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, gpu_prog *Prog) 150 : IslNodeBuilder(Builder, Annotator, P, DL, LI, SE, DT, S), Prog(Prog) { 151 getExprBuilder().setIDToSAI(&IDToSAI); 152 } 153 154 /// Create after-run-time-check initialization code. 155 void initializeAfterRTH(); 156 157 /// Finalize the generated scop. 158 virtual void finalize(); 159 160 /// Track if the full build process was successful. 161 /// 162 /// This value is set to false, if throughout the build process an error 163 /// occurred which prevents us from generating valid GPU code. 164 bool BuildSuccessful = true; 165 166 /// The maximal number of loops surrounding a sequential kernel. 167 unsigned DeepestSequential = 0; 168 169 /// The maximal number of loops surrounding a parallel kernel. 170 unsigned DeepestParallel = 0; 171 172 private: 173 /// A vector of array base pointers for which a new ScopArrayInfo was created. 174 /// 175 /// This vector is used to delete the ScopArrayInfo when it is not needed any 176 /// more. 177 std::vector<Value *> LocalArrays; 178 179 /// A map from ScopArrays to their corresponding device allocations. 180 std::map<ScopArrayInfo *, Value *> DeviceAllocations; 181 182 /// The current GPU context. 183 Value *GPUContext; 184 185 /// The set of isl_ids allocated in the kernel 186 std::vector<isl_id *> KernelIds; 187 188 /// A module containing GPU code. 189 /// 190 /// This pointer is only set in case we are currently generating GPU code. 191 std::unique_ptr<Module> GPUModule; 192 193 /// The GPU program we generate code for. 194 gpu_prog *Prog; 195 196 /// Class to free isl_ids. 197 class IslIdDeleter { 198 public: 199 void operator()(__isl_take isl_id *Id) { isl_id_free(Id); }; 200 }; 201 202 /// A set containing all isl_ids allocated in a GPU kernel. 203 /// 204 /// By releasing this set all isl_ids will be freed. 205 std::set<std::unique_ptr<isl_id, IslIdDeleter>> KernelIDs; 206 207 IslExprBuilder::IDToScopArrayInfoTy IDToSAI; 208 209 /// Create code for user-defined AST nodes. 210 /// 211 /// These AST nodes can be of type: 212 /// 213 /// - ScopStmt: A computational statement (TODO) 214 /// - Kernel: A GPU kernel call (TODO) 215 /// - Data-Transfer: A GPU <-> CPU data-transfer 216 /// - In-kernel synchronization 217 /// - In-kernel memory copy statement 218 /// 219 /// @param UserStmt The ast node to generate code for. 220 virtual void createUser(__isl_take isl_ast_node *UserStmt); 221 222 enum DataDirection { HOST_TO_DEVICE, DEVICE_TO_HOST }; 223 224 /// Create code for a data transfer statement 225 /// 226 /// @param TransferStmt The data transfer statement. 227 /// @param Direction The direction in which to transfer data. 228 void createDataTransfer(__isl_take isl_ast_node *TransferStmt, 229 enum DataDirection Direction); 230 231 /// Find llvm::Values referenced in GPU kernel. 232 /// 233 /// @param Kernel The kernel to scan for llvm::Values 234 /// 235 /// @returns A set of values referenced by the kernel. 236 SetVector<Value *> getReferencesInKernel(ppcg_kernel *Kernel); 237 238 /// Compute the sizes of the execution grid for a given kernel. 239 /// 240 /// @param Kernel The kernel to compute grid sizes for. 241 /// 242 /// @returns A tuple with grid sizes for X and Y dimension 243 std::tuple<Value *, Value *> getGridSizes(ppcg_kernel *Kernel); 244 245 /// Compute the sizes of the thread blocks for a given kernel. 246 /// 247 /// @param Kernel The kernel to compute thread block sizes for. 248 /// 249 /// @returns A tuple with thread block sizes for X, Y, and Z dimensions. 250 std::tuple<Value *, Value *, Value *> getBlockSizes(ppcg_kernel *Kernel); 251 252 /// Create kernel launch parameters. 253 /// 254 /// @param Kernel The kernel to create parameters for. 255 /// @param F The kernel function that has been created. 256 /// @param SubtreeValues The set of llvm::Values referenced by this kernel. 257 /// 258 /// @returns A stack allocated array with pointers to the parameter 259 /// values that are passed to the kernel. 260 Value *createLaunchParameters(ppcg_kernel *Kernel, Function *F, 261 SetVector<Value *> SubtreeValues); 262 263 /// Create declarations for kernel variable. 264 /// 265 /// This includes shared memory declarations. 266 /// 267 /// @param Kernel The kernel definition to create variables for. 268 /// @param FN The function into which to generate the variables. 269 void createKernelVariables(ppcg_kernel *Kernel, Function *FN); 270 271 /// Add CUDA annotations to module. 272 /// 273 /// Add a set of CUDA annotations that declares the maximal block dimensions 274 /// that will be used to execute the CUDA kernel. This allows the NVIDIA 275 /// PTX compiler to bound the number of allocated registers to ensure the 276 /// resulting kernel is known to run with up to as many block dimensions 277 /// as specified here. 278 /// 279 /// @param M The module to add the annotations to. 280 /// @param BlockDimX The size of block dimension X. 281 /// @param BlockDimY The size of block dimension Y. 282 /// @param BlockDimZ The size of block dimension Z. 283 void addCUDAAnnotations(Module *M, Value *BlockDimX, Value *BlockDimY, 284 Value *BlockDimZ); 285 286 /// Create GPU kernel. 287 /// 288 /// Code generate the kernel described by @p KernelStmt. 289 /// 290 /// @param KernelStmt The ast node to generate kernel code for. 291 void createKernel(__isl_take isl_ast_node *KernelStmt); 292 293 /// Generate code that computes the size of an array. 294 /// 295 /// @param Array The array for which to compute a size. 296 Value *getArraySize(gpu_array_info *Array); 297 298 /// Generate code to compute the minimal offset at which an array is accessed. 299 /// 300 /// The offset of an array is the minimal array location accessed in a scop. 301 /// 302 /// Example: 303 /// 304 /// for (long i = 0; i < 100; i++) 305 /// A[i + 42] += ... 306 /// 307 /// getArrayOffset(A) results in 42. 308 /// 309 /// @param Array The array for which to compute the offset. 310 /// @returns An llvm::Value that contains the offset of the array. 311 Value *getArrayOffset(gpu_array_info *Array); 312 313 /// Prepare the kernel arguments for kernel code generation 314 /// 315 /// @param Kernel The kernel to generate code for. 316 /// @param FN The function created for the kernel. 317 void prepareKernelArguments(ppcg_kernel *Kernel, Function *FN); 318 319 /// Create kernel function. 320 /// 321 /// Create a kernel function located in a newly created module that can serve 322 /// as target for device code generation. Set the Builder to point to the 323 /// start block of this newly created function. 324 /// 325 /// @param Kernel The kernel to generate code for. 326 /// @param SubtreeValues The set of llvm::Values referenced by this kernel. 327 void createKernelFunction(ppcg_kernel *Kernel, 328 SetVector<Value *> &SubtreeValues); 329 330 /// Create the declaration of a kernel function. 331 /// 332 /// The kernel function takes as arguments: 333 /// 334 /// - One i8 pointer for each external array reference used in the kernel. 335 /// - Host iterators 336 /// - Parameters 337 /// - Other LLVM Value references (TODO) 338 /// 339 /// @param Kernel The kernel to generate the function declaration for. 340 /// @param SubtreeValues The set of llvm::Values referenced by this kernel. 341 /// 342 /// @returns The newly declared function. 343 Function *createKernelFunctionDecl(ppcg_kernel *Kernel, 344 SetVector<Value *> &SubtreeValues); 345 346 /// Insert intrinsic functions to obtain thread and block ids. 347 /// 348 /// @param The kernel to generate the intrinsic functions for. 349 void insertKernelIntrinsics(ppcg_kernel *Kernel); 350 351 /// Create a global-to-shared or shared-to-global copy statement. 352 /// 353 /// @param CopyStmt The copy statement to generate code for 354 void createKernelCopy(ppcg_kernel_stmt *CopyStmt); 355 356 /// Create code for a ScopStmt called in @p Expr. 357 /// 358 /// @param Expr The expression containing the call. 359 /// @param KernelStmt The kernel statement referenced in the call. 360 void createScopStmt(isl_ast_expr *Expr, ppcg_kernel_stmt *KernelStmt); 361 362 /// Create an in-kernel synchronization call. 363 void createKernelSync(); 364 365 /// Create a PTX assembly string for the current GPU kernel. 366 /// 367 /// @returns A string containing the corresponding PTX assembly code. 368 std::string createKernelASM(); 369 370 /// Remove references from the dominator tree to the kernel function @p F. 371 /// 372 /// @param F The function to remove references to. 373 void clearDominators(Function *F); 374 375 /// Remove references from scalar evolution to the kernel function @p F. 376 /// 377 /// @param F The function to remove references to. 378 void clearScalarEvolution(Function *F); 379 380 /// Remove references from loop info to the kernel function @p F. 381 /// 382 /// @param F The function to remove references to. 383 void clearLoops(Function *F); 384 385 /// Finalize the generation of the kernel function. 386 /// 387 /// Free the LLVM-IR module corresponding to the kernel and -- if requested -- 388 /// dump its IR to stderr. 389 /// 390 /// @returns The Assembly string of the kernel. 391 std::string finalizeKernelFunction(); 392 393 /// Finalize the generation of the kernel arguments. 394 /// 395 /// This function ensures that not-read-only scalars used in a kernel are 396 /// stored back to the global memory location they ared backed up with before 397 /// the kernel terminates. 398 /// 399 /// @params Kernel The kernel to finalize kernel arguments for. 400 void finalizeKernelArguments(ppcg_kernel *Kernel); 401 402 /// Create code that allocates memory to store arrays on device. 403 void allocateDeviceArrays(); 404 405 /// Free all allocated device arrays. 406 void freeDeviceArrays(); 407 408 /// Create a call to initialize the GPU context. 409 /// 410 /// @returns A pointer to the newly initialized context. 411 Value *createCallInitContext(); 412 413 /// Create a call to get the device pointer for a kernel allocation. 414 /// 415 /// @param Allocation The Polly GPU allocation 416 /// 417 /// @returns The device parameter corresponding to this allocation. 418 Value *createCallGetDevicePtr(Value *Allocation); 419 420 /// Create a call to free the GPU context. 421 /// 422 /// @param Context A pointer to an initialized GPU context. 423 void createCallFreeContext(Value *Context); 424 425 /// Create a call to allocate memory on the device. 426 /// 427 /// @param Size The size of memory to allocate 428 /// 429 /// @returns A pointer that identifies this allocation. 430 Value *createCallAllocateMemoryForDevice(Value *Size); 431 432 /// Create a call to free a device array. 433 /// 434 /// @param Array The device array to free. 435 void createCallFreeDeviceMemory(Value *Array); 436 437 /// Create a call to copy data from host to device. 438 /// 439 /// @param HostPtr A pointer to the host data that should be copied. 440 /// @param DevicePtr A device pointer specifying the location to copy to. 441 void createCallCopyFromHostToDevice(Value *HostPtr, Value *DevicePtr, 442 Value *Size); 443 444 /// Create a call to copy data from device to host. 445 /// 446 /// @param DevicePtr A pointer to the device data that should be copied. 447 /// @param HostPtr A host pointer specifying the location to copy to. 448 void createCallCopyFromDeviceToHost(Value *DevicePtr, Value *HostPtr, 449 Value *Size); 450 451 /// Create a call to get a kernel from an assembly string. 452 /// 453 /// @param Buffer The string describing the kernel. 454 /// @param Entry The name of the kernel function to call. 455 /// 456 /// @returns A pointer to a kernel object 457 Value *createCallGetKernel(Value *Buffer, Value *Entry); 458 459 /// Create a call to free a GPU kernel. 460 /// 461 /// @param GPUKernel THe kernel to free. 462 void createCallFreeKernel(Value *GPUKernel); 463 464 /// Create a call to launch a GPU kernel. 465 /// 466 /// @param GPUKernel The kernel to launch. 467 /// @param GridDimX The size of the first grid dimension. 468 /// @param GridDimY The size of the second grid dimension. 469 /// @param GridBlockX The size of the first block dimension. 470 /// @param GridBlockY The size of the second block dimension. 471 /// @param GridBlockZ The size of the third block dimension. 472 /// @param Paramters A pointer to an array that contains itself pointers to 473 /// the parameter values passed for each kernel argument. 474 void createCallLaunchKernel(Value *GPUKernel, Value *GridDimX, 475 Value *GridDimY, Value *BlockDimX, 476 Value *BlockDimY, Value *BlockDimZ, 477 Value *Parameters); 478 }; 479 480 void GPUNodeBuilder::initializeAfterRTH() { 481 BasicBlock *NewBB = SplitBlock(Builder.GetInsertBlock(), 482 &*Builder.GetInsertPoint(), &DT, &LI); 483 NewBB->setName("polly.acc.initialize"); 484 Builder.SetInsertPoint(&NewBB->front()); 485 486 GPUContext = createCallInitContext(); 487 allocateDeviceArrays(); 488 } 489 490 void GPUNodeBuilder::finalize() { 491 freeDeviceArrays(); 492 createCallFreeContext(GPUContext); 493 IslNodeBuilder::finalize(); 494 } 495 496 void GPUNodeBuilder::allocateDeviceArrays() { 497 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 498 499 for (int i = 0; i < Prog->n_array; ++i) { 500 gpu_array_info *Array = &Prog->array[i]; 501 auto *ScopArray = (ScopArrayInfo *)Array->user; 502 std::string DevArrayName("p_dev_array_"); 503 DevArrayName.append(Array->name); 504 505 Value *ArraySize = getArraySize(Array); 506 Value *Offset = getArrayOffset(Array); 507 if (Offset) 508 ArraySize = Builder.CreateSub( 509 ArraySize, 510 Builder.CreateMul(Offset, 511 Builder.getInt64(ScopArray->getElemSizeInBytes()))); 512 Value *DevArray = createCallAllocateMemoryForDevice(ArraySize); 513 DevArray->setName(DevArrayName); 514 DeviceAllocations[ScopArray] = DevArray; 515 } 516 517 isl_ast_build_free(Build); 518 } 519 520 void GPUNodeBuilder::addCUDAAnnotations(Module *M, Value *BlockDimX, 521 Value *BlockDimY, Value *BlockDimZ) { 522 auto AnnotationNode = M->getOrInsertNamedMetadata("nvvm.annotations"); 523 524 for (auto &F : *M) { 525 if (F.getCallingConv() != CallingConv::PTX_Kernel) 526 continue; 527 528 Value *V[] = {BlockDimX, BlockDimY, BlockDimZ}; 529 530 Metadata *Elements[] = { 531 ValueAsMetadata::get(&F), MDString::get(M->getContext(), "maxntidx"), 532 ValueAsMetadata::get(V[0]), MDString::get(M->getContext(), "maxntidy"), 533 ValueAsMetadata::get(V[1]), MDString::get(M->getContext(), "maxntidz"), 534 ValueAsMetadata::get(V[2]), 535 }; 536 MDNode *Node = MDNode::get(M->getContext(), Elements); 537 AnnotationNode->addOperand(Node); 538 } 539 } 540 541 void GPUNodeBuilder::freeDeviceArrays() { 542 for (auto &Array : DeviceAllocations) 543 createCallFreeDeviceMemory(Array.second); 544 } 545 546 Value *GPUNodeBuilder::createCallGetKernel(Value *Buffer, Value *Entry) { 547 const char *Name = "polly_getKernel"; 548 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 549 Function *F = M->getFunction(Name); 550 551 // If F is not available, declare it. 552 if (!F) { 553 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 554 std::vector<Type *> Args; 555 Args.push_back(Builder.getInt8PtrTy()); 556 Args.push_back(Builder.getInt8PtrTy()); 557 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 558 F = Function::Create(Ty, Linkage, Name, M); 559 } 560 561 return Builder.CreateCall(F, {Buffer, Entry}); 562 } 563 564 Value *GPUNodeBuilder::createCallGetDevicePtr(Value *Allocation) { 565 const char *Name = "polly_getDevicePtr"; 566 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 567 Function *F = M->getFunction(Name); 568 569 // If F is not available, declare it. 570 if (!F) { 571 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 572 std::vector<Type *> Args; 573 Args.push_back(Builder.getInt8PtrTy()); 574 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 575 F = Function::Create(Ty, Linkage, Name, M); 576 } 577 578 return Builder.CreateCall(F, {Allocation}); 579 } 580 581 void GPUNodeBuilder::createCallLaunchKernel(Value *GPUKernel, Value *GridDimX, 582 Value *GridDimY, Value *BlockDimX, 583 Value *BlockDimY, Value *BlockDimZ, 584 Value *Parameters) { 585 const char *Name = "polly_launchKernel"; 586 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 587 Function *F = M->getFunction(Name); 588 589 // If F is not available, declare it. 590 if (!F) { 591 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 592 std::vector<Type *> Args; 593 Args.push_back(Builder.getInt8PtrTy()); 594 Args.push_back(Builder.getInt32Ty()); 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.getInt8PtrTy()); 600 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 601 F = Function::Create(Ty, Linkage, Name, M); 602 } 603 604 Builder.CreateCall(F, {GPUKernel, GridDimX, GridDimY, BlockDimX, BlockDimY, 605 BlockDimZ, Parameters}); 606 } 607 608 void GPUNodeBuilder::createCallFreeKernel(Value *GPUKernel) { 609 const char *Name = "polly_freeKernel"; 610 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 611 Function *F = M->getFunction(Name); 612 613 // If F is not available, declare it. 614 if (!F) { 615 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 616 std::vector<Type *> Args; 617 Args.push_back(Builder.getInt8PtrTy()); 618 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 619 F = Function::Create(Ty, Linkage, Name, M); 620 } 621 622 Builder.CreateCall(F, {GPUKernel}); 623 } 624 625 void GPUNodeBuilder::createCallFreeDeviceMemory(Value *Array) { 626 const char *Name = "polly_freeDeviceMemory"; 627 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 628 Function *F = M->getFunction(Name); 629 630 // If F is not available, declare it. 631 if (!F) { 632 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 633 std::vector<Type *> Args; 634 Args.push_back(Builder.getInt8PtrTy()); 635 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 636 F = Function::Create(Ty, Linkage, Name, M); 637 } 638 639 Builder.CreateCall(F, {Array}); 640 } 641 642 Value *GPUNodeBuilder::createCallAllocateMemoryForDevice(Value *Size) { 643 const char *Name = "polly_allocateMemoryForDevice"; 644 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 645 Function *F = M->getFunction(Name); 646 647 // If F is not available, declare it. 648 if (!F) { 649 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 650 std::vector<Type *> Args; 651 Args.push_back(Builder.getInt64Ty()); 652 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 653 F = Function::Create(Ty, Linkage, Name, M); 654 } 655 656 return Builder.CreateCall(F, {Size}); 657 } 658 659 void GPUNodeBuilder::createCallCopyFromHostToDevice(Value *HostData, 660 Value *DeviceData, 661 Value *Size) { 662 const char *Name = "polly_copyFromHostToDevice"; 663 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 664 Function *F = M->getFunction(Name); 665 666 // If F is not available, declare it. 667 if (!F) { 668 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 669 std::vector<Type *> Args; 670 Args.push_back(Builder.getInt8PtrTy()); 671 Args.push_back(Builder.getInt8PtrTy()); 672 Args.push_back(Builder.getInt64Ty()); 673 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 674 F = Function::Create(Ty, Linkage, Name, M); 675 } 676 677 Builder.CreateCall(F, {HostData, DeviceData, Size}); 678 } 679 680 void GPUNodeBuilder::createCallCopyFromDeviceToHost(Value *DeviceData, 681 Value *HostData, 682 Value *Size) { 683 const char *Name = "polly_copyFromDeviceToHost"; 684 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 685 Function *F = M->getFunction(Name); 686 687 // If F is not available, declare it. 688 if (!F) { 689 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 690 std::vector<Type *> Args; 691 Args.push_back(Builder.getInt8PtrTy()); 692 Args.push_back(Builder.getInt8PtrTy()); 693 Args.push_back(Builder.getInt64Ty()); 694 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 695 F = Function::Create(Ty, Linkage, Name, M); 696 } 697 698 Builder.CreateCall(F, {DeviceData, HostData, Size}); 699 } 700 701 Value *GPUNodeBuilder::createCallInitContext() { 702 const char *Name = "polly_initContext"; 703 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 704 Function *F = M->getFunction(Name); 705 706 // If F is not available, declare it. 707 if (!F) { 708 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 709 std::vector<Type *> Args; 710 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 711 F = Function::Create(Ty, Linkage, Name, M); 712 } 713 714 return Builder.CreateCall(F, {}); 715 } 716 717 void GPUNodeBuilder::createCallFreeContext(Value *Context) { 718 const char *Name = "polly_freeContext"; 719 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 720 Function *F = M->getFunction(Name); 721 722 // If F is not available, declare it. 723 if (!F) { 724 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 725 std::vector<Type *> Args; 726 Args.push_back(Builder.getInt8PtrTy()); 727 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 728 F = Function::Create(Ty, Linkage, Name, M); 729 } 730 731 Builder.CreateCall(F, {Context}); 732 } 733 734 /// Check if one string is a prefix of another. 735 /// 736 /// @param String The string in which to look for the prefix. 737 /// @param Prefix The prefix to look for. 738 static bool isPrefix(std::string String, std::string Prefix) { 739 return String.find(Prefix) == 0; 740 } 741 742 Value *GPUNodeBuilder::getArraySize(gpu_array_info *Array) { 743 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 744 Value *ArraySize = ConstantInt::get(Builder.getInt64Ty(), Array->size); 745 746 if (!gpu_array_is_scalar(Array)) { 747 auto OffsetDimZero = isl_pw_aff_copy(Array->bound[0]); 748 isl_ast_expr *Res = isl_ast_build_expr_from_pw_aff(Build, OffsetDimZero); 749 750 for (unsigned int i = 1; i < Array->n_index; i++) { 751 isl_pw_aff *Bound_I = isl_pw_aff_copy(Array->bound[i]); 752 isl_ast_expr *Expr = isl_ast_build_expr_from_pw_aff(Build, Bound_I); 753 Res = isl_ast_expr_mul(Res, Expr); 754 } 755 756 Value *NumElements = ExprBuilder.create(Res); 757 if (NumElements->getType() != ArraySize->getType()) 758 NumElements = Builder.CreateSExt(NumElements, ArraySize->getType()); 759 ArraySize = Builder.CreateMul(ArraySize, NumElements); 760 } 761 isl_ast_build_free(Build); 762 return ArraySize; 763 } 764 765 Value *GPUNodeBuilder::getArrayOffset(gpu_array_info *Array) { 766 if (gpu_array_is_scalar(Array)) 767 return nullptr; 768 769 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 770 771 isl_set *Min = isl_set_lexmin(isl_set_copy(Array->extent)); 772 773 isl_set *ZeroSet = isl_set_universe(isl_set_get_space(Min)); 774 775 for (long i = 0; i < isl_set_dim(Min, isl_dim_set); i++) 776 ZeroSet = isl_set_fix_si(ZeroSet, isl_dim_set, i, 0); 777 778 if (isl_set_is_subset(Min, ZeroSet)) { 779 isl_set_free(Min); 780 isl_set_free(ZeroSet); 781 isl_ast_build_free(Build); 782 return nullptr; 783 } 784 isl_set_free(ZeroSet); 785 786 isl_ast_expr *Result = 787 isl_ast_expr_from_val(isl_val_int_from_si(isl_set_get_ctx(Min), 0)); 788 789 for (long i = 0; i < isl_set_dim(Min, isl_dim_set); i++) { 790 if (i > 0) { 791 isl_pw_aff *Bound_I = isl_pw_aff_copy(Array->bound[i - 1]); 792 isl_ast_expr *BExpr = isl_ast_build_expr_from_pw_aff(Build, Bound_I); 793 Result = isl_ast_expr_mul(Result, BExpr); 794 } 795 isl_pw_aff *DimMin = isl_set_dim_min(isl_set_copy(Min), i); 796 isl_ast_expr *MExpr = isl_ast_build_expr_from_pw_aff(Build, DimMin); 797 Result = isl_ast_expr_add(Result, MExpr); 798 } 799 800 Value *ResultValue = ExprBuilder.create(Result); 801 isl_set_free(Min); 802 isl_ast_build_free(Build); 803 804 return ResultValue; 805 } 806 807 void GPUNodeBuilder::createDataTransfer(__isl_take isl_ast_node *TransferStmt, 808 enum DataDirection Direction) { 809 isl_ast_expr *Expr = isl_ast_node_user_get_expr(TransferStmt); 810 isl_ast_expr *Arg = isl_ast_expr_get_op_arg(Expr, 0); 811 isl_id *Id = isl_ast_expr_get_id(Arg); 812 auto Array = (gpu_array_info *)isl_id_get_user(Id); 813 auto ScopArray = (ScopArrayInfo *)(Array->user); 814 815 Value *Size = getArraySize(Array); 816 Value *Offset = getArrayOffset(Array); 817 Value *DevPtr = DeviceAllocations[ScopArray]; 818 819 Value *HostPtr; 820 821 if (gpu_array_is_scalar(Array)) 822 HostPtr = BlockGen.getOrCreateAlloca(ScopArray); 823 else 824 HostPtr = ScopArray->getBasePtr(); 825 826 if (Offset) { 827 HostPtr = Builder.CreatePointerCast( 828 HostPtr, ScopArray->getElementType()->getPointerTo()); 829 HostPtr = Builder.CreateGEP(HostPtr, Offset); 830 } 831 832 HostPtr = Builder.CreatePointerCast(HostPtr, Builder.getInt8PtrTy()); 833 834 if (Offset) { 835 Size = Builder.CreateSub( 836 Size, Builder.CreateMul( 837 Offset, Builder.getInt64(ScopArray->getElemSizeInBytes()))); 838 } 839 840 if (Direction == HOST_TO_DEVICE) 841 createCallCopyFromHostToDevice(HostPtr, DevPtr, Size); 842 else 843 createCallCopyFromDeviceToHost(DevPtr, HostPtr, Size); 844 845 isl_id_free(Id); 846 isl_ast_expr_free(Arg); 847 isl_ast_expr_free(Expr); 848 isl_ast_node_free(TransferStmt); 849 } 850 851 void GPUNodeBuilder::createUser(__isl_take isl_ast_node *UserStmt) { 852 isl_ast_expr *Expr = isl_ast_node_user_get_expr(UserStmt); 853 isl_ast_expr *StmtExpr = isl_ast_expr_get_op_arg(Expr, 0); 854 isl_id *Id = isl_ast_expr_get_id(StmtExpr); 855 isl_id_free(Id); 856 isl_ast_expr_free(StmtExpr); 857 858 const char *Str = isl_id_get_name(Id); 859 if (!strcmp(Str, "kernel")) { 860 createKernel(UserStmt); 861 isl_ast_expr_free(Expr); 862 return; 863 } 864 865 if (isPrefix(Str, "to_device")) { 866 createDataTransfer(UserStmt, HOST_TO_DEVICE); 867 isl_ast_expr_free(Expr); 868 return; 869 } 870 871 if (isPrefix(Str, "from_device")) { 872 createDataTransfer(UserStmt, DEVICE_TO_HOST); 873 isl_ast_expr_free(Expr); 874 return; 875 } 876 877 isl_id *Anno = isl_ast_node_get_annotation(UserStmt); 878 struct ppcg_kernel_stmt *KernelStmt = 879 (struct ppcg_kernel_stmt *)isl_id_get_user(Anno); 880 isl_id_free(Anno); 881 882 switch (KernelStmt->type) { 883 case ppcg_kernel_domain: 884 createScopStmt(Expr, KernelStmt); 885 isl_ast_node_free(UserStmt); 886 return; 887 case ppcg_kernel_copy: 888 createKernelCopy(KernelStmt); 889 isl_ast_expr_free(Expr); 890 isl_ast_node_free(UserStmt); 891 return; 892 case ppcg_kernel_sync: 893 createKernelSync(); 894 isl_ast_expr_free(Expr); 895 isl_ast_node_free(UserStmt); 896 return; 897 } 898 899 isl_ast_expr_free(Expr); 900 isl_ast_node_free(UserStmt); 901 return; 902 } 903 void GPUNodeBuilder::createKernelCopy(ppcg_kernel_stmt *KernelStmt) { 904 isl_ast_expr *LocalIndex = isl_ast_expr_copy(KernelStmt->u.c.local_index); 905 LocalIndex = isl_ast_expr_address_of(LocalIndex); 906 Value *LocalAddr = ExprBuilder.create(LocalIndex); 907 isl_ast_expr *Index = isl_ast_expr_copy(KernelStmt->u.c.index); 908 Index = isl_ast_expr_address_of(Index); 909 Value *GlobalAddr = ExprBuilder.create(Index); 910 911 if (KernelStmt->u.c.read) { 912 LoadInst *Load = Builder.CreateLoad(GlobalAddr, "shared.read"); 913 Builder.CreateStore(Load, LocalAddr); 914 } else { 915 LoadInst *Load = Builder.CreateLoad(LocalAddr, "shared.write"); 916 Builder.CreateStore(Load, GlobalAddr); 917 } 918 } 919 920 void GPUNodeBuilder::createScopStmt(isl_ast_expr *Expr, 921 ppcg_kernel_stmt *KernelStmt) { 922 auto Stmt = (ScopStmt *)KernelStmt->u.d.stmt->stmt; 923 isl_id_to_ast_expr *Indexes = KernelStmt->u.d.ref2expr; 924 925 LoopToScevMapT LTS; 926 LTS.insert(OutsideLoopIterations.begin(), OutsideLoopIterations.end()); 927 928 createSubstitutions(Expr, Stmt, LTS); 929 930 if (Stmt->isBlockStmt()) 931 BlockGen.copyStmt(*Stmt, LTS, Indexes); 932 else 933 RegionGen.copyStmt(*Stmt, LTS, Indexes); 934 } 935 936 void GPUNodeBuilder::createKernelSync() { 937 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 938 auto *Sync = Intrinsic::getDeclaration(M, Intrinsic::nvvm_barrier0); 939 Builder.CreateCall(Sync, {}); 940 } 941 942 /// Collect llvm::Values referenced from @p Node 943 /// 944 /// This function only applies to isl_ast_nodes that are user_nodes referring 945 /// to a ScopStmt. All other node types are ignore. 946 /// 947 /// @param Node The node to collect references for. 948 /// @param User A user pointer used as storage for the data that is collected. 949 /// 950 /// @returns isl_bool_true if data could be collected successfully. 951 isl_bool collectReferencesInGPUStmt(__isl_keep isl_ast_node *Node, void *User) { 952 if (isl_ast_node_get_type(Node) != isl_ast_node_user) 953 return isl_bool_true; 954 955 isl_ast_expr *Expr = isl_ast_node_user_get_expr(Node); 956 isl_ast_expr *StmtExpr = isl_ast_expr_get_op_arg(Expr, 0); 957 isl_id *Id = isl_ast_expr_get_id(StmtExpr); 958 const char *Str = isl_id_get_name(Id); 959 isl_id_free(Id); 960 isl_ast_expr_free(StmtExpr); 961 isl_ast_expr_free(Expr); 962 963 if (!isPrefix(Str, "Stmt")) 964 return isl_bool_true; 965 966 Id = isl_ast_node_get_annotation(Node); 967 auto *KernelStmt = (ppcg_kernel_stmt *)isl_id_get_user(Id); 968 auto Stmt = (ScopStmt *)KernelStmt->u.d.stmt->stmt; 969 isl_id_free(Id); 970 971 addReferencesFromStmt(Stmt, User, false /* CreateScalarRefs */); 972 973 return isl_bool_true; 974 } 975 976 SetVector<Value *> GPUNodeBuilder::getReferencesInKernel(ppcg_kernel *Kernel) { 977 SetVector<Value *> SubtreeValues; 978 SetVector<const SCEV *> SCEVs; 979 SetVector<const Loop *> Loops; 980 SubtreeReferences References = { 981 LI, SE, S, ValueMap, SubtreeValues, SCEVs, getBlockGenerator()}; 982 983 for (const auto &I : IDToValue) 984 SubtreeValues.insert(I.second); 985 986 isl_ast_node_foreach_descendant_top_down( 987 Kernel->tree, collectReferencesInGPUStmt, &References); 988 989 for (const SCEV *Expr : SCEVs) 990 findValues(Expr, SE, SubtreeValues); 991 992 for (auto &SAI : S.arrays()) 993 SubtreeValues.remove(SAI->getBasePtr()); 994 995 isl_space *Space = S.getParamSpace(); 996 for (long i = 0; i < isl_space_dim(Space, isl_dim_param); i++) { 997 isl_id *Id = isl_space_get_dim_id(Space, isl_dim_param, i); 998 assert(IDToValue.count(Id)); 999 Value *Val = IDToValue[Id]; 1000 SubtreeValues.remove(Val); 1001 isl_id_free(Id); 1002 } 1003 isl_space_free(Space); 1004 1005 for (long i = 0; i < isl_space_dim(Kernel->space, isl_dim_set); i++) { 1006 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1007 assert(IDToValue.count(Id)); 1008 Value *Val = IDToValue[Id]; 1009 SubtreeValues.remove(Val); 1010 isl_id_free(Id); 1011 } 1012 1013 return SubtreeValues; 1014 } 1015 1016 void GPUNodeBuilder::clearDominators(Function *F) { 1017 DomTreeNode *N = DT.getNode(&F->getEntryBlock()); 1018 std::vector<BasicBlock *> Nodes; 1019 for (po_iterator<DomTreeNode *> I = po_begin(N), E = po_end(N); I != E; ++I) 1020 Nodes.push_back(I->getBlock()); 1021 1022 for (BasicBlock *BB : Nodes) 1023 DT.eraseNode(BB); 1024 } 1025 1026 void GPUNodeBuilder::clearScalarEvolution(Function *F) { 1027 for (BasicBlock &BB : *F) { 1028 Loop *L = LI.getLoopFor(&BB); 1029 if (L) 1030 SE.forgetLoop(L); 1031 } 1032 } 1033 1034 void GPUNodeBuilder::clearLoops(Function *F) { 1035 for (BasicBlock &BB : *F) { 1036 Loop *L = LI.getLoopFor(&BB); 1037 if (L) 1038 SE.forgetLoop(L); 1039 LI.removeBlock(&BB); 1040 } 1041 } 1042 1043 std::tuple<Value *, Value *> GPUNodeBuilder::getGridSizes(ppcg_kernel *Kernel) { 1044 std::vector<Value *> Sizes; 1045 isl_ast_build *Context = isl_ast_build_from_context(S.getContext()); 1046 1047 for (long i = 0; i < Kernel->n_grid; i++) { 1048 isl_pw_aff *Size = isl_multi_pw_aff_get_pw_aff(Kernel->grid_size, i); 1049 isl_ast_expr *GridSize = isl_ast_build_expr_from_pw_aff(Context, Size); 1050 Value *Res = ExprBuilder.create(GridSize); 1051 Res = Builder.CreateTrunc(Res, Builder.getInt32Ty()); 1052 Sizes.push_back(Res); 1053 } 1054 isl_ast_build_free(Context); 1055 1056 for (long i = Kernel->n_grid; i < 3; i++) 1057 Sizes.push_back(ConstantInt::get(Builder.getInt32Ty(), 1)); 1058 1059 return std::make_tuple(Sizes[0], Sizes[1]); 1060 } 1061 1062 std::tuple<Value *, Value *, Value *> 1063 GPUNodeBuilder::getBlockSizes(ppcg_kernel *Kernel) { 1064 std::vector<Value *> Sizes; 1065 1066 for (long i = 0; i < Kernel->n_block; i++) { 1067 Value *Res = ConstantInt::get(Builder.getInt32Ty(), Kernel->block_dim[i]); 1068 Sizes.push_back(Res); 1069 } 1070 1071 for (long i = Kernel->n_block; i < 3; i++) 1072 Sizes.push_back(ConstantInt::get(Builder.getInt32Ty(), 1)); 1073 1074 return std::make_tuple(Sizes[0], Sizes[1], Sizes[2]); 1075 } 1076 1077 Value * 1078 GPUNodeBuilder::createLaunchParameters(ppcg_kernel *Kernel, Function *F, 1079 SetVector<Value *> SubtreeValues) { 1080 Type *ArrayTy = ArrayType::get(Builder.getInt8PtrTy(), 1081 std::distance(F->arg_begin(), F->arg_end())); 1082 1083 BasicBlock *EntryBlock = 1084 &Builder.GetInsertBlock()->getParent()->getEntryBlock(); 1085 std::string Launch = "polly_launch_" + std::to_string(Kernel->id); 1086 Instruction *Parameters = 1087 new AllocaInst(ArrayTy, Launch + "_params", EntryBlock->getTerminator()); 1088 1089 int Index = 0; 1090 for (long i = 0; i < Prog->n_array; i++) { 1091 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1092 continue; 1093 1094 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1095 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(Id); 1096 1097 Value *DevArray = DeviceAllocations[const_cast<ScopArrayInfo *>(SAI)]; 1098 DevArray = createCallGetDevicePtr(DevArray); 1099 1100 Value *Offset = getArrayOffset(&Prog->array[i]); 1101 1102 if (Offset) { 1103 DevArray = Builder.CreatePointerCast( 1104 DevArray, SAI->getElementType()->getPointerTo()); 1105 DevArray = Builder.CreateGEP(DevArray, Builder.CreateNeg(Offset)); 1106 DevArray = Builder.CreatePointerCast(DevArray, Builder.getInt8PtrTy()); 1107 } 1108 Value *Slot = Builder.CreateGEP( 1109 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1110 1111 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1112 Value *ValPtr = BlockGen.getOrCreateAlloca(SAI); 1113 Value *ValPtrCast = 1114 Builder.CreatePointerCast(ValPtr, Builder.getInt8PtrTy()); 1115 Builder.CreateStore(ValPtrCast, Slot); 1116 } else { 1117 Instruction *Param = new AllocaInst( 1118 Builder.getInt8PtrTy(), Launch + "_param_" + std::to_string(Index), 1119 EntryBlock->getTerminator()); 1120 Builder.CreateStore(DevArray, Param); 1121 Value *ParamTyped = 1122 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1123 Builder.CreateStore(ParamTyped, Slot); 1124 } 1125 Index++; 1126 } 1127 1128 int NumHostIters = isl_space_dim(Kernel->space, isl_dim_set); 1129 1130 for (long i = 0; i < NumHostIters; i++) { 1131 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1132 Value *Val = IDToValue[Id]; 1133 isl_id_free(Id); 1134 Instruction *Param = new AllocaInst( 1135 Val->getType(), Launch + "_param_" + std::to_string(Index), 1136 EntryBlock->getTerminator()); 1137 Builder.CreateStore(Val, Param); 1138 Value *Slot = Builder.CreateGEP( 1139 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1140 Value *ParamTyped = 1141 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1142 Builder.CreateStore(ParamTyped, Slot); 1143 Index++; 1144 } 1145 1146 int NumVars = isl_space_dim(Kernel->space, isl_dim_param); 1147 1148 for (long i = 0; i < NumVars; i++) { 1149 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1150 Value *Val = IDToValue[Id]; 1151 isl_id_free(Id); 1152 Instruction *Param = new AllocaInst( 1153 Val->getType(), Launch + "_param_" + std::to_string(Index), 1154 EntryBlock->getTerminator()); 1155 Builder.CreateStore(Val, Param); 1156 Value *Slot = Builder.CreateGEP( 1157 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1158 Value *ParamTyped = 1159 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1160 Builder.CreateStore(ParamTyped, Slot); 1161 Index++; 1162 } 1163 1164 for (auto Val : SubtreeValues) { 1165 Instruction *Param = new AllocaInst( 1166 Val->getType(), Launch + "_param_" + std::to_string(Index), 1167 EntryBlock->getTerminator()); 1168 Builder.CreateStore(Val, Param); 1169 Value *Slot = Builder.CreateGEP( 1170 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1171 Value *ParamTyped = 1172 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1173 Builder.CreateStore(ParamTyped, Slot); 1174 Index++; 1175 } 1176 1177 auto Location = EntryBlock->getTerminator(); 1178 return new BitCastInst(Parameters, Builder.getInt8PtrTy(), 1179 Launch + "_params_i8ptr", Location); 1180 } 1181 1182 void GPUNodeBuilder::createKernel(__isl_take isl_ast_node *KernelStmt) { 1183 isl_id *Id = isl_ast_node_get_annotation(KernelStmt); 1184 ppcg_kernel *Kernel = (ppcg_kernel *)isl_id_get_user(Id); 1185 isl_id_free(Id); 1186 isl_ast_node_free(KernelStmt); 1187 1188 if (Kernel->n_grid > 1) 1189 DeepestParallel = 1190 std::max(DeepestParallel, isl_space_dim(Kernel->space, isl_dim_set)); 1191 else 1192 DeepestSequential = 1193 std::max(DeepestSequential, isl_space_dim(Kernel->space, isl_dim_set)); 1194 1195 Value *BlockDimX, *BlockDimY, *BlockDimZ; 1196 std::tie(BlockDimX, BlockDimY, BlockDimZ) = getBlockSizes(Kernel); 1197 1198 SetVector<Value *> SubtreeValues = getReferencesInKernel(Kernel); 1199 1200 assert(Kernel->tree && "Device AST of kernel node is empty"); 1201 1202 Instruction &HostInsertPoint = *Builder.GetInsertPoint(); 1203 IslExprBuilder::IDToValueTy HostIDs = IDToValue; 1204 ValueMapT HostValueMap = ValueMap; 1205 BlockGenerator::ScalarAllocaMapTy HostScalarMap = ScalarMap; 1206 BlockGenerator::ScalarAllocaMapTy HostPHIOpMap = PHIOpMap; 1207 ScalarMap.clear(); 1208 PHIOpMap.clear(); 1209 1210 SetVector<const Loop *> Loops; 1211 1212 // Create for all loops we depend on values that contain the current loop 1213 // iteration. These values are necessary to generate code for SCEVs that 1214 // depend on such loops. As a result we need to pass them to the subfunction. 1215 for (const Loop *L : Loops) { 1216 const SCEV *OuterLIV = SE.getAddRecExpr(SE.getUnknown(Builder.getInt64(0)), 1217 SE.getUnknown(Builder.getInt64(1)), 1218 L, SCEV::FlagAnyWrap); 1219 Value *V = generateSCEV(OuterLIV); 1220 OutsideLoopIterations[L] = SE.getUnknown(V); 1221 SubtreeValues.insert(V); 1222 } 1223 1224 createKernelFunction(Kernel, SubtreeValues); 1225 1226 create(isl_ast_node_copy(Kernel->tree)); 1227 1228 finalizeKernelArguments(Kernel); 1229 Function *F = Builder.GetInsertBlock()->getParent(); 1230 addCUDAAnnotations(F->getParent(), BlockDimX, BlockDimY, BlockDimZ); 1231 clearDominators(F); 1232 clearScalarEvolution(F); 1233 clearLoops(F); 1234 1235 IDToValue = HostIDs; 1236 1237 ValueMap = std::move(HostValueMap); 1238 ScalarMap = std::move(HostScalarMap); 1239 PHIOpMap = std::move(HostPHIOpMap); 1240 EscapeMap.clear(); 1241 IDToSAI.clear(); 1242 Annotator.resetAlternativeAliasBases(); 1243 for (auto &BasePtr : LocalArrays) 1244 S.invalidateScopArrayInfo(BasePtr, ScopArrayInfo::MK_Array); 1245 LocalArrays.clear(); 1246 1247 std::string ASMString = finalizeKernelFunction(); 1248 Builder.SetInsertPoint(&HostInsertPoint); 1249 Value *Parameters = createLaunchParameters(Kernel, F, SubtreeValues); 1250 1251 std::string Name = "kernel_" + std::to_string(Kernel->id); 1252 Value *KernelString = Builder.CreateGlobalStringPtr(ASMString, Name); 1253 Value *NameString = Builder.CreateGlobalStringPtr(Name, Name + "_name"); 1254 Value *GPUKernel = createCallGetKernel(KernelString, NameString); 1255 1256 Value *GridDimX, *GridDimY; 1257 std::tie(GridDimX, GridDimY) = getGridSizes(Kernel); 1258 1259 createCallLaunchKernel(GPUKernel, GridDimX, GridDimY, BlockDimX, BlockDimY, 1260 BlockDimZ, Parameters); 1261 createCallFreeKernel(GPUKernel); 1262 1263 for (auto Id : KernelIds) 1264 isl_id_free(Id); 1265 1266 KernelIds.clear(); 1267 } 1268 1269 /// Compute the DataLayout string for the NVPTX backend. 1270 /// 1271 /// @param is64Bit Are we looking for a 64 bit architecture? 1272 static std::string computeNVPTXDataLayout(bool is64Bit) { 1273 std::string Ret = "e"; 1274 1275 if (!is64Bit) 1276 Ret += "-p:32:32"; 1277 1278 Ret += "-i64:64-v16:16-v32:32-n16:32:64"; 1279 1280 return Ret; 1281 } 1282 1283 Function * 1284 GPUNodeBuilder::createKernelFunctionDecl(ppcg_kernel *Kernel, 1285 SetVector<Value *> &SubtreeValues) { 1286 std::vector<Type *> Args; 1287 std::string Identifier = "kernel_" + std::to_string(Kernel->id); 1288 1289 for (long i = 0; i < Prog->n_array; i++) { 1290 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1291 continue; 1292 1293 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1294 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1295 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(Id); 1296 Args.push_back(SAI->getElementType()); 1297 } else { 1298 Args.push_back(Builder.getInt8PtrTy()); 1299 } 1300 } 1301 1302 int NumHostIters = isl_space_dim(Kernel->space, isl_dim_set); 1303 1304 for (long i = 0; i < NumHostIters; i++) 1305 Args.push_back(Builder.getInt64Ty()); 1306 1307 int NumVars = isl_space_dim(Kernel->space, isl_dim_param); 1308 1309 for (long i = 0; i < NumVars; i++) { 1310 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1311 Value *Val = IDToValue[Id]; 1312 isl_id_free(Id); 1313 Args.push_back(Val->getType()); 1314 } 1315 1316 for (auto *V : SubtreeValues) 1317 Args.push_back(V->getType()); 1318 1319 auto *FT = FunctionType::get(Builder.getVoidTy(), Args, false); 1320 auto *FN = Function::Create(FT, Function::ExternalLinkage, Identifier, 1321 GPUModule.get()); 1322 FN->setCallingConv(CallingConv::PTX_Kernel); 1323 1324 auto Arg = FN->arg_begin(); 1325 for (long i = 0; i < Kernel->n_array; i++) { 1326 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1327 continue; 1328 1329 Arg->setName(Kernel->array[i].array->name); 1330 1331 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1332 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1333 Type *EleTy = SAI->getElementType(); 1334 Value *Val = &*Arg; 1335 SmallVector<const SCEV *, 4> Sizes; 1336 isl_ast_build *Build = 1337 isl_ast_build_from_context(isl_set_copy(Prog->context)); 1338 Sizes.push_back(nullptr); 1339 for (long j = 1; j < Kernel->array[i].array->n_index; j++) { 1340 isl_ast_expr *DimSize = isl_ast_build_expr_from_pw_aff( 1341 Build, isl_pw_aff_copy(Kernel->array[i].array->bound[j])); 1342 auto V = ExprBuilder.create(DimSize); 1343 Sizes.push_back(SE.getSCEV(V)); 1344 } 1345 const ScopArrayInfo *SAIRep = 1346 S.getOrCreateScopArrayInfo(Val, EleTy, Sizes, ScopArrayInfo::MK_Array); 1347 LocalArrays.push_back(Val); 1348 1349 isl_ast_build_free(Build); 1350 KernelIds.push_back(Id); 1351 IDToSAI[Id] = SAIRep; 1352 Arg++; 1353 } 1354 1355 for (long i = 0; i < NumHostIters; i++) { 1356 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1357 Arg->setName(isl_id_get_name(Id)); 1358 IDToValue[Id] = &*Arg; 1359 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1360 Arg++; 1361 } 1362 1363 for (long i = 0; i < NumVars; i++) { 1364 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1365 Arg->setName(isl_id_get_name(Id)); 1366 Value *Val = IDToValue[Id]; 1367 ValueMap[Val] = &*Arg; 1368 IDToValue[Id] = &*Arg; 1369 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1370 Arg++; 1371 } 1372 1373 for (auto *V : SubtreeValues) { 1374 Arg->setName(V->getName()); 1375 ValueMap[V] = &*Arg; 1376 Arg++; 1377 } 1378 1379 return FN; 1380 } 1381 1382 void GPUNodeBuilder::insertKernelIntrinsics(ppcg_kernel *Kernel) { 1383 Intrinsic::ID IntrinsicsBID[] = {Intrinsic::nvvm_read_ptx_sreg_ctaid_x, 1384 Intrinsic::nvvm_read_ptx_sreg_ctaid_y}; 1385 1386 Intrinsic::ID IntrinsicsTID[] = {Intrinsic::nvvm_read_ptx_sreg_tid_x, 1387 Intrinsic::nvvm_read_ptx_sreg_tid_y, 1388 Intrinsic::nvvm_read_ptx_sreg_tid_z}; 1389 1390 auto addId = [this](__isl_take isl_id *Id, Intrinsic::ID Intr) mutable { 1391 std::string Name = isl_id_get_name(Id); 1392 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 1393 Function *IntrinsicFn = Intrinsic::getDeclaration(M, Intr); 1394 Value *Val = Builder.CreateCall(IntrinsicFn, {}); 1395 Val = Builder.CreateIntCast(Val, Builder.getInt64Ty(), false, Name); 1396 IDToValue[Id] = Val; 1397 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1398 }; 1399 1400 for (int i = 0; i < Kernel->n_grid; ++i) { 1401 isl_id *Id = isl_id_list_get_id(Kernel->block_ids, i); 1402 addId(Id, IntrinsicsBID[i]); 1403 } 1404 1405 for (int i = 0; i < Kernel->n_block; ++i) { 1406 isl_id *Id = isl_id_list_get_id(Kernel->thread_ids, i); 1407 addId(Id, IntrinsicsTID[i]); 1408 } 1409 } 1410 1411 void GPUNodeBuilder::prepareKernelArguments(ppcg_kernel *Kernel, Function *FN) { 1412 auto Arg = FN->arg_begin(); 1413 for (long i = 0; i < Kernel->n_array; i++) { 1414 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1415 continue; 1416 1417 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1418 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1419 isl_id_free(Id); 1420 1421 if (SAI->getNumberOfDimensions() > 0) { 1422 Arg++; 1423 continue; 1424 } 1425 1426 Value *Val = &*Arg; 1427 1428 if (!gpu_array_is_read_only_scalar(&Prog->array[i])) { 1429 Type *TypePtr = SAI->getElementType()->getPointerTo(); 1430 Value *TypedArgPtr = Builder.CreatePointerCast(Val, TypePtr); 1431 Val = Builder.CreateLoad(TypedArgPtr); 1432 } 1433 1434 Value *Alloca = BlockGen.getOrCreateAlloca(SAI); 1435 Builder.CreateStore(Val, Alloca); 1436 1437 Arg++; 1438 } 1439 } 1440 1441 void GPUNodeBuilder::finalizeKernelArguments(ppcg_kernel *Kernel) { 1442 auto *FN = Builder.GetInsertBlock()->getParent(); 1443 auto Arg = FN->arg_begin(); 1444 1445 bool StoredScalar = false; 1446 for (long i = 0; i < Kernel->n_array; i++) { 1447 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1448 continue; 1449 1450 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1451 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1452 isl_id_free(Id); 1453 1454 if (SAI->getNumberOfDimensions() > 0) { 1455 Arg++; 1456 continue; 1457 } 1458 1459 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1460 Arg++; 1461 continue; 1462 } 1463 1464 Value *Alloca = BlockGen.getOrCreateAlloca(SAI); 1465 Value *ArgPtr = &*Arg; 1466 Type *TypePtr = SAI->getElementType()->getPointerTo(); 1467 Value *TypedArgPtr = Builder.CreatePointerCast(ArgPtr, TypePtr); 1468 Value *Val = Builder.CreateLoad(Alloca); 1469 Builder.CreateStore(Val, TypedArgPtr); 1470 StoredScalar = true; 1471 1472 Arg++; 1473 } 1474 1475 if (StoredScalar) 1476 /// In case more than one thread contains scalar stores, the generated 1477 /// code might be incorrect, if we only store at the end of the kernel. 1478 /// To support this case we need to store these scalars back at each 1479 /// memory store or at least before each kernel barrier. 1480 if (Kernel->n_block != 0 || Kernel->n_grid != 0) 1481 BuildSuccessful = 0; 1482 } 1483 1484 void GPUNodeBuilder::createKernelVariables(ppcg_kernel *Kernel, Function *FN) { 1485 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 1486 1487 for (int i = 0; i < Kernel->n_var; ++i) { 1488 struct ppcg_kernel_var &Var = Kernel->var[i]; 1489 isl_id *Id = isl_space_get_tuple_id(Var.array->space, isl_dim_set); 1490 Type *EleTy = ScopArrayInfo::getFromId(Id)->getElementType(); 1491 1492 Type *ArrayTy = EleTy; 1493 SmallVector<const SCEV *, 4> Sizes; 1494 1495 Sizes.push_back(nullptr); 1496 for (unsigned int j = 1; j < Var.array->n_index; ++j) { 1497 isl_val *Val = isl_vec_get_element_val(Var.size, j); 1498 long Bound = isl_val_get_num_si(Val); 1499 isl_val_free(Val); 1500 Sizes.push_back(S.getSE()->getConstant(Builder.getInt64Ty(), Bound)); 1501 } 1502 1503 for (int j = Var.array->n_index - 1; j >= 0; --j) { 1504 isl_val *Val = isl_vec_get_element_val(Var.size, j); 1505 long Bound = isl_val_get_num_si(Val); 1506 isl_val_free(Val); 1507 ArrayTy = ArrayType::get(ArrayTy, Bound); 1508 } 1509 1510 const ScopArrayInfo *SAI; 1511 Value *Allocation; 1512 if (Var.type == ppcg_access_shared) { 1513 auto GlobalVar = new GlobalVariable( 1514 *M, ArrayTy, false, GlobalValue::InternalLinkage, 0, Var.name, 1515 nullptr, GlobalValue::ThreadLocalMode::NotThreadLocal, 3); 1516 GlobalVar->setAlignment(EleTy->getPrimitiveSizeInBits() / 8); 1517 GlobalVar->setInitializer(Constant::getNullValue(ArrayTy)); 1518 1519 Allocation = GlobalVar; 1520 } else if (Var.type == ppcg_access_private) { 1521 Allocation = Builder.CreateAlloca(ArrayTy, 0, "private_array"); 1522 } else { 1523 llvm_unreachable("unknown variable type"); 1524 } 1525 SAI = S.getOrCreateScopArrayInfo(Allocation, EleTy, Sizes, 1526 ScopArrayInfo::MK_Array); 1527 Id = isl_id_alloc(S.getIslCtx(), Var.name, nullptr); 1528 IDToValue[Id] = Allocation; 1529 LocalArrays.push_back(Allocation); 1530 KernelIds.push_back(Id); 1531 IDToSAI[Id] = SAI; 1532 } 1533 } 1534 1535 void GPUNodeBuilder::createKernelFunction(ppcg_kernel *Kernel, 1536 SetVector<Value *> &SubtreeValues) { 1537 1538 std::string Identifier = "kernel_" + std::to_string(Kernel->id); 1539 GPUModule.reset(new Module(Identifier, Builder.getContext())); 1540 GPUModule->setTargetTriple(Triple::normalize("nvptx64-nvidia-cuda")); 1541 GPUModule->setDataLayout(computeNVPTXDataLayout(true /* is64Bit */)); 1542 1543 Function *FN = createKernelFunctionDecl(Kernel, SubtreeValues); 1544 1545 BasicBlock *PrevBlock = Builder.GetInsertBlock(); 1546 auto EntryBlock = BasicBlock::Create(Builder.getContext(), "entry", FN); 1547 1548 DominatorTree &DT = P->getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 1549 DT.addNewBlock(EntryBlock, PrevBlock); 1550 1551 Builder.SetInsertPoint(EntryBlock); 1552 Builder.CreateRetVoid(); 1553 Builder.SetInsertPoint(EntryBlock, EntryBlock->begin()); 1554 1555 ScopDetection::markFunctionAsInvalid(FN); 1556 1557 prepareKernelArguments(Kernel, FN); 1558 createKernelVariables(Kernel, FN); 1559 insertKernelIntrinsics(Kernel); 1560 } 1561 1562 std::string GPUNodeBuilder::createKernelASM() { 1563 llvm::Triple GPUTriple(Triple::normalize("nvptx64-nvidia-cuda")); 1564 std::string ErrMsg; 1565 auto GPUTarget = TargetRegistry::lookupTarget(GPUTriple.getTriple(), ErrMsg); 1566 1567 if (!GPUTarget) { 1568 errs() << ErrMsg << "\n"; 1569 return ""; 1570 } 1571 1572 TargetOptions Options; 1573 Options.UnsafeFPMath = FastMath; 1574 std::unique_ptr<TargetMachine> TargetM( 1575 GPUTarget->createTargetMachine(GPUTriple.getTriple(), CudaVersion, "", 1576 Options, Optional<Reloc::Model>())); 1577 1578 SmallString<0> ASMString; 1579 raw_svector_ostream ASMStream(ASMString); 1580 llvm::legacy::PassManager PM; 1581 1582 PM.add(createTargetTransformInfoWrapperPass(TargetM->getTargetIRAnalysis())); 1583 1584 if (TargetM->addPassesToEmitFile( 1585 PM, ASMStream, TargetMachine::CGFT_AssemblyFile, true /* verify */)) { 1586 errs() << "The target does not support generation of this file type!\n"; 1587 return ""; 1588 } 1589 1590 PM.run(*GPUModule); 1591 1592 return ASMStream.str(); 1593 } 1594 1595 std::string GPUNodeBuilder::finalizeKernelFunction() { 1596 if (verifyModule(*GPUModule)) { 1597 BuildSuccessful = false; 1598 return ""; 1599 } 1600 1601 if (DumpKernelIR) 1602 outs() << *GPUModule << "\n"; 1603 1604 // Optimize module. 1605 llvm::legacy::PassManager OptPasses; 1606 PassManagerBuilder PassBuilder; 1607 PassBuilder.OptLevel = 3; 1608 PassBuilder.SizeLevel = 0; 1609 PassBuilder.populateModulePassManager(OptPasses); 1610 OptPasses.run(*GPUModule); 1611 1612 std::string Assembly = createKernelASM(); 1613 1614 if (DumpKernelASM) 1615 outs() << Assembly << "\n"; 1616 1617 GPUModule.release(); 1618 KernelIDs.clear(); 1619 1620 return Assembly; 1621 } 1622 1623 namespace { 1624 class PPCGCodeGeneration : public ScopPass { 1625 public: 1626 static char ID; 1627 1628 /// The scop that is currently processed. 1629 Scop *S; 1630 1631 LoopInfo *LI; 1632 DominatorTree *DT; 1633 ScalarEvolution *SE; 1634 const DataLayout *DL; 1635 RegionInfo *RI; 1636 1637 PPCGCodeGeneration() : ScopPass(ID) {} 1638 1639 /// Construct compilation options for PPCG. 1640 /// 1641 /// @returns The compilation options. 1642 ppcg_options *createPPCGOptions() { 1643 auto DebugOptions = 1644 (ppcg_debug_options *)malloc(sizeof(ppcg_debug_options)); 1645 auto Options = (ppcg_options *)malloc(sizeof(ppcg_options)); 1646 1647 DebugOptions->dump_schedule_constraints = false; 1648 DebugOptions->dump_schedule = false; 1649 DebugOptions->dump_final_schedule = false; 1650 DebugOptions->dump_sizes = false; 1651 DebugOptions->verbose = false; 1652 1653 Options->debug = DebugOptions; 1654 1655 Options->reschedule = true; 1656 Options->scale_tile_loops = false; 1657 Options->wrap = false; 1658 1659 Options->non_negative_parameters = false; 1660 Options->ctx = nullptr; 1661 Options->sizes = nullptr; 1662 1663 Options->tile_size = 32; 1664 1665 Options->use_private_memory = PrivateMemory; 1666 Options->use_shared_memory = SharedMemory; 1667 Options->max_shared_memory = 48 * 1024; 1668 1669 Options->target = PPCG_TARGET_CUDA; 1670 Options->openmp = false; 1671 Options->linearize_device_arrays = true; 1672 Options->live_range_reordering = false; 1673 1674 Options->opencl_compiler_options = nullptr; 1675 Options->opencl_use_gpu = false; 1676 Options->opencl_n_include_file = 0; 1677 Options->opencl_include_files = nullptr; 1678 Options->opencl_print_kernel_types = false; 1679 Options->opencl_embed_kernel_code = false; 1680 1681 Options->save_schedule_file = nullptr; 1682 Options->load_schedule_file = nullptr; 1683 1684 return Options; 1685 } 1686 1687 /// Get a tagged access relation containing all accesses of type @p AccessTy. 1688 /// 1689 /// Instead of a normal access of the form: 1690 /// 1691 /// Stmt[i,j,k] -> Array[f_0(i,j,k), f_1(i,j,k)] 1692 /// 1693 /// a tagged access has the form 1694 /// 1695 /// [Stmt[i,j,k] -> id[]] -> Array[f_0(i,j,k), f_1(i,j,k)] 1696 /// 1697 /// where 'id' is an additional space that references the memory access that 1698 /// triggered the access. 1699 /// 1700 /// @param AccessTy The type of the memory accesses to collect. 1701 /// 1702 /// @return The relation describing all tagged memory accesses. 1703 isl_union_map *getTaggedAccesses(enum MemoryAccess::AccessType AccessTy) { 1704 isl_union_map *Accesses = isl_union_map_empty(S->getParamSpace()); 1705 1706 for (auto &Stmt : *S) 1707 for (auto &Acc : Stmt) 1708 if (Acc->getType() == AccessTy) { 1709 isl_map *Relation = Acc->getAccessRelation(); 1710 Relation = isl_map_intersect_domain(Relation, Stmt.getDomain()); 1711 1712 isl_space *Space = isl_map_get_space(Relation); 1713 Space = isl_space_range(Space); 1714 Space = isl_space_from_range(Space); 1715 Space = isl_space_set_tuple_id(Space, isl_dim_in, Acc->getId()); 1716 isl_map *Universe = isl_map_universe(Space); 1717 Relation = isl_map_domain_product(Relation, Universe); 1718 Accesses = isl_union_map_add_map(Accesses, Relation); 1719 } 1720 1721 return Accesses; 1722 } 1723 1724 /// Get the set of all read accesses, tagged with the access id. 1725 /// 1726 /// @see getTaggedAccesses 1727 isl_union_map *getTaggedReads() { 1728 return getTaggedAccesses(MemoryAccess::READ); 1729 } 1730 1731 /// Get the set of all may (and must) accesses, tagged with the access id. 1732 /// 1733 /// @see getTaggedAccesses 1734 isl_union_map *getTaggedMayWrites() { 1735 return isl_union_map_union(getTaggedAccesses(MemoryAccess::MAY_WRITE), 1736 getTaggedAccesses(MemoryAccess::MUST_WRITE)); 1737 } 1738 1739 /// Get the set of all must accesses, tagged with the access id. 1740 /// 1741 /// @see getTaggedAccesses 1742 isl_union_map *getTaggedMustWrites() { 1743 return getTaggedAccesses(MemoryAccess::MUST_WRITE); 1744 } 1745 1746 /// Collect parameter and array names as isl_ids. 1747 /// 1748 /// To reason about the different parameters and arrays used, ppcg requires 1749 /// a list of all isl_ids in use. As PPCG traditionally performs 1750 /// source-to-source compilation each of these isl_ids is mapped to the 1751 /// expression that represents it. As we do not have a corresponding 1752 /// expression in Polly, we just map each id to a 'zero' expression to match 1753 /// the data format that ppcg expects. 1754 /// 1755 /// @returns Retun a map from collected ids to 'zero' ast expressions. 1756 __isl_give isl_id_to_ast_expr *getNames() { 1757 auto *Names = isl_id_to_ast_expr_alloc( 1758 S->getIslCtx(), 1759 S->getNumParams() + std::distance(S->array_begin(), S->array_end())); 1760 auto *Zero = isl_ast_expr_from_val(isl_val_zero(S->getIslCtx())); 1761 auto *Space = S->getParamSpace(); 1762 1763 for (int I = 0, E = S->getNumParams(); I < E; ++I) { 1764 isl_id *Id = isl_space_get_dim_id(Space, isl_dim_param, I); 1765 Names = isl_id_to_ast_expr_set(Names, Id, isl_ast_expr_copy(Zero)); 1766 } 1767 1768 for (auto &Array : S->arrays()) { 1769 auto Id = Array->getBasePtrId(); 1770 Names = isl_id_to_ast_expr_set(Names, Id, isl_ast_expr_copy(Zero)); 1771 } 1772 1773 isl_space_free(Space); 1774 isl_ast_expr_free(Zero); 1775 1776 return Names; 1777 } 1778 1779 /// Create a new PPCG scop from the current scop. 1780 /// 1781 /// The PPCG scop is initialized with data from the current polly::Scop. From 1782 /// this initial data, the data-dependences in the PPCG scop are initialized. 1783 /// We do not use Polly's dependence analysis for now, to ensure we match 1784 /// the PPCG default behaviour more closely. 1785 /// 1786 /// @returns A new ppcg scop. 1787 ppcg_scop *createPPCGScop() { 1788 auto PPCGScop = (ppcg_scop *)malloc(sizeof(ppcg_scop)); 1789 1790 PPCGScop->options = createPPCGOptions(); 1791 1792 PPCGScop->start = 0; 1793 PPCGScop->end = 0; 1794 1795 PPCGScop->context = S->getContext(); 1796 PPCGScop->domain = S->getDomains(); 1797 PPCGScop->call = nullptr; 1798 PPCGScop->tagged_reads = getTaggedReads(); 1799 PPCGScop->reads = S->getReads(); 1800 PPCGScop->live_in = nullptr; 1801 PPCGScop->tagged_may_writes = getTaggedMayWrites(); 1802 PPCGScop->may_writes = S->getWrites(); 1803 PPCGScop->tagged_must_writes = getTaggedMustWrites(); 1804 PPCGScop->must_writes = S->getMustWrites(); 1805 PPCGScop->live_out = nullptr; 1806 PPCGScop->tagged_must_kills = isl_union_map_empty(S->getParamSpace()); 1807 PPCGScop->tagger = nullptr; 1808 1809 PPCGScop->independence = nullptr; 1810 PPCGScop->dep_flow = nullptr; 1811 PPCGScop->tagged_dep_flow = nullptr; 1812 PPCGScop->dep_false = nullptr; 1813 PPCGScop->dep_forced = nullptr; 1814 PPCGScop->dep_order = nullptr; 1815 PPCGScop->tagged_dep_order = nullptr; 1816 1817 PPCGScop->schedule = S->getScheduleTree(); 1818 PPCGScop->names = getNames(); 1819 1820 PPCGScop->pet = nullptr; 1821 1822 compute_tagger(PPCGScop); 1823 compute_dependences(PPCGScop); 1824 1825 return PPCGScop; 1826 } 1827 1828 /// Collect the array acesses in a statement. 1829 /// 1830 /// @param Stmt The statement for which to collect the accesses. 1831 /// 1832 /// @returns A list of array accesses. 1833 gpu_stmt_access *getStmtAccesses(ScopStmt &Stmt) { 1834 gpu_stmt_access *Accesses = nullptr; 1835 1836 for (MemoryAccess *Acc : Stmt) { 1837 auto Access = isl_alloc_type(S->getIslCtx(), struct gpu_stmt_access); 1838 Access->read = Acc->isRead(); 1839 Access->write = Acc->isWrite(); 1840 Access->access = Acc->getAccessRelation(); 1841 isl_space *Space = isl_map_get_space(Access->access); 1842 Space = isl_space_range(Space); 1843 Space = isl_space_from_range(Space); 1844 Space = isl_space_set_tuple_id(Space, isl_dim_in, Acc->getId()); 1845 isl_map *Universe = isl_map_universe(Space); 1846 Access->tagged_access = 1847 isl_map_domain_product(Acc->getAccessRelation(), Universe); 1848 Access->exact_write = !Acc->isMayWrite(); 1849 Access->ref_id = Acc->getId(); 1850 Access->next = Accesses; 1851 Access->n_index = Acc->getScopArrayInfo()->getNumberOfDimensions(); 1852 Accesses = Access; 1853 } 1854 1855 return Accesses; 1856 } 1857 1858 /// Collect the list of GPU statements. 1859 /// 1860 /// Each statement has an id, a pointer to the underlying data structure, 1861 /// as well as a list with all memory accesses. 1862 /// 1863 /// TODO: Initialize the list of memory accesses. 1864 /// 1865 /// @returns A linked-list of statements. 1866 gpu_stmt *getStatements() { 1867 gpu_stmt *Stmts = isl_calloc_array(S->getIslCtx(), struct gpu_stmt, 1868 std::distance(S->begin(), S->end())); 1869 1870 int i = 0; 1871 for (auto &Stmt : *S) { 1872 gpu_stmt *GPUStmt = &Stmts[i]; 1873 1874 GPUStmt->id = Stmt.getDomainId(); 1875 1876 // We use the pet stmt pointer to keep track of the Polly statements. 1877 GPUStmt->stmt = (pet_stmt *)&Stmt; 1878 GPUStmt->accesses = getStmtAccesses(Stmt); 1879 i++; 1880 } 1881 1882 return Stmts; 1883 } 1884 1885 /// Derive the extent of an array. 1886 /// 1887 /// The extent of an array is the set of elements that are within the 1888 /// accessed array. For the inner dimensions, the extent constraints are 1889 /// 0 and the size of the corresponding array dimension. For the first 1890 /// (outermost) dimension, the extent constraints are the minimal and maximal 1891 /// subscript value for the first dimension. 1892 /// 1893 /// @param Array The array to derive the extent for. 1894 /// 1895 /// @returns An isl_set describing the extent of the array. 1896 __isl_give isl_set *getExtent(ScopArrayInfo *Array) { 1897 unsigned NumDims = Array->getNumberOfDimensions(); 1898 isl_union_map *Accesses = S->getAccesses(); 1899 Accesses = isl_union_map_intersect_domain(Accesses, S->getDomains()); 1900 Accesses = isl_union_map_detect_equalities(Accesses); 1901 isl_union_set *AccessUSet = isl_union_map_range(Accesses); 1902 AccessUSet = isl_union_set_coalesce(AccessUSet); 1903 AccessUSet = isl_union_set_detect_equalities(AccessUSet); 1904 AccessUSet = isl_union_set_coalesce(AccessUSet); 1905 1906 if (isl_union_set_is_empty(AccessUSet)) { 1907 isl_union_set_free(AccessUSet); 1908 return isl_set_empty(Array->getSpace()); 1909 } 1910 1911 if (Array->getNumberOfDimensions() == 0) { 1912 isl_union_set_free(AccessUSet); 1913 return isl_set_universe(Array->getSpace()); 1914 } 1915 1916 isl_set *AccessSet = 1917 isl_union_set_extract_set(AccessUSet, Array->getSpace()); 1918 1919 isl_union_set_free(AccessUSet); 1920 isl_local_space *LS = isl_local_space_from_space(Array->getSpace()); 1921 1922 isl_pw_aff *Val = 1923 isl_pw_aff_from_aff(isl_aff_var_on_domain(LS, isl_dim_set, 0)); 1924 1925 isl_pw_aff *OuterMin = isl_set_dim_min(isl_set_copy(AccessSet), 0); 1926 isl_pw_aff *OuterMax = isl_set_dim_max(AccessSet, 0); 1927 OuterMin = isl_pw_aff_add_dims(OuterMin, isl_dim_in, 1928 isl_pw_aff_dim(Val, isl_dim_in)); 1929 OuterMax = isl_pw_aff_add_dims(OuterMax, isl_dim_in, 1930 isl_pw_aff_dim(Val, isl_dim_in)); 1931 OuterMin = 1932 isl_pw_aff_set_tuple_id(OuterMin, isl_dim_in, Array->getBasePtrId()); 1933 OuterMax = 1934 isl_pw_aff_set_tuple_id(OuterMax, isl_dim_in, Array->getBasePtrId()); 1935 1936 isl_set *Extent = isl_set_universe(Array->getSpace()); 1937 1938 Extent = isl_set_intersect( 1939 Extent, isl_pw_aff_le_set(OuterMin, isl_pw_aff_copy(Val))); 1940 Extent = isl_set_intersect(Extent, isl_pw_aff_ge_set(OuterMax, Val)); 1941 1942 for (unsigned i = 1; i < NumDims; ++i) 1943 Extent = isl_set_lower_bound_si(Extent, isl_dim_set, i, 0); 1944 1945 for (unsigned i = 1; i < NumDims; ++i) { 1946 isl_pw_aff *PwAff = 1947 const_cast<isl_pw_aff *>(Array->getDimensionSizePw(i)); 1948 isl_pw_aff *Val = isl_pw_aff_from_aff(isl_aff_var_on_domain( 1949 isl_local_space_from_space(Array->getSpace()), isl_dim_set, i)); 1950 PwAff = isl_pw_aff_add_dims(PwAff, isl_dim_in, 1951 isl_pw_aff_dim(Val, isl_dim_in)); 1952 PwAff = isl_pw_aff_set_tuple_id(PwAff, isl_dim_in, 1953 isl_pw_aff_get_tuple_id(Val, isl_dim_in)); 1954 auto *Set = isl_pw_aff_gt_set(PwAff, Val); 1955 Extent = isl_set_intersect(Set, Extent); 1956 } 1957 1958 return Extent; 1959 } 1960 1961 /// Derive the bounds of an array. 1962 /// 1963 /// For the first dimension we derive the bound of the array from the extent 1964 /// of this dimension. For inner dimensions we obtain their size directly from 1965 /// ScopArrayInfo. 1966 /// 1967 /// @param PPCGArray The array to compute bounds for. 1968 /// @param Array The polly array from which to take the information. 1969 void setArrayBounds(gpu_array_info &PPCGArray, ScopArrayInfo *Array) { 1970 if (PPCGArray.n_index > 0) { 1971 if (isl_set_is_empty(PPCGArray.extent)) { 1972 isl_set *Dom = isl_set_copy(PPCGArray.extent); 1973 isl_local_space *LS = isl_local_space_from_space( 1974 isl_space_params(isl_set_get_space(Dom))); 1975 isl_set_free(Dom); 1976 isl_aff *Zero = isl_aff_zero_on_domain(LS); 1977 PPCGArray.bound[0] = isl_pw_aff_from_aff(Zero); 1978 } else { 1979 isl_set *Dom = isl_set_copy(PPCGArray.extent); 1980 Dom = isl_set_project_out(Dom, isl_dim_set, 1, PPCGArray.n_index - 1); 1981 isl_pw_aff *Bound = isl_set_dim_max(isl_set_copy(Dom), 0); 1982 isl_set_free(Dom); 1983 Dom = isl_pw_aff_domain(isl_pw_aff_copy(Bound)); 1984 isl_local_space *LS = 1985 isl_local_space_from_space(isl_set_get_space(Dom)); 1986 isl_aff *One = isl_aff_zero_on_domain(LS); 1987 One = isl_aff_add_constant_si(One, 1); 1988 Bound = isl_pw_aff_add(Bound, isl_pw_aff_alloc(Dom, One)); 1989 Bound = isl_pw_aff_gist(Bound, S->getContext()); 1990 PPCGArray.bound[0] = Bound; 1991 } 1992 } 1993 1994 for (unsigned i = 1; i < PPCGArray.n_index; ++i) { 1995 isl_pw_aff *Bound = Array->getDimensionSizePw(i); 1996 auto LS = isl_pw_aff_get_domain_space(Bound); 1997 auto Aff = isl_multi_aff_zero(LS); 1998 Bound = isl_pw_aff_pullback_multi_aff(Bound, Aff); 1999 PPCGArray.bound[i] = Bound; 2000 } 2001 } 2002 2003 /// Create the arrays for @p PPCGProg. 2004 /// 2005 /// @param PPCGProg The program to compute the arrays for. 2006 void createArrays(gpu_prog *PPCGProg) { 2007 int i = 0; 2008 for (auto &Array : S->arrays()) { 2009 std::string TypeName; 2010 raw_string_ostream OS(TypeName); 2011 2012 OS << *Array->getElementType(); 2013 TypeName = OS.str(); 2014 2015 gpu_array_info &PPCGArray = PPCGProg->array[i]; 2016 2017 PPCGArray.space = Array->getSpace(); 2018 PPCGArray.type = strdup(TypeName.c_str()); 2019 PPCGArray.size = Array->getElementType()->getPrimitiveSizeInBits() / 8; 2020 PPCGArray.name = strdup(Array->getName().c_str()); 2021 PPCGArray.extent = nullptr; 2022 PPCGArray.n_index = Array->getNumberOfDimensions(); 2023 PPCGArray.bound = 2024 isl_alloc_array(S->getIslCtx(), isl_pw_aff *, PPCGArray.n_index); 2025 PPCGArray.extent = getExtent(Array); 2026 PPCGArray.n_ref = 0; 2027 PPCGArray.refs = nullptr; 2028 PPCGArray.accessed = true; 2029 PPCGArray.read_only_scalar = 2030 Array->isReadOnly() && Array->getNumberOfDimensions() == 0; 2031 PPCGArray.has_compound_element = false; 2032 PPCGArray.local = false; 2033 PPCGArray.declare_local = false; 2034 PPCGArray.global = false; 2035 PPCGArray.linearize = false; 2036 PPCGArray.dep_order = nullptr; 2037 PPCGArray.user = Array; 2038 2039 setArrayBounds(PPCGArray, Array); 2040 i++; 2041 2042 collect_references(PPCGProg, &PPCGArray); 2043 } 2044 } 2045 2046 /// Create an identity map between the arrays in the scop. 2047 /// 2048 /// @returns An identity map between the arrays in the scop. 2049 isl_union_map *getArrayIdentity() { 2050 isl_union_map *Maps = isl_union_map_empty(S->getParamSpace()); 2051 2052 for (auto &Array : S->arrays()) { 2053 isl_space *Space = Array->getSpace(); 2054 Space = isl_space_map_from_set(Space); 2055 isl_map *Identity = isl_map_identity(Space); 2056 Maps = isl_union_map_add_map(Maps, Identity); 2057 } 2058 2059 return Maps; 2060 } 2061 2062 /// Create a default-initialized PPCG GPU program. 2063 /// 2064 /// @returns A new gpu grogram description. 2065 gpu_prog *createPPCGProg(ppcg_scop *PPCGScop) { 2066 2067 if (!PPCGScop) 2068 return nullptr; 2069 2070 auto PPCGProg = isl_calloc_type(S->getIslCtx(), struct gpu_prog); 2071 2072 PPCGProg->ctx = S->getIslCtx(); 2073 PPCGProg->scop = PPCGScop; 2074 PPCGProg->context = isl_set_copy(PPCGScop->context); 2075 PPCGProg->read = isl_union_map_copy(PPCGScop->reads); 2076 PPCGProg->may_write = isl_union_map_copy(PPCGScop->may_writes); 2077 PPCGProg->must_write = isl_union_map_copy(PPCGScop->must_writes); 2078 PPCGProg->tagged_must_kill = 2079 isl_union_map_copy(PPCGScop->tagged_must_kills); 2080 PPCGProg->to_inner = getArrayIdentity(); 2081 PPCGProg->to_outer = getArrayIdentity(); 2082 PPCGProg->any_to_outer = nullptr; 2083 PPCGProg->array_order = nullptr; 2084 PPCGProg->n_stmts = std::distance(S->begin(), S->end()); 2085 PPCGProg->stmts = getStatements(); 2086 PPCGProg->n_array = std::distance(S->array_begin(), S->array_end()); 2087 PPCGProg->array = isl_calloc_array(S->getIslCtx(), struct gpu_array_info, 2088 PPCGProg->n_array); 2089 2090 createArrays(PPCGProg); 2091 2092 PPCGProg->may_persist = compute_may_persist(PPCGProg); 2093 2094 return PPCGProg; 2095 } 2096 2097 struct PrintGPUUserData { 2098 struct cuda_info *CudaInfo; 2099 struct gpu_prog *PPCGProg; 2100 std::vector<ppcg_kernel *> Kernels; 2101 }; 2102 2103 /// Print a user statement node in the host code. 2104 /// 2105 /// We use ppcg's printing facilities to print the actual statement and 2106 /// additionally build up a list of all kernels that are encountered in the 2107 /// host ast. 2108 /// 2109 /// @param P The printer to print to 2110 /// @param Options The printing options to use 2111 /// @param Node The node to print 2112 /// @param User A user pointer to carry additional data. This pointer is 2113 /// expected to be of type PrintGPUUserData. 2114 /// 2115 /// @returns A printer to which the output has been printed. 2116 static __isl_give isl_printer * 2117 printHostUser(__isl_take isl_printer *P, 2118 __isl_take isl_ast_print_options *Options, 2119 __isl_take isl_ast_node *Node, void *User) { 2120 auto Data = (struct PrintGPUUserData *)User; 2121 auto Id = isl_ast_node_get_annotation(Node); 2122 2123 if (Id) { 2124 bool IsUser = !strcmp(isl_id_get_name(Id), "user"); 2125 2126 // If this is a user statement, format it ourselves as ppcg would 2127 // otherwise try to call pet functionality that is not available in 2128 // Polly. 2129 if (IsUser) { 2130 P = isl_printer_start_line(P); 2131 P = isl_printer_print_ast_node(P, Node); 2132 P = isl_printer_end_line(P); 2133 isl_id_free(Id); 2134 isl_ast_print_options_free(Options); 2135 return P; 2136 } 2137 2138 auto Kernel = (struct ppcg_kernel *)isl_id_get_user(Id); 2139 isl_id_free(Id); 2140 Data->Kernels.push_back(Kernel); 2141 } 2142 2143 return print_host_user(P, Options, Node, User); 2144 } 2145 2146 /// Print C code corresponding to the control flow in @p Kernel. 2147 /// 2148 /// @param Kernel The kernel to print 2149 void printKernel(ppcg_kernel *Kernel) { 2150 auto *P = isl_printer_to_str(S->getIslCtx()); 2151 P = isl_printer_set_output_format(P, ISL_FORMAT_C); 2152 auto *Options = isl_ast_print_options_alloc(S->getIslCtx()); 2153 P = isl_ast_node_print(Kernel->tree, P, Options); 2154 char *String = isl_printer_get_str(P); 2155 printf("%s\n", String); 2156 free(String); 2157 isl_printer_free(P); 2158 } 2159 2160 /// Print C code corresponding to the GPU code described by @p Tree. 2161 /// 2162 /// @param Tree An AST describing GPU code 2163 /// @param PPCGProg The PPCG program from which @Tree has been constructed. 2164 void printGPUTree(isl_ast_node *Tree, gpu_prog *PPCGProg) { 2165 auto *P = isl_printer_to_str(S->getIslCtx()); 2166 P = isl_printer_set_output_format(P, ISL_FORMAT_C); 2167 2168 PrintGPUUserData Data; 2169 Data.PPCGProg = PPCGProg; 2170 2171 auto *Options = isl_ast_print_options_alloc(S->getIslCtx()); 2172 Options = 2173 isl_ast_print_options_set_print_user(Options, printHostUser, &Data); 2174 P = isl_ast_node_print(Tree, P, Options); 2175 char *String = isl_printer_get_str(P); 2176 printf("# host\n"); 2177 printf("%s\n", String); 2178 free(String); 2179 isl_printer_free(P); 2180 2181 for (auto Kernel : Data.Kernels) { 2182 printf("# kernel%d\n", Kernel->id); 2183 printKernel(Kernel); 2184 } 2185 } 2186 2187 // Generate a GPU program using PPCG. 2188 // 2189 // GPU mapping consists of multiple steps: 2190 // 2191 // 1) Compute new schedule for the program. 2192 // 2) Map schedule to GPU (TODO) 2193 // 3) Generate code for new schedule (TODO) 2194 // 2195 // We do not use here the Polly ScheduleOptimizer, as the schedule optimizer 2196 // is mostly CPU specific. Instead, we use PPCG's GPU code generation 2197 // strategy directly from this pass. 2198 gpu_gen *generateGPU(ppcg_scop *PPCGScop, gpu_prog *PPCGProg) { 2199 2200 auto PPCGGen = isl_calloc_type(S->getIslCtx(), struct gpu_gen); 2201 2202 PPCGGen->ctx = S->getIslCtx(); 2203 PPCGGen->options = PPCGScop->options; 2204 PPCGGen->print = nullptr; 2205 PPCGGen->print_user = nullptr; 2206 PPCGGen->build_ast_expr = &pollyBuildAstExprForStmt; 2207 PPCGGen->prog = PPCGProg; 2208 PPCGGen->tree = nullptr; 2209 PPCGGen->types.n = 0; 2210 PPCGGen->types.name = nullptr; 2211 PPCGGen->sizes = nullptr; 2212 PPCGGen->used_sizes = nullptr; 2213 PPCGGen->kernel_id = 0; 2214 2215 // Set scheduling strategy to same strategy PPCG is using. 2216 isl_options_set_schedule_outer_coincidence(PPCGGen->ctx, true); 2217 isl_options_set_schedule_maximize_band_depth(PPCGGen->ctx, true); 2218 isl_options_set_schedule_whole_component(PPCGGen->ctx, false); 2219 2220 isl_schedule *Schedule = get_schedule(PPCGGen); 2221 2222 int has_permutable = has_any_permutable_node(Schedule); 2223 2224 if (!has_permutable || has_permutable < 0) { 2225 Schedule = isl_schedule_free(Schedule); 2226 } else { 2227 Schedule = map_to_device(PPCGGen, Schedule); 2228 PPCGGen->tree = generate_code(PPCGGen, isl_schedule_copy(Schedule)); 2229 } 2230 2231 if (DumpSchedule) { 2232 isl_printer *P = isl_printer_to_str(S->getIslCtx()); 2233 P = isl_printer_set_yaml_style(P, ISL_YAML_STYLE_BLOCK); 2234 P = isl_printer_print_str(P, "Schedule\n"); 2235 P = isl_printer_print_str(P, "========\n"); 2236 if (Schedule) 2237 P = isl_printer_print_schedule(P, Schedule); 2238 else 2239 P = isl_printer_print_str(P, "No schedule found\n"); 2240 2241 printf("%s\n", isl_printer_get_str(P)); 2242 isl_printer_free(P); 2243 } 2244 2245 if (DumpCode) { 2246 printf("Code\n"); 2247 printf("====\n"); 2248 if (PPCGGen->tree) 2249 printGPUTree(PPCGGen->tree, PPCGProg); 2250 else 2251 printf("No code generated\n"); 2252 } 2253 2254 isl_schedule_free(Schedule); 2255 2256 return PPCGGen; 2257 } 2258 2259 /// Free gpu_gen structure. 2260 /// 2261 /// @param PPCGGen The ppcg_gen object to free. 2262 void freePPCGGen(gpu_gen *PPCGGen) { 2263 isl_ast_node_free(PPCGGen->tree); 2264 isl_union_map_free(PPCGGen->sizes); 2265 isl_union_map_free(PPCGGen->used_sizes); 2266 free(PPCGGen); 2267 } 2268 2269 /// Free the options in the ppcg scop structure. 2270 /// 2271 /// ppcg is not freeing these options for us. To avoid leaks we do this 2272 /// ourselves. 2273 /// 2274 /// @param PPCGScop The scop referencing the options to free. 2275 void freeOptions(ppcg_scop *PPCGScop) { 2276 free(PPCGScop->options->debug); 2277 PPCGScop->options->debug = nullptr; 2278 free(PPCGScop->options); 2279 PPCGScop->options = nullptr; 2280 } 2281 2282 /// Approximate the number of points in the set. 2283 /// 2284 /// This function returns an ast expression that overapproximates the number 2285 /// of points in an isl set through the rectangular hull surrounding this set. 2286 /// 2287 /// @param Set The set to count. 2288 /// @param Build The isl ast build object to use for creating the ast 2289 /// expression. 2290 /// 2291 /// @returns An approximation of the number of points in the set. 2292 __isl_give isl_ast_expr *approxPointsInSet(__isl_take isl_set *Set, 2293 __isl_keep isl_ast_build *Build) { 2294 2295 isl_val *One = isl_val_int_from_si(isl_set_get_ctx(Set), 1); 2296 auto *Expr = isl_ast_expr_from_val(isl_val_copy(One)); 2297 2298 isl_space *Space = isl_set_get_space(Set); 2299 Space = isl_space_params(Space); 2300 auto *Univ = isl_set_universe(Space); 2301 isl_pw_aff *OneAff = isl_pw_aff_val_on_domain(Univ, One); 2302 2303 for (long i = 0; i < isl_set_dim(Set, isl_dim_set); i++) { 2304 isl_pw_aff *Max = isl_set_dim_max(isl_set_copy(Set), i); 2305 isl_pw_aff *Min = isl_set_dim_min(isl_set_copy(Set), i); 2306 isl_pw_aff *DimSize = isl_pw_aff_sub(Max, Min); 2307 DimSize = isl_pw_aff_add(DimSize, isl_pw_aff_copy(OneAff)); 2308 auto DimSizeExpr = isl_ast_build_expr_from_pw_aff(Build, DimSize); 2309 Expr = isl_ast_expr_mul(Expr, DimSizeExpr); 2310 } 2311 2312 isl_set_free(Set); 2313 isl_pw_aff_free(OneAff); 2314 2315 return Expr; 2316 } 2317 2318 /// Approximate a number of dynamic instructions executed by a given 2319 /// statement. 2320 /// 2321 /// @param Stmt The statement for which to compute the number of dynamic 2322 /// instructions. 2323 /// @param Build The isl ast build object to use for creating the ast 2324 /// expression. 2325 /// @returns An approximation of the number of dynamic instructions executed 2326 /// by @p Stmt. 2327 __isl_give isl_ast_expr *approxDynamicInst(ScopStmt &Stmt, 2328 __isl_keep isl_ast_build *Build) { 2329 auto Iterations = approxPointsInSet(Stmt.getDomain(), Build); 2330 2331 long InstCount = 0; 2332 2333 if (Stmt.isBlockStmt()) { 2334 auto *BB = Stmt.getBasicBlock(); 2335 InstCount = std::distance(BB->begin(), BB->end()); 2336 } else { 2337 auto *R = Stmt.getRegion(); 2338 2339 for (auto *BB : R->blocks()) { 2340 InstCount += std::distance(BB->begin(), BB->end()); 2341 } 2342 } 2343 2344 isl_val *InstVal = isl_val_int_from_si(S->getIslCtx(), InstCount); 2345 auto *InstExpr = isl_ast_expr_from_val(InstVal); 2346 return isl_ast_expr_mul(InstExpr, Iterations); 2347 } 2348 2349 /// Approximate dynamic instructions executed in scop. 2350 /// 2351 /// @param S The scop for which to approximate dynamic instructions. 2352 /// @param Build The isl ast build object to use for creating the ast 2353 /// expression. 2354 /// @returns An approximation of the number of dynamic instructions executed 2355 /// in @p S. 2356 __isl_give isl_ast_expr * 2357 getNumberOfIterations(Scop &S, __isl_keep isl_ast_build *Build) { 2358 isl_ast_expr *Instructions; 2359 2360 isl_val *Zero = isl_val_int_from_si(S.getIslCtx(), 0); 2361 Instructions = isl_ast_expr_from_val(Zero); 2362 2363 for (ScopStmt &Stmt : S) { 2364 isl_ast_expr *StmtInstructions = approxDynamicInst(Stmt, Build); 2365 Instructions = isl_ast_expr_add(Instructions, StmtInstructions); 2366 } 2367 return Instructions; 2368 } 2369 2370 /// Create a check that ensures sufficient compute in scop. 2371 /// 2372 /// @param S The scop for which to ensure sufficient compute. 2373 /// @param Build The isl ast build object to use for creating the ast 2374 /// expression. 2375 /// @returns An expression that evaluates to TRUE in case of sufficient 2376 /// compute and to FALSE, otherwise. 2377 __isl_give isl_ast_expr * 2378 createSufficientComputeCheck(Scop &S, __isl_keep isl_ast_build *Build) { 2379 auto Iterations = getNumberOfIterations(S, Build); 2380 auto *MinComputeVal = isl_val_int_from_si(S.getIslCtx(), MinCompute); 2381 auto *MinComputeExpr = isl_ast_expr_from_val(MinComputeVal); 2382 return isl_ast_expr_ge(Iterations, MinComputeExpr); 2383 } 2384 2385 /// Generate code for a given GPU AST described by @p Root. 2386 /// 2387 /// @param Root An isl_ast_node pointing to the root of the GPU AST. 2388 /// @param Prog The GPU Program to generate code for. 2389 void generateCode(__isl_take isl_ast_node *Root, gpu_prog *Prog) { 2390 ScopAnnotator Annotator; 2391 Annotator.buildAliasScopes(*S); 2392 2393 Region *R = &S->getRegion(); 2394 2395 simplifyRegion(R, DT, LI, RI); 2396 2397 BasicBlock *EnteringBB = R->getEnteringBlock(); 2398 2399 PollyIRBuilder Builder = createPollyIRBuilder(EnteringBB, Annotator); 2400 2401 GPUNodeBuilder NodeBuilder(Builder, Annotator, this, *DL, *LI, *SE, *DT, *S, 2402 Prog); 2403 2404 // Only build the run-time condition and parameters _after_ having 2405 // introduced the conditional branch. This is important as the conditional 2406 // branch will guard the original scop from new induction variables that 2407 // the SCEVExpander may introduce while code generating the parameters and 2408 // which may introduce scalar dependences that prevent us from correctly 2409 // code generating this scop. 2410 BasicBlock *StartBlock = 2411 executeScopConditionally(*S, this, Builder.getTrue()); 2412 2413 // TODO: Handle LICM 2414 auto SplitBlock = StartBlock->getSinglePredecessor(); 2415 Builder.SetInsertPoint(SplitBlock->getTerminator()); 2416 NodeBuilder.addParameters(S->getContext()); 2417 2418 isl_ast_build *Build = isl_ast_build_alloc(S->getIslCtx()); 2419 isl_ast_expr *Condition = IslAst::buildRunCondition(S, Build); 2420 isl_ast_expr *SufficientCompute = createSufficientComputeCheck(*S, Build); 2421 Condition = isl_ast_expr_and(Condition, SufficientCompute); 2422 isl_ast_build_free(Build); 2423 2424 Value *RTC = NodeBuilder.createRTC(Condition); 2425 Builder.GetInsertBlock()->getTerminator()->setOperand(0, RTC); 2426 2427 Builder.SetInsertPoint(&*StartBlock->begin()); 2428 2429 NodeBuilder.initializeAfterRTH(); 2430 NodeBuilder.create(Root); 2431 NodeBuilder.finalize(); 2432 2433 /// In case a sequential kernel has more surrounding loops as any parallel 2434 /// kernel, the SCoP is probably mostly sequential. Hence, there is no 2435 /// point in running it on a CPU. 2436 if (NodeBuilder.DeepestSequential > NodeBuilder.DeepestParallel) 2437 SplitBlock->getTerminator()->setOperand(0, Builder.getFalse()); 2438 2439 if (!NodeBuilder.BuildSuccessful) 2440 SplitBlock->getTerminator()->setOperand(0, Builder.getFalse()); 2441 } 2442 2443 bool runOnScop(Scop &CurrentScop) override { 2444 S = &CurrentScop; 2445 LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 2446 DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 2447 SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 2448 DL = &S->getRegion().getEntry()->getParent()->getParent()->getDataLayout(); 2449 RI = &getAnalysis<RegionInfoPass>().getRegionInfo(); 2450 2451 // We currently do not support scops with invariant loads. 2452 if (S->hasInvariantAccesses()) 2453 return false; 2454 2455 auto PPCGScop = createPPCGScop(); 2456 auto PPCGProg = createPPCGProg(PPCGScop); 2457 auto PPCGGen = generateGPU(PPCGScop, PPCGProg); 2458 2459 if (PPCGGen->tree) 2460 generateCode(isl_ast_node_copy(PPCGGen->tree), PPCGProg); 2461 2462 freeOptions(PPCGScop); 2463 freePPCGGen(PPCGGen); 2464 gpu_prog_free(PPCGProg); 2465 ppcg_scop_free(PPCGScop); 2466 2467 return true; 2468 } 2469 2470 void printScop(raw_ostream &, Scop &) const override {} 2471 2472 void getAnalysisUsage(AnalysisUsage &AU) const override { 2473 AU.addRequired<DominatorTreeWrapperPass>(); 2474 AU.addRequired<RegionInfoPass>(); 2475 AU.addRequired<ScalarEvolutionWrapperPass>(); 2476 AU.addRequired<ScopDetection>(); 2477 AU.addRequired<ScopInfoRegionPass>(); 2478 AU.addRequired<LoopInfoWrapperPass>(); 2479 2480 AU.addPreserved<AAResultsWrapperPass>(); 2481 AU.addPreserved<BasicAAWrapperPass>(); 2482 AU.addPreserved<LoopInfoWrapperPass>(); 2483 AU.addPreserved<DominatorTreeWrapperPass>(); 2484 AU.addPreserved<GlobalsAAWrapperPass>(); 2485 AU.addPreserved<PostDominatorTreeWrapperPass>(); 2486 AU.addPreserved<ScopDetection>(); 2487 AU.addPreserved<ScalarEvolutionWrapperPass>(); 2488 AU.addPreserved<SCEVAAWrapperPass>(); 2489 2490 // FIXME: We do not yet add regions for the newly generated code to the 2491 // region tree. 2492 AU.addPreserved<RegionInfoPass>(); 2493 AU.addPreserved<ScopInfoRegionPass>(); 2494 } 2495 }; 2496 } 2497 2498 char PPCGCodeGeneration::ID = 1; 2499 2500 Pass *polly::createPPCGCodeGenerationPass() { return new PPCGCodeGeneration(); } 2501 2502 INITIALIZE_PASS_BEGIN(PPCGCodeGeneration, "polly-codegen-ppcg", 2503 "Polly - Apply PPCG translation to SCOP", false, false) 2504 INITIALIZE_PASS_DEPENDENCY(DependenceInfo); 2505 INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass); 2506 INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass); 2507 INITIALIZE_PASS_DEPENDENCY(RegionInfoPass); 2508 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass); 2509 INITIALIZE_PASS_DEPENDENCY(ScopDetection); 2510 INITIALIZE_PASS_END(PPCGCodeGeneration, "polly-codegen-ppcg", 2511 "Polly - Apply PPCG translation to SCOP", false, false) 2512