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, 607 {GPUKernel, GridDimX, GridDimY, BlockDimX, BlockDimY, 608 BlockDimZ, Parameters}); 609 } 610 611 void GPUNodeBuilder::createCallFreeKernel(Value *GPUKernel) { 612 const char *Name = "polly_freeKernel"; 613 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 614 Function *F = M->getFunction(Name); 615 616 // If F is not available, declare it. 617 if (!F) { 618 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 619 std::vector<Type *> Args; 620 Args.push_back(Builder.getInt8PtrTy()); 621 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 622 F = Function::Create(Ty, Linkage, Name, M); 623 } 624 625 Builder.CreateCall(F, {GPUKernel}); 626 } 627 628 void GPUNodeBuilder::createCallFreeDeviceMemory(Value *Array) { 629 const char *Name = "polly_freeDeviceMemory"; 630 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 631 Function *F = M->getFunction(Name); 632 633 // If F is not available, declare it. 634 if (!F) { 635 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 636 std::vector<Type *> Args; 637 Args.push_back(Builder.getInt8PtrTy()); 638 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 639 F = Function::Create(Ty, Linkage, Name, M); 640 } 641 642 Builder.CreateCall(F, {Array}); 643 } 644 645 Value *GPUNodeBuilder::createCallAllocateMemoryForDevice(Value *Size) { 646 const char *Name = "polly_allocateMemoryForDevice"; 647 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 648 Function *F = M->getFunction(Name); 649 650 // If F is not available, declare it. 651 if (!F) { 652 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 653 std::vector<Type *> Args; 654 Args.push_back(Builder.getInt64Ty()); 655 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 656 F = Function::Create(Ty, Linkage, Name, M); 657 } 658 659 return Builder.CreateCall(F, {Size}); 660 } 661 662 void GPUNodeBuilder::createCallCopyFromHostToDevice(Value *HostData, 663 Value *DeviceData, 664 Value *Size) { 665 const char *Name = "polly_copyFromHostToDevice"; 666 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 667 Function *F = M->getFunction(Name); 668 669 // If F is not available, declare it. 670 if (!F) { 671 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 672 std::vector<Type *> Args; 673 Args.push_back(Builder.getInt8PtrTy()); 674 Args.push_back(Builder.getInt8PtrTy()); 675 Args.push_back(Builder.getInt64Ty()); 676 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 677 F = Function::Create(Ty, Linkage, Name, M); 678 } 679 680 Builder.CreateCall(F, {HostData, DeviceData, Size}); 681 } 682 683 void GPUNodeBuilder::createCallCopyFromDeviceToHost(Value *DeviceData, 684 Value *HostData, 685 Value *Size) { 686 const char *Name = "polly_copyFromDeviceToHost"; 687 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 688 Function *F = M->getFunction(Name); 689 690 // If F is not available, declare it. 691 if (!F) { 692 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 693 std::vector<Type *> Args; 694 Args.push_back(Builder.getInt8PtrTy()); 695 Args.push_back(Builder.getInt8PtrTy()); 696 Args.push_back(Builder.getInt64Ty()); 697 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 698 F = Function::Create(Ty, Linkage, Name, M); 699 } 700 701 Builder.CreateCall(F, {DeviceData, HostData, Size}); 702 } 703 704 Value *GPUNodeBuilder::createCallInitContext() { 705 const char *Name = "polly_initContext"; 706 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 707 Function *F = M->getFunction(Name); 708 709 // If F is not available, declare it. 710 if (!F) { 711 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 712 std::vector<Type *> Args; 713 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 714 F = Function::Create(Ty, Linkage, Name, M); 715 } 716 717 return Builder.CreateCall(F, {}); 718 } 719 720 void GPUNodeBuilder::createCallFreeContext(Value *Context) { 721 const char *Name = "polly_freeContext"; 722 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 723 Function *F = M->getFunction(Name); 724 725 // If F is not available, declare it. 726 if (!F) { 727 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 728 std::vector<Type *> Args; 729 Args.push_back(Builder.getInt8PtrTy()); 730 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 731 F = Function::Create(Ty, Linkage, Name, M); 732 } 733 734 Builder.CreateCall(F, {Context}); 735 } 736 737 /// Check if one string is a prefix of another. 738 /// 739 /// @param String The string in which to look for the prefix. 740 /// @param Prefix The prefix to look for. 741 static bool isPrefix(std::string String, std::string Prefix) { 742 return String.find(Prefix) == 0; 743 } 744 745 Value *GPUNodeBuilder::getArraySize(gpu_array_info *Array) { 746 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 747 Value *ArraySize = ConstantInt::get(Builder.getInt64Ty(), Array->size); 748 749 if (!gpu_array_is_scalar(Array)) { 750 auto OffsetDimZero = isl_pw_aff_copy(Array->bound[0]); 751 isl_ast_expr *Res = isl_ast_build_expr_from_pw_aff(Build, OffsetDimZero); 752 753 for (unsigned int i = 1; i < Array->n_index; i++) { 754 isl_pw_aff *Bound_I = isl_pw_aff_copy(Array->bound[i]); 755 isl_ast_expr *Expr = isl_ast_build_expr_from_pw_aff(Build, Bound_I); 756 Res = isl_ast_expr_mul(Res, Expr); 757 } 758 759 Value *NumElements = ExprBuilder.create(Res); 760 if (NumElements->getType() != ArraySize->getType()) 761 NumElements = Builder.CreateSExt(NumElements, ArraySize->getType()); 762 ArraySize = Builder.CreateMul(ArraySize, NumElements); 763 } 764 isl_ast_build_free(Build); 765 return ArraySize; 766 } 767 768 Value *GPUNodeBuilder::getArrayOffset(gpu_array_info *Array) { 769 if (gpu_array_is_scalar(Array)) 770 return nullptr; 771 772 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 773 774 isl_set *Min = isl_set_lexmin(isl_set_copy(Array->extent)); 775 776 isl_set *ZeroSet = isl_set_universe(isl_set_get_space(Min)); 777 778 for (long i = 0; i < isl_set_dim(Min, isl_dim_set); i++) 779 ZeroSet = isl_set_fix_si(ZeroSet, isl_dim_set, i, 0); 780 781 if (isl_set_is_subset(Min, ZeroSet)) { 782 isl_set_free(Min); 783 isl_set_free(ZeroSet); 784 isl_ast_build_free(Build); 785 return nullptr; 786 } 787 isl_set_free(ZeroSet); 788 789 isl_ast_expr *Result = 790 isl_ast_expr_from_val(isl_val_int_from_si(isl_set_get_ctx(Min), 0)); 791 792 for (long i = 0; i < isl_set_dim(Min, isl_dim_set); i++) { 793 if (i > 0) { 794 isl_pw_aff *Bound_I = isl_pw_aff_copy(Array->bound[i - 1]); 795 isl_ast_expr *BExpr = isl_ast_build_expr_from_pw_aff(Build, Bound_I); 796 Result = isl_ast_expr_mul(Result, BExpr); 797 } 798 isl_pw_aff *DimMin = isl_set_dim_min(isl_set_copy(Min), i); 799 isl_ast_expr *MExpr = isl_ast_build_expr_from_pw_aff(Build, DimMin); 800 Result = isl_ast_expr_add(Result, MExpr); 801 } 802 803 Value *ResultValue = ExprBuilder.create(Result); 804 isl_set_free(Min); 805 isl_ast_build_free(Build); 806 807 return ResultValue; 808 } 809 810 void GPUNodeBuilder::createDataTransfer(__isl_take isl_ast_node *TransferStmt, 811 enum DataDirection Direction) { 812 isl_ast_expr *Expr = isl_ast_node_user_get_expr(TransferStmt); 813 isl_ast_expr *Arg = isl_ast_expr_get_op_arg(Expr, 0); 814 isl_id *Id = isl_ast_expr_get_id(Arg); 815 auto Array = (gpu_array_info *)isl_id_get_user(Id); 816 auto ScopArray = (ScopArrayInfo *)(Array->user); 817 818 Value *Size = getArraySize(Array); 819 Value *Offset = getArrayOffset(Array); 820 Value *DevPtr = DeviceAllocations[ScopArray]; 821 822 Value *HostPtr; 823 824 if (gpu_array_is_scalar(Array)) 825 HostPtr = BlockGen.getOrCreateAlloca(ScopArray); 826 else 827 HostPtr = ScopArray->getBasePtr(); 828 829 if (Offset) { 830 HostPtr = Builder.CreatePointerCast( 831 HostPtr, ScopArray->getElementType()->getPointerTo()); 832 HostPtr = Builder.CreateGEP(HostPtr, Offset); 833 } 834 835 HostPtr = Builder.CreatePointerCast(HostPtr, Builder.getInt8PtrTy()); 836 837 if (Offset) { 838 Size = Builder.CreateSub( 839 Size, 840 Builder.CreateMul(Offset, 841 Builder.getInt64(ScopArray->getElemSizeInBytes()))); 842 } 843 844 if (Direction == HOST_TO_DEVICE) 845 createCallCopyFromHostToDevice(HostPtr, DevPtr, Size); 846 else 847 createCallCopyFromDeviceToHost(DevPtr, HostPtr, Size); 848 849 isl_id_free(Id); 850 isl_ast_expr_free(Arg); 851 isl_ast_expr_free(Expr); 852 isl_ast_node_free(TransferStmt); 853 } 854 855 void GPUNodeBuilder::createUser(__isl_take isl_ast_node *UserStmt) { 856 isl_ast_expr *Expr = isl_ast_node_user_get_expr(UserStmt); 857 isl_ast_expr *StmtExpr = isl_ast_expr_get_op_arg(Expr, 0); 858 isl_id *Id = isl_ast_expr_get_id(StmtExpr); 859 isl_id_free(Id); 860 isl_ast_expr_free(StmtExpr); 861 862 const char *Str = isl_id_get_name(Id); 863 if (!strcmp(Str, "kernel")) { 864 createKernel(UserStmt); 865 isl_ast_expr_free(Expr); 866 return; 867 } 868 869 if (isPrefix(Str, "to_device")) { 870 createDataTransfer(UserStmt, HOST_TO_DEVICE); 871 isl_ast_expr_free(Expr); 872 return; 873 } 874 875 if (isPrefix(Str, "from_device")) { 876 createDataTransfer(UserStmt, DEVICE_TO_HOST); 877 isl_ast_expr_free(Expr); 878 return; 879 } 880 881 isl_id *Anno = isl_ast_node_get_annotation(UserStmt); 882 struct ppcg_kernel_stmt *KernelStmt = 883 (struct ppcg_kernel_stmt *)isl_id_get_user(Anno); 884 isl_id_free(Anno); 885 886 switch (KernelStmt->type) { 887 case ppcg_kernel_domain: 888 createScopStmt(Expr, KernelStmt); 889 isl_ast_node_free(UserStmt); 890 return; 891 case ppcg_kernel_copy: 892 createKernelCopy(KernelStmt); 893 isl_ast_expr_free(Expr); 894 isl_ast_node_free(UserStmt); 895 return; 896 case ppcg_kernel_sync: 897 createKernelSync(); 898 isl_ast_expr_free(Expr); 899 isl_ast_node_free(UserStmt); 900 return; 901 } 902 903 isl_ast_expr_free(Expr); 904 isl_ast_node_free(UserStmt); 905 return; 906 } 907 void GPUNodeBuilder::createKernelCopy(ppcg_kernel_stmt *KernelStmt) { 908 isl_ast_expr *LocalIndex = isl_ast_expr_copy(KernelStmt->u.c.local_index); 909 LocalIndex = isl_ast_expr_address_of(LocalIndex); 910 Value *LocalAddr = ExprBuilder.create(LocalIndex); 911 isl_ast_expr *Index = isl_ast_expr_copy(KernelStmt->u.c.index); 912 Index = isl_ast_expr_address_of(Index); 913 Value *GlobalAddr = ExprBuilder.create(Index); 914 915 if (KernelStmt->u.c.read) { 916 LoadInst *Load = Builder.CreateLoad(GlobalAddr, "shared.read"); 917 Builder.CreateStore(Load, LocalAddr); 918 } else { 919 LoadInst *Load = Builder.CreateLoad(LocalAddr, "shared.write"); 920 Builder.CreateStore(Load, GlobalAddr); 921 } 922 } 923 924 void GPUNodeBuilder::createScopStmt(isl_ast_expr *Expr, 925 ppcg_kernel_stmt *KernelStmt) { 926 auto Stmt = (ScopStmt *)KernelStmt->u.d.stmt->stmt; 927 isl_id_to_ast_expr *Indexes = KernelStmt->u.d.ref2expr; 928 929 LoopToScevMapT LTS; 930 LTS.insert(OutsideLoopIterations.begin(), OutsideLoopIterations.end()); 931 932 createSubstitutions(Expr, Stmt, LTS); 933 934 if (Stmt->isBlockStmt()) 935 BlockGen.copyStmt(*Stmt, LTS, Indexes); 936 else 937 RegionGen.copyStmt(*Stmt, LTS, Indexes); 938 } 939 940 void GPUNodeBuilder::createKernelSync() { 941 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 942 auto *Sync = Intrinsic::getDeclaration(M, Intrinsic::nvvm_barrier0); 943 Builder.CreateCall(Sync, {}); 944 } 945 946 /// Collect llvm::Values referenced from @p Node 947 /// 948 /// This function only applies to isl_ast_nodes that are user_nodes referring 949 /// to a ScopStmt. All other node types are ignore. 950 /// 951 /// @param Node The node to collect references for. 952 /// @param User A user pointer used as storage for the data that is collected. 953 /// 954 /// @returns isl_bool_true if data could be collected successfully. 955 isl_bool collectReferencesInGPUStmt(__isl_keep isl_ast_node *Node, void *User) { 956 if (isl_ast_node_get_type(Node) != isl_ast_node_user) 957 return isl_bool_true; 958 959 isl_ast_expr *Expr = isl_ast_node_user_get_expr(Node); 960 isl_ast_expr *StmtExpr = isl_ast_expr_get_op_arg(Expr, 0); 961 isl_id *Id = isl_ast_expr_get_id(StmtExpr); 962 const char *Str = isl_id_get_name(Id); 963 isl_id_free(Id); 964 isl_ast_expr_free(StmtExpr); 965 isl_ast_expr_free(Expr); 966 967 if (!isPrefix(Str, "Stmt")) 968 return isl_bool_true; 969 970 Id = isl_ast_node_get_annotation(Node); 971 auto *KernelStmt = (ppcg_kernel_stmt *)isl_id_get_user(Id); 972 auto Stmt = (ScopStmt *)KernelStmt->u.d.stmt->stmt; 973 isl_id_free(Id); 974 975 addReferencesFromStmt(Stmt, User, false /* CreateScalarRefs */); 976 977 return isl_bool_true; 978 } 979 980 SetVector<Value *> GPUNodeBuilder::getReferencesInKernel(ppcg_kernel *Kernel) { 981 SetVector<Value *> SubtreeValues; 982 SetVector<const SCEV *> SCEVs; 983 SetVector<const Loop *> Loops; 984 SubtreeReferences References = { 985 LI, SE, S, ValueMap, SubtreeValues, SCEVs, getBlockGenerator()}; 986 987 for (const auto &I : IDToValue) 988 SubtreeValues.insert(I.second); 989 990 isl_ast_node_foreach_descendant_top_down( 991 Kernel->tree, collectReferencesInGPUStmt, &References); 992 993 for (const SCEV *Expr : SCEVs) 994 findValues(Expr, SE, SubtreeValues); 995 996 for (auto &SAI : S.arrays()) 997 SubtreeValues.remove(SAI->getBasePtr()); 998 999 isl_space *Space = S.getParamSpace(); 1000 for (long i = 0; i < isl_space_dim(Space, isl_dim_param); i++) { 1001 isl_id *Id = isl_space_get_dim_id(Space, isl_dim_param, i); 1002 assert(IDToValue.count(Id)); 1003 Value *Val = IDToValue[Id]; 1004 SubtreeValues.remove(Val); 1005 isl_id_free(Id); 1006 } 1007 isl_space_free(Space); 1008 1009 for (long i = 0; i < isl_space_dim(Kernel->space, isl_dim_set); i++) { 1010 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1011 assert(IDToValue.count(Id)); 1012 Value *Val = IDToValue[Id]; 1013 SubtreeValues.remove(Val); 1014 isl_id_free(Id); 1015 } 1016 1017 return SubtreeValues; 1018 } 1019 1020 void GPUNodeBuilder::clearDominators(Function *F) { 1021 DomTreeNode *N = DT.getNode(&F->getEntryBlock()); 1022 std::vector<BasicBlock *> Nodes; 1023 for (po_iterator<DomTreeNode *> I = po_begin(N), E = po_end(N); I != E; ++I) 1024 Nodes.push_back(I->getBlock()); 1025 1026 for (BasicBlock *BB : Nodes) 1027 DT.eraseNode(BB); 1028 } 1029 1030 void GPUNodeBuilder::clearScalarEvolution(Function *F) { 1031 for (BasicBlock &BB : *F) { 1032 Loop *L = LI.getLoopFor(&BB); 1033 if (L) 1034 SE.forgetLoop(L); 1035 } 1036 } 1037 1038 void GPUNodeBuilder::clearLoops(Function *F) { 1039 for (BasicBlock &BB : *F) { 1040 Loop *L = LI.getLoopFor(&BB); 1041 if (L) 1042 SE.forgetLoop(L); 1043 LI.removeBlock(&BB); 1044 } 1045 } 1046 1047 std::tuple<Value *, Value *> GPUNodeBuilder::getGridSizes(ppcg_kernel *Kernel) { 1048 std::vector<Value *> Sizes; 1049 isl_ast_build *Context = isl_ast_build_from_context(S.getContext()); 1050 1051 for (long i = 0; i < Kernel->n_grid; i++) { 1052 isl_pw_aff *Size = isl_multi_pw_aff_get_pw_aff(Kernel->grid_size, i); 1053 isl_ast_expr *GridSize = isl_ast_build_expr_from_pw_aff(Context, Size); 1054 Value *Res = ExprBuilder.create(GridSize); 1055 Res = Builder.CreateTrunc(Res, Builder.getInt32Ty()); 1056 Sizes.push_back(Res); 1057 } 1058 isl_ast_build_free(Context); 1059 1060 for (long i = Kernel->n_grid; i < 3; i++) 1061 Sizes.push_back(ConstantInt::get(Builder.getInt32Ty(), 1)); 1062 1063 return std::make_tuple(Sizes[0], Sizes[1]); 1064 } 1065 1066 std::tuple<Value *, Value *, Value *> 1067 GPUNodeBuilder::getBlockSizes(ppcg_kernel *Kernel) { 1068 std::vector<Value *> Sizes; 1069 1070 for (long i = 0; i < Kernel->n_block; i++) { 1071 Value *Res = ConstantInt::get(Builder.getInt32Ty(), Kernel->block_dim[i]); 1072 Sizes.push_back(Res); 1073 } 1074 1075 for (long i = Kernel->n_block; i < 3; i++) 1076 Sizes.push_back(ConstantInt::get(Builder.getInt32Ty(), 1)); 1077 1078 return std::make_tuple(Sizes[0], Sizes[1], Sizes[2]); 1079 } 1080 1081 Value * 1082 GPUNodeBuilder::createLaunchParameters(ppcg_kernel *Kernel, Function *F, 1083 SetVector<Value *> SubtreeValues) { 1084 Type *ArrayTy = ArrayType::get(Builder.getInt8PtrTy(), 1085 std::distance(F->arg_begin(), F->arg_end())); 1086 1087 BasicBlock *EntryBlock = 1088 &Builder.GetInsertBlock()->getParent()->getEntryBlock(); 1089 std::string Launch = "polly_launch_" + std::to_string(Kernel->id); 1090 Instruction *Parameters = 1091 new AllocaInst(ArrayTy, Launch + "_params", EntryBlock->getTerminator()); 1092 1093 int Index = 0; 1094 for (long i = 0; i < Prog->n_array; i++) { 1095 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1096 continue; 1097 1098 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1099 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(Id); 1100 1101 Value *DevArray = DeviceAllocations[const_cast<ScopArrayInfo *>(SAI)]; 1102 DevArray = createCallGetDevicePtr(DevArray); 1103 1104 Value *Offset = getArrayOffset(&Prog->array[i]); 1105 1106 if (Offset) { 1107 DevArray = Builder.CreatePointerCast( 1108 DevArray, SAI->getElementType()->getPointerTo()); 1109 DevArray = Builder.CreateGEP(DevArray, Builder.CreateNeg(Offset)); 1110 DevArray = Builder.CreatePointerCast(DevArray, Builder.getInt8PtrTy()); 1111 } 1112 Value *Slot = Builder.CreateGEP( 1113 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1114 1115 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1116 Value *ValPtr = BlockGen.getOrCreateAlloca(SAI); 1117 Value *ValPtrCast = 1118 Builder.CreatePointerCast(ValPtr, Builder.getInt8PtrTy()); 1119 Builder.CreateStore(ValPtrCast, Slot); 1120 } else { 1121 Instruction *Param = new AllocaInst( 1122 Builder.getInt8PtrTy(), Launch + "_param_" + std::to_string(Index), 1123 EntryBlock->getTerminator()); 1124 Builder.CreateStore(DevArray, Param); 1125 Value *ParamTyped = 1126 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1127 Builder.CreateStore(ParamTyped, Slot); 1128 } 1129 Index++; 1130 } 1131 1132 int NumHostIters = isl_space_dim(Kernel->space, isl_dim_set); 1133 1134 for (long i = 0; i < NumHostIters; i++) { 1135 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1136 Value *Val = IDToValue[Id]; 1137 isl_id_free(Id); 1138 Instruction *Param = new AllocaInst( 1139 Val->getType(), Launch + "_param_" + std::to_string(Index), 1140 EntryBlock->getTerminator()); 1141 Builder.CreateStore(Val, Param); 1142 Value *Slot = Builder.CreateGEP( 1143 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1144 Value *ParamTyped = 1145 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1146 Builder.CreateStore(ParamTyped, Slot); 1147 Index++; 1148 } 1149 1150 int NumVars = isl_space_dim(Kernel->space, isl_dim_param); 1151 1152 for (long i = 0; i < NumVars; i++) { 1153 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1154 Value *Val = IDToValue[Id]; 1155 isl_id_free(Id); 1156 Instruction *Param = new AllocaInst( 1157 Val->getType(), Launch + "_param_" + std::to_string(Index), 1158 EntryBlock->getTerminator()); 1159 Builder.CreateStore(Val, Param); 1160 Value *Slot = Builder.CreateGEP( 1161 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1162 Value *ParamTyped = 1163 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1164 Builder.CreateStore(ParamTyped, Slot); 1165 Index++; 1166 } 1167 1168 for (auto Val : SubtreeValues) { 1169 Instruction *Param = new AllocaInst( 1170 Val->getType(), Launch + "_param_" + std::to_string(Index), 1171 EntryBlock->getTerminator()); 1172 Builder.CreateStore(Val, Param); 1173 Value *Slot = Builder.CreateGEP( 1174 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1175 Value *ParamTyped = 1176 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1177 Builder.CreateStore(ParamTyped, Slot); 1178 Index++; 1179 } 1180 1181 auto Location = EntryBlock->getTerminator(); 1182 return new BitCastInst(Parameters, Builder.getInt8PtrTy(), 1183 Launch + "_params_i8ptr", Location); 1184 } 1185 1186 void GPUNodeBuilder::createKernel(__isl_take isl_ast_node *KernelStmt) { 1187 isl_id *Id = isl_ast_node_get_annotation(KernelStmt); 1188 ppcg_kernel *Kernel = (ppcg_kernel *)isl_id_get_user(Id); 1189 isl_id_free(Id); 1190 isl_ast_node_free(KernelStmt); 1191 1192 if (Kernel->n_grid > 1) 1193 DeepestParallel = 1194 std::max(DeepestParallel, isl_space_dim(Kernel->space, isl_dim_set)); 1195 else 1196 DeepestSequential = 1197 std::max(DeepestSequential, isl_space_dim(Kernel->space, isl_dim_set)); 1198 1199 Value *BlockDimX, *BlockDimY, *BlockDimZ; 1200 std::tie(BlockDimX, BlockDimY, BlockDimZ) = getBlockSizes(Kernel); 1201 1202 SetVector<Value *> SubtreeValues = getReferencesInKernel(Kernel); 1203 1204 assert(Kernel->tree && "Device AST of kernel node is empty"); 1205 1206 Instruction &HostInsertPoint = *Builder.GetInsertPoint(); 1207 IslExprBuilder::IDToValueTy HostIDs = IDToValue; 1208 ValueMapT HostValueMap = ValueMap; 1209 BlockGenerator::AllocaMapTy HostScalarMap = ScalarMap; 1210 ScalarMap.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 EscapeMap.clear(); 1242 IDToSAI.clear(); 1243 Annotator.resetAlternativeAliasBases(); 1244 for (auto &BasePtr : LocalArrays) 1245 S.invalidateScopArrayInfo(BasePtr, MemoryKind::Array); 1246 LocalArrays.clear(); 1247 1248 std::string ASMString = finalizeKernelFunction(); 1249 Builder.SetInsertPoint(&HostInsertPoint); 1250 Value *Parameters = createLaunchParameters(Kernel, F, SubtreeValues); 1251 1252 std::string Name = "kernel_" + std::to_string(Kernel->id); 1253 Value *KernelString = Builder.CreateGlobalStringPtr(ASMString, Name); 1254 Value *NameString = Builder.CreateGlobalStringPtr(Name, Name + "_name"); 1255 Value *GPUKernel = createCallGetKernel(KernelString, NameString); 1256 1257 Value *GridDimX, *GridDimY; 1258 std::tie(GridDimX, GridDimY) = getGridSizes(Kernel); 1259 1260 createCallLaunchKernel(GPUKernel, GridDimX, GridDimY, BlockDimX, BlockDimY, 1261 BlockDimZ, Parameters); 1262 createCallFreeKernel(GPUKernel); 1263 1264 for (auto Id : KernelIds) 1265 isl_id_free(Id); 1266 1267 KernelIds.clear(); 1268 } 1269 1270 /// Compute the DataLayout string for the NVPTX backend. 1271 /// 1272 /// @param is64Bit Are we looking for a 64 bit architecture? 1273 static std::string computeNVPTXDataLayout(bool is64Bit) { 1274 std::string Ret = "e"; 1275 1276 if (!is64Bit) 1277 Ret += "-p:32:32"; 1278 1279 Ret += "-i64:64-v16:16-v32:32-n16:32:64"; 1280 1281 return Ret; 1282 } 1283 1284 Function * 1285 GPUNodeBuilder::createKernelFunctionDecl(ppcg_kernel *Kernel, 1286 SetVector<Value *> &SubtreeValues) { 1287 std::vector<Type *> Args; 1288 std::string Identifier = "kernel_" + std::to_string(Kernel->id); 1289 1290 for (long i = 0; i < Prog->n_array; i++) { 1291 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1292 continue; 1293 1294 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1295 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1296 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(Id); 1297 Args.push_back(SAI->getElementType()); 1298 } else { 1299 Args.push_back(Builder.getInt8PtrTy()); 1300 } 1301 } 1302 1303 int NumHostIters = isl_space_dim(Kernel->space, isl_dim_set); 1304 1305 for (long i = 0; i < NumHostIters; i++) 1306 Args.push_back(Builder.getInt64Ty()); 1307 1308 int NumVars = isl_space_dim(Kernel->space, isl_dim_param); 1309 1310 for (long i = 0; i < NumVars; i++) { 1311 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1312 Value *Val = IDToValue[Id]; 1313 isl_id_free(Id); 1314 Args.push_back(Val->getType()); 1315 } 1316 1317 for (auto *V : SubtreeValues) 1318 Args.push_back(V->getType()); 1319 1320 auto *FT = FunctionType::get(Builder.getVoidTy(), Args, false); 1321 auto *FN = Function::Create(FT, Function::ExternalLinkage, Identifier, 1322 GPUModule.get()); 1323 FN->setCallingConv(CallingConv::PTX_Kernel); 1324 1325 auto Arg = FN->arg_begin(); 1326 for (long i = 0; i < Kernel->n_array; i++) { 1327 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1328 continue; 1329 1330 Arg->setName(Kernel->array[i].array->name); 1331 1332 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1333 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1334 Type *EleTy = SAI->getElementType(); 1335 Value *Val = &*Arg; 1336 SmallVector<const SCEV *, 4> Sizes; 1337 isl_ast_build *Build = 1338 isl_ast_build_from_context(isl_set_copy(Prog->context)); 1339 Sizes.push_back(nullptr); 1340 for (long j = 1; j < Kernel->array[i].array->n_index; j++) { 1341 isl_ast_expr *DimSize = isl_ast_build_expr_from_pw_aff( 1342 Build, isl_pw_aff_copy(Kernel->array[i].array->bound[j])); 1343 auto V = ExprBuilder.create(DimSize); 1344 Sizes.push_back(SE.getSCEV(V)); 1345 } 1346 const ScopArrayInfo *SAIRep = 1347 S.getOrCreateScopArrayInfo(Val, EleTy, Sizes, MemoryKind::Array); 1348 LocalArrays.push_back(Val); 1349 1350 isl_ast_build_free(Build); 1351 KernelIds.push_back(Id); 1352 IDToSAI[Id] = SAIRep; 1353 Arg++; 1354 } 1355 1356 for (long i = 0; i < NumHostIters; i++) { 1357 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1358 Arg->setName(isl_id_get_name(Id)); 1359 IDToValue[Id] = &*Arg; 1360 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1361 Arg++; 1362 } 1363 1364 for (long i = 0; i < NumVars; i++) { 1365 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1366 Arg->setName(isl_id_get_name(Id)); 1367 Value *Val = IDToValue[Id]; 1368 ValueMap[Val] = &*Arg; 1369 IDToValue[Id] = &*Arg; 1370 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1371 Arg++; 1372 } 1373 1374 for (auto *V : SubtreeValues) { 1375 Arg->setName(V->getName()); 1376 ValueMap[V] = &*Arg; 1377 Arg++; 1378 } 1379 1380 return FN; 1381 } 1382 1383 void GPUNodeBuilder::insertKernelIntrinsics(ppcg_kernel *Kernel) { 1384 Intrinsic::ID IntrinsicsBID[] = {Intrinsic::nvvm_read_ptx_sreg_ctaid_x, 1385 Intrinsic::nvvm_read_ptx_sreg_ctaid_y}; 1386 1387 Intrinsic::ID IntrinsicsTID[] = {Intrinsic::nvvm_read_ptx_sreg_tid_x, 1388 Intrinsic::nvvm_read_ptx_sreg_tid_y, 1389 Intrinsic::nvvm_read_ptx_sreg_tid_z}; 1390 1391 auto addId = [this](__isl_take isl_id *Id, Intrinsic::ID Intr) mutable { 1392 std::string Name = isl_id_get_name(Id); 1393 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 1394 Function *IntrinsicFn = Intrinsic::getDeclaration(M, Intr); 1395 Value *Val = Builder.CreateCall(IntrinsicFn, {}); 1396 Val = Builder.CreateIntCast(Val, Builder.getInt64Ty(), false, Name); 1397 IDToValue[Id] = Val; 1398 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1399 }; 1400 1401 for (int i = 0; i < Kernel->n_grid; ++i) { 1402 isl_id *Id = isl_id_list_get_id(Kernel->block_ids, i); 1403 addId(Id, IntrinsicsBID[i]); 1404 } 1405 1406 for (int i = 0; i < Kernel->n_block; ++i) { 1407 isl_id *Id = isl_id_list_get_id(Kernel->thread_ids, i); 1408 addId(Id, IntrinsicsTID[i]); 1409 } 1410 } 1411 1412 void GPUNodeBuilder::prepareKernelArguments(ppcg_kernel *Kernel, Function *FN) { 1413 auto Arg = FN->arg_begin(); 1414 for (long i = 0; i < Kernel->n_array; i++) { 1415 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1416 continue; 1417 1418 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1419 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1420 isl_id_free(Id); 1421 1422 if (SAI->getNumberOfDimensions() > 0) { 1423 Arg++; 1424 continue; 1425 } 1426 1427 Value *Val = &*Arg; 1428 1429 if (!gpu_array_is_read_only_scalar(&Prog->array[i])) { 1430 Type *TypePtr = SAI->getElementType()->getPointerTo(); 1431 Value *TypedArgPtr = Builder.CreatePointerCast(Val, TypePtr); 1432 Val = Builder.CreateLoad(TypedArgPtr); 1433 } 1434 1435 Value *Alloca = BlockGen.getOrCreateAlloca(SAI); 1436 Builder.CreateStore(Val, Alloca); 1437 1438 Arg++; 1439 } 1440 } 1441 1442 void GPUNodeBuilder::finalizeKernelArguments(ppcg_kernel *Kernel) { 1443 auto *FN = Builder.GetInsertBlock()->getParent(); 1444 auto Arg = FN->arg_begin(); 1445 1446 bool StoredScalar = false; 1447 for (long i = 0; i < Kernel->n_array; i++) { 1448 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1449 continue; 1450 1451 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1452 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1453 isl_id_free(Id); 1454 1455 if (SAI->getNumberOfDimensions() > 0) { 1456 Arg++; 1457 continue; 1458 } 1459 1460 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1461 Arg++; 1462 continue; 1463 } 1464 1465 Value *Alloca = BlockGen.getOrCreateAlloca(SAI); 1466 Value *ArgPtr = &*Arg; 1467 Type *TypePtr = SAI->getElementType()->getPointerTo(); 1468 Value *TypedArgPtr = Builder.CreatePointerCast(ArgPtr, TypePtr); 1469 Value *Val = Builder.CreateLoad(Alloca); 1470 Builder.CreateStore(Val, TypedArgPtr); 1471 StoredScalar = true; 1472 1473 Arg++; 1474 } 1475 1476 if (StoredScalar) 1477 /// In case more than one thread contains scalar stores, the generated 1478 /// code might be incorrect, if we only store at the end of the kernel. 1479 /// To support this case we need to store these scalars back at each 1480 /// memory store or at least before each kernel barrier. 1481 if (Kernel->n_block != 0 || Kernel->n_grid != 0) 1482 BuildSuccessful = 0; 1483 } 1484 1485 void GPUNodeBuilder::createKernelVariables(ppcg_kernel *Kernel, Function *FN) { 1486 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 1487 1488 for (int i = 0; i < Kernel->n_var; ++i) { 1489 struct ppcg_kernel_var &Var = Kernel->var[i]; 1490 isl_id *Id = isl_space_get_tuple_id(Var.array->space, isl_dim_set); 1491 Type *EleTy = ScopArrayInfo::getFromId(Id)->getElementType(); 1492 1493 Type *ArrayTy = EleTy; 1494 SmallVector<const SCEV *, 4> Sizes; 1495 1496 Sizes.push_back(nullptr); 1497 for (unsigned int j = 1; j < Var.array->n_index; ++j) { 1498 isl_val *Val = isl_vec_get_element_val(Var.size, j); 1499 long Bound = isl_val_get_num_si(Val); 1500 isl_val_free(Val); 1501 Sizes.push_back(S.getSE()->getConstant(Builder.getInt64Ty(), Bound)); 1502 } 1503 1504 for (int j = Var.array->n_index - 1; j >= 0; --j) { 1505 isl_val *Val = isl_vec_get_element_val(Var.size, j); 1506 long Bound = isl_val_get_num_si(Val); 1507 isl_val_free(Val); 1508 ArrayTy = ArrayType::get(ArrayTy, Bound); 1509 } 1510 1511 const ScopArrayInfo *SAI; 1512 Value *Allocation; 1513 if (Var.type == ppcg_access_shared) { 1514 auto GlobalVar = new GlobalVariable( 1515 *M, ArrayTy, false, GlobalValue::InternalLinkage, 0, Var.name, 1516 nullptr, GlobalValue::ThreadLocalMode::NotThreadLocal, 3); 1517 GlobalVar->setAlignment(EleTy->getPrimitiveSizeInBits() / 8); 1518 GlobalVar->setInitializer(Constant::getNullValue(ArrayTy)); 1519 1520 Allocation = GlobalVar; 1521 } else if (Var.type == ppcg_access_private) { 1522 Allocation = Builder.CreateAlloca(ArrayTy, 0, "private_array"); 1523 } else { 1524 llvm_unreachable("unknown variable type"); 1525 } 1526 SAI = 1527 S.getOrCreateScopArrayInfo(Allocation, EleTy, Sizes, MemoryKind::Array); 1528 Id = isl_id_alloc(S.getIslCtx(), Var.name, nullptr); 1529 IDToValue[Id] = Allocation; 1530 LocalArrays.push_back(Allocation); 1531 KernelIds.push_back(Id); 1532 IDToSAI[Id] = SAI; 1533 } 1534 } 1535 1536 void GPUNodeBuilder::createKernelFunction(ppcg_kernel *Kernel, 1537 SetVector<Value *> &SubtreeValues) { 1538 1539 std::string Identifier = "kernel_" + std::to_string(Kernel->id); 1540 GPUModule.reset(new Module(Identifier, Builder.getContext())); 1541 GPUModule->setTargetTriple(Triple::normalize("nvptx64-nvidia-cuda")); 1542 GPUModule->setDataLayout(computeNVPTXDataLayout(true /* is64Bit */)); 1543 1544 Function *FN = createKernelFunctionDecl(Kernel, SubtreeValues); 1545 1546 BasicBlock *PrevBlock = Builder.GetInsertBlock(); 1547 auto EntryBlock = BasicBlock::Create(Builder.getContext(), "entry", FN); 1548 1549 DominatorTree &DT = P->getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 1550 DT.addNewBlock(EntryBlock, PrevBlock); 1551 1552 Builder.SetInsertPoint(EntryBlock); 1553 Builder.CreateRetVoid(); 1554 Builder.SetInsertPoint(EntryBlock, EntryBlock->begin()); 1555 1556 ScopDetection::markFunctionAsInvalid(FN); 1557 1558 prepareKernelArguments(Kernel, FN); 1559 createKernelVariables(Kernel, FN); 1560 insertKernelIntrinsics(Kernel); 1561 } 1562 1563 std::string GPUNodeBuilder::createKernelASM() { 1564 llvm::Triple GPUTriple(Triple::normalize("nvptx64-nvidia-cuda")); 1565 std::string ErrMsg; 1566 auto GPUTarget = TargetRegistry::lookupTarget(GPUTriple.getTriple(), ErrMsg); 1567 1568 if (!GPUTarget) { 1569 errs() << ErrMsg << "\n"; 1570 return ""; 1571 } 1572 1573 TargetOptions Options; 1574 Options.UnsafeFPMath = FastMath; 1575 std::unique_ptr<TargetMachine> TargetM( 1576 GPUTarget->createTargetMachine(GPUTriple.getTriple(), CudaVersion, "", 1577 Options, Optional<Reloc::Model>())); 1578 1579 SmallString<0> ASMString; 1580 raw_svector_ostream ASMStream(ASMString); 1581 llvm::legacy::PassManager PM; 1582 1583 PM.add(createTargetTransformInfoWrapperPass(TargetM->getTargetIRAnalysis())); 1584 1585 if (TargetM->addPassesToEmitFile( 1586 PM, ASMStream, TargetMachine::CGFT_AssemblyFile, true /* verify */)) { 1587 errs() << "The target does not support generation of this file type!\n"; 1588 return ""; 1589 } 1590 1591 PM.run(*GPUModule); 1592 1593 return ASMStream.str(); 1594 } 1595 1596 std::string GPUNodeBuilder::finalizeKernelFunction() { 1597 if (verifyModule(*GPUModule)) { 1598 BuildSuccessful = false; 1599 return ""; 1600 } 1601 1602 if (DumpKernelIR) 1603 outs() << *GPUModule << "\n"; 1604 1605 // Optimize module. 1606 llvm::legacy::PassManager OptPasses; 1607 PassManagerBuilder PassBuilder; 1608 PassBuilder.OptLevel = 3; 1609 PassBuilder.SizeLevel = 0; 1610 PassBuilder.populateModulePassManager(OptPasses); 1611 OptPasses.run(*GPUModule); 1612 1613 std::string Assembly = createKernelASM(); 1614 1615 if (DumpKernelASM) 1616 outs() << Assembly << "\n"; 1617 1618 GPUModule.release(); 1619 KernelIDs.clear(); 1620 1621 return Assembly; 1622 } 1623 1624 namespace { 1625 class PPCGCodeGeneration : public ScopPass { 1626 public: 1627 static char ID; 1628 1629 /// The scop that is currently processed. 1630 Scop *S; 1631 1632 LoopInfo *LI; 1633 DominatorTree *DT; 1634 ScalarEvolution *SE; 1635 const DataLayout *DL; 1636 RegionInfo *RI; 1637 1638 PPCGCodeGeneration() : ScopPass(ID) {} 1639 1640 /// Construct compilation options for PPCG. 1641 /// 1642 /// @returns The compilation options. 1643 ppcg_options *createPPCGOptions() { 1644 auto DebugOptions = 1645 (ppcg_debug_options *)malloc(sizeof(ppcg_debug_options)); 1646 auto Options = (ppcg_options *)malloc(sizeof(ppcg_options)); 1647 1648 DebugOptions->dump_schedule_constraints = false; 1649 DebugOptions->dump_schedule = false; 1650 DebugOptions->dump_final_schedule = false; 1651 DebugOptions->dump_sizes = false; 1652 DebugOptions->verbose = false; 1653 1654 Options->debug = DebugOptions; 1655 1656 Options->reschedule = true; 1657 Options->scale_tile_loops = false; 1658 Options->wrap = false; 1659 1660 Options->non_negative_parameters = false; 1661 Options->ctx = nullptr; 1662 Options->sizes = nullptr; 1663 1664 Options->tile_size = 32; 1665 1666 Options->use_private_memory = PrivateMemory; 1667 Options->use_shared_memory = SharedMemory; 1668 Options->max_shared_memory = 48 * 1024; 1669 1670 Options->target = PPCG_TARGET_CUDA; 1671 Options->openmp = false; 1672 Options->linearize_device_arrays = true; 1673 Options->live_range_reordering = false; 1674 1675 Options->opencl_compiler_options = nullptr; 1676 Options->opencl_use_gpu = false; 1677 Options->opencl_n_include_file = 0; 1678 Options->opencl_include_files = nullptr; 1679 Options->opencl_print_kernel_types = false; 1680 Options->opencl_embed_kernel_code = false; 1681 1682 Options->save_schedule_file = nullptr; 1683 Options->load_schedule_file = nullptr; 1684 1685 return Options; 1686 } 1687 1688 /// Get a tagged access relation containing all accesses of type @p AccessTy. 1689 /// 1690 /// Instead of a normal access of the form: 1691 /// 1692 /// Stmt[i,j,k] -> Array[f_0(i,j,k), f_1(i,j,k)] 1693 /// 1694 /// a tagged access has the form 1695 /// 1696 /// [Stmt[i,j,k] -> id[]] -> Array[f_0(i,j,k), f_1(i,j,k)] 1697 /// 1698 /// where 'id' is an additional space that references the memory access that 1699 /// triggered the access. 1700 /// 1701 /// @param AccessTy The type of the memory accesses to collect. 1702 /// 1703 /// @return The relation describing all tagged memory accesses. 1704 isl_union_map *getTaggedAccesses(enum MemoryAccess::AccessType AccessTy) { 1705 isl_union_map *Accesses = isl_union_map_empty(S->getParamSpace()); 1706 1707 for (auto &Stmt : *S) 1708 for (auto &Acc : Stmt) 1709 if (Acc->getType() == AccessTy) { 1710 isl_map *Relation = Acc->getAccessRelation(); 1711 Relation = isl_map_intersect_domain(Relation, Stmt.getDomain()); 1712 1713 isl_space *Space = isl_map_get_space(Relation); 1714 Space = isl_space_range(Space); 1715 Space = isl_space_from_range(Space); 1716 Space = isl_space_set_tuple_id(Space, isl_dim_in, Acc->getId()); 1717 isl_map *Universe = isl_map_universe(Space); 1718 Relation = isl_map_domain_product(Relation, Universe); 1719 Accesses = isl_union_map_add_map(Accesses, Relation); 1720 } 1721 1722 return Accesses; 1723 } 1724 1725 /// Get the set of all read accesses, tagged with the access id. 1726 /// 1727 /// @see getTaggedAccesses 1728 isl_union_map *getTaggedReads() { 1729 return getTaggedAccesses(MemoryAccess::READ); 1730 } 1731 1732 /// Get the set of all may (and must) accesses, tagged with the access id. 1733 /// 1734 /// @see getTaggedAccesses 1735 isl_union_map *getTaggedMayWrites() { 1736 return isl_union_map_union(getTaggedAccesses(MemoryAccess::MAY_WRITE), 1737 getTaggedAccesses(MemoryAccess::MUST_WRITE)); 1738 } 1739 1740 /// Get the set of all must accesses, tagged with the access id. 1741 /// 1742 /// @see getTaggedAccesses 1743 isl_union_map *getTaggedMustWrites() { 1744 return getTaggedAccesses(MemoryAccess::MUST_WRITE); 1745 } 1746 1747 /// Collect parameter and array names as isl_ids. 1748 /// 1749 /// To reason about the different parameters and arrays used, ppcg requires 1750 /// a list of all isl_ids in use. As PPCG traditionally performs 1751 /// source-to-source compilation each of these isl_ids is mapped to the 1752 /// expression that represents it. As we do not have a corresponding 1753 /// expression in Polly, we just map each id to a 'zero' expression to match 1754 /// the data format that ppcg expects. 1755 /// 1756 /// @returns Retun a map from collected ids to 'zero' ast expressions. 1757 __isl_give isl_id_to_ast_expr *getNames() { 1758 auto *Names = isl_id_to_ast_expr_alloc( 1759 S->getIslCtx(), 1760 S->getNumParams() + std::distance(S->array_begin(), S->array_end())); 1761 auto *Zero = isl_ast_expr_from_val(isl_val_zero(S->getIslCtx())); 1762 auto *Space = S->getParamSpace(); 1763 1764 for (int I = 0, E = S->getNumParams(); I < E; ++I) { 1765 isl_id *Id = isl_space_get_dim_id(Space, isl_dim_param, I); 1766 Names = isl_id_to_ast_expr_set(Names, Id, isl_ast_expr_copy(Zero)); 1767 } 1768 1769 for (auto &Array : S->arrays()) { 1770 auto Id = Array->getBasePtrId(); 1771 Names = isl_id_to_ast_expr_set(Names, Id, isl_ast_expr_copy(Zero)); 1772 } 1773 1774 isl_space_free(Space); 1775 isl_ast_expr_free(Zero); 1776 1777 return Names; 1778 } 1779 1780 /// Create a new PPCG scop from the current scop. 1781 /// 1782 /// The PPCG scop is initialized with data from the current polly::Scop. From 1783 /// this initial data, the data-dependences in the PPCG scop are initialized. 1784 /// We do not use Polly's dependence analysis for now, to ensure we match 1785 /// the PPCG default behaviour more closely. 1786 /// 1787 /// @returns A new ppcg scop. 1788 ppcg_scop *createPPCGScop() { 1789 auto PPCGScop = (ppcg_scop *)malloc(sizeof(ppcg_scop)); 1790 1791 PPCGScop->options = createPPCGOptions(); 1792 1793 PPCGScop->start = 0; 1794 PPCGScop->end = 0; 1795 1796 PPCGScop->context = S->getContext(); 1797 PPCGScop->domain = S->getDomains(); 1798 PPCGScop->call = nullptr; 1799 PPCGScop->tagged_reads = getTaggedReads(); 1800 PPCGScop->reads = S->getReads(); 1801 PPCGScop->live_in = nullptr; 1802 PPCGScop->tagged_may_writes = getTaggedMayWrites(); 1803 PPCGScop->may_writes = S->getWrites(); 1804 PPCGScop->tagged_must_writes = getTaggedMustWrites(); 1805 PPCGScop->must_writes = S->getMustWrites(); 1806 PPCGScop->live_out = nullptr; 1807 PPCGScop->tagged_must_kills = isl_union_map_empty(S->getParamSpace()); 1808 PPCGScop->tagger = nullptr; 1809 1810 PPCGScop->independence = nullptr; 1811 PPCGScop->dep_flow = nullptr; 1812 PPCGScop->tagged_dep_flow = nullptr; 1813 PPCGScop->dep_false = nullptr; 1814 PPCGScop->dep_forced = nullptr; 1815 PPCGScop->dep_order = nullptr; 1816 PPCGScop->tagged_dep_order = nullptr; 1817 1818 PPCGScop->schedule = S->getScheduleTree(); 1819 PPCGScop->names = getNames(); 1820 1821 PPCGScop->pet = nullptr; 1822 1823 compute_tagger(PPCGScop); 1824 compute_dependences(PPCGScop); 1825 1826 return PPCGScop; 1827 } 1828 1829 /// Collect the array acesses in a statement. 1830 /// 1831 /// @param Stmt The statement for which to collect the accesses. 1832 /// 1833 /// @returns A list of array accesses. 1834 gpu_stmt_access *getStmtAccesses(ScopStmt &Stmt) { 1835 gpu_stmt_access *Accesses = nullptr; 1836 1837 for (MemoryAccess *Acc : Stmt) { 1838 auto Access = isl_alloc_type(S->getIslCtx(), struct gpu_stmt_access); 1839 Access->read = Acc->isRead(); 1840 Access->write = Acc->isWrite(); 1841 Access->access = Acc->getAccessRelation(); 1842 isl_space *Space = isl_map_get_space(Access->access); 1843 Space = isl_space_range(Space); 1844 Space = isl_space_from_range(Space); 1845 Space = isl_space_set_tuple_id(Space, isl_dim_in, Acc->getId()); 1846 isl_map *Universe = isl_map_universe(Space); 1847 Access->tagged_access = 1848 isl_map_domain_product(Acc->getAccessRelation(), Universe); 1849 Access->exact_write = !Acc->isMayWrite(); 1850 Access->ref_id = Acc->getId(); 1851 Access->next = Accesses; 1852 Access->n_index = Acc->getScopArrayInfo()->getNumberOfDimensions(); 1853 Accesses = Access; 1854 } 1855 1856 return Accesses; 1857 } 1858 1859 /// Collect the list of GPU statements. 1860 /// 1861 /// Each statement has an id, a pointer to the underlying data structure, 1862 /// as well as a list with all memory accesses. 1863 /// 1864 /// TODO: Initialize the list of memory accesses. 1865 /// 1866 /// @returns A linked-list of statements. 1867 gpu_stmt *getStatements() { 1868 gpu_stmt *Stmts = isl_calloc_array(S->getIslCtx(), struct gpu_stmt, 1869 std::distance(S->begin(), S->end())); 1870 1871 int i = 0; 1872 for (auto &Stmt : *S) { 1873 gpu_stmt *GPUStmt = &Stmts[i]; 1874 1875 GPUStmt->id = Stmt.getDomainId(); 1876 1877 // We use the pet stmt pointer to keep track of the Polly statements. 1878 GPUStmt->stmt = (pet_stmt *)&Stmt; 1879 GPUStmt->accesses = getStmtAccesses(Stmt); 1880 i++; 1881 } 1882 1883 return Stmts; 1884 } 1885 1886 /// Derive the extent of an array. 1887 /// 1888 /// The extent of an array is the set of elements that are within the 1889 /// accessed array. For the inner dimensions, the extent constraints are 1890 /// 0 and the size of the corresponding array dimension. For the first 1891 /// (outermost) dimension, the extent constraints are the minimal and maximal 1892 /// subscript value for the first dimension. 1893 /// 1894 /// @param Array The array to derive the extent for. 1895 /// 1896 /// @returns An isl_set describing the extent of the array. 1897 __isl_give isl_set *getExtent(ScopArrayInfo *Array) { 1898 unsigned NumDims = Array->getNumberOfDimensions(); 1899 isl_union_map *Accesses = S->getAccesses(); 1900 Accesses = isl_union_map_intersect_domain(Accesses, S->getDomains()); 1901 Accesses = isl_union_map_detect_equalities(Accesses); 1902 isl_union_set *AccessUSet = isl_union_map_range(Accesses); 1903 AccessUSet = isl_union_set_coalesce(AccessUSet); 1904 AccessUSet = isl_union_set_detect_equalities(AccessUSet); 1905 AccessUSet = isl_union_set_coalesce(AccessUSet); 1906 1907 if (isl_union_set_is_empty(AccessUSet)) { 1908 isl_union_set_free(AccessUSet); 1909 return isl_set_empty(Array->getSpace()); 1910 } 1911 1912 if (Array->getNumberOfDimensions() == 0) { 1913 isl_union_set_free(AccessUSet); 1914 return isl_set_universe(Array->getSpace()); 1915 } 1916 1917 isl_set *AccessSet = 1918 isl_union_set_extract_set(AccessUSet, Array->getSpace()); 1919 1920 isl_union_set_free(AccessUSet); 1921 isl_local_space *LS = isl_local_space_from_space(Array->getSpace()); 1922 1923 isl_pw_aff *Val = 1924 isl_pw_aff_from_aff(isl_aff_var_on_domain(LS, isl_dim_set, 0)); 1925 1926 isl_pw_aff *OuterMin = isl_set_dim_min(isl_set_copy(AccessSet), 0); 1927 isl_pw_aff *OuterMax = isl_set_dim_max(AccessSet, 0); 1928 OuterMin = isl_pw_aff_add_dims(OuterMin, isl_dim_in, 1929 isl_pw_aff_dim(Val, isl_dim_in)); 1930 OuterMax = isl_pw_aff_add_dims(OuterMax, isl_dim_in, 1931 isl_pw_aff_dim(Val, isl_dim_in)); 1932 OuterMin = 1933 isl_pw_aff_set_tuple_id(OuterMin, isl_dim_in, Array->getBasePtrId()); 1934 OuterMax = 1935 isl_pw_aff_set_tuple_id(OuterMax, isl_dim_in, Array->getBasePtrId()); 1936 1937 isl_set *Extent = isl_set_universe(Array->getSpace()); 1938 1939 Extent = isl_set_intersect( 1940 Extent, isl_pw_aff_le_set(OuterMin, isl_pw_aff_copy(Val))); 1941 Extent = isl_set_intersect(Extent, isl_pw_aff_ge_set(OuterMax, Val)); 1942 1943 for (unsigned i = 1; i < NumDims; ++i) 1944 Extent = isl_set_lower_bound_si(Extent, isl_dim_set, i, 0); 1945 1946 for (unsigned i = 1; i < NumDims; ++i) { 1947 isl_pw_aff *PwAff = 1948 const_cast<isl_pw_aff *>(Array->getDimensionSizePw(i)); 1949 isl_pw_aff *Val = isl_pw_aff_from_aff(isl_aff_var_on_domain( 1950 isl_local_space_from_space(Array->getSpace()), isl_dim_set, i)); 1951 PwAff = isl_pw_aff_add_dims(PwAff, isl_dim_in, 1952 isl_pw_aff_dim(Val, isl_dim_in)); 1953 PwAff = isl_pw_aff_set_tuple_id(PwAff, isl_dim_in, 1954 isl_pw_aff_get_tuple_id(Val, isl_dim_in)); 1955 auto *Set = isl_pw_aff_gt_set(PwAff, Val); 1956 Extent = isl_set_intersect(Set, Extent); 1957 } 1958 1959 return Extent; 1960 } 1961 1962 /// Derive the bounds of an array. 1963 /// 1964 /// For the first dimension we derive the bound of the array from the extent 1965 /// of this dimension. For inner dimensions we obtain their size directly from 1966 /// ScopArrayInfo. 1967 /// 1968 /// @param PPCGArray The array to compute bounds for. 1969 /// @param Array The polly array from which to take the information. 1970 void setArrayBounds(gpu_array_info &PPCGArray, ScopArrayInfo *Array) { 1971 if (PPCGArray.n_index > 0) { 1972 if (isl_set_is_empty(PPCGArray.extent)) { 1973 isl_set *Dom = isl_set_copy(PPCGArray.extent); 1974 isl_local_space *LS = isl_local_space_from_space( 1975 isl_space_params(isl_set_get_space(Dom))); 1976 isl_set_free(Dom); 1977 isl_aff *Zero = isl_aff_zero_on_domain(LS); 1978 PPCGArray.bound[0] = isl_pw_aff_from_aff(Zero); 1979 } else { 1980 isl_set *Dom = isl_set_copy(PPCGArray.extent); 1981 Dom = isl_set_project_out(Dom, isl_dim_set, 1, PPCGArray.n_index - 1); 1982 isl_pw_aff *Bound = isl_set_dim_max(isl_set_copy(Dom), 0); 1983 isl_set_free(Dom); 1984 Dom = isl_pw_aff_domain(isl_pw_aff_copy(Bound)); 1985 isl_local_space *LS = 1986 isl_local_space_from_space(isl_set_get_space(Dom)); 1987 isl_aff *One = isl_aff_zero_on_domain(LS); 1988 One = isl_aff_add_constant_si(One, 1); 1989 Bound = isl_pw_aff_add(Bound, isl_pw_aff_alloc(Dom, One)); 1990 Bound = isl_pw_aff_gist(Bound, S->getContext()); 1991 PPCGArray.bound[0] = Bound; 1992 } 1993 } 1994 1995 for (unsigned i = 1; i < PPCGArray.n_index; ++i) { 1996 isl_pw_aff *Bound = Array->getDimensionSizePw(i); 1997 auto LS = isl_pw_aff_get_domain_space(Bound); 1998 auto Aff = isl_multi_aff_zero(LS); 1999 Bound = isl_pw_aff_pullback_multi_aff(Bound, Aff); 2000 PPCGArray.bound[i] = Bound; 2001 } 2002 } 2003 2004 /// Create the arrays for @p PPCGProg. 2005 /// 2006 /// @param PPCGProg The program to compute the arrays for. 2007 void createArrays(gpu_prog *PPCGProg) { 2008 int i = 0; 2009 for (auto &Array : S->arrays()) { 2010 std::string TypeName; 2011 raw_string_ostream OS(TypeName); 2012 2013 OS << *Array->getElementType(); 2014 TypeName = OS.str(); 2015 2016 gpu_array_info &PPCGArray = PPCGProg->array[i]; 2017 2018 PPCGArray.space = Array->getSpace(); 2019 PPCGArray.type = strdup(TypeName.c_str()); 2020 PPCGArray.size = Array->getElementType()->getPrimitiveSizeInBits() / 8; 2021 PPCGArray.name = strdup(Array->getName().c_str()); 2022 PPCGArray.extent = nullptr; 2023 PPCGArray.n_index = Array->getNumberOfDimensions(); 2024 PPCGArray.bound = 2025 isl_alloc_array(S->getIslCtx(), isl_pw_aff *, PPCGArray.n_index); 2026 PPCGArray.extent = getExtent(Array); 2027 PPCGArray.n_ref = 0; 2028 PPCGArray.refs = nullptr; 2029 PPCGArray.accessed = true; 2030 PPCGArray.read_only_scalar = 2031 Array->isReadOnly() && Array->getNumberOfDimensions() == 0; 2032 PPCGArray.has_compound_element = false; 2033 PPCGArray.local = false; 2034 PPCGArray.declare_local = false; 2035 PPCGArray.global = false; 2036 PPCGArray.linearize = false; 2037 PPCGArray.dep_order = nullptr; 2038 PPCGArray.user = Array; 2039 2040 setArrayBounds(PPCGArray, Array); 2041 i++; 2042 2043 collect_references(PPCGProg, &PPCGArray); 2044 } 2045 } 2046 2047 /// Create an identity map between the arrays in the scop. 2048 /// 2049 /// @returns An identity map between the arrays in the scop. 2050 isl_union_map *getArrayIdentity() { 2051 isl_union_map *Maps = isl_union_map_empty(S->getParamSpace()); 2052 2053 for (auto &Array : S->arrays()) { 2054 isl_space *Space = Array->getSpace(); 2055 Space = isl_space_map_from_set(Space); 2056 isl_map *Identity = isl_map_identity(Space); 2057 Maps = isl_union_map_add_map(Maps, Identity); 2058 } 2059 2060 return Maps; 2061 } 2062 2063 /// Create a default-initialized PPCG GPU program. 2064 /// 2065 /// @returns A new gpu grogram description. 2066 gpu_prog *createPPCGProg(ppcg_scop *PPCGScop) { 2067 2068 if (!PPCGScop) 2069 return nullptr; 2070 2071 auto PPCGProg = isl_calloc_type(S->getIslCtx(), struct gpu_prog); 2072 2073 PPCGProg->ctx = S->getIslCtx(); 2074 PPCGProg->scop = PPCGScop; 2075 PPCGProg->context = isl_set_copy(PPCGScop->context); 2076 PPCGProg->read = isl_union_map_copy(PPCGScop->reads); 2077 PPCGProg->may_write = isl_union_map_copy(PPCGScop->may_writes); 2078 PPCGProg->must_write = isl_union_map_copy(PPCGScop->must_writes); 2079 PPCGProg->tagged_must_kill = 2080 isl_union_map_copy(PPCGScop->tagged_must_kills); 2081 PPCGProg->to_inner = getArrayIdentity(); 2082 PPCGProg->to_outer = getArrayIdentity(); 2083 PPCGProg->any_to_outer = nullptr; 2084 PPCGProg->array_order = nullptr; 2085 PPCGProg->n_stmts = std::distance(S->begin(), S->end()); 2086 PPCGProg->stmts = getStatements(); 2087 PPCGProg->n_array = std::distance(S->array_begin(), S->array_end()); 2088 PPCGProg->array = isl_calloc_array(S->getIslCtx(), struct gpu_array_info, 2089 PPCGProg->n_array); 2090 2091 createArrays(PPCGProg); 2092 2093 PPCGProg->may_persist = compute_may_persist(PPCGProg); 2094 2095 return PPCGProg; 2096 } 2097 2098 struct PrintGPUUserData { 2099 struct cuda_info *CudaInfo; 2100 struct gpu_prog *PPCGProg; 2101 std::vector<ppcg_kernel *> Kernels; 2102 }; 2103 2104 /// Print a user statement node in the host code. 2105 /// 2106 /// We use ppcg's printing facilities to print the actual statement and 2107 /// additionally build up a list of all kernels that are encountered in the 2108 /// host ast. 2109 /// 2110 /// @param P The printer to print to 2111 /// @param Options The printing options to use 2112 /// @param Node The node to print 2113 /// @param User A user pointer to carry additional data. This pointer is 2114 /// expected to be of type PrintGPUUserData. 2115 /// 2116 /// @returns A printer to which the output has been printed. 2117 static __isl_give isl_printer * 2118 printHostUser(__isl_take isl_printer *P, 2119 __isl_take isl_ast_print_options *Options, 2120 __isl_take isl_ast_node *Node, void *User) { 2121 auto Data = (struct PrintGPUUserData *)User; 2122 auto Id = isl_ast_node_get_annotation(Node); 2123 2124 if (Id) { 2125 bool IsUser = !strcmp(isl_id_get_name(Id), "user"); 2126 2127 // If this is a user statement, format it ourselves as ppcg would 2128 // otherwise try to call pet functionality that is not available in 2129 // Polly. 2130 if (IsUser) { 2131 P = isl_printer_start_line(P); 2132 P = isl_printer_print_ast_node(P, Node); 2133 P = isl_printer_end_line(P); 2134 isl_id_free(Id); 2135 isl_ast_print_options_free(Options); 2136 return P; 2137 } 2138 2139 auto Kernel = (struct ppcg_kernel *)isl_id_get_user(Id); 2140 isl_id_free(Id); 2141 Data->Kernels.push_back(Kernel); 2142 } 2143 2144 return print_host_user(P, Options, Node, User); 2145 } 2146 2147 /// Print C code corresponding to the control flow in @p Kernel. 2148 /// 2149 /// @param Kernel The kernel to print 2150 void printKernel(ppcg_kernel *Kernel) { 2151 auto *P = isl_printer_to_str(S->getIslCtx()); 2152 P = isl_printer_set_output_format(P, ISL_FORMAT_C); 2153 auto *Options = isl_ast_print_options_alloc(S->getIslCtx()); 2154 P = isl_ast_node_print(Kernel->tree, P, Options); 2155 char *String = isl_printer_get_str(P); 2156 printf("%s\n", String); 2157 free(String); 2158 isl_printer_free(P); 2159 } 2160 2161 /// Print C code corresponding to the GPU code described by @p Tree. 2162 /// 2163 /// @param Tree An AST describing GPU code 2164 /// @param PPCGProg The PPCG program from which @Tree has been constructed. 2165 void printGPUTree(isl_ast_node *Tree, gpu_prog *PPCGProg) { 2166 auto *P = isl_printer_to_str(S->getIslCtx()); 2167 P = isl_printer_set_output_format(P, ISL_FORMAT_C); 2168 2169 PrintGPUUserData Data; 2170 Data.PPCGProg = PPCGProg; 2171 2172 auto *Options = isl_ast_print_options_alloc(S->getIslCtx()); 2173 Options = 2174 isl_ast_print_options_set_print_user(Options, printHostUser, &Data); 2175 P = isl_ast_node_print(Tree, P, Options); 2176 char *String = isl_printer_get_str(P); 2177 printf("# host\n"); 2178 printf("%s\n", String); 2179 free(String); 2180 isl_printer_free(P); 2181 2182 for (auto Kernel : Data.Kernels) { 2183 printf("# kernel%d\n", Kernel->id); 2184 printKernel(Kernel); 2185 } 2186 } 2187 2188 // Generate a GPU program using PPCG. 2189 // 2190 // GPU mapping consists of multiple steps: 2191 // 2192 // 1) Compute new schedule for the program. 2193 // 2) Map schedule to GPU (TODO) 2194 // 3) Generate code for new schedule (TODO) 2195 // 2196 // We do not use here the Polly ScheduleOptimizer, as the schedule optimizer 2197 // is mostly CPU specific. Instead, we use PPCG's GPU code generation 2198 // strategy directly from this pass. 2199 gpu_gen *generateGPU(ppcg_scop *PPCGScop, gpu_prog *PPCGProg) { 2200 2201 auto PPCGGen = isl_calloc_type(S->getIslCtx(), struct gpu_gen); 2202 2203 PPCGGen->ctx = S->getIslCtx(); 2204 PPCGGen->options = PPCGScop->options; 2205 PPCGGen->print = nullptr; 2206 PPCGGen->print_user = nullptr; 2207 PPCGGen->build_ast_expr = &pollyBuildAstExprForStmt; 2208 PPCGGen->prog = PPCGProg; 2209 PPCGGen->tree = nullptr; 2210 PPCGGen->types.n = 0; 2211 PPCGGen->types.name = nullptr; 2212 PPCGGen->sizes = nullptr; 2213 PPCGGen->used_sizes = nullptr; 2214 PPCGGen->kernel_id = 0; 2215 2216 // Set scheduling strategy to same strategy PPCG is using. 2217 isl_options_set_schedule_outer_coincidence(PPCGGen->ctx, true); 2218 isl_options_set_schedule_maximize_band_depth(PPCGGen->ctx, true); 2219 isl_options_set_schedule_whole_component(PPCGGen->ctx, false); 2220 2221 isl_schedule *Schedule = get_schedule(PPCGGen); 2222 2223 int has_permutable = has_any_permutable_node(Schedule); 2224 2225 if (!has_permutable || has_permutable < 0) { 2226 Schedule = isl_schedule_free(Schedule); 2227 } else { 2228 Schedule = map_to_device(PPCGGen, Schedule); 2229 PPCGGen->tree = generate_code(PPCGGen, isl_schedule_copy(Schedule)); 2230 } 2231 2232 if (DumpSchedule) { 2233 isl_printer *P = isl_printer_to_str(S->getIslCtx()); 2234 P = isl_printer_set_yaml_style(P, ISL_YAML_STYLE_BLOCK); 2235 P = isl_printer_print_str(P, "Schedule\n"); 2236 P = isl_printer_print_str(P, "========\n"); 2237 if (Schedule) 2238 P = isl_printer_print_schedule(P, Schedule); 2239 else 2240 P = isl_printer_print_str(P, "No schedule found\n"); 2241 2242 printf("%s\n", isl_printer_get_str(P)); 2243 isl_printer_free(P); 2244 } 2245 2246 if (DumpCode) { 2247 printf("Code\n"); 2248 printf("====\n"); 2249 if (PPCGGen->tree) 2250 printGPUTree(PPCGGen->tree, PPCGProg); 2251 else 2252 printf("No code generated\n"); 2253 } 2254 2255 isl_schedule_free(Schedule); 2256 2257 return PPCGGen; 2258 } 2259 2260 /// Free gpu_gen structure. 2261 /// 2262 /// @param PPCGGen The ppcg_gen object to free. 2263 void freePPCGGen(gpu_gen *PPCGGen) { 2264 isl_ast_node_free(PPCGGen->tree); 2265 isl_union_map_free(PPCGGen->sizes); 2266 isl_union_map_free(PPCGGen->used_sizes); 2267 free(PPCGGen); 2268 } 2269 2270 /// Free the options in the ppcg scop structure. 2271 /// 2272 /// ppcg is not freeing these options for us. To avoid leaks we do this 2273 /// ourselves. 2274 /// 2275 /// @param PPCGScop The scop referencing the options to free. 2276 void freeOptions(ppcg_scop *PPCGScop) { 2277 free(PPCGScop->options->debug); 2278 PPCGScop->options->debug = nullptr; 2279 free(PPCGScop->options); 2280 PPCGScop->options = nullptr; 2281 } 2282 2283 /// Approximate the number of points in the set. 2284 /// 2285 /// This function returns an ast expression that overapproximates the number 2286 /// of points in an isl set through the rectangular hull surrounding this set. 2287 /// 2288 /// @param Set The set to count. 2289 /// @param Build The isl ast build object to use for creating the ast 2290 /// expression. 2291 /// 2292 /// @returns An approximation of the number of points in the set. 2293 __isl_give isl_ast_expr *approxPointsInSet(__isl_take isl_set *Set, 2294 __isl_keep isl_ast_build *Build) { 2295 2296 isl_val *One = isl_val_int_from_si(isl_set_get_ctx(Set), 1); 2297 auto *Expr = isl_ast_expr_from_val(isl_val_copy(One)); 2298 2299 isl_space *Space = isl_set_get_space(Set); 2300 Space = isl_space_params(Space); 2301 auto *Univ = isl_set_universe(Space); 2302 isl_pw_aff *OneAff = isl_pw_aff_val_on_domain(Univ, One); 2303 2304 for (long i = 0; i < isl_set_dim(Set, isl_dim_set); i++) { 2305 isl_pw_aff *Max = isl_set_dim_max(isl_set_copy(Set), i); 2306 isl_pw_aff *Min = isl_set_dim_min(isl_set_copy(Set), i); 2307 isl_pw_aff *DimSize = isl_pw_aff_sub(Max, Min); 2308 DimSize = isl_pw_aff_add(DimSize, isl_pw_aff_copy(OneAff)); 2309 auto DimSizeExpr = isl_ast_build_expr_from_pw_aff(Build, DimSize); 2310 Expr = isl_ast_expr_mul(Expr, DimSizeExpr); 2311 } 2312 2313 isl_set_free(Set); 2314 isl_pw_aff_free(OneAff); 2315 2316 return Expr; 2317 } 2318 2319 /// Approximate a number of dynamic instructions executed by a given 2320 /// statement. 2321 /// 2322 /// @param Stmt The statement for which to compute the number of dynamic 2323 /// instructions. 2324 /// @param Build The isl ast build object to use for creating the ast 2325 /// expression. 2326 /// @returns An approximation of the number of dynamic instructions executed 2327 /// by @p Stmt. 2328 __isl_give isl_ast_expr *approxDynamicInst(ScopStmt &Stmt, 2329 __isl_keep isl_ast_build *Build) { 2330 auto Iterations = approxPointsInSet(Stmt.getDomain(), Build); 2331 2332 long InstCount = 0; 2333 2334 if (Stmt.isBlockStmt()) { 2335 auto *BB = Stmt.getBasicBlock(); 2336 InstCount = std::distance(BB->begin(), BB->end()); 2337 } else { 2338 auto *R = Stmt.getRegion(); 2339 2340 for (auto *BB : R->blocks()) { 2341 InstCount += std::distance(BB->begin(), BB->end()); 2342 } 2343 } 2344 2345 isl_val *InstVal = isl_val_int_from_si(S->getIslCtx(), InstCount); 2346 auto *InstExpr = isl_ast_expr_from_val(InstVal); 2347 return isl_ast_expr_mul(InstExpr, Iterations); 2348 } 2349 2350 /// Approximate dynamic instructions executed in scop. 2351 /// 2352 /// @param S The scop for which to approximate dynamic instructions. 2353 /// @param Build The isl ast build object to use for creating the ast 2354 /// expression. 2355 /// @returns An approximation of the number of dynamic instructions executed 2356 /// in @p S. 2357 __isl_give isl_ast_expr * 2358 getNumberOfIterations(Scop &S, __isl_keep isl_ast_build *Build) { 2359 isl_ast_expr *Instructions; 2360 2361 isl_val *Zero = isl_val_int_from_si(S.getIslCtx(), 0); 2362 Instructions = isl_ast_expr_from_val(Zero); 2363 2364 for (ScopStmt &Stmt : S) { 2365 isl_ast_expr *StmtInstructions = approxDynamicInst(Stmt, Build); 2366 Instructions = isl_ast_expr_add(Instructions, StmtInstructions); 2367 } 2368 return Instructions; 2369 } 2370 2371 /// Create a check that ensures sufficient compute in scop. 2372 /// 2373 /// @param S The scop for which to ensure sufficient compute. 2374 /// @param Build The isl ast build object to use for creating the ast 2375 /// expression. 2376 /// @returns An expression that evaluates to TRUE in case of sufficient 2377 /// compute and to FALSE, otherwise. 2378 __isl_give isl_ast_expr * 2379 createSufficientComputeCheck(Scop &S, __isl_keep isl_ast_build *Build) { 2380 auto Iterations = getNumberOfIterations(S, Build); 2381 auto *MinComputeVal = isl_val_int_from_si(S.getIslCtx(), MinCompute); 2382 auto *MinComputeExpr = isl_ast_expr_from_val(MinComputeVal); 2383 return isl_ast_expr_ge(Iterations, MinComputeExpr); 2384 } 2385 2386 /// Generate code for a given GPU AST described by @p Root. 2387 /// 2388 /// @param Root An isl_ast_node pointing to the root of the GPU AST. 2389 /// @param Prog The GPU Program to generate code for. 2390 void generateCode(__isl_take isl_ast_node *Root, gpu_prog *Prog) { 2391 ScopAnnotator Annotator; 2392 Annotator.buildAliasScopes(*S); 2393 2394 Region *R = &S->getRegion(); 2395 2396 simplifyRegion(R, DT, LI, RI); 2397 2398 BasicBlock *EnteringBB = R->getEnteringBlock(); 2399 2400 PollyIRBuilder Builder = createPollyIRBuilder(EnteringBB, Annotator); 2401 2402 // Only build the run-time condition and parameters _after_ having 2403 // introduced the conditional branch. This is important as the conditional 2404 // branch will guard the original scop from new induction variables that 2405 // the SCEVExpander may introduce while code generating the parameters and 2406 // which may introduce scalar dependences that prevent us from correctly 2407 // code generating this scop. 2408 BasicBlock *StartBlock = 2409 executeScopConditionally(*S, this, Builder.getTrue()); 2410 2411 GPUNodeBuilder NodeBuilder(Builder, Annotator, this, *DL, *LI, *SE, *DT, *S, 2412 StartBlock, Prog); 2413 2414 // TODO: Handle LICM 2415 auto SplitBlock = StartBlock->getSinglePredecessor(); 2416 Builder.SetInsertPoint(SplitBlock->getTerminator()); 2417 NodeBuilder.addParameters(S->getContext()); 2418 2419 isl_ast_build *Build = isl_ast_build_alloc(S->getIslCtx()); 2420 isl_ast_expr *Condition = IslAst::buildRunCondition(S, Build); 2421 isl_ast_expr *SufficientCompute = createSufficientComputeCheck(*S, Build); 2422 Condition = isl_ast_expr_and(Condition, SufficientCompute); 2423 isl_ast_build_free(Build); 2424 2425 Value *RTC = NodeBuilder.createRTC(Condition); 2426 Builder.GetInsertBlock()->getTerminator()->setOperand(0, RTC); 2427 2428 Builder.SetInsertPoint(&*StartBlock->begin()); 2429 2430 NodeBuilder.initializeAfterRTH(); 2431 NodeBuilder.create(Root); 2432 NodeBuilder.finalize(); 2433 2434 /// In case a sequential kernel has more surrounding loops as any parallel 2435 /// kernel, the SCoP is probably mostly sequential. Hence, there is no 2436 /// point in running it on a CPU. 2437 if (NodeBuilder.DeepestSequential > NodeBuilder.DeepestParallel) 2438 SplitBlock->getTerminator()->setOperand(0, Builder.getFalse()); 2439 2440 if (!NodeBuilder.BuildSuccessful) 2441 SplitBlock->getTerminator()->setOperand(0, Builder.getFalse()); 2442 } 2443 2444 bool runOnScop(Scop &CurrentScop) override { 2445 S = &CurrentScop; 2446 LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 2447 DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 2448 SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 2449 DL = &S->getRegion().getEntry()->getParent()->getParent()->getDataLayout(); 2450 RI = &getAnalysis<RegionInfoPass>().getRegionInfo(); 2451 2452 // We currently do not support scops with invariant loads. 2453 if (S->hasInvariantAccesses()) 2454 return false; 2455 2456 auto PPCGScop = createPPCGScop(); 2457 auto PPCGProg = createPPCGProg(PPCGScop); 2458 auto PPCGGen = generateGPU(PPCGScop, PPCGProg); 2459 2460 if (PPCGGen->tree) 2461 generateCode(isl_ast_node_copy(PPCGGen->tree), PPCGProg); 2462 2463 freeOptions(PPCGScop); 2464 freePPCGGen(PPCGGen); 2465 gpu_prog_free(PPCGProg); 2466 ppcg_scop_free(PPCGScop); 2467 2468 return true; 2469 } 2470 2471 void printScop(raw_ostream &, Scop &) const override {} 2472 2473 void getAnalysisUsage(AnalysisUsage &AU) const override { 2474 AU.addRequired<DominatorTreeWrapperPass>(); 2475 AU.addRequired<RegionInfoPass>(); 2476 AU.addRequired<ScalarEvolutionWrapperPass>(); 2477 AU.addRequired<ScopDetection>(); 2478 AU.addRequired<ScopInfoRegionPass>(); 2479 AU.addRequired<LoopInfoWrapperPass>(); 2480 2481 AU.addPreserved<AAResultsWrapperPass>(); 2482 AU.addPreserved<BasicAAWrapperPass>(); 2483 AU.addPreserved<LoopInfoWrapperPass>(); 2484 AU.addPreserved<DominatorTreeWrapperPass>(); 2485 AU.addPreserved<GlobalsAAWrapperPass>(); 2486 AU.addPreserved<PostDominatorTreeWrapperPass>(); 2487 AU.addPreserved<ScopDetection>(); 2488 AU.addPreserved<ScalarEvolutionWrapperPass>(); 2489 AU.addPreserved<SCEVAAWrapperPass>(); 2490 2491 // FIXME: We do not yet add regions for the newly generated code to the 2492 // region tree. 2493 AU.addPreserved<RegionInfoPass>(); 2494 AU.addPreserved<ScopInfoRegionPass>(); 2495 } 2496 }; 2497 } 2498 2499 char PPCGCodeGeneration::ID = 1; 2500 2501 Pass *polly::createPPCGCodeGenerationPass() { return new PPCGCodeGeneration(); } 2502 2503 INITIALIZE_PASS_BEGIN(PPCGCodeGeneration, "polly-codegen-ppcg", 2504 "Polly - Apply PPCG translation to SCOP", false, false) 2505 INITIALIZE_PASS_DEPENDENCY(DependenceInfo); 2506 INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass); 2507 INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass); 2508 INITIALIZE_PASS_DEPENDENCY(RegionInfoPass); 2509 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass); 2510 INITIALIZE_PASS_DEPENDENCY(ScopDetection); 2511 INITIALIZE_PASS_END(PPCGCodeGeneration, "polly-codegen-ppcg", 2512 "Polly - Apply PPCG translation to SCOP", false, false) 2513