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/ScalarEvolutionAliasAnalysis.h" 29 #include "llvm/Analysis/TargetLibraryInfo.h" 30 #include "llvm/Analysis/TargetTransformInfo.h" 31 #include "llvm/IR/LegacyPassManager.h" 32 #include "llvm/IR/Verifier.h" 33 #include "llvm/Support/TargetRegistry.h" 34 #include "llvm/Support/TargetSelect.h" 35 #include "llvm/Target/TargetMachine.h" 36 #include "llvm/Transforms/IPO/PassManagerBuilder.h" 37 #include "llvm/Transforms/Utils/BasicBlockUtils.h" 38 39 #include "isl/union_map.h" 40 41 extern "C" { 42 #include "ppcg/cuda.h" 43 #include "ppcg/gpu.h" 44 #include "ppcg/gpu_print.h" 45 #include "ppcg/ppcg.h" 46 #include "ppcg/schedule.h" 47 } 48 49 #include "llvm/Support/Debug.h" 50 51 using namespace polly; 52 using namespace llvm; 53 54 #define DEBUG_TYPE "polly-codegen-ppcg" 55 56 static cl::opt<bool> DumpSchedule("polly-acc-dump-schedule", 57 cl::desc("Dump the computed GPU Schedule"), 58 cl::Hidden, cl::init(false), cl::ZeroOrMore, 59 cl::cat(PollyCategory)); 60 61 static cl::opt<bool> 62 DumpCode("polly-acc-dump-code", 63 cl::desc("Dump C code describing the GPU mapping"), cl::Hidden, 64 cl::init(false), cl::ZeroOrMore, cl::cat(PollyCategory)); 65 66 static cl::opt<bool> DumpKernelIR("polly-acc-dump-kernel-ir", 67 cl::desc("Dump the kernel LLVM-IR"), 68 cl::Hidden, cl::init(false), cl::ZeroOrMore, 69 cl::cat(PollyCategory)); 70 71 static cl::opt<bool> DumpKernelASM("polly-acc-dump-kernel-asm", 72 cl::desc("Dump the kernel assembly code"), 73 cl::Hidden, cl::init(false), cl::ZeroOrMore, 74 cl::cat(PollyCategory)); 75 76 static cl::opt<bool> FastMath("polly-acc-fastmath", 77 cl::desc("Allow unsafe math optimizations"), 78 cl::Hidden, cl::init(false), cl::ZeroOrMore, 79 cl::cat(PollyCategory)); 80 static cl::opt<bool> SharedMemory("polly-acc-use-shared", 81 cl::desc("Use shared memory"), cl::Hidden, 82 cl::init(false), cl::ZeroOrMore, 83 cl::cat(PollyCategory)); 84 static cl::opt<bool> PrivateMemory("polly-acc-use-private", 85 cl::desc("Use private memory"), cl::Hidden, 86 cl::init(false), cl::ZeroOrMore, 87 cl::cat(PollyCategory)); 88 89 static cl::opt<std::string> 90 CudaVersion("polly-acc-cuda-version", 91 cl::desc("The CUDA version to compile for"), cl::Hidden, 92 cl::init("sm_30"), cl::ZeroOrMore, cl::cat(PollyCategory)); 93 94 static cl::opt<int> 95 MinCompute("polly-acc-mincompute", 96 cl::desc("Minimal number of compute statements to run on GPU."), 97 cl::Hidden, cl::init(10 * 512 * 512)); 98 99 /// Create the ast expressions for a ScopStmt. 100 /// 101 /// This function is a callback for to generate the ast expressions for each 102 /// of the scheduled ScopStmts. 103 static __isl_give isl_id_to_ast_expr *pollyBuildAstExprForStmt( 104 void *StmtT, isl_ast_build *Build, 105 isl_multi_pw_aff *(*FunctionIndex)(__isl_take isl_multi_pw_aff *MPA, 106 isl_id *Id, void *User), 107 void *UserIndex, 108 isl_ast_expr *(*FunctionExpr)(isl_ast_expr *Expr, isl_id *Id, void *User), 109 void *UserExpr) { 110 111 ScopStmt *Stmt = (ScopStmt *)StmtT; 112 113 isl_ctx *Ctx; 114 115 if (!Stmt || !Build) 116 return NULL; 117 118 Ctx = isl_ast_build_get_ctx(Build); 119 isl_id_to_ast_expr *RefToExpr = isl_id_to_ast_expr_alloc(Ctx, 0); 120 121 for (MemoryAccess *Acc : *Stmt) { 122 isl_map *AddrFunc = Acc->getAddressFunction(); 123 AddrFunc = isl_map_intersect_domain(AddrFunc, Stmt->getDomain()); 124 isl_id *RefId = Acc->getId(); 125 isl_pw_multi_aff *PMA = isl_pw_multi_aff_from_map(AddrFunc); 126 isl_multi_pw_aff *MPA = isl_multi_pw_aff_from_pw_multi_aff(PMA); 127 MPA = isl_multi_pw_aff_coalesce(MPA); 128 MPA = FunctionIndex(MPA, RefId, UserIndex); 129 isl_ast_expr *Access = isl_ast_build_access_from_multi_pw_aff(Build, MPA); 130 Access = FunctionExpr(Access, RefId, UserExpr); 131 RefToExpr = isl_id_to_ast_expr_set(RefToExpr, RefId, Access); 132 } 133 134 return RefToExpr; 135 } 136 137 /// Generate code for a GPU specific isl AST. 138 /// 139 /// The GPUNodeBuilder augments the general existing IslNodeBuilder, which 140 /// generates code for general-prupose AST nodes, with special functionality 141 /// for generating GPU specific user nodes. 142 /// 143 /// @see GPUNodeBuilder::createUser 144 class GPUNodeBuilder : public IslNodeBuilder { 145 public: 146 GPUNodeBuilder(PollyIRBuilder &Builder, ScopAnnotator &Annotator, 147 const DataLayout &DL, LoopInfo &LI, ScalarEvolution &SE, 148 DominatorTree &DT, Scop &S, BasicBlock *StartBlock, 149 gpu_prog *Prog) 150 : IslNodeBuilder(Builder, Annotator, DL, LI, SE, DT, S, StartBlock), 151 Prog(Prog) { 152 getExprBuilder().setIDToSAI(&IDToSAI); 153 } 154 155 /// Create after-run-time-check initialization code. 156 void initializeAfterRTH(); 157 158 /// Finalize the generated scop. 159 virtual void finalize(); 160 161 /// Track if the full build process was successful. 162 /// 163 /// This value is set to false, if throughout the build process an error 164 /// occurred which prevents us from generating valid GPU code. 165 bool BuildSuccessful = true; 166 167 /// The maximal number of loops surrounding a sequential kernel. 168 unsigned DeepestSequential = 0; 169 170 /// The maximal number of loops surrounding a parallel kernel. 171 unsigned DeepestParallel = 0; 172 173 private: 174 /// A vector of array base pointers for which a new ScopArrayInfo was created. 175 /// 176 /// This vector is used to delete the ScopArrayInfo when it is not needed any 177 /// more. 178 std::vector<Value *> LocalArrays; 179 180 /// A map from ScopArrays to their corresponding device allocations. 181 std::map<ScopArrayInfo *, Value *> DeviceAllocations; 182 183 /// The current GPU context. 184 Value *GPUContext; 185 186 /// The set of isl_ids allocated in the kernel 187 std::vector<isl_id *> KernelIds; 188 189 /// A module containing GPU code. 190 /// 191 /// This pointer is only set in case we are currently generating GPU code. 192 std::unique_ptr<Module> GPUModule; 193 194 /// The GPU program we generate code for. 195 gpu_prog *Prog; 196 197 /// Class to free isl_ids. 198 class IslIdDeleter { 199 public: 200 void operator()(__isl_take isl_id *Id) { isl_id_free(Id); }; 201 }; 202 203 /// A set containing all isl_ids allocated in a GPU kernel. 204 /// 205 /// By releasing this set all isl_ids will be freed. 206 std::set<std::unique_ptr<isl_id, IslIdDeleter>> KernelIDs; 207 208 IslExprBuilder::IDToScopArrayInfoTy IDToSAI; 209 210 /// Create code for user-defined AST nodes. 211 /// 212 /// These AST nodes can be of type: 213 /// 214 /// - ScopStmt: A computational statement (TODO) 215 /// - Kernel: A GPU kernel call (TODO) 216 /// - Data-Transfer: A GPU <-> CPU data-transfer 217 /// - In-kernel synchronization 218 /// - In-kernel memory copy statement 219 /// 220 /// @param UserStmt The ast node to generate code for. 221 virtual void createUser(__isl_take isl_ast_node *UserStmt); 222 223 enum DataDirection { HOST_TO_DEVICE, DEVICE_TO_HOST }; 224 225 /// Create code for a data transfer statement 226 /// 227 /// @param TransferStmt The data transfer statement. 228 /// @param Direction The direction in which to transfer data. 229 void createDataTransfer(__isl_take isl_ast_node *TransferStmt, 230 enum DataDirection Direction); 231 232 /// Find llvm::Values referenced in GPU kernel. 233 /// 234 /// @param Kernel The kernel to scan for llvm::Values 235 /// 236 /// @returns A set of values referenced by the kernel. 237 SetVector<Value *> getReferencesInKernel(ppcg_kernel *Kernel); 238 239 /// Compute the sizes of the execution grid for a given kernel. 240 /// 241 /// @param Kernel The kernel to compute grid sizes for. 242 /// 243 /// @returns A tuple with grid sizes for X and Y dimension 244 std::tuple<Value *, Value *> getGridSizes(ppcg_kernel *Kernel); 245 246 /// Compute the sizes of the thread blocks for a given kernel. 247 /// 248 /// @param Kernel The kernel to compute thread block sizes for. 249 /// 250 /// @returns A tuple with thread block sizes for X, Y, and Z dimensions. 251 std::tuple<Value *, Value *, Value *> getBlockSizes(ppcg_kernel *Kernel); 252 253 /// Create kernel launch parameters. 254 /// 255 /// @param Kernel The kernel to create parameters for. 256 /// @param F The kernel function that has been created. 257 /// @param SubtreeValues The set of llvm::Values referenced by this kernel. 258 /// 259 /// @returns A stack allocated array with pointers to the parameter 260 /// values that are passed to the kernel. 261 Value *createLaunchParameters(ppcg_kernel *Kernel, Function *F, 262 SetVector<Value *> SubtreeValues); 263 264 /// Create declarations for kernel variable. 265 /// 266 /// This includes shared memory declarations. 267 /// 268 /// @param Kernel The kernel definition to create variables for. 269 /// @param FN The function into which to generate the variables. 270 void createKernelVariables(ppcg_kernel *Kernel, Function *FN); 271 272 /// Add CUDA annotations to module. 273 /// 274 /// Add a set of CUDA annotations that declares the maximal block dimensions 275 /// that will be used to execute the CUDA kernel. This allows the NVIDIA 276 /// PTX compiler to bound the number of allocated registers to ensure the 277 /// resulting kernel is known to run with up to as many block dimensions 278 /// as specified here. 279 /// 280 /// @param M The module to add the annotations to. 281 /// @param BlockDimX The size of block dimension X. 282 /// @param BlockDimY The size of block dimension Y. 283 /// @param BlockDimZ The size of block dimension Z. 284 void addCUDAAnnotations(Module *M, Value *BlockDimX, Value *BlockDimY, 285 Value *BlockDimZ); 286 287 /// Create GPU kernel. 288 /// 289 /// Code generate the kernel described by @p KernelStmt. 290 /// 291 /// @param KernelStmt The ast node to generate kernel code for. 292 void createKernel(__isl_take isl_ast_node *KernelStmt); 293 294 /// Generate code that computes the size of an array. 295 /// 296 /// @param Array The array for which to compute a size. 297 Value *getArraySize(gpu_array_info *Array); 298 299 /// Generate code to compute the minimal offset at which an array is accessed. 300 /// 301 /// The offset of an array is the minimal array location accessed in a scop. 302 /// 303 /// Example: 304 /// 305 /// for (long i = 0; i < 100; i++) 306 /// A[i + 42] += ... 307 /// 308 /// getArrayOffset(A) results in 42. 309 /// 310 /// @param Array The array for which to compute the offset. 311 /// @returns An llvm::Value that contains the offset of the array. 312 Value *getArrayOffset(gpu_array_info *Array); 313 314 /// Prepare the kernel arguments for kernel code generation 315 /// 316 /// @param Kernel The kernel to generate code for. 317 /// @param FN The function created for the kernel. 318 void prepareKernelArguments(ppcg_kernel *Kernel, Function *FN); 319 320 /// Create kernel function. 321 /// 322 /// Create a kernel function located in a newly created module that can serve 323 /// as target for device code generation. Set the Builder to point to the 324 /// start block of this newly created function. 325 /// 326 /// @param Kernel The kernel to generate code for. 327 /// @param SubtreeValues The set of llvm::Values referenced by this kernel. 328 void createKernelFunction(ppcg_kernel *Kernel, 329 SetVector<Value *> &SubtreeValues); 330 331 /// Create the declaration of a kernel function. 332 /// 333 /// The kernel function takes as arguments: 334 /// 335 /// - One i8 pointer for each external array reference used in the kernel. 336 /// - Host iterators 337 /// - Parameters 338 /// - Other LLVM Value references (TODO) 339 /// 340 /// @param Kernel The kernel to generate the function declaration for. 341 /// @param SubtreeValues The set of llvm::Values referenced by this kernel. 342 /// 343 /// @returns The newly declared function. 344 Function *createKernelFunctionDecl(ppcg_kernel *Kernel, 345 SetVector<Value *> &SubtreeValues); 346 347 /// Insert intrinsic functions to obtain thread and block ids. 348 /// 349 /// @param The kernel to generate the intrinsic functions for. 350 void insertKernelIntrinsics(ppcg_kernel *Kernel); 351 352 /// Create a global-to-shared or shared-to-global copy statement. 353 /// 354 /// @param CopyStmt The copy statement to generate code for 355 void createKernelCopy(ppcg_kernel_stmt *CopyStmt); 356 357 /// Create code for a ScopStmt called in @p Expr. 358 /// 359 /// @param Expr The expression containing the call. 360 /// @param KernelStmt The kernel statement referenced in the call. 361 void createScopStmt(isl_ast_expr *Expr, ppcg_kernel_stmt *KernelStmt); 362 363 /// Create an in-kernel synchronization call. 364 void createKernelSync(); 365 366 /// Create a PTX assembly string for the current GPU kernel. 367 /// 368 /// @returns A string containing the corresponding PTX assembly code. 369 std::string createKernelASM(); 370 371 /// Remove references from the dominator tree to the kernel function @p F. 372 /// 373 /// @param F The function to remove references to. 374 void clearDominators(Function *F); 375 376 /// Remove references from scalar evolution to the kernel function @p F. 377 /// 378 /// @param F The function to remove references to. 379 void clearScalarEvolution(Function *F); 380 381 /// Remove references from loop info to the kernel function @p F. 382 /// 383 /// @param F The function to remove references to. 384 void clearLoops(Function *F); 385 386 /// Finalize the generation of the kernel function. 387 /// 388 /// Free the LLVM-IR module corresponding to the kernel and -- if requested -- 389 /// dump its IR to stderr. 390 /// 391 /// @returns The Assembly string of the kernel. 392 std::string finalizeKernelFunction(); 393 394 /// Finalize the generation of the kernel arguments. 395 /// 396 /// This function ensures that not-read-only scalars used in a kernel are 397 /// stored back to the global memory location they ared backed up with before 398 /// the kernel terminates. 399 /// 400 /// @params Kernel The kernel to finalize kernel arguments for. 401 void finalizeKernelArguments(ppcg_kernel *Kernel); 402 403 /// Create code that allocates memory to store arrays on device. 404 void allocateDeviceArrays(); 405 406 /// Free all allocated device arrays. 407 void freeDeviceArrays(); 408 409 /// Create a call to initialize the GPU context. 410 /// 411 /// @returns A pointer to the newly initialized context. 412 Value *createCallInitContext(); 413 414 /// Create a call to get the device pointer for a kernel allocation. 415 /// 416 /// @param Allocation The Polly GPU allocation 417 /// 418 /// @returns The device parameter corresponding to this allocation. 419 Value *createCallGetDevicePtr(Value *Allocation); 420 421 /// Create a call to free the GPU context. 422 /// 423 /// @param Context A pointer to an initialized GPU context. 424 void createCallFreeContext(Value *Context); 425 426 /// Create a call to allocate memory on the device. 427 /// 428 /// @param Size The size of memory to allocate 429 /// 430 /// @returns A pointer that identifies this allocation. 431 Value *createCallAllocateMemoryForDevice(Value *Size); 432 433 /// Create a call to free a device array. 434 /// 435 /// @param Array The device array to free. 436 void createCallFreeDeviceMemory(Value *Array); 437 438 /// Create a call to copy data from host to device. 439 /// 440 /// @param HostPtr A pointer to the host data that should be copied. 441 /// @param DevicePtr A device pointer specifying the location to copy to. 442 void createCallCopyFromHostToDevice(Value *HostPtr, Value *DevicePtr, 443 Value *Size); 444 445 /// Create a call to copy data from device to host. 446 /// 447 /// @param DevicePtr A pointer to the device data that should be copied. 448 /// @param HostPtr A host pointer specifying the location to copy to. 449 void createCallCopyFromDeviceToHost(Value *DevicePtr, Value *HostPtr, 450 Value *Size); 451 452 /// Create a call to get a kernel from an assembly string. 453 /// 454 /// @param Buffer The string describing the kernel. 455 /// @param Entry The name of the kernel function to call. 456 /// 457 /// @returns A pointer to a kernel object 458 Value *createCallGetKernel(Value *Buffer, Value *Entry); 459 460 /// Create a call to free a GPU kernel. 461 /// 462 /// @param GPUKernel THe kernel to free. 463 void createCallFreeKernel(Value *GPUKernel); 464 465 /// Create a call to launch a GPU kernel. 466 /// 467 /// @param GPUKernel The kernel to launch. 468 /// @param GridDimX The size of the first grid dimension. 469 /// @param GridDimY The size of the second grid dimension. 470 /// @param GridBlockX The size of the first block dimension. 471 /// @param GridBlockY The size of the second block dimension. 472 /// @param GridBlockZ The size of the third block dimension. 473 /// @param Paramters A pointer to an array that contains itself pointers to 474 /// the parameter values passed for each kernel argument. 475 void createCallLaunchKernel(Value *GPUKernel, Value *GridDimX, 476 Value *GridDimY, Value *BlockDimX, 477 Value *BlockDimY, Value *BlockDimZ, 478 Value *Parameters); 479 }; 480 481 void GPUNodeBuilder::initializeAfterRTH() { 482 BasicBlock *NewBB = SplitBlock(Builder.GetInsertBlock(), 483 &*Builder.GetInsertPoint(), &DT, &LI); 484 NewBB->setName("polly.acc.initialize"); 485 Builder.SetInsertPoint(&NewBB->front()); 486 487 GPUContext = createCallInitContext(); 488 allocateDeviceArrays(); 489 } 490 491 void GPUNodeBuilder::finalize() { 492 freeDeviceArrays(); 493 createCallFreeContext(GPUContext); 494 IslNodeBuilder::finalize(); 495 } 496 497 void GPUNodeBuilder::allocateDeviceArrays() { 498 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 499 500 for (int i = 0; i < Prog->n_array; ++i) { 501 gpu_array_info *Array = &Prog->array[i]; 502 auto *ScopArray = (ScopArrayInfo *)Array->user; 503 std::string DevArrayName("p_dev_array_"); 504 DevArrayName.append(Array->name); 505 506 Value *ArraySize = getArraySize(Array); 507 Value *Offset = getArrayOffset(Array); 508 if (Offset) 509 ArraySize = Builder.CreateSub( 510 ArraySize, 511 Builder.CreateMul(Offset, 512 Builder.getInt64(ScopArray->getElemSizeInBytes()))); 513 Value *DevArray = createCallAllocateMemoryForDevice(ArraySize); 514 DevArray->setName(DevArrayName); 515 DeviceAllocations[ScopArray] = DevArray; 516 } 517 518 isl_ast_build_free(Build); 519 } 520 521 void GPUNodeBuilder::addCUDAAnnotations(Module *M, Value *BlockDimX, 522 Value *BlockDimY, Value *BlockDimZ) { 523 auto AnnotationNode = M->getOrInsertNamedMetadata("nvvm.annotations"); 524 525 for (auto &F : *M) { 526 if (F.getCallingConv() != CallingConv::PTX_Kernel) 527 continue; 528 529 Value *V[] = {BlockDimX, BlockDimY, BlockDimZ}; 530 531 Metadata *Elements[] = { 532 ValueAsMetadata::get(&F), MDString::get(M->getContext(), "maxntidx"), 533 ValueAsMetadata::get(V[0]), MDString::get(M->getContext(), "maxntidy"), 534 ValueAsMetadata::get(V[1]), MDString::get(M->getContext(), "maxntidz"), 535 ValueAsMetadata::get(V[2]), 536 }; 537 MDNode *Node = MDNode::get(M->getContext(), Elements); 538 AnnotationNode->addOperand(Node); 539 } 540 } 541 542 void GPUNodeBuilder::freeDeviceArrays() { 543 for (auto &Array : DeviceAllocations) 544 createCallFreeDeviceMemory(Array.second); 545 } 546 547 Value *GPUNodeBuilder::createCallGetKernel(Value *Buffer, Value *Entry) { 548 const char *Name = "polly_getKernel"; 549 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 550 Function *F = M->getFunction(Name); 551 552 // If F is not available, declare it. 553 if (!F) { 554 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 555 std::vector<Type *> Args; 556 Args.push_back(Builder.getInt8PtrTy()); 557 Args.push_back(Builder.getInt8PtrTy()); 558 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 559 F = Function::Create(Ty, Linkage, Name, M); 560 } 561 562 return Builder.CreateCall(F, {Buffer, Entry}); 563 } 564 565 Value *GPUNodeBuilder::createCallGetDevicePtr(Value *Allocation) { 566 const char *Name = "polly_getDevicePtr"; 567 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 568 Function *F = M->getFunction(Name); 569 570 // If F is not available, declare it. 571 if (!F) { 572 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 573 std::vector<Type *> Args; 574 Args.push_back(Builder.getInt8PtrTy()); 575 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 576 F = Function::Create(Ty, Linkage, Name, M); 577 } 578 579 return Builder.CreateCall(F, {Allocation}); 580 } 581 582 void GPUNodeBuilder::createCallLaunchKernel(Value *GPUKernel, Value *GridDimX, 583 Value *GridDimY, Value *BlockDimX, 584 Value *BlockDimY, Value *BlockDimZ, 585 Value *Parameters) { 586 const char *Name = "polly_launchKernel"; 587 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 588 Function *F = M->getFunction(Name); 589 590 // If F is not available, declare it. 591 if (!F) { 592 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 593 std::vector<Type *> Args; 594 Args.push_back(Builder.getInt8PtrTy()); 595 Args.push_back(Builder.getInt32Ty()); 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.getInt8PtrTy()); 601 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 602 F = Function::Create(Ty, Linkage, Name, M); 603 } 604 605 Builder.CreateCall(F, {GPUKernel, GridDimX, GridDimY, BlockDimX, BlockDimY, 606 BlockDimZ, Parameters}); 607 } 608 609 void GPUNodeBuilder::createCallFreeKernel(Value *GPUKernel) { 610 const char *Name = "polly_freeKernel"; 611 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 612 Function *F = M->getFunction(Name); 613 614 // If F is not available, declare it. 615 if (!F) { 616 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 617 std::vector<Type *> Args; 618 Args.push_back(Builder.getInt8PtrTy()); 619 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 620 F = Function::Create(Ty, Linkage, Name, M); 621 } 622 623 Builder.CreateCall(F, {GPUKernel}); 624 } 625 626 void GPUNodeBuilder::createCallFreeDeviceMemory(Value *Array) { 627 const char *Name = "polly_freeDeviceMemory"; 628 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 629 Function *F = M->getFunction(Name); 630 631 // If F is not available, declare it. 632 if (!F) { 633 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 634 std::vector<Type *> Args; 635 Args.push_back(Builder.getInt8PtrTy()); 636 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 637 F = Function::Create(Ty, Linkage, Name, M); 638 } 639 640 Builder.CreateCall(F, {Array}); 641 } 642 643 Value *GPUNodeBuilder::createCallAllocateMemoryForDevice(Value *Size) { 644 const char *Name = "polly_allocateMemoryForDevice"; 645 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 646 Function *F = M->getFunction(Name); 647 648 // If F is not available, declare it. 649 if (!F) { 650 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 651 std::vector<Type *> Args; 652 Args.push_back(Builder.getInt64Ty()); 653 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 654 F = Function::Create(Ty, Linkage, Name, M); 655 } 656 657 return Builder.CreateCall(F, {Size}); 658 } 659 660 void GPUNodeBuilder::createCallCopyFromHostToDevice(Value *HostData, 661 Value *DeviceData, 662 Value *Size) { 663 const char *Name = "polly_copyFromHostToDevice"; 664 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 665 Function *F = M->getFunction(Name); 666 667 // If F is not available, declare it. 668 if (!F) { 669 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 670 std::vector<Type *> Args; 671 Args.push_back(Builder.getInt8PtrTy()); 672 Args.push_back(Builder.getInt8PtrTy()); 673 Args.push_back(Builder.getInt64Ty()); 674 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 675 F = Function::Create(Ty, Linkage, Name, M); 676 } 677 678 Builder.CreateCall(F, {HostData, DeviceData, Size}); 679 } 680 681 void GPUNodeBuilder::createCallCopyFromDeviceToHost(Value *DeviceData, 682 Value *HostData, 683 Value *Size) { 684 const char *Name = "polly_copyFromDeviceToHost"; 685 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 686 Function *F = M->getFunction(Name); 687 688 // If F is not available, declare it. 689 if (!F) { 690 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 691 std::vector<Type *> Args; 692 Args.push_back(Builder.getInt8PtrTy()); 693 Args.push_back(Builder.getInt8PtrTy()); 694 Args.push_back(Builder.getInt64Ty()); 695 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 696 F = Function::Create(Ty, Linkage, Name, M); 697 } 698 699 Builder.CreateCall(F, {DeviceData, HostData, Size}); 700 } 701 702 Value *GPUNodeBuilder::createCallInitContext() { 703 const char *Name = "polly_initContext"; 704 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 705 Function *F = M->getFunction(Name); 706 707 // If F is not available, declare it. 708 if (!F) { 709 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 710 std::vector<Type *> Args; 711 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 712 F = Function::Create(Ty, Linkage, Name, M); 713 } 714 715 return Builder.CreateCall(F, {}); 716 } 717 718 void GPUNodeBuilder::createCallFreeContext(Value *Context) { 719 const char *Name = "polly_freeContext"; 720 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 721 Function *F = M->getFunction(Name); 722 723 // If F is not available, declare it. 724 if (!F) { 725 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 726 std::vector<Type *> Args; 727 Args.push_back(Builder.getInt8PtrTy()); 728 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 729 F = Function::Create(Ty, Linkage, Name, M); 730 } 731 732 Builder.CreateCall(F, {Context}); 733 } 734 735 /// Check if one string is a prefix of another. 736 /// 737 /// @param String The string in which to look for the prefix. 738 /// @param Prefix The prefix to look for. 739 static bool isPrefix(std::string String, std::string Prefix) { 740 return String.find(Prefix) == 0; 741 } 742 743 Value *GPUNodeBuilder::getArraySize(gpu_array_info *Array) { 744 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 745 Value *ArraySize = ConstantInt::get(Builder.getInt64Ty(), Array->size); 746 747 if (!gpu_array_is_scalar(Array)) { 748 auto OffsetDimZero = isl_pw_aff_copy(Array->bound[0]); 749 isl_ast_expr *Res = isl_ast_build_expr_from_pw_aff(Build, OffsetDimZero); 750 751 for (unsigned int i = 1; i < Array->n_index; i++) { 752 isl_pw_aff *Bound_I = isl_pw_aff_copy(Array->bound[i]); 753 isl_ast_expr *Expr = isl_ast_build_expr_from_pw_aff(Build, Bound_I); 754 Res = isl_ast_expr_mul(Res, Expr); 755 } 756 757 Value *NumElements = ExprBuilder.create(Res); 758 if (NumElements->getType() != ArraySize->getType()) 759 NumElements = Builder.CreateSExt(NumElements, ArraySize->getType()); 760 ArraySize = Builder.CreateMul(ArraySize, NumElements); 761 } 762 isl_ast_build_free(Build); 763 return ArraySize; 764 } 765 766 Value *GPUNodeBuilder::getArrayOffset(gpu_array_info *Array) { 767 if (gpu_array_is_scalar(Array)) 768 return nullptr; 769 770 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 771 772 isl_set *Min = isl_set_lexmin(isl_set_copy(Array->extent)); 773 774 isl_set *ZeroSet = isl_set_universe(isl_set_get_space(Min)); 775 776 for (long i = 0; i < isl_set_dim(Min, isl_dim_set); i++) 777 ZeroSet = isl_set_fix_si(ZeroSet, isl_dim_set, i, 0); 778 779 if (isl_set_is_subset(Min, ZeroSet)) { 780 isl_set_free(Min); 781 isl_set_free(ZeroSet); 782 isl_ast_build_free(Build); 783 return nullptr; 784 } 785 isl_set_free(ZeroSet); 786 787 isl_ast_expr *Result = 788 isl_ast_expr_from_val(isl_val_int_from_si(isl_set_get_ctx(Min), 0)); 789 790 for (long i = 0; i < isl_set_dim(Min, isl_dim_set); i++) { 791 if (i > 0) { 792 isl_pw_aff *Bound_I = isl_pw_aff_copy(Array->bound[i - 1]); 793 isl_ast_expr *BExpr = isl_ast_build_expr_from_pw_aff(Build, Bound_I); 794 Result = isl_ast_expr_mul(Result, BExpr); 795 } 796 isl_pw_aff *DimMin = isl_set_dim_min(isl_set_copy(Min), i); 797 isl_ast_expr *MExpr = isl_ast_build_expr_from_pw_aff(Build, DimMin); 798 Result = isl_ast_expr_add(Result, MExpr); 799 } 800 801 Value *ResultValue = ExprBuilder.create(Result); 802 isl_set_free(Min); 803 isl_ast_build_free(Build); 804 805 return ResultValue; 806 } 807 808 void GPUNodeBuilder::createDataTransfer(__isl_take isl_ast_node *TransferStmt, 809 enum DataDirection Direction) { 810 isl_ast_expr *Expr = isl_ast_node_user_get_expr(TransferStmt); 811 isl_ast_expr *Arg = isl_ast_expr_get_op_arg(Expr, 0); 812 isl_id *Id = isl_ast_expr_get_id(Arg); 813 auto Array = (gpu_array_info *)isl_id_get_user(Id); 814 auto ScopArray = (ScopArrayInfo *)(Array->user); 815 816 Value *Size = getArraySize(Array); 817 Value *Offset = getArrayOffset(Array); 818 Value *DevPtr = DeviceAllocations[ScopArray]; 819 820 Value *HostPtr; 821 822 if (gpu_array_is_scalar(Array)) 823 HostPtr = BlockGen.getOrCreateAlloca(ScopArray); 824 else 825 HostPtr = ScopArray->getBasePtr(); 826 827 if (Offset) { 828 HostPtr = Builder.CreatePointerCast( 829 HostPtr, ScopArray->getElementType()->getPointerTo()); 830 HostPtr = Builder.CreateGEP(HostPtr, Offset); 831 } 832 833 HostPtr = Builder.CreatePointerCast(HostPtr, Builder.getInt8PtrTy()); 834 835 if (Offset) { 836 Size = Builder.CreateSub( 837 Size, Builder.CreateMul( 838 Offset, Builder.getInt64(ScopArray->getElemSizeInBytes()))); 839 } 840 841 if (Direction == HOST_TO_DEVICE) 842 createCallCopyFromHostToDevice(HostPtr, DevPtr, Size); 843 else 844 createCallCopyFromDeviceToHost(DevPtr, HostPtr, Size); 845 846 isl_id_free(Id); 847 isl_ast_expr_free(Arg); 848 isl_ast_expr_free(Expr); 849 isl_ast_node_free(TransferStmt); 850 } 851 852 void GPUNodeBuilder::createUser(__isl_take isl_ast_node *UserStmt) { 853 isl_ast_expr *Expr = isl_ast_node_user_get_expr(UserStmt); 854 isl_ast_expr *StmtExpr = isl_ast_expr_get_op_arg(Expr, 0); 855 isl_id *Id = isl_ast_expr_get_id(StmtExpr); 856 isl_id_free(Id); 857 isl_ast_expr_free(StmtExpr); 858 859 const char *Str = isl_id_get_name(Id); 860 if (!strcmp(Str, "kernel")) { 861 createKernel(UserStmt); 862 isl_ast_expr_free(Expr); 863 return; 864 } 865 866 if (isPrefix(Str, "to_device")) { 867 createDataTransfer(UserStmt, HOST_TO_DEVICE); 868 isl_ast_expr_free(Expr); 869 return; 870 } 871 872 if (isPrefix(Str, "from_device")) { 873 createDataTransfer(UserStmt, DEVICE_TO_HOST); 874 isl_ast_expr_free(Expr); 875 return; 876 } 877 878 isl_id *Anno = isl_ast_node_get_annotation(UserStmt); 879 struct ppcg_kernel_stmt *KernelStmt = 880 (struct ppcg_kernel_stmt *)isl_id_get_user(Anno); 881 isl_id_free(Anno); 882 883 switch (KernelStmt->type) { 884 case ppcg_kernel_domain: 885 createScopStmt(Expr, KernelStmt); 886 isl_ast_node_free(UserStmt); 887 return; 888 case ppcg_kernel_copy: 889 createKernelCopy(KernelStmt); 890 isl_ast_expr_free(Expr); 891 isl_ast_node_free(UserStmt); 892 return; 893 case ppcg_kernel_sync: 894 createKernelSync(); 895 isl_ast_expr_free(Expr); 896 isl_ast_node_free(UserStmt); 897 return; 898 } 899 900 isl_ast_expr_free(Expr); 901 isl_ast_node_free(UserStmt); 902 return; 903 } 904 void GPUNodeBuilder::createKernelCopy(ppcg_kernel_stmt *KernelStmt) { 905 isl_ast_expr *LocalIndex = isl_ast_expr_copy(KernelStmt->u.c.local_index); 906 LocalIndex = isl_ast_expr_address_of(LocalIndex); 907 Value *LocalAddr = ExprBuilder.create(LocalIndex); 908 isl_ast_expr *Index = isl_ast_expr_copy(KernelStmt->u.c.index); 909 Index = isl_ast_expr_address_of(Index); 910 Value *GlobalAddr = ExprBuilder.create(Index); 911 912 if (KernelStmt->u.c.read) { 913 LoadInst *Load = Builder.CreateLoad(GlobalAddr, "shared.read"); 914 Builder.CreateStore(Load, LocalAddr); 915 } else { 916 LoadInst *Load = Builder.CreateLoad(LocalAddr, "shared.write"); 917 Builder.CreateStore(Load, GlobalAddr); 918 } 919 } 920 921 void GPUNodeBuilder::createScopStmt(isl_ast_expr *Expr, 922 ppcg_kernel_stmt *KernelStmt) { 923 auto Stmt = (ScopStmt *)KernelStmt->u.d.stmt->stmt; 924 isl_id_to_ast_expr *Indexes = KernelStmt->u.d.ref2expr; 925 926 LoopToScevMapT LTS; 927 LTS.insert(OutsideLoopIterations.begin(), OutsideLoopIterations.end()); 928 929 createSubstitutions(Expr, Stmt, LTS); 930 931 if (Stmt->isBlockStmt()) 932 BlockGen.copyStmt(*Stmt, LTS, Indexes); 933 else 934 RegionGen.copyStmt(*Stmt, LTS, Indexes); 935 } 936 937 void GPUNodeBuilder::createKernelSync() { 938 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 939 auto *Sync = Intrinsic::getDeclaration(M, Intrinsic::nvvm_barrier0); 940 Builder.CreateCall(Sync, {}); 941 } 942 943 /// Collect llvm::Values referenced from @p Node 944 /// 945 /// This function only applies to isl_ast_nodes that are user_nodes referring 946 /// to a ScopStmt. All other node types are ignore. 947 /// 948 /// @param Node The node to collect references for. 949 /// @param User A user pointer used as storage for the data that is collected. 950 /// 951 /// @returns isl_bool_true if data could be collected successfully. 952 isl_bool collectReferencesInGPUStmt(__isl_keep isl_ast_node *Node, void *User) { 953 if (isl_ast_node_get_type(Node) != isl_ast_node_user) 954 return isl_bool_true; 955 956 isl_ast_expr *Expr = isl_ast_node_user_get_expr(Node); 957 isl_ast_expr *StmtExpr = isl_ast_expr_get_op_arg(Expr, 0); 958 isl_id *Id = isl_ast_expr_get_id(StmtExpr); 959 const char *Str = isl_id_get_name(Id); 960 isl_id_free(Id); 961 isl_ast_expr_free(StmtExpr); 962 isl_ast_expr_free(Expr); 963 964 if (!isPrefix(Str, "Stmt")) 965 return isl_bool_true; 966 967 Id = isl_ast_node_get_annotation(Node); 968 auto *KernelStmt = (ppcg_kernel_stmt *)isl_id_get_user(Id); 969 auto Stmt = (ScopStmt *)KernelStmt->u.d.stmt->stmt; 970 isl_id_free(Id); 971 972 addReferencesFromStmt(Stmt, User, false /* CreateScalarRefs */); 973 974 return isl_bool_true; 975 } 976 977 SetVector<Value *> GPUNodeBuilder::getReferencesInKernel(ppcg_kernel *Kernel) { 978 SetVector<Value *> SubtreeValues; 979 SetVector<const SCEV *> SCEVs; 980 SetVector<const Loop *> Loops; 981 SubtreeReferences References = { 982 LI, SE, S, ValueMap, SubtreeValues, SCEVs, getBlockGenerator()}; 983 984 for (const auto &I : IDToValue) 985 SubtreeValues.insert(I.second); 986 987 isl_ast_node_foreach_descendant_top_down( 988 Kernel->tree, collectReferencesInGPUStmt, &References); 989 990 for (const SCEV *Expr : SCEVs) 991 findValues(Expr, SE, SubtreeValues); 992 993 for (auto &SAI : S.arrays()) 994 SubtreeValues.remove(SAI->getBasePtr()); 995 996 isl_space *Space = S.getParamSpace(); 997 for (long i = 0; i < isl_space_dim(Space, isl_dim_param); i++) { 998 isl_id *Id = isl_space_get_dim_id(Space, isl_dim_param, i); 999 assert(IDToValue.count(Id)); 1000 Value *Val = IDToValue[Id]; 1001 SubtreeValues.remove(Val); 1002 isl_id_free(Id); 1003 } 1004 isl_space_free(Space); 1005 1006 for (long i = 0; i < isl_space_dim(Kernel->space, isl_dim_set); i++) { 1007 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1008 assert(IDToValue.count(Id)); 1009 Value *Val = IDToValue[Id]; 1010 SubtreeValues.remove(Val); 1011 isl_id_free(Id); 1012 } 1013 1014 return SubtreeValues; 1015 } 1016 1017 void GPUNodeBuilder::clearDominators(Function *F) { 1018 DomTreeNode *N = DT.getNode(&F->getEntryBlock()); 1019 std::vector<BasicBlock *> Nodes; 1020 for (po_iterator<DomTreeNode *> I = po_begin(N), E = po_end(N); I != E; ++I) 1021 Nodes.push_back(I->getBlock()); 1022 1023 for (BasicBlock *BB : Nodes) 1024 DT.eraseNode(BB); 1025 } 1026 1027 void GPUNodeBuilder::clearScalarEvolution(Function *F) { 1028 for (BasicBlock &BB : *F) { 1029 Loop *L = LI.getLoopFor(&BB); 1030 if (L) 1031 SE.forgetLoop(L); 1032 } 1033 } 1034 1035 void GPUNodeBuilder::clearLoops(Function *F) { 1036 for (BasicBlock &BB : *F) { 1037 Loop *L = LI.getLoopFor(&BB); 1038 if (L) 1039 SE.forgetLoop(L); 1040 LI.removeBlock(&BB); 1041 } 1042 } 1043 1044 std::tuple<Value *, Value *> GPUNodeBuilder::getGridSizes(ppcg_kernel *Kernel) { 1045 std::vector<Value *> Sizes; 1046 isl_ast_build *Context = isl_ast_build_from_context(S.getContext()); 1047 1048 for (long i = 0; i < Kernel->n_grid; i++) { 1049 isl_pw_aff *Size = isl_multi_pw_aff_get_pw_aff(Kernel->grid_size, i); 1050 isl_ast_expr *GridSize = isl_ast_build_expr_from_pw_aff(Context, Size); 1051 Value *Res = ExprBuilder.create(GridSize); 1052 Res = Builder.CreateTrunc(Res, Builder.getInt32Ty()); 1053 Sizes.push_back(Res); 1054 } 1055 isl_ast_build_free(Context); 1056 1057 for (long i = Kernel->n_grid; i < 3; i++) 1058 Sizes.push_back(ConstantInt::get(Builder.getInt32Ty(), 1)); 1059 1060 return std::make_tuple(Sizes[0], Sizes[1]); 1061 } 1062 1063 std::tuple<Value *, Value *, Value *> 1064 GPUNodeBuilder::getBlockSizes(ppcg_kernel *Kernel) { 1065 std::vector<Value *> Sizes; 1066 1067 for (long i = 0; i < Kernel->n_block; i++) { 1068 Value *Res = ConstantInt::get(Builder.getInt32Ty(), Kernel->block_dim[i]); 1069 Sizes.push_back(Res); 1070 } 1071 1072 for (long i = Kernel->n_block; i < 3; i++) 1073 Sizes.push_back(ConstantInt::get(Builder.getInt32Ty(), 1)); 1074 1075 return std::make_tuple(Sizes[0], Sizes[1], Sizes[2]); 1076 } 1077 1078 Value * 1079 GPUNodeBuilder::createLaunchParameters(ppcg_kernel *Kernel, Function *F, 1080 SetVector<Value *> SubtreeValues) { 1081 Type *ArrayTy = ArrayType::get(Builder.getInt8PtrTy(), 1082 std::distance(F->arg_begin(), F->arg_end())); 1083 1084 BasicBlock *EntryBlock = 1085 &Builder.GetInsertBlock()->getParent()->getEntryBlock(); 1086 std::string Launch = "polly_launch_" + std::to_string(Kernel->id); 1087 Instruction *Parameters = 1088 new AllocaInst(ArrayTy, Launch + "_params", EntryBlock->getTerminator()); 1089 1090 int Index = 0; 1091 for (long i = 0; i < Prog->n_array; i++) { 1092 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1093 continue; 1094 1095 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1096 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(Id); 1097 1098 Value *DevArray = DeviceAllocations[const_cast<ScopArrayInfo *>(SAI)]; 1099 DevArray = createCallGetDevicePtr(DevArray); 1100 1101 Value *Offset = getArrayOffset(&Prog->array[i]); 1102 1103 if (Offset) { 1104 DevArray = Builder.CreatePointerCast( 1105 DevArray, SAI->getElementType()->getPointerTo()); 1106 DevArray = Builder.CreateGEP(DevArray, Builder.CreateNeg(Offset)); 1107 DevArray = Builder.CreatePointerCast(DevArray, Builder.getInt8PtrTy()); 1108 } 1109 Value *Slot = Builder.CreateGEP( 1110 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1111 1112 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1113 Value *ValPtr = BlockGen.getOrCreateAlloca(SAI); 1114 Value *ValPtrCast = 1115 Builder.CreatePointerCast(ValPtr, Builder.getInt8PtrTy()); 1116 Builder.CreateStore(ValPtrCast, Slot); 1117 } else { 1118 Instruction *Param = new AllocaInst( 1119 Builder.getInt8PtrTy(), Launch + "_param_" + std::to_string(Index), 1120 EntryBlock->getTerminator()); 1121 Builder.CreateStore(DevArray, Param); 1122 Value *ParamTyped = 1123 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1124 Builder.CreateStore(ParamTyped, Slot); 1125 } 1126 Index++; 1127 } 1128 1129 int NumHostIters = isl_space_dim(Kernel->space, isl_dim_set); 1130 1131 for (long i = 0; i < NumHostIters; i++) { 1132 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1133 Value *Val = IDToValue[Id]; 1134 isl_id_free(Id); 1135 Instruction *Param = new AllocaInst( 1136 Val->getType(), Launch + "_param_" + std::to_string(Index), 1137 EntryBlock->getTerminator()); 1138 Builder.CreateStore(Val, Param); 1139 Value *Slot = Builder.CreateGEP( 1140 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1141 Value *ParamTyped = 1142 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1143 Builder.CreateStore(ParamTyped, Slot); 1144 Index++; 1145 } 1146 1147 int NumVars = isl_space_dim(Kernel->space, isl_dim_param); 1148 1149 for (long i = 0; i < NumVars; i++) { 1150 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1151 Value *Val = IDToValue[Id]; 1152 isl_id_free(Id); 1153 Instruction *Param = new AllocaInst( 1154 Val->getType(), Launch + "_param_" + std::to_string(Index), 1155 EntryBlock->getTerminator()); 1156 Builder.CreateStore(Val, Param); 1157 Value *Slot = Builder.CreateGEP( 1158 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1159 Value *ParamTyped = 1160 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1161 Builder.CreateStore(ParamTyped, Slot); 1162 Index++; 1163 } 1164 1165 for (auto Val : SubtreeValues) { 1166 Instruction *Param = new AllocaInst( 1167 Val->getType(), Launch + "_param_" + std::to_string(Index), 1168 EntryBlock->getTerminator()); 1169 Builder.CreateStore(Val, Param); 1170 Value *Slot = Builder.CreateGEP( 1171 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1172 Value *ParamTyped = 1173 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1174 Builder.CreateStore(ParamTyped, Slot); 1175 Index++; 1176 } 1177 1178 auto Location = EntryBlock->getTerminator(); 1179 return new BitCastInst(Parameters, Builder.getInt8PtrTy(), 1180 Launch + "_params_i8ptr", Location); 1181 } 1182 1183 void GPUNodeBuilder::createKernel(__isl_take isl_ast_node *KernelStmt) { 1184 isl_id *Id = isl_ast_node_get_annotation(KernelStmt); 1185 ppcg_kernel *Kernel = (ppcg_kernel *)isl_id_get_user(Id); 1186 isl_id_free(Id); 1187 isl_ast_node_free(KernelStmt); 1188 1189 if (Kernel->n_grid > 1) 1190 DeepestParallel = 1191 std::max(DeepestParallel, isl_space_dim(Kernel->space, isl_dim_set)); 1192 else 1193 DeepestSequential = 1194 std::max(DeepestSequential, isl_space_dim(Kernel->space, isl_dim_set)); 1195 1196 Value *BlockDimX, *BlockDimY, *BlockDimZ; 1197 std::tie(BlockDimX, BlockDimY, BlockDimZ) = getBlockSizes(Kernel); 1198 1199 SetVector<Value *> SubtreeValues = getReferencesInKernel(Kernel); 1200 1201 assert(Kernel->tree && "Device AST of kernel node is empty"); 1202 1203 Instruction &HostInsertPoint = *Builder.GetInsertPoint(); 1204 IslExprBuilder::IDToValueTy HostIDs = IDToValue; 1205 ValueMapT HostValueMap = ValueMap; 1206 BlockGenerator::AllocaMapTy HostScalarMap = ScalarMap; 1207 ScalarMap.clear(); 1208 1209 SetVector<const Loop *> Loops; 1210 1211 // Create for all loops we depend on values that contain the current loop 1212 // iteration. These values are necessary to generate code for SCEVs that 1213 // depend on such loops. As a result we need to pass them to the subfunction. 1214 for (const Loop *L : Loops) { 1215 const SCEV *OuterLIV = SE.getAddRecExpr(SE.getUnknown(Builder.getInt64(0)), 1216 SE.getUnknown(Builder.getInt64(1)), 1217 L, SCEV::FlagAnyWrap); 1218 Value *V = generateSCEV(OuterLIV); 1219 OutsideLoopIterations[L] = SE.getUnknown(V); 1220 SubtreeValues.insert(V); 1221 } 1222 1223 createKernelFunction(Kernel, SubtreeValues); 1224 1225 create(isl_ast_node_copy(Kernel->tree)); 1226 1227 finalizeKernelArguments(Kernel); 1228 Function *F = Builder.GetInsertBlock()->getParent(); 1229 addCUDAAnnotations(F->getParent(), BlockDimX, BlockDimY, BlockDimZ); 1230 clearDominators(F); 1231 clearScalarEvolution(F); 1232 clearLoops(F); 1233 1234 IDToValue = HostIDs; 1235 1236 ValueMap = std::move(HostValueMap); 1237 ScalarMap = std::move(HostScalarMap); 1238 EscapeMap.clear(); 1239 IDToSAI.clear(); 1240 Annotator.resetAlternativeAliasBases(); 1241 for (auto &BasePtr : LocalArrays) 1242 S.invalidateScopArrayInfo(BasePtr, MemoryKind::Array); 1243 LocalArrays.clear(); 1244 1245 std::string ASMString = finalizeKernelFunction(); 1246 Builder.SetInsertPoint(&HostInsertPoint); 1247 Value *Parameters = createLaunchParameters(Kernel, F, SubtreeValues); 1248 1249 std::string Name = "kernel_" + std::to_string(Kernel->id); 1250 Value *KernelString = Builder.CreateGlobalStringPtr(ASMString, Name); 1251 Value *NameString = Builder.CreateGlobalStringPtr(Name, Name + "_name"); 1252 Value *GPUKernel = createCallGetKernel(KernelString, NameString); 1253 1254 Value *GridDimX, *GridDimY; 1255 std::tie(GridDimX, GridDimY) = getGridSizes(Kernel); 1256 1257 createCallLaunchKernel(GPUKernel, GridDimX, GridDimY, BlockDimX, BlockDimY, 1258 BlockDimZ, Parameters); 1259 createCallFreeKernel(GPUKernel); 1260 1261 for (auto Id : KernelIds) 1262 isl_id_free(Id); 1263 1264 KernelIds.clear(); 1265 } 1266 1267 /// Compute the DataLayout string for the NVPTX backend. 1268 /// 1269 /// @param is64Bit Are we looking for a 64 bit architecture? 1270 static std::string computeNVPTXDataLayout(bool is64Bit) { 1271 std::string Ret = "e"; 1272 1273 if (!is64Bit) 1274 Ret += "-p:32:32"; 1275 1276 Ret += "-i64:64-v16:16-v32:32-n16:32:64"; 1277 1278 return Ret; 1279 } 1280 1281 Function * 1282 GPUNodeBuilder::createKernelFunctionDecl(ppcg_kernel *Kernel, 1283 SetVector<Value *> &SubtreeValues) { 1284 std::vector<Type *> Args; 1285 std::string Identifier = "kernel_" + std::to_string(Kernel->id); 1286 1287 for (long i = 0; i < Prog->n_array; i++) { 1288 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1289 continue; 1290 1291 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1292 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1293 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(Id); 1294 Args.push_back(SAI->getElementType()); 1295 } else { 1296 Args.push_back(Builder.getInt8PtrTy()); 1297 } 1298 } 1299 1300 int NumHostIters = isl_space_dim(Kernel->space, isl_dim_set); 1301 1302 for (long i = 0; i < NumHostIters; i++) 1303 Args.push_back(Builder.getInt64Ty()); 1304 1305 int NumVars = isl_space_dim(Kernel->space, isl_dim_param); 1306 1307 for (long i = 0; i < NumVars; i++) { 1308 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1309 Value *Val = IDToValue[Id]; 1310 isl_id_free(Id); 1311 Args.push_back(Val->getType()); 1312 } 1313 1314 for (auto *V : SubtreeValues) 1315 Args.push_back(V->getType()); 1316 1317 auto *FT = FunctionType::get(Builder.getVoidTy(), Args, false); 1318 auto *FN = Function::Create(FT, Function::ExternalLinkage, Identifier, 1319 GPUModule.get()); 1320 FN->setCallingConv(CallingConv::PTX_Kernel); 1321 1322 auto Arg = FN->arg_begin(); 1323 for (long i = 0; i < Kernel->n_array; i++) { 1324 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1325 continue; 1326 1327 Arg->setName(Kernel->array[i].array->name); 1328 1329 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1330 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1331 Type *EleTy = SAI->getElementType(); 1332 Value *Val = &*Arg; 1333 SmallVector<const SCEV *, 4> Sizes; 1334 isl_ast_build *Build = 1335 isl_ast_build_from_context(isl_set_copy(Prog->context)); 1336 Sizes.push_back(nullptr); 1337 for (long j = 1; j < Kernel->array[i].array->n_index; j++) { 1338 isl_ast_expr *DimSize = isl_ast_build_expr_from_pw_aff( 1339 Build, isl_pw_aff_copy(Kernel->array[i].array->bound[j])); 1340 auto V = ExprBuilder.create(DimSize); 1341 Sizes.push_back(SE.getSCEV(V)); 1342 } 1343 const ScopArrayInfo *SAIRep = 1344 S.getOrCreateScopArrayInfo(Val, EleTy, Sizes, MemoryKind::Array); 1345 LocalArrays.push_back(Val); 1346 1347 isl_ast_build_free(Build); 1348 KernelIds.push_back(Id); 1349 IDToSAI[Id] = SAIRep; 1350 Arg++; 1351 } 1352 1353 for (long i = 0; i < NumHostIters; i++) { 1354 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1355 Arg->setName(isl_id_get_name(Id)); 1356 IDToValue[Id] = &*Arg; 1357 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1358 Arg++; 1359 } 1360 1361 for (long i = 0; i < NumVars; i++) { 1362 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1363 Arg->setName(isl_id_get_name(Id)); 1364 Value *Val = IDToValue[Id]; 1365 ValueMap[Val] = &*Arg; 1366 IDToValue[Id] = &*Arg; 1367 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1368 Arg++; 1369 } 1370 1371 for (auto *V : SubtreeValues) { 1372 Arg->setName(V->getName()); 1373 ValueMap[V] = &*Arg; 1374 Arg++; 1375 } 1376 1377 return FN; 1378 } 1379 1380 void GPUNodeBuilder::insertKernelIntrinsics(ppcg_kernel *Kernel) { 1381 Intrinsic::ID IntrinsicsBID[] = {Intrinsic::nvvm_read_ptx_sreg_ctaid_x, 1382 Intrinsic::nvvm_read_ptx_sreg_ctaid_y}; 1383 1384 Intrinsic::ID IntrinsicsTID[] = {Intrinsic::nvvm_read_ptx_sreg_tid_x, 1385 Intrinsic::nvvm_read_ptx_sreg_tid_y, 1386 Intrinsic::nvvm_read_ptx_sreg_tid_z}; 1387 1388 auto addId = [this](__isl_take isl_id *Id, Intrinsic::ID Intr) mutable { 1389 std::string Name = isl_id_get_name(Id); 1390 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 1391 Function *IntrinsicFn = Intrinsic::getDeclaration(M, Intr); 1392 Value *Val = Builder.CreateCall(IntrinsicFn, {}); 1393 Val = Builder.CreateIntCast(Val, Builder.getInt64Ty(), false, Name); 1394 IDToValue[Id] = Val; 1395 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1396 }; 1397 1398 for (int i = 0; i < Kernel->n_grid; ++i) { 1399 isl_id *Id = isl_id_list_get_id(Kernel->block_ids, i); 1400 addId(Id, IntrinsicsBID[i]); 1401 } 1402 1403 for (int i = 0; i < Kernel->n_block; ++i) { 1404 isl_id *Id = isl_id_list_get_id(Kernel->thread_ids, i); 1405 addId(Id, IntrinsicsTID[i]); 1406 } 1407 } 1408 1409 void GPUNodeBuilder::prepareKernelArguments(ppcg_kernel *Kernel, Function *FN) { 1410 auto Arg = FN->arg_begin(); 1411 for (long i = 0; i < Kernel->n_array; i++) { 1412 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1413 continue; 1414 1415 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1416 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1417 isl_id_free(Id); 1418 1419 if (SAI->getNumberOfDimensions() > 0) { 1420 Arg++; 1421 continue; 1422 } 1423 1424 Value *Val = &*Arg; 1425 1426 if (!gpu_array_is_read_only_scalar(&Prog->array[i])) { 1427 Type *TypePtr = SAI->getElementType()->getPointerTo(); 1428 Value *TypedArgPtr = Builder.CreatePointerCast(Val, TypePtr); 1429 Val = Builder.CreateLoad(TypedArgPtr); 1430 } 1431 1432 Value *Alloca = BlockGen.getOrCreateAlloca(SAI); 1433 Builder.CreateStore(Val, Alloca); 1434 1435 Arg++; 1436 } 1437 } 1438 1439 void GPUNodeBuilder::finalizeKernelArguments(ppcg_kernel *Kernel) { 1440 auto *FN = Builder.GetInsertBlock()->getParent(); 1441 auto Arg = FN->arg_begin(); 1442 1443 bool StoredScalar = false; 1444 for (long i = 0; i < Kernel->n_array; i++) { 1445 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1446 continue; 1447 1448 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1449 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1450 isl_id_free(Id); 1451 1452 if (SAI->getNumberOfDimensions() > 0) { 1453 Arg++; 1454 continue; 1455 } 1456 1457 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1458 Arg++; 1459 continue; 1460 } 1461 1462 Value *Alloca = BlockGen.getOrCreateAlloca(SAI); 1463 Value *ArgPtr = &*Arg; 1464 Type *TypePtr = SAI->getElementType()->getPointerTo(); 1465 Value *TypedArgPtr = Builder.CreatePointerCast(ArgPtr, TypePtr); 1466 Value *Val = Builder.CreateLoad(Alloca); 1467 Builder.CreateStore(Val, TypedArgPtr); 1468 StoredScalar = true; 1469 1470 Arg++; 1471 } 1472 1473 if (StoredScalar) 1474 /// In case more than one thread contains scalar stores, the generated 1475 /// code might be incorrect, if we only store at the end of the kernel. 1476 /// To support this case we need to store these scalars back at each 1477 /// memory store or at least before each kernel barrier. 1478 if (Kernel->n_block != 0 || Kernel->n_grid != 0) 1479 BuildSuccessful = 0; 1480 } 1481 1482 void GPUNodeBuilder::createKernelVariables(ppcg_kernel *Kernel, Function *FN) { 1483 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 1484 1485 for (int i = 0; i < Kernel->n_var; ++i) { 1486 struct ppcg_kernel_var &Var = Kernel->var[i]; 1487 isl_id *Id = isl_space_get_tuple_id(Var.array->space, isl_dim_set); 1488 Type *EleTy = ScopArrayInfo::getFromId(Id)->getElementType(); 1489 1490 Type *ArrayTy = EleTy; 1491 SmallVector<const SCEV *, 4> Sizes; 1492 1493 Sizes.push_back(nullptr); 1494 for (unsigned int j = 1; j < Var.array->n_index; ++j) { 1495 isl_val *Val = isl_vec_get_element_val(Var.size, j); 1496 long Bound = isl_val_get_num_si(Val); 1497 isl_val_free(Val); 1498 Sizes.push_back(S.getSE()->getConstant(Builder.getInt64Ty(), Bound)); 1499 } 1500 1501 for (int j = Var.array->n_index - 1; j >= 0; --j) { 1502 isl_val *Val = isl_vec_get_element_val(Var.size, j); 1503 long Bound = isl_val_get_num_si(Val); 1504 isl_val_free(Val); 1505 ArrayTy = ArrayType::get(ArrayTy, Bound); 1506 } 1507 1508 const ScopArrayInfo *SAI; 1509 Value *Allocation; 1510 if (Var.type == ppcg_access_shared) { 1511 auto GlobalVar = new GlobalVariable( 1512 *M, ArrayTy, false, GlobalValue::InternalLinkage, 0, Var.name, 1513 nullptr, GlobalValue::ThreadLocalMode::NotThreadLocal, 3); 1514 GlobalVar->setAlignment(EleTy->getPrimitiveSizeInBits() / 8); 1515 GlobalVar->setInitializer(Constant::getNullValue(ArrayTy)); 1516 1517 Allocation = GlobalVar; 1518 } else if (Var.type == ppcg_access_private) { 1519 Allocation = Builder.CreateAlloca(ArrayTy, 0, "private_array"); 1520 } else { 1521 llvm_unreachable("unknown variable type"); 1522 } 1523 SAI = 1524 S.getOrCreateScopArrayInfo(Allocation, EleTy, Sizes, MemoryKind::Array); 1525 Id = isl_id_alloc(S.getIslCtx(), Var.name, nullptr); 1526 IDToValue[Id] = Allocation; 1527 LocalArrays.push_back(Allocation); 1528 KernelIds.push_back(Id); 1529 IDToSAI[Id] = SAI; 1530 } 1531 } 1532 1533 void GPUNodeBuilder::createKernelFunction(ppcg_kernel *Kernel, 1534 SetVector<Value *> &SubtreeValues) { 1535 1536 std::string Identifier = "kernel_" + std::to_string(Kernel->id); 1537 GPUModule.reset(new Module(Identifier, Builder.getContext())); 1538 GPUModule->setTargetTriple(Triple::normalize("nvptx64-nvidia-cuda")); 1539 GPUModule->setDataLayout(computeNVPTXDataLayout(true /* is64Bit */)); 1540 1541 Function *FN = createKernelFunctionDecl(Kernel, SubtreeValues); 1542 1543 BasicBlock *PrevBlock = Builder.GetInsertBlock(); 1544 auto EntryBlock = BasicBlock::Create(Builder.getContext(), "entry", FN); 1545 1546 DT.addNewBlock(EntryBlock, PrevBlock); 1547 1548 Builder.SetInsertPoint(EntryBlock); 1549 Builder.CreateRetVoid(); 1550 Builder.SetInsertPoint(EntryBlock, EntryBlock->begin()); 1551 1552 ScopDetection::markFunctionAsInvalid(FN); 1553 1554 prepareKernelArguments(Kernel, FN); 1555 createKernelVariables(Kernel, FN); 1556 insertKernelIntrinsics(Kernel); 1557 } 1558 1559 std::string GPUNodeBuilder::createKernelASM() { 1560 llvm::Triple GPUTriple(Triple::normalize("nvptx64-nvidia-cuda")); 1561 std::string ErrMsg; 1562 auto GPUTarget = TargetRegistry::lookupTarget(GPUTriple.getTriple(), ErrMsg); 1563 1564 if (!GPUTarget) { 1565 errs() << ErrMsg << "\n"; 1566 return ""; 1567 } 1568 1569 TargetOptions Options; 1570 Options.UnsafeFPMath = FastMath; 1571 std::unique_ptr<TargetMachine> TargetM( 1572 GPUTarget->createTargetMachine(GPUTriple.getTriple(), CudaVersion, "", 1573 Options, Optional<Reloc::Model>())); 1574 1575 SmallString<0> ASMString; 1576 raw_svector_ostream ASMStream(ASMString); 1577 llvm::legacy::PassManager PM; 1578 1579 PM.add(createTargetTransformInfoWrapperPass(TargetM->getTargetIRAnalysis())); 1580 1581 if (TargetM->addPassesToEmitFile( 1582 PM, ASMStream, TargetMachine::CGFT_AssemblyFile, true /* verify */)) { 1583 errs() << "The target does not support generation of this file type!\n"; 1584 return ""; 1585 } 1586 1587 PM.run(*GPUModule); 1588 1589 return ASMStream.str(); 1590 } 1591 1592 std::string GPUNodeBuilder::finalizeKernelFunction() { 1593 if (verifyModule(*GPUModule)) { 1594 BuildSuccessful = false; 1595 return ""; 1596 } 1597 1598 if (DumpKernelIR) 1599 outs() << *GPUModule << "\n"; 1600 1601 // Optimize module. 1602 llvm::legacy::PassManager OptPasses; 1603 PassManagerBuilder PassBuilder; 1604 PassBuilder.OptLevel = 3; 1605 PassBuilder.SizeLevel = 0; 1606 PassBuilder.populateModulePassManager(OptPasses); 1607 OptPasses.run(*GPUModule); 1608 1609 std::string Assembly = createKernelASM(); 1610 1611 if (DumpKernelASM) 1612 outs() << Assembly << "\n"; 1613 1614 GPUModule.release(); 1615 KernelIDs.clear(); 1616 1617 return Assembly; 1618 } 1619 1620 namespace { 1621 class PPCGCodeGeneration : public ScopPass { 1622 public: 1623 static char ID; 1624 1625 /// The scop that is currently processed. 1626 Scop *S; 1627 1628 LoopInfo *LI; 1629 DominatorTree *DT; 1630 ScalarEvolution *SE; 1631 const DataLayout *DL; 1632 RegionInfo *RI; 1633 1634 PPCGCodeGeneration() : ScopPass(ID) {} 1635 1636 /// Construct compilation options for PPCG. 1637 /// 1638 /// @returns The compilation options. 1639 ppcg_options *createPPCGOptions() { 1640 auto DebugOptions = 1641 (ppcg_debug_options *)malloc(sizeof(ppcg_debug_options)); 1642 auto Options = (ppcg_options *)malloc(sizeof(ppcg_options)); 1643 1644 DebugOptions->dump_schedule_constraints = false; 1645 DebugOptions->dump_schedule = false; 1646 DebugOptions->dump_final_schedule = false; 1647 DebugOptions->dump_sizes = false; 1648 DebugOptions->verbose = false; 1649 1650 Options->debug = DebugOptions; 1651 1652 Options->reschedule = true; 1653 Options->scale_tile_loops = false; 1654 Options->wrap = false; 1655 1656 Options->non_negative_parameters = false; 1657 Options->ctx = nullptr; 1658 Options->sizes = nullptr; 1659 1660 Options->tile_size = 32; 1661 1662 Options->use_private_memory = PrivateMemory; 1663 Options->use_shared_memory = SharedMemory; 1664 Options->max_shared_memory = 48 * 1024; 1665 1666 Options->target = PPCG_TARGET_CUDA; 1667 Options->openmp = false; 1668 Options->linearize_device_arrays = true; 1669 Options->live_range_reordering = false; 1670 1671 Options->opencl_compiler_options = nullptr; 1672 Options->opencl_use_gpu = false; 1673 Options->opencl_n_include_file = 0; 1674 Options->opencl_include_files = nullptr; 1675 Options->opencl_print_kernel_types = false; 1676 Options->opencl_embed_kernel_code = false; 1677 1678 Options->save_schedule_file = nullptr; 1679 Options->load_schedule_file = nullptr; 1680 1681 return Options; 1682 } 1683 1684 /// Get a tagged access relation containing all accesses of type @p AccessTy. 1685 /// 1686 /// Instead of a normal access of the form: 1687 /// 1688 /// Stmt[i,j,k] -> Array[f_0(i,j,k), f_1(i,j,k)] 1689 /// 1690 /// a tagged access has the form 1691 /// 1692 /// [Stmt[i,j,k] -> id[]] -> Array[f_0(i,j,k), f_1(i,j,k)] 1693 /// 1694 /// where 'id' is an additional space that references the memory access that 1695 /// triggered the access. 1696 /// 1697 /// @param AccessTy The type of the memory accesses to collect. 1698 /// 1699 /// @return The relation describing all tagged memory accesses. 1700 isl_union_map *getTaggedAccesses(enum MemoryAccess::AccessType AccessTy) { 1701 isl_union_map *Accesses = isl_union_map_empty(S->getParamSpace()); 1702 1703 for (auto &Stmt : *S) 1704 for (auto &Acc : Stmt) 1705 if (Acc->getType() == AccessTy) { 1706 isl_map *Relation = Acc->getAccessRelation(); 1707 Relation = isl_map_intersect_domain(Relation, Stmt.getDomain()); 1708 1709 isl_space *Space = isl_map_get_space(Relation); 1710 Space = isl_space_range(Space); 1711 Space = isl_space_from_range(Space); 1712 Space = isl_space_set_tuple_id(Space, isl_dim_in, Acc->getId()); 1713 isl_map *Universe = isl_map_universe(Space); 1714 Relation = isl_map_domain_product(Relation, Universe); 1715 Accesses = isl_union_map_add_map(Accesses, Relation); 1716 } 1717 1718 return Accesses; 1719 } 1720 1721 /// Get the set of all read accesses, tagged with the access id. 1722 /// 1723 /// @see getTaggedAccesses 1724 isl_union_map *getTaggedReads() { 1725 return getTaggedAccesses(MemoryAccess::READ); 1726 } 1727 1728 /// Get the set of all may (and must) accesses, tagged with the access id. 1729 /// 1730 /// @see getTaggedAccesses 1731 isl_union_map *getTaggedMayWrites() { 1732 return isl_union_map_union(getTaggedAccesses(MemoryAccess::MAY_WRITE), 1733 getTaggedAccesses(MemoryAccess::MUST_WRITE)); 1734 } 1735 1736 /// Get the set of all must accesses, tagged with the access id. 1737 /// 1738 /// @see getTaggedAccesses 1739 isl_union_map *getTaggedMustWrites() { 1740 return getTaggedAccesses(MemoryAccess::MUST_WRITE); 1741 } 1742 1743 /// Collect parameter and array names as isl_ids. 1744 /// 1745 /// To reason about the different parameters and arrays used, ppcg requires 1746 /// a list of all isl_ids in use. As PPCG traditionally performs 1747 /// source-to-source compilation each of these isl_ids is mapped to the 1748 /// expression that represents it. As we do not have a corresponding 1749 /// expression in Polly, we just map each id to a 'zero' expression to match 1750 /// the data format that ppcg expects. 1751 /// 1752 /// @returns Retun a map from collected ids to 'zero' ast expressions. 1753 __isl_give isl_id_to_ast_expr *getNames() { 1754 auto *Names = isl_id_to_ast_expr_alloc( 1755 S->getIslCtx(), 1756 S->getNumParams() + std::distance(S->array_begin(), S->array_end())); 1757 auto *Zero = isl_ast_expr_from_val(isl_val_zero(S->getIslCtx())); 1758 auto *Space = S->getParamSpace(); 1759 1760 for (int I = 0, E = S->getNumParams(); I < E; ++I) { 1761 isl_id *Id = isl_space_get_dim_id(Space, isl_dim_param, I); 1762 Names = isl_id_to_ast_expr_set(Names, Id, isl_ast_expr_copy(Zero)); 1763 } 1764 1765 for (auto &Array : S->arrays()) { 1766 auto Id = Array->getBasePtrId(); 1767 Names = isl_id_to_ast_expr_set(Names, Id, isl_ast_expr_copy(Zero)); 1768 } 1769 1770 isl_space_free(Space); 1771 isl_ast_expr_free(Zero); 1772 1773 return Names; 1774 } 1775 1776 /// Create a new PPCG scop from the current scop. 1777 /// 1778 /// The PPCG scop is initialized with data from the current polly::Scop. From 1779 /// this initial data, the data-dependences in the PPCG scop are initialized. 1780 /// We do not use Polly's dependence analysis for now, to ensure we match 1781 /// the PPCG default behaviour more closely. 1782 /// 1783 /// @returns A new ppcg scop. 1784 ppcg_scop *createPPCGScop() { 1785 auto PPCGScop = (ppcg_scop *)malloc(sizeof(ppcg_scop)); 1786 1787 PPCGScop->options = createPPCGOptions(); 1788 1789 PPCGScop->start = 0; 1790 PPCGScop->end = 0; 1791 1792 PPCGScop->context = S->getContext(); 1793 PPCGScop->domain = S->getDomains(); 1794 PPCGScop->call = nullptr; 1795 PPCGScop->tagged_reads = getTaggedReads(); 1796 PPCGScop->reads = S->getReads(); 1797 PPCGScop->live_in = nullptr; 1798 PPCGScop->tagged_may_writes = getTaggedMayWrites(); 1799 PPCGScop->may_writes = S->getWrites(); 1800 PPCGScop->tagged_must_writes = getTaggedMustWrites(); 1801 PPCGScop->must_writes = S->getMustWrites(); 1802 PPCGScop->live_out = nullptr; 1803 PPCGScop->tagged_must_kills = isl_union_map_empty(S->getParamSpace()); 1804 PPCGScop->tagger = nullptr; 1805 1806 PPCGScop->independence = nullptr; 1807 PPCGScop->dep_flow = nullptr; 1808 PPCGScop->tagged_dep_flow = nullptr; 1809 PPCGScop->dep_false = nullptr; 1810 PPCGScop->dep_forced = nullptr; 1811 PPCGScop->dep_order = nullptr; 1812 PPCGScop->tagged_dep_order = nullptr; 1813 1814 PPCGScop->schedule = S->getScheduleTree(); 1815 PPCGScop->names = getNames(); 1816 1817 PPCGScop->pet = nullptr; 1818 1819 compute_tagger(PPCGScop); 1820 compute_dependences(PPCGScop); 1821 1822 return PPCGScop; 1823 } 1824 1825 /// Collect the array acesses in a statement. 1826 /// 1827 /// @param Stmt The statement for which to collect the accesses. 1828 /// 1829 /// @returns A list of array accesses. 1830 gpu_stmt_access *getStmtAccesses(ScopStmt &Stmt) { 1831 gpu_stmt_access *Accesses = nullptr; 1832 1833 for (MemoryAccess *Acc : Stmt) { 1834 auto Access = isl_alloc_type(S->getIslCtx(), struct gpu_stmt_access); 1835 Access->read = Acc->isRead(); 1836 Access->write = Acc->isWrite(); 1837 Access->access = Acc->getAccessRelation(); 1838 isl_space *Space = isl_map_get_space(Access->access); 1839 Space = isl_space_range(Space); 1840 Space = isl_space_from_range(Space); 1841 Space = isl_space_set_tuple_id(Space, isl_dim_in, Acc->getId()); 1842 isl_map *Universe = isl_map_universe(Space); 1843 Access->tagged_access = 1844 isl_map_domain_product(Acc->getAccessRelation(), Universe); 1845 Access->exact_write = !Acc->isMayWrite(); 1846 Access->ref_id = Acc->getId(); 1847 Access->next = Accesses; 1848 Access->n_index = Acc->getScopArrayInfo()->getNumberOfDimensions(); 1849 Accesses = Access; 1850 } 1851 1852 return Accesses; 1853 } 1854 1855 /// Collect the list of GPU statements. 1856 /// 1857 /// Each statement has an id, a pointer to the underlying data structure, 1858 /// as well as a list with all memory accesses. 1859 /// 1860 /// TODO: Initialize the list of memory accesses. 1861 /// 1862 /// @returns A linked-list of statements. 1863 gpu_stmt *getStatements() { 1864 gpu_stmt *Stmts = isl_calloc_array(S->getIslCtx(), struct gpu_stmt, 1865 std::distance(S->begin(), S->end())); 1866 1867 int i = 0; 1868 for (auto &Stmt : *S) { 1869 gpu_stmt *GPUStmt = &Stmts[i]; 1870 1871 GPUStmt->id = Stmt.getDomainId(); 1872 1873 // We use the pet stmt pointer to keep track of the Polly statements. 1874 GPUStmt->stmt = (pet_stmt *)&Stmt; 1875 GPUStmt->accesses = getStmtAccesses(Stmt); 1876 i++; 1877 } 1878 1879 return Stmts; 1880 } 1881 1882 /// Derive the extent of an array. 1883 /// 1884 /// The extent of an array is the set of elements that are within the 1885 /// accessed array. For the inner dimensions, the extent constraints are 1886 /// 0 and the size of the corresponding array dimension. For the first 1887 /// (outermost) dimension, the extent constraints are the minimal and maximal 1888 /// subscript value for the first dimension. 1889 /// 1890 /// @param Array The array to derive the extent for. 1891 /// 1892 /// @returns An isl_set describing the extent of the array. 1893 __isl_give isl_set *getExtent(ScopArrayInfo *Array) { 1894 unsigned NumDims = Array->getNumberOfDimensions(); 1895 isl_union_map *Accesses = S->getAccesses(); 1896 Accesses = isl_union_map_intersect_domain(Accesses, S->getDomains()); 1897 Accesses = isl_union_map_detect_equalities(Accesses); 1898 isl_union_set *AccessUSet = isl_union_map_range(Accesses); 1899 AccessUSet = isl_union_set_coalesce(AccessUSet); 1900 AccessUSet = isl_union_set_detect_equalities(AccessUSet); 1901 AccessUSet = isl_union_set_coalesce(AccessUSet); 1902 1903 if (isl_union_set_is_empty(AccessUSet)) { 1904 isl_union_set_free(AccessUSet); 1905 return isl_set_empty(Array->getSpace()); 1906 } 1907 1908 if (Array->getNumberOfDimensions() == 0) { 1909 isl_union_set_free(AccessUSet); 1910 return isl_set_universe(Array->getSpace()); 1911 } 1912 1913 isl_set *AccessSet = 1914 isl_union_set_extract_set(AccessUSet, Array->getSpace()); 1915 1916 isl_union_set_free(AccessUSet); 1917 isl_local_space *LS = isl_local_space_from_space(Array->getSpace()); 1918 1919 isl_pw_aff *Val = 1920 isl_pw_aff_from_aff(isl_aff_var_on_domain(LS, isl_dim_set, 0)); 1921 1922 isl_pw_aff *OuterMin = isl_set_dim_min(isl_set_copy(AccessSet), 0); 1923 isl_pw_aff *OuterMax = isl_set_dim_max(AccessSet, 0); 1924 OuterMin = isl_pw_aff_add_dims(OuterMin, isl_dim_in, 1925 isl_pw_aff_dim(Val, isl_dim_in)); 1926 OuterMax = isl_pw_aff_add_dims(OuterMax, isl_dim_in, 1927 isl_pw_aff_dim(Val, isl_dim_in)); 1928 OuterMin = 1929 isl_pw_aff_set_tuple_id(OuterMin, isl_dim_in, Array->getBasePtrId()); 1930 OuterMax = 1931 isl_pw_aff_set_tuple_id(OuterMax, isl_dim_in, Array->getBasePtrId()); 1932 1933 isl_set *Extent = isl_set_universe(Array->getSpace()); 1934 1935 Extent = isl_set_intersect( 1936 Extent, isl_pw_aff_le_set(OuterMin, isl_pw_aff_copy(Val))); 1937 Extent = isl_set_intersect(Extent, isl_pw_aff_ge_set(OuterMax, Val)); 1938 1939 for (unsigned i = 1; i < NumDims; ++i) 1940 Extent = isl_set_lower_bound_si(Extent, isl_dim_set, i, 0); 1941 1942 for (unsigned i = 1; i < NumDims; ++i) { 1943 isl_pw_aff *PwAff = 1944 const_cast<isl_pw_aff *>(Array->getDimensionSizePw(i)); 1945 isl_pw_aff *Val = isl_pw_aff_from_aff(isl_aff_var_on_domain( 1946 isl_local_space_from_space(Array->getSpace()), isl_dim_set, i)); 1947 PwAff = isl_pw_aff_add_dims(PwAff, isl_dim_in, 1948 isl_pw_aff_dim(Val, isl_dim_in)); 1949 PwAff = isl_pw_aff_set_tuple_id(PwAff, isl_dim_in, 1950 isl_pw_aff_get_tuple_id(Val, isl_dim_in)); 1951 auto *Set = isl_pw_aff_gt_set(PwAff, Val); 1952 Extent = isl_set_intersect(Set, Extent); 1953 } 1954 1955 return Extent; 1956 } 1957 1958 /// Derive the bounds of an array. 1959 /// 1960 /// For the first dimension we derive the bound of the array from the extent 1961 /// of this dimension. For inner dimensions we obtain their size directly from 1962 /// ScopArrayInfo. 1963 /// 1964 /// @param PPCGArray The array to compute bounds for. 1965 /// @param Array The polly array from which to take the information. 1966 void setArrayBounds(gpu_array_info &PPCGArray, ScopArrayInfo *Array) { 1967 if (PPCGArray.n_index > 0) { 1968 if (isl_set_is_empty(PPCGArray.extent)) { 1969 isl_set *Dom = isl_set_copy(PPCGArray.extent); 1970 isl_local_space *LS = isl_local_space_from_space( 1971 isl_space_params(isl_set_get_space(Dom))); 1972 isl_set_free(Dom); 1973 isl_aff *Zero = isl_aff_zero_on_domain(LS); 1974 PPCGArray.bound[0] = isl_pw_aff_from_aff(Zero); 1975 } else { 1976 isl_set *Dom = isl_set_copy(PPCGArray.extent); 1977 Dom = isl_set_project_out(Dom, isl_dim_set, 1, PPCGArray.n_index - 1); 1978 isl_pw_aff *Bound = isl_set_dim_max(isl_set_copy(Dom), 0); 1979 isl_set_free(Dom); 1980 Dom = isl_pw_aff_domain(isl_pw_aff_copy(Bound)); 1981 isl_local_space *LS = 1982 isl_local_space_from_space(isl_set_get_space(Dom)); 1983 isl_aff *One = isl_aff_zero_on_domain(LS); 1984 One = isl_aff_add_constant_si(One, 1); 1985 Bound = isl_pw_aff_add(Bound, isl_pw_aff_alloc(Dom, One)); 1986 Bound = isl_pw_aff_gist(Bound, S->getContext()); 1987 PPCGArray.bound[0] = Bound; 1988 } 1989 } 1990 1991 for (unsigned i = 1; i < PPCGArray.n_index; ++i) { 1992 isl_pw_aff *Bound = Array->getDimensionSizePw(i); 1993 auto LS = isl_pw_aff_get_domain_space(Bound); 1994 auto Aff = isl_multi_aff_zero(LS); 1995 Bound = isl_pw_aff_pullback_multi_aff(Bound, Aff); 1996 PPCGArray.bound[i] = Bound; 1997 } 1998 } 1999 2000 /// Create the arrays for @p PPCGProg. 2001 /// 2002 /// @param PPCGProg The program to compute the arrays for. 2003 void createArrays(gpu_prog *PPCGProg) { 2004 int i = 0; 2005 for (auto &Array : S->arrays()) { 2006 std::string TypeName; 2007 raw_string_ostream OS(TypeName); 2008 2009 OS << *Array->getElementType(); 2010 TypeName = OS.str(); 2011 2012 gpu_array_info &PPCGArray = PPCGProg->array[i]; 2013 2014 PPCGArray.space = Array->getSpace(); 2015 PPCGArray.type = strdup(TypeName.c_str()); 2016 PPCGArray.size = Array->getElementType()->getPrimitiveSizeInBits() / 8; 2017 PPCGArray.name = strdup(Array->getName().c_str()); 2018 PPCGArray.extent = nullptr; 2019 PPCGArray.n_index = Array->getNumberOfDimensions(); 2020 PPCGArray.bound = 2021 isl_alloc_array(S->getIslCtx(), isl_pw_aff *, PPCGArray.n_index); 2022 PPCGArray.extent = getExtent(Array); 2023 PPCGArray.n_ref = 0; 2024 PPCGArray.refs = nullptr; 2025 PPCGArray.accessed = true; 2026 PPCGArray.read_only_scalar = 2027 Array->isReadOnly() && Array->getNumberOfDimensions() == 0; 2028 PPCGArray.has_compound_element = false; 2029 PPCGArray.local = false; 2030 PPCGArray.declare_local = false; 2031 PPCGArray.global = false; 2032 PPCGArray.linearize = false; 2033 PPCGArray.dep_order = nullptr; 2034 PPCGArray.user = Array; 2035 2036 setArrayBounds(PPCGArray, Array); 2037 i++; 2038 2039 collect_references(PPCGProg, &PPCGArray); 2040 } 2041 } 2042 2043 /// Create an identity map between the arrays in the scop. 2044 /// 2045 /// @returns An identity map between the arrays in the scop. 2046 isl_union_map *getArrayIdentity() { 2047 isl_union_map *Maps = isl_union_map_empty(S->getParamSpace()); 2048 2049 for (auto &Array : S->arrays()) { 2050 isl_space *Space = Array->getSpace(); 2051 Space = isl_space_map_from_set(Space); 2052 isl_map *Identity = isl_map_identity(Space); 2053 Maps = isl_union_map_add_map(Maps, Identity); 2054 } 2055 2056 return Maps; 2057 } 2058 2059 /// Create a default-initialized PPCG GPU program. 2060 /// 2061 /// @returns A new gpu grogram description. 2062 gpu_prog *createPPCGProg(ppcg_scop *PPCGScop) { 2063 2064 if (!PPCGScop) 2065 return nullptr; 2066 2067 auto PPCGProg = isl_calloc_type(S->getIslCtx(), struct gpu_prog); 2068 2069 PPCGProg->ctx = S->getIslCtx(); 2070 PPCGProg->scop = PPCGScop; 2071 PPCGProg->context = isl_set_copy(PPCGScop->context); 2072 PPCGProg->read = isl_union_map_copy(PPCGScop->reads); 2073 PPCGProg->may_write = isl_union_map_copy(PPCGScop->may_writes); 2074 PPCGProg->must_write = isl_union_map_copy(PPCGScop->must_writes); 2075 PPCGProg->tagged_must_kill = 2076 isl_union_map_copy(PPCGScop->tagged_must_kills); 2077 PPCGProg->to_inner = getArrayIdentity(); 2078 PPCGProg->to_outer = getArrayIdentity(); 2079 PPCGProg->any_to_outer = nullptr; 2080 PPCGProg->array_order = nullptr; 2081 PPCGProg->n_stmts = std::distance(S->begin(), S->end()); 2082 PPCGProg->stmts = getStatements(); 2083 PPCGProg->n_array = std::distance(S->array_begin(), S->array_end()); 2084 PPCGProg->array = isl_calloc_array(S->getIslCtx(), struct gpu_array_info, 2085 PPCGProg->n_array); 2086 2087 createArrays(PPCGProg); 2088 2089 PPCGProg->may_persist = compute_may_persist(PPCGProg); 2090 2091 return PPCGProg; 2092 } 2093 2094 struct PrintGPUUserData { 2095 struct cuda_info *CudaInfo; 2096 struct gpu_prog *PPCGProg; 2097 std::vector<ppcg_kernel *> Kernels; 2098 }; 2099 2100 /// Print a user statement node in the host code. 2101 /// 2102 /// We use ppcg's printing facilities to print the actual statement and 2103 /// additionally build up a list of all kernels that are encountered in the 2104 /// host ast. 2105 /// 2106 /// @param P The printer to print to 2107 /// @param Options The printing options to use 2108 /// @param Node The node to print 2109 /// @param User A user pointer to carry additional data. This pointer is 2110 /// expected to be of type PrintGPUUserData. 2111 /// 2112 /// @returns A printer to which the output has been printed. 2113 static __isl_give isl_printer * 2114 printHostUser(__isl_take isl_printer *P, 2115 __isl_take isl_ast_print_options *Options, 2116 __isl_take isl_ast_node *Node, void *User) { 2117 auto Data = (struct PrintGPUUserData *)User; 2118 auto Id = isl_ast_node_get_annotation(Node); 2119 2120 if (Id) { 2121 bool IsUser = !strcmp(isl_id_get_name(Id), "user"); 2122 2123 // If this is a user statement, format it ourselves as ppcg would 2124 // otherwise try to call pet functionality that is not available in 2125 // Polly. 2126 if (IsUser) { 2127 P = isl_printer_start_line(P); 2128 P = isl_printer_print_ast_node(P, Node); 2129 P = isl_printer_end_line(P); 2130 isl_id_free(Id); 2131 isl_ast_print_options_free(Options); 2132 return P; 2133 } 2134 2135 auto Kernel = (struct ppcg_kernel *)isl_id_get_user(Id); 2136 isl_id_free(Id); 2137 Data->Kernels.push_back(Kernel); 2138 } 2139 2140 return print_host_user(P, Options, Node, User); 2141 } 2142 2143 /// Print C code corresponding to the control flow in @p Kernel. 2144 /// 2145 /// @param Kernel The kernel to print 2146 void printKernel(ppcg_kernel *Kernel) { 2147 auto *P = isl_printer_to_str(S->getIslCtx()); 2148 P = isl_printer_set_output_format(P, ISL_FORMAT_C); 2149 auto *Options = isl_ast_print_options_alloc(S->getIslCtx()); 2150 P = isl_ast_node_print(Kernel->tree, P, Options); 2151 char *String = isl_printer_get_str(P); 2152 printf("%s\n", String); 2153 free(String); 2154 isl_printer_free(P); 2155 } 2156 2157 /// Print C code corresponding to the GPU code described by @p Tree. 2158 /// 2159 /// @param Tree An AST describing GPU code 2160 /// @param PPCGProg The PPCG program from which @Tree has been constructed. 2161 void printGPUTree(isl_ast_node *Tree, gpu_prog *PPCGProg) { 2162 auto *P = isl_printer_to_str(S->getIslCtx()); 2163 P = isl_printer_set_output_format(P, ISL_FORMAT_C); 2164 2165 PrintGPUUserData Data; 2166 Data.PPCGProg = PPCGProg; 2167 2168 auto *Options = isl_ast_print_options_alloc(S->getIslCtx()); 2169 Options = 2170 isl_ast_print_options_set_print_user(Options, printHostUser, &Data); 2171 P = isl_ast_node_print(Tree, P, Options); 2172 char *String = isl_printer_get_str(P); 2173 printf("# host\n"); 2174 printf("%s\n", String); 2175 free(String); 2176 isl_printer_free(P); 2177 2178 for (auto Kernel : Data.Kernels) { 2179 printf("# kernel%d\n", Kernel->id); 2180 printKernel(Kernel); 2181 } 2182 } 2183 2184 // Generate a GPU program using PPCG. 2185 // 2186 // GPU mapping consists of multiple steps: 2187 // 2188 // 1) Compute new schedule for the program. 2189 // 2) Map schedule to GPU (TODO) 2190 // 3) Generate code for new schedule (TODO) 2191 // 2192 // We do not use here the Polly ScheduleOptimizer, as the schedule optimizer 2193 // is mostly CPU specific. Instead, we use PPCG's GPU code generation 2194 // strategy directly from this pass. 2195 gpu_gen *generateGPU(ppcg_scop *PPCGScop, gpu_prog *PPCGProg) { 2196 2197 auto PPCGGen = isl_calloc_type(S->getIslCtx(), struct gpu_gen); 2198 2199 PPCGGen->ctx = S->getIslCtx(); 2200 PPCGGen->options = PPCGScop->options; 2201 PPCGGen->print = nullptr; 2202 PPCGGen->print_user = nullptr; 2203 PPCGGen->build_ast_expr = &pollyBuildAstExprForStmt; 2204 PPCGGen->prog = PPCGProg; 2205 PPCGGen->tree = nullptr; 2206 PPCGGen->types.n = 0; 2207 PPCGGen->types.name = nullptr; 2208 PPCGGen->sizes = nullptr; 2209 PPCGGen->used_sizes = nullptr; 2210 PPCGGen->kernel_id = 0; 2211 2212 // Set scheduling strategy to same strategy PPCG is using. 2213 isl_options_set_schedule_outer_coincidence(PPCGGen->ctx, true); 2214 isl_options_set_schedule_maximize_band_depth(PPCGGen->ctx, true); 2215 isl_options_set_schedule_whole_component(PPCGGen->ctx, false); 2216 2217 isl_schedule *Schedule = get_schedule(PPCGGen); 2218 2219 int has_permutable = has_any_permutable_node(Schedule); 2220 2221 if (!has_permutable || has_permutable < 0) { 2222 Schedule = isl_schedule_free(Schedule); 2223 } else { 2224 Schedule = map_to_device(PPCGGen, Schedule); 2225 PPCGGen->tree = generate_code(PPCGGen, isl_schedule_copy(Schedule)); 2226 } 2227 2228 if (DumpSchedule) { 2229 isl_printer *P = isl_printer_to_str(S->getIslCtx()); 2230 P = isl_printer_set_yaml_style(P, ISL_YAML_STYLE_BLOCK); 2231 P = isl_printer_print_str(P, "Schedule\n"); 2232 P = isl_printer_print_str(P, "========\n"); 2233 if (Schedule) 2234 P = isl_printer_print_schedule(P, Schedule); 2235 else 2236 P = isl_printer_print_str(P, "No schedule found\n"); 2237 2238 printf("%s\n", isl_printer_get_str(P)); 2239 isl_printer_free(P); 2240 } 2241 2242 if (DumpCode) { 2243 printf("Code\n"); 2244 printf("====\n"); 2245 if (PPCGGen->tree) 2246 printGPUTree(PPCGGen->tree, PPCGProg); 2247 else 2248 printf("No code generated\n"); 2249 } 2250 2251 isl_schedule_free(Schedule); 2252 2253 return PPCGGen; 2254 } 2255 2256 /// Free gpu_gen structure. 2257 /// 2258 /// @param PPCGGen The ppcg_gen object to free. 2259 void freePPCGGen(gpu_gen *PPCGGen) { 2260 isl_ast_node_free(PPCGGen->tree); 2261 isl_union_map_free(PPCGGen->sizes); 2262 isl_union_map_free(PPCGGen->used_sizes); 2263 free(PPCGGen); 2264 } 2265 2266 /// Free the options in the ppcg scop structure. 2267 /// 2268 /// ppcg is not freeing these options for us. To avoid leaks we do this 2269 /// ourselves. 2270 /// 2271 /// @param PPCGScop The scop referencing the options to free. 2272 void freeOptions(ppcg_scop *PPCGScop) { 2273 free(PPCGScop->options->debug); 2274 PPCGScop->options->debug = nullptr; 2275 free(PPCGScop->options); 2276 PPCGScop->options = nullptr; 2277 } 2278 2279 /// Approximate the number of points in the set. 2280 /// 2281 /// This function returns an ast expression that overapproximates the number 2282 /// of points in an isl set through the rectangular hull surrounding this set. 2283 /// 2284 /// @param Set The set to count. 2285 /// @param Build The isl ast build object to use for creating the ast 2286 /// expression. 2287 /// 2288 /// @returns An approximation of the number of points in the set. 2289 __isl_give isl_ast_expr *approxPointsInSet(__isl_take isl_set *Set, 2290 __isl_keep isl_ast_build *Build) { 2291 2292 isl_val *One = isl_val_int_from_si(isl_set_get_ctx(Set), 1); 2293 auto *Expr = isl_ast_expr_from_val(isl_val_copy(One)); 2294 2295 isl_space *Space = isl_set_get_space(Set); 2296 Space = isl_space_params(Space); 2297 auto *Univ = isl_set_universe(Space); 2298 isl_pw_aff *OneAff = isl_pw_aff_val_on_domain(Univ, One); 2299 2300 for (long i = 0; i < isl_set_dim(Set, isl_dim_set); i++) { 2301 isl_pw_aff *Max = isl_set_dim_max(isl_set_copy(Set), i); 2302 isl_pw_aff *Min = isl_set_dim_min(isl_set_copy(Set), i); 2303 isl_pw_aff *DimSize = isl_pw_aff_sub(Max, Min); 2304 DimSize = isl_pw_aff_add(DimSize, isl_pw_aff_copy(OneAff)); 2305 auto DimSizeExpr = isl_ast_build_expr_from_pw_aff(Build, DimSize); 2306 Expr = isl_ast_expr_mul(Expr, DimSizeExpr); 2307 } 2308 2309 isl_set_free(Set); 2310 isl_pw_aff_free(OneAff); 2311 2312 return Expr; 2313 } 2314 2315 /// Approximate a number of dynamic instructions executed by a given 2316 /// statement. 2317 /// 2318 /// @param Stmt The statement for which to compute the number of dynamic 2319 /// instructions. 2320 /// @param Build The isl ast build object to use for creating the ast 2321 /// expression. 2322 /// @returns An approximation of the number of dynamic instructions executed 2323 /// by @p Stmt. 2324 __isl_give isl_ast_expr *approxDynamicInst(ScopStmt &Stmt, 2325 __isl_keep isl_ast_build *Build) { 2326 auto Iterations = approxPointsInSet(Stmt.getDomain(), Build); 2327 2328 long InstCount = 0; 2329 2330 if (Stmt.isBlockStmt()) { 2331 auto *BB = Stmt.getBasicBlock(); 2332 InstCount = std::distance(BB->begin(), BB->end()); 2333 } else { 2334 auto *R = Stmt.getRegion(); 2335 2336 for (auto *BB : R->blocks()) { 2337 InstCount += std::distance(BB->begin(), BB->end()); 2338 } 2339 } 2340 2341 isl_val *InstVal = isl_val_int_from_si(S->getIslCtx(), InstCount); 2342 auto *InstExpr = isl_ast_expr_from_val(InstVal); 2343 return isl_ast_expr_mul(InstExpr, Iterations); 2344 } 2345 2346 /// Approximate dynamic instructions executed in scop. 2347 /// 2348 /// @param S The scop for which to approximate dynamic instructions. 2349 /// @param Build The isl ast build object to use for creating the ast 2350 /// expression. 2351 /// @returns An approximation of the number of dynamic instructions executed 2352 /// in @p S. 2353 __isl_give isl_ast_expr * 2354 getNumberOfIterations(Scop &S, __isl_keep isl_ast_build *Build) { 2355 isl_ast_expr *Instructions; 2356 2357 isl_val *Zero = isl_val_int_from_si(S.getIslCtx(), 0); 2358 Instructions = isl_ast_expr_from_val(Zero); 2359 2360 for (ScopStmt &Stmt : S) { 2361 isl_ast_expr *StmtInstructions = approxDynamicInst(Stmt, Build); 2362 Instructions = isl_ast_expr_add(Instructions, StmtInstructions); 2363 } 2364 return Instructions; 2365 } 2366 2367 /// Create a check that ensures sufficient compute in scop. 2368 /// 2369 /// @param S The scop for which to ensure sufficient compute. 2370 /// @param Build The isl ast build object to use for creating the ast 2371 /// expression. 2372 /// @returns An expression that evaluates to TRUE in case of sufficient 2373 /// compute and to FALSE, otherwise. 2374 __isl_give isl_ast_expr * 2375 createSufficientComputeCheck(Scop &S, __isl_keep isl_ast_build *Build) { 2376 auto Iterations = getNumberOfIterations(S, Build); 2377 auto *MinComputeVal = isl_val_int_from_si(S.getIslCtx(), MinCompute); 2378 auto *MinComputeExpr = isl_ast_expr_from_val(MinComputeVal); 2379 return isl_ast_expr_ge(Iterations, MinComputeExpr); 2380 } 2381 2382 /// Generate code for a given GPU AST described by @p Root. 2383 /// 2384 /// @param Root An isl_ast_node pointing to the root of the GPU AST. 2385 /// @param Prog The GPU Program to generate code for. 2386 void generateCode(__isl_take isl_ast_node *Root, gpu_prog *Prog) { 2387 ScopAnnotator Annotator; 2388 Annotator.buildAliasScopes(*S); 2389 2390 Region *R = &S->getRegion(); 2391 2392 simplifyRegion(R, DT, LI, RI); 2393 2394 BasicBlock *EnteringBB = R->getEnteringBlock(); 2395 2396 PollyIRBuilder Builder = createPollyIRBuilder(EnteringBB, Annotator); 2397 2398 // Only build the run-time condition and parameters _after_ having 2399 // introduced the conditional branch. This is important as the conditional 2400 // branch will guard the original scop from new induction variables that 2401 // the SCEVExpander may introduce while code generating the parameters and 2402 // which may introduce scalar dependences that prevent us from correctly 2403 // code generating this scop. 2404 BasicBlock *StartBlock = 2405 executeScopConditionally(*S, Builder.getTrue(), *DT, *RI, *LI); 2406 2407 GPUNodeBuilder NodeBuilder(Builder, Annotator, *DL, *LI, *SE, *DT, *S, 2408 StartBlock, Prog); 2409 2410 // TODO: Handle LICM 2411 auto SplitBlock = StartBlock->getSinglePredecessor(); 2412 Builder.SetInsertPoint(SplitBlock->getTerminator()); 2413 NodeBuilder.addParameters(S->getContext()); 2414 2415 isl_ast_build *Build = isl_ast_build_alloc(S->getIslCtx()); 2416 isl_ast_expr *Condition = IslAst::buildRunCondition(S, Build); 2417 isl_ast_expr *SufficientCompute = createSufficientComputeCheck(*S, Build); 2418 Condition = isl_ast_expr_and(Condition, SufficientCompute); 2419 isl_ast_build_free(Build); 2420 2421 Value *RTC = NodeBuilder.createRTC(Condition); 2422 Builder.GetInsertBlock()->getTerminator()->setOperand(0, RTC); 2423 2424 Builder.SetInsertPoint(&*StartBlock->begin()); 2425 2426 NodeBuilder.initializeAfterRTH(); 2427 NodeBuilder.create(Root); 2428 NodeBuilder.finalize(); 2429 2430 /// In case a sequential kernel has more surrounding loops as any parallel 2431 /// kernel, the SCoP is probably mostly sequential. Hence, there is no 2432 /// point in running it on a GPU. 2433 if (NodeBuilder.DeepestSequential > NodeBuilder.DeepestParallel) 2434 SplitBlock->getTerminator()->setOperand(0, Builder.getFalse()); 2435 2436 if (!NodeBuilder.BuildSuccessful) 2437 SplitBlock->getTerminator()->setOperand(0, Builder.getFalse()); 2438 } 2439 2440 bool runOnScop(Scop &CurrentScop) override { 2441 S = &CurrentScop; 2442 LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 2443 DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 2444 SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 2445 DL = &S->getRegion().getEntry()->getParent()->getParent()->getDataLayout(); 2446 RI = &getAnalysis<RegionInfoPass>().getRegionInfo(); 2447 2448 // We currently do not support scops with invariant loads. 2449 if (S->hasInvariantAccesses()) 2450 return false; 2451 2452 auto PPCGScop = createPPCGScop(); 2453 auto PPCGProg = createPPCGProg(PPCGScop); 2454 auto PPCGGen = generateGPU(PPCGScop, PPCGProg); 2455 2456 if (PPCGGen->tree) 2457 generateCode(isl_ast_node_copy(PPCGGen->tree), PPCGProg); 2458 2459 freeOptions(PPCGScop); 2460 freePPCGGen(PPCGGen); 2461 gpu_prog_free(PPCGProg); 2462 ppcg_scop_free(PPCGScop); 2463 2464 return true; 2465 } 2466 2467 void printScop(raw_ostream &, Scop &) const override {} 2468 2469 void getAnalysisUsage(AnalysisUsage &AU) const override { 2470 AU.addRequired<DominatorTreeWrapperPass>(); 2471 AU.addRequired<RegionInfoPass>(); 2472 AU.addRequired<ScalarEvolutionWrapperPass>(); 2473 AU.addRequired<ScopDetection>(); 2474 AU.addRequired<ScopInfoRegionPass>(); 2475 AU.addRequired<LoopInfoWrapperPass>(); 2476 2477 AU.addPreserved<AAResultsWrapperPass>(); 2478 AU.addPreserved<BasicAAWrapperPass>(); 2479 AU.addPreserved<LoopInfoWrapperPass>(); 2480 AU.addPreserved<DominatorTreeWrapperPass>(); 2481 AU.addPreserved<GlobalsAAWrapperPass>(); 2482 AU.addPreserved<ScopDetection>(); 2483 AU.addPreserved<ScalarEvolutionWrapperPass>(); 2484 AU.addPreserved<SCEVAAWrapperPass>(); 2485 2486 // FIXME: We do not yet add regions for the newly generated code to the 2487 // region tree. 2488 AU.addPreserved<RegionInfoPass>(); 2489 AU.addPreserved<ScopInfoRegionPass>(); 2490 } 2491 }; 2492 } // namespace 2493 2494 char PPCGCodeGeneration::ID = 1; 2495 2496 Pass *polly::createPPCGCodeGenerationPass() { return new PPCGCodeGeneration(); } 2497 2498 INITIALIZE_PASS_BEGIN(PPCGCodeGeneration, "polly-codegen-ppcg", 2499 "Polly - Apply PPCG translation to SCOP", false, false) 2500 INITIALIZE_PASS_DEPENDENCY(DependenceInfo); 2501 INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass); 2502 INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass); 2503 INITIALIZE_PASS_DEPENDENCY(RegionInfoPass); 2504 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass); 2505 INITIALIZE_PASS_DEPENDENCY(ScopDetection); 2506 INITIALIZE_PASS_END(PPCGCodeGeneration, "polly-codegen-ppcg", 2507 "Polly - Apply PPCG translation to SCOP", false, false) 2508