1 //===------ PPCGCodeGeneration.cpp - Polly Accelerator Code Generation. ---===// 2 // 3 // The LLVM Compiler Infrastructure 4 // 5 // This file is distributed under the University of Illinois Open Source 6 // License. See LICENSE.TXT for details. 7 // 8 //===----------------------------------------------------------------------===// 9 // 10 // Take a scop created by ScopInfo and map it to GPU code using the ppcg 11 // GPU mapping strategy. 12 // 13 //===----------------------------------------------------------------------===// 14 15 #include "polly/CodeGen/IslAst.h" 16 #include "polly/CodeGen/IslNodeBuilder.h" 17 #include "polly/CodeGen/Utils.h" 18 #include "polly/DependenceInfo.h" 19 #include "polly/LinkAllPasses.h" 20 #include "polly/Options.h" 21 #include "polly/ScopDetection.h" 22 #include "polly/ScopInfo.h" 23 #include "polly/Support/SCEVValidator.h" 24 #include "llvm/ADT/PostOrderIterator.h" 25 #include "llvm/Analysis/AliasAnalysis.h" 26 #include "llvm/Analysis/BasicAliasAnalysis.h" 27 #include "llvm/Analysis/GlobalsModRef.h" 28 #include "llvm/Analysis/PostDominators.h" 29 #include "llvm/Analysis/ScalarEvolutionAliasAnalysis.h" 30 #include "llvm/Analysis/TargetLibraryInfo.h" 31 #include "llvm/Analysis/TargetTransformInfo.h" 32 #include "llvm/IR/LegacyPassManager.h" 33 #include "llvm/IR/Verifier.h" 34 #include "llvm/Support/TargetRegistry.h" 35 #include "llvm/Support/TargetSelect.h" 36 #include "llvm/Target/TargetMachine.h" 37 #include "llvm/Transforms/IPO/PassManagerBuilder.h" 38 #include "llvm/Transforms/Utils/BasicBlockUtils.h" 39 40 #include "isl/union_map.h" 41 42 extern "C" { 43 #include "ppcg/cuda.h" 44 #include "ppcg/gpu.h" 45 #include "ppcg/gpu_print.h" 46 #include "ppcg/ppcg.h" 47 #include "ppcg/schedule.h" 48 } 49 50 #include "llvm/Support/Debug.h" 51 52 using namespace polly; 53 using namespace llvm; 54 55 #define DEBUG_TYPE "polly-codegen-ppcg" 56 57 static cl::opt<bool> DumpSchedule("polly-acc-dump-schedule", 58 cl::desc("Dump the computed GPU Schedule"), 59 cl::Hidden, cl::init(false), cl::ZeroOrMore, 60 cl::cat(PollyCategory)); 61 62 static cl::opt<bool> 63 DumpCode("polly-acc-dump-code", 64 cl::desc("Dump C code describing the GPU mapping"), cl::Hidden, 65 cl::init(false), cl::ZeroOrMore, cl::cat(PollyCategory)); 66 67 static cl::opt<bool> DumpKernelIR("polly-acc-dump-kernel-ir", 68 cl::desc("Dump the kernel LLVM-IR"), 69 cl::Hidden, cl::init(false), cl::ZeroOrMore, 70 cl::cat(PollyCategory)); 71 72 static cl::opt<bool> DumpKernelASM("polly-acc-dump-kernel-asm", 73 cl::desc("Dump the kernel assembly code"), 74 cl::Hidden, cl::init(false), cl::ZeroOrMore, 75 cl::cat(PollyCategory)); 76 77 static cl::opt<bool> FastMath("polly-acc-fastmath", 78 cl::desc("Allow unsafe math optimizations"), 79 cl::Hidden, cl::init(false), cl::ZeroOrMore, 80 cl::cat(PollyCategory)); 81 static cl::opt<bool> SharedMemory("polly-acc-use-shared", 82 cl::desc("Use shared memory"), cl::Hidden, 83 cl::init(false), cl::ZeroOrMore, 84 cl::cat(PollyCategory)); 85 static cl::opt<bool> PrivateMemory("polly-acc-use-private", 86 cl::desc("Use private memory"), cl::Hidden, 87 cl::init(false), cl::ZeroOrMore, 88 cl::cat(PollyCategory)); 89 90 static cl::opt<std::string> 91 CudaVersion("polly-acc-cuda-version", 92 cl::desc("The CUDA version to compile for"), cl::Hidden, 93 cl::init("sm_30"), cl::ZeroOrMore, cl::cat(PollyCategory)); 94 95 /// Create the ast expressions for a ScopStmt. 96 /// 97 /// This function is a callback for to generate the ast expressions for each 98 /// of the scheduled ScopStmts. 99 static __isl_give isl_id_to_ast_expr *pollyBuildAstExprForStmt( 100 void *StmtT, isl_ast_build *Build, 101 isl_multi_pw_aff *(*FunctionIndex)(__isl_take isl_multi_pw_aff *MPA, 102 isl_id *Id, void *User), 103 void *UserIndex, 104 isl_ast_expr *(*FunctionExpr)(isl_ast_expr *Expr, isl_id *Id, void *User), 105 void *UserExpr) { 106 107 ScopStmt *Stmt = (ScopStmt *)StmtT; 108 109 isl_ctx *Ctx; 110 111 if (!Stmt || !Build) 112 return NULL; 113 114 Ctx = isl_ast_build_get_ctx(Build); 115 isl_id_to_ast_expr *RefToExpr = isl_id_to_ast_expr_alloc(Ctx, 0); 116 117 for (MemoryAccess *Acc : *Stmt) { 118 isl_map *AddrFunc = Acc->getAddressFunction(); 119 AddrFunc = isl_map_intersect_domain(AddrFunc, Stmt->getDomain()); 120 isl_id *RefId = Acc->getId(); 121 isl_pw_multi_aff *PMA = isl_pw_multi_aff_from_map(AddrFunc); 122 isl_multi_pw_aff *MPA = isl_multi_pw_aff_from_pw_multi_aff(PMA); 123 MPA = isl_multi_pw_aff_coalesce(MPA); 124 MPA = FunctionIndex(MPA, RefId, UserIndex); 125 isl_ast_expr *Access = isl_ast_build_access_from_multi_pw_aff(Build, MPA); 126 Access = FunctionExpr(Access, RefId, UserExpr); 127 RefToExpr = isl_id_to_ast_expr_set(RefToExpr, RefId, Access); 128 } 129 130 return RefToExpr; 131 } 132 133 /// Generate code for a GPU specific isl AST. 134 /// 135 /// The GPUNodeBuilder augments the general existing IslNodeBuilder, which 136 /// generates code for general-prupose AST nodes, with special functionality 137 /// for generating GPU specific user nodes. 138 /// 139 /// @see GPUNodeBuilder::createUser 140 class GPUNodeBuilder : public IslNodeBuilder { 141 public: 142 GPUNodeBuilder(PollyIRBuilder &Builder, ScopAnnotator &Annotator, Pass *P, 143 const DataLayout &DL, LoopInfo &LI, ScalarEvolution &SE, 144 DominatorTree &DT, Scop &S, gpu_prog *Prog) 145 : IslNodeBuilder(Builder, Annotator, P, DL, LI, SE, DT, S), Prog(Prog) { 146 getExprBuilder().setIDToSAI(&IDToSAI); 147 } 148 149 /// Create after-run-time-check initialization code. 150 void initializeAfterRTH(); 151 152 /// Finalize the generated scop. 153 virtual void finalize(); 154 155 /// Track if the full build process was successful. 156 /// 157 /// This value is set to false, if throughout the build process an error 158 /// occurred which prevents us from generating valid GPU code. 159 bool BuildSuccessful = true; 160 161 private: 162 /// A vector of array base pointers for which a new ScopArrayInfo was created. 163 /// 164 /// This vector is used to delete the ScopArrayInfo when it is not needed any 165 /// more. 166 std::vector<Value *> LocalArrays; 167 168 /// A map from ScopArrays to their corresponding device allocations. 169 std::map<ScopArrayInfo *, Value *> DeviceAllocations; 170 171 /// The current GPU context. 172 Value *GPUContext; 173 174 /// The set of isl_ids allocated in the kernel 175 std::vector<isl_id *> KernelIds; 176 177 /// A module containing GPU code. 178 /// 179 /// This pointer is only set in case we are currently generating GPU code. 180 std::unique_ptr<Module> GPUModule; 181 182 /// The GPU program we generate code for. 183 gpu_prog *Prog; 184 185 /// Class to free isl_ids. 186 class IslIdDeleter { 187 public: 188 void operator()(__isl_take isl_id *Id) { isl_id_free(Id); }; 189 }; 190 191 /// A set containing all isl_ids allocated in a GPU kernel. 192 /// 193 /// By releasing this set all isl_ids will be freed. 194 std::set<std::unique_ptr<isl_id, IslIdDeleter>> KernelIDs; 195 196 IslExprBuilder::IDToScopArrayInfoTy IDToSAI; 197 198 /// Create code for user-defined AST nodes. 199 /// 200 /// These AST nodes can be of type: 201 /// 202 /// - ScopStmt: A computational statement (TODO) 203 /// - Kernel: A GPU kernel call (TODO) 204 /// - Data-Transfer: A GPU <-> CPU data-transfer 205 /// - In-kernel synchronization 206 /// - In-kernel memory copy statement 207 /// 208 /// @param UserStmt The ast node to generate code for. 209 virtual void createUser(__isl_take isl_ast_node *UserStmt); 210 211 enum DataDirection { HOST_TO_DEVICE, DEVICE_TO_HOST }; 212 213 /// Create code for a data transfer statement 214 /// 215 /// @param TransferStmt The data transfer statement. 216 /// @param Direction The direction in which to transfer data. 217 void createDataTransfer(__isl_take isl_ast_node *TransferStmt, 218 enum DataDirection Direction); 219 220 /// Find llvm::Values referenced in GPU kernel. 221 /// 222 /// @param Kernel The kernel to scan for llvm::Values 223 /// 224 /// @returns A set of values referenced by the kernel. 225 SetVector<Value *> getReferencesInKernel(ppcg_kernel *Kernel); 226 227 /// Compute the sizes of the execution grid for a given kernel. 228 /// 229 /// @param Kernel The kernel to compute grid sizes for. 230 /// 231 /// @returns A tuple with grid sizes for X and Y dimension 232 std::tuple<Value *, Value *> getGridSizes(ppcg_kernel *Kernel); 233 234 /// Compute the sizes of the thread blocks for a given kernel. 235 /// 236 /// @param Kernel The kernel to compute thread block sizes for. 237 /// 238 /// @returns A tuple with thread block sizes for X, Y, and Z dimensions. 239 std::tuple<Value *, Value *, Value *> getBlockSizes(ppcg_kernel *Kernel); 240 241 /// Create kernel launch parameters. 242 /// 243 /// @param Kernel The kernel to create parameters for. 244 /// @param F The kernel function that has been created. 245 /// @param SubtreeValues The set of llvm::Values referenced by this kernel. 246 /// 247 /// @returns A stack allocated array with pointers to the parameter 248 /// values that are passed to the kernel. 249 Value *createLaunchParameters(ppcg_kernel *Kernel, Function *F, 250 SetVector<Value *> SubtreeValues); 251 252 /// Create declarations for kernel variable. 253 /// 254 /// This includes shared memory declarations. 255 /// 256 /// @param Kernel The kernel definition to create variables for. 257 /// @param FN The function into which to generate the variables. 258 void createKernelVariables(ppcg_kernel *Kernel, Function *FN); 259 260 /// Add CUDA annotations to module. 261 /// 262 /// Add a set of CUDA annotations that declares the maximal block dimensions 263 /// that will be used to execute the CUDA kernel. This allows the NVIDIA 264 /// PTX compiler to bound the number of allocated registers to ensure the 265 /// resulting kernel is known to run with up to as many block dimensions 266 /// as specified here. 267 /// 268 /// @param M The module to add the annotations to. 269 /// @param BlockDimX The size of block dimension X. 270 /// @param BlockDimY The size of block dimension Y. 271 /// @param BlockDimZ The size of block dimension Z. 272 void addCUDAAnnotations(Module *M, Value *BlockDimX, Value *BlockDimY, 273 Value *BlockDimZ); 274 275 /// Create GPU kernel. 276 /// 277 /// Code generate the kernel described by @p KernelStmt. 278 /// 279 /// @param KernelStmt The ast node to generate kernel code for. 280 void createKernel(__isl_take isl_ast_node *KernelStmt); 281 282 /// Generate code that computes the size of an array. 283 /// 284 /// @param Array The array for which to compute a size. 285 Value *getArraySize(gpu_array_info *Array); 286 287 /// Generate code to compute the minimal offset at which an array is accessed. 288 /// 289 /// The offset of an array is the minimal array location accessed in a scop. 290 /// 291 /// Example: 292 /// 293 /// for (long i = 0; i < 100; i++) 294 /// A[i + 42] += ... 295 /// 296 /// getArrayOffset(A) results in 42. 297 /// 298 /// @param Array The array for which to compute the offset. 299 /// @returns An llvm::Value that contains the offset of the array. 300 Value *getArrayOffset(gpu_array_info *Array); 301 302 /// Prepare the kernel arguments for kernel code generation 303 /// 304 /// @param Kernel The kernel to generate code for. 305 /// @param FN The function created for the kernel. 306 void prepareKernelArguments(ppcg_kernel *Kernel, Function *FN); 307 308 /// Create kernel function. 309 /// 310 /// Create a kernel function located in a newly created module that can serve 311 /// as target for device code generation. Set the Builder to point to the 312 /// start block of this newly created function. 313 /// 314 /// @param Kernel The kernel to generate code for. 315 /// @param SubtreeValues The set of llvm::Values referenced by this kernel. 316 void createKernelFunction(ppcg_kernel *Kernel, 317 SetVector<Value *> &SubtreeValues); 318 319 /// Create the declaration of a kernel function. 320 /// 321 /// The kernel function takes as arguments: 322 /// 323 /// - One i8 pointer for each external array reference used in the kernel. 324 /// - Host iterators 325 /// - Parameters 326 /// - Other LLVM Value references (TODO) 327 /// 328 /// @param Kernel The kernel to generate the function declaration for. 329 /// @param SubtreeValues The set of llvm::Values referenced by this kernel. 330 /// 331 /// @returns The newly declared function. 332 Function *createKernelFunctionDecl(ppcg_kernel *Kernel, 333 SetVector<Value *> &SubtreeValues); 334 335 /// Insert intrinsic functions to obtain thread and block ids. 336 /// 337 /// @param The kernel to generate the intrinsic functions for. 338 void insertKernelIntrinsics(ppcg_kernel *Kernel); 339 340 /// Create a global-to-shared or shared-to-global copy statement. 341 /// 342 /// @param CopyStmt The copy statement to generate code for 343 void createKernelCopy(ppcg_kernel_stmt *CopyStmt); 344 345 /// Create code for a ScopStmt called in @p Expr. 346 /// 347 /// @param Expr The expression containing the call. 348 /// @param KernelStmt The kernel statement referenced in the call. 349 void createScopStmt(isl_ast_expr *Expr, ppcg_kernel_stmt *KernelStmt); 350 351 /// Create an in-kernel synchronization call. 352 void createKernelSync(); 353 354 /// Create a PTX assembly string for the current GPU kernel. 355 /// 356 /// @returns A string containing the corresponding PTX assembly code. 357 std::string createKernelASM(); 358 359 /// Remove references from the dominator tree to the kernel function @p F. 360 /// 361 /// @param F The function to remove references to. 362 void clearDominators(Function *F); 363 364 /// Remove references from scalar evolution to the kernel function @p F. 365 /// 366 /// @param F The function to remove references to. 367 void clearScalarEvolution(Function *F); 368 369 /// Remove references from loop info to the kernel function @p F. 370 /// 371 /// @param F The function to remove references to. 372 void clearLoops(Function *F); 373 374 /// Finalize the generation of the kernel function. 375 /// 376 /// Free the LLVM-IR module corresponding to the kernel and -- if requested -- 377 /// dump its IR to stderr. 378 /// 379 /// @returns The Assembly string of the kernel. 380 std::string finalizeKernelFunction(); 381 382 /// Finalize the generation of the kernel arguments. 383 /// 384 /// This function ensures that not-read-only scalars used in a kernel are 385 /// stored back to the global memory location they ared backed up with before 386 /// the kernel terminates. 387 /// 388 /// @params Kernel The kernel to finalize kernel arguments for. 389 void finalizeKernelArguments(ppcg_kernel *Kernel); 390 391 /// Create code that allocates memory to store arrays on device. 392 void allocateDeviceArrays(); 393 394 /// Free all allocated device arrays. 395 void freeDeviceArrays(); 396 397 /// Create a call to initialize the GPU context. 398 /// 399 /// @returns A pointer to the newly initialized context. 400 Value *createCallInitContext(); 401 402 /// Create a call to get the device pointer for a kernel allocation. 403 /// 404 /// @param Allocation The Polly GPU allocation 405 /// 406 /// @returns The device parameter corresponding to this allocation. 407 Value *createCallGetDevicePtr(Value *Allocation); 408 409 /// Create a call to free the GPU context. 410 /// 411 /// @param Context A pointer to an initialized GPU context. 412 void createCallFreeContext(Value *Context); 413 414 /// Create a call to allocate memory on the device. 415 /// 416 /// @param Size The size of memory to allocate 417 /// 418 /// @returns A pointer that identifies this allocation. 419 Value *createCallAllocateMemoryForDevice(Value *Size); 420 421 /// Create a call to free a device array. 422 /// 423 /// @param Array The device array to free. 424 void createCallFreeDeviceMemory(Value *Array); 425 426 /// Create a call to copy data from host to device. 427 /// 428 /// @param HostPtr A pointer to the host data that should be copied. 429 /// @param DevicePtr A device pointer specifying the location to copy to. 430 void createCallCopyFromHostToDevice(Value *HostPtr, Value *DevicePtr, 431 Value *Size); 432 433 /// Create a call to copy data from device to host. 434 /// 435 /// @param DevicePtr A pointer to the device data that should be copied. 436 /// @param HostPtr A host pointer specifying the location to copy to. 437 void createCallCopyFromDeviceToHost(Value *DevicePtr, Value *HostPtr, 438 Value *Size); 439 440 /// Create a call to get a kernel from an assembly string. 441 /// 442 /// @param Buffer The string describing the kernel. 443 /// @param Entry The name of the kernel function to call. 444 /// 445 /// @returns A pointer to a kernel object 446 Value *createCallGetKernel(Value *Buffer, Value *Entry); 447 448 /// Create a call to free a GPU kernel. 449 /// 450 /// @param GPUKernel THe kernel to free. 451 void createCallFreeKernel(Value *GPUKernel); 452 453 /// Create a call to launch a GPU kernel. 454 /// 455 /// @param GPUKernel The kernel to launch. 456 /// @param GridDimX The size of the first grid dimension. 457 /// @param GridDimY The size of the second grid dimension. 458 /// @param GridBlockX The size of the first block dimension. 459 /// @param GridBlockY The size of the second block dimension. 460 /// @param GridBlockZ The size of the third block dimension. 461 /// @param Paramters A pointer to an array that contains itself pointers to 462 /// the parameter values passed for each kernel argument. 463 void createCallLaunchKernel(Value *GPUKernel, Value *GridDimX, 464 Value *GridDimY, Value *BlockDimX, 465 Value *BlockDimY, Value *BlockDimZ, 466 Value *Parameters); 467 }; 468 469 void GPUNodeBuilder::initializeAfterRTH() { 470 BasicBlock *NewBB = SplitBlock(Builder.GetInsertBlock(), 471 &*Builder.GetInsertPoint(), &DT, &LI); 472 NewBB->setName("polly.acc.initialize"); 473 Builder.SetInsertPoint(&NewBB->front()); 474 475 GPUContext = createCallInitContext(); 476 allocateDeviceArrays(); 477 } 478 479 void GPUNodeBuilder::finalize() { 480 freeDeviceArrays(); 481 createCallFreeContext(GPUContext); 482 IslNodeBuilder::finalize(); 483 } 484 485 void GPUNodeBuilder::allocateDeviceArrays() { 486 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 487 488 for (int i = 0; i < Prog->n_array; ++i) { 489 gpu_array_info *Array = &Prog->array[i]; 490 auto *ScopArray = (ScopArrayInfo *)Array->user; 491 std::string DevArrayName("p_dev_array_"); 492 DevArrayName.append(Array->name); 493 494 Value *ArraySize = getArraySize(Array); 495 Value *Offset = getArrayOffset(Array); 496 if (Offset) 497 ArraySize = Builder.CreateSub( 498 ArraySize, 499 Builder.CreateMul(Offset, 500 Builder.getInt64(ScopArray->getElemSizeInBytes()))); 501 Value *DevArray = createCallAllocateMemoryForDevice(ArraySize); 502 DevArray->setName(DevArrayName); 503 DeviceAllocations[ScopArray] = DevArray; 504 } 505 506 isl_ast_build_free(Build); 507 } 508 509 void GPUNodeBuilder::addCUDAAnnotations(Module *M, Value *BlockDimX, 510 Value *BlockDimY, Value *BlockDimZ) { 511 auto AnnotationNode = M->getOrInsertNamedMetadata("nvvm.annotations"); 512 513 for (auto &F : *M) { 514 if (F.getCallingConv() != CallingConv::PTX_Kernel) 515 continue; 516 517 Value *V[] = {BlockDimX, BlockDimY, BlockDimZ}; 518 519 Metadata *Elements[] = { 520 ValueAsMetadata::get(&F), MDString::get(M->getContext(), "maxntidx"), 521 ValueAsMetadata::get(V[0]), MDString::get(M->getContext(), "maxntidy"), 522 ValueAsMetadata::get(V[1]), MDString::get(M->getContext(), "maxntidz"), 523 ValueAsMetadata::get(V[2]), 524 }; 525 MDNode *Node = MDNode::get(M->getContext(), Elements); 526 AnnotationNode->addOperand(Node); 527 } 528 } 529 530 void GPUNodeBuilder::freeDeviceArrays() { 531 for (auto &Array : DeviceAllocations) 532 createCallFreeDeviceMemory(Array.second); 533 } 534 535 Value *GPUNodeBuilder::createCallGetKernel(Value *Buffer, Value *Entry) { 536 const char *Name = "polly_getKernel"; 537 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 538 Function *F = M->getFunction(Name); 539 540 // If F is not available, declare it. 541 if (!F) { 542 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 543 std::vector<Type *> Args; 544 Args.push_back(Builder.getInt8PtrTy()); 545 Args.push_back(Builder.getInt8PtrTy()); 546 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 547 F = Function::Create(Ty, Linkage, Name, M); 548 } 549 550 return Builder.CreateCall(F, {Buffer, Entry}); 551 } 552 553 Value *GPUNodeBuilder::createCallGetDevicePtr(Value *Allocation) { 554 const char *Name = "polly_getDevicePtr"; 555 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 556 Function *F = M->getFunction(Name); 557 558 // If F is not available, declare it. 559 if (!F) { 560 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 561 std::vector<Type *> Args; 562 Args.push_back(Builder.getInt8PtrTy()); 563 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 564 F = Function::Create(Ty, Linkage, Name, M); 565 } 566 567 return Builder.CreateCall(F, {Allocation}); 568 } 569 570 void GPUNodeBuilder::createCallLaunchKernel(Value *GPUKernel, Value *GridDimX, 571 Value *GridDimY, Value *BlockDimX, 572 Value *BlockDimY, Value *BlockDimZ, 573 Value *Parameters) { 574 const char *Name = "polly_launchKernel"; 575 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 576 Function *F = M->getFunction(Name); 577 578 // If F is not available, declare it. 579 if (!F) { 580 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 581 std::vector<Type *> Args; 582 Args.push_back(Builder.getInt8PtrTy()); 583 Args.push_back(Builder.getInt32Ty()); 584 Args.push_back(Builder.getInt32Ty()); 585 Args.push_back(Builder.getInt32Ty()); 586 Args.push_back(Builder.getInt32Ty()); 587 Args.push_back(Builder.getInt32Ty()); 588 Args.push_back(Builder.getInt8PtrTy()); 589 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 590 F = Function::Create(Ty, Linkage, Name, M); 591 } 592 593 Builder.CreateCall(F, {GPUKernel, GridDimX, GridDimY, BlockDimX, BlockDimY, 594 BlockDimZ, Parameters}); 595 } 596 597 void GPUNodeBuilder::createCallFreeKernel(Value *GPUKernel) { 598 const char *Name = "polly_freeKernel"; 599 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 600 Function *F = M->getFunction(Name); 601 602 // If F is not available, declare it. 603 if (!F) { 604 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 605 std::vector<Type *> Args; 606 Args.push_back(Builder.getInt8PtrTy()); 607 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 608 F = Function::Create(Ty, Linkage, Name, M); 609 } 610 611 Builder.CreateCall(F, {GPUKernel}); 612 } 613 614 void GPUNodeBuilder::createCallFreeDeviceMemory(Value *Array) { 615 const char *Name = "polly_freeDeviceMemory"; 616 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 617 Function *F = M->getFunction(Name); 618 619 // If F is not available, declare it. 620 if (!F) { 621 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 622 std::vector<Type *> Args; 623 Args.push_back(Builder.getInt8PtrTy()); 624 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 625 F = Function::Create(Ty, Linkage, Name, M); 626 } 627 628 Builder.CreateCall(F, {Array}); 629 } 630 631 Value *GPUNodeBuilder::createCallAllocateMemoryForDevice(Value *Size) { 632 const char *Name = "polly_allocateMemoryForDevice"; 633 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 634 Function *F = M->getFunction(Name); 635 636 // If F is not available, declare it. 637 if (!F) { 638 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 639 std::vector<Type *> Args; 640 Args.push_back(Builder.getInt64Ty()); 641 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 642 F = Function::Create(Ty, Linkage, Name, M); 643 } 644 645 return Builder.CreateCall(F, {Size}); 646 } 647 648 void GPUNodeBuilder::createCallCopyFromHostToDevice(Value *HostData, 649 Value *DeviceData, 650 Value *Size) { 651 const char *Name = "polly_copyFromHostToDevice"; 652 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 653 Function *F = M->getFunction(Name); 654 655 // If F is not available, declare it. 656 if (!F) { 657 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 658 std::vector<Type *> Args; 659 Args.push_back(Builder.getInt8PtrTy()); 660 Args.push_back(Builder.getInt8PtrTy()); 661 Args.push_back(Builder.getInt64Ty()); 662 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 663 F = Function::Create(Ty, Linkage, Name, M); 664 } 665 666 Builder.CreateCall(F, {HostData, DeviceData, Size}); 667 } 668 669 void GPUNodeBuilder::createCallCopyFromDeviceToHost(Value *DeviceData, 670 Value *HostData, 671 Value *Size) { 672 const char *Name = "polly_copyFromDeviceToHost"; 673 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 674 Function *F = M->getFunction(Name); 675 676 // If F is not available, declare it. 677 if (!F) { 678 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 679 std::vector<Type *> Args; 680 Args.push_back(Builder.getInt8PtrTy()); 681 Args.push_back(Builder.getInt8PtrTy()); 682 Args.push_back(Builder.getInt64Ty()); 683 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 684 F = Function::Create(Ty, Linkage, Name, M); 685 } 686 687 Builder.CreateCall(F, {DeviceData, HostData, Size}); 688 } 689 690 Value *GPUNodeBuilder::createCallInitContext() { 691 const char *Name = "polly_initContext"; 692 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 693 Function *F = M->getFunction(Name); 694 695 // If F is not available, declare it. 696 if (!F) { 697 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 698 std::vector<Type *> Args; 699 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 700 F = Function::Create(Ty, Linkage, Name, M); 701 } 702 703 return Builder.CreateCall(F, {}); 704 } 705 706 void GPUNodeBuilder::createCallFreeContext(Value *Context) { 707 const char *Name = "polly_freeContext"; 708 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 709 Function *F = M->getFunction(Name); 710 711 // If F is not available, declare it. 712 if (!F) { 713 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 714 std::vector<Type *> Args; 715 Args.push_back(Builder.getInt8PtrTy()); 716 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 717 F = Function::Create(Ty, Linkage, Name, M); 718 } 719 720 Builder.CreateCall(F, {Context}); 721 } 722 723 /// Check if one string is a prefix of another. 724 /// 725 /// @param String The string in which to look for the prefix. 726 /// @param Prefix The prefix to look for. 727 static bool isPrefix(std::string String, std::string Prefix) { 728 return String.find(Prefix) == 0; 729 } 730 731 Value *GPUNodeBuilder::getArraySize(gpu_array_info *Array) { 732 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 733 Value *ArraySize = ConstantInt::get(Builder.getInt64Ty(), Array->size); 734 735 if (!gpu_array_is_scalar(Array)) { 736 auto OffsetDimZero = isl_pw_aff_copy(Array->bound[0]); 737 isl_ast_expr *Res = isl_ast_build_expr_from_pw_aff(Build, OffsetDimZero); 738 739 for (unsigned int i = 1; i < Array->n_index; i++) { 740 isl_pw_aff *Bound_I = isl_pw_aff_copy(Array->bound[i]); 741 isl_ast_expr *Expr = isl_ast_build_expr_from_pw_aff(Build, Bound_I); 742 Res = isl_ast_expr_mul(Res, Expr); 743 } 744 745 Value *NumElements = ExprBuilder.create(Res); 746 if (NumElements->getType() != ArraySize->getType()) 747 NumElements = Builder.CreateSExt(NumElements, ArraySize->getType()); 748 ArraySize = Builder.CreateMul(ArraySize, NumElements); 749 } 750 isl_ast_build_free(Build); 751 return ArraySize; 752 } 753 754 Value *GPUNodeBuilder::getArrayOffset(gpu_array_info *Array) { 755 if (gpu_array_is_scalar(Array)) 756 return nullptr; 757 758 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 759 760 isl_set *Min = isl_set_lexmin(isl_set_copy(Array->extent)); 761 762 isl_set *ZeroSet = isl_set_universe(isl_set_get_space(Min)); 763 764 for (long i = 0; i < isl_set_dim(Min, isl_dim_set); i++) 765 ZeroSet = isl_set_fix_si(ZeroSet, isl_dim_set, i, 0); 766 767 if (isl_set_is_subset(Min, ZeroSet)) { 768 isl_set_free(Min); 769 isl_set_free(ZeroSet); 770 isl_ast_build_free(Build); 771 return nullptr; 772 } 773 isl_set_free(ZeroSet); 774 775 isl_ast_expr *Result = 776 isl_ast_expr_from_val(isl_val_int_from_si(isl_set_get_ctx(Min), 0)); 777 778 for (long i = 0; i < isl_set_dim(Min, isl_dim_set); i++) { 779 if (i > 0) { 780 isl_pw_aff *Bound_I = isl_pw_aff_copy(Array->bound[i - 1]); 781 isl_ast_expr *BExpr = isl_ast_build_expr_from_pw_aff(Build, Bound_I); 782 Result = isl_ast_expr_mul(Result, BExpr); 783 } 784 isl_pw_aff *DimMin = isl_set_dim_min(isl_set_copy(Min), i); 785 isl_ast_expr *MExpr = isl_ast_build_expr_from_pw_aff(Build, DimMin); 786 Result = isl_ast_expr_add(Result, MExpr); 787 } 788 789 Value *ResultValue = ExprBuilder.create(Result); 790 isl_set_free(Min); 791 isl_ast_build_free(Build); 792 793 return ResultValue; 794 } 795 796 void GPUNodeBuilder::createDataTransfer(__isl_take isl_ast_node *TransferStmt, 797 enum DataDirection Direction) { 798 isl_ast_expr *Expr = isl_ast_node_user_get_expr(TransferStmt); 799 isl_ast_expr *Arg = isl_ast_expr_get_op_arg(Expr, 0); 800 isl_id *Id = isl_ast_expr_get_id(Arg); 801 auto Array = (gpu_array_info *)isl_id_get_user(Id); 802 auto ScopArray = (ScopArrayInfo *)(Array->user); 803 804 Value *Size = getArraySize(Array); 805 Value *Offset = getArrayOffset(Array); 806 Value *DevPtr = DeviceAllocations[ScopArray]; 807 808 Value *HostPtr; 809 810 if (gpu_array_is_scalar(Array)) 811 HostPtr = BlockGen.getOrCreateAlloca(ScopArray); 812 else 813 HostPtr = ScopArray->getBasePtr(); 814 815 if (Offset) { 816 HostPtr = Builder.CreatePointerCast( 817 HostPtr, ScopArray->getElementType()->getPointerTo()); 818 HostPtr = Builder.CreateGEP(HostPtr, Offset); 819 } 820 821 HostPtr = Builder.CreatePointerCast(HostPtr, Builder.getInt8PtrTy()); 822 823 if (Offset) { 824 Size = Builder.CreateSub( 825 Size, Builder.CreateMul( 826 Offset, Builder.getInt64(ScopArray->getElemSizeInBytes()))); 827 } 828 829 if (Direction == HOST_TO_DEVICE) 830 createCallCopyFromHostToDevice(HostPtr, DevPtr, Size); 831 else 832 createCallCopyFromDeviceToHost(DevPtr, HostPtr, Size); 833 834 isl_id_free(Id); 835 isl_ast_expr_free(Arg); 836 isl_ast_expr_free(Expr); 837 isl_ast_node_free(TransferStmt); 838 } 839 840 void GPUNodeBuilder::createUser(__isl_take isl_ast_node *UserStmt) { 841 isl_ast_expr *Expr = isl_ast_node_user_get_expr(UserStmt); 842 isl_ast_expr *StmtExpr = isl_ast_expr_get_op_arg(Expr, 0); 843 isl_id *Id = isl_ast_expr_get_id(StmtExpr); 844 isl_id_free(Id); 845 isl_ast_expr_free(StmtExpr); 846 847 const char *Str = isl_id_get_name(Id); 848 if (!strcmp(Str, "kernel")) { 849 createKernel(UserStmt); 850 isl_ast_expr_free(Expr); 851 return; 852 } 853 854 if (isPrefix(Str, "to_device")) { 855 createDataTransfer(UserStmt, HOST_TO_DEVICE); 856 isl_ast_expr_free(Expr); 857 return; 858 } 859 860 if (isPrefix(Str, "from_device")) { 861 createDataTransfer(UserStmt, DEVICE_TO_HOST); 862 isl_ast_expr_free(Expr); 863 return; 864 } 865 866 isl_id *Anno = isl_ast_node_get_annotation(UserStmt); 867 struct ppcg_kernel_stmt *KernelStmt = 868 (struct ppcg_kernel_stmt *)isl_id_get_user(Anno); 869 isl_id_free(Anno); 870 871 switch (KernelStmt->type) { 872 case ppcg_kernel_domain: 873 createScopStmt(Expr, KernelStmt); 874 isl_ast_node_free(UserStmt); 875 return; 876 case ppcg_kernel_copy: 877 createKernelCopy(KernelStmt); 878 isl_ast_expr_free(Expr); 879 isl_ast_node_free(UserStmt); 880 return; 881 case ppcg_kernel_sync: 882 createKernelSync(); 883 isl_ast_expr_free(Expr); 884 isl_ast_node_free(UserStmt); 885 return; 886 } 887 888 isl_ast_expr_free(Expr); 889 isl_ast_node_free(UserStmt); 890 return; 891 } 892 void GPUNodeBuilder::createKernelCopy(ppcg_kernel_stmt *KernelStmt) { 893 isl_ast_expr *LocalIndex = isl_ast_expr_copy(KernelStmt->u.c.local_index); 894 LocalIndex = isl_ast_expr_address_of(LocalIndex); 895 Value *LocalAddr = ExprBuilder.create(LocalIndex); 896 isl_ast_expr *Index = isl_ast_expr_copy(KernelStmt->u.c.index); 897 Index = isl_ast_expr_address_of(Index); 898 Value *GlobalAddr = ExprBuilder.create(Index); 899 900 if (KernelStmt->u.c.read) { 901 LoadInst *Load = Builder.CreateLoad(GlobalAddr, "shared.read"); 902 Builder.CreateStore(Load, LocalAddr); 903 } else { 904 LoadInst *Load = Builder.CreateLoad(LocalAddr, "shared.write"); 905 Builder.CreateStore(Load, GlobalAddr); 906 } 907 } 908 909 void GPUNodeBuilder::createScopStmt(isl_ast_expr *Expr, 910 ppcg_kernel_stmt *KernelStmt) { 911 auto Stmt = (ScopStmt *)KernelStmt->u.d.stmt->stmt; 912 isl_id_to_ast_expr *Indexes = KernelStmt->u.d.ref2expr; 913 914 LoopToScevMapT LTS; 915 LTS.insert(OutsideLoopIterations.begin(), OutsideLoopIterations.end()); 916 917 createSubstitutions(Expr, Stmt, LTS); 918 919 if (Stmt->isBlockStmt()) 920 BlockGen.copyStmt(*Stmt, LTS, Indexes); 921 else 922 RegionGen.copyStmt(*Stmt, LTS, Indexes); 923 } 924 925 void GPUNodeBuilder::createKernelSync() { 926 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 927 auto *Sync = Intrinsic::getDeclaration(M, Intrinsic::nvvm_barrier0); 928 Builder.CreateCall(Sync, {}); 929 } 930 931 /// Collect llvm::Values referenced from @p Node 932 /// 933 /// This function only applies to isl_ast_nodes that are user_nodes referring 934 /// to a ScopStmt. All other node types are ignore. 935 /// 936 /// @param Node The node to collect references for. 937 /// @param User A user pointer used as storage for the data that is collected. 938 /// 939 /// @returns isl_bool_true if data could be collected successfully. 940 isl_bool collectReferencesInGPUStmt(__isl_keep isl_ast_node *Node, void *User) { 941 if (isl_ast_node_get_type(Node) != isl_ast_node_user) 942 return isl_bool_true; 943 944 isl_ast_expr *Expr = isl_ast_node_user_get_expr(Node); 945 isl_ast_expr *StmtExpr = isl_ast_expr_get_op_arg(Expr, 0); 946 isl_id *Id = isl_ast_expr_get_id(StmtExpr); 947 const char *Str = isl_id_get_name(Id); 948 isl_id_free(Id); 949 isl_ast_expr_free(StmtExpr); 950 isl_ast_expr_free(Expr); 951 952 if (!isPrefix(Str, "Stmt")) 953 return isl_bool_true; 954 955 Id = isl_ast_node_get_annotation(Node); 956 auto *KernelStmt = (ppcg_kernel_stmt *)isl_id_get_user(Id); 957 auto Stmt = (ScopStmt *)KernelStmt->u.d.stmt->stmt; 958 isl_id_free(Id); 959 960 addReferencesFromStmt(Stmt, User, false /* CreateScalarRefs */); 961 962 return isl_bool_true; 963 } 964 965 SetVector<Value *> GPUNodeBuilder::getReferencesInKernel(ppcg_kernel *Kernel) { 966 SetVector<Value *> SubtreeValues; 967 SetVector<const SCEV *> SCEVs; 968 SetVector<const Loop *> Loops; 969 SubtreeReferences References = { 970 LI, SE, S, ValueMap, SubtreeValues, SCEVs, getBlockGenerator()}; 971 972 for (const auto &I : IDToValue) 973 SubtreeValues.insert(I.second); 974 975 isl_ast_node_foreach_descendant_top_down( 976 Kernel->tree, collectReferencesInGPUStmt, &References); 977 978 for (const SCEV *Expr : SCEVs) 979 findValues(Expr, SE, SubtreeValues); 980 981 for (auto &SAI : S.arrays()) 982 SubtreeValues.remove(SAI->getBasePtr()); 983 984 isl_space *Space = S.getParamSpace(); 985 for (long i = 0; i < isl_space_dim(Space, isl_dim_param); i++) { 986 isl_id *Id = isl_space_get_dim_id(Space, isl_dim_param, i); 987 assert(IDToValue.count(Id)); 988 Value *Val = IDToValue[Id]; 989 SubtreeValues.remove(Val); 990 isl_id_free(Id); 991 } 992 isl_space_free(Space); 993 994 for (long i = 0; i < isl_space_dim(Kernel->space, isl_dim_set); i++) { 995 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 996 assert(IDToValue.count(Id)); 997 Value *Val = IDToValue[Id]; 998 SubtreeValues.remove(Val); 999 isl_id_free(Id); 1000 } 1001 1002 return SubtreeValues; 1003 } 1004 1005 void GPUNodeBuilder::clearDominators(Function *F) { 1006 DomTreeNode *N = DT.getNode(&F->getEntryBlock()); 1007 std::vector<BasicBlock *> Nodes; 1008 for (po_iterator<DomTreeNode *> I = po_begin(N), E = po_end(N); I != E; ++I) 1009 Nodes.push_back(I->getBlock()); 1010 1011 for (BasicBlock *BB : Nodes) 1012 DT.eraseNode(BB); 1013 } 1014 1015 void GPUNodeBuilder::clearScalarEvolution(Function *F) { 1016 for (BasicBlock &BB : *F) { 1017 Loop *L = LI.getLoopFor(&BB); 1018 if (L) 1019 SE.forgetLoop(L); 1020 } 1021 } 1022 1023 void GPUNodeBuilder::clearLoops(Function *F) { 1024 for (BasicBlock &BB : *F) { 1025 Loop *L = LI.getLoopFor(&BB); 1026 if (L) 1027 SE.forgetLoop(L); 1028 LI.removeBlock(&BB); 1029 } 1030 } 1031 1032 std::tuple<Value *, Value *> GPUNodeBuilder::getGridSizes(ppcg_kernel *Kernel) { 1033 std::vector<Value *> Sizes; 1034 isl_ast_build *Context = isl_ast_build_from_context(S.getContext()); 1035 1036 for (long i = 0; i < Kernel->n_grid; i++) { 1037 isl_pw_aff *Size = isl_multi_pw_aff_get_pw_aff(Kernel->grid_size, i); 1038 isl_ast_expr *GridSize = isl_ast_build_expr_from_pw_aff(Context, Size); 1039 Value *Res = ExprBuilder.create(GridSize); 1040 Res = Builder.CreateTrunc(Res, Builder.getInt32Ty()); 1041 Sizes.push_back(Res); 1042 } 1043 isl_ast_build_free(Context); 1044 1045 for (long i = Kernel->n_grid; i < 3; i++) 1046 Sizes.push_back(ConstantInt::get(Builder.getInt32Ty(), 1)); 1047 1048 return std::make_tuple(Sizes[0], Sizes[1]); 1049 } 1050 1051 std::tuple<Value *, Value *, Value *> 1052 GPUNodeBuilder::getBlockSizes(ppcg_kernel *Kernel) { 1053 std::vector<Value *> Sizes; 1054 1055 for (long i = 0; i < Kernel->n_block; i++) { 1056 Value *Res = ConstantInt::get(Builder.getInt32Ty(), Kernel->block_dim[i]); 1057 Sizes.push_back(Res); 1058 } 1059 1060 for (long i = Kernel->n_block; i < 3; i++) 1061 Sizes.push_back(ConstantInt::get(Builder.getInt32Ty(), 1)); 1062 1063 return std::make_tuple(Sizes[0], Sizes[1], Sizes[2]); 1064 } 1065 1066 Value * 1067 GPUNodeBuilder::createLaunchParameters(ppcg_kernel *Kernel, Function *F, 1068 SetVector<Value *> SubtreeValues) { 1069 Type *ArrayTy = ArrayType::get(Builder.getInt8PtrTy(), 1070 std::distance(F->arg_begin(), F->arg_end())); 1071 1072 BasicBlock *EntryBlock = 1073 &Builder.GetInsertBlock()->getParent()->getEntryBlock(); 1074 std::string Launch = "polly_launch_" + std::to_string(Kernel->id); 1075 Instruction *Parameters = 1076 new AllocaInst(ArrayTy, Launch + "_params", EntryBlock->getTerminator()); 1077 1078 int Index = 0; 1079 for (long i = 0; i < Prog->n_array; i++) { 1080 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1081 continue; 1082 1083 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1084 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(Id); 1085 1086 Value *DevArray = DeviceAllocations[const_cast<ScopArrayInfo *>(SAI)]; 1087 DevArray = createCallGetDevicePtr(DevArray); 1088 1089 Value *Offset = getArrayOffset(&Prog->array[i]); 1090 1091 if (Offset) { 1092 DevArray = Builder.CreatePointerCast( 1093 DevArray, SAI->getElementType()->getPointerTo()); 1094 DevArray = Builder.CreateGEP(DevArray, Builder.CreateNeg(Offset)); 1095 DevArray = Builder.CreatePointerCast(DevArray, Builder.getInt8PtrTy()); 1096 } 1097 Value *Slot = Builder.CreateGEP( 1098 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1099 1100 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1101 Value *ValPtr = BlockGen.getOrCreateAlloca(SAI); 1102 Value *ValPtrCast = 1103 Builder.CreatePointerCast(ValPtr, Builder.getInt8PtrTy()); 1104 Builder.CreateStore(ValPtrCast, Slot); 1105 } else { 1106 Instruction *Param = new AllocaInst( 1107 Builder.getInt8PtrTy(), Launch + "_param_" + std::to_string(Index), 1108 EntryBlock->getTerminator()); 1109 Builder.CreateStore(DevArray, Param); 1110 Value *ParamTyped = 1111 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1112 Builder.CreateStore(ParamTyped, Slot); 1113 } 1114 Index++; 1115 } 1116 1117 int NumHostIters = isl_space_dim(Kernel->space, isl_dim_set); 1118 1119 for (long i = 0; i < NumHostIters; i++) { 1120 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1121 Value *Val = IDToValue[Id]; 1122 isl_id_free(Id); 1123 Instruction *Param = new AllocaInst( 1124 Val->getType(), Launch + "_param_" + std::to_string(Index), 1125 EntryBlock->getTerminator()); 1126 Builder.CreateStore(Val, Param); 1127 Value *Slot = Builder.CreateGEP( 1128 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1129 Value *ParamTyped = 1130 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1131 Builder.CreateStore(ParamTyped, Slot); 1132 Index++; 1133 } 1134 1135 int NumVars = isl_space_dim(Kernel->space, isl_dim_param); 1136 1137 for (long i = 0; i < NumVars; i++) { 1138 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1139 Value *Val = IDToValue[Id]; 1140 isl_id_free(Id); 1141 Instruction *Param = new AllocaInst( 1142 Val->getType(), Launch + "_param_" + std::to_string(Index), 1143 EntryBlock->getTerminator()); 1144 Builder.CreateStore(Val, Param); 1145 Value *Slot = Builder.CreateGEP( 1146 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1147 Value *ParamTyped = 1148 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1149 Builder.CreateStore(ParamTyped, Slot); 1150 Index++; 1151 } 1152 1153 for (auto Val : SubtreeValues) { 1154 Instruction *Param = new AllocaInst( 1155 Val->getType(), Launch + "_param_" + std::to_string(Index), 1156 EntryBlock->getTerminator()); 1157 Builder.CreateStore(Val, Param); 1158 Value *Slot = Builder.CreateGEP( 1159 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1160 Value *ParamTyped = 1161 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1162 Builder.CreateStore(ParamTyped, Slot); 1163 Index++; 1164 } 1165 1166 auto Location = EntryBlock->getTerminator(); 1167 return new BitCastInst(Parameters, Builder.getInt8PtrTy(), 1168 Launch + "_params_i8ptr", Location); 1169 } 1170 1171 void GPUNodeBuilder::createKernel(__isl_take isl_ast_node *KernelStmt) { 1172 isl_id *Id = isl_ast_node_get_annotation(KernelStmt); 1173 ppcg_kernel *Kernel = (ppcg_kernel *)isl_id_get_user(Id); 1174 isl_id_free(Id); 1175 isl_ast_node_free(KernelStmt); 1176 1177 Value *BlockDimX, *BlockDimY, *BlockDimZ; 1178 std::tie(BlockDimX, BlockDimY, BlockDimZ) = getBlockSizes(Kernel); 1179 1180 SetVector<Value *> SubtreeValues = getReferencesInKernel(Kernel); 1181 1182 assert(Kernel->tree && "Device AST of kernel node is empty"); 1183 1184 Instruction &HostInsertPoint = *Builder.GetInsertPoint(); 1185 IslExprBuilder::IDToValueTy HostIDs = IDToValue; 1186 ValueMapT HostValueMap = ValueMap; 1187 BlockGenerator::ScalarAllocaMapTy HostScalarMap = ScalarMap; 1188 BlockGenerator::ScalarAllocaMapTy HostPHIOpMap = PHIOpMap; 1189 ScalarMap.clear(); 1190 PHIOpMap.clear(); 1191 1192 SetVector<const Loop *> Loops; 1193 1194 // Create for all loops we depend on values that contain the current loop 1195 // iteration. These values are necessary to generate code for SCEVs that 1196 // depend on such loops. As a result we need to pass them to the subfunction. 1197 for (const Loop *L : Loops) { 1198 const SCEV *OuterLIV = SE.getAddRecExpr(SE.getUnknown(Builder.getInt64(0)), 1199 SE.getUnknown(Builder.getInt64(1)), 1200 L, SCEV::FlagAnyWrap); 1201 Value *V = generateSCEV(OuterLIV); 1202 OutsideLoopIterations[L] = SE.getUnknown(V); 1203 SubtreeValues.insert(V); 1204 } 1205 1206 createKernelFunction(Kernel, SubtreeValues); 1207 1208 create(isl_ast_node_copy(Kernel->tree)); 1209 1210 finalizeKernelArguments(Kernel); 1211 Function *F = Builder.GetInsertBlock()->getParent(); 1212 addCUDAAnnotations(F->getParent(), BlockDimX, BlockDimY, BlockDimZ); 1213 clearDominators(F); 1214 clearScalarEvolution(F); 1215 clearLoops(F); 1216 1217 IDToValue = HostIDs; 1218 1219 ValueMap = std::move(HostValueMap); 1220 ScalarMap = std::move(HostScalarMap); 1221 PHIOpMap = std::move(HostPHIOpMap); 1222 EscapeMap.clear(); 1223 IDToSAI.clear(); 1224 Annotator.resetAlternativeAliasBases(); 1225 for (auto &BasePtr : LocalArrays) 1226 S.invalidateScopArrayInfo(BasePtr, ScopArrayInfo::MK_Array); 1227 LocalArrays.clear(); 1228 1229 std::string ASMString = finalizeKernelFunction(); 1230 Builder.SetInsertPoint(&HostInsertPoint); 1231 Value *Parameters = createLaunchParameters(Kernel, F, SubtreeValues); 1232 1233 std::string Name = "kernel_" + std::to_string(Kernel->id); 1234 Value *KernelString = Builder.CreateGlobalStringPtr(ASMString, Name); 1235 Value *NameString = Builder.CreateGlobalStringPtr(Name, Name + "_name"); 1236 Value *GPUKernel = createCallGetKernel(KernelString, NameString); 1237 1238 Value *GridDimX, *GridDimY; 1239 std::tie(GridDimX, GridDimY) = getGridSizes(Kernel); 1240 1241 createCallLaunchKernel(GPUKernel, GridDimX, GridDimY, BlockDimX, BlockDimY, 1242 BlockDimZ, Parameters); 1243 createCallFreeKernel(GPUKernel); 1244 1245 for (auto Id : KernelIds) 1246 isl_id_free(Id); 1247 1248 KernelIds.clear(); 1249 } 1250 1251 /// Compute the DataLayout string for the NVPTX backend. 1252 /// 1253 /// @param is64Bit Are we looking for a 64 bit architecture? 1254 static std::string computeNVPTXDataLayout(bool is64Bit) { 1255 std::string Ret = "e"; 1256 1257 if (!is64Bit) 1258 Ret += "-p:32:32"; 1259 1260 Ret += "-i64:64-v16:16-v32:32-n16:32:64"; 1261 1262 return Ret; 1263 } 1264 1265 Function * 1266 GPUNodeBuilder::createKernelFunctionDecl(ppcg_kernel *Kernel, 1267 SetVector<Value *> &SubtreeValues) { 1268 std::vector<Type *> Args; 1269 std::string Identifier = "kernel_" + std::to_string(Kernel->id); 1270 1271 for (long i = 0; i < Prog->n_array; i++) { 1272 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1273 continue; 1274 1275 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1276 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1277 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(Id); 1278 Args.push_back(SAI->getElementType()); 1279 } else { 1280 Args.push_back(Builder.getInt8PtrTy()); 1281 } 1282 } 1283 1284 int NumHostIters = isl_space_dim(Kernel->space, isl_dim_set); 1285 1286 for (long i = 0; i < NumHostIters; i++) 1287 Args.push_back(Builder.getInt64Ty()); 1288 1289 int NumVars = isl_space_dim(Kernel->space, isl_dim_param); 1290 1291 for (long i = 0; i < NumVars; i++) { 1292 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1293 Value *Val = IDToValue[Id]; 1294 isl_id_free(Id); 1295 Args.push_back(Val->getType()); 1296 } 1297 1298 for (auto *V : SubtreeValues) 1299 Args.push_back(V->getType()); 1300 1301 auto *FT = FunctionType::get(Builder.getVoidTy(), Args, false); 1302 auto *FN = Function::Create(FT, Function::ExternalLinkage, Identifier, 1303 GPUModule.get()); 1304 FN->setCallingConv(CallingConv::PTX_Kernel); 1305 1306 auto Arg = FN->arg_begin(); 1307 for (long i = 0; i < Kernel->n_array; i++) { 1308 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1309 continue; 1310 1311 Arg->setName(Kernel->array[i].array->name); 1312 1313 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1314 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1315 Type *EleTy = SAI->getElementType(); 1316 Value *Val = &*Arg; 1317 SmallVector<const SCEV *, 4> Sizes; 1318 isl_ast_build *Build = 1319 isl_ast_build_from_context(isl_set_copy(Prog->context)); 1320 Sizes.push_back(nullptr); 1321 for (long j = 1; j < Kernel->array[i].array->n_index; j++) { 1322 isl_ast_expr *DimSize = isl_ast_build_expr_from_pw_aff( 1323 Build, isl_pw_aff_copy(Kernel->array[i].array->bound[j])); 1324 auto V = ExprBuilder.create(DimSize); 1325 Sizes.push_back(SE.getSCEV(V)); 1326 } 1327 const ScopArrayInfo *SAIRep = 1328 S.getOrCreateScopArrayInfo(Val, EleTy, Sizes, ScopArrayInfo::MK_Array); 1329 LocalArrays.push_back(Val); 1330 1331 isl_ast_build_free(Build); 1332 KernelIds.push_back(Id); 1333 IDToSAI[Id] = SAIRep; 1334 Arg++; 1335 } 1336 1337 for (long i = 0; i < NumHostIters; i++) { 1338 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1339 Arg->setName(isl_id_get_name(Id)); 1340 IDToValue[Id] = &*Arg; 1341 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1342 Arg++; 1343 } 1344 1345 for (long i = 0; i < NumVars; i++) { 1346 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1347 Arg->setName(isl_id_get_name(Id)); 1348 Value *Val = IDToValue[Id]; 1349 ValueMap[Val] = &*Arg; 1350 IDToValue[Id] = &*Arg; 1351 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1352 Arg++; 1353 } 1354 1355 for (auto *V : SubtreeValues) { 1356 Arg->setName(V->getName()); 1357 ValueMap[V] = &*Arg; 1358 Arg++; 1359 } 1360 1361 return FN; 1362 } 1363 1364 void GPUNodeBuilder::insertKernelIntrinsics(ppcg_kernel *Kernel) { 1365 Intrinsic::ID IntrinsicsBID[] = {Intrinsic::nvvm_read_ptx_sreg_ctaid_x, 1366 Intrinsic::nvvm_read_ptx_sreg_ctaid_y}; 1367 1368 Intrinsic::ID IntrinsicsTID[] = {Intrinsic::nvvm_read_ptx_sreg_tid_x, 1369 Intrinsic::nvvm_read_ptx_sreg_tid_y, 1370 Intrinsic::nvvm_read_ptx_sreg_tid_z}; 1371 1372 auto addId = [this](__isl_take isl_id *Id, Intrinsic::ID Intr) mutable { 1373 std::string Name = isl_id_get_name(Id); 1374 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 1375 Function *IntrinsicFn = Intrinsic::getDeclaration(M, Intr); 1376 Value *Val = Builder.CreateCall(IntrinsicFn, {}); 1377 Val = Builder.CreateIntCast(Val, Builder.getInt64Ty(), false, Name); 1378 IDToValue[Id] = Val; 1379 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1380 }; 1381 1382 for (int i = 0; i < Kernel->n_grid; ++i) { 1383 isl_id *Id = isl_id_list_get_id(Kernel->block_ids, i); 1384 addId(Id, IntrinsicsBID[i]); 1385 } 1386 1387 for (int i = 0; i < Kernel->n_block; ++i) { 1388 isl_id *Id = isl_id_list_get_id(Kernel->thread_ids, i); 1389 addId(Id, IntrinsicsTID[i]); 1390 } 1391 } 1392 1393 void GPUNodeBuilder::prepareKernelArguments(ppcg_kernel *Kernel, Function *FN) { 1394 auto Arg = FN->arg_begin(); 1395 for (long i = 0; i < Kernel->n_array; i++) { 1396 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1397 continue; 1398 1399 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1400 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1401 isl_id_free(Id); 1402 1403 if (SAI->getNumberOfDimensions() > 0) { 1404 Arg++; 1405 continue; 1406 } 1407 1408 Value *Val = &*Arg; 1409 1410 if (!gpu_array_is_read_only_scalar(&Prog->array[i])) { 1411 Type *TypePtr = SAI->getElementType()->getPointerTo(); 1412 Value *TypedArgPtr = Builder.CreatePointerCast(Val, TypePtr); 1413 Val = Builder.CreateLoad(TypedArgPtr); 1414 } 1415 1416 Value *Alloca = BlockGen.getOrCreateAlloca(SAI); 1417 Builder.CreateStore(Val, Alloca); 1418 1419 Arg++; 1420 } 1421 } 1422 1423 void GPUNodeBuilder::finalizeKernelArguments(ppcg_kernel *Kernel) { 1424 auto *FN = Builder.GetInsertBlock()->getParent(); 1425 auto Arg = FN->arg_begin(); 1426 1427 bool StoredScalar = false; 1428 for (long i = 0; i < Kernel->n_array; i++) { 1429 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1430 continue; 1431 1432 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1433 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1434 isl_id_free(Id); 1435 1436 if (SAI->getNumberOfDimensions() > 0) { 1437 Arg++; 1438 continue; 1439 } 1440 1441 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1442 Arg++; 1443 continue; 1444 } 1445 1446 Value *Alloca = BlockGen.getOrCreateAlloca(SAI); 1447 Value *ArgPtr = &*Arg; 1448 Type *TypePtr = SAI->getElementType()->getPointerTo(); 1449 Value *TypedArgPtr = Builder.CreatePointerCast(ArgPtr, TypePtr); 1450 Value *Val = Builder.CreateLoad(Alloca); 1451 Builder.CreateStore(Val, TypedArgPtr); 1452 StoredScalar = true; 1453 1454 Arg++; 1455 } 1456 1457 if (StoredScalar) 1458 /// In case more than one thread contains scalar stores, the generated 1459 /// code might be incorrect, if we only store at the end of the kernel. 1460 /// To support this case we need to store these scalars back at each 1461 /// memory store or at least before each kernel barrier. 1462 if (Kernel->n_block != 0 || Kernel->n_grid != 0) 1463 BuildSuccessful = 0; 1464 } 1465 1466 void GPUNodeBuilder::createKernelVariables(ppcg_kernel *Kernel, Function *FN) { 1467 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 1468 1469 for (int i = 0; i < Kernel->n_var; ++i) { 1470 struct ppcg_kernel_var &Var = Kernel->var[i]; 1471 isl_id *Id = isl_space_get_tuple_id(Var.array->space, isl_dim_set); 1472 Type *EleTy = ScopArrayInfo::getFromId(Id)->getElementType(); 1473 1474 Type *ArrayTy = EleTy; 1475 SmallVector<const SCEV *, 4> Sizes; 1476 1477 Sizes.push_back(nullptr); 1478 for (unsigned int j = 1; j < Var.array->n_index; ++j) { 1479 isl_val *Val = isl_vec_get_element_val(Var.size, j); 1480 long Bound = isl_val_get_num_si(Val); 1481 isl_val_free(Val); 1482 Sizes.push_back(S.getSE()->getConstant(Builder.getInt64Ty(), Bound)); 1483 } 1484 1485 for (int j = Var.array->n_index - 1; j >= 0; --j) { 1486 isl_val *Val = isl_vec_get_element_val(Var.size, j); 1487 long Bound = isl_val_get_num_si(Val); 1488 isl_val_free(Val); 1489 ArrayTy = ArrayType::get(ArrayTy, Bound); 1490 } 1491 1492 const ScopArrayInfo *SAI; 1493 Value *Allocation; 1494 if (Var.type == ppcg_access_shared) { 1495 auto GlobalVar = new GlobalVariable( 1496 *M, ArrayTy, false, GlobalValue::InternalLinkage, 0, Var.name, 1497 nullptr, GlobalValue::ThreadLocalMode::NotThreadLocal, 3); 1498 GlobalVar->setAlignment(EleTy->getPrimitiveSizeInBits() / 8); 1499 GlobalVar->setInitializer(Constant::getNullValue(ArrayTy)); 1500 1501 Allocation = GlobalVar; 1502 } else if (Var.type == ppcg_access_private) { 1503 Allocation = Builder.CreateAlloca(ArrayTy, 0, "private_array"); 1504 } else { 1505 llvm_unreachable("unknown variable type"); 1506 } 1507 SAI = S.getOrCreateScopArrayInfo(Allocation, EleTy, Sizes, 1508 ScopArrayInfo::MK_Array); 1509 Id = isl_id_alloc(S.getIslCtx(), Var.name, nullptr); 1510 IDToValue[Id] = Allocation; 1511 LocalArrays.push_back(Allocation); 1512 KernelIds.push_back(Id); 1513 IDToSAI[Id] = SAI; 1514 } 1515 } 1516 1517 void GPUNodeBuilder::createKernelFunction(ppcg_kernel *Kernel, 1518 SetVector<Value *> &SubtreeValues) { 1519 1520 std::string Identifier = "kernel_" + std::to_string(Kernel->id); 1521 GPUModule.reset(new Module(Identifier, Builder.getContext())); 1522 GPUModule->setTargetTriple(Triple::normalize("nvptx64-nvidia-cuda")); 1523 GPUModule->setDataLayout(computeNVPTXDataLayout(true /* is64Bit */)); 1524 1525 Function *FN = createKernelFunctionDecl(Kernel, SubtreeValues); 1526 1527 BasicBlock *PrevBlock = Builder.GetInsertBlock(); 1528 auto EntryBlock = BasicBlock::Create(Builder.getContext(), "entry", FN); 1529 1530 DominatorTree &DT = P->getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 1531 DT.addNewBlock(EntryBlock, PrevBlock); 1532 1533 Builder.SetInsertPoint(EntryBlock); 1534 Builder.CreateRetVoid(); 1535 Builder.SetInsertPoint(EntryBlock, EntryBlock->begin()); 1536 1537 ScopDetection::markFunctionAsInvalid(FN); 1538 1539 prepareKernelArguments(Kernel, FN); 1540 createKernelVariables(Kernel, FN); 1541 insertKernelIntrinsics(Kernel); 1542 } 1543 1544 std::string GPUNodeBuilder::createKernelASM() { 1545 llvm::Triple GPUTriple(Triple::normalize("nvptx64-nvidia-cuda")); 1546 std::string ErrMsg; 1547 auto GPUTarget = TargetRegistry::lookupTarget(GPUTriple.getTriple(), ErrMsg); 1548 1549 if (!GPUTarget) { 1550 errs() << ErrMsg << "\n"; 1551 return ""; 1552 } 1553 1554 TargetOptions Options; 1555 Options.UnsafeFPMath = FastMath; 1556 std::unique_ptr<TargetMachine> TargetM( 1557 GPUTarget->createTargetMachine(GPUTriple.getTriple(), CudaVersion, "", 1558 Options, Optional<Reloc::Model>())); 1559 1560 SmallString<0> ASMString; 1561 raw_svector_ostream ASMStream(ASMString); 1562 llvm::legacy::PassManager PM; 1563 1564 PM.add(createTargetTransformInfoWrapperPass(TargetM->getTargetIRAnalysis())); 1565 1566 if (TargetM->addPassesToEmitFile( 1567 PM, ASMStream, TargetMachine::CGFT_AssemblyFile, true /* verify */)) { 1568 errs() << "The target does not support generation of this file type!\n"; 1569 return ""; 1570 } 1571 1572 PM.run(*GPUModule); 1573 1574 return ASMStream.str(); 1575 } 1576 1577 std::string GPUNodeBuilder::finalizeKernelFunction() { 1578 if (verifyModule(*GPUModule)) { 1579 BuildSuccessful = false; 1580 return ""; 1581 } 1582 1583 if (DumpKernelIR) 1584 outs() << *GPUModule << "\n"; 1585 1586 // Optimize module. 1587 llvm::legacy::PassManager OptPasses; 1588 PassManagerBuilder PassBuilder; 1589 PassBuilder.OptLevel = 3; 1590 PassBuilder.SizeLevel = 0; 1591 PassBuilder.populateModulePassManager(OptPasses); 1592 OptPasses.run(*GPUModule); 1593 1594 std::string Assembly = createKernelASM(); 1595 1596 if (DumpKernelASM) 1597 outs() << Assembly << "\n"; 1598 1599 GPUModule.release(); 1600 KernelIDs.clear(); 1601 1602 return Assembly; 1603 } 1604 1605 namespace { 1606 class PPCGCodeGeneration : public ScopPass { 1607 public: 1608 static char ID; 1609 1610 /// The scop that is currently processed. 1611 Scop *S; 1612 1613 LoopInfo *LI; 1614 DominatorTree *DT; 1615 ScalarEvolution *SE; 1616 const DataLayout *DL; 1617 RegionInfo *RI; 1618 1619 PPCGCodeGeneration() : ScopPass(ID) {} 1620 1621 /// Construct compilation options for PPCG. 1622 /// 1623 /// @returns The compilation options. 1624 ppcg_options *createPPCGOptions() { 1625 auto DebugOptions = 1626 (ppcg_debug_options *)malloc(sizeof(ppcg_debug_options)); 1627 auto Options = (ppcg_options *)malloc(sizeof(ppcg_options)); 1628 1629 DebugOptions->dump_schedule_constraints = false; 1630 DebugOptions->dump_schedule = false; 1631 DebugOptions->dump_final_schedule = false; 1632 DebugOptions->dump_sizes = false; 1633 DebugOptions->verbose = false; 1634 1635 Options->debug = DebugOptions; 1636 1637 Options->reschedule = true; 1638 Options->scale_tile_loops = false; 1639 Options->wrap = false; 1640 1641 Options->non_negative_parameters = false; 1642 Options->ctx = nullptr; 1643 Options->sizes = nullptr; 1644 1645 Options->tile_size = 32; 1646 1647 Options->use_private_memory = PrivateMemory; 1648 Options->use_shared_memory = SharedMemory; 1649 Options->max_shared_memory = 48 * 1024; 1650 1651 Options->target = PPCG_TARGET_CUDA; 1652 Options->openmp = false; 1653 Options->linearize_device_arrays = true; 1654 Options->live_range_reordering = false; 1655 1656 Options->opencl_compiler_options = nullptr; 1657 Options->opencl_use_gpu = false; 1658 Options->opencl_n_include_file = 0; 1659 Options->opencl_include_files = nullptr; 1660 Options->opencl_print_kernel_types = false; 1661 Options->opencl_embed_kernel_code = false; 1662 1663 Options->save_schedule_file = nullptr; 1664 Options->load_schedule_file = nullptr; 1665 1666 return Options; 1667 } 1668 1669 /// Get a tagged access relation containing all accesses of type @p AccessTy. 1670 /// 1671 /// Instead of a normal access of the form: 1672 /// 1673 /// Stmt[i,j,k] -> Array[f_0(i,j,k), f_1(i,j,k)] 1674 /// 1675 /// a tagged access has the form 1676 /// 1677 /// [Stmt[i,j,k] -> id[]] -> Array[f_0(i,j,k), f_1(i,j,k)] 1678 /// 1679 /// where 'id' is an additional space that references the memory access that 1680 /// triggered the access. 1681 /// 1682 /// @param AccessTy The type of the memory accesses to collect. 1683 /// 1684 /// @return The relation describing all tagged memory accesses. 1685 isl_union_map *getTaggedAccesses(enum MemoryAccess::AccessType AccessTy) { 1686 isl_union_map *Accesses = isl_union_map_empty(S->getParamSpace()); 1687 1688 for (auto &Stmt : *S) 1689 for (auto &Acc : Stmt) 1690 if (Acc->getType() == AccessTy) { 1691 isl_map *Relation = Acc->getAccessRelation(); 1692 Relation = isl_map_intersect_domain(Relation, Stmt.getDomain()); 1693 1694 isl_space *Space = isl_map_get_space(Relation); 1695 Space = isl_space_range(Space); 1696 Space = isl_space_from_range(Space); 1697 Space = isl_space_set_tuple_id(Space, isl_dim_in, Acc->getId()); 1698 isl_map *Universe = isl_map_universe(Space); 1699 Relation = isl_map_domain_product(Relation, Universe); 1700 Accesses = isl_union_map_add_map(Accesses, Relation); 1701 } 1702 1703 return Accesses; 1704 } 1705 1706 /// Get the set of all read accesses, tagged with the access id. 1707 /// 1708 /// @see getTaggedAccesses 1709 isl_union_map *getTaggedReads() { 1710 return getTaggedAccesses(MemoryAccess::READ); 1711 } 1712 1713 /// Get the set of all may (and must) accesses, tagged with the access id. 1714 /// 1715 /// @see getTaggedAccesses 1716 isl_union_map *getTaggedMayWrites() { 1717 return isl_union_map_union(getTaggedAccesses(MemoryAccess::MAY_WRITE), 1718 getTaggedAccesses(MemoryAccess::MUST_WRITE)); 1719 } 1720 1721 /// Get the set of all must accesses, tagged with the access id. 1722 /// 1723 /// @see getTaggedAccesses 1724 isl_union_map *getTaggedMustWrites() { 1725 return getTaggedAccesses(MemoryAccess::MUST_WRITE); 1726 } 1727 1728 /// Collect parameter and array names as isl_ids. 1729 /// 1730 /// To reason about the different parameters and arrays used, ppcg requires 1731 /// a list of all isl_ids in use. As PPCG traditionally performs 1732 /// source-to-source compilation each of these isl_ids is mapped to the 1733 /// expression that represents it. As we do not have a corresponding 1734 /// expression in Polly, we just map each id to a 'zero' expression to match 1735 /// the data format that ppcg expects. 1736 /// 1737 /// @returns Retun a map from collected ids to 'zero' ast expressions. 1738 __isl_give isl_id_to_ast_expr *getNames() { 1739 auto *Names = isl_id_to_ast_expr_alloc( 1740 S->getIslCtx(), 1741 S->getNumParams() + std::distance(S->array_begin(), S->array_end())); 1742 auto *Zero = isl_ast_expr_from_val(isl_val_zero(S->getIslCtx())); 1743 auto *Space = S->getParamSpace(); 1744 1745 for (int I = 0, E = S->getNumParams(); I < E; ++I) { 1746 isl_id *Id = isl_space_get_dim_id(Space, isl_dim_param, I); 1747 Names = isl_id_to_ast_expr_set(Names, Id, isl_ast_expr_copy(Zero)); 1748 } 1749 1750 for (auto &Array : S->arrays()) { 1751 auto Id = Array->getBasePtrId(); 1752 Names = isl_id_to_ast_expr_set(Names, Id, isl_ast_expr_copy(Zero)); 1753 } 1754 1755 isl_space_free(Space); 1756 isl_ast_expr_free(Zero); 1757 1758 return Names; 1759 } 1760 1761 /// Create a new PPCG scop from the current scop. 1762 /// 1763 /// The PPCG scop is initialized with data from the current polly::Scop. From 1764 /// this initial data, the data-dependences in the PPCG scop are initialized. 1765 /// We do not use Polly's dependence analysis for now, to ensure we match 1766 /// the PPCG default behaviour more closely. 1767 /// 1768 /// @returns A new ppcg scop. 1769 ppcg_scop *createPPCGScop() { 1770 auto PPCGScop = (ppcg_scop *)malloc(sizeof(ppcg_scop)); 1771 1772 PPCGScop->options = createPPCGOptions(); 1773 1774 PPCGScop->start = 0; 1775 PPCGScop->end = 0; 1776 1777 PPCGScop->context = S->getContext(); 1778 PPCGScop->domain = S->getDomains(); 1779 PPCGScop->call = nullptr; 1780 PPCGScop->tagged_reads = getTaggedReads(); 1781 PPCGScop->reads = S->getReads(); 1782 PPCGScop->live_in = nullptr; 1783 PPCGScop->tagged_may_writes = getTaggedMayWrites(); 1784 PPCGScop->may_writes = S->getWrites(); 1785 PPCGScop->tagged_must_writes = getTaggedMustWrites(); 1786 PPCGScop->must_writes = S->getMustWrites(); 1787 PPCGScop->live_out = nullptr; 1788 PPCGScop->tagged_must_kills = isl_union_map_empty(S->getParamSpace()); 1789 PPCGScop->tagger = nullptr; 1790 1791 PPCGScop->independence = nullptr; 1792 PPCGScop->dep_flow = nullptr; 1793 PPCGScop->tagged_dep_flow = nullptr; 1794 PPCGScop->dep_false = nullptr; 1795 PPCGScop->dep_forced = nullptr; 1796 PPCGScop->dep_order = nullptr; 1797 PPCGScop->tagged_dep_order = nullptr; 1798 1799 PPCGScop->schedule = S->getScheduleTree(); 1800 PPCGScop->names = getNames(); 1801 1802 PPCGScop->pet = nullptr; 1803 1804 compute_tagger(PPCGScop); 1805 compute_dependences(PPCGScop); 1806 1807 return PPCGScop; 1808 } 1809 1810 /// Collect the array acesses in a statement. 1811 /// 1812 /// @param Stmt The statement for which to collect the accesses. 1813 /// 1814 /// @returns A list of array accesses. 1815 gpu_stmt_access *getStmtAccesses(ScopStmt &Stmt) { 1816 gpu_stmt_access *Accesses = nullptr; 1817 1818 for (MemoryAccess *Acc : Stmt) { 1819 auto Access = isl_alloc_type(S->getIslCtx(), struct gpu_stmt_access); 1820 Access->read = Acc->isRead(); 1821 Access->write = Acc->isWrite(); 1822 Access->access = Acc->getAccessRelation(); 1823 isl_space *Space = isl_map_get_space(Access->access); 1824 Space = isl_space_range(Space); 1825 Space = isl_space_from_range(Space); 1826 Space = isl_space_set_tuple_id(Space, isl_dim_in, Acc->getId()); 1827 isl_map *Universe = isl_map_universe(Space); 1828 Access->tagged_access = 1829 isl_map_domain_product(Acc->getAccessRelation(), Universe); 1830 Access->exact_write = !Acc->isMayWrite(); 1831 Access->ref_id = Acc->getId(); 1832 Access->next = Accesses; 1833 Access->n_index = Acc->getScopArrayInfo()->getNumberOfDimensions(); 1834 Accesses = Access; 1835 } 1836 1837 return Accesses; 1838 } 1839 1840 /// Collect the list of GPU statements. 1841 /// 1842 /// Each statement has an id, a pointer to the underlying data structure, 1843 /// as well as a list with all memory accesses. 1844 /// 1845 /// TODO: Initialize the list of memory accesses. 1846 /// 1847 /// @returns A linked-list of statements. 1848 gpu_stmt *getStatements() { 1849 gpu_stmt *Stmts = isl_calloc_array(S->getIslCtx(), struct gpu_stmt, 1850 std::distance(S->begin(), S->end())); 1851 1852 int i = 0; 1853 for (auto &Stmt : *S) { 1854 gpu_stmt *GPUStmt = &Stmts[i]; 1855 1856 GPUStmt->id = Stmt.getDomainId(); 1857 1858 // We use the pet stmt pointer to keep track of the Polly statements. 1859 GPUStmt->stmt = (pet_stmt *)&Stmt; 1860 GPUStmt->accesses = getStmtAccesses(Stmt); 1861 i++; 1862 } 1863 1864 return Stmts; 1865 } 1866 1867 /// Derive the extent of an array. 1868 /// 1869 /// The extent of an array is the set of elements that are within the 1870 /// accessed array. For the inner dimensions, the extent constraints are 1871 /// 0 and the size of the corresponding array dimension. For the first 1872 /// (outermost) dimension, the extent constraints are the minimal and maximal 1873 /// subscript value for the first dimension. 1874 /// 1875 /// @param Array The array to derive the extent for. 1876 /// 1877 /// @returns An isl_set describing the extent of the array. 1878 __isl_give isl_set *getExtent(ScopArrayInfo *Array) { 1879 unsigned NumDims = Array->getNumberOfDimensions(); 1880 isl_union_map *Accesses = S->getAccesses(); 1881 Accesses = isl_union_map_intersect_domain(Accesses, S->getDomains()); 1882 Accesses = isl_union_map_detect_equalities(Accesses); 1883 isl_union_set *AccessUSet = isl_union_map_range(Accesses); 1884 AccessUSet = isl_union_set_coalesce(AccessUSet); 1885 AccessUSet = isl_union_set_detect_equalities(AccessUSet); 1886 AccessUSet = isl_union_set_coalesce(AccessUSet); 1887 1888 if (isl_union_set_is_empty(AccessUSet)) { 1889 isl_union_set_free(AccessUSet); 1890 return isl_set_empty(Array->getSpace()); 1891 } 1892 1893 if (Array->getNumberOfDimensions() == 0) { 1894 isl_union_set_free(AccessUSet); 1895 return isl_set_universe(Array->getSpace()); 1896 } 1897 1898 isl_set *AccessSet = 1899 isl_union_set_extract_set(AccessUSet, Array->getSpace()); 1900 1901 isl_union_set_free(AccessUSet); 1902 isl_local_space *LS = isl_local_space_from_space(Array->getSpace()); 1903 1904 isl_pw_aff *Val = 1905 isl_pw_aff_from_aff(isl_aff_var_on_domain(LS, isl_dim_set, 0)); 1906 1907 isl_pw_aff *OuterMin = isl_set_dim_min(isl_set_copy(AccessSet), 0); 1908 isl_pw_aff *OuterMax = isl_set_dim_max(AccessSet, 0); 1909 OuterMin = isl_pw_aff_add_dims(OuterMin, isl_dim_in, 1910 isl_pw_aff_dim(Val, isl_dim_in)); 1911 OuterMax = isl_pw_aff_add_dims(OuterMax, isl_dim_in, 1912 isl_pw_aff_dim(Val, isl_dim_in)); 1913 OuterMin = 1914 isl_pw_aff_set_tuple_id(OuterMin, isl_dim_in, Array->getBasePtrId()); 1915 OuterMax = 1916 isl_pw_aff_set_tuple_id(OuterMax, isl_dim_in, Array->getBasePtrId()); 1917 1918 isl_set *Extent = isl_set_universe(Array->getSpace()); 1919 1920 Extent = isl_set_intersect( 1921 Extent, isl_pw_aff_le_set(OuterMin, isl_pw_aff_copy(Val))); 1922 Extent = isl_set_intersect(Extent, isl_pw_aff_ge_set(OuterMax, Val)); 1923 1924 for (unsigned i = 1; i < NumDims; ++i) 1925 Extent = isl_set_lower_bound_si(Extent, isl_dim_set, i, 0); 1926 1927 for (unsigned i = 1; i < NumDims; ++i) { 1928 isl_pw_aff *PwAff = 1929 const_cast<isl_pw_aff *>(Array->getDimensionSizePw(i)); 1930 isl_pw_aff *Val = isl_pw_aff_from_aff(isl_aff_var_on_domain( 1931 isl_local_space_from_space(Array->getSpace()), isl_dim_set, i)); 1932 PwAff = isl_pw_aff_add_dims(PwAff, isl_dim_in, 1933 isl_pw_aff_dim(Val, isl_dim_in)); 1934 PwAff = isl_pw_aff_set_tuple_id(PwAff, isl_dim_in, 1935 isl_pw_aff_get_tuple_id(Val, isl_dim_in)); 1936 auto *Set = isl_pw_aff_gt_set(PwAff, Val); 1937 Extent = isl_set_intersect(Set, Extent); 1938 } 1939 1940 return Extent; 1941 } 1942 1943 /// Derive the bounds of an array. 1944 /// 1945 /// For the first dimension we derive the bound of the array from the extent 1946 /// of this dimension. For inner dimensions we obtain their size directly from 1947 /// ScopArrayInfo. 1948 /// 1949 /// @param PPCGArray The array to compute bounds for. 1950 /// @param Array The polly array from which to take the information. 1951 void setArrayBounds(gpu_array_info &PPCGArray, ScopArrayInfo *Array) { 1952 if (PPCGArray.n_index > 0) { 1953 if (isl_set_is_empty(PPCGArray.extent)) { 1954 isl_set *Dom = isl_set_copy(PPCGArray.extent); 1955 isl_local_space *LS = isl_local_space_from_space( 1956 isl_space_params(isl_set_get_space(Dom))); 1957 isl_set_free(Dom); 1958 isl_aff *Zero = isl_aff_zero_on_domain(LS); 1959 PPCGArray.bound[0] = isl_pw_aff_from_aff(Zero); 1960 } else { 1961 isl_set *Dom = isl_set_copy(PPCGArray.extent); 1962 Dom = isl_set_project_out(Dom, isl_dim_set, 1, PPCGArray.n_index - 1); 1963 isl_pw_aff *Bound = isl_set_dim_max(isl_set_copy(Dom), 0); 1964 isl_set_free(Dom); 1965 Dom = isl_pw_aff_domain(isl_pw_aff_copy(Bound)); 1966 isl_local_space *LS = 1967 isl_local_space_from_space(isl_set_get_space(Dom)); 1968 isl_aff *One = isl_aff_zero_on_domain(LS); 1969 One = isl_aff_add_constant_si(One, 1); 1970 Bound = isl_pw_aff_add(Bound, isl_pw_aff_alloc(Dom, One)); 1971 Bound = isl_pw_aff_gist(Bound, S->getContext()); 1972 PPCGArray.bound[0] = Bound; 1973 } 1974 } 1975 1976 for (unsigned i = 1; i < PPCGArray.n_index; ++i) { 1977 isl_pw_aff *Bound = Array->getDimensionSizePw(i); 1978 auto LS = isl_pw_aff_get_domain_space(Bound); 1979 auto Aff = isl_multi_aff_zero(LS); 1980 Bound = isl_pw_aff_pullback_multi_aff(Bound, Aff); 1981 PPCGArray.bound[i] = Bound; 1982 } 1983 } 1984 1985 /// Create the arrays for @p PPCGProg. 1986 /// 1987 /// @param PPCGProg The program to compute the arrays for. 1988 void createArrays(gpu_prog *PPCGProg) { 1989 int i = 0; 1990 for (auto &Array : S->arrays()) { 1991 std::string TypeName; 1992 raw_string_ostream OS(TypeName); 1993 1994 OS << *Array->getElementType(); 1995 TypeName = OS.str(); 1996 1997 gpu_array_info &PPCGArray = PPCGProg->array[i]; 1998 1999 PPCGArray.space = Array->getSpace(); 2000 PPCGArray.type = strdup(TypeName.c_str()); 2001 PPCGArray.size = Array->getElementType()->getPrimitiveSizeInBits() / 8; 2002 PPCGArray.name = strdup(Array->getName().c_str()); 2003 PPCGArray.extent = nullptr; 2004 PPCGArray.n_index = Array->getNumberOfDimensions(); 2005 PPCGArray.bound = 2006 isl_alloc_array(S->getIslCtx(), isl_pw_aff *, PPCGArray.n_index); 2007 PPCGArray.extent = getExtent(Array); 2008 PPCGArray.n_ref = 0; 2009 PPCGArray.refs = nullptr; 2010 PPCGArray.accessed = true; 2011 PPCGArray.read_only_scalar = 2012 Array->isReadOnly() && Array->getNumberOfDimensions() == 0; 2013 PPCGArray.has_compound_element = false; 2014 PPCGArray.local = false; 2015 PPCGArray.declare_local = false; 2016 PPCGArray.global = false; 2017 PPCGArray.linearize = false; 2018 PPCGArray.dep_order = nullptr; 2019 PPCGArray.user = Array; 2020 2021 setArrayBounds(PPCGArray, Array); 2022 i++; 2023 2024 collect_references(PPCGProg, &PPCGArray); 2025 } 2026 } 2027 2028 /// Create an identity map between the arrays in the scop. 2029 /// 2030 /// @returns An identity map between the arrays in the scop. 2031 isl_union_map *getArrayIdentity() { 2032 isl_union_map *Maps = isl_union_map_empty(S->getParamSpace()); 2033 2034 for (auto &Array : S->arrays()) { 2035 isl_space *Space = Array->getSpace(); 2036 Space = isl_space_map_from_set(Space); 2037 isl_map *Identity = isl_map_identity(Space); 2038 Maps = isl_union_map_add_map(Maps, Identity); 2039 } 2040 2041 return Maps; 2042 } 2043 2044 /// Create a default-initialized PPCG GPU program. 2045 /// 2046 /// @returns A new gpu grogram description. 2047 gpu_prog *createPPCGProg(ppcg_scop *PPCGScop) { 2048 2049 if (!PPCGScop) 2050 return nullptr; 2051 2052 auto PPCGProg = isl_calloc_type(S->getIslCtx(), struct gpu_prog); 2053 2054 PPCGProg->ctx = S->getIslCtx(); 2055 PPCGProg->scop = PPCGScop; 2056 PPCGProg->context = isl_set_copy(PPCGScop->context); 2057 PPCGProg->read = isl_union_map_copy(PPCGScop->reads); 2058 PPCGProg->may_write = isl_union_map_copy(PPCGScop->may_writes); 2059 PPCGProg->must_write = isl_union_map_copy(PPCGScop->must_writes); 2060 PPCGProg->tagged_must_kill = 2061 isl_union_map_copy(PPCGScop->tagged_must_kills); 2062 PPCGProg->to_inner = getArrayIdentity(); 2063 PPCGProg->to_outer = getArrayIdentity(); 2064 PPCGProg->any_to_outer = nullptr; 2065 PPCGProg->array_order = nullptr; 2066 PPCGProg->n_stmts = std::distance(S->begin(), S->end()); 2067 PPCGProg->stmts = getStatements(); 2068 PPCGProg->n_array = std::distance(S->array_begin(), S->array_end()); 2069 PPCGProg->array = isl_calloc_array(S->getIslCtx(), struct gpu_array_info, 2070 PPCGProg->n_array); 2071 2072 createArrays(PPCGProg); 2073 2074 PPCGProg->may_persist = compute_may_persist(PPCGProg); 2075 2076 return PPCGProg; 2077 } 2078 2079 struct PrintGPUUserData { 2080 struct cuda_info *CudaInfo; 2081 struct gpu_prog *PPCGProg; 2082 std::vector<ppcg_kernel *> Kernels; 2083 }; 2084 2085 /// Print a user statement node in the host code. 2086 /// 2087 /// We use ppcg's printing facilities to print the actual statement and 2088 /// additionally build up a list of all kernels that are encountered in the 2089 /// host ast. 2090 /// 2091 /// @param P The printer to print to 2092 /// @param Options The printing options to use 2093 /// @param Node The node to print 2094 /// @param User A user pointer to carry additional data. This pointer is 2095 /// expected to be of type PrintGPUUserData. 2096 /// 2097 /// @returns A printer to which the output has been printed. 2098 static __isl_give isl_printer * 2099 printHostUser(__isl_take isl_printer *P, 2100 __isl_take isl_ast_print_options *Options, 2101 __isl_take isl_ast_node *Node, void *User) { 2102 auto Data = (struct PrintGPUUserData *)User; 2103 auto Id = isl_ast_node_get_annotation(Node); 2104 2105 if (Id) { 2106 bool IsUser = !strcmp(isl_id_get_name(Id), "user"); 2107 2108 // If this is a user statement, format it ourselves as ppcg would 2109 // otherwise try to call pet functionality that is not available in 2110 // Polly. 2111 if (IsUser) { 2112 P = isl_printer_start_line(P); 2113 P = isl_printer_print_ast_node(P, Node); 2114 P = isl_printer_end_line(P); 2115 isl_id_free(Id); 2116 isl_ast_print_options_free(Options); 2117 return P; 2118 } 2119 2120 auto Kernel = (struct ppcg_kernel *)isl_id_get_user(Id); 2121 isl_id_free(Id); 2122 Data->Kernels.push_back(Kernel); 2123 } 2124 2125 return print_host_user(P, Options, Node, User); 2126 } 2127 2128 /// Print C code corresponding to the control flow in @p Kernel. 2129 /// 2130 /// @param Kernel The kernel to print 2131 void printKernel(ppcg_kernel *Kernel) { 2132 auto *P = isl_printer_to_str(S->getIslCtx()); 2133 P = isl_printer_set_output_format(P, ISL_FORMAT_C); 2134 auto *Options = isl_ast_print_options_alloc(S->getIslCtx()); 2135 P = isl_ast_node_print(Kernel->tree, P, Options); 2136 char *String = isl_printer_get_str(P); 2137 printf("%s\n", String); 2138 free(String); 2139 isl_printer_free(P); 2140 } 2141 2142 /// Print C code corresponding to the GPU code described by @p Tree. 2143 /// 2144 /// @param Tree An AST describing GPU code 2145 /// @param PPCGProg The PPCG program from which @Tree has been constructed. 2146 void printGPUTree(isl_ast_node *Tree, gpu_prog *PPCGProg) { 2147 auto *P = isl_printer_to_str(S->getIslCtx()); 2148 P = isl_printer_set_output_format(P, ISL_FORMAT_C); 2149 2150 PrintGPUUserData Data; 2151 Data.PPCGProg = PPCGProg; 2152 2153 auto *Options = isl_ast_print_options_alloc(S->getIslCtx()); 2154 Options = 2155 isl_ast_print_options_set_print_user(Options, printHostUser, &Data); 2156 P = isl_ast_node_print(Tree, P, Options); 2157 char *String = isl_printer_get_str(P); 2158 printf("# host\n"); 2159 printf("%s\n", String); 2160 free(String); 2161 isl_printer_free(P); 2162 2163 for (auto Kernel : Data.Kernels) { 2164 printf("# kernel%d\n", Kernel->id); 2165 printKernel(Kernel); 2166 } 2167 } 2168 2169 // Generate a GPU program using PPCG. 2170 // 2171 // GPU mapping consists of multiple steps: 2172 // 2173 // 1) Compute new schedule for the program. 2174 // 2) Map schedule to GPU (TODO) 2175 // 3) Generate code for new schedule (TODO) 2176 // 2177 // We do not use here the Polly ScheduleOptimizer, as the schedule optimizer 2178 // is mostly CPU specific. Instead, we use PPCG's GPU code generation 2179 // strategy directly from this pass. 2180 gpu_gen *generateGPU(ppcg_scop *PPCGScop, gpu_prog *PPCGProg) { 2181 2182 auto PPCGGen = isl_calloc_type(S->getIslCtx(), struct gpu_gen); 2183 2184 PPCGGen->ctx = S->getIslCtx(); 2185 PPCGGen->options = PPCGScop->options; 2186 PPCGGen->print = nullptr; 2187 PPCGGen->print_user = nullptr; 2188 PPCGGen->build_ast_expr = &pollyBuildAstExprForStmt; 2189 PPCGGen->prog = PPCGProg; 2190 PPCGGen->tree = nullptr; 2191 PPCGGen->types.n = 0; 2192 PPCGGen->types.name = nullptr; 2193 PPCGGen->sizes = nullptr; 2194 PPCGGen->used_sizes = nullptr; 2195 PPCGGen->kernel_id = 0; 2196 2197 // Set scheduling strategy to same strategy PPCG is using. 2198 isl_options_set_schedule_outer_coincidence(PPCGGen->ctx, true); 2199 isl_options_set_schedule_maximize_band_depth(PPCGGen->ctx, true); 2200 isl_options_set_schedule_whole_component(PPCGGen->ctx, false); 2201 2202 isl_schedule *Schedule = get_schedule(PPCGGen); 2203 2204 int has_permutable = has_any_permutable_node(Schedule); 2205 2206 if (!has_permutable || has_permutable < 0) { 2207 Schedule = isl_schedule_free(Schedule); 2208 } else { 2209 Schedule = map_to_device(PPCGGen, Schedule); 2210 PPCGGen->tree = generate_code(PPCGGen, isl_schedule_copy(Schedule)); 2211 } 2212 2213 if (DumpSchedule) { 2214 isl_printer *P = isl_printer_to_str(S->getIslCtx()); 2215 P = isl_printer_set_yaml_style(P, ISL_YAML_STYLE_BLOCK); 2216 P = isl_printer_print_str(P, "Schedule\n"); 2217 P = isl_printer_print_str(P, "========\n"); 2218 if (Schedule) 2219 P = isl_printer_print_schedule(P, Schedule); 2220 else 2221 P = isl_printer_print_str(P, "No schedule found\n"); 2222 2223 printf("%s\n", isl_printer_get_str(P)); 2224 isl_printer_free(P); 2225 } 2226 2227 if (DumpCode) { 2228 printf("Code\n"); 2229 printf("====\n"); 2230 if (PPCGGen->tree) 2231 printGPUTree(PPCGGen->tree, PPCGProg); 2232 else 2233 printf("No code generated\n"); 2234 } 2235 2236 isl_schedule_free(Schedule); 2237 2238 return PPCGGen; 2239 } 2240 2241 /// Free gpu_gen structure. 2242 /// 2243 /// @param PPCGGen The ppcg_gen object to free. 2244 void freePPCGGen(gpu_gen *PPCGGen) { 2245 isl_ast_node_free(PPCGGen->tree); 2246 isl_union_map_free(PPCGGen->sizes); 2247 isl_union_map_free(PPCGGen->used_sizes); 2248 free(PPCGGen); 2249 } 2250 2251 /// Free the options in the ppcg scop structure. 2252 /// 2253 /// ppcg is not freeing these options for us. To avoid leaks we do this 2254 /// ourselves. 2255 /// 2256 /// @param PPCGScop The scop referencing the options to free. 2257 void freeOptions(ppcg_scop *PPCGScop) { 2258 free(PPCGScop->options->debug); 2259 PPCGScop->options->debug = nullptr; 2260 free(PPCGScop->options); 2261 PPCGScop->options = nullptr; 2262 } 2263 2264 /// Generate code for a given GPU AST described by @p Root. 2265 /// 2266 /// @param Root An isl_ast_node pointing to the root of the GPU AST. 2267 /// @param Prog The GPU Program to generate code for. 2268 void generateCode(__isl_take isl_ast_node *Root, gpu_prog *Prog) { 2269 ScopAnnotator Annotator; 2270 Annotator.buildAliasScopes(*S); 2271 2272 Region *R = &S->getRegion(); 2273 2274 simplifyRegion(R, DT, LI, RI); 2275 2276 BasicBlock *EnteringBB = R->getEnteringBlock(); 2277 2278 PollyIRBuilder Builder = createPollyIRBuilder(EnteringBB, Annotator); 2279 2280 GPUNodeBuilder NodeBuilder(Builder, Annotator, this, *DL, *LI, *SE, *DT, *S, 2281 Prog); 2282 2283 // Only build the run-time condition and parameters _after_ having 2284 // introduced the conditional branch. This is important as the conditional 2285 // branch will guard the original scop from new induction variables that 2286 // the SCEVExpander may introduce while code generating the parameters and 2287 // which may introduce scalar dependences that prevent us from correctly 2288 // code generating this scop. 2289 BasicBlock *StartBlock = 2290 executeScopConditionally(*S, this, Builder.getTrue()); 2291 2292 // TODO: Handle LICM 2293 auto SplitBlock = StartBlock->getSinglePredecessor(); 2294 Builder.SetInsertPoint(SplitBlock->getTerminator()); 2295 NodeBuilder.addParameters(S->getContext()); 2296 2297 isl_ast_build *Build = isl_ast_build_alloc(S->getIslCtx()); 2298 isl_ast_expr *Condition = IslAst::buildRunCondition(S, Build); 2299 isl_ast_build_free(Build); 2300 2301 Value *RTC = NodeBuilder.createRTC(Condition); 2302 Builder.GetInsertBlock()->getTerminator()->setOperand(0, RTC); 2303 2304 Builder.SetInsertPoint(&*StartBlock->begin()); 2305 2306 NodeBuilder.initializeAfterRTH(); 2307 NodeBuilder.create(Root); 2308 NodeBuilder.finalize(); 2309 2310 if (!NodeBuilder.BuildSuccessful) 2311 SplitBlock->getTerminator()->setOperand(0, Builder.getFalse()); 2312 } 2313 2314 bool runOnScop(Scop &CurrentScop) override { 2315 S = &CurrentScop; 2316 LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 2317 DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 2318 SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 2319 DL = &S->getRegion().getEntry()->getParent()->getParent()->getDataLayout(); 2320 RI = &getAnalysis<RegionInfoPass>().getRegionInfo(); 2321 2322 // We currently do not support scops with invariant loads. 2323 if (S->hasInvariantAccesses()) 2324 return false; 2325 2326 auto PPCGScop = createPPCGScop(); 2327 auto PPCGProg = createPPCGProg(PPCGScop); 2328 auto PPCGGen = generateGPU(PPCGScop, PPCGProg); 2329 2330 if (PPCGGen->tree) 2331 generateCode(isl_ast_node_copy(PPCGGen->tree), PPCGProg); 2332 2333 freeOptions(PPCGScop); 2334 freePPCGGen(PPCGGen); 2335 gpu_prog_free(PPCGProg); 2336 ppcg_scop_free(PPCGScop); 2337 2338 return true; 2339 } 2340 2341 void printScop(raw_ostream &, Scop &) const override {} 2342 2343 void getAnalysisUsage(AnalysisUsage &AU) const override { 2344 AU.addRequired<DominatorTreeWrapperPass>(); 2345 AU.addRequired<RegionInfoPass>(); 2346 AU.addRequired<ScalarEvolutionWrapperPass>(); 2347 AU.addRequired<ScopDetection>(); 2348 AU.addRequired<ScopInfoRegionPass>(); 2349 AU.addRequired<LoopInfoWrapperPass>(); 2350 2351 AU.addPreserved<AAResultsWrapperPass>(); 2352 AU.addPreserved<BasicAAWrapperPass>(); 2353 AU.addPreserved<LoopInfoWrapperPass>(); 2354 AU.addPreserved<DominatorTreeWrapperPass>(); 2355 AU.addPreserved<GlobalsAAWrapperPass>(); 2356 AU.addPreserved<PostDominatorTreeWrapperPass>(); 2357 AU.addPreserved<ScopDetection>(); 2358 AU.addPreserved<ScalarEvolutionWrapperPass>(); 2359 AU.addPreserved<SCEVAAWrapperPass>(); 2360 2361 // FIXME: We do not yet add regions for the newly generated code to the 2362 // region tree. 2363 AU.addPreserved<RegionInfoPass>(); 2364 AU.addPreserved<ScopInfoRegionPass>(); 2365 } 2366 }; 2367 } 2368 2369 char PPCGCodeGeneration::ID = 1; 2370 2371 Pass *polly::createPPCGCodeGenerationPass() { return new PPCGCodeGeneration(); } 2372 2373 INITIALIZE_PASS_BEGIN(PPCGCodeGeneration, "polly-codegen-ppcg", 2374 "Polly - Apply PPCG translation to SCOP", false, false) 2375 INITIALIZE_PASS_DEPENDENCY(DependenceInfo); 2376 INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass); 2377 INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass); 2378 INITIALIZE_PASS_DEPENDENCY(RegionInfoPass); 2379 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass); 2380 INITIALIZE_PASS_DEPENDENCY(ScopDetection); 2381 INITIALIZE_PASS_END(PPCGCodeGeneration, "polly-codegen-ppcg", 2382 "Polly - Apply PPCG translation to SCOP", false, false) 2383