;
      continue;
    }

    Value *Val = &*Arg;

    if (!gpu_array_is_read_only_scalar(&Prog->array[i])) {
      Type *TypePtr = SAI->getElementType()->getPointerTo();
      Value *TypedArgPtr = Builder.CreatePointerCast(Val, TypePtr);
      Val = Builder.CreateLoad(TypedArgPtr);
    }

    Value *Alloca = BlockGen.getOrCreateAlloca(SAI);
    Builder.CreateStore(Val, Alloca);

    Arg++;
  }
}

void GPUNodeBuilder::finalizeKernelArguments(ppcg_kernel *Kernel) {
  auto *FN = Builder.GetInsertBlock()->getParent();
  auto Arg = FN->arg_begin();

  bool StoredScalar = false;
  for (long i = 0; i < Kernel->n_array; i++) {
    if (!ppcg_kernel_requires_array_argument(Kernel, i))
      continue;

    isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set);
    const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl::manage_copy(Id));
    isl_id_free(Id);

    if (SAI->getNumberOfDimensions() > 0) {
      Arg++;
      continue;
    }

    if (gpu_array_is_read_only_scalar(&Prog->array[i])) {
      Arg++;
      continue;
    }

    Value *Alloca = BlockGen.getOrCreateAlloca(SAI);
    Value *ArgPtr = &*Arg;
    Type *TypePtr = SAI->getElementType()->getPointerTo();
    Value *TypedArgPtr = Builder.CreatePointerCast(ArgPtr, TypePtr);
    Value *Val = Builder.CreateLoad(Alloca);
    Builder.CreateStore(Val, TypedArgPtr);
    StoredScalar = true;

    Arg++;
  }

  if (StoredScalar) {
    /// In case more than one thread contains scalar stores, the generated
    /// code might be incorrect, if we only store at the end of the kernel.
    /// To support this case we need to store these scalars back at each
    /// memory store or at least before each kernel barrier.
    if (Kernel->n_block != 0 || Kernel->n_grid != 0) {
      BuildSuccessful = 0;
      LLVM_DEBUG(
          dbgs() << getUniqueScopName(&S)
                 << " has a store to a scalar value that"
                    " would be undefined to run in parallel. Bailing out.\n";);
    }
  }
}

void GPUNodeBuilder::createKernelVariables(ppcg_kernel *Kernel, Function *FN) {
  Module *M = Builder.GetInsertBlock()->getParent()->getParent();

  for (int i = 0; i < Kernel->n_var; ++i) {
    struct ppcg_kernel_var &Var = Kernel->var[i];
    isl_id *Id = isl_space_get_tuple_id(Var.array->space, isl_dim_set);
    Type *EleTy = ScopArrayInfo::getFromId(isl::manage(Id))->getElementType();

    Type *ArrayTy = EleTy;
    SmallVector<const SCEV *, 4> Sizes;

    Sizes.push_back(nullptr);
    for (unsigned int j = 1; j < Var.array->n_index; ++j) {
      isl_val *Val = isl_vec_get_element_val(Var.size, j);
      long Bound = isl_val_get_num_si(Val);
      isl_val_free(Val);
      Sizes.push_back(S.getSE()->getConstant(Builder.getInt64Ty(), Bound));
    }

    for (int j = Var.array->n_index - 1; j >= 0; --j) {
      isl_val *Val = isl_vec_get_element_val(Var.size, j);
      long Bound = isl_val_get_num_si(Val);
      isl_val_free(Val);
      ArrayTy = ArrayType::get(ArrayTy, Bound);
    }

    const ScopArrayInfo *SAI;
    Value *Allocation;
    if (Var.type == ppcg_access_shared) {
      auto GlobalVar = new GlobalVariable(
          *M, ArrayTy, false, GlobalValue::InternalLinkage, 0, Var.name,
          nullptr, GlobalValue::ThreadLocalMode::NotThreadLocal, 3);
      GlobalVar->setAlignment(EleTy->getPrimitiveSizeInBits() / 8);
      GlobalVar->setInitializer(Constant::getNullValue(ArrayTy));

      Allocation = GlobalVar;
    } else if (Var.type == ppcg_access_private) {
      Allocation = Builder.CreateAlloca(ArrayTy, 0, "private_array");
    } else {
      llvm_unreachable("unknown variable type");
    }
    SAI =
        S.getOrCreateScopArrayInfo(Allocation, EleTy, Sizes, MemoryKind::Array);
    Id = isl_id_alloc(S.getIslCtx().get(), Var.name, nullptr);
    IDToValue[Id] = Allocation;
    LocalArrays.push_back(Allocation);
    KernelIds.push_back(Id);
    IDToSAI[Id] = SAI;
  }
}

void GPUNodeBuilder::createKernelFunction(
    ppcg_kernel *Kernel, SetVector<Value *> &SubtreeValues,
    SetVector<Function *> &SubtreeFunctions) {
  std::string Identifier = getKernelFuncName(Kernel->id);
  GPUModule.reset(new Module(Identifier, Builder.getContext()));

  switch (Arch) {
  case GPUArch::NVPTX64:
    if (Runtime == GPURuntime::CUDA)
      GPUModule->setTargetTriple(Triple::normalize("nvptx64-nvidia-cuda"));
    else if (Runtime == GPURuntime::OpenCL)
      GPUModule->setTargetTriple(Triple::normalize("nvptx64-nvidia-nvcl"));
    GPUModule->setDataLayout(computeNVPTXDataLayout(true /* is64Bit */));
    break;
  case GPUArch::SPIR32:
    GPUModule->setTargetTriple(Triple::normalize("spir-unknown-unknown"));
    GPUModule->setDataLayout(computeSPIRDataLayout(false /* is64Bit */));
    break;
  case GPUArch::SPIR64:
    GPUModule->setTargetTriple(Triple::normalize("spir64-unknown-unknown"));
    GPUModule->setDataLayout(computeSPIRDataLayout(true /* is64Bit */));
    break;
  }

  Function *FN = createKernelFunctionDecl(Kernel, SubtreeValues);

  BasicBlock *PrevBlock = Builder.GetInsertBlock();
  auto EntryBlock = BasicBlock::Create(Builder.getContext(), "entry", FN);

  DT.addNewBlock(EntryBlock, PrevBlock);

  Builder.SetInsertPoint(EntryBlock);
  Builder.CreateRetVoid();
  Builder.SetInsertPoint(EntryBlock, EntryBlock->begin());

  ScopDetection::markFunctionAsInvalid(FN);

  prepareKernelArguments(Kernel, FN);
  createKernelVariables(Kernel, FN);

  switch (Arch) {
  case GPUArch::NVPTX64:
    insertKernelIntrinsics(Kernel);
    break;
  case GPUArch::SPIR32:
    insertKernelCallsSPIR(Kernel, false);
    break;
  case GPUArch::SPIR64:
    insertKernelCallsSPIR(Kernel, true);
    break;
  }
}

std::string GPUNodeBuilder::createKernelASM() {
  llvm::Triple GPUTriple;

  switch (Arch) {
  case GPUArch::NVPTX64:
    switch (Runtime) {
    case GPURuntime::CUDA:
      GPUTriple = llvm::Triple(Triple::normalize("nvptx64-nvidia-cuda"));
      break;
    case GPURuntime::OpenCL:
      GPUTriple = llvm::Triple(Triple::normalize("nvptx64-nvidia-nvcl"));
      break;
    }
    break;
  case GPUArch::SPIR64:
  case GPUArch::SPIR32:
    std::string SPIRAssembly;
    raw_string_ostream IROstream(SPIRAssembly);
    IROstream << *GPUModule;
    IROstream.flush();
    return SPIRAssembly;
  }

  std::string ErrMsg;
  auto GPUTarget = TargetRegistry::lookupTarget(GPUTriple.getTriple(), ErrMsg);

  if (!GPUTarget) {
    errs() << ErrMsg << "\n";
    return "";
  }

  TargetOptions Options;
  Options.UnsafeFPMath = FastMath;

  std::string subtarget;

  switch (Arch) {
  case GPUArch::NVPTX64:
    subtarget = CudaVersion;
    break;
  case GPUArch::SPIR32:
  case GPUArch::SPIR64:
    llvm_unreachable("No subtarget for SPIR architecture");
  }

  std::unique_ptr<TargetMachine> TargetM(GPUTarget->createTargetMachine(
      GPUTriple.getTriple(), subtarget, "", Options, Optional<Reloc::Model>()));

  SmallString<0> ASMString;
  raw_svector_ostream ASMStream(ASMString);
  llvm::legacy::PassManager PM;

  PM.add(createTargetTransformInfoWrapperPass(TargetM->getTargetIRAnalysis()));

  if (TargetM->addPassesToEmitFile(PM, ASMStream, nullptr,
                                   TargetMachine::CGFT_AssemblyFile,
                                   true /* verify */)) {
    errs() << "The target does not support generation of this file type!\n";
    return "";
  }

  PM.run(*GPUModule);

  return ASMStream.str();
}

bool GPUNodeBuilder::requiresCUDALibDevice() {
  bool RequiresLibDevice = false;
  for (Function &F : GPUModule->functions()) {
    if (!F.isDeclaration())
      continue;

    const std::string CUDALibDeviceFunc = getCUDALibDeviceFuntion(F.getName());
    if (CUDALibDeviceFunc.length() != 0) {
      // We need to handle the case where a module looks like this:
      // @expf(..)
      // @llvm.exp.f64(..)
      // Both of these functions would be renamed to `__nv_expf`.
      //
      // So, we must first check for the existence of the libdevice function.
      // If this exists, we replace our current function with it.
      //
      // If it does not exist, we rename the current function to the
      // libdevice functiono name.
      if (Function *Replacement = F.getParent()->getFunction(CUDALibDeviceFunc))
        F.replaceAllUsesWith(Replacement);
      else
        F.setName(CUDALibDeviceFunc);
      RequiresLibDevice = true;
    }
  }

  return RequiresLibDevice;
}

void GPUNodeBuilder::addCUDALibDevice() {
  if (Arch != GPUArch::NVPTX64)
    return;

  if (requiresCUDALibDevice()) {
    SMDiagnostic Error;

    errs() << CUDALibDevice << "\n";
    auto LibDeviceModule =
        parseIRFile(CUDALibDevice, Error, GPUModule->getContext());

    if (!LibDeviceModule) {
      BuildSuccessful = false;
      report_fatal_error("Could not find or load libdevice. Skipping GPU "
                         "kernel generation. Please set -polly-acc-libdevice "
                         "accordingly.\n");
      return;
    }

    Linker L(*GPUModule);

    // Set an nvptx64 target triple to avoid linker warnings. The original
    // triple of the libdevice files are nvptx-unknown-unknown.
    LibDeviceModule->setTargetTriple(Triple::normalize("nvptx64-nvidia-cuda"));
    L.linkInModule(std::move(LibDeviceModule), Linker::LinkOnlyNeeded);
  }
}

std::string GPUNodeBuilder::finalizeKernelFunction() {

  if (verifyModule(*GPUModule)) {
    LLVM_DEBUG(dbgs() << "verifyModule failed on module:\n";
               GPUModule->print(dbgs(), nullptr); dbgs() << "\n";);
    LLVM_DEBUG(dbgs() << "verifyModule Error:\n";
               verifyModule(*GPUModule, &dbgs()););

    if (FailOnVerifyModuleFailure)
      llvm_unreachable("VerifyModule failed.");

    BuildSuccessful = false;
    return "";
  }

  addCUDALibDevice();

  if (DumpKernelIR)
    outs() << *GPUModule << "\n";

  if (Arch != GPUArch::SPIR32 && Arch != GPUArch::SPIR64) {
    // Optimize module.
    llvm::legacy::PassManager OptPasses;
    PassManagerBuilder PassBuilder;
    PassBuilder.OptLevel = 3;
    PassBuilder.SizeLevel = 0;
    PassBuilder.populateModulePassManager(OptPasses);
    OptPasses.run(*GPUModule);
  }

  std::string Assembly = createKernelASM();

  if (DumpKernelASM)
    outs() << Assembly << "\n";

  GPUModule.release();
  KernelIDs.clear();

  return Assembly;
}
/// Construct an `isl_pw_aff_list` from a vector of `isl_pw_aff`
/// @param PwAffs The list of piecewise affine functions to create an
///               `isl_pw_aff_list` from. We expect an rvalue ref because
///               all the isl_pw_aff are used up by this function.
///
/// @returns  The `isl_pw_aff_list`.
__isl_give isl_pw_aff_list *
createPwAffList(isl_ctx *Context,
                const std::vector<__isl_take isl_pw_aff *> &&PwAffs) {
  isl_pw_aff_list *List = isl_pw_aff_list_alloc(Context, PwAffs.size());

  for (unsigned i = 0; i < PwAffs.size(); i++) {
    List = isl_pw_aff_list_insert(List, i, PwAffs[i]);
  }
  return List;
}

/// Align all the `PwAffs` such that they have the same parameter dimensions.
///
/// We loop over all `pw_aff` and align all of their spaces together to
/// create a common space for all the `pw_aff`. This common space is the
/// `AlignSpace`. We then align all the `pw_aff` to this space. We start
/// with the given `SeedSpace`.
/// @param PwAffs    The list of piecewise affine functions we want to align.
///                  This is an rvalue reference because the entire vector is
///                  used up by the end of the operation.
/// @param SeedSpace The space to start the alignment process with.
/// @returns         A std::pair, whose first element is the aligned space,
///                  whose second element is the vector of aligned piecewise
///                  affines.
static std::pair<__isl_give isl_space *, std::vector<__isl_give isl_pw_aff *>>
alignPwAffs(const std::vector<__isl_take isl_pw_aff *> &&PwAffs,
            __isl_take isl_space *SeedSpace) {
  assert(SeedSpace && "Invalid seed space given.");

  isl_space *AlignSpace = SeedSpace;
  for (isl_pw_aff *PwAff : PwAffs) {
    isl_space *PwAffSpace = isl_pw_aff_get_domain_space(PwAff);
    AlignSpace = isl_space_align_params(AlignSpace, PwAffSpace);
  }
  std::vector<isl_pw_aff *> AdjustedPwAffs;

  for (unsigned i = 0; i < PwAffs.size(); i++) {
    isl_pw_aff *Adjusted = PwAffs[i];
    assert(Adjusted && "Invalid pw_aff given.");
    Adjusted = isl_pw_aff_align_params(Adjusted, isl_space_copy(AlignSpace));
    AdjustedPwAffs.push_back(Adjusted);
  }
  return std::make_pair(AlignSpace, AdjustedPwAffs);
}

namespace {
class PPCGCodeGeneration : public ScopPass {
public:
  static char ID;

  GPURuntime Runtime = GPURuntime::CUDA;

  GPUArch Architecture = GPUArch::NVPTX64;

  /// The scop that is currently processed.
  Scop *S;

  LoopInfo *LI;
  DominatorTree *DT;
  ScalarEvolution *SE;
  const DataLayout *DL;
  RegionInfo *RI;

  PPCGCodeGeneration() : ScopPass(ID) {}

  /// Construct compilation options for PPCG.
  ///
  /// @returns The compilation options.
  ppcg_options *createPPCGOptions() {
    auto DebugOptions =
        (ppcg_debug_options *)malloc(sizeof(ppcg_debug_options));
    auto Options = (ppcg_options *)malloc(sizeof(ppcg_options));

    DebugOptions->dump_schedule_constraints = false;
    DebugOptions->dump_schedule = false;
    DebugOptions->dump_final_schedule = false;
    DebugOptions->dump_sizes = false;
    DebugOptions->verbose = false;

    Options->debug = DebugOptions;

    Options->group_chains = false;
    Options->reschedule = true;
    Options->scale_tile_loops = false;
    Options->wrap = false;

    Options->non_negative_parameters = false;
    Options->ctx = nullptr;
    Options->sizes = nullptr;

    Options->tile = true;
    Options->tile_size = 32;

    Options->isolate_full_tiles = false;

    Options->use_private_memory = PrivateMemory;
    Options->use_shared_memory = SharedMemory;
    Options->max_shared_memory = 48 * 1024;

    Options->target = PPCG_TARGET_CUDA;
    Options->openmp = false;
    Options->linearize_device_arrays = true;
    Options->allow_gnu_extensions = false;

    Options->unroll_copy_shared = false;
    Options->unroll_gpu_tile = false;
    Options->live_range_reordering = true;

    Options->live_range_reordering = true;
    Options->hybrid = false;
    Options->opencl_compiler_options = nullptr;
    Options->opencl_use_gpu = false;
    Options->opencl_n_include_file = 0;
    Options->opencl_include_files = nullptr;
    Options->opencl_print_kernel_types = false;
    Options->opencl_embed_kernel_code = false;

    Options->save_schedule_file = nullptr;
    Options->load_schedule_file = nullptr;

    return Options;
  }

  /// Get a tagged access relation containing all accesses of type @p AccessTy.
  ///
  /// Instead of a normal access of the form:
  ///
  ///   Stmt[i,j,k] -> Array[f_0(i,j,k), f_1(i,j,k)]
  ///
  /// a tagged access has the form
  ///
  ///   [Stmt[i,j,k] -> id[]] -> Array[f_0(i,j,k), f_1(i,j,k)]
  ///
  /// where 'id' is an additional space that references the memory access that
  /// triggered the access.
  ///
  /// @param AccessTy The type of the memory accesses to collect.
  ///
  /// @return The relation describing all tagged memory accesses.
  isl_union_map *getTaggedAccesses(enum MemoryAccess::AccessType AccessTy) {
    isl_union_map *Accesses = isl_union_map_empty(S->getParamSpace().release());

    for (auto &Stmt : *S)
      for (auto &Acc : Stmt)
        if (Acc->getType() == AccessTy) {
          isl_map *Relation = Acc->getAccessRelation().release();
          Relation =
              isl_map_intersect_domain(Relation, Stmt.getDomain().release());

          isl_space *Space = isl_map_get_space(Relation);
          Space = isl_space_range(Space);
          Space = isl_space_from_range(Space);
          Space =
              isl_space_set_tuple_id(Space, isl_dim_in, Acc->getId().release());
          isl_map *Universe = isl_map_universe(Space);
          Relation = isl_map_domain_product(Relation, Universe);
          Accesses = isl_union_map_add_map(Accesses, Relation);
        }

    return Accesses;
  }

  /// Get the set of all read accesses, tagged with the access id.
  ///
  /// @see getTaggedAccesses
  isl_union_map *getTaggedReads() {
    return getTaggedAccesses(MemoryAccess::READ);
  }

  /// Get the set of all may (and must) accesses, tagged with the access id.
  ///
  /// @see getTaggedAccesses
  isl_union_map *getTaggedMayWrites() {
    return isl_union_map_union(getTaggedAccesses(MemoryAccess::MAY_WRITE),
                               getTaggedAccesses(MemoryAccess::MUST_WRITE));
  }

  /// Get the set of all must accesses, tagged with the access id.
  ///
  /// @see getTaggedAccesses
  isl_union_map *getTaggedMustWrites() {
    return getTaggedAccesses(MemoryAccess::MUST_WRITE);
  }

  /// Collect parameter and array names as isl_ids.
  ///
  /// To reason about the different parameters and arrays used, ppcg requires
  /// a list of all isl_ids in use. As PPCG traditionally performs
  /// source-to-source compilation each of these isl_ids is mapped to the
  /// expression that represents it. As we do not have a corresponding
  /// expression in Polly, we just map each id to a 'zero' expression to match
  /// the data format that ppcg expects.
  ///
  /// @returns Retun a map from collected ids to 'zero' ast expressions.
  __isl_give isl_id_to_ast_expr *getNames() {
    auto *Names = isl_id_to_ast_expr_alloc(
        S->getIslCtx().get(),
        S->getNumParams() + std::distance(S->array_begin(), S->array_end()));
    auto *Zero = isl_ast_expr_from_val(isl_val_zero(S->getIslCtx().get()));

    for (const SCEV *P : S->parameters()) {
      isl_id *Id = S->getIdForParam(P).release();
      Names = isl_id_to_ast_expr_set(Names, Id, isl_ast_expr_copy(Zero));
    }

    for (auto &Array : S->arrays()) {
      auto Id = Array->getBasePtrId().release();
      Names = isl_id_to_ast_expr_set(Names, Id, isl_ast_expr_copy(Zero));
    }

    isl_ast_expr_free(Zero);

    return Names;
  }

  /// Create a new PPCG scop from the current scop.
  ///
  /// The PPCG scop is initialized with data from the current polly::Scop. From
  /// this initial data, the data-dependences in the PPCG scop are initialized.
  /// We do not use Polly's dependence analysis for now, to ensure we match
  /// the PPCG default behaviour more closely.
  ///
  /// @returns A new ppcg scop.
  ppcg_scop *createPPCGScop() {
    MustKillsInfo KillsInfo = computeMustKillsInfo(*S);

    auto PPCGScop = (ppcg_scop *)malloc(sizeof(ppcg_scop));

    PPCGScop->options = createPPCGOptions();
    // enable live range reordering
    PPCGScop->options->live_range_reordering = 1;

    PPCGScop->start = 0;
    PPCGScop->end = 0;

    PPCGScop->context = S->getContext().release();
    PPCGScop->domain = S->getDomains().release();
    // TODO: investigate this further. PPCG calls collect_call_domains.
    PPCGScop->call = isl_union_set_from_set(S->getContext().release());
    PPCGScop->tagged_reads = getTaggedReads();
    PPCGScop->reads = S->getReads().release();
    PPCGScop->live_in = nullptr;
    PPCGScop->tagged_may_writes = getTaggedMayWrites();
    PPCGScop->may_writes = S->getWrites().release();
    PPCGScop->tagged_must_writes = getTaggedMustWrites();
    PPCGScop->must_writes = S->getMustWrites().release();
    PPCGScop->live_out = nullptr;
    PPCGScop->tagged_must_kills = KillsInfo.TaggedMustKills.release();
    PPCGScop->must_kills = KillsInfo.MustKills.release();

    PPCGScop->tagger = nullptr;
    PPCGScop->independence =
        isl_union_map_empty(isl_set_get_space(PPCGScop->context));
    PPCGScop->dep_flow = nullptr;
    PPCGScop->tagged_dep_flow = nullptr;
    PPCGScop->dep_false = nullptr;
    PPCGScop->dep_forced = nullptr;
    PPCGScop->dep_order = nullptr;
    PPCGScop->tagged_dep_order = nullptr;

    PPCGScop->schedule = S->getScheduleTree().release();
    // If we have something non-trivial to kill, add it to the schedule
    if (KillsInfo.KillsSchedule.get())
      PPCGScop->schedule = isl_schedule_sequence(
          PPCGScop->schedule, KillsInfo.KillsSchedule.release());

    PPCGScop->names = getNames();
    PPCGScop->pet = nullptr;

    compute_tagger(PPCGScop);
    compute_dependences(PPCGScop);
    eliminate_dead_code(PPCGScop);

    return PPCGScop;
  }

  /// Collect the array accesses in a statement.
  ///
  /// @param Stmt The statement for which to collect the accesses.
  ///
  /// @returns A list of array accesses.
  gpu_stmt_access *getStmtAccesses(ScopStmt &Stmt) {
    gpu_stmt_access *Accesses = nullptr;

    for (MemoryAccess *Acc : Stmt) {
      auto Access =
          isl_alloc_type(S->getIslCtx().get(), struct gpu_stmt_access);
      Access->read = Acc->isRead();
      Access->write = Acc->isWrite();
      Access->access = Acc->getAccessRelation().release();
      isl_space *Space = isl_map_get_space(Access->access);
      Space = isl_space_range(Space);
      Space = isl_space_from_range(Space);
      Space = isl_space_set_tuple_id(Space, isl_dim_in, Acc->getId().release());
      isl_map *Universe = isl_map_universe(Space);
      Access->tagged_access =
          isl_map_domain_product(Acc->getAccessRelation().release(), Universe);
      Access->exact_write = !Acc->isMayWrite();
      Access->ref_id = Acc->getId().release();
      Access->next = Accesses;
      Access->n_index = Acc->getScopArrayInfo()->getNumberOfDimensions();
      // TODO: Also mark one-element accesses to arrays as fixed-element.
      Access->fixed_element =
          Acc->isLatestScalarKind() ? isl_bool_true : isl_bool_false;
      Accesses = Access;
    }

    return Accesses;
  }

  /// Collect the list of GPU statements.
  ///
  /// Each statement has an id, a pointer to the underlying data structure,
  /// as well as a list with all memory accesses.
  ///
  /// TODO: Initialize the list of memory accesses.
  ///
  /// @returns A linked-list of statements.
  gpu_stmt *getStatements() {
    gpu_stmt *Stmts = isl_calloc_array(S->getIslCtx().get(), struct gpu_stmt,
                                       std::distance(S->begin(), S->end()));

    int i = 0;
    for (auto &Stmt : *S) {
      gpu_stmt *GPUStmt = &Stmts[i];

      GPUStmt->id = Stmt.getDomainId().release();

      // We use the pet stmt pointer to keep track of the Polly statements.
      GPUStmt->stmt = (pet_stmt *)&Stmt;
      GPUStmt->accesses = getStmtAccesses(Stmt);
      i++;
    }

    return Stmts;
  }

  /// Derive the extent of an array.
  ///
  /// The extent of an array is the set of elements that are within the
  /// accessed array. For the inner dimensions, the extent constraints are
  /// 0 and the size of the corresponding array dimension. For the first
  /// (outermost) dimension, the extent constraints are the minimal and maximal
  /// subscript value for the first dimension.
  ///
  /// @param Array The array to derive the extent for.
  ///
  /// @returns An isl_set describing the extent of the array.
  isl::set getExtent(ScopArrayInfo *Array) {
    unsigned NumDims = Array->getNumberOfDimensions();

    if (Array->getNumberOfDimensions() == 0)
      return isl::set::universe(Array->getSpace());

    isl::union_map Accesses = S->getAccesses(Array);
    isl::union_set AccessUSet = Accesses.range();
    AccessUSet = AccessUSet.coalesce();
    AccessUSet = AccessUSet.detect_equalities();
    AccessUSet = AccessUSet.coalesce();

    if (AccessUSet.is_empty())
      return isl::set::empty(Array->getSpace());

    isl::set AccessSet = AccessUSet.extract_set(Array->getSpace());

    isl::local_space LS = isl::local_space(Array->getSpace());

    isl::pw_aff Val = isl::aff::var_on_domain(LS, isl::dim::set, 0);
    isl::pw_aff OuterMin = AccessSet.dim_min(0);
    isl::pw_aff OuterMax = AccessSet.dim_max(0);
    OuterMin = OuterMin.add_dims(isl::dim::in, Val.dim(isl::dim::in));
    OuterMax = OuterMax.add_dims(isl::dim::in, Val.dim(isl::dim::in));
    OuterMin = OuterMin.set_tuple_id(isl::dim::in, Array->getBasePtrId());
    OuterMax = OuterMax.set_tuple_id(isl::dim::in, Array->getBasePtrId());

    isl::set Extent = isl::set::universe(Array->getSpace());

    Extent = Extent.intersect(OuterMin.le_set(Val));
    Extent = Extent.intersect(OuterMax.ge_set(Val));

    for (unsigned i = 1; i < NumDims; ++i)
      Extent = Extent.lower_bound_si(isl::dim::set, i, 0);

    for (unsigned i = 0; i < NumDims; ++i) {
      isl::pw_aff PwAff = Array->getDimensionSizePw(i);

      // isl_pw_aff can be NULL for zero dimension. Only in the case of a
      // Fortran array will we have a legitimate dimension.
      if (PwAff.is_null()) {
        assert(i == 0 && "invalid dimension isl_pw_aff for nonzero dimension");
        continue;
      }

      isl::pw_aff Val = isl::aff::var_on_domain(
          isl::local_space(Array->getSpace()), isl::dim::set, i);
      PwAff = PwAff.add_dims(isl::dim::in, Val.dim(isl::dim::in));
      PwAff = PwAff.set_tuple_id(isl::dim::in, Val.get_tuple_id(isl::dim::in));
      isl::set Set = PwAff.gt_set(Val);
      Extent = Set.intersect(Extent);
    }

    return Extent;
  }

  /// Derive the bounds of an array.
  ///
  /// For the first dimension we derive the bound of the array from the extent
  /// of this dimension. For inner dimensions we obtain their size directly from
  /// ScopArrayInfo.
  ///
  /// @param PPCGArray The array to compute bounds for.
  /// @param Array The polly array from which to take the information.
  void setArrayBounds(gpu_array_info &PPCGArray, ScopArrayInfo *Array) {
    std::vector<isl_pw_aff *> Bounds;

    if (PPCGArray.n_index > 0) {
      if (isl_set_is_empty(PPCGArray.extent)) {
        isl_set *Dom = isl_set_copy(PPCGArray.extent);
        isl_local_space *LS = isl_local_space_from_space(
            isl_space_params(isl_set_get_space(Dom)));
        isl_set_free(Dom);
        isl_pw_aff *Zero = isl_pw_aff_from_aff(isl_aff_zero_on_domain(LS));
        Bounds.push_back(Zero);
      } else {
        isl_set *Dom = isl_set_copy(PPCGArray.extent);
        Dom = isl_set_project_out(Dom, isl_dim_set, 1, PPCGArray.n_index - 1);
        isl_pw_aff *Bound = isl_set_dim_max(isl_set_copy(Dom), 0);
        isl_set_free(Dom);
        Dom = isl_pw_aff_domain(isl_pw_aff_copy(Bound));
        isl_local_space *LS =
            isl_local_space_from_space(isl_set_get_space(Dom));
        isl_aff *One = isl_aff_zero_on_domain(LS);
        One = isl_aff_add_constant_si(One, 1);
        Bound = isl_pw_aff_add(Bound, isl_pw_aff_alloc(Dom, One));
        Bound = isl_pw_aff_gist(Bound, S->getContext().release());
        Bounds.push_back(Bound);
      }
    }

    for (unsigned i = 1; i < PPCGArray.n_index; ++i) {
      isl_pw_aff *Bound = Array->getDimensionSizePw(i).release();
      auto LS = isl_pw_aff_get_domain_space(Bound);
      auto Aff = isl_multi_aff_zero(LS);

      // We need types to work out, which is why we perform this weird dance
      // with `Aff` and `Bound`. Consider this example:

      // LS: [p] -> { [] }
      // Zero: [p] -> { [] } | Implicitly, is [p] -> { ~ -> [] }.
      // This `~` is used to denote a "null space" (which is different from
      // a *zero dimensional* space), which is something that ISL does not
      // show you when pretty printing.

      // Bound: [p] -> { [] -> [(10p)] } | Here, the [] is a *zero dimensional*
      // space, not a "null space" which does not exist at all.

      // When we pullback (precompose) `Bound` with `Zero`, we get:
      // Bound . Zero =
      //     ([p] -> { [] -> [(10p)] }) . ([p] -> {~ -> [] }) =
      //     [p] -> { ~ -> [(10p)] } =
      //     [p] -> [(10p)] (as ISL pretty prints it)
      // Bound Pullback: [p] -> { [(10p)] }

      // We want this kind of an expression for Bound, without a
      // zero dimensional input, but with a "null space" input for the types
      // to work out later on, as far as I (Siddharth Bhat) understand.
      // I was unable to find a reference to this in the ISL manual.
      // References: Tobias Grosser.

      Bound = isl_pw_aff_pullback_multi_aff(Bound, Aff);
      Bounds.push_back(Bound);
    }

    /// To construct a `isl_multi_pw_aff`, we need all the indivisual `pw_aff`
    /// to have the same parameter dimensions. So, we need to align them to an
    /// appropriate space.
    /// Scop::Context is _not_ an appropriate space, because when we have
    /// `-polly-ignore-parameter-bounds` enabled, the Scop::Context does not
    /// contain all parameter dimensions.
    /// So, use the helper `alignPwAffs` to align all the `isl_pw_aff` together.
    isl_space *SeedAlignSpace = S->getParamSpace().release();
    SeedAlignSpace = isl_space_add_dims(SeedAlignSpace, isl_dim_set, 1);

    isl_space *AlignSpace = nullptr;
    std::vector<isl_pw_aff *> AlignedBounds;
    std::tie(AlignSpace, AlignedBounds) =
        alignPwAffs(std::move(Bounds), SeedAlignSpace);

    assert(AlignSpace && "alignPwAffs did not initialise AlignSpace");

    isl_pw_aff_list *BoundsList =
        createPwAffList(S->getIslCtx().get(), std::move(AlignedBounds));

    isl_space *BoundsSpace = isl_set_get_space(PPCGArray.extent);
    BoundsSpace = isl_space_align_params(BoundsSpace, AlignSpace);

    assert(BoundsSpace && "Unable to access space of array.");
    assert(BoundsList && "Unable to access list of bounds.");

    PPCGArray.bound =
        isl_multi_pw_aff_from_pw_aff_list(BoundsSpace, BoundsList);
    assert(PPCGArray.bound && "PPCGArray.bound was not constructed correctly.");
  }

  /// Create the arrays for @p PPCGProg.
  ///
  /// @param PPCGProg The program to compute the arrays for.
  void createArrays(gpu_prog *PPCGProg,
                    const SmallVector<ScopArrayInfo *, 4> &ValidSAIs) {
    int i = 0;
    for (auto &Array : ValidSAIs) {
      std::string TypeName;
      raw_string_ostream OS(TypeName);

      OS << *Array->getElementType();
      TypeName = OS.str();

      gpu_array_info &PPCGArray = PPCGProg->array[i];

      PPCGArray.space = Array->getSpace().release();
      PPCGArray.type = strdup(TypeName.c_str());
      PPCGArray.size = DL->getTypeAllocSize(Array->getElementType());
      PPCGArray.name = strdup(Array->getName().c_str());
      PPCGArray.extent = nullptr;
      PPCGArray.n_index = Array->getNumberOfDimensions();
      PPCGArray.extent = getExtent(Array).release();
      PPCGArray.n_ref = 0;
      PPCGArray.refs = nullptr;
      PPCGArray.accessed = true;
      PPCGArray.read_only_scalar =
          Array->isReadOnly() && Array->getNumberOfDimensions() == 0;
      PPCGArray.has_compound_element = false;
      PPCGArray.local = false;
      PPCGArray.declare_local = false;
      PPCGArray.global = false;
      PPCGArray.linearize = false;
      PPCGArray.dep_order = nullptr;
      PPCGArray.user = Array;

      PPCGArray.bound = nullptr;
      setArrayBounds(PPCGArray, Array);
      i++;

      collect_references(PPCGProg, &PPCGArray);
      PPCGArray.only_fixed_element = only_fixed_element_accessed(&PPCGArray);
    }
  }

  /// Create an identity map between the arrays in the scop.
  ///
  /// @returns An identity map between the arrays in the scop.
  isl_union_map *getArrayIdentity() {
    isl_union_map *Maps = isl_union_map_empty(S->getParamSpace().release());

    for (auto &Array : S->arrays()) {
      isl_space *Space = Array->getSpace().release();
      Space = isl_space_map_from_set(Space);
      isl_map *Identity = isl_map_identity(Space);
      Maps = isl_union_map_add_map(Maps, Identity);
    }

    return Maps;
  }

  /// Create a default-initialized PPCG GPU program.
  ///
  /// @returns A new gpu program description.
  gpu_prog *createPPCGProg(ppcg_scop *PPCGScop) {

    if (!PPCGScop)
      return nullptr;

    auto PPCGProg = isl_calloc_type(S->getIslCtx().get(), struct gpu_prog);

    PPCGProg->ctx = S->getIslCtx().get();
    PPCGProg->scop = PPCGScop;
    PPCGProg->context = isl_set_copy(PPCGScop->context);
    PPCGProg->read = isl_union_map_copy(PPCGScop->reads);
    PPCGProg->may_write = isl_union_map_copy(PPCGScop->may_writes);
    PPCGProg->must_write = isl_union_map_copy(PPCGScop->must_writes);
    PPCGProg->tagged_must_kill =
        isl_union_map_copy(PPCGScop->tagged_must_kills);
    PPCGProg->to_inner = getArrayIdentity();
    PPCGProg->to_outer = getArrayIdentity();
    // TODO: verify that this assignment is correct.
    PPCGProg->any_to_outer = nullptr;
    PPCGProg->n_stmts = std::distance(S->begin(), S->end());
    PPCGProg->stmts = getStatements();

    // Only consider arrays that have a non-empty extent.
    // Otherwise, this will cause us to consider the following kinds of
    // empty arrays:
    //     1. Invariant loads that are represented by SAI objects.
    //     2. Arrays with statically known zero size.
    auto ValidSAIsRange =
        make_filter_range(S->arrays(), [this](ScopArrayInfo *SAI) -> bool {
          return !getExtent(SAI).is_empty();
        });
    SmallVector<ScopArrayInfo *, 4> ValidSAIs(ValidSAIsRange.begin(),
                                              ValidSAIsRange.end());

    PPCGProg->n_array =
        ValidSAIs.size(); // std::distance(S->array_begin(), S->array_end());
    PPCGProg->array = isl_calloc_array(
        S->getIslCtx().get(), struct gpu_array_info, PPCGProg->n_array);

    createArrays(PPCGProg, ValidSAIs);

    PPCGProg->array_order = nullptr;
    collect_order_dependences(PPCGProg);

    PPCGProg->may_persist = compute_may_persist(PPCGProg);
    return PPCGProg;
  }

  struct PrintGPUUserData {
    struct cuda_info *CudaInfo;
    struct gpu_prog *PPCGProg;
    std::vector<ppcg_kernel *> Kernels;
  };

  /// Print a user statement node in the host code.
  ///
  /// We use ppcg's printing facilities to print the actual statement and
  /// additionally build up a list of all kernels that are encountered in the
  /// host ast.
  ///
  /// @param P The printer to print to
  /// @param Options The printing options to use
  /// @param Node The node to print
  /// @param User A user pointer to carry additional data. This pointer is
  ///             expected to be of type PrintGPUUserData.
  ///
  /// @returns A printer to which the output has been printed.
  static __isl_give isl_printer *
  printHostUser(__isl_take isl_printer *P,
                __isl_take isl_ast_print_options *Options,
                __isl_take isl_ast_node *Node, void *User) {
    auto Data = (struct PrintGPUUserData *)User;
    auto Id = isl_ast_node_get_annotation(Node);

    if (Id) {
      bool IsUser = !strcmp(isl_id_get_name(Id), "user");

      // If this is a user statement, format it ourselves as ppcg would
      // otherwise try to call pet functionality that is not available in
      // Polly.
      if (IsUser) {
        P = isl_printer_start_line(P);
        P = isl_printer_print_ast_node(P, Node);
        P = isl_printer_end_line(P);
        isl_id_free(Id);
        isl_ast_print_options_free(Options);
        return P;
      }

      auto Kernel = (struct ppcg_kernel *)isl_id_get_user(Id);
      isl_id_free(Id);
      Data->Kernels.push_back(Kernel);
    }

    return print_host_user(P, Options, Node, User);
  }

  /// Print C code corresponding to the control flow in @p Kernel.
  ///
  /// @param Kernel The kernel to print
  void printKernel(ppcg_kernel *Kernel) {
    auto *P = isl_printer_to_str(S->getIslCtx().get());
    P = isl_printer_set_output_format(P, ISL_FORMAT_C);
    auto *Options = isl_ast_print_options_alloc(S->getIslCtx().get());
    P = isl_ast_node_print(Kernel->tree, P, Options);
    char *String = isl_printer_get_str(P);
    outs() << String << "\n";
    free(String);
    isl_printer_free(P);
  }

  /// Print C code corresponding to the GPU code described by @p Tree.
  ///
  /// @param Tree An AST describing GPU code
  /// @param PPCGProg The PPCG program from which @Tree has been constructed.
  void printGPUTree(isl_ast_node *Tree, gpu_prog *PPCGProg) {
    auto *P = isl_printer_to_str(S->getIslCtx().get());
    P = isl_printer_set_output_format(P, ISL_FORMAT_C);

    PrintGPUUserData Data;
    Data.PPCGProg = PPCGProg;

    auto *Options = isl_ast_print_options_alloc(S->getIslCtx().get());
    Options =
        isl_ast_print_options_set_print_user(Options, printHostUser, &Data);
    P = isl_ast_node_print(Tree, P, Options);
    char *String = isl_printer_get_str(P);
    outs() << "# host\n";
    outs() << String << "\n";
    free(String);
    isl_printer_free(P);

    for (auto Kernel : Data.Kernels) {
      outs() << "# kernel" << Kernel->id << "\n";
      printKernel(Kernel);
    }
  }

  // Generate a GPU program using PPCG.
  //
  // GPU mapping consists of multiple steps:
  //
  //  1) Compute new schedule for the program.
  //  2) Map schedule to GPU (TODO)
  //  3) Generate code for new schedule (TODO)
  //
  // We do not use here the Polly ScheduleOptimizer, as the schedule optimizer
  // is mostly CPU specific. Instead, we use PPCG's GPU code generation
  // strategy directly from this pass.
  gpu_gen *generateGPU(ppcg_scop *PPCGScop, gpu_prog *PPCGProg) {

    auto PPCGGen = isl_calloc_type(S->getIslCtx().get(), struct gpu_gen);

    PPCGGen->ctx = S->getIslCtx().get();
    PPCGGen->options = PPCGScop->options;
    PPCGGen->print = nullptr;
    PPCGGen->print_user = nullptr;
    PPCGGen->build_ast_expr = &pollyBuildAstExprForStmt;
    PPCGGen->prog = PPCGProg;
    PPCGGen->tree = nullptr;
    PPCGGen->types.n = 0;
    PPCGGen->types.name = nullptr;
    PPCGGen->sizes = nullptr;
    PPCGGen->used_sizes = nullptr;
    PPCGGen->kernel_id = 0;

    // Set scheduling strategy to same strategy PPCG is using.
    isl_options_set_schedule_outer_coincidence(PPCGGen->ctx, true);
    isl_options_set_schedule_maximize_band_depth(PPCGGen->ctx, true);
    isl_options_set_schedule_whole_component(PPCGGen->ctx, false);

    isl_schedule *Schedule = get_schedule(PPCGGen);

    int has_permutable = has_any_permutable_node(Schedule);

    Schedule =
        isl_schedule_align_params(Schedule, S->getFullParamSpace().release());

    if (!has_permutable || has_permutable < 0) {
      Schedule = isl_schedule_free(Schedule);
      LLVM_DEBUG(dbgs() << getUniqueScopName(S)
                        << " does not have permutable bands. Bailing out\n";);
    } else {
      const bool CreateTransferToFromDevice = !PollyManagedMemory;
      Schedule = map_to_device(PPCGGen, Schedule, CreateTransferToFromDevice);
      PPCGGen->tree = generate_code(PPCGGen, isl_schedule_copy(Schedule));
    }

    if (DumpSchedule) {
      isl_printer *P = isl_printer_to_str(S->getIslCtx().get());
      P = isl_printer_set_yaml_style(P, ISL_YAML_STYLE_BLOCK);
      P = isl_printer_print_str(P, "Schedule\n");
      P = isl_printer_print_str(P, "========\n");
      if (Schedule)
        P = isl_printer_print_schedule(P, Schedule);
      else
        P = isl_printer_print_str(P, "No schedule found\n");

      outs() << isl_printer_get_str(P) << "\n";
      isl_printer_free(P);
    }

    if (DumpCode) {
      outs() << "Code\n";
      outs() << "====\n";
      if (PPCGGen->tree)
        printGPUTree(PPCGGen->tree, PPCGProg);
      else
        outs() << "No code generated\n";
    }

    isl_schedule_free(Schedule);

    return PPCGGen;
  }

  /// Free gpu_gen structure.
  ///
  /// @param PPCGGen The ppcg_gen object to free.
  void freePPCGGen(gpu_gen *PPCGGen) {
    isl_ast_node_free(PPCGGen->tree);
    isl_union_map_free(PPCGGen->sizes);
    isl_union_map_free(PPCGGen->used_sizes);
    free(PPCGGen);
  }

  /// Free the options in the ppcg scop structure.
  ///
  /// ppcg is not freeing these options for us. To avoid leaks we do this
  /// ourselves.
  ///
  /// @param PPCGScop The scop referencing the options to free.
  void freeOptions(ppcg_scop *PPCGScop) {
    free(PPCGScop->options->debug);
    PPCGScop->options->debug = nullptr;
    free(PPCGScop->options);
    PPCGScop->options = nullptr;
  }

  /// Approximate the number of points in the set.
  ///
  /// This function returns an ast expression that overapproximates the number
  /// of points in an isl set through the rectangular hull surrounding this set.
  ///
  /// @param Set   The set to count.
  /// @param Build The isl ast build object to use for creating the ast
  ///              expression.
  ///
  /// @returns An approximation of the number of points in the set.
  __isl_give isl_ast_expr *approxPointsInSet(__isl_take isl_set *Set,
                                             __isl_keep isl_ast_build *Build) {

    isl_val *One = isl_val_int_from_si(isl_set_get_ctx(Set), 1);
    auto *Expr = isl_ast_expr_from_val(isl_val_copy(One));

    isl_space *Space = isl_set_get_space(Set);
    Space = isl_space_params(Space);
    auto *Univ = isl_set_universe(Space);
    isl_pw_aff *OneAff = isl_pw_aff_val_on_domain(Univ, One);

    for (long i = 0, n = isl_set_dim(Set, isl_dim_set); i < n; i++) {
      isl_pw_aff *Max = isl_set_dim_max(isl_set_copy(Set), i);
      isl_pw_aff *Min = isl_set_dim_min(isl_set_copy(Set), i);
      isl_pw_aff *DimSize = isl_pw_aff_sub(Max, Min);
      DimSize = isl_pw_aff_add(DimSize, isl_pw_aff_copy(OneAff));
      auto DimSizeExpr = isl_ast_build_expr_from_pw_aff(Build, DimSize);
      Expr = isl_ast_expr_mul(Expr, DimSizeExpr);
    }

    isl_set_free(Set);
    isl_pw_aff_free(OneAff);

    return Expr;
  }

  /// Approximate a number of dynamic instructions executed by a given
  /// statement.
  ///
  /// @param Stmt  The statement for which to compute the number of dynamic
  ///              instructions.
  /// @param Build The isl ast build object to use for creating the ast
  ///              expression.
  /// @returns An approximation of the number of dynamic instructions executed
  ///          by @p Stmt.
  __isl_give isl_ast_expr *approxDynamicInst(ScopStmt &Stmt,
                                             __isl_keep isl_ast_build *Build) {
    auto Iterations = approxPointsInSet(Stmt.getDomain().release(), Build);

    long InstCount = 0;

    if (Stmt.isBlockStmt()) {
      auto *BB = Stmt.getBasicBlock();
      InstCount = std::distance(BB->begin(), BB->end());
    } else {
      auto *R = Stmt.getRegion();

      for (auto *BB : R->blocks()) {
        InstCount += std::distance(BB->begin(), BB->end());
      }
    }

    isl_val *InstVal = isl_val_int_from_si(S->getIslCtx().get(), InstCount);
    auto *InstExpr = isl_ast_expr_from_val(InstVal);
    return isl_ast_expr_mul(InstExpr, Iterations);
  }

  /// Approximate dynamic instructions executed in scop.
  ///
  /// @param S     The scop for which to approximate dynamic instructions.
  /// @param Build The isl ast build object to use for creating the ast
  ///              expression.
  /// @returns An approximation of the number of dynamic instructions executed
  ///          in @p S.
  __isl_give isl_ast_expr *
  getNumberOfIterations(Scop &S, __isl_keep isl_ast_build *Build) {
    isl_ast_expr *Instructions;

    isl_val *Zero = isl_val_int_from_si(S.getIslCtx().get(), 0);
    Instructions = isl_ast_expr_from_val(Zero);

    for (ScopStmt &Stmt : S) {
      isl_ast_expr *StmtInstructions = approxDynamicInst(Stmt, Build);
      Instructions = isl_ast_expr_add(Instructions, StmtInstructions);
    }
    return Instructions;
  }

  /// Create a check that ensures sufficient compute in scop.
  ///
  /// @param S     The scop for which to ensure sufficient compute.
  /// @param Build The isl ast build object to use for creating the ast
  ///              expression.
  /// @returns An expression that evaluates to TRUE in case of sufficient
  ///          compute and to FALSE, otherwise.
  __isl_give isl_ast_expr *
  createSufficientComputeCheck(Scop &S, __isl_keep isl_ast_build *Build) {
    auto Iterations = getNumberOfIterations(S, Build);
    auto *MinComputeVal = isl_val_int_from_si(S.getIslCtx().get(), MinCompute);
    auto *MinComputeExpr = isl_ast_expr_from_val(MinComputeVal);
    return isl_ast_expr_ge(Iterations, MinComputeExpr);
  }

  /// Check if the basic block contains a function we cannot codegen for GPU
  /// kernels.
  ///
  /// If this basic block does something with a `Function` other than calling
  /// a function that we support in a kernel, return true.
  bool containsInvalidKernelFunctionInBlock(const BasicBlock *BB,
                                            bool AllowCUDALibDevice) {
    for (const Instruction &Inst : *BB) {
      const CallInst *Call = dyn_cast<CallInst>(&Inst);
      if (Call && isValidFunctionInKernel(Call->getCalledFunction(),
                                          AllowCUDALibDevice))
        continue;

      for (Value *Op : Inst.operands())
        // Look for (<func-type>*) among operands of Inst
        if (auto PtrTy = dyn_cast<PointerType>(Op->getType())) {
          if (isa<FunctionType>(PtrTy->getElementType())) {
            LLVM_DEBUG(dbgs()
                       << Inst << " has illegal use of function in kernel.\n");
            return true;
          }
        }
    }
    return false;
  }

  /// Return whether the Scop S uses functions in a way that we do not support.
  bool containsInvalidKernelFunction(const Scop &S, bool AllowCUDALibDevice) {
    for (auto &Stmt : S) {
      if (Stmt.isBlockStmt()) {
        if (containsInvalidKernelFunctionInBlock(Stmt.getBasicBlock(),
                                                 AllowCUDALibDevice))
          return true;
      } else {
        assert(Stmt.isRegionStmt() &&
               "Stmt was neither block nor region statement");
        for (const BasicBlock *BB : Stmt.getRegion()->blocks())
          if (containsInvalidKernelFunctionInBlock(BB, AllowCUDALibDevice))
            return true;
      }
    }
    return false;
  }

  /// Generate code for a given GPU AST described by @p Root.
  ///
  /// @param Root An isl_ast_node pointing to the root of the GPU AST.
  /// @param Prog The GPU Program to generate code for.
  void generateCode(__isl_take isl_ast_node *Root, gpu_prog *Prog) {
    ScopAnnotator Annotator;
    Annotator.buildAliasScopes(*S);

    Region *R = &S->getRegion();

    simplifyRegion(R, DT, LI, RI);

    BasicBlock *EnteringBB = R->getEnteringBlock();

    PollyIRBuilder Builder = createPollyIRBuilder(EnteringBB, Annotator);

    // Only build the run-time condition and parameters _after_ having
    // introduced the conditional branch. This is important as the conditional
    // branch will guard the original scop from new induction variables that
    // the SCEVExpander may introduce while code generating the parameters and
    // which may introduce scalar dependences that prevent us from correctly
    // code generating this scop.
    BBPair StartExitBlocks;
    BranchInst *CondBr = nullptr;
    std::tie(StartExitBlocks, CondBr) =
        executeScopConditionally(*S, Builder.getTrue(), *DT, *RI, *LI);
    BasicBlock *StartBlock = std::get<0>(StartExitBlocks);

    assert(CondBr && "CondBr not initialized by executeScopConditionally");

    GPUNodeBuilder NodeBuilder(Builder, Annotator, *DL, *LI, *SE, *DT, *S,
                               StartBlock, Prog, Runtime, Architecture);

    // TODO: Handle LICM
    auto SplitBlock = StartBlock->getSinglePredecessor();
    Builder.SetInsertPoint(SplitBlock->getTerminator());

    isl_ast_build *Build = isl_ast_build_alloc(S->getIslCtx().get());
    isl_ast_expr *Condition = IslAst::buildRunCondition(*S, Build);
    isl_ast_expr *SufficientCompute = createSufficientComputeCheck(*S, Build);
    Condition = isl_ast_expr_and(Condition, SufficientCompute);
    isl_ast_build_free(Build);

    // preload invariant loads. Note: This should happen before the RTC
    // because the RTC may depend on values that are invariant load hoisted.
    if (!NodeBuilder.preloadInvariantLoads()) {
      // Patch the introduced branch condition to ensure that we always execute
      // the original SCoP.
      auto *FalseI1 = Builder.getFalse();
      auto *SplitBBTerm = Builder.GetInsertBlock()->getTerminator();
      SplitBBTerm->setOperand(0, FalseI1);

      LLVM_DEBUG(dbgs() << "preloading invariant loads failed in function: " +
                               S->getFunction().getName() +
                               " | Scop Region: " + S->getNameStr());
      // adjust the dominator tree accordingly.
      auto *ExitingBlock = StartBlock->getUniqueSuccessor();
      assert(ExitingBlock);
      auto *MergeBlock = ExitingBlock->getUniqueSuccessor();
      assert(MergeBlock);
      polly::markBlockUnreachable(*StartBlock, Builder);
      polly::markBlockUnreachable(*ExitingBlock, Builder);
      auto *ExitingBB = S->getExitingBlock();
      assert(ExitingBB);

      DT->changeImmediateDominator(MergeBlock, ExitingBB);
      DT->eraseNode(ExitingBlock);
      isl_ast_expr_free(Condition);
      isl_ast_node_free(Root);
    } else {

      if (polly::PerfMonitoring) {
        PerfMonitor P(*S, EnteringBB->getParent()->getParent());
        P.initialize();
        P.insertRegionStart(SplitBlock->getTerminator());

        // TODO: actually think if this is the correct exiting block to place
        // the `end` performance marker. Invariant load hoisting changes
        // the CFG in a way that I do not precisely understand, so I
        // (Siddharth<siddu.druid@gmail.com>) should come back to this and
        // think about which exiting block to use.
        auto *ExitingBlock = StartBlock->getUniqueSuccessor();
        assert(ExitingBlock);
        BasicBlock *MergeBlock = ExitingBlock->getUniqueSuccessor();
        P.insertRegionEnd(MergeBlock->getTerminator());
      }

      NodeBuilder.addParameters(S->getContext().release());
      Value *RTC = NodeBuilder.createRTC(Condition);
      Builder.GetInsertBlock()->getTerminator()->setOperand(0, RTC);

      Builder.SetInsertPoint(&*StartBlock->begin());

      NodeBuilder.create(Root);
    }

    /// In case a sequential kernel has more surrounding loops as any parallel
    /// kernel, the SCoP is probably mostly sequential. Hence, there is no
    /// point in running it on a GPU.
    if (NodeBuilder.DeepestSequential > NodeBuilder.DeepestParallel)
      CondBr->setOperand(0, Builder.getFalse());

    if (!NodeBuilder.BuildSuccessful)
      CondBr->setOperand(0, Builder.getFalse());
  }

  bool runOnScop(Scop &CurrentScop) override {
    S = &CurrentScop;
    LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
    DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree();
    SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE();
    DL = &S->getRegion().getEntry()->getModule()->getDataLayout();
    RI = &getAnalysis<RegionInfoPass>().getRegionInfo();

    LLVM_DEBUG(dbgs() << "PPCGCodeGen running on : " << getUniqueScopName(S)
                      << " | loop depth: " << S->getMaxLoopDepth() << "\n");

    // We currently do not support functions other than intrinsics inside
    // kernels, as code generation will need to offload function calls to the
    // kernel. This may lead to a kernel trying to call a function on the host.
    // This also allows us to prevent codegen from trying to take the
    // address of an intrinsic function to send to the kernel.
    if (containsInvalidKernelFunction(CurrentScop,
                                      Architecture == GPUArch::NVPTX64)) {
      LLVM_DEBUG(
          dbgs() << getUniqueScopName(S)
                 << " contains function which cannot be materialised in a GPU "
                    "kernel. Bailing out.\n";);
      return false;
    }

    auto PPCGScop = createPPCGScop();
    auto PPCGProg = createPPCGProg(PPCGScop);
    auto PPCGGen = generateGPU(PPCGScop, PPCGProg);

    if (PPCGGen->tree) {
      generateCode(isl_ast_node_copy(PPCGGen->tree), PPCGProg);
      CurrentScop.markAsToBeSkipped();
    } else {
      LLVM_DEBUG(dbgs() << getUniqueScopName(S)
                        << " has empty PPCGGen->tree. Bailing out.\n");
    }

    freeOptions(PPCGScop);
    freePPCGGen(PPCGGen);
    gpu_prog_free(PPCGProg);
    ppcg_scop_free(PPCGScop);

    return true;
  }

  void printScop(raw_ostream &, Scop &) const override {}

  void getAnalysisUsage(AnalysisUsage &AU) const override {
    ScopPass::getAnalysisUsage(AU);

    AU.addRequired<DominatorTreeWrapperPass>();
    AU.addRequired<RegionInfoPass>();
    AU.addRequired<ScalarEvolutionWrapperPass>();
    AU.addRequired<ScopDetectionWrapperPass>();
    AU.addRequired<ScopInfoRegionPass>();
    AU.addRequired<LoopInfoWrapperPass>();

    // FIXME: We do not yet add regions for the newly generated code to the
    //        region tree.
  }
};
} // namespace

char PPCGCodeGeneration::ID = 1;

Pass *polly::createPPCGCodeGenerationPass(GPUArch Arch, GPURuntime Runtime) {
  PPCGCodeGeneration *generator = new PPCGCodeGeneration();
  generator->Runtime = Runtime;
  generator->Architecture = Arch;
  return generator;
}

INITIALIZE_PASS_BEGIN(PPCGCodeGeneration, "polly-codegen-ppcg",
                      "Polly - Apply PPCG translation to SCOP", false, false)
INITIALIZE_PASS_DEPENDENCY(DependenceInfo);
INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass);
INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass);
INITIALIZE_PASS_DEPENDENCY(RegionInfoPass);
INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass);
INITIALIZE_PASS_DEPENDENCY(ScopDetectionWrapperPass);
INITIALIZE_PASS_END(PPCGCodeGeneration, "polly-codegen-ppcg",
                    "Polly - Apply PPCG translation to SCOP", false, false)