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 static cl::opt<int> 96 MinCompute("polly-acc-mincompute", 97 cl::desc("Minimal number of compute statements to run on GPU."), 98 cl::Hidden, cl::init(10 * 512 * 512)); 99 100 /// Create the ast expressions for a ScopStmt. 101 /// 102 /// This function is a callback for to generate the ast expressions for each 103 /// of the scheduled ScopStmts. 104 static __isl_give isl_id_to_ast_expr *pollyBuildAstExprForStmt( 105 void *StmtT, isl_ast_build *Build, 106 isl_multi_pw_aff *(*FunctionIndex)(__isl_take isl_multi_pw_aff *MPA, 107 isl_id *Id, void *User), 108 void *UserIndex, 109 isl_ast_expr *(*FunctionExpr)(isl_ast_expr *Expr, isl_id *Id, void *User), 110 void *UserExpr) { 111 112 ScopStmt *Stmt = (ScopStmt *)StmtT; 113 114 isl_ctx *Ctx; 115 116 if (!Stmt || !Build) 117 return NULL; 118 119 Ctx = isl_ast_build_get_ctx(Build); 120 isl_id_to_ast_expr *RefToExpr = isl_id_to_ast_expr_alloc(Ctx, 0); 121 122 for (MemoryAccess *Acc : *Stmt) { 123 isl_map *AddrFunc = Acc->getAddressFunction(); 124 AddrFunc = isl_map_intersect_domain(AddrFunc, Stmt->getDomain()); 125 isl_id *RefId = Acc->getId(); 126 isl_pw_multi_aff *PMA = isl_pw_multi_aff_from_map(AddrFunc); 127 isl_multi_pw_aff *MPA = isl_multi_pw_aff_from_pw_multi_aff(PMA); 128 MPA = isl_multi_pw_aff_coalesce(MPA); 129 MPA = FunctionIndex(MPA, RefId, UserIndex); 130 isl_ast_expr *Access = isl_ast_build_access_from_multi_pw_aff(Build, MPA); 131 Access = FunctionExpr(Access, RefId, UserExpr); 132 RefToExpr = isl_id_to_ast_expr_set(RefToExpr, RefId, Access); 133 } 134 135 return RefToExpr; 136 } 137 138 /// Generate code for a GPU specific isl AST. 139 /// 140 /// The GPUNodeBuilder augments the general existing IslNodeBuilder, which 141 /// generates code for general-prupose AST nodes, with special functionality 142 /// for generating GPU specific user nodes. 143 /// 144 /// @see GPUNodeBuilder::createUser 145 class GPUNodeBuilder : public IslNodeBuilder { 146 public: 147 GPUNodeBuilder(PollyIRBuilder &Builder, ScopAnnotator &Annotator, Pass *P, 148 const DataLayout &DL, LoopInfo &LI, ScalarEvolution &SE, 149 DominatorTree &DT, Scop &S, BasicBlock *StartBlock, 150 gpu_prog *Prog) 151 : IslNodeBuilder(Builder, Annotator, P, DL, LI, SE, DT, S, StartBlock), 152 Prog(Prog) { 153 getExprBuilder().setIDToSAI(&IDToSAI); 154 } 155 156 /// Create after-run-time-check initialization code. 157 void initializeAfterRTH(); 158 159 /// Finalize the generated scop. 160 virtual void finalize(); 161 162 /// Track if the full build process was successful. 163 /// 164 /// This value is set to false, if throughout the build process an error 165 /// occurred which prevents us from generating valid GPU code. 166 bool BuildSuccessful = true; 167 168 /// The maximal number of loops surrounding a sequential kernel. 169 unsigned DeepestSequential = 0; 170 171 /// The maximal number of loops surrounding a parallel kernel. 172 unsigned DeepestParallel = 0; 173 174 private: 175 /// A vector of array base pointers for which a new ScopArrayInfo was created. 176 /// 177 /// This vector is used to delete the ScopArrayInfo when it is not needed any 178 /// more. 179 std::vector<Value *> LocalArrays; 180 181 /// A map from ScopArrays to their corresponding device allocations. 182 std::map<ScopArrayInfo *, Value *> DeviceAllocations; 183 184 /// The current GPU context. 185 Value *GPUContext; 186 187 /// The set of isl_ids allocated in the kernel 188 std::vector<isl_id *> KernelIds; 189 190 /// A module containing GPU code. 191 /// 192 /// This pointer is only set in case we are currently generating GPU code. 193 std::unique_ptr<Module> GPUModule; 194 195 /// The GPU program we generate code for. 196 gpu_prog *Prog; 197 198 /// Class to free isl_ids. 199 class IslIdDeleter { 200 public: 201 void operator()(__isl_take isl_id *Id) { isl_id_free(Id); }; 202 }; 203 204 /// A set containing all isl_ids allocated in a GPU kernel. 205 /// 206 /// By releasing this set all isl_ids will be freed. 207 std::set<std::unique_ptr<isl_id, IslIdDeleter>> KernelIDs; 208 209 IslExprBuilder::IDToScopArrayInfoTy IDToSAI; 210 211 /// Create code for user-defined AST nodes. 212 /// 213 /// These AST nodes can be of type: 214 /// 215 /// - ScopStmt: A computational statement (TODO) 216 /// - Kernel: A GPU kernel call (TODO) 217 /// - Data-Transfer: A GPU <-> CPU data-transfer 218 /// - In-kernel synchronization 219 /// - In-kernel memory copy statement 220 /// 221 /// @param UserStmt The ast node to generate code for. 222 virtual void createUser(__isl_take isl_ast_node *UserStmt); 223 224 enum DataDirection { HOST_TO_DEVICE, DEVICE_TO_HOST }; 225 226 /// Create code for a data transfer statement 227 /// 228 /// @param TransferStmt The data transfer statement. 229 /// @param Direction The direction in which to transfer data. 230 void createDataTransfer(__isl_take isl_ast_node *TransferStmt, 231 enum DataDirection Direction); 232 233 /// Find llvm::Values referenced in GPU kernel. 234 /// 235 /// @param Kernel The kernel to scan for llvm::Values 236 /// 237 /// @returns A set of values referenced by the kernel. 238 SetVector<Value *> getReferencesInKernel(ppcg_kernel *Kernel); 239 240 /// Compute the sizes of the execution grid for a given kernel. 241 /// 242 /// @param Kernel The kernel to compute grid sizes for. 243 /// 244 /// @returns A tuple with grid sizes for X and Y dimension 245 std::tuple<Value *, Value *> getGridSizes(ppcg_kernel *Kernel); 246 247 /// Compute the sizes of the thread blocks for a given kernel. 248 /// 249 /// @param Kernel The kernel to compute thread block sizes for. 250 /// 251 /// @returns A tuple with thread block sizes for X, Y, and Z dimensions. 252 std::tuple<Value *, Value *, Value *> getBlockSizes(ppcg_kernel *Kernel); 253 254 /// Create kernel launch parameters. 255 /// 256 /// @param Kernel The kernel to create parameters for. 257 /// @param F The kernel function that has been created. 258 /// @param SubtreeValues The set of llvm::Values referenced by this kernel. 259 /// 260 /// @returns A stack allocated array with pointers to the parameter 261 /// values that are passed to the kernel. 262 Value *createLaunchParameters(ppcg_kernel *Kernel, Function *F, 263 SetVector<Value *> SubtreeValues); 264 265 /// Create declarations for kernel variable. 266 /// 267 /// This includes shared memory declarations. 268 /// 269 /// @param Kernel The kernel definition to create variables for. 270 /// @param FN The function into which to generate the variables. 271 void createKernelVariables(ppcg_kernel *Kernel, Function *FN); 272 273 /// Add CUDA annotations to module. 274 /// 275 /// Add a set of CUDA annotations that declares the maximal block dimensions 276 /// that will be used to execute the CUDA kernel. This allows the NVIDIA 277 /// PTX compiler to bound the number of allocated registers to ensure the 278 /// resulting kernel is known to run with up to as many block dimensions 279 /// as specified here. 280 /// 281 /// @param M The module to add the annotations to. 282 /// @param BlockDimX The size of block dimension X. 283 /// @param BlockDimY The size of block dimension Y. 284 /// @param BlockDimZ The size of block dimension Z. 285 void addCUDAAnnotations(Module *M, Value *BlockDimX, Value *BlockDimY, 286 Value *BlockDimZ); 287 288 /// Create GPU kernel. 289 /// 290 /// Code generate the kernel described by @p KernelStmt. 291 /// 292 /// @param KernelStmt The ast node to generate kernel code for. 293 void createKernel(__isl_take isl_ast_node *KernelStmt); 294 295 /// Generate code that computes the size of an array. 296 /// 297 /// @param Array The array for which to compute a size. 298 Value *getArraySize(gpu_array_info *Array); 299 300 /// Generate code to compute the minimal offset at which an array is accessed. 301 /// 302 /// The offset of an array is the minimal array location accessed in a scop. 303 /// 304 /// Example: 305 /// 306 /// for (long i = 0; i < 100; i++) 307 /// A[i + 42] += ... 308 /// 309 /// getArrayOffset(A) results in 42. 310 /// 311 /// @param Array The array for which to compute the offset. 312 /// @returns An llvm::Value that contains the offset of the array. 313 Value *getArrayOffset(gpu_array_info *Array); 314 315 /// Prepare the kernel arguments for kernel code generation 316 /// 317 /// @param Kernel The kernel to generate code for. 318 /// @param FN The function created for the kernel. 319 void prepareKernelArguments(ppcg_kernel *Kernel, Function *FN); 320 321 /// Create kernel function. 322 /// 323 /// Create a kernel function located in a newly created module that can serve 324 /// as target for device code generation. Set the Builder to point to the 325 /// start block of this newly created function. 326 /// 327 /// @param Kernel The kernel to generate code for. 328 /// @param SubtreeValues The set of llvm::Values referenced by this kernel. 329 void createKernelFunction(ppcg_kernel *Kernel, 330 SetVector<Value *> &SubtreeValues); 331 332 /// Create the declaration of a kernel function. 333 /// 334 /// The kernel function takes as arguments: 335 /// 336 /// - One i8 pointer for each external array reference used in the kernel. 337 /// - Host iterators 338 /// - Parameters 339 /// - Other LLVM Value references (TODO) 340 /// 341 /// @param Kernel The kernel to generate the function declaration for. 342 /// @param SubtreeValues The set of llvm::Values referenced by this kernel. 343 /// 344 /// @returns The newly declared function. 345 Function *createKernelFunctionDecl(ppcg_kernel *Kernel, 346 SetVector<Value *> &SubtreeValues); 347 348 /// Insert intrinsic functions to obtain thread and block ids. 349 /// 350 /// @param The kernel to generate the intrinsic functions for. 351 void insertKernelIntrinsics(ppcg_kernel *Kernel); 352 353 /// Create a global-to-shared or shared-to-global copy statement. 354 /// 355 /// @param CopyStmt The copy statement to generate code for 356 void createKernelCopy(ppcg_kernel_stmt *CopyStmt); 357 358 /// Create code for a ScopStmt called in @p Expr. 359 /// 360 /// @param Expr The expression containing the call. 361 /// @param KernelStmt The kernel statement referenced in the call. 362 void createScopStmt(isl_ast_expr *Expr, ppcg_kernel_stmt *KernelStmt); 363 364 /// Create an in-kernel synchronization call. 365 void createKernelSync(); 366 367 /// Create a PTX assembly string for the current GPU kernel. 368 /// 369 /// @returns A string containing the corresponding PTX assembly code. 370 std::string createKernelASM(); 371 372 /// Remove references from the dominator tree to the kernel function @p F. 373 /// 374 /// @param F The function to remove references to. 375 void clearDominators(Function *F); 376 377 /// Remove references from scalar evolution to the kernel function @p F. 378 /// 379 /// @param F The function to remove references to. 380 void clearScalarEvolution(Function *F); 381 382 /// Remove references from loop info to the kernel function @p F. 383 /// 384 /// @param F The function to remove references to. 385 void clearLoops(Function *F); 386 387 /// Finalize the generation of the kernel function. 388 /// 389 /// Free the LLVM-IR module corresponding to the kernel and -- if requested -- 390 /// dump its IR to stderr. 391 /// 392 /// @returns The Assembly string of the kernel. 393 std::string finalizeKernelFunction(); 394 395 /// Finalize the generation of the kernel arguments. 396 /// 397 /// This function ensures that not-read-only scalars used in a kernel are 398 /// stored back to the global memory location they ared backed up with before 399 /// the kernel terminates. 400 /// 401 /// @params Kernel The kernel to finalize kernel arguments for. 402 void finalizeKernelArguments(ppcg_kernel *Kernel); 403 404 /// Create code that allocates memory to store arrays on device. 405 void allocateDeviceArrays(); 406 407 /// Free all allocated device arrays. 408 void freeDeviceArrays(); 409 410 /// Create a call to initialize the GPU context. 411 /// 412 /// @returns A pointer to the newly initialized context. 413 Value *createCallInitContext(); 414 415 /// Create a call to get the device pointer for a kernel allocation. 416 /// 417 /// @param Allocation The Polly GPU allocation 418 /// 419 /// @returns The device parameter corresponding to this allocation. 420 Value *createCallGetDevicePtr(Value *Allocation); 421 422 /// Create a call to free the GPU context. 423 /// 424 /// @param Context A pointer to an initialized GPU context. 425 void createCallFreeContext(Value *Context); 426 427 /// Create a call to allocate memory on the device. 428 /// 429 /// @param Size The size of memory to allocate 430 /// 431 /// @returns A pointer that identifies this allocation. 432 Value *createCallAllocateMemoryForDevice(Value *Size); 433 434 /// Create a call to free a device array. 435 /// 436 /// @param Array The device array to free. 437 void createCallFreeDeviceMemory(Value *Array); 438 439 /// Create a call to copy data from host to device. 440 /// 441 /// @param HostPtr A pointer to the host data that should be copied. 442 /// @param DevicePtr A device pointer specifying the location to copy to. 443 void createCallCopyFromHostToDevice(Value *HostPtr, Value *DevicePtr, 444 Value *Size); 445 446 /// Create a call to copy data from device to host. 447 /// 448 /// @param DevicePtr A pointer to the device data that should be copied. 449 /// @param HostPtr A host pointer specifying the location to copy to. 450 void createCallCopyFromDeviceToHost(Value *DevicePtr, Value *HostPtr, 451 Value *Size); 452 453 /// Create a call to get a kernel from an assembly string. 454 /// 455 /// @param Buffer The string describing the kernel. 456 /// @param Entry The name of the kernel function to call. 457 /// 458 /// @returns A pointer to a kernel object 459 Value *createCallGetKernel(Value *Buffer, Value *Entry); 460 461 /// Create a call to free a GPU kernel. 462 /// 463 /// @param GPUKernel THe kernel to free. 464 void createCallFreeKernel(Value *GPUKernel); 465 466 /// Create a call to launch a GPU kernel. 467 /// 468 /// @param GPUKernel The kernel to launch. 469 /// @param GridDimX The size of the first grid dimension. 470 /// @param GridDimY The size of the second grid dimension. 471 /// @param GridBlockX The size of the first block dimension. 472 /// @param GridBlockY The size of the second block dimension. 473 /// @param GridBlockZ The size of the third block dimension. 474 /// @param Paramters A pointer to an array that contains itself pointers to 475 /// the parameter values passed for each kernel argument. 476 void createCallLaunchKernel(Value *GPUKernel, Value *GridDimX, 477 Value *GridDimY, Value *BlockDimX, 478 Value *BlockDimY, Value *BlockDimZ, 479 Value *Parameters); 480 }; 481 482 void GPUNodeBuilder::initializeAfterRTH() { 483 BasicBlock *NewBB = SplitBlock(Builder.GetInsertBlock(), 484 &*Builder.GetInsertPoint(), &DT, &LI); 485 NewBB->setName("polly.acc.initialize"); 486 Builder.SetInsertPoint(&NewBB->front()); 487 488 GPUContext = createCallInitContext(); 489 allocateDeviceArrays(); 490 } 491 492 void GPUNodeBuilder::finalize() { 493 freeDeviceArrays(); 494 createCallFreeContext(GPUContext); 495 IslNodeBuilder::finalize(); 496 } 497 498 void GPUNodeBuilder::allocateDeviceArrays() { 499 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 500 501 for (int i = 0; i < Prog->n_array; ++i) { 502 gpu_array_info *Array = &Prog->array[i]; 503 auto *ScopArray = (ScopArrayInfo *)Array->user; 504 std::string DevArrayName("p_dev_array_"); 505 DevArrayName.append(Array->name); 506 507 Value *ArraySize = getArraySize(Array); 508 Value *Offset = getArrayOffset(Array); 509 if (Offset) 510 ArraySize = Builder.CreateSub( 511 ArraySize, 512 Builder.CreateMul(Offset, 513 Builder.getInt64(ScopArray->getElemSizeInBytes()))); 514 Value *DevArray = createCallAllocateMemoryForDevice(ArraySize); 515 DevArray->setName(DevArrayName); 516 DeviceAllocations[ScopArray] = DevArray; 517 } 518 519 isl_ast_build_free(Build); 520 } 521 522 void GPUNodeBuilder::addCUDAAnnotations(Module *M, Value *BlockDimX, 523 Value *BlockDimY, Value *BlockDimZ) { 524 auto AnnotationNode = M->getOrInsertNamedMetadata("nvvm.annotations"); 525 526 for (auto &F : *M) { 527 if (F.getCallingConv() != CallingConv::PTX_Kernel) 528 continue; 529 530 Value *V[] = {BlockDimX, BlockDimY, BlockDimZ}; 531 532 Metadata *Elements[] = { 533 ValueAsMetadata::get(&F), MDString::get(M->getContext(), "maxntidx"), 534 ValueAsMetadata::get(V[0]), MDString::get(M->getContext(), "maxntidy"), 535 ValueAsMetadata::get(V[1]), MDString::get(M->getContext(), "maxntidz"), 536 ValueAsMetadata::get(V[2]), 537 }; 538 MDNode *Node = MDNode::get(M->getContext(), Elements); 539 AnnotationNode->addOperand(Node); 540 } 541 } 542 543 void GPUNodeBuilder::freeDeviceArrays() { 544 for (auto &Array : DeviceAllocations) 545 createCallFreeDeviceMemory(Array.second); 546 } 547 548 Value *GPUNodeBuilder::createCallGetKernel(Value *Buffer, Value *Entry) { 549 const char *Name = "polly_getKernel"; 550 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 551 Function *F = M->getFunction(Name); 552 553 // If F is not available, declare it. 554 if (!F) { 555 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 556 std::vector<Type *> Args; 557 Args.push_back(Builder.getInt8PtrTy()); 558 Args.push_back(Builder.getInt8PtrTy()); 559 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 560 F = Function::Create(Ty, Linkage, Name, M); 561 } 562 563 return Builder.CreateCall(F, {Buffer, Entry}); 564 } 565 566 Value *GPUNodeBuilder::createCallGetDevicePtr(Value *Allocation) { 567 const char *Name = "polly_getDevicePtr"; 568 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 569 Function *F = M->getFunction(Name); 570 571 // If F is not available, declare it. 572 if (!F) { 573 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 574 std::vector<Type *> Args; 575 Args.push_back(Builder.getInt8PtrTy()); 576 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 577 F = Function::Create(Ty, Linkage, Name, M); 578 } 579 580 return Builder.CreateCall(F, {Allocation}); 581 } 582 583 void GPUNodeBuilder::createCallLaunchKernel(Value *GPUKernel, Value *GridDimX, 584 Value *GridDimY, Value *BlockDimX, 585 Value *BlockDimY, Value *BlockDimZ, 586 Value *Parameters) { 587 const char *Name = "polly_launchKernel"; 588 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 589 Function *F = M->getFunction(Name); 590 591 // If F is not available, declare it. 592 if (!F) { 593 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 594 std::vector<Type *> Args; 595 Args.push_back(Builder.getInt8PtrTy()); 596 Args.push_back(Builder.getInt32Ty()); 597 Args.push_back(Builder.getInt32Ty()); 598 Args.push_back(Builder.getInt32Ty()); 599 Args.push_back(Builder.getInt32Ty()); 600 Args.push_back(Builder.getInt32Ty()); 601 Args.push_back(Builder.getInt8PtrTy()); 602 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 603 F = Function::Create(Ty, Linkage, Name, M); 604 } 605 606 Builder.CreateCall(F, {GPUKernel, GridDimX, GridDimY, BlockDimX, BlockDimY, 607 BlockDimZ, Parameters}); 608 } 609 610 void GPUNodeBuilder::createCallFreeKernel(Value *GPUKernel) { 611 const char *Name = "polly_freeKernel"; 612 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 613 Function *F = M->getFunction(Name); 614 615 // If F is not available, declare it. 616 if (!F) { 617 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 618 std::vector<Type *> Args; 619 Args.push_back(Builder.getInt8PtrTy()); 620 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 621 F = Function::Create(Ty, Linkage, Name, M); 622 } 623 624 Builder.CreateCall(F, {GPUKernel}); 625 } 626 627 void GPUNodeBuilder::createCallFreeDeviceMemory(Value *Array) { 628 const char *Name = "polly_freeDeviceMemory"; 629 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 630 Function *F = M->getFunction(Name); 631 632 // If F is not available, declare it. 633 if (!F) { 634 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 635 std::vector<Type *> Args; 636 Args.push_back(Builder.getInt8PtrTy()); 637 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 638 F = Function::Create(Ty, Linkage, Name, M); 639 } 640 641 Builder.CreateCall(F, {Array}); 642 } 643 644 Value *GPUNodeBuilder::createCallAllocateMemoryForDevice(Value *Size) { 645 const char *Name = "polly_allocateMemoryForDevice"; 646 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 647 Function *F = M->getFunction(Name); 648 649 // If F is not available, declare it. 650 if (!F) { 651 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 652 std::vector<Type *> Args; 653 Args.push_back(Builder.getInt64Ty()); 654 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 655 F = Function::Create(Ty, Linkage, Name, M); 656 } 657 658 return Builder.CreateCall(F, {Size}); 659 } 660 661 void GPUNodeBuilder::createCallCopyFromHostToDevice(Value *HostData, 662 Value *DeviceData, 663 Value *Size) { 664 const char *Name = "polly_copyFromHostToDevice"; 665 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 666 Function *F = M->getFunction(Name); 667 668 // If F is not available, declare it. 669 if (!F) { 670 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 671 std::vector<Type *> Args; 672 Args.push_back(Builder.getInt8PtrTy()); 673 Args.push_back(Builder.getInt8PtrTy()); 674 Args.push_back(Builder.getInt64Ty()); 675 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 676 F = Function::Create(Ty, Linkage, Name, M); 677 } 678 679 Builder.CreateCall(F, {HostData, DeviceData, Size}); 680 } 681 682 void GPUNodeBuilder::createCallCopyFromDeviceToHost(Value *DeviceData, 683 Value *HostData, 684 Value *Size) { 685 const char *Name = "polly_copyFromDeviceToHost"; 686 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 687 Function *F = M->getFunction(Name); 688 689 // If F is not available, declare it. 690 if (!F) { 691 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 692 std::vector<Type *> Args; 693 Args.push_back(Builder.getInt8PtrTy()); 694 Args.push_back(Builder.getInt8PtrTy()); 695 Args.push_back(Builder.getInt64Ty()); 696 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 697 F = Function::Create(Ty, Linkage, Name, M); 698 } 699 700 Builder.CreateCall(F, {DeviceData, HostData, Size}); 701 } 702 703 Value *GPUNodeBuilder::createCallInitContext() { 704 const char *Name = "polly_initContext"; 705 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 706 Function *F = M->getFunction(Name); 707 708 // If F is not available, declare it. 709 if (!F) { 710 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 711 std::vector<Type *> Args; 712 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 713 F = Function::Create(Ty, Linkage, Name, M); 714 } 715 716 return Builder.CreateCall(F, {}); 717 } 718 719 void GPUNodeBuilder::createCallFreeContext(Value *Context) { 720 const char *Name = "polly_freeContext"; 721 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 722 Function *F = M->getFunction(Name); 723 724 // If F is not available, declare it. 725 if (!F) { 726 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 727 std::vector<Type *> Args; 728 Args.push_back(Builder.getInt8PtrTy()); 729 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 730 F = Function::Create(Ty, Linkage, Name, M); 731 } 732 733 Builder.CreateCall(F, {Context}); 734 } 735 736 /// Check if one string is a prefix of another. 737 /// 738 /// @param String The string in which to look for the prefix. 739 /// @param Prefix The prefix to look for. 740 static bool isPrefix(std::string String, std::string Prefix) { 741 return String.find(Prefix) == 0; 742 } 743 744 Value *GPUNodeBuilder::getArraySize(gpu_array_info *Array) { 745 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 746 Value *ArraySize = ConstantInt::get(Builder.getInt64Ty(), Array->size); 747 748 if (!gpu_array_is_scalar(Array)) { 749 auto OffsetDimZero = isl_pw_aff_copy(Array->bound[0]); 750 isl_ast_expr *Res = isl_ast_build_expr_from_pw_aff(Build, OffsetDimZero); 751 752 for (unsigned int i = 1; i < Array->n_index; i++) { 753 isl_pw_aff *Bound_I = isl_pw_aff_copy(Array->bound[i]); 754 isl_ast_expr *Expr = isl_ast_build_expr_from_pw_aff(Build, Bound_I); 755 Res = isl_ast_expr_mul(Res, Expr); 756 } 757 758 Value *NumElements = ExprBuilder.create(Res); 759 if (NumElements->getType() != ArraySize->getType()) 760 NumElements = Builder.CreateSExt(NumElements, ArraySize->getType()); 761 ArraySize = Builder.CreateMul(ArraySize, NumElements); 762 } 763 isl_ast_build_free(Build); 764 return ArraySize; 765 } 766 767 Value *GPUNodeBuilder::getArrayOffset(gpu_array_info *Array) { 768 if (gpu_array_is_scalar(Array)) 769 return nullptr; 770 771 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 772 773 isl_set *Min = isl_set_lexmin(isl_set_copy(Array->extent)); 774 775 isl_set *ZeroSet = isl_set_universe(isl_set_get_space(Min)); 776 777 for (long i = 0; i < isl_set_dim(Min, isl_dim_set); i++) 778 ZeroSet = isl_set_fix_si(ZeroSet, isl_dim_set, i, 0); 779 780 if (isl_set_is_subset(Min, ZeroSet)) { 781 isl_set_free(Min); 782 isl_set_free(ZeroSet); 783 isl_ast_build_free(Build); 784 return nullptr; 785 } 786 isl_set_free(ZeroSet); 787 788 isl_ast_expr *Result = 789 isl_ast_expr_from_val(isl_val_int_from_si(isl_set_get_ctx(Min), 0)); 790 791 for (long i = 0; i < isl_set_dim(Min, isl_dim_set); i++) { 792 if (i > 0) { 793 isl_pw_aff *Bound_I = isl_pw_aff_copy(Array->bound[i - 1]); 794 isl_ast_expr *BExpr = isl_ast_build_expr_from_pw_aff(Build, Bound_I); 795 Result = isl_ast_expr_mul(Result, BExpr); 796 } 797 isl_pw_aff *DimMin = isl_set_dim_min(isl_set_copy(Min), i); 798 isl_ast_expr *MExpr = isl_ast_build_expr_from_pw_aff(Build, DimMin); 799 Result = isl_ast_expr_add(Result, MExpr); 800 } 801 802 Value *ResultValue = ExprBuilder.create(Result); 803 isl_set_free(Min); 804 isl_ast_build_free(Build); 805 806 return ResultValue; 807 } 808 809 void GPUNodeBuilder::createDataTransfer(__isl_take isl_ast_node *TransferStmt, 810 enum DataDirection Direction) { 811 isl_ast_expr *Expr = isl_ast_node_user_get_expr(TransferStmt); 812 isl_ast_expr *Arg = isl_ast_expr_get_op_arg(Expr, 0); 813 isl_id *Id = isl_ast_expr_get_id(Arg); 814 auto Array = (gpu_array_info *)isl_id_get_user(Id); 815 auto ScopArray = (ScopArrayInfo *)(Array->user); 816 817 Value *Size = getArraySize(Array); 818 Value *Offset = getArrayOffset(Array); 819 Value *DevPtr = DeviceAllocations[ScopArray]; 820 821 Value *HostPtr; 822 823 if (gpu_array_is_scalar(Array)) 824 HostPtr = BlockGen.getOrCreateAlloca(ScopArray); 825 else 826 HostPtr = ScopArray->getBasePtr(); 827 828 if (Offset) { 829 HostPtr = Builder.CreatePointerCast( 830 HostPtr, ScopArray->getElementType()->getPointerTo()); 831 HostPtr = Builder.CreateGEP(HostPtr, Offset); 832 } 833 834 HostPtr = Builder.CreatePointerCast(HostPtr, Builder.getInt8PtrTy()); 835 836 if (Offset) { 837 Size = Builder.CreateSub( 838 Size, Builder.CreateMul( 839 Offset, Builder.getInt64(ScopArray->getElemSizeInBytes()))); 840 } 841 842 if (Direction == HOST_TO_DEVICE) 843 createCallCopyFromHostToDevice(HostPtr, DevPtr, Size); 844 else 845 createCallCopyFromDeviceToHost(DevPtr, HostPtr, Size); 846 847 isl_id_free(Id); 848 isl_ast_expr_free(Arg); 849 isl_ast_expr_free(Expr); 850 isl_ast_node_free(TransferStmt); 851 } 852 853 void GPUNodeBuilder::createUser(__isl_take isl_ast_node *UserStmt) { 854 isl_ast_expr *Expr = isl_ast_node_user_get_expr(UserStmt); 855 isl_ast_expr *StmtExpr = isl_ast_expr_get_op_arg(Expr, 0); 856 isl_id *Id = isl_ast_expr_get_id(StmtExpr); 857 isl_id_free(Id); 858 isl_ast_expr_free(StmtExpr); 859 860 const char *Str = isl_id_get_name(Id); 861 if (!strcmp(Str, "kernel")) { 862 createKernel(UserStmt); 863 isl_ast_expr_free(Expr); 864 return; 865 } 866 867 if (isPrefix(Str, "to_device")) { 868 createDataTransfer(UserStmt, HOST_TO_DEVICE); 869 isl_ast_expr_free(Expr); 870 return; 871 } 872 873 if (isPrefix(Str, "from_device")) { 874 createDataTransfer(UserStmt, DEVICE_TO_HOST); 875 isl_ast_expr_free(Expr); 876 return; 877 } 878 879 isl_id *Anno = isl_ast_node_get_annotation(UserStmt); 880 struct ppcg_kernel_stmt *KernelStmt = 881 (struct ppcg_kernel_stmt *)isl_id_get_user(Anno); 882 isl_id_free(Anno); 883 884 switch (KernelStmt->type) { 885 case ppcg_kernel_domain: 886 createScopStmt(Expr, KernelStmt); 887 isl_ast_node_free(UserStmt); 888 return; 889 case ppcg_kernel_copy: 890 createKernelCopy(KernelStmt); 891 isl_ast_expr_free(Expr); 892 isl_ast_node_free(UserStmt); 893 return; 894 case ppcg_kernel_sync: 895 createKernelSync(); 896 isl_ast_expr_free(Expr); 897 isl_ast_node_free(UserStmt); 898 return; 899 } 900 901 isl_ast_expr_free(Expr); 902 isl_ast_node_free(UserStmt); 903 return; 904 } 905 void GPUNodeBuilder::createKernelCopy(ppcg_kernel_stmt *KernelStmt) { 906 isl_ast_expr *LocalIndex = isl_ast_expr_copy(KernelStmt->u.c.local_index); 907 LocalIndex = isl_ast_expr_address_of(LocalIndex); 908 Value *LocalAddr = ExprBuilder.create(LocalIndex); 909 isl_ast_expr *Index = isl_ast_expr_copy(KernelStmt->u.c.index); 910 Index = isl_ast_expr_address_of(Index); 911 Value *GlobalAddr = ExprBuilder.create(Index); 912 913 if (KernelStmt->u.c.read) { 914 LoadInst *Load = Builder.CreateLoad(GlobalAddr, "shared.read"); 915 Builder.CreateStore(Load, LocalAddr); 916 } else { 917 LoadInst *Load = Builder.CreateLoad(LocalAddr, "shared.write"); 918 Builder.CreateStore(Load, GlobalAddr); 919 } 920 } 921 922 void GPUNodeBuilder::createScopStmt(isl_ast_expr *Expr, 923 ppcg_kernel_stmt *KernelStmt) { 924 auto Stmt = (ScopStmt *)KernelStmt->u.d.stmt->stmt; 925 isl_id_to_ast_expr *Indexes = KernelStmt->u.d.ref2expr; 926 927 LoopToScevMapT LTS; 928 LTS.insert(OutsideLoopIterations.begin(), OutsideLoopIterations.end()); 929 930 createSubstitutions(Expr, Stmt, LTS); 931 932 if (Stmt->isBlockStmt()) 933 BlockGen.copyStmt(*Stmt, LTS, Indexes); 934 else 935 RegionGen.copyStmt(*Stmt, LTS, Indexes); 936 } 937 938 void GPUNodeBuilder::createKernelSync() { 939 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 940 auto *Sync = Intrinsic::getDeclaration(M, Intrinsic::nvvm_barrier0); 941 Builder.CreateCall(Sync, {}); 942 } 943 944 /// Collect llvm::Values referenced from @p Node 945 /// 946 /// This function only applies to isl_ast_nodes that are user_nodes referring 947 /// to a ScopStmt. All other node types are ignore. 948 /// 949 /// @param Node The node to collect references for. 950 /// @param User A user pointer used as storage for the data that is collected. 951 /// 952 /// @returns isl_bool_true if data could be collected successfully. 953 isl_bool collectReferencesInGPUStmt(__isl_keep isl_ast_node *Node, void *User) { 954 if (isl_ast_node_get_type(Node) != isl_ast_node_user) 955 return isl_bool_true; 956 957 isl_ast_expr *Expr = isl_ast_node_user_get_expr(Node); 958 isl_ast_expr *StmtExpr = isl_ast_expr_get_op_arg(Expr, 0); 959 isl_id *Id = isl_ast_expr_get_id(StmtExpr); 960 const char *Str = isl_id_get_name(Id); 961 isl_id_free(Id); 962 isl_ast_expr_free(StmtExpr); 963 isl_ast_expr_free(Expr); 964 965 if (!isPrefix(Str, "Stmt")) 966 return isl_bool_true; 967 968 Id = isl_ast_node_get_annotation(Node); 969 auto *KernelStmt = (ppcg_kernel_stmt *)isl_id_get_user(Id); 970 auto Stmt = (ScopStmt *)KernelStmt->u.d.stmt->stmt; 971 isl_id_free(Id); 972 973 addReferencesFromStmt(Stmt, User, false /* CreateScalarRefs */); 974 975 return isl_bool_true; 976 } 977 978 SetVector<Value *> GPUNodeBuilder::getReferencesInKernel(ppcg_kernel *Kernel) { 979 SetVector<Value *> SubtreeValues; 980 SetVector<const SCEV *> SCEVs; 981 SetVector<const Loop *> Loops; 982 SubtreeReferences References = { 983 LI, SE, S, ValueMap, SubtreeValues, SCEVs, getBlockGenerator()}; 984 985 for (const auto &I : IDToValue) 986 SubtreeValues.insert(I.second); 987 988 isl_ast_node_foreach_descendant_top_down( 989 Kernel->tree, collectReferencesInGPUStmt, &References); 990 991 for (const SCEV *Expr : SCEVs) 992 findValues(Expr, SE, SubtreeValues); 993 994 for (auto &SAI : S.arrays()) 995 SubtreeValues.remove(SAI->getBasePtr()); 996 997 isl_space *Space = S.getParamSpace(); 998 for (long i = 0; i < isl_space_dim(Space, isl_dim_param); i++) { 999 isl_id *Id = isl_space_get_dim_id(Space, isl_dim_param, i); 1000 assert(IDToValue.count(Id)); 1001 Value *Val = IDToValue[Id]; 1002 SubtreeValues.remove(Val); 1003 isl_id_free(Id); 1004 } 1005 isl_space_free(Space); 1006 1007 for (long i = 0; i < isl_space_dim(Kernel->space, isl_dim_set); i++) { 1008 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1009 assert(IDToValue.count(Id)); 1010 Value *Val = IDToValue[Id]; 1011 SubtreeValues.remove(Val); 1012 isl_id_free(Id); 1013 } 1014 1015 return SubtreeValues; 1016 } 1017 1018 void GPUNodeBuilder::clearDominators(Function *F) { 1019 DomTreeNode *N = DT.getNode(&F->getEntryBlock()); 1020 std::vector<BasicBlock *> Nodes; 1021 for (po_iterator<DomTreeNode *> I = po_begin(N), E = po_end(N); I != E; ++I) 1022 Nodes.push_back(I->getBlock()); 1023 1024 for (BasicBlock *BB : Nodes) 1025 DT.eraseNode(BB); 1026 } 1027 1028 void GPUNodeBuilder::clearScalarEvolution(Function *F) { 1029 for (BasicBlock &BB : *F) { 1030 Loop *L = LI.getLoopFor(&BB); 1031 if (L) 1032 SE.forgetLoop(L); 1033 } 1034 } 1035 1036 void GPUNodeBuilder::clearLoops(Function *F) { 1037 for (BasicBlock &BB : *F) { 1038 Loop *L = LI.getLoopFor(&BB); 1039 if (L) 1040 SE.forgetLoop(L); 1041 LI.removeBlock(&BB); 1042 } 1043 } 1044 1045 std::tuple<Value *, Value *> GPUNodeBuilder::getGridSizes(ppcg_kernel *Kernel) { 1046 std::vector<Value *> Sizes; 1047 isl_ast_build *Context = isl_ast_build_from_context(S.getContext()); 1048 1049 for (long i = 0; i < Kernel->n_grid; i++) { 1050 isl_pw_aff *Size = isl_multi_pw_aff_get_pw_aff(Kernel->grid_size, i); 1051 isl_ast_expr *GridSize = isl_ast_build_expr_from_pw_aff(Context, Size); 1052 Value *Res = ExprBuilder.create(GridSize); 1053 Res = Builder.CreateTrunc(Res, Builder.getInt32Ty()); 1054 Sizes.push_back(Res); 1055 } 1056 isl_ast_build_free(Context); 1057 1058 for (long i = Kernel->n_grid; i < 3; i++) 1059 Sizes.push_back(ConstantInt::get(Builder.getInt32Ty(), 1)); 1060 1061 return std::make_tuple(Sizes[0], Sizes[1]); 1062 } 1063 1064 std::tuple<Value *, Value *, Value *> 1065 GPUNodeBuilder::getBlockSizes(ppcg_kernel *Kernel) { 1066 std::vector<Value *> Sizes; 1067 1068 for (long i = 0; i < Kernel->n_block; i++) { 1069 Value *Res = ConstantInt::get(Builder.getInt32Ty(), Kernel->block_dim[i]); 1070 Sizes.push_back(Res); 1071 } 1072 1073 for (long i = Kernel->n_block; i < 3; i++) 1074 Sizes.push_back(ConstantInt::get(Builder.getInt32Ty(), 1)); 1075 1076 return std::make_tuple(Sizes[0], Sizes[1], Sizes[2]); 1077 } 1078 1079 Value * 1080 GPUNodeBuilder::createLaunchParameters(ppcg_kernel *Kernel, Function *F, 1081 SetVector<Value *> SubtreeValues) { 1082 Type *ArrayTy = ArrayType::get(Builder.getInt8PtrTy(), 1083 std::distance(F->arg_begin(), F->arg_end())); 1084 1085 BasicBlock *EntryBlock = 1086 &Builder.GetInsertBlock()->getParent()->getEntryBlock(); 1087 std::string Launch = "polly_launch_" + std::to_string(Kernel->id); 1088 Instruction *Parameters = 1089 new AllocaInst(ArrayTy, Launch + "_params", EntryBlock->getTerminator()); 1090 1091 int Index = 0; 1092 for (long i = 0; i < Prog->n_array; i++) { 1093 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1094 continue; 1095 1096 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1097 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(Id); 1098 1099 Value *DevArray = DeviceAllocations[const_cast<ScopArrayInfo *>(SAI)]; 1100 DevArray = createCallGetDevicePtr(DevArray); 1101 1102 Value *Offset = getArrayOffset(&Prog->array[i]); 1103 1104 if (Offset) { 1105 DevArray = Builder.CreatePointerCast( 1106 DevArray, SAI->getElementType()->getPointerTo()); 1107 DevArray = Builder.CreateGEP(DevArray, Builder.CreateNeg(Offset)); 1108 DevArray = Builder.CreatePointerCast(DevArray, Builder.getInt8PtrTy()); 1109 } 1110 Value *Slot = Builder.CreateGEP( 1111 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1112 1113 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1114 Value *ValPtr = BlockGen.getOrCreateAlloca(SAI); 1115 Value *ValPtrCast = 1116 Builder.CreatePointerCast(ValPtr, Builder.getInt8PtrTy()); 1117 Builder.CreateStore(ValPtrCast, Slot); 1118 } else { 1119 Instruction *Param = new AllocaInst( 1120 Builder.getInt8PtrTy(), Launch + "_param_" + std::to_string(Index), 1121 EntryBlock->getTerminator()); 1122 Builder.CreateStore(DevArray, Param); 1123 Value *ParamTyped = 1124 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1125 Builder.CreateStore(ParamTyped, Slot); 1126 } 1127 Index++; 1128 } 1129 1130 int NumHostIters = isl_space_dim(Kernel->space, isl_dim_set); 1131 1132 for (long i = 0; i < NumHostIters; i++) { 1133 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1134 Value *Val = IDToValue[Id]; 1135 isl_id_free(Id); 1136 Instruction *Param = new AllocaInst( 1137 Val->getType(), Launch + "_param_" + std::to_string(Index), 1138 EntryBlock->getTerminator()); 1139 Builder.CreateStore(Val, Param); 1140 Value *Slot = Builder.CreateGEP( 1141 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1142 Value *ParamTyped = 1143 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1144 Builder.CreateStore(ParamTyped, Slot); 1145 Index++; 1146 } 1147 1148 int NumVars = isl_space_dim(Kernel->space, isl_dim_param); 1149 1150 for (long i = 0; i < NumVars; i++) { 1151 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1152 Value *Val = IDToValue[Id]; 1153 isl_id_free(Id); 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 for (auto Val : SubtreeValues) { 1167 Instruction *Param = new AllocaInst( 1168 Val->getType(), Launch + "_param_" + std::to_string(Index), 1169 EntryBlock->getTerminator()); 1170 Builder.CreateStore(Val, Param); 1171 Value *Slot = Builder.CreateGEP( 1172 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1173 Value *ParamTyped = 1174 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1175 Builder.CreateStore(ParamTyped, Slot); 1176 Index++; 1177 } 1178 1179 auto Location = EntryBlock->getTerminator(); 1180 return new BitCastInst(Parameters, Builder.getInt8PtrTy(), 1181 Launch + "_params_i8ptr", Location); 1182 } 1183 1184 void GPUNodeBuilder::createKernel(__isl_take isl_ast_node *KernelStmt) { 1185 isl_id *Id = isl_ast_node_get_annotation(KernelStmt); 1186 ppcg_kernel *Kernel = (ppcg_kernel *)isl_id_get_user(Id); 1187 isl_id_free(Id); 1188 isl_ast_node_free(KernelStmt); 1189 1190 if (Kernel->n_grid > 1) 1191 DeepestParallel = 1192 std::max(DeepestParallel, isl_space_dim(Kernel->space, isl_dim_set)); 1193 else 1194 DeepestSequential = 1195 std::max(DeepestSequential, isl_space_dim(Kernel->space, isl_dim_set)); 1196 1197 Value *BlockDimX, *BlockDimY, *BlockDimZ; 1198 std::tie(BlockDimX, BlockDimY, BlockDimZ) = getBlockSizes(Kernel); 1199 1200 SetVector<Value *> SubtreeValues = getReferencesInKernel(Kernel); 1201 1202 assert(Kernel->tree && "Device AST of kernel node is empty"); 1203 1204 Instruction &HostInsertPoint = *Builder.GetInsertPoint(); 1205 IslExprBuilder::IDToValueTy HostIDs = IDToValue; 1206 ValueMapT HostValueMap = ValueMap; 1207 BlockGenerator::ScalarAllocaMapTy HostScalarMap = ScalarMap; 1208 BlockGenerator::ScalarAllocaMapTy HostPHIOpMap = PHIOpMap; 1209 ScalarMap.clear(); 1210 PHIOpMap.clear(); 1211 1212 SetVector<const Loop *> Loops; 1213 1214 // Create for all loops we depend on values that contain the current loop 1215 // iteration. These values are necessary to generate code for SCEVs that 1216 // depend on such loops. As a result we need to pass them to the subfunction. 1217 for (const Loop *L : Loops) { 1218 const SCEV *OuterLIV = SE.getAddRecExpr(SE.getUnknown(Builder.getInt64(0)), 1219 SE.getUnknown(Builder.getInt64(1)), 1220 L, SCEV::FlagAnyWrap); 1221 Value *V = generateSCEV(OuterLIV); 1222 OutsideLoopIterations[L] = SE.getUnknown(V); 1223 SubtreeValues.insert(V); 1224 } 1225 1226 createKernelFunction(Kernel, SubtreeValues); 1227 1228 create(isl_ast_node_copy(Kernel->tree)); 1229 1230 finalizeKernelArguments(Kernel); 1231 Function *F = Builder.GetInsertBlock()->getParent(); 1232 addCUDAAnnotations(F->getParent(), BlockDimX, BlockDimY, BlockDimZ); 1233 clearDominators(F); 1234 clearScalarEvolution(F); 1235 clearLoops(F); 1236 1237 IDToValue = HostIDs; 1238 1239 ValueMap = std::move(HostValueMap); 1240 ScalarMap = std::move(HostScalarMap); 1241 PHIOpMap = std::move(HostPHIOpMap); 1242 EscapeMap.clear(); 1243 IDToSAI.clear(); 1244 Annotator.resetAlternativeAliasBases(); 1245 for (auto &BasePtr : LocalArrays) 1246 S.invalidateScopArrayInfo(BasePtr, ScopArrayInfo::MK_Array); 1247 LocalArrays.clear(); 1248 1249 std::string ASMString = finalizeKernelFunction(); 1250 Builder.SetInsertPoint(&HostInsertPoint); 1251 Value *Parameters = createLaunchParameters(Kernel, F, SubtreeValues); 1252 1253 std::string Name = "kernel_" + std::to_string(Kernel->id); 1254 Value *KernelString = Builder.CreateGlobalStringPtr(ASMString, Name); 1255 Value *NameString = Builder.CreateGlobalStringPtr(Name, Name + "_name"); 1256 Value *GPUKernel = createCallGetKernel(KernelString, NameString); 1257 1258 Value *GridDimX, *GridDimY; 1259 std::tie(GridDimX, GridDimY) = getGridSizes(Kernel); 1260 1261 createCallLaunchKernel(GPUKernel, GridDimX, GridDimY, BlockDimX, BlockDimY, 1262 BlockDimZ, Parameters); 1263 createCallFreeKernel(GPUKernel); 1264 1265 for (auto Id : KernelIds) 1266 isl_id_free(Id); 1267 1268 KernelIds.clear(); 1269 } 1270 1271 /// Compute the DataLayout string for the NVPTX backend. 1272 /// 1273 /// @param is64Bit Are we looking for a 64 bit architecture? 1274 static std::string computeNVPTXDataLayout(bool is64Bit) { 1275 std::string Ret = "e"; 1276 1277 if (!is64Bit) 1278 Ret += "-p:32:32"; 1279 1280 Ret += "-i64:64-v16:16-v32:32-n16:32:64"; 1281 1282 return Ret; 1283 } 1284 1285 Function * 1286 GPUNodeBuilder::createKernelFunctionDecl(ppcg_kernel *Kernel, 1287 SetVector<Value *> &SubtreeValues) { 1288 std::vector<Type *> Args; 1289 std::string Identifier = "kernel_" + std::to_string(Kernel->id); 1290 1291 for (long i = 0; i < Prog->n_array; i++) { 1292 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1293 continue; 1294 1295 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1296 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1297 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(Id); 1298 Args.push_back(SAI->getElementType()); 1299 } else { 1300 Args.push_back(Builder.getInt8PtrTy()); 1301 } 1302 } 1303 1304 int NumHostIters = isl_space_dim(Kernel->space, isl_dim_set); 1305 1306 for (long i = 0; i < NumHostIters; i++) 1307 Args.push_back(Builder.getInt64Ty()); 1308 1309 int NumVars = isl_space_dim(Kernel->space, isl_dim_param); 1310 1311 for (long i = 0; i < NumVars; i++) { 1312 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1313 Value *Val = IDToValue[Id]; 1314 isl_id_free(Id); 1315 Args.push_back(Val->getType()); 1316 } 1317 1318 for (auto *V : SubtreeValues) 1319 Args.push_back(V->getType()); 1320 1321 auto *FT = FunctionType::get(Builder.getVoidTy(), Args, false); 1322 auto *FN = Function::Create(FT, Function::ExternalLinkage, Identifier, 1323 GPUModule.get()); 1324 FN->setCallingConv(CallingConv::PTX_Kernel); 1325 1326 auto Arg = FN->arg_begin(); 1327 for (long i = 0; i < Kernel->n_array; i++) { 1328 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1329 continue; 1330 1331 Arg->setName(Kernel->array[i].array->name); 1332 1333 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1334 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1335 Type *EleTy = SAI->getElementType(); 1336 Value *Val = &*Arg; 1337 SmallVector<const SCEV *, 4> Sizes; 1338 isl_ast_build *Build = 1339 isl_ast_build_from_context(isl_set_copy(Prog->context)); 1340 Sizes.push_back(nullptr); 1341 for (long j = 1; j < Kernel->array[i].array->n_index; j++) { 1342 isl_ast_expr *DimSize = isl_ast_build_expr_from_pw_aff( 1343 Build, isl_pw_aff_copy(Kernel->array[i].array->bound[j])); 1344 auto V = ExprBuilder.create(DimSize); 1345 Sizes.push_back(SE.getSCEV(V)); 1346 } 1347 const ScopArrayInfo *SAIRep = 1348 S.getOrCreateScopArrayInfo(Val, EleTy, Sizes, ScopArrayInfo::MK_Array); 1349 LocalArrays.push_back(Val); 1350 1351 isl_ast_build_free(Build); 1352 KernelIds.push_back(Id); 1353 IDToSAI[Id] = SAIRep; 1354 Arg++; 1355 } 1356 1357 for (long i = 0; i < NumHostIters; i++) { 1358 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1359 Arg->setName(isl_id_get_name(Id)); 1360 IDToValue[Id] = &*Arg; 1361 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1362 Arg++; 1363 } 1364 1365 for (long i = 0; i < NumVars; i++) { 1366 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1367 Arg->setName(isl_id_get_name(Id)); 1368 Value *Val = IDToValue[Id]; 1369 ValueMap[Val] = &*Arg; 1370 IDToValue[Id] = &*Arg; 1371 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1372 Arg++; 1373 } 1374 1375 for (auto *V : SubtreeValues) { 1376 Arg->setName(V->getName()); 1377 ValueMap[V] = &*Arg; 1378 Arg++; 1379 } 1380 1381 return FN; 1382 } 1383 1384 void GPUNodeBuilder::insertKernelIntrinsics(ppcg_kernel *Kernel) { 1385 Intrinsic::ID IntrinsicsBID[] = {Intrinsic::nvvm_read_ptx_sreg_ctaid_x, 1386 Intrinsic::nvvm_read_ptx_sreg_ctaid_y}; 1387 1388 Intrinsic::ID IntrinsicsTID[] = {Intrinsic::nvvm_read_ptx_sreg_tid_x, 1389 Intrinsic::nvvm_read_ptx_sreg_tid_y, 1390 Intrinsic::nvvm_read_ptx_sreg_tid_z}; 1391 1392 auto addId = [this](__isl_take isl_id *Id, Intrinsic::ID Intr) mutable { 1393 std::string Name = isl_id_get_name(Id); 1394 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 1395 Function *IntrinsicFn = Intrinsic::getDeclaration(M, Intr); 1396 Value *Val = Builder.CreateCall(IntrinsicFn, {}); 1397 Val = Builder.CreateIntCast(Val, Builder.getInt64Ty(), false, Name); 1398 IDToValue[Id] = Val; 1399 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1400 }; 1401 1402 for (int i = 0; i < Kernel->n_grid; ++i) { 1403 isl_id *Id = isl_id_list_get_id(Kernel->block_ids, i); 1404 addId(Id, IntrinsicsBID[i]); 1405 } 1406 1407 for (int i = 0; i < Kernel->n_block; ++i) { 1408 isl_id *Id = isl_id_list_get_id(Kernel->thread_ids, i); 1409 addId(Id, IntrinsicsTID[i]); 1410 } 1411 } 1412 1413 void GPUNodeBuilder::prepareKernelArguments(ppcg_kernel *Kernel, Function *FN) { 1414 auto Arg = FN->arg_begin(); 1415 for (long i = 0; i < Kernel->n_array; i++) { 1416 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1417 continue; 1418 1419 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1420 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1421 isl_id_free(Id); 1422 1423 if (SAI->getNumberOfDimensions() > 0) { 1424 Arg++; 1425 continue; 1426 } 1427 1428 Value *Val = &*Arg; 1429 1430 if (!gpu_array_is_read_only_scalar(&Prog->array[i])) { 1431 Type *TypePtr = SAI->getElementType()->getPointerTo(); 1432 Value *TypedArgPtr = Builder.CreatePointerCast(Val, TypePtr); 1433 Val = Builder.CreateLoad(TypedArgPtr); 1434 } 1435 1436 Value *Alloca = BlockGen.getOrCreateAlloca(SAI); 1437 Builder.CreateStore(Val, Alloca); 1438 1439 Arg++; 1440 } 1441 } 1442 1443 void GPUNodeBuilder::finalizeKernelArguments(ppcg_kernel *Kernel) { 1444 auto *FN = Builder.GetInsertBlock()->getParent(); 1445 auto Arg = FN->arg_begin(); 1446 1447 bool StoredScalar = false; 1448 for (long i = 0; i < Kernel->n_array; i++) { 1449 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1450 continue; 1451 1452 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1453 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1454 isl_id_free(Id); 1455 1456 if (SAI->getNumberOfDimensions() > 0) { 1457 Arg++; 1458 continue; 1459 } 1460 1461 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1462 Arg++; 1463 continue; 1464 } 1465 1466 Value *Alloca = BlockGen.getOrCreateAlloca(SAI); 1467 Value *ArgPtr = &*Arg; 1468 Type *TypePtr = SAI->getElementType()->getPointerTo(); 1469 Value *TypedArgPtr = Builder.CreatePointerCast(ArgPtr, TypePtr); 1470 Value *Val = Builder.CreateLoad(Alloca); 1471 Builder.CreateStore(Val, TypedArgPtr); 1472 StoredScalar = true; 1473 1474 Arg++; 1475 } 1476 1477 if (StoredScalar) 1478 /// In case more than one thread contains scalar stores, the generated 1479 /// code might be incorrect, if we only store at the end of the kernel. 1480 /// To support this case we need to store these scalars back at each 1481 /// memory store or at least before each kernel barrier. 1482 if (Kernel->n_block != 0 || Kernel->n_grid != 0) 1483 BuildSuccessful = 0; 1484 } 1485 1486 void GPUNodeBuilder::createKernelVariables(ppcg_kernel *Kernel, Function *FN) { 1487 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 1488 1489 for (int i = 0; i < Kernel->n_var; ++i) { 1490 struct ppcg_kernel_var &Var = Kernel->var[i]; 1491 isl_id *Id = isl_space_get_tuple_id(Var.array->space, isl_dim_set); 1492 Type *EleTy = ScopArrayInfo::getFromId(Id)->getElementType(); 1493 1494 Type *ArrayTy = EleTy; 1495 SmallVector<const SCEV *, 4> Sizes; 1496 1497 Sizes.push_back(nullptr); 1498 for (unsigned int j = 1; j < Var.array->n_index; ++j) { 1499 isl_val *Val = isl_vec_get_element_val(Var.size, j); 1500 long Bound = isl_val_get_num_si(Val); 1501 isl_val_free(Val); 1502 Sizes.push_back(S.getSE()->getConstant(Builder.getInt64Ty(), Bound)); 1503 } 1504 1505 for (int j = Var.array->n_index - 1; j >= 0; --j) { 1506 isl_val *Val = isl_vec_get_element_val(Var.size, j); 1507 long Bound = isl_val_get_num_si(Val); 1508 isl_val_free(Val); 1509 ArrayTy = ArrayType::get(ArrayTy, Bound); 1510 } 1511 1512 const ScopArrayInfo *SAI; 1513 Value *Allocation; 1514 if (Var.type == ppcg_access_shared) { 1515 auto GlobalVar = new GlobalVariable( 1516 *M, ArrayTy, false, GlobalValue::InternalLinkage, 0, Var.name, 1517 nullptr, GlobalValue::ThreadLocalMode::NotThreadLocal, 3); 1518 GlobalVar->setAlignment(EleTy->getPrimitiveSizeInBits() / 8); 1519 GlobalVar->setInitializer(Constant::getNullValue(ArrayTy)); 1520 1521 Allocation = GlobalVar; 1522 } else if (Var.type == ppcg_access_private) { 1523 Allocation = Builder.CreateAlloca(ArrayTy, 0, "private_array"); 1524 } else { 1525 llvm_unreachable("unknown variable type"); 1526 } 1527 SAI = S.getOrCreateScopArrayInfo(Allocation, EleTy, Sizes, 1528 ScopArrayInfo::MK_Array); 1529 Id = isl_id_alloc(S.getIslCtx(), Var.name, nullptr); 1530 IDToValue[Id] = Allocation; 1531 LocalArrays.push_back(Allocation); 1532 KernelIds.push_back(Id); 1533 IDToSAI[Id] = SAI; 1534 } 1535 } 1536 1537 void GPUNodeBuilder::createKernelFunction(ppcg_kernel *Kernel, 1538 SetVector<Value *> &SubtreeValues) { 1539 1540 std::string Identifier = "kernel_" + std::to_string(Kernel->id); 1541 GPUModule.reset(new Module(Identifier, Builder.getContext())); 1542 GPUModule->setTargetTriple(Triple::normalize("nvptx64-nvidia-cuda")); 1543 GPUModule->setDataLayout(computeNVPTXDataLayout(true /* is64Bit */)); 1544 1545 Function *FN = createKernelFunctionDecl(Kernel, SubtreeValues); 1546 1547 BasicBlock *PrevBlock = Builder.GetInsertBlock(); 1548 auto EntryBlock = BasicBlock::Create(Builder.getContext(), "entry", FN); 1549 1550 DominatorTree &DT = P->getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 1551 DT.addNewBlock(EntryBlock, PrevBlock); 1552 1553 Builder.SetInsertPoint(EntryBlock); 1554 Builder.CreateRetVoid(); 1555 Builder.SetInsertPoint(EntryBlock, EntryBlock->begin()); 1556 1557 ScopDetection::markFunctionAsInvalid(FN); 1558 1559 prepareKernelArguments(Kernel, FN); 1560 createKernelVariables(Kernel, FN); 1561 insertKernelIntrinsics(Kernel); 1562 } 1563 1564 std::string GPUNodeBuilder::createKernelASM() { 1565 llvm::Triple GPUTriple(Triple::normalize("nvptx64-nvidia-cuda")); 1566 std::string ErrMsg; 1567 auto GPUTarget = TargetRegistry::lookupTarget(GPUTriple.getTriple(), ErrMsg); 1568 1569 if (!GPUTarget) { 1570 errs() << ErrMsg << "\n"; 1571 return ""; 1572 } 1573 1574 TargetOptions Options; 1575 Options.UnsafeFPMath = FastMath; 1576 std::unique_ptr<TargetMachine> TargetM( 1577 GPUTarget->createTargetMachine(GPUTriple.getTriple(), CudaVersion, "", 1578 Options, Optional<Reloc::Model>())); 1579 1580 SmallString<0> ASMString; 1581 raw_svector_ostream ASMStream(ASMString); 1582 llvm::legacy::PassManager PM; 1583 1584 PM.add(createTargetTransformInfoWrapperPass(TargetM->getTargetIRAnalysis())); 1585 1586 if (TargetM->addPassesToEmitFile( 1587 PM, ASMStream, TargetMachine::CGFT_AssemblyFile, true /* verify */)) { 1588 errs() << "The target does not support generation of this file type!\n"; 1589 return ""; 1590 } 1591 1592 PM.run(*GPUModule); 1593 1594 return ASMStream.str(); 1595 } 1596 1597 std::string GPUNodeBuilder::finalizeKernelFunction() { 1598 if (verifyModule(*GPUModule)) { 1599 BuildSuccessful = false; 1600 return ""; 1601 } 1602 1603 if (DumpKernelIR) 1604 outs() << *GPUModule << "\n"; 1605 1606 // Optimize module. 1607 llvm::legacy::PassManager OptPasses; 1608 PassManagerBuilder PassBuilder; 1609 PassBuilder.OptLevel = 3; 1610 PassBuilder.SizeLevel = 0; 1611 PassBuilder.populateModulePassManager(OptPasses); 1612 OptPasses.run(*GPUModule); 1613 1614 std::string Assembly = createKernelASM(); 1615 1616 if (DumpKernelASM) 1617 outs() << Assembly << "\n"; 1618 1619 GPUModule.release(); 1620 KernelIDs.clear(); 1621 1622 return Assembly; 1623 } 1624 1625 namespace { 1626 class PPCGCodeGeneration : public ScopPass { 1627 public: 1628 static char ID; 1629 1630 /// The scop that is currently processed. 1631 Scop *S; 1632 1633 LoopInfo *LI; 1634 DominatorTree *DT; 1635 ScalarEvolution *SE; 1636 const DataLayout *DL; 1637 RegionInfo *RI; 1638 1639 PPCGCodeGeneration() : ScopPass(ID) {} 1640 1641 /// Construct compilation options for PPCG. 1642 /// 1643 /// @returns The compilation options. 1644 ppcg_options *createPPCGOptions() { 1645 auto DebugOptions = 1646 (ppcg_debug_options *)malloc(sizeof(ppcg_debug_options)); 1647 auto Options = (ppcg_options *)malloc(sizeof(ppcg_options)); 1648 1649 DebugOptions->dump_schedule_constraints = false; 1650 DebugOptions->dump_schedule = false; 1651 DebugOptions->dump_final_schedule = false; 1652 DebugOptions->dump_sizes = false; 1653 DebugOptions->verbose = false; 1654 1655 Options->debug = DebugOptions; 1656 1657 Options->reschedule = true; 1658 Options->scale_tile_loops = false; 1659 Options->wrap = false; 1660 1661 Options->non_negative_parameters = false; 1662 Options->ctx = nullptr; 1663 Options->sizes = nullptr; 1664 1665 Options->tile_size = 32; 1666 1667 Options->use_private_memory = PrivateMemory; 1668 Options->use_shared_memory = SharedMemory; 1669 Options->max_shared_memory = 48 * 1024; 1670 1671 Options->target = PPCG_TARGET_CUDA; 1672 Options->openmp = false; 1673 Options->linearize_device_arrays = true; 1674 Options->live_range_reordering = false; 1675 1676 Options->opencl_compiler_options = nullptr; 1677 Options->opencl_use_gpu = false; 1678 Options->opencl_n_include_file = 0; 1679 Options->opencl_include_files = nullptr; 1680 Options->opencl_print_kernel_types = false; 1681 Options->opencl_embed_kernel_code = false; 1682 1683 Options->save_schedule_file = nullptr; 1684 Options->load_schedule_file = nullptr; 1685 1686 return Options; 1687 } 1688 1689 /// Get a tagged access relation containing all accesses of type @p AccessTy. 1690 /// 1691 /// Instead of a normal access of the form: 1692 /// 1693 /// Stmt[i,j,k] -> Array[f_0(i,j,k), f_1(i,j,k)] 1694 /// 1695 /// a tagged access has the form 1696 /// 1697 /// [Stmt[i,j,k] -> id[]] -> Array[f_0(i,j,k), f_1(i,j,k)] 1698 /// 1699 /// where 'id' is an additional space that references the memory access that 1700 /// triggered the access. 1701 /// 1702 /// @param AccessTy The type of the memory accesses to collect. 1703 /// 1704 /// @return The relation describing all tagged memory accesses. 1705 isl_union_map *getTaggedAccesses(enum MemoryAccess::AccessType AccessTy) { 1706 isl_union_map *Accesses = isl_union_map_empty(S->getParamSpace()); 1707 1708 for (auto &Stmt : *S) 1709 for (auto &Acc : Stmt) 1710 if (Acc->getType() == AccessTy) { 1711 isl_map *Relation = Acc->getAccessRelation(); 1712 Relation = isl_map_intersect_domain(Relation, Stmt.getDomain()); 1713 1714 isl_space *Space = isl_map_get_space(Relation); 1715 Space = isl_space_range(Space); 1716 Space = isl_space_from_range(Space); 1717 Space = isl_space_set_tuple_id(Space, isl_dim_in, Acc->getId()); 1718 isl_map *Universe = isl_map_universe(Space); 1719 Relation = isl_map_domain_product(Relation, Universe); 1720 Accesses = isl_union_map_add_map(Accesses, Relation); 1721 } 1722 1723 return Accesses; 1724 } 1725 1726 /// Get the set of all read accesses, tagged with the access id. 1727 /// 1728 /// @see getTaggedAccesses 1729 isl_union_map *getTaggedReads() { 1730 return getTaggedAccesses(MemoryAccess::READ); 1731 } 1732 1733 /// Get the set of all may (and must) accesses, tagged with the access id. 1734 /// 1735 /// @see getTaggedAccesses 1736 isl_union_map *getTaggedMayWrites() { 1737 return isl_union_map_union(getTaggedAccesses(MemoryAccess::MAY_WRITE), 1738 getTaggedAccesses(MemoryAccess::MUST_WRITE)); 1739 } 1740 1741 /// Get the set of all must accesses, tagged with the access id. 1742 /// 1743 /// @see getTaggedAccesses 1744 isl_union_map *getTaggedMustWrites() { 1745 return getTaggedAccesses(MemoryAccess::MUST_WRITE); 1746 } 1747 1748 /// Collect parameter and array names as isl_ids. 1749 /// 1750 /// To reason about the different parameters and arrays used, ppcg requires 1751 /// a list of all isl_ids in use. As PPCG traditionally performs 1752 /// source-to-source compilation each of these isl_ids is mapped to the 1753 /// expression that represents it. As we do not have a corresponding 1754 /// expression in Polly, we just map each id to a 'zero' expression to match 1755 /// the data format that ppcg expects. 1756 /// 1757 /// @returns Retun a map from collected ids to 'zero' ast expressions. 1758 __isl_give isl_id_to_ast_expr *getNames() { 1759 auto *Names = isl_id_to_ast_expr_alloc( 1760 S->getIslCtx(), 1761 S->getNumParams() + std::distance(S->array_begin(), S->array_end())); 1762 auto *Zero = isl_ast_expr_from_val(isl_val_zero(S->getIslCtx())); 1763 auto *Space = S->getParamSpace(); 1764 1765 for (int I = 0, E = S->getNumParams(); I < E; ++I) { 1766 isl_id *Id = isl_space_get_dim_id(Space, isl_dim_param, I); 1767 Names = isl_id_to_ast_expr_set(Names, Id, isl_ast_expr_copy(Zero)); 1768 } 1769 1770 for (auto &Array : S->arrays()) { 1771 auto Id = Array->getBasePtrId(); 1772 Names = isl_id_to_ast_expr_set(Names, Id, isl_ast_expr_copy(Zero)); 1773 } 1774 1775 isl_space_free(Space); 1776 isl_ast_expr_free(Zero); 1777 1778 return Names; 1779 } 1780 1781 /// Create a new PPCG scop from the current scop. 1782 /// 1783 /// The PPCG scop is initialized with data from the current polly::Scop. From 1784 /// this initial data, the data-dependences in the PPCG scop are initialized. 1785 /// We do not use Polly's dependence analysis for now, to ensure we match 1786 /// the PPCG default behaviour more closely. 1787 /// 1788 /// @returns A new ppcg scop. 1789 ppcg_scop *createPPCGScop() { 1790 auto PPCGScop = (ppcg_scop *)malloc(sizeof(ppcg_scop)); 1791 1792 PPCGScop->options = createPPCGOptions(); 1793 1794 PPCGScop->start = 0; 1795 PPCGScop->end = 0; 1796 1797 PPCGScop->context = S->getContext(); 1798 PPCGScop->domain = S->getDomains(); 1799 PPCGScop->call = nullptr; 1800 PPCGScop->tagged_reads = getTaggedReads(); 1801 PPCGScop->reads = S->getReads(); 1802 PPCGScop->live_in = nullptr; 1803 PPCGScop->tagged_may_writes = getTaggedMayWrites(); 1804 PPCGScop->may_writes = S->getWrites(); 1805 PPCGScop->tagged_must_writes = getTaggedMustWrites(); 1806 PPCGScop->must_writes = S->getMustWrites(); 1807 PPCGScop->live_out = nullptr; 1808 PPCGScop->tagged_must_kills = isl_union_map_empty(S->getParamSpace()); 1809 PPCGScop->tagger = nullptr; 1810 1811 PPCGScop->independence = nullptr; 1812 PPCGScop->dep_flow = nullptr; 1813 PPCGScop->tagged_dep_flow = nullptr; 1814 PPCGScop->dep_false = nullptr; 1815 PPCGScop->dep_forced = nullptr; 1816 PPCGScop->dep_order = nullptr; 1817 PPCGScop->tagged_dep_order = nullptr; 1818 1819 PPCGScop->schedule = S->getScheduleTree(); 1820 PPCGScop->names = getNames(); 1821 1822 PPCGScop->pet = nullptr; 1823 1824 compute_tagger(PPCGScop); 1825 compute_dependences(PPCGScop); 1826 1827 return PPCGScop; 1828 } 1829 1830 /// Collect the array acesses in a statement. 1831 /// 1832 /// @param Stmt The statement for which to collect the accesses. 1833 /// 1834 /// @returns A list of array accesses. 1835 gpu_stmt_access *getStmtAccesses(ScopStmt &Stmt) { 1836 gpu_stmt_access *Accesses = nullptr; 1837 1838 for (MemoryAccess *Acc : Stmt) { 1839 auto Access = isl_alloc_type(S->getIslCtx(), struct gpu_stmt_access); 1840 Access->read = Acc->isRead(); 1841 Access->write = Acc->isWrite(); 1842 Access->access = Acc->getAccessRelation(); 1843 isl_space *Space = isl_map_get_space(Access->access); 1844 Space = isl_space_range(Space); 1845 Space = isl_space_from_range(Space); 1846 Space = isl_space_set_tuple_id(Space, isl_dim_in, Acc->getId()); 1847 isl_map *Universe = isl_map_universe(Space); 1848 Access->tagged_access = 1849 isl_map_domain_product(Acc->getAccessRelation(), Universe); 1850 Access->exact_write = !Acc->isMayWrite(); 1851 Access->ref_id = Acc->getId(); 1852 Access->next = Accesses; 1853 Access->n_index = Acc->getScopArrayInfo()->getNumberOfDimensions(); 1854 Accesses = Access; 1855 } 1856 1857 return Accesses; 1858 } 1859 1860 /// Collect the list of GPU statements. 1861 /// 1862 /// Each statement has an id, a pointer to the underlying data structure, 1863 /// as well as a list with all memory accesses. 1864 /// 1865 /// TODO: Initialize the list of memory accesses. 1866 /// 1867 /// @returns A linked-list of statements. 1868 gpu_stmt *getStatements() { 1869 gpu_stmt *Stmts = isl_calloc_array(S->getIslCtx(), struct gpu_stmt, 1870 std::distance(S->begin(), S->end())); 1871 1872 int i = 0; 1873 for (auto &Stmt : *S) { 1874 gpu_stmt *GPUStmt = &Stmts[i]; 1875 1876 GPUStmt->id = Stmt.getDomainId(); 1877 1878 // We use the pet stmt pointer to keep track of the Polly statements. 1879 GPUStmt->stmt = (pet_stmt *)&Stmt; 1880 GPUStmt->accesses = getStmtAccesses(Stmt); 1881 i++; 1882 } 1883 1884 return Stmts; 1885 } 1886 1887 /// Derive the extent of an array. 1888 /// 1889 /// The extent of an array is the set of elements that are within the 1890 /// accessed array. For the inner dimensions, the extent constraints are 1891 /// 0 and the size of the corresponding array dimension. For the first 1892 /// (outermost) dimension, the extent constraints are the minimal and maximal 1893 /// subscript value for the first dimension. 1894 /// 1895 /// @param Array The array to derive the extent for. 1896 /// 1897 /// @returns An isl_set describing the extent of the array. 1898 __isl_give isl_set *getExtent(ScopArrayInfo *Array) { 1899 unsigned NumDims = Array->getNumberOfDimensions(); 1900 isl_union_map *Accesses = S->getAccesses(); 1901 Accesses = isl_union_map_intersect_domain(Accesses, S->getDomains()); 1902 Accesses = isl_union_map_detect_equalities(Accesses); 1903 isl_union_set *AccessUSet = isl_union_map_range(Accesses); 1904 AccessUSet = isl_union_set_coalesce(AccessUSet); 1905 AccessUSet = isl_union_set_detect_equalities(AccessUSet); 1906 AccessUSet = isl_union_set_coalesce(AccessUSet); 1907 1908 if (isl_union_set_is_empty(AccessUSet)) { 1909 isl_union_set_free(AccessUSet); 1910 return isl_set_empty(Array->getSpace()); 1911 } 1912 1913 if (Array->getNumberOfDimensions() == 0) { 1914 isl_union_set_free(AccessUSet); 1915 return isl_set_universe(Array->getSpace()); 1916 } 1917 1918 isl_set *AccessSet = 1919 isl_union_set_extract_set(AccessUSet, Array->getSpace()); 1920 1921 isl_union_set_free(AccessUSet); 1922 isl_local_space *LS = isl_local_space_from_space(Array->getSpace()); 1923 1924 isl_pw_aff *Val = 1925 isl_pw_aff_from_aff(isl_aff_var_on_domain(LS, isl_dim_set, 0)); 1926 1927 isl_pw_aff *OuterMin = isl_set_dim_min(isl_set_copy(AccessSet), 0); 1928 isl_pw_aff *OuterMax = isl_set_dim_max(AccessSet, 0); 1929 OuterMin = isl_pw_aff_add_dims(OuterMin, isl_dim_in, 1930 isl_pw_aff_dim(Val, isl_dim_in)); 1931 OuterMax = isl_pw_aff_add_dims(OuterMax, isl_dim_in, 1932 isl_pw_aff_dim(Val, isl_dim_in)); 1933 OuterMin = 1934 isl_pw_aff_set_tuple_id(OuterMin, isl_dim_in, Array->getBasePtrId()); 1935 OuterMax = 1936 isl_pw_aff_set_tuple_id(OuterMax, isl_dim_in, Array->getBasePtrId()); 1937 1938 isl_set *Extent = isl_set_universe(Array->getSpace()); 1939 1940 Extent = isl_set_intersect( 1941 Extent, isl_pw_aff_le_set(OuterMin, isl_pw_aff_copy(Val))); 1942 Extent = isl_set_intersect(Extent, isl_pw_aff_ge_set(OuterMax, Val)); 1943 1944 for (unsigned i = 1; i < NumDims; ++i) 1945 Extent = isl_set_lower_bound_si(Extent, isl_dim_set, i, 0); 1946 1947 for (unsigned i = 1; i < NumDims; ++i) { 1948 isl_pw_aff *PwAff = 1949 const_cast<isl_pw_aff *>(Array->getDimensionSizePw(i)); 1950 isl_pw_aff *Val = isl_pw_aff_from_aff(isl_aff_var_on_domain( 1951 isl_local_space_from_space(Array->getSpace()), isl_dim_set, i)); 1952 PwAff = isl_pw_aff_add_dims(PwAff, isl_dim_in, 1953 isl_pw_aff_dim(Val, isl_dim_in)); 1954 PwAff = isl_pw_aff_set_tuple_id(PwAff, isl_dim_in, 1955 isl_pw_aff_get_tuple_id(Val, isl_dim_in)); 1956 auto *Set = isl_pw_aff_gt_set(PwAff, Val); 1957 Extent = isl_set_intersect(Set, Extent); 1958 } 1959 1960 return Extent; 1961 } 1962 1963 /// Derive the bounds of an array. 1964 /// 1965 /// For the first dimension we derive the bound of the array from the extent 1966 /// of this dimension. For inner dimensions we obtain their size directly from 1967 /// ScopArrayInfo. 1968 /// 1969 /// @param PPCGArray The array to compute bounds for. 1970 /// @param Array The polly array from which to take the information. 1971 void setArrayBounds(gpu_array_info &PPCGArray, ScopArrayInfo *Array) { 1972 if (PPCGArray.n_index > 0) { 1973 if (isl_set_is_empty(PPCGArray.extent)) { 1974 isl_set *Dom = isl_set_copy(PPCGArray.extent); 1975 isl_local_space *LS = isl_local_space_from_space( 1976 isl_space_params(isl_set_get_space(Dom))); 1977 isl_set_free(Dom); 1978 isl_aff *Zero = isl_aff_zero_on_domain(LS); 1979 PPCGArray.bound[0] = isl_pw_aff_from_aff(Zero); 1980 } else { 1981 isl_set *Dom = isl_set_copy(PPCGArray.extent); 1982 Dom = isl_set_project_out(Dom, isl_dim_set, 1, PPCGArray.n_index - 1); 1983 isl_pw_aff *Bound = isl_set_dim_max(isl_set_copy(Dom), 0); 1984 isl_set_free(Dom); 1985 Dom = isl_pw_aff_domain(isl_pw_aff_copy(Bound)); 1986 isl_local_space *LS = 1987 isl_local_space_from_space(isl_set_get_space(Dom)); 1988 isl_aff *One = isl_aff_zero_on_domain(LS); 1989 One = isl_aff_add_constant_si(One, 1); 1990 Bound = isl_pw_aff_add(Bound, isl_pw_aff_alloc(Dom, One)); 1991 Bound = isl_pw_aff_gist(Bound, S->getContext()); 1992 PPCGArray.bound[0] = Bound; 1993 } 1994 } 1995 1996 for (unsigned i = 1; i < PPCGArray.n_index; ++i) { 1997 isl_pw_aff *Bound = Array->getDimensionSizePw(i); 1998 auto LS = isl_pw_aff_get_domain_space(Bound); 1999 auto Aff = isl_multi_aff_zero(LS); 2000 Bound = isl_pw_aff_pullback_multi_aff(Bound, Aff); 2001 PPCGArray.bound[i] = Bound; 2002 } 2003 } 2004 2005 /// Create the arrays for @p PPCGProg. 2006 /// 2007 /// @param PPCGProg The program to compute the arrays for. 2008 void createArrays(gpu_prog *PPCGProg) { 2009 int i = 0; 2010 for (auto &Array : S->arrays()) { 2011 std::string TypeName; 2012 raw_string_ostream OS(TypeName); 2013 2014 OS << *Array->getElementType(); 2015 TypeName = OS.str(); 2016 2017 gpu_array_info &PPCGArray = PPCGProg->array[i]; 2018 2019 PPCGArray.space = Array->getSpace(); 2020 PPCGArray.type = strdup(TypeName.c_str()); 2021 PPCGArray.size = Array->getElementType()->getPrimitiveSizeInBits() / 8; 2022 PPCGArray.name = strdup(Array->getName().c_str()); 2023 PPCGArray.extent = nullptr; 2024 PPCGArray.n_index = Array->getNumberOfDimensions(); 2025 PPCGArray.bound = 2026 isl_alloc_array(S->getIslCtx(), isl_pw_aff *, PPCGArray.n_index); 2027 PPCGArray.extent = getExtent(Array); 2028 PPCGArray.n_ref = 0; 2029 PPCGArray.refs = nullptr; 2030 PPCGArray.accessed = true; 2031 PPCGArray.read_only_scalar = 2032 Array->isReadOnly() && Array->getNumberOfDimensions() == 0; 2033 PPCGArray.has_compound_element = false; 2034 PPCGArray.local = false; 2035 PPCGArray.declare_local = false; 2036 PPCGArray.global = false; 2037 PPCGArray.linearize = false; 2038 PPCGArray.dep_order = nullptr; 2039 PPCGArray.user = Array; 2040 2041 setArrayBounds(PPCGArray, Array); 2042 i++; 2043 2044 collect_references(PPCGProg, &PPCGArray); 2045 } 2046 } 2047 2048 /// Create an identity map between the arrays in the scop. 2049 /// 2050 /// @returns An identity map between the arrays in the scop. 2051 isl_union_map *getArrayIdentity() { 2052 isl_union_map *Maps = isl_union_map_empty(S->getParamSpace()); 2053 2054 for (auto &Array : S->arrays()) { 2055 isl_space *Space = Array->getSpace(); 2056 Space = isl_space_map_from_set(Space); 2057 isl_map *Identity = isl_map_identity(Space); 2058 Maps = isl_union_map_add_map(Maps, Identity); 2059 } 2060 2061 return Maps; 2062 } 2063 2064 /// Create a default-initialized PPCG GPU program. 2065 /// 2066 /// @returns A new gpu grogram description. 2067 gpu_prog *createPPCGProg(ppcg_scop *PPCGScop) { 2068 2069 if (!PPCGScop) 2070 return nullptr; 2071 2072 auto PPCGProg = isl_calloc_type(S->getIslCtx(), struct gpu_prog); 2073 2074 PPCGProg->ctx = S->getIslCtx(); 2075 PPCGProg->scop = PPCGScop; 2076 PPCGProg->context = isl_set_copy(PPCGScop->context); 2077 PPCGProg->read = isl_union_map_copy(PPCGScop->reads); 2078 PPCGProg->may_write = isl_union_map_copy(PPCGScop->may_writes); 2079 PPCGProg->must_write = isl_union_map_copy(PPCGScop->must_writes); 2080 PPCGProg->tagged_must_kill = 2081 isl_union_map_copy(PPCGScop->tagged_must_kills); 2082 PPCGProg->to_inner = getArrayIdentity(); 2083 PPCGProg->to_outer = getArrayIdentity(); 2084 PPCGProg->any_to_outer = nullptr; 2085 PPCGProg->array_order = nullptr; 2086 PPCGProg->n_stmts = std::distance(S->begin(), S->end()); 2087 PPCGProg->stmts = getStatements(); 2088 PPCGProg->n_array = std::distance(S->array_begin(), S->array_end()); 2089 PPCGProg->array = isl_calloc_array(S->getIslCtx(), struct gpu_array_info, 2090 PPCGProg->n_array); 2091 2092 createArrays(PPCGProg); 2093 2094 PPCGProg->may_persist = compute_may_persist(PPCGProg); 2095 2096 return PPCGProg; 2097 } 2098 2099 struct PrintGPUUserData { 2100 struct cuda_info *CudaInfo; 2101 struct gpu_prog *PPCGProg; 2102 std::vector<ppcg_kernel *> Kernels; 2103 }; 2104 2105 /// Print a user statement node in the host code. 2106 /// 2107 /// We use ppcg's printing facilities to print the actual statement and 2108 /// additionally build up a list of all kernels that are encountered in the 2109 /// host ast. 2110 /// 2111 /// @param P The printer to print to 2112 /// @param Options The printing options to use 2113 /// @param Node The node to print 2114 /// @param User A user pointer to carry additional data. This pointer is 2115 /// expected to be of type PrintGPUUserData. 2116 /// 2117 /// @returns A printer to which the output has been printed. 2118 static __isl_give isl_printer * 2119 printHostUser(__isl_take isl_printer *P, 2120 __isl_take isl_ast_print_options *Options, 2121 __isl_take isl_ast_node *Node, void *User) { 2122 auto Data = (struct PrintGPUUserData *)User; 2123 auto Id = isl_ast_node_get_annotation(Node); 2124 2125 if (Id) { 2126 bool IsUser = !strcmp(isl_id_get_name(Id), "user"); 2127 2128 // If this is a user statement, format it ourselves as ppcg would 2129 // otherwise try to call pet functionality that is not available in 2130 // Polly. 2131 if (IsUser) { 2132 P = isl_printer_start_line(P); 2133 P = isl_printer_print_ast_node(P, Node); 2134 P = isl_printer_end_line(P); 2135 isl_id_free(Id); 2136 isl_ast_print_options_free(Options); 2137 return P; 2138 } 2139 2140 auto Kernel = (struct ppcg_kernel *)isl_id_get_user(Id); 2141 isl_id_free(Id); 2142 Data->Kernels.push_back(Kernel); 2143 } 2144 2145 return print_host_user(P, Options, Node, User); 2146 } 2147 2148 /// Print C code corresponding to the control flow in @p Kernel. 2149 /// 2150 /// @param Kernel The kernel to print 2151 void printKernel(ppcg_kernel *Kernel) { 2152 auto *P = isl_printer_to_str(S->getIslCtx()); 2153 P = isl_printer_set_output_format(P, ISL_FORMAT_C); 2154 auto *Options = isl_ast_print_options_alloc(S->getIslCtx()); 2155 P = isl_ast_node_print(Kernel->tree, P, Options); 2156 char *String = isl_printer_get_str(P); 2157 printf("%s\n", String); 2158 free(String); 2159 isl_printer_free(P); 2160 } 2161 2162 /// Print C code corresponding to the GPU code described by @p Tree. 2163 /// 2164 /// @param Tree An AST describing GPU code 2165 /// @param PPCGProg The PPCG program from which @Tree has been constructed. 2166 void printGPUTree(isl_ast_node *Tree, gpu_prog *PPCGProg) { 2167 auto *P = isl_printer_to_str(S->getIslCtx()); 2168 P = isl_printer_set_output_format(P, ISL_FORMAT_C); 2169 2170 PrintGPUUserData Data; 2171 Data.PPCGProg = PPCGProg; 2172 2173 auto *Options = isl_ast_print_options_alloc(S->getIslCtx()); 2174 Options = 2175 isl_ast_print_options_set_print_user(Options, printHostUser, &Data); 2176 P = isl_ast_node_print(Tree, P, Options); 2177 char *String = isl_printer_get_str(P); 2178 printf("# host\n"); 2179 printf("%s\n", String); 2180 free(String); 2181 isl_printer_free(P); 2182 2183 for (auto Kernel : Data.Kernels) { 2184 printf("# kernel%d\n", Kernel->id); 2185 printKernel(Kernel); 2186 } 2187 } 2188 2189 // Generate a GPU program using PPCG. 2190 // 2191 // GPU mapping consists of multiple steps: 2192 // 2193 // 1) Compute new schedule for the program. 2194 // 2) Map schedule to GPU (TODO) 2195 // 3) Generate code for new schedule (TODO) 2196 // 2197 // We do not use here the Polly ScheduleOptimizer, as the schedule optimizer 2198 // is mostly CPU specific. Instead, we use PPCG's GPU code generation 2199 // strategy directly from this pass. 2200 gpu_gen *generateGPU(ppcg_scop *PPCGScop, gpu_prog *PPCGProg) { 2201 2202 auto PPCGGen = isl_calloc_type(S->getIslCtx(), struct gpu_gen); 2203 2204 PPCGGen->ctx = S->getIslCtx(); 2205 PPCGGen->options = PPCGScop->options; 2206 PPCGGen->print = nullptr; 2207 PPCGGen->print_user = nullptr; 2208 PPCGGen->build_ast_expr = &pollyBuildAstExprForStmt; 2209 PPCGGen->prog = PPCGProg; 2210 PPCGGen->tree = nullptr; 2211 PPCGGen->types.n = 0; 2212 PPCGGen->types.name = nullptr; 2213 PPCGGen->sizes = nullptr; 2214 PPCGGen->used_sizes = nullptr; 2215 PPCGGen->kernel_id = 0; 2216 2217 // Set scheduling strategy to same strategy PPCG is using. 2218 isl_options_set_schedule_outer_coincidence(PPCGGen->ctx, true); 2219 isl_options_set_schedule_maximize_band_depth(PPCGGen->ctx, true); 2220 isl_options_set_schedule_whole_component(PPCGGen->ctx, false); 2221 2222 isl_schedule *Schedule = get_schedule(PPCGGen); 2223 2224 int has_permutable = has_any_permutable_node(Schedule); 2225 2226 if (!has_permutable || has_permutable < 0) { 2227 Schedule = isl_schedule_free(Schedule); 2228 } else { 2229 Schedule = map_to_device(PPCGGen, Schedule); 2230 PPCGGen->tree = generate_code(PPCGGen, isl_schedule_copy(Schedule)); 2231 } 2232 2233 if (DumpSchedule) { 2234 isl_printer *P = isl_printer_to_str(S->getIslCtx()); 2235 P = isl_printer_set_yaml_style(P, ISL_YAML_STYLE_BLOCK); 2236 P = isl_printer_print_str(P, "Schedule\n"); 2237 P = isl_printer_print_str(P, "========\n"); 2238 if (Schedule) 2239 P = isl_printer_print_schedule(P, Schedule); 2240 else 2241 P = isl_printer_print_str(P, "No schedule found\n"); 2242 2243 printf("%s\n", isl_printer_get_str(P)); 2244 isl_printer_free(P); 2245 } 2246 2247 if (DumpCode) { 2248 printf("Code\n"); 2249 printf("====\n"); 2250 if (PPCGGen->tree) 2251 printGPUTree(PPCGGen->tree, PPCGProg); 2252 else 2253 printf("No code generated\n"); 2254 } 2255 2256 isl_schedule_free(Schedule); 2257 2258 return PPCGGen; 2259 } 2260 2261 /// Free gpu_gen structure. 2262 /// 2263 /// @param PPCGGen The ppcg_gen object to free. 2264 void freePPCGGen(gpu_gen *PPCGGen) { 2265 isl_ast_node_free(PPCGGen->tree); 2266 isl_union_map_free(PPCGGen->sizes); 2267 isl_union_map_free(PPCGGen->used_sizes); 2268 free(PPCGGen); 2269 } 2270 2271 /// Free the options in the ppcg scop structure. 2272 /// 2273 /// ppcg is not freeing these options for us. To avoid leaks we do this 2274 /// ourselves. 2275 /// 2276 /// @param PPCGScop The scop referencing the options to free. 2277 void freeOptions(ppcg_scop *PPCGScop) { 2278 free(PPCGScop->options->debug); 2279 PPCGScop->options->debug = nullptr; 2280 free(PPCGScop->options); 2281 PPCGScop->options = nullptr; 2282 } 2283 2284 /// Approximate the number of points in the set. 2285 /// 2286 /// This function returns an ast expression that overapproximates the number 2287 /// of points in an isl set through the rectangular hull surrounding this set. 2288 /// 2289 /// @param Set The set to count. 2290 /// @param Build The isl ast build object to use for creating the ast 2291 /// expression. 2292 /// 2293 /// @returns An approximation of the number of points in the set. 2294 __isl_give isl_ast_expr *approxPointsInSet(__isl_take isl_set *Set, 2295 __isl_keep isl_ast_build *Build) { 2296 2297 isl_val *One = isl_val_int_from_si(isl_set_get_ctx(Set), 1); 2298 auto *Expr = isl_ast_expr_from_val(isl_val_copy(One)); 2299 2300 isl_space *Space = isl_set_get_space(Set); 2301 Space = isl_space_params(Space); 2302 auto *Univ = isl_set_universe(Space); 2303 isl_pw_aff *OneAff = isl_pw_aff_val_on_domain(Univ, One); 2304 2305 for (long i = 0; i < isl_set_dim(Set, isl_dim_set); i++) { 2306 isl_pw_aff *Max = isl_set_dim_max(isl_set_copy(Set), i); 2307 isl_pw_aff *Min = isl_set_dim_min(isl_set_copy(Set), i); 2308 isl_pw_aff *DimSize = isl_pw_aff_sub(Max, Min); 2309 DimSize = isl_pw_aff_add(DimSize, isl_pw_aff_copy(OneAff)); 2310 auto DimSizeExpr = isl_ast_build_expr_from_pw_aff(Build, DimSize); 2311 Expr = isl_ast_expr_mul(Expr, DimSizeExpr); 2312 } 2313 2314 isl_set_free(Set); 2315 isl_pw_aff_free(OneAff); 2316 2317 return Expr; 2318 } 2319 2320 /// Approximate a number of dynamic instructions executed by a given 2321 /// statement. 2322 /// 2323 /// @param Stmt The statement for which to compute the number of dynamic 2324 /// instructions. 2325 /// @param Build The isl ast build object to use for creating the ast 2326 /// expression. 2327 /// @returns An approximation of the number of dynamic instructions executed 2328 /// by @p Stmt. 2329 __isl_give isl_ast_expr *approxDynamicInst(ScopStmt &Stmt, 2330 __isl_keep isl_ast_build *Build) { 2331 auto Iterations = approxPointsInSet(Stmt.getDomain(), Build); 2332 2333 long InstCount = 0; 2334 2335 if (Stmt.isBlockStmt()) { 2336 auto *BB = Stmt.getBasicBlock(); 2337 InstCount = std::distance(BB->begin(), BB->end()); 2338 } else { 2339 auto *R = Stmt.getRegion(); 2340 2341 for (auto *BB : R->blocks()) { 2342 InstCount += std::distance(BB->begin(), BB->end()); 2343 } 2344 } 2345 2346 isl_val *InstVal = isl_val_int_from_si(S->getIslCtx(), InstCount); 2347 auto *InstExpr = isl_ast_expr_from_val(InstVal); 2348 return isl_ast_expr_mul(InstExpr, Iterations); 2349 } 2350 2351 /// Approximate dynamic instructions executed in scop. 2352 /// 2353 /// @param S The scop for which to approximate dynamic instructions. 2354 /// @param Build The isl ast build object to use for creating the ast 2355 /// expression. 2356 /// @returns An approximation of the number of dynamic instructions executed 2357 /// in @p S. 2358 __isl_give isl_ast_expr * 2359 getNumberOfIterations(Scop &S, __isl_keep isl_ast_build *Build) { 2360 isl_ast_expr *Instructions; 2361 2362 isl_val *Zero = isl_val_int_from_si(S.getIslCtx(), 0); 2363 Instructions = isl_ast_expr_from_val(Zero); 2364 2365 for (ScopStmt &Stmt : S) { 2366 isl_ast_expr *StmtInstructions = approxDynamicInst(Stmt, Build); 2367 Instructions = isl_ast_expr_add(Instructions, StmtInstructions); 2368 } 2369 return Instructions; 2370 } 2371 2372 /// Create a check that ensures sufficient compute in scop. 2373 /// 2374 /// @param S The scop for which to ensure sufficient compute. 2375 /// @param Build The isl ast build object to use for creating the ast 2376 /// expression. 2377 /// @returns An expression that evaluates to TRUE in case of sufficient 2378 /// compute and to FALSE, otherwise. 2379 __isl_give isl_ast_expr * 2380 createSufficientComputeCheck(Scop &S, __isl_keep isl_ast_build *Build) { 2381 auto Iterations = getNumberOfIterations(S, Build); 2382 auto *MinComputeVal = isl_val_int_from_si(S.getIslCtx(), MinCompute); 2383 auto *MinComputeExpr = isl_ast_expr_from_val(MinComputeVal); 2384 return isl_ast_expr_ge(Iterations, MinComputeExpr); 2385 } 2386 2387 /// Generate code for a given GPU AST described by @p Root. 2388 /// 2389 /// @param Root An isl_ast_node pointing to the root of the GPU AST. 2390 /// @param Prog The GPU Program to generate code for. 2391 void generateCode(__isl_take isl_ast_node *Root, gpu_prog *Prog) { 2392 ScopAnnotator Annotator; 2393 Annotator.buildAliasScopes(*S); 2394 2395 Region *R = &S->getRegion(); 2396 2397 simplifyRegion(R, DT, LI, RI); 2398 2399 BasicBlock *EnteringBB = R->getEnteringBlock(); 2400 2401 PollyIRBuilder Builder = createPollyIRBuilder(EnteringBB, Annotator); 2402 2403 // Only build the run-time condition and parameters _after_ having 2404 // introduced the conditional branch. This is important as the conditional 2405 // branch will guard the original scop from new induction variables that 2406 // the SCEVExpander may introduce while code generating the parameters and 2407 // which may introduce scalar dependences that prevent us from correctly 2408 // code generating this scop. 2409 BasicBlock *StartBlock = 2410 executeScopConditionally(*S, this, Builder.getTrue()); 2411 2412 GPUNodeBuilder NodeBuilder(Builder, Annotator, this, *DL, *LI, *SE, *DT, *S, 2413 StartBlock, Prog); 2414 2415 // TODO: Handle LICM 2416 auto SplitBlock = StartBlock->getSinglePredecessor(); 2417 Builder.SetInsertPoint(SplitBlock->getTerminator()); 2418 NodeBuilder.addParameters(S->getContext()); 2419 2420 isl_ast_build *Build = isl_ast_build_alloc(S->getIslCtx()); 2421 isl_ast_expr *Condition = IslAst::buildRunCondition(S, Build); 2422 isl_ast_expr *SufficientCompute = createSufficientComputeCheck(*S, Build); 2423 Condition = isl_ast_expr_and(Condition, SufficientCompute); 2424 isl_ast_build_free(Build); 2425 2426 Value *RTC = NodeBuilder.createRTC(Condition); 2427 Builder.GetInsertBlock()->getTerminator()->setOperand(0, RTC); 2428 2429 Builder.SetInsertPoint(&*StartBlock->begin()); 2430 2431 NodeBuilder.initializeAfterRTH(); 2432 NodeBuilder.create(Root); 2433 NodeBuilder.finalize(); 2434 2435 /// In case a sequential kernel has more surrounding loops as any parallel 2436 /// kernel, the SCoP is probably mostly sequential. Hence, there is no 2437 /// point in running it on a CPU. 2438 if (NodeBuilder.DeepestSequential > NodeBuilder.DeepestParallel) 2439 SplitBlock->getTerminator()->setOperand(0, Builder.getFalse()); 2440 2441 if (!NodeBuilder.BuildSuccessful) 2442 SplitBlock->getTerminator()->setOperand(0, Builder.getFalse()); 2443 } 2444 2445 bool runOnScop(Scop &CurrentScop) override { 2446 S = &CurrentScop; 2447 LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 2448 DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 2449 SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 2450 DL = &S->getRegion().getEntry()->getParent()->getParent()->getDataLayout(); 2451 RI = &getAnalysis<RegionInfoPass>().getRegionInfo(); 2452 2453 // We currently do not support scops with invariant loads. 2454 if (S->hasInvariantAccesses()) 2455 return false; 2456 2457 auto PPCGScop = createPPCGScop(); 2458 auto PPCGProg = createPPCGProg(PPCGScop); 2459 auto PPCGGen = generateGPU(PPCGScop, PPCGProg); 2460 2461 if (PPCGGen->tree) 2462 generateCode(isl_ast_node_copy(PPCGGen->tree), PPCGProg); 2463 2464 freeOptions(PPCGScop); 2465 freePPCGGen(PPCGGen); 2466 gpu_prog_free(PPCGProg); 2467 ppcg_scop_free(PPCGScop); 2468 2469 return true; 2470 } 2471 2472 void printScop(raw_ostream &, Scop &) const override {} 2473 2474 void getAnalysisUsage(AnalysisUsage &AU) const override { 2475 AU.addRequired<DominatorTreeWrapperPass>(); 2476 AU.addRequired<RegionInfoPass>(); 2477 AU.addRequired<ScalarEvolutionWrapperPass>(); 2478 AU.addRequired<ScopDetection>(); 2479 AU.addRequired<ScopInfoRegionPass>(); 2480 AU.addRequired<LoopInfoWrapperPass>(); 2481 2482 AU.addPreserved<AAResultsWrapperPass>(); 2483 AU.addPreserved<BasicAAWrapperPass>(); 2484 AU.addPreserved<LoopInfoWrapperPass>(); 2485 AU.addPreserved<DominatorTreeWrapperPass>(); 2486 AU.addPreserved<GlobalsAAWrapperPass>(); 2487 AU.addPreserved<PostDominatorTreeWrapperPass>(); 2488 AU.addPreserved<ScopDetection>(); 2489 AU.addPreserved<ScalarEvolutionWrapperPass>(); 2490 AU.addPreserved<SCEVAAWrapperPass>(); 2491 2492 // FIXME: We do not yet add regions for the newly generated code to the 2493 // region tree. 2494 AU.addPreserved<RegionInfoPass>(); 2495 AU.addPreserved<ScopInfoRegionPass>(); 2496 } 2497 }; 2498 } 2499 2500 char PPCGCodeGeneration::ID = 1; 2501 2502 Pass *polly::createPPCGCodeGenerationPass() { return new PPCGCodeGeneration(); } 2503 2504 INITIALIZE_PASS_BEGIN(PPCGCodeGeneration, "polly-codegen-ppcg", 2505 "Polly - Apply PPCG translation to SCOP", false, false) 2506 INITIALIZE_PASS_DEPENDENCY(DependenceInfo); 2507 INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass); 2508 INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass); 2509 INITIALIZE_PASS_DEPENDENCY(RegionInfoPass); 2510 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass); 2511 INITIALIZE_PASS_DEPENDENCY(ScopDetection); 2512 INITIALIZE_PASS_END(PPCGCodeGeneration, "polly-codegen-ppcg", 2513 "Polly - Apply PPCG translation to SCOP", false, false) 2514