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 private: 167 /// A vector of array base pointers for which a new ScopArrayInfo was created. 168 /// 169 /// This vector is used to delete the ScopArrayInfo when it is not needed any 170 /// more. 171 std::vector<Value *> LocalArrays; 172 173 /// A map from ScopArrays to their corresponding device allocations. 174 std::map<ScopArrayInfo *, Value *> DeviceAllocations; 175 176 /// The current GPU context. 177 Value *GPUContext; 178 179 /// The set of isl_ids allocated in the kernel 180 std::vector<isl_id *> KernelIds; 181 182 /// A module containing GPU code. 183 /// 184 /// This pointer is only set in case we are currently generating GPU code. 185 std::unique_ptr<Module> GPUModule; 186 187 /// The GPU program we generate code for. 188 gpu_prog *Prog; 189 190 /// Class to free isl_ids. 191 class IslIdDeleter { 192 public: 193 void operator()(__isl_take isl_id *Id) { isl_id_free(Id); }; 194 }; 195 196 /// A set containing all isl_ids allocated in a GPU kernel. 197 /// 198 /// By releasing this set all isl_ids will be freed. 199 std::set<std::unique_ptr<isl_id, IslIdDeleter>> KernelIDs; 200 201 IslExprBuilder::IDToScopArrayInfoTy IDToSAI; 202 203 /// Create code for user-defined AST nodes. 204 /// 205 /// These AST nodes can be of type: 206 /// 207 /// - ScopStmt: A computational statement (TODO) 208 /// - Kernel: A GPU kernel call (TODO) 209 /// - Data-Transfer: A GPU <-> CPU data-transfer 210 /// - In-kernel synchronization 211 /// - In-kernel memory copy statement 212 /// 213 /// @param UserStmt The ast node to generate code for. 214 virtual void createUser(__isl_take isl_ast_node *UserStmt); 215 216 enum DataDirection { HOST_TO_DEVICE, DEVICE_TO_HOST }; 217 218 /// Create code for a data transfer statement 219 /// 220 /// @param TransferStmt The data transfer statement. 221 /// @param Direction The direction in which to transfer data. 222 void createDataTransfer(__isl_take isl_ast_node *TransferStmt, 223 enum DataDirection Direction); 224 225 /// Find llvm::Values referenced in GPU kernel. 226 /// 227 /// @param Kernel The kernel to scan for llvm::Values 228 /// 229 /// @returns A set of values referenced by the kernel. 230 SetVector<Value *> getReferencesInKernel(ppcg_kernel *Kernel); 231 232 /// Compute the sizes of the execution grid for a given kernel. 233 /// 234 /// @param Kernel The kernel to compute grid sizes for. 235 /// 236 /// @returns A tuple with grid sizes for X and Y dimension 237 std::tuple<Value *, Value *> getGridSizes(ppcg_kernel *Kernel); 238 239 /// Compute the sizes of the thread blocks for a given kernel. 240 /// 241 /// @param Kernel The kernel to compute thread block sizes for. 242 /// 243 /// @returns A tuple with thread block sizes for X, Y, and Z dimensions. 244 std::tuple<Value *, Value *, Value *> getBlockSizes(ppcg_kernel *Kernel); 245 246 /// Create kernel launch parameters. 247 /// 248 /// @param Kernel The kernel to create parameters for. 249 /// @param F The kernel function that has been created. 250 /// @param SubtreeValues The set of llvm::Values referenced by this kernel. 251 /// 252 /// @returns A stack allocated array with pointers to the parameter 253 /// values that are passed to the kernel. 254 Value *createLaunchParameters(ppcg_kernel *Kernel, Function *F, 255 SetVector<Value *> SubtreeValues); 256 257 /// Create declarations for kernel variable. 258 /// 259 /// This includes shared memory declarations. 260 /// 261 /// @param Kernel The kernel definition to create variables for. 262 /// @param FN The function into which to generate the variables. 263 void createKernelVariables(ppcg_kernel *Kernel, Function *FN); 264 265 /// Add CUDA annotations to module. 266 /// 267 /// Add a set of CUDA annotations that declares the maximal block dimensions 268 /// that will be used to execute the CUDA kernel. This allows the NVIDIA 269 /// PTX compiler to bound the number of allocated registers to ensure the 270 /// resulting kernel is known to run with up to as many block dimensions 271 /// as specified here. 272 /// 273 /// @param M The module to add the annotations to. 274 /// @param BlockDimX The size of block dimension X. 275 /// @param BlockDimY The size of block dimension Y. 276 /// @param BlockDimZ The size of block dimension Z. 277 void addCUDAAnnotations(Module *M, Value *BlockDimX, Value *BlockDimY, 278 Value *BlockDimZ); 279 280 /// Create GPU kernel. 281 /// 282 /// Code generate the kernel described by @p KernelStmt. 283 /// 284 /// @param KernelStmt The ast node to generate kernel code for. 285 void createKernel(__isl_take isl_ast_node *KernelStmt); 286 287 /// Generate code that computes the size of an array. 288 /// 289 /// @param Array The array for which to compute a size. 290 Value *getArraySize(gpu_array_info *Array); 291 292 /// Generate code to compute the minimal offset at which an array is accessed. 293 /// 294 /// The offset of an array is the minimal array location accessed in a scop. 295 /// 296 /// Example: 297 /// 298 /// for (long i = 0; i < 100; i++) 299 /// A[i + 42] += ... 300 /// 301 /// getArrayOffset(A) results in 42. 302 /// 303 /// @param Array The array for which to compute the offset. 304 /// @returns An llvm::Value that contains the offset of the array. 305 Value *getArrayOffset(gpu_array_info *Array); 306 307 /// Prepare the kernel arguments for kernel code generation 308 /// 309 /// @param Kernel The kernel to generate code for. 310 /// @param FN The function created for the kernel. 311 void prepareKernelArguments(ppcg_kernel *Kernel, Function *FN); 312 313 /// Create kernel function. 314 /// 315 /// Create a kernel function located in a newly created module that can serve 316 /// as target for device code generation. Set the Builder to point to the 317 /// start block of this newly created function. 318 /// 319 /// @param Kernel The kernel to generate code for. 320 /// @param SubtreeValues The set of llvm::Values referenced by this kernel. 321 void createKernelFunction(ppcg_kernel *Kernel, 322 SetVector<Value *> &SubtreeValues); 323 324 /// Create the declaration of a kernel function. 325 /// 326 /// The kernel function takes as arguments: 327 /// 328 /// - One i8 pointer for each external array reference used in the kernel. 329 /// - Host iterators 330 /// - Parameters 331 /// - Other LLVM Value references (TODO) 332 /// 333 /// @param Kernel The kernel to generate the function declaration for. 334 /// @param SubtreeValues The set of llvm::Values referenced by this kernel. 335 /// 336 /// @returns The newly declared function. 337 Function *createKernelFunctionDecl(ppcg_kernel *Kernel, 338 SetVector<Value *> &SubtreeValues); 339 340 /// Insert intrinsic functions to obtain thread and block ids. 341 /// 342 /// @param The kernel to generate the intrinsic functions for. 343 void insertKernelIntrinsics(ppcg_kernel *Kernel); 344 345 /// Create a global-to-shared or shared-to-global copy statement. 346 /// 347 /// @param CopyStmt The copy statement to generate code for 348 void createKernelCopy(ppcg_kernel_stmt *CopyStmt); 349 350 /// Create code for a ScopStmt called in @p Expr. 351 /// 352 /// @param Expr The expression containing the call. 353 /// @param KernelStmt The kernel statement referenced in the call. 354 void createScopStmt(isl_ast_expr *Expr, ppcg_kernel_stmt *KernelStmt); 355 356 /// Create an in-kernel synchronization call. 357 void createKernelSync(); 358 359 /// Create a PTX assembly string for the current GPU kernel. 360 /// 361 /// @returns A string containing the corresponding PTX assembly code. 362 std::string createKernelASM(); 363 364 /// Remove references from the dominator tree to the kernel function @p F. 365 /// 366 /// @param F The function to remove references to. 367 void clearDominators(Function *F); 368 369 /// Remove references from scalar evolution to the kernel function @p F. 370 /// 371 /// @param F The function to remove references to. 372 void clearScalarEvolution(Function *F); 373 374 /// Remove references from loop info to the kernel function @p F. 375 /// 376 /// @param F The function to remove references to. 377 void clearLoops(Function *F); 378 379 /// Finalize the generation of the kernel function. 380 /// 381 /// Free the LLVM-IR module corresponding to the kernel and -- if requested -- 382 /// dump its IR to stderr. 383 /// 384 /// @returns The Assembly string of the kernel. 385 std::string finalizeKernelFunction(); 386 387 /// Finalize the generation of the kernel arguments. 388 /// 389 /// This function ensures that not-read-only scalars used in a kernel are 390 /// stored back to the global memory location they ared backed up with before 391 /// the kernel terminates. 392 /// 393 /// @params Kernel The kernel to finalize kernel arguments for. 394 void finalizeKernelArguments(ppcg_kernel *Kernel); 395 396 /// Create code that allocates memory to store arrays on device. 397 void allocateDeviceArrays(); 398 399 /// Free all allocated device arrays. 400 void freeDeviceArrays(); 401 402 /// Create a call to initialize the GPU context. 403 /// 404 /// @returns A pointer to the newly initialized context. 405 Value *createCallInitContext(); 406 407 /// Create a call to get the device pointer for a kernel allocation. 408 /// 409 /// @param Allocation The Polly GPU allocation 410 /// 411 /// @returns The device parameter corresponding to this allocation. 412 Value *createCallGetDevicePtr(Value *Allocation); 413 414 /// Create a call to free the GPU context. 415 /// 416 /// @param Context A pointer to an initialized GPU context. 417 void createCallFreeContext(Value *Context); 418 419 /// Create a call to allocate memory on the device. 420 /// 421 /// @param Size The size of memory to allocate 422 /// 423 /// @returns A pointer that identifies this allocation. 424 Value *createCallAllocateMemoryForDevice(Value *Size); 425 426 /// Create a call to free a device array. 427 /// 428 /// @param Array The device array to free. 429 void createCallFreeDeviceMemory(Value *Array); 430 431 /// Create a call to copy data from host to device. 432 /// 433 /// @param HostPtr A pointer to the host data that should be copied. 434 /// @param DevicePtr A device pointer specifying the location to copy to. 435 void createCallCopyFromHostToDevice(Value *HostPtr, Value *DevicePtr, 436 Value *Size); 437 438 /// Create a call to copy data from device to host. 439 /// 440 /// @param DevicePtr A pointer to the device data that should be copied. 441 /// @param HostPtr A host pointer specifying the location to copy to. 442 void createCallCopyFromDeviceToHost(Value *DevicePtr, Value *HostPtr, 443 Value *Size); 444 445 /// Create a call to get a kernel from an assembly string. 446 /// 447 /// @param Buffer The string describing the kernel. 448 /// @param Entry The name of the kernel function to call. 449 /// 450 /// @returns A pointer to a kernel object 451 Value *createCallGetKernel(Value *Buffer, Value *Entry); 452 453 /// Create a call to free a GPU kernel. 454 /// 455 /// @param GPUKernel THe kernel to free. 456 void createCallFreeKernel(Value *GPUKernel); 457 458 /// Create a call to launch a GPU kernel. 459 /// 460 /// @param GPUKernel The kernel to launch. 461 /// @param GridDimX The size of the first grid dimension. 462 /// @param GridDimY The size of the second grid dimension. 463 /// @param GridBlockX The size of the first block dimension. 464 /// @param GridBlockY The size of the second block dimension. 465 /// @param GridBlockZ The size of the third block dimension. 466 /// @param Paramters A pointer to an array that contains itself pointers to 467 /// the parameter values passed for each kernel argument. 468 void createCallLaunchKernel(Value *GPUKernel, Value *GridDimX, 469 Value *GridDimY, Value *BlockDimX, 470 Value *BlockDimY, Value *BlockDimZ, 471 Value *Parameters); 472 }; 473 474 void GPUNodeBuilder::initializeAfterRTH() { 475 BasicBlock *NewBB = SplitBlock(Builder.GetInsertBlock(), 476 &*Builder.GetInsertPoint(), &DT, &LI); 477 NewBB->setName("polly.acc.initialize"); 478 Builder.SetInsertPoint(&NewBB->front()); 479 480 GPUContext = createCallInitContext(); 481 allocateDeviceArrays(); 482 } 483 484 void GPUNodeBuilder::finalize() { 485 freeDeviceArrays(); 486 createCallFreeContext(GPUContext); 487 IslNodeBuilder::finalize(); 488 } 489 490 void GPUNodeBuilder::allocateDeviceArrays() { 491 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 492 493 for (int i = 0; i < Prog->n_array; ++i) { 494 gpu_array_info *Array = &Prog->array[i]; 495 auto *ScopArray = (ScopArrayInfo *)Array->user; 496 std::string DevArrayName("p_dev_array_"); 497 DevArrayName.append(Array->name); 498 499 Value *ArraySize = getArraySize(Array); 500 Value *Offset = getArrayOffset(Array); 501 if (Offset) 502 ArraySize = Builder.CreateSub( 503 ArraySize, 504 Builder.CreateMul(Offset, 505 Builder.getInt64(ScopArray->getElemSizeInBytes()))); 506 Value *DevArray = createCallAllocateMemoryForDevice(ArraySize); 507 DevArray->setName(DevArrayName); 508 DeviceAllocations[ScopArray] = DevArray; 509 } 510 511 isl_ast_build_free(Build); 512 } 513 514 void GPUNodeBuilder::addCUDAAnnotations(Module *M, Value *BlockDimX, 515 Value *BlockDimY, Value *BlockDimZ) { 516 auto AnnotationNode = M->getOrInsertNamedMetadata("nvvm.annotations"); 517 518 for (auto &F : *M) { 519 if (F.getCallingConv() != CallingConv::PTX_Kernel) 520 continue; 521 522 Value *V[] = {BlockDimX, BlockDimY, BlockDimZ}; 523 524 Metadata *Elements[] = { 525 ValueAsMetadata::get(&F), MDString::get(M->getContext(), "maxntidx"), 526 ValueAsMetadata::get(V[0]), MDString::get(M->getContext(), "maxntidy"), 527 ValueAsMetadata::get(V[1]), MDString::get(M->getContext(), "maxntidz"), 528 ValueAsMetadata::get(V[2]), 529 }; 530 MDNode *Node = MDNode::get(M->getContext(), Elements); 531 AnnotationNode->addOperand(Node); 532 } 533 } 534 535 void GPUNodeBuilder::freeDeviceArrays() { 536 for (auto &Array : DeviceAllocations) 537 createCallFreeDeviceMemory(Array.second); 538 } 539 540 Value *GPUNodeBuilder::createCallGetKernel(Value *Buffer, Value *Entry) { 541 const char *Name = "polly_getKernel"; 542 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 543 Function *F = M->getFunction(Name); 544 545 // If F is not available, declare it. 546 if (!F) { 547 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 548 std::vector<Type *> Args; 549 Args.push_back(Builder.getInt8PtrTy()); 550 Args.push_back(Builder.getInt8PtrTy()); 551 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 552 F = Function::Create(Ty, Linkage, Name, M); 553 } 554 555 return Builder.CreateCall(F, {Buffer, Entry}); 556 } 557 558 Value *GPUNodeBuilder::createCallGetDevicePtr(Value *Allocation) { 559 const char *Name = "polly_getDevicePtr"; 560 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 561 Function *F = M->getFunction(Name); 562 563 // If F is not available, declare it. 564 if (!F) { 565 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 566 std::vector<Type *> Args; 567 Args.push_back(Builder.getInt8PtrTy()); 568 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 569 F = Function::Create(Ty, Linkage, Name, M); 570 } 571 572 return Builder.CreateCall(F, {Allocation}); 573 } 574 575 void GPUNodeBuilder::createCallLaunchKernel(Value *GPUKernel, Value *GridDimX, 576 Value *GridDimY, Value *BlockDimX, 577 Value *BlockDimY, Value *BlockDimZ, 578 Value *Parameters) { 579 const char *Name = "polly_launchKernel"; 580 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 581 Function *F = M->getFunction(Name); 582 583 // If F is not available, declare it. 584 if (!F) { 585 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 586 std::vector<Type *> Args; 587 Args.push_back(Builder.getInt8PtrTy()); 588 Args.push_back(Builder.getInt32Ty()); 589 Args.push_back(Builder.getInt32Ty()); 590 Args.push_back(Builder.getInt32Ty()); 591 Args.push_back(Builder.getInt32Ty()); 592 Args.push_back(Builder.getInt32Ty()); 593 Args.push_back(Builder.getInt8PtrTy()); 594 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 595 F = Function::Create(Ty, Linkage, Name, M); 596 } 597 598 Builder.CreateCall(F, {GPUKernel, GridDimX, GridDimY, BlockDimX, BlockDimY, 599 BlockDimZ, Parameters}); 600 } 601 602 void GPUNodeBuilder::createCallFreeKernel(Value *GPUKernel) { 603 const char *Name = "polly_freeKernel"; 604 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 605 Function *F = M->getFunction(Name); 606 607 // If F is not available, declare it. 608 if (!F) { 609 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 610 std::vector<Type *> Args; 611 Args.push_back(Builder.getInt8PtrTy()); 612 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 613 F = Function::Create(Ty, Linkage, Name, M); 614 } 615 616 Builder.CreateCall(F, {GPUKernel}); 617 } 618 619 void GPUNodeBuilder::createCallFreeDeviceMemory(Value *Array) { 620 const char *Name = "polly_freeDeviceMemory"; 621 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 622 Function *F = M->getFunction(Name); 623 624 // If F is not available, declare it. 625 if (!F) { 626 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 627 std::vector<Type *> Args; 628 Args.push_back(Builder.getInt8PtrTy()); 629 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 630 F = Function::Create(Ty, Linkage, Name, M); 631 } 632 633 Builder.CreateCall(F, {Array}); 634 } 635 636 Value *GPUNodeBuilder::createCallAllocateMemoryForDevice(Value *Size) { 637 const char *Name = "polly_allocateMemoryForDevice"; 638 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 639 Function *F = M->getFunction(Name); 640 641 // If F is not available, declare it. 642 if (!F) { 643 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 644 std::vector<Type *> Args; 645 Args.push_back(Builder.getInt64Ty()); 646 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 647 F = Function::Create(Ty, Linkage, Name, M); 648 } 649 650 return Builder.CreateCall(F, {Size}); 651 } 652 653 void GPUNodeBuilder::createCallCopyFromHostToDevice(Value *HostData, 654 Value *DeviceData, 655 Value *Size) { 656 const char *Name = "polly_copyFromHostToDevice"; 657 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 658 Function *F = M->getFunction(Name); 659 660 // If F is not available, declare it. 661 if (!F) { 662 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 663 std::vector<Type *> Args; 664 Args.push_back(Builder.getInt8PtrTy()); 665 Args.push_back(Builder.getInt8PtrTy()); 666 Args.push_back(Builder.getInt64Ty()); 667 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 668 F = Function::Create(Ty, Linkage, Name, M); 669 } 670 671 Builder.CreateCall(F, {HostData, DeviceData, Size}); 672 } 673 674 void GPUNodeBuilder::createCallCopyFromDeviceToHost(Value *DeviceData, 675 Value *HostData, 676 Value *Size) { 677 const char *Name = "polly_copyFromDeviceToHost"; 678 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 679 Function *F = M->getFunction(Name); 680 681 // If F is not available, declare it. 682 if (!F) { 683 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 684 std::vector<Type *> Args; 685 Args.push_back(Builder.getInt8PtrTy()); 686 Args.push_back(Builder.getInt8PtrTy()); 687 Args.push_back(Builder.getInt64Ty()); 688 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 689 F = Function::Create(Ty, Linkage, Name, M); 690 } 691 692 Builder.CreateCall(F, {DeviceData, HostData, Size}); 693 } 694 695 Value *GPUNodeBuilder::createCallInitContext() { 696 const char *Name = "polly_initContext"; 697 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 698 Function *F = M->getFunction(Name); 699 700 // If F is not available, declare it. 701 if (!F) { 702 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 703 std::vector<Type *> Args; 704 FunctionType *Ty = FunctionType::get(Builder.getInt8PtrTy(), Args, false); 705 F = Function::Create(Ty, Linkage, Name, M); 706 } 707 708 return Builder.CreateCall(F, {}); 709 } 710 711 void GPUNodeBuilder::createCallFreeContext(Value *Context) { 712 const char *Name = "polly_freeContext"; 713 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 714 Function *F = M->getFunction(Name); 715 716 // If F is not available, declare it. 717 if (!F) { 718 GlobalValue::LinkageTypes Linkage = Function::ExternalLinkage; 719 std::vector<Type *> Args; 720 Args.push_back(Builder.getInt8PtrTy()); 721 FunctionType *Ty = FunctionType::get(Builder.getVoidTy(), Args, false); 722 F = Function::Create(Ty, Linkage, Name, M); 723 } 724 725 Builder.CreateCall(F, {Context}); 726 } 727 728 /// Check if one string is a prefix of another. 729 /// 730 /// @param String The string in which to look for the prefix. 731 /// @param Prefix The prefix to look for. 732 static bool isPrefix(std::string String, std::string Prefix) { 733 return String.find(Prefix) == 0; 734 } 735 736 Value *GPUNodeBuilder::getArraySize(gpu_array_info *Array) { 737 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 738 Value *ArraySize = ConstantInt::get(Builder.getInt64Ty(), Array->size); 739 740 if (!gpu_array_is_scalar(Array)) { 741 auto OffsetDimZero = isl_pw_aff_copy(Array->bound[0]); 742 isl_ast_expr *Res = isl_ast_build_expr_from_pw_aff(Build, OffsetDimZero); 743 744 for (unsigned int i = 1; i < Array->n_index; i++) { 745 isl_pw_aff *Bound_I = isl_pw_aff_copy(Array->bound[i]); 746 isl_ast_expr *Expr = isl_ast_build_expr_from_pw_aff(Build, Bound_I); 747 Res = isl_ast_expr_mul(Res, Expr); 748 } 749 750 Value *NumElements = ExprBuilder.create(Res); 751 if (NumElements->getType() != ArraySize->getType()) 752 NumElements = Builder.CreateSExt(NumElements, ArraySize->getType()); 753 ArraySize = Builder.CreateMul(ArraySize, NumElements); 754 } 755 isl_ast_build_free(Build); 756 return ArraySize; 757 } 758 759 Value *GPUNodeBuilder::getArrayOffset(gpu_array_info *Array) { 760 if (gpu_array_is_scalar(Array)) 761 return nullptr; 762 763 isl_ast_build *Build = isl_ast_build_from_context(S.getContext()); 764 765 isl_set *Min = isl_set_lexmin(isl_set_copy(Array->extent)); 766 767 isl_set *ZeroSet = isl_set_universe(isl_set_get_space(Min)); 768 769 for (long i = 0; i < isl_set_dim(Min, isl_dim_set); i++) 770 ZeroSet = isl_set_fix_si(ZeroSet, isl_dim_set, i, 0); 771 772 if (isl_set_is_subset(Min, ZeroSet)) { 773 isl_set_free(Min); 774 isl_set_free(ZeroSet); 775 isl_ast_build_free(Build); 776 return nullptr; 777 } 778 isl_set_free(ZeroSet); 779 780 isl_ast_expr *Result = 781 isl_ast_expr_from_val(isl_val_int_from_si(isl_set_get_ctx(Min), 0)); 782 783 for (long i = 0; i < isl_set_dim(Min, isl_dim_set); i++) { 784 if (i > 0) { 785 isl_pw_aff *Bound_I = isl_pw_aff_copy(Array->bound[i - 1]); 786 isl_ast_expr *BExpr = isl_ast_build_expr_from_pw_aff(Build, Bound_I); 787 Result = isl_ast_expr_mul(Result, BExpr); 788 } 789 isl_pw_aff *DimMin = isl_set_dim_min(isl_set_copy(Min), i); 790 isl_ast_expr *MExpr = isl_ast_build_expr_from_pw_aff(Build, DimMin); 791 Result = isl_ast_expr_add(Result, MExpr); 792 } 793 794 Value *ResultValue = ExprBuilder.create(Result); 795 isl_set_free(Min); 796 isl_ast_build_free(Build); 797 798 return ResultValue; 799 } 800 801 void GPUNodeBuilder::createDataTransfer(__isl_take isl_ast_node *TransferStmt, 802 enum DataDirection Direction) { 803 isl_ast_expr *Expr = isl_ast_node_user_get_expr(TransferStmt); 804 isl_ast_expr *Arg = isl_ast_expr_get_op_arg(Expr, 0); 805 isl_id *Id = isl_ast_expr_get_id(Arg); 806 auto Array = (gpu_array_info *)isl_id_get_user(Id); 807 auto ScopArray = (ScopArrayInfo *)(Array->user); 808 809 Value *Size = getArraySize(Array); 810 Value *Offset = getArrayOffset(Array); 811 Value *DevPtr = DeviceAllocations[ScopArray]; 812 813 Value *HostPtr; 814 815 if (gpu_array_is_scalar(Array)) 816 HostPtr = BlockGen.getOrCreateAlloca(ScopArray); 817 else 818 HostPtr = ScopArray->getBasePtr(); 819 820 if (Offset) { 821 HostPtr = Builder.CreatePointerCast( 822 HostPtr, ScopArray->getElementType()->getPointerTo()); 823 HostPtr = Builder.CreateGEP(HostPtr, Offset); 824 } 825 826 HostPtr = Builder.CreatePointerCast(HostPtr, Builder.getInt8PtrTy()); 827 828 if (Offset) { 829 Size = Builder.CreateSub( 830 Size, Builder.CreateMul( 831 Offset, Builder.getInt64(ScopArray->getElemSizeInBytes()))); 832 } 833 834 if (Direction == HOST_TO_DEVICE) 835 createCallCopyFromHostToDevice(HostPtr, DevPtr, Size); 836 else 837 createCallCopyFromDeviceToHost(DevPtr, HostPtr, Size); 838 839 isl_id_free(Id); 840 isl_ast_expr_free(Arg); 841 isl_ast_expr_free(Expr); 842 isl_ast_node_free(TransferStmt); 843 } 844 845 void GPUNodeBuilder::createUser(__isl_take isl_ast_node *UserStmt) { 846 isl_ast_expr *Expr = isl_ast_node_user_get_expr(UserStmt); 847 isl_ast_expr *StmtExpr = isl_ast_expr_get_op_arg(Expr, 0); 848 isl_id *Id = isl_ast_expr_get_id(StmtExpr); 849 isl_id_free(Id); 850 isl_ast_expr_free(StmtExpr); 851 852 const char *Str = isl_id_get_name(Id); 853 if (!strcmp(Str, "kernel")) { 854 createKernel(UserStmt); 855 isl_ast_expr_free(Expr); 856 return; 857 } 858 859 if (isPrefix(Str, "to_device")) { 860 createDataTransfer(UserStmt, HOST_TO_DEVICE); 861 isl_ast_expr_free(Expr); 862 return; 863 } 864 865 if (isPrefix(Str, "from_device")) { 866 createDataTransfer(UserStmt, DEVICE_TO_HOST); 867 isl_ast_expr_free(Expr); 868 return; 869 } 870 871 isl_id *Anno = isl_ast_node_get_annotation(UserStmt); 872 struct ppcg_kernel_stmt *KernelStmt = 873 (struct ppcg_kernel_stmt *)isl_id_get_user(Anno); 874 isl_id_free(Anno); 875 876 switch (KernelStmt->type) { 877 case ppcg_kernel_domain: 878 createScopStmt(Expr, KernelStmt); 879 isl_ast_node_free(UserStmt); 880 return; 881 case ppcg_kernel_copy: 882 createKernelCopy(KernelStmt); 883 isl_ast_expr_free(Expr); 884 isl_ast_node_free(UserStmt); 885 return; 886 case ppcg_kernel_sync: 887 createKernelSync(); 888 isl_ast_expr_free(Expr); 889 isl_ast_node_free(UserStmt); 890 return; 891 } 892 893 isl_ast_expr_free(Expr); 894 isl_ast_node_free(UserStmt); 895 return; 896 } 897 void GPUNodeBuilder::createKernelCopy(ppcg_kernel_stmt *KernelStmt) { 898 isl_ast_expr *LocalIndex = isl_ast_expr_copy(KernelStmt->u.c.local_index); 899 LocalIndex = isl_ast_expr_address_of(LocalIndex); 900 Value *LocalAddr = ExprBuilder.create(LocalIndex); 901 isl_ast_expr *Index = isl_ast_expr_copy(KernelStmt->u.c.index); 902 Index = isl_ast_expr_address_of(Index); 903 Value *GlobalAddr = ExprBuilder.create(Index); 904 905 if (KernelStmt->u.c.read) { 906 LoadInst *Load = Builder.CreateLoad(GlobalAddr, "shared.read"); 907 Builder.CreateStore(Load, LocalAddr); 908 } else { 909 LoadInst *Load = Builder.CreateLoad(LocalAddr, "shared.write"); 910 Builder.CreateStore(Load, GlobalAddr); 911 } 912 } 913 914 void GPUNodeBuilder::createScopStmt(isl_ast_expr *Expr, 915 ppcg_kernel_stmt *KernelStmt) { 916 auto Stmt = (ScopStmt *)KernelStmt->u.d.stmt->stmt; 917 isl_id_to_ast_expr *Indexes = KernelStmt->u.d.ref2expr; 918 919 LoopToScevMapT LTS; 920 LTS.insert(OutsideLoopIterations.begin(), OutsideLoopIterations.end()); 921 922 createSubstitutions(Expr, Stmt, LTS); 923 924 if (Stmt->isBlockStmt()) 925 BlockGen.copyStmt(*Stmt, LTS, Indexes); 926 else 927 RegionGen.copyStmt(*Stmt, LTS, Indexes); 928 } 929 930 void GPUNodeBuilder::createKernelSync() { 931 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 932 auto *Sync = Intrinsic::getDeclaration(M, Intrinsic::nvvm_barrier0); 933 Builder.CreateCall(Sync, {}); 934 } 935 936 /// Collect llvm::Values referenced from @p Node 937 /// 938 /// This function only applies to isl_ast_nodes that are user_nodes referring 939 /// to a ScopStmt. All other node types are ignore. 940 /// 941 /// @param Node The node to collect references for. 942 /// @param User A user pointer used as storage for the data that is collected. 943 /// 944 /// @returns isl_bool_true if data could be collected successfully. 945 isl_bool collectReferencesInGPUStmt(__isl_keep isl_ast_node *Node, void *User) { 946 if (isl_ast_node_get_type(Node) != isl_ast_node_user) 947 return isl_bool_true; 948 949 isl_ast_expr *Expr = isl_ast_node_user_get_expr(Node); 950 isl_ast_expr *StmtExpr = isl_ast_expr_get_op_arg(Expr, 0); 951 isl_id *Id = isl_ast_expr_get_id(StmtExpr); 952 const char *Str = isl_id_get_name(Id); 953 isl_id_free(Id); 954 isl_ast_expr_free(StmtExpr); 955 isl_ast_expr_free(Expr); 956 957 if (!isPrefix(Str, "Stmt")) 958 return isl_bool_true; 959 960 Id = isl_ast_node_get_annotation(Node); 961 auto *KernelStmt = (ppcg_kernel_stmt *)isl_id_get_user(Id); 962 auto Stmt = (ScopStmt *)KernelStmt->u.d.stmt->stmt; 963 isl_id_free(Id); 964 965 addReferencesFromStmt(Stmt, User, false /* CreateScalarRefs */); 966 967 return isl_bool_true; 968 } 969 970 SetVector<Value *> GPUNodeBuilder::getReferencesInKernel(ppcg_kernel *Kernel) { 971 SetVector<Value *> SubtreeValues; 972 SetVector<const SCEV *> SCEVs; 973 SetVector<const Loop *> Loops; 974 SubtreeReferences References = { 975 LI, SE, S, ValueMap, SubtreeValues, SCEVs, getBlockGenerator()}; 976 977 for (const auto &I : IDToValue) 978 SubtreeValues.insert(I.second); 979 980 isl_ast_node_foreach_descendant_top_down( 981 Kernel->tree, collectReferencesInGPUStmt, &References); 982 983 for (const SCEV *Expr : SCEVs) 984 findValues(Expr, SE, SubtreeValues); 985 986 for (auto &SAI : S.arrays()) 987 SubtreeValues.remove(SAI->getBasePtr()); 988 989 isl_space *Space = S.getParamSpace(); 990 for (long i = 0; i < isl_space_dim(Space, isl_dim_param); i++) { 991 isl_id *Id = isl_space_get_dim_id(Space, isl_dim_param, i); 992 assert(IDToValue.count(Id)); 993 Value *Val = IDToValue[Id]; 994 SubtreeValues.remove(Val); 995 isl_id_free(Id); 996 } 997 isl_space_free(Space); 998 999 for (long i = 0; i < isl_space_dim(Kernel->space, isl_dim_set); i++) { 1000 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1001 assert(IDToValue.count(Id)); 1002 Value *Val = IDToValue[Id]; 1003 SubtreeValues.remove(Val); 1004 isl_id_free(Id); 1005 } 1006 1007 return SubtreeValues; 1008 } 1009 1010 void GPUNodeBuilder::clearDominators(Function *F) { 1011 DomTreeNode *N = DT.getNode(&F->getEntryBlock()); 1012 std::vector<BasicBlock *> Nodes; 1013 for (po_iterator<DomTreeNode *> I = po_begin(N), E = po_end(N); I != E; ++I) 1014 Nodes.push_back(I->getBlock()); 1015 1016 for (BasicBlock *BB : Nodes) 1017 DT.eraseNode(BB); 1018 } 1019 1020 void GPUNodeBuilder::clearScalarEvolution(Function *F) { 1021 for (BasicBlock &BB : *F) { 1022 Loop *L = LI.getLoopFor(&BB); 1023 if (L) 1024 SE.forgetLoop(L); 1025 } 1026 } 1027 1028 void GPUNodeBuilder::clearLoops(Function *F) { 1029 for (BasicBlock &BB : *F) { 1030 Loop *L = LI.getLoopFor(&BB); 1031 if (L) 1032 SE.forgetLoop(L); 1033 LI.removeBlock(&BB); 1034 } 1035 } 1036 1037 std::tuple<Value *, Value *> GPUNodeBuilder::getGridSizes(ppcg_kernel *Kernel) { 1038 std::vector<Value *> Sizes; 1039 isl_ast_build *Context = isl_ast_build_from_context(S.getContext()); 1040 1041 for (long i = 0; i < Kernel->n_grid; i++) { 1042 isl_pw_aff *Size = isl_multi_pw_aff_get_pw_aff(Kernel->grid_size, i); 1043 isl_ast_expr *GridSize = isl_ast_build_expr_from_pw_aff(Context, Size); 1044 Value *Res = ExprBuilder.create(GridSize); 1045 Res = Builder.CreateTrunc(Res, Builder.getInt32Ty()); 1046 Sizes.push_back(Res); 1047 } 1048 isl_ast_build_free(Context); 1049 1050 for (long i = Kernel->n_grid; i < 3; i++) 1051 Sizes.push_back(ConstantInt::get(Builder.getInt32Ty(), 1)); 1052 1053 return std::make_tuple(Sizes[0], Sizes[1]); 1054 } 1055 1056 std::tuple<Value *, Value *, Value *> 1057 GPUNodeBuilder::getBlockSizes(ppcg_kernel *Kernel) { 1058 std::vector<Value *> Sizes; 1059 1060 for (long i = 0; i < Kernel->n_block; i++) { 1061 Value *Res = ConstantInt::get(Builder.getInt32Ty(), Kernel->block_dim[i]); 1062 Sizes.push_back(Res); 1063 } 1064 1065 for (long i = Kernel->n_block; i < 3; i++) 1066 Sizes.push_back(ConstantInt::get(Builder.getInt32Ty(), 1)); 1067 1068 return std::make_tuple(Sizes[0], Sizes[1], Sizes[2]); 1069 } 1070 1071 Value * 1072 GPUNodeBuilder::createLaunchParameters(ppcg_kernel *Kernel, Function *F, 1073 SetVector<Value *> SubtreeValues) { 1074 Type *ArrayTy = ArrayType::get(Builder.getInt8PtrTy(), 1075 std::distance(F->arg_begin(), F->arg_end())); 1076 1077 BasicBlock *EntryBlock = 1078 &Builder.GetInsertBlock()->getParent()->getEntryBlock(); 1079 std::string Launch = "polly_launch_" + std::to_string(Kernel->id); 1080 Instruction *Parameters = 1081 new AllocaInst(ArrayTy, Launch + "_params", EntryBlock->getTerminator()); 1082 1083 int Index = 0; 1084 for (long i = 0; i < Prog->n_array; i++) { 1085 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1086 continue; 1087 1088 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1089 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(Id); 1090 1091 Value *DevArray = DeviceAllocations[const_cast<ScopArrayInfo *>(SAI)]; 1092 DevArray = createCallGetDevicePtr(DevArray); 1093 1094 Value *Offset = getArrayOffset(&Prog->array[i]); 1095 1096 if (Offset) { 1097 DevArray = Builder.CreatePointerCast( 1098 DevArray, SAI->getElementType()->getPointerTo()); 1099 DevArray = Builder.CreateGEP(DevArray, Builder.CreateNeg(Offset)); 1100 DevArray = Builder.CreatePointerCast(DevArray, Builder.getInt8PtrTy()); 1101 } 1102 Value *Slot = Builder.CreateGEP( 1103 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1104 1105 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1106 Value *ValPtr = BlockGen.getOrCreateAlloca(SAI); 1107 Value *ValPtrCast = 1108 Builder.CreatePointerCast(ValPtr, Builder.getInt8PtrTy()); 1109 Builder.CreateStore(ValPtrCast, Slot); 1110 } else { 1111 Instruction *Param = new AllocaInst( 1112 Builder.getInt8PtrTy(), Launch + "_param_" + std::to_string(Index), 1113 EntryBlock->getTerminator()); 1114 Builder.CreateStore(DevArray, Param); 1115 Value *ParamTyped = 1116 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1117 Builder.CreateStore(ParamTyped, Slot); 1118 } 1119 Index++; 1120 } 1121 1122 int NumHostIters = isl_space_dim(Kernel->space, isl_dim_set); 1123 1124 for (long i = 0; i < NumHostIters; i++) { 1125 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1126 Value *Val = IDToValue[Id]; 1127 isl_id_free(Id); 1128 Instruction *Param = new AllocaInst( 1129 Val->getType(), Launch + "_param_" + std::to_string(Index), 1130 EntryBlock->getTerminator()); 1131 Builder.CreateStore(Val, Param); 1132 Value *Slot = Builder.CreateGEP( 1133 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1134 Value *ParamTyped = 1135 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1136 Builder.CreateStore(ParamTyped, Slot); 1137 Index++; 1138 } 1139 1140 int NumVars = isl_space_dim(Kernel->space, isl_dim_param); 1141 1142 for (long i = 0; i < NumVars; i++) { 1143 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1144 Value *Val = IDToValue[Id]; 1145 isl_id_free(Id); 1146 Instruction *Param = new AllocaInst( 1147 Val->getType(), Launch + "_param_" + std::to_string(Index), 1148 EntryBlock->getTerminator()); 1149 Builder.CreateStore(Val, Param); 1150 Value *Slot = Builder.CreateGEP( 1151 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1152 Value *ParamTyped = 1153 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1154 Builder.CreateStore(ParamTyped, Slot); 1155 Index++; 1156 } 1157 1158 for (auto Val : SubtreeValues) { 1159 Instruction *Param = new AllocaInst( 1160 Val->getType(), Launch + "_param_" + std::to_string(Index), 1161 EntryBlock->getTerminator()); 1162 Builder.CreateStore(Val, Param); 1163 Value *Slot = Builder.CreateGEP( 1164 Parameters, {Builder.getInt64(0), Builder.getInt64(Index)}); 1165 Value *ParamTyped = 1166 Builder.CreatePointerCast(Param, Builder.getInt8PtrTy()); 1167 Builder.CreateStore(ParamTyped, Slot); 1168 Index++; 1169 } 1170 1171 auto Location = EntryBlock->getTerminator(); 1172 return new BitCastInst(Parameters, Builder.getInt8PtrTy(), 1173 Launch + "_params_i8ptr", Location); 1174 } 1175 1176 void GPUNodeBuilder::createKernel(__isl_take isl_ast_node *KernelStmt) { 1177 isl_id *Id = isl_ast_node_get_annotation(KernelStmt); 1178 ppcg_kernel *Kernel = (ppcg_kernel *)isl_id_get_user(Id); 1179 isl_id_free(Id); 1180 isl_ast_node_free(KernelStmt); 1181 1182 Value *BlockDimX, *BlockDimY, *BlockDimZ; 1183 std::tie(BlockDimX, BlockDimY, BlockDimZ) = getBlockSizes(Kernel); 1184 1185 SetVector<Value *> SubtreeValues = getReferencesInKernel(Kernel); 1186 1187 assert(Kernel->tree && "Device AST of kernel node is empty"); 1188 1189 Instruction &HostInsertPoint = *Builder.GetInsertPoint(); 1190 IslExprBuilder::IDToValueTy HostIDs = IDToValue; 1191 ValueMapT HostValueMap = ValueMap; 1192 BlockGenerator::ScalarAllocaMapTy HostScalarMap = ScalarMap; 1193 BlockGenerator::ScalarAllocaMapTy HostPHIOpMap = PHIOpMap; 1194 ScalarMap.clear(); 1195 PHIOpMap.clear(); 1196 1197 SetVector<const Loop *> Loops; 1198 1199 // Create for all loops we depend on values that contain the current loop 1200 // iteration. These values are necessary to generate code for SCEVs that 1201 // depend on such loops. As a result we need to pass them to the subfunction. 1202 for (const Loop *L : Loops) { 1203 const SCEV *OuterLIV = SE.getAddRecExpr(SE.getUnknown(Builder.getInt64(0)), 1204 SE.getUnknown(Builder.getInt64(1)), 1205 L, SCEV::FlagAnyWrap); 1206 Value *V = generateSCEV(OuterLIV); 1207 OutsideLoopIterations[L] = SE.getUnknown(V); 1208 SubtreeValues.insert(V); 1209 } 1210 1211 createKernelFunction(Kernel, SubtreeValues); 1212 1213 create(isl_ast_node_copy(Kernel->tree)); 1214 1215 finalizeKernelArguments(Kernel); 1216 Function *F = Builder.GetInsertBlock()->getParent(); 1217 addCUDAAnnotations(F->getParent(), BlockDimX, BlockDimY, BlockDimZ); 1218 clearDominators(F); 1219 clearScalarEvolution(F); 1220 clearLoops(F); 1221 1222 IDToValue = HostIDs; 1223 1224 ValueMap = std::move(HostValueMap); 1225 ScalarMap = std::move(HostScalarMap); 1226 PHIOpMap = std::move(HostPHIOpMap); 1227 EscapeMap.clear(); 1228 IDToSAI.clear(); 1229 Annotator.resetAlternativeAliasBases(); 1230 for (auto &BasePtr : LocalArrays) 1231 S.invalidateScopArrayInfo(BasePtr, ScopArrayInfo::MK_Array); 1232 LocalArrays.clear(); 1233 1234 std::string ASMString = finalizeKernelFunction(); 1235 Builder.SetInsertPoint(&HostInsertPoint); 1236 Value *Parameters = createLaunchParameters(Kernel, F, SubtreeValues); 1237 1238 std::string Name = "kernel_" + std::to_string(Kernel->id); 1239 Value *KernelString = Builder.CreateGlobalStringPtr(ASMString, Name); 1240 Value *NameString = Builder.CreateGlobalStringPtr(Name, Name + "_name"); 1241 Value *GPUKernel = createCallGetKernel(KernelString, NameString); 1242 1243 Value *GridDimX, *GridDimY; 1244 std::tie(GridDimX, GridDimY) = getGridSizes(Kernel); 1245 1246 createCallLaunchKernel(GPUKernel, GridDimX, GridDimY, BlockDimX, BlockDimY, 1247 BlockDimZ, Parameters); 1248 createCallFreeKernel(GPUKernel); 1249 1250 for (auto Id : KernelIds) 1251 isl_id_free(Id); 1252 1253 KernelIds.clear(); 1254 } 1255 1256 /// Compute the DataLayout string for the NVPTX backend. 1257 /// 1258 /// @param is64Bit Are we looking for a 64 bit architecture? 1259 static std::string computeNVPTXDataLayout(bool is64Bit) { 1260 std::string Ret = "e"; 1261 1262 if (!is64Bit) 1263 Ret += "-p:32:32"; 1264 1265 Ret += "-i64:64-v16:16-v32:32-n16:32:64"; 1266 1267 return Ret; 1268 } 1269 1270 Function * 1271 GPUNodeBuilder::createKernelFunctionDecl(ppcg_kernel *Kernel, 1272 SetVector<Value *> &SubtreeValues) { 1273 std::vector<Type *> Args; 1274 std::string Identifier = "kernel_" + std::to_string(Kernel->id); 1275 1276 for (long i = 0; i < Prog->n_array; i++) { 1277 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1278 continue; 1279 1280 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1281 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1282 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(Id); 1283 Args.push_back(SAI->getElementType()); 1284 } else { 1285 Args.push_back(Builder.getInt8PtrTy()); 1286 } 1287 } 1288 1289 int NumHostIters = isl_space_dim(Kernel->space, isl_dim_set); 1290 1291 for (long i = 0; i < NumHostIters; i++) 1292 Args.push_back(Builder.getInt64Ty()); 1293 1294 int NumVars = isl_space_dim(Kernel->space, isl_dim_param); 1295 1296 for (long i = 0; i < NumVars; i++) { 1297 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1298 Value *Val = IDToValue[Id]; 1299 isl_id_free(Id); 1300 Args.push_back(Val->getType()); 1301 } 1302 1303 for (auto *V : SubtreeValues) 1304 Args.push_back(V->getType()); 1305 1306 auto *FT = FunctionType::get(Builder.getVoidTy(), Args, false); 1307 auto *FN = Function::Create(FT, Function::ExternalLinkage, Identifier, 1308 GPUModule.get()); 1309 FN->setCallingConv(CallingConv::PTX_Kernel); 1310 1311 auto Arg = FN->arg_begin(); 1312 for (long i = 0; i < Kernel->n_array; i++) { 1313 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1314 continue; 1315 1316 Arg->setName(Kernel->array[i].array->name); 1317 1318 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1319 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1320 Type *EleTy = SAI->getElementType(); 1321 Value *Val = &*Arg; 1322 SmallVector<const SCEV *, 4> Sizes; 1323 isl_ast_build *Build = 1324 isl_ast_build_from_context(isl_set_copy(Prog->context)); 1325 Sizes.push_back(nullptr); 1326 for (long j = 1; j < Kernel->array[i].array->n_index; j++) { 1327 isl_ast_expr *DimSize = isl_ast_build_expr_from_pw_aff( 1328 Build, isl_pw_aff_copy(Kernel->array[i].array->bound[j])); 1329 auto V = ExprBuilder.create(DimSize); 1330 Sizes.push_back(SE.getSCEV(V)); 1331 } 1332 const ScopArrayInfo *SAIRep = 1333 S.getOrCreateScopArrayInfo(Val, EleTy, Sizes, ScopArrayInfo::MK_Array); 1334 LocalArrays.push_back(Val); 1335 1336 isl_ast_build_free(Build); 1337 KernelIds.push_back(Id); 1338 IDToSAI[Id] = SAIRep; 1339 Arg++; 1340 } 1341 1342 for (long i = 0; i < NumHostIters; i++) { 1343 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_set, i); 1344 Arg->setName(isl_id_get_name(Id)); 1345 IDToValue[Id] = &*Arg; 1346 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1347 Arg++; 1348 } 1349 1350 for (long i = 0; i < NumVars; i++) { 1351 isl_id *Id = isl_space_get_dim_id(Kernel->space, isl_dim_param, i); 1352 Arg->setName(isl_id_get_name(Id)); 1353 Value *Val = IDToValue[Id]; 1354 ValueMap[Val] = &*Arg; 1355 IDToValue[Id] = &*Arg; 1356 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1357 Arg++; 1358 } 1359 1360 for (auto *V : SubtreeValues) { 1361 Arg->setName(V->getName()); 1362 ValueMap[V] = &*Arg; 1363 Arg++; 1364 } 1365 1366 return FN; 1367 } 1368 1369 void GPUNodeBuilder::insertKernelIntrinsics(ppcg_kernel *Kernel) { 1370 Intrinsic::ID IntrinsicsBID[] = {Intrinsic::nvvm_read_ptx_sreg_ctaid_x, 1371 Intrinsic::nvvm_read_ptx_sreg_ctaid_y}; 1372 1373 Intrinsic::ID IntrinsicsTID[] = {Intrinsic::nvvm_read_ptx_sreg_tid_x, 1374 Intrinsic::nvvm_read_ptx_sreg_tid_y, 1375 Intrinsic::nvvm_read_ptx_sreg_tid_z}; 1376 1377 auto addId = [this](__isl_take isl_id *Id, Intrinsic::ID Intr) mutable { 1378 std::string Name = isl_id_get_name(Id); 1379 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 1380 Function *IntrinsicFn = Intrinsic::getDeclaration(M, Intr); 1381 Value *Val = Builder.CreateCall(IntrinsicFn, {}); 1382 Val = Builder.CreateIntCast(Val, Builder.getInt64Ty(), false, Name); 1383 IDToValue[Id] = Val; 1384 KernelIDs.insert(std::unique_ptr<isl_id, IslIdDeleter>(Id)); 1385 }; 1386 1387 for (int i = 0; i < Kernel->n_grid; ++i) { 1388 isl_id *Id = isl_id_list_get_id(Kernel->block_ids, i); 1389 addId(Id, IntrinsicsBID[i]); 1390 } 1391 1392 for (int i = 0; i < Kernel->n_block; ++i) { 1393 isl_id *Id = isl_id_list_get_id(Kernel->thread_ids, i); 1394 addId(Id, IntrinsicsTID[i]); 1395 } 1396 } 1397 1398 void GPUNodeBuilder::prepareKernelArguments(ppcg_kernel *Kernel, Function *FN) { 1399 auto Arg = FN->arg_begin(); 1400 for (long i = 0; i < Kernel->n_array; i++) { 1401 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1402 continue; 1403 1404 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1405 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1406 isl_id_free(Id); 1407 1408 if (SAI->getNumberOfDimensions() > 0) { 1409 Arg++; 1410 continue; 1411 } 1412 1413 Value *Val = &*Arg; 1414 1415 if (!gpu_array_is_read_only_scalar(&Prog->array[i])) { 1416 Type *TypePtr = SAI->getElementType()->getPointerTo(); 1417 Value *TypedArgPtr = Builder.CreatePointerCast(Val, TypePtr); 1418 Val = Builder.CreateLoad(TypedArgPtr); 1419 } 1420 1421 Value *Alloca = BlockGen.getOrCreateAlloca(SAI); 1422 Builder.CreateStore(Val, Alloca); 1423 1424 Arg++; 1425 } 1426 } 1427 1428 void GPUNodeBuilder::finalizeKernelArguments(ppcg_kernel *Kernel) { 1429 auto *FN = Builder.GetInsertBlock()->getParent(); 1430 auto Arg = FN->arg_begin(); 1431 1432 bool StoredScalar = false; 1433 for (long i = 0; i < Kernel->n_array; i++) { 1434 if (!ppcg_kernel_requires_array_argument(Kernel, i)) 1435 continue; 1436 1437 isl_id *Id = isl_space_get_tuple_id(Prog->array[i].space, isl_dim_set); 1438 const ScopArrayInfo *SAI = ScopArrayInfo::getFromId(isl_id_copy(Id)); 1439 isl_id_free(Id); 1440 1441 if (SAI->getNumberOfDimensions() > 0) { 1442 Arg++; 1443 continue; 1444 } 1445 1446 if (gpu_array_is_read_only_scalar(&Prog->array[i])) { 1447 Arg++; 1448 continue; 1449 } 1450 1451 Value *Alloca = BlockGen.getOrCreateAlloca(SAI); 1452 Value *ArgPtr = &*Arg; 1453 Type *TypePtr = SAI->getElementType()->getPointerTo(); 1454 Value *TypedArgPtr = Builder.CreatePointerCast(ArgPtr, TypePtr); 1455 Value *Val = Builder.CreateLoad(Alloca); 1456 Builder.CreateStore(Val, TypedArgPtr); 1457 StoredScalar = true; 1458 1459 Arg++; 1460 } 1461 1462 if (StoredScalar) 1463 /// In case more than one thread contains scalar stores, the generated 1464 /// code might be incorrect, if we only store at the end of the kernel. 1465 /// To support this case we need to store these scalars back at each 1466 /// memory store or at least before each kernel barrier. 1467 if (Kernel->n_block != 0 || Kernel->n_grid != 0) 1468 BuildSuccessful = 0; 1469 } 1470 1471 void GPUNodeBuilder::createKernelVariables(ppcg_kernel *Kernel, Function *FN) { 1472 Module *M = Builder.GetInsertBlock()->getParent()->getParent(); 1473 1474 for (int i = 0; i < Kernel->n_var; ++i) { 1475 struct ppcg_kernel_var &Var = Kernel->var[i]; 1476 isl_id *Id = isl_space_get_tuple_id(Var.array->space, isl_dim_set); 1477 Type *EleTy = ScopArrayInfo::getFromId(Id)->getElementType(); 1478 1479 Type *ArrayTy = EleTy; 1480 SmallVector<const SCEV *, 4> Sizes; 1481 1482 Sizes.push_back(nullptr); 1483 for (unsigned int j = 1; j < Var.array->n_index; ++j) { 1484 isl_val *Val = isl_vec_get_element_val(Var.size, j); 1485 long Bound = isl_val_get_num_si(Val); 1486 isl_val_free(Val); 1487 Sizes.push_back(S.getSE()->getConstant(Builder.getInt64Ty(), Bound)); 1488 } 1489 1490 for (int j = Var.array->n_index - 1; j >= 0; --j) { 1491 isl_val *Val = isl_vec_get_element_val(Var.size, j); 1492 long Bound = isl_val_get_num_si(Val); 1493 isl_val_free(Val); 1494 ArrayTy = ArrayType::get(ArrayTy, Bound); 1495 } 1496 1497 const ScopArrayInfo *SAI; 1498 Value *Allocation; 1499 if (Var.type == ppcg_access_shared) { 1500 auto GlobalVar = new GlobalVariable( 1501 *M, ArrayTy, false, GlobalValue::InternalLinkage, 0, Var.name, 1502 nullptr, GlobalValue::ThreadLocalMode::NotThreadLocal, 3); 1503 GlobalVar->setAlignment(EleTy->getPrimitiveSizeInBits() / 8); 1504 GlobalVar->setInitializer(Constant::getNullValue(ArrayTy)); 1505 1506 Allocation = GlobalVar; 1507 } else if (Var.type == ppcg_access_private) { 1508 Allocation = Builder.CreateAlloca(ArrayTy, 0, "private_array"); 1509 } else { 1510 llvm_unreachable("unknown variable type"); 1511 } 1512 SAI = S.getOrCreateScopArrayInfo(Allocation, EleTy, Sizes, 1513 ScopArrayInfo::MK_Array); 1514 Id = isl_id_alloc(S.getIslCtx(), Var.name, nullptr); 1515 IDToValue[Id] = Allocation; 1516 LocalArrays.push_back(Allocation); 1517 KernelIds.push_back(Id); 1518 IDToSAI[Id] = SAI; 1519 } 1520 } 1521 1522 void GPUNodeBuilder::createKernelFunction(ppcg_kernel *Kernel, 1523 SetVector<Value *> &SubtreeValues) { 1524 1525 std::string Identifier = "kernel_" + std::to_string(Kernel->id); 1526 GPUModule.reset(new Module(Identifier, Builder.getContext())); 1527 GPUModule->setTargetTriple(Triple::normalize("nvptx64-nvidia-cuda")); 1528 GPUModule->setDataLayout(computeNVPTXDataLayout(true /* is64Bit */)); 1529 1530 Function *FN = createKernelFunctionDecl(Kernel, SubtreeValues); 1531 1532 BasicBlock *PrevBlock = Builder.GetInsertBlock(); 1533 auto EntryBlock = BasicBlock::Create(Builder.getContext(), "entry", FN); 1534 1535 DominatorTree &DT = P->getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 1536 DT.addNewBlock(EntryBlock, PrevBlock); 1537 1538 Builder.SetInsertPoint(EntryBlock); 1539 Builder.CreateRetVoid(); 1540 Builder.SetInsertPoint(EntryBlock, EntryBlock->begin()); 1541 1542 ScopDetection::markFunctionAsInvalid(FN); 1543 1544 prepareKernelArguments(Kernel, FN); 1545 createKernelVariables(Kernel, FN); 1546 insertKernelIntrinsics(Kernel); 1547 } 1548 1549 std::string GPUNodeBuilder::createKernelASM() { 1550 llvm::Triple GPUTriple(Triple::normalize("nvptx64-nvidia-cuda")); 1551 std::string ErrMsg; 1552 auto GPUTarget = TargetRegistry::lookupTarget(GPUTriple.getTriple(), ErrMsg); 1553 1554 if (!GPUTarget) { 1555 errs() << ErrMsg << "\n"; 1556 return ""; 1557 } 1558 1559 TargetOptions Options; 1560 Options.UnsafeFPMath = FastMath; 1561 std::unique_ptr<TargetMachine> TargetM( 1562 GPUTarget->createTargetMachine(GPUTriple.getTriple(), CudaVersion, "", 1563 Options, Optional<Reloc::Model>())); 1564 1565 SmallString<0> ASMString; 1566 raw_svector_ostream ASMStream(ASMString); 1567 llvm::legacy::PassManager PM; 1568 1569 PM.add(createTargetTransformInfoWrapperPass(TargetM->getTargetIRAnalysis())); 1570 1571 if (TargetM->addPassesToEmitFile( 1572 PM, ASMStream, TargetMachine::CGFT_AssemblyFile, true /* verify */)) { 1573 errs() << "The target does not support generation of this file type!\n"; 1574 return ""; 1575 } 1576 1577 PM.run(*GPUModule); 1578 1579 return ASMStream.str(); 1580 } 1581 1582 std::string GPUNodeBuilder::finalizeKernelFunction() { 1583 if (verifyModule(*GPUModule)) { 1584 BuildSuccessful = false; 1585 return ""; 1586 } 1587 1588 if (DumpKernelIR) 1589 outs() << *GPUModule << "\n"; 1590 1591 // Optimize module. 1592 llvm::legacy::PassManager OptPasses; 1593 PassManagerBuilder PassBuilder; 1594 PassBuilder.OptLevel = 3; 1595 PassBuilder.SizeLevel = 0; 1596 PassBuilder.populateModulePassManager(OptPasses); 1597 OptPasses.run(*GPUModule); 1598 1599 std::string Assembly = createKernelASM(); 1600 1601 if (DumpKernelASM) 1602 outs() << Assembly << "\n"; 1603 1604 GPUModule.release(); 1605 KernelIDs.clear(); 1606 1607 return Assembly; 1608 } 1609 1610 namespace { 1611 class PPCGCodeGeneration : public ScopPass { 1612 public: 1613 static char ID; 1614 1615 /// The scop that is currently processed. 1616 Scop *S; 1617 1618 LoopInfo *LI; 1619 DominatorTree *DT; 1620 ScalarEvolution *SE; 1621 const DataLayout *DL; 1622 RegionInfo *RI; 1623 1624 PPCGCodeGeneration() : ScopPass(ID) {} 1625 1626 /// Construct compilation options for PPCG. 1627 /// 1628 /// @returns The compilation options. 1629 ppcg_options *createPPCGOptions() { 1630 auto DebugOptions = 1631 (ppcg_debug_options *)malloc(sizeof(ppcg_debug_options)); 1632 auto Options = (ppcg_options *)malloc(sizeof(ppcg_options)); 1633 1634 DebugOptions->dump_schedule_constraints = false; 1635 DebugOptions->dump_schedule = false; 1636 DebugOptions->dump_final_schedule = false; 1637 DebugOptions->dump_sizes = false; 1638 DebugOptions->verbose = false; 1639 1640 Options->debug = DebugOptions; 1641 1642 Options->reschedule = true; 1643 Options->scale_tile_loops = false; 1644 Options->wrap = false; 1645 1646 Options->non_negative_parameters = false; 1647 Options->ctx = nullptr; 1648 Options->sizes = nullptr; 1649 1650 Options->tile_size = 32; 1651 1652 Options->use_private_memory = PrivateMemory; 1653 Options->use_shared_memory = SharedMemory; 1654 Options->max_shared_memory = 48 * 1024; 1655 1656 Options->target = PPCG_TARGET_CUDA; 1657 Options->openmp = false; 1658 Options->linearize_device_arrays = true; 1659 Options->live_range_reordering = false; 1660 1661 Options->opencl_compiler_options = nullptr; 1662 Options->opencl_use_gpu = false; 1663 Options->opencl_n_include_file = 0; 1664 Options->opencl_include_files = nullptr; 1665 Options->opencl_print_kernel_types = false; 1666 Options->opencl_embed_kernel_code = false; 1667 1668 Options->save_schedule_file = nullptr; 1669 Options->load_schedule_file = nullptr; 1670 1671 return Options; 1672 } 1673 1674 /// Get a tagged access relation containing all accesses of type @p AccessTy. 1675 /// 1676 /// Instead of a normal access of the form: 1677 /// 1678 /// Stmt[i,j,k] -> Array[f_0(i,j,k), f_1(i,j,k)] 1679 /// 1680 /// a tagged access has the form 1681 /// 1682 /// [Stmt[i,j,k] -> id[]] -> Array[f_0(i,j,k), f_1(i,j,k)] 1683 /// 1684 /// where 'id' is an additional space that references the memory access that 1685 /// triggered the access. 1686 /// 1687 /// @param AccessTy The type of the memory accesses to collect. 1688 /// 1689 /// @return The relation describing all tagged memory accesses. 1690 isl_union_map *getTaggedAccesses(enum MemoryAccess::AccessType AccessTy) { 1691 isl_union_map *Accesses = isl_union_map_empty(S->getParamSpace()); 1692 1693 for (auto &Stmt : *S) 1694 for (auto &Acc : Stmt) 1695 if (Acc->getType() == AccessTy) { 1696 isl_map *Relation = Acc->getAccessRelation(); 1697 Relation = isl_map_intersect_domain(Relation, Stmt.getDomain()); 1698 1699 isl_space *Space = isl_map_get_space(Relation); 1700 Space = isl_space_range(Space); 1701 Space = isl_space_from_range(Space); 1702 Space = isl_space_set_tuple_id(Space, isl_dim_in, Acc->getId()); 1703 isl_map *Universe = isl_map_universe(Space); 1704 Relation = isl_map_domain_product(Relation, Universe); 1705 Accesses = isl_union_map_add_map(Accesses, Relation); 1706 } 1707 1708 return Accesses; 1709 } 1710 1711 /// Get the set of all read accesses, tagged with the access id. 1712 /// 1713 /// @see getTaggedAccesses 1714 isl_union_map *getTaggedReads() { 1715 return getTaggedAccesses(MemoryAccess::READ); 1716 } 1717 1718 /// Get the set of all may (and must) accesses, tagged with the access id. 1719 /// 1720 /// @see getTaggedAccesses 1721 isl_union_map *getTaggedMayWrites() { 1722 return isl_union_map_union(getTaggedAccesses(MemoryAccess::MAY_WRITE), 1723 getTaggedAccesses(MemoryAccess::MUST_WRITE)); 1724 } 1725 1726 /// Get the set of all must accesses, tagged with the access id. 1727 /// 1728 /// @see getTaggedAccesses 1729 isl_union_map *getTaggedMustWrites() { 1730 return getTaggedAccesses(MemoryAccess::MUST_WRITE); 1731 } 1732 1733 /// Collect parameter and array names as isl_ids. 1734 /// 1735 /// To reason about the different parameters and arrays used, ppcg requires 1736 /// a list of all isl_ids in use. As PPCG traditionally performs 1737 /// source-to-source compilation each of these isl_ids is mapped to the 1738 /// expression that represents it. As we do not have a corresponding 1739 /// expression in Polly, we just map each id to a 'zero' expression to match 1740 /// the data format that ppcg expects. 1741 /// 1742 /// @returns Retun a map from collected ids to 'zero' ast expressions. 1743 __isl_give isl_id_to_ast_expr *getNames() { 1744 auto *Names = isl_id_to_ast_expr_alloc( 1745 S->getIslCtx(), 1746 S->getNumParams() + std::distance(S->array_begin(), S->array_end())); 1747 auto *Zero = isl_ast_expr_from_val(isl_val_zero(S->getIslCtx())); 1748 auto *Space = S->getParamSpace(); 1749 1750 for (int I = 0, E = S->getNumParams(); I < E; ++I) { 1751 isl_id *Id = isl_space_get_dim_id(Space, isl_dim_param, I); 1752 Names = isl_id_to_ast_expr_set(Names, Id, isl_ast_expr_copy(Zero)); 1753 } 1754 1755 for (auto &Array : S->arrays()) { 1756 auto Id = Array->getBasePtrId(); 1757 Names = isl_id_to_ast_expr_set(Names, Id, isl_ast_expr_copy(Zero)); 1758 } 1759 1760 isl_space_free(Space); 1761 isl_ast_expr_free(Zero); 1762 1763 return Names; 1764 } 1765 1766 /// Create a new PPCG scop from the current scop. 1767 /// 1768 /// The PPCG scop is initialized with data from the current polly::Scop. From 1769 /// this initial data, the data-dependences in the PPCG scop are initialized. 1770 /// We do not use Polly's dependence analysis for now, to ensure we match 1771 /// the PPCG default behaviour more closely. 1772 /// 1773 /// @returns A new ppcg scop. 1774 ppcg_scop *createPPCGScop() { 1775 auto PPCGScop = (ppcg_scop *)malloc(sizeof(ppcg_scop)); 1776 1777 PPCGScop->options = createPPCGOptions(); 1778 1779 PPCGScop->start = 0; 1780 PPCGScop->end = 0; 1781 1782 PPCGScop->context = S->getContext(); 1783 PPCGScop->domain = S->getDomains(); 1784 PPCGScop->call = nullptr; 1785 PPCGScop->tagged_reads = getTaggedReads(); 1786 PPCGScop->reads = S->getReads(); 1787 PPCGScop->live_in = nullptr; 1788 PPCGScop->tagged_may_writes = getTaggedMayWrites(); 1789 PPCGScop->may_writes = S->getWrites(); 1790 PPCGScop->tagged_must_writes = getTaggedMustWrites(); 1791 PPCGScop->must_writes = S->getMustWrites(); 1792 PPCGScop->live_out = nullptr; 1793 PPCGScop->tagged_must_kills = isl_union_map_empty(S->getParamSpace()); 1794 PPCGScop->tagger = nullptr; 1795 1796 PPCGScop->independence = nullptr; 1797 PPCGScop->dep_flow = nullptr; 1798 PPCGScop->tagged_dep_flow = nullptr; 1799 PPCGScop->dep_false = nullptr; 1800 PPCGScop->dep_forced = nullptr; 1801 PPCGScop->dep_order = nullptr; 1802 PPCGScop->tagged_dep_order = nullptr; 1803 1804 PPCGScop->schedule = S->getScheduleTree(); 1805 PPCGScop->names = getNames(); 1806 1807 PPCGScop->pet = nullptr; 1808 1809 compute_tagger(PPCGScop); 1810 compute_dependences(PPCGScop); 1811 1812 return PPCGScop; 1813 } 1814 1815 /// Collect the array acesses in a statement. 1816 /// 1817 /// @param Stmt The statement for which to collect the accesses. 1818 /// 1819 /// @returns A list of array accesses. 1820 gpu_stmt_access *getStmtAccesses(ScopStmt &Stmt) { 1821 gpu_stmt_access *Accesses = nullptr; 1822 1823 for (MemoryAccess *Acc : Stmt) { 1824 auto Access = isl_alloc_type(S->getIslCtx(), struct gpu_stmt_access); 1825 Access->read = Acc->isRead(); 1826 Access->write = Acc->isWrite(); 1827 Access->access = Acc->getAccessRelation(); 1828 isl_space *Space = isl_map_get_space(Access->access); 1829 Space = isl_space_range(Space); 1830 Space = isl_space_from_range(Space); 1831 Space = isl_space_set_tuple_id(Space, isl_dim_in, Acc->getId()); 1832 isl_map *Universe = isl_map_universe(Space); 1833 Access->tagged_access = 1834 isl_map_domain_product(Acc->getAccessRelation(), Universe); 1835 Access->exact_write = !Acc->isMayWrite(); 1836 Access->ref_id = Acc->getId(); 1837 Access->next = Accesses; 1838 Access->n_index = Acc->getScopArrayInfo()->getNumberOfDimensions(); 1839 Accesses = Access; 1840 } 1841 1842 return Accesses; 1843 } 1844 1845 /// Collect the list of GPU statements. 1846 /// 1847 /// Each statement has an id, a pointer to the underlying data structure, 1848 /// as well as a list with all memory accesses. 1849 /// 1850 /// TODO: Initialize the list of memory accesses. 1851 /// 1852 /// @returns A linked-list of statements. 1853 gpu_stmt *getStatements() { 1854 gpu_stmt *Stmts = isl_calloc_array(S->getIslCtx(), struct gpu_stmt, 1855 std::distance(S->begin(), S->end())); 1856 1857 int i = 0; 1858 for (auto &Stmt : *S) { 1859 gpu_stmt *GPUStmt = &Stmts[i]; 1860 1861 GPUStmt->id = Stmt.getDomainId(); 1862 1863 // We use the pet stmt pointer to keep track of the Polly statements. 1864 GPUStmt->stmt = (pet_stmt *)&Stmt; 1865 GPUStmt->accesses = getStmtAccesses(Stmt); 1866 i++; 1867 } 1868 1869 return Stmts; 1870 } 1871 1872 /// Derive the extent of an array. 1873 /// 1874 /// The extent of an array is the set of elements that are within the 1875 /// accessed array. For the inner dimensions, the extent constraints are 1876 /// 0 and the size of the corresponding array dimension. For the first 1877 /// (outermost) dimension, the extent constraints are the minimal and maximal 1878 /// subscript value for the first dimension. 1879 /// 1880 /// @param Array The array to derive the extent for. 1881 /// 1882 /// @returns An isl_set describing the extent of the array. 1883 __isl_give isl_set *getExtent(ScopArrayInfo *Array) { 1884 unsigned NumDims = Array->getNumberOfDimensions(); 1885 isl_union_map *Accesses = S->getAccesses(); 1886 Accesses = isl_union_map_intersect_domain(Accesses, S->getDomains()); 1887 Accesses = isl_union_map_detect_equalities(Accesses); 1888 isl_union_set *AccessUSet = isl_union_map_range(Accesses); 1889 AccessUSet = isl_union_set_coalesce(AccessUSet); 1890 AccessUSet = isl_union_set_detect_equalities(AccessUSet); 1891 AccessUSet = isl_union_set_coalesce(AccessUSet); 1892 1893 if (isl_union_set_is_empty(AccessUSet)) { 1894 isl_union_set_free(AccessUSet); 1895 return isl_set_empty(Array->getSpace()); 1896 } 1897 1898 if (Array->getNumberOfDimensions() == 0) { 1899 isl_union_set_free(AccessUSet); 1900 return isl_set_universe(Array->getSpace()); 1901 } 1902 1903 isl_set *AccessSet = 1904 isl_union_set_extract_set(AccessUSet, Array->getSpace()); 1905 1906 isl_union_set_free(AccessUSet); 1907 isl_local_space *LS = isl_local_space_from_space(Array->getSpace()); 1908 1909 isl_pw_aff *Val = 1910 isl_pw_aff_from_aff(isl_aff_var_on_domain(LS, isl_dim_set, 0)); 1911 1912 isl_pw_aff *OuterMin = isl_set_dim_min(isl_set_copy(AccessSet), 0); 1913 isl_pw_aff *OuterMax = isl_set_dim_max(AccessSet, 0); 1914 OuterMin = isl_pw_aff_add_dims(OuterMin, isl_dim_in, 1915 isl_pw_aff_dim(Val, isl_dim_in)); 1916 OuterMax = isl_pw_aff_add_dims(OuterMax, isl_dim_in, 1917 isl_pw_aff_dim(Val, isl_dim_in)); 1918 OuterMin = 1919 isl_pw_aff_set_tuple_id(OuterMin, isl_dim_in, Array->getBasePtrId()); 1920 OuterMax = 1921 isl_pw_aff_set_tuple_id(OuterMax, isl_dim_in, Array->getBasePtrId()); 1922 1923 isl_set *Extent = isl_set_universe(Array->getSpace()); 1924 1925 Extent = isl_set_intersect( 1926 Extent, isl_pw_aff_le_set(OuterMin, isl_pw_aff_copy(Val))); 1927 Extent = isl_set_intersect(Extent, isl_pw_aff_ge_set(OuterMax, Val)); 1928 1929 for (unsigned i = 1; i < NumDims; ++i) 1930 Extent = isl_set_lower_bound_si(Extent, isl_dim_set, i, 0); 1931 1932 for (unsigned i = 1; i < NumDims; ++i) { 1933 isl_pw_aff *PwAff = 1934 const_cast<isl_pw_aff *>(Array->getDimensionSizePw(i)); 1935 isl_pw_aff *Val = isl_pw_aff_from_aff(isl_aff_var_on_domain( 1936 isl_local_space_from_space(Array->getSpace()), isl_dim_set, i)); 1937 PwAff = isl_pw_aff_add_dims(PwAff, isl_dim_in, 1938 isl_pw_aff_dim(Val, isl_dim_in)); 1939 PwAff = isl_pw_aff_set_tuple_id(PwAff, isl_dim_in, 1940 isl_pw_aff_get_tuple_id(Val, isl_dim_in)); 1941 auto *Set = isl_pw_aff_gt_set(PwAff, Val); 1942 Extent = isl_set_intersect(Set, Extent); 1943 } 1944 1945 return Extent; 1946 } 1947 1948 /// Derive the bounds of an array. 1949 /// 1950 /// For the first dimension we derive the bound of the array from the extent 1951 /// of this dimension. For inner dimensions we obtain their size directly from 1952 /// ScopArrayInfo. 1953 /// 1954 /// @param PPCGArray The array to compute bounds for. 1955 /// @param Array The polly array from which to take the information. 1956 void setArrayBounds(gpu_array_info &PPCGArray, ScopArrayInfo *Array) { 1957 if (PPCGArray.n_index > 0) { 1958 if (isl_set_is_empty(PPCGArray.extent)) { 1959 isl_set *Dom = isl_set_copy(PPCGArray.extent); 1960 isl_local_space *LS = isl_local_space_from_space( 1961 isl_space_params(isl_set_get_space(Dom))); 1962 isl_set_free(Dom); 1963 isl_aff *Zero = isl_aff_zero_on_domain(LS); 1964 PPCGArray.bound[0] = isl_pw_aff_from_aff(Zero); 1965 } else { 1966 isl_set *Dom = isl_set_copy(PPCGArray.extent); 1967 Dom = isl_set_project_out(Dom, isl_dim_set, 1, PPCGArray.n_index - 1); 1968 isl_pw_aff *Bound = isl_set_dim_max(isl_set_copy(Dom), 0); 1969 isl_set_free(Dom); 1970 Dom = isl_pw_aff_domain(isl_pw_aff_copy(Bound)); 1971 isl_local_space *LS = 1972 isl_local_space_from_space(isl_set_get_space(Dom)); 1973 isl_aff *One = isl_aff_zero_on_domain(LS); 1974 One = isl_aff_add_constant_si(One, 1); 1975 Bound = isl_pw_aff_add(Bound, isl_pw_aff_alloc(Dom, One)); 1976 Bound = isl_pw_aff_gist(Bound, S->getContext()); 1977 PPCGArray.bound[0] = Bound; 1978 } 1979 } 1980 1981 for (unsigned i = 1; i < PPCGArray.n_index; ++i) { 1982 isl_pw_aff *Bound = Array->getDimensionSizePw(i); 1983 auto LS = isl_pw_aff_get_domain_space(Bound); 1984 auto Aff = isl_multi_aff_zero(LS); 1985 Bound = isl_pw_aff_pullback_multi_aff(Bound, Aff); 1986 PPCGArray.bound[i] = Bound; 1987 } 1988 } 1989 1990 /// Create the arrays for @p PPCGProg. 1991 /// 1992 /// @param PPCGProg The program to compute the arrays for. 1993 void createArrays(gpu_prog *PPCGProg) { 1994 int i = 0; 1995 for (auto &Array : S->arrays()) { 1996 std::string TypeName; 1997 raw_string_ostream OS(TypeName); 1998 1999 OS << *Array->getElementType(); 2000 TypeName = OS.str(); 2001 2002 gpu_array_info &PPCGArray = PPCGProg->array[i]; 2003 2004 PPCGArray.space = Array->getSpace(); 2005 PPCGArray.type = strdup(TypeName.c_str()); 2006 PPCGArray.size = Array->getElementType()->getPrimitiveSizeInBits() / 8; 2007 PPCGArray.name = strdup(Array->getName().c_str()); 2008 PPCGArray.extent = nullptr; 2009 PPCGArray.n_index = Array->getNumberOfDimensions(); 2010 PPCGArray.bound = 2011 isl_alloc_array(S->getIslCtx(), isl_pw_aff *, PPCGArray.n_index); 2012 PPCGArray.extent = getExtent(Array); 2013 PPCGArray.n_ref = 0; 2014 PPCGArray.refs = nullptr; 2015 PPCGArray.accessed = true; 2016 PPCGArray.read_only_scalar = 2017 Array->isReadOnly() && Array->getNumberOfDimensions() == 0; 2018 PPCGArray.has_compound_element = false; 2019 PPCGArray.local = false; 2020 PPCGArray.declare_local = false; 2021 PPCGArray.global = false; 2022 PPCGArray.linearize = false; 2023 PPCGArray.dep_order = nullptr; 2024 PPCGArray.user = Array; 2025 2026 setArrayBounds(PPCGArray, Array); 2027 i++; 2028 2029 collect_references(PPCGProg, &PPCGArray); 2030 } 2031 } 2032 2033 /// Create an identity map between the arrays in the scop. 2034 /// 2035 /// @returns An identity map between the arrays in the scop. 2036 isl_union_map *getArrayIdentity() { 2037 isl_union_map *Maps = isl_union_map_empty(S->getParamSpace()); 2038 2039 for (auto &Array : S->arrays()) { 2040 isl_space *Space = Array->getSpace(); 2041 Space = isl_space_map_from_set(Space); 2042 isl_map *Identity = isl_map_identity(Space); 2043 Maps = isl_union_map_add_map(Maps, Identity); 2044 } 2045 2046 return Maps; 2047 } 2048 2049 /// Create a default-initialized PPCG GPU program. 2050 /// 2051 /// @returns A new gpu grogram description. 2052 gpu_prog *createPPCGProg(ppcg_scop *PPCGScop) { 2053 2054 if (!PPCGScop) 2055 return nullptr; 2056 2057 auto PPCGProg = isl_calloc_type(S->getIslCtx(), struct gpu_prog); 2058 2059 PPCGProg->ctx = S->getIslCtx(); 2060 PPCGProg->scop = PPCGScop; 2061 PPCGProg->context = isl_set_copy(PPCGScop->context); 2062 PPCGProg->read = isl_union_map_copy(PPCGScop->reads); 2063 PPCGProg->may_write = isl_union_map_copy(PPCGScop->may_writes); 2064 PPCGProg->must_write = isl_union_map_copy(PPCGScop->must_writes); 2065 PPCGProg->tagged_must_kill = 2066 isl_union_map_copy(PPCGScop->tagged_must_kills); 2067 PPCGProg->to_inner = getArrayIdentity(); 2068 PPCGProg->to_outer = getArrayIdentity(); 2069 PPCGProg->any_to_outer = nullptr; 2070 PPCGProg->array_order = nullptr; 2071 PPCGProg->n_stmts = std::distance(S->begin(), S->end()); 2072 PPCGProg->stmts = getStatements(); 2073 PPCGProg->n_array = std::distance(S->array_begin(), S->array_end()); 2074 PPCGProg->array = isl_calloc_array(S->getIslCtx(), struct gpu_array_info, 2075 PPCGProg->n_array); 2076 2077 createArrays(PPCGProg); 2078 2079 PPCGProg->may_persist = compute_may_persist(PPCGProg); 2080 2081 return PPCGProg; 2082 } 2083 2084 struct PrintGPUUserData { 2085 struct cuda_info *CudaInfo; 2086 struct gpu_prog *PPCGProg; 2087 std::vector<ppcg_kernel *> Kernels; 2088 }; 2089 2090 /// Print a user statement node in the host code. 2091 /// 2092 /// We use ppcg's printing facilities to print the actual statement and 2093 /// additionally build up a list of all kernels that are encountered in the 2094 /// host ast. 2095 /// 2096 /// @param P The printer to print to 2097 /// @param Options The printing options to use 2098 /// @param Node The node to print 2099 /// @param User A user pointer to carry additional data. This pointer is 2100 /// expected to be of type PrintGPUUserData. 2101 /// 2102 /// @returns A printer to which the output has been printed. 2103 static __isl_give isl_printer * 2104 printHostUser(__isl_take isl_printer *P, 2105 __isl_take isl_ast_print_options *Options, 2106 __isl_take isl_ast_node *Node, void *User) { 2107 auto Data = (struct PrintGPUUserData *)User; 2108 auto Id = isl_ast_node_get_annotation(Node); 2109 2110 if (Id) { 2111 bool IsUser = !strcmp(isl_id_get_name(Id), "user"); 2112 2113 // If this is a user statement, format it ourselves as ppcg would 2114 // otherwise try to call pet functionality that is not available in 2115 // Polly. 2116 if (IsUser) { 2117 P = isl_printer_start_line(P); 2118 P = isl_printer_print_ast_node(P, Node); 2119 P = isl_printer_end_line(P); 2120 isl_id_free(Id); 2121 isl_ast_print_options_free(Options); 2122 return P; 2123 } 2124 2125 auto Kernel = (struct ppcg_kernel *)isl_id_get_user(Id); 2126 isl_id_free(Id); 2127 Data->Kernels.push_back(Kernel); 2128 } 2129 2130 return print_host_user(P, Options, Node, User); 2131 } 2132 2133 /// Print C code corresponding to the control flow in @p Kernel. 2134 /// 2135 /// @param Kernel The kernel to print 2136 void printKernel(ppcg_kernel *Kernel) { 2137 auto *P = isl_printer_to_str(S->getIslCtx()); 2138 P = isl_printer_set_output_format(P, ISL_FORMAT_C); 2139 auto *Options = isl_ast_print_options_alloc(S->getIslCtx()); 2140 P = isl_ast_node_print(Kernel->tree, P, Options); 2141 char *String = isl_printer_get_str(P); 2142 printf("%s\n", String); 2143 free(String); 2144 isl_printer_free(P); 2145 } 2146 2147 /// Print C code corresponding to the GPU code described by @p Tree. 2148 /// 2149 /// @param Tree An AST describing GPU code 2150 /// @param PPCGProg The PPCG program from which @Tree has been constructed. 2151 void printGPUTree(isl_ast_node *Tree, gpu_prog *PPCGProg) { 2152 auto *P = isl_printer_to_str(S->getIslCtx()); 2153 P = isl_printer_set_output_format(P, ISL_FORMAT_C); 2154 2155 PrintGPUUserData Data; 2156 Data.PPCGProg = PPCGProg; 2157 2158 auto *Options = isl_ast_print_options_alloc(S->getIslCtx()); 2159 Options = 2160 isl_ast_print_options_set_print_user(Options, printHostUser, &Data); 2161 P = isl_ast_node_print(Tree, P, Options); 2162 char *String = isl_printer_get_str(P); 2163 printf("# host\n"); 2164 printf("%s\n", String); 2165 free(String); 2166 isl_printer_free(P); 2167 2168 for (auto Kernel : Data.Kernels) { 2169 printf("# kernel%d\n", Kernel->id); 2170 printKernel(Kernel); 2171 } 2172 } 2173 2174 // Generate a GPU program using PPCG. 2175 // 2176 // GPU mapping consists of multiple steps: 2177 // 2178 // 1) Compute new schedule for the program. 2179 // 2) Map schedule to GPU (TODO) 2180 // 3) Generate code for new schedule (TODO) 2181 // 2182 // We do not use here the Polly ScheduleOptimizer, as the schedule optimizer 2183 // is mostly CPU specific. Instead, we use PPCG's GPU code generation 2184 // strategy directly from this pass. 2185 gpu_gen *generateGPU(ppcg_scop *PPCGScop, gpu_prog *PPCGProg) { 2186 2187 auto PPCGGen = isl_calloc_type(S->getIslCtx(), struct gpu_gen); 2188 2189 PPCGGen->ctx = S->getIslCtx(); 2190 PPCGGen->options = PPCGScop->options; 2191 PPCGGen->print = nullptr; 2192 PPCGGen->print_user = nullptr; 2193 PPCGGen->build_ast_expr = &pollyBuildAstExprForStmt; 2194 PPCGGen->prog = PPCGProg; 2195 PPCGGen->tree = nullptr; 2196 PPCGGen->types.n = 0; 2197 PPCGGen->types.name = nullptr; 2198 PPCGGen->sizes = nullptr; 2199 PPCGGen->used_sizes = nullptr; 2200 PPCGGen->kernel_id = 0; 2201 2202 // Set scheduling strategy to same strategy PPCG is using. 2203 isl_options_set_schedule_outer_coincidence(PPCGGen->ctx, true); 2204 isl_options_set_schedule_maximize_band_depth(PPCGGen->ctx, true); 2205 isl_options_set_schedule_whole_component(PPCGGen->ctx, false); 2206 2207 isl_schedule *Schedule = get_schedule(PPCGGen); 2208 2209 int has_permutable = has_any_permutable_node(Schedule); 2210 2211 if (!has_permutable || has_permutable < 0) { 2212 Schedule = isl_schedule_free(Schedule); 2213 } else { 2214 Schedule = map_to_device(PPCGGen, Schedule); 2215 PPCGGen->tree = generate_code(PPCGGen, isl_schedule_copy(Schedule)); 2216 } 2217 2218 if (DumpSchedule) { 2219 isl_printer *P = isl_printer_to_str(S->getIslCtx()); 2220 P = isl_printer_set_yaml_style(P, ISL_YAML_STYLE_BLOCK); 2221 P = isl_printer_print_str(P, "Schedule\n"); 2222 P = isl_printer_print_str(P, "========\n"); 2223 if (Schedule) 2224 P = isl_printer_print_schedule(P, Schedule); 2225 else 2226 P = isl_printer_print_str(P, "No schedule found\n"); 2227 2228 printf("%s\n", isl_printer_get_str(P)); 2229 isl_printer_free(P); 2230 } 2231 2232 if (DumpCode) { 2233 printf("Code\n"); 2234 printf("====\n"); 2235 if (PPCGGen->tree) 2236 printGPUTree(PPCGGen->tree, PPCGProg); 2237 else 2238 printf("No code generated\n"); 2239 } 2240 2241 isl_schedule_free(Schedule); 2242 2243 return PPCGGen; 2244 } 2245 2246 /// Free gpu_gen structure. 2247 /// 2248 /// @param PPCGGen The ppcg_gen object to free. 2249 void freePPCGGen(gpu_gen *PPCGGen) { 2250 isl_ast_node_free(PPCGGen->tree); 2251 isl_union_map_free(PPCGGen->sizes); 2252 isl_union_map_free(PPCGGen->used_sizes); 2253 free(PPCGGen); 2254 } 2255 2256 /// Free the options in the ppcg scop structure. 2257 /// 2258 /// ppcg is not freeing these options for us. To avoid leaks we do this 2259 /// ourselves. 2260 /// 2261 /// @param PPCGScop The scop referencing the options to free. 2262 void freeOptions(ppcg_scop *PPCGScop) { 2263 free(PPCGScop->options->debug); 2264 PPCGScop->options->debug = nullptr; 2265 free(PPCGScop->options); 2266 PPCGScop->options = nullptr; 2267 } 2268 2269 /// Approximate the number of points in the set. 2270 /// 2271 /// This function returns an ast expression that overapproximates the number 2272 /// of points in an isl set through the rectangular hull surrounding this set. 2273 /// 2274 /// @param Set The set to count. 2275 /// @param Build The isl ast build object to use for creating the ast 2276 /// expression. 2277 /// 2278 /// @returns An approximation of the number of points in the set. 2279 __isl_give isl_ast_expr *approxPointsInSet(__isl_take isl_set *Set, 2280 __isl_keep isl_ast_build *Build) { 2281 2282 isl_val *One = isl_val_int_from_si(isl_set_get_ctx(Set), 1); 2283 auto *Expr = isl_ast_expr_from_val(isl_val_copy(One)); 2284 2285 isl_space *Space = isl_set_get_space(Set); 2286 Space = isl_space_params(Space); 2287 auto *Univ = isl_set_universe(Space); 2288 isl_pw_aff *OneAff = isl_pw_aff_val_on_domain(Univ, One); 2289 2290 for (long i = 0; i < isl_set_dim(Set, isl_dim_set); i++) { 2291 isl_pw_aff *Max = isl_set_dim_max(isl_set_copy(Set), i); 2292 isl_pw_aff *Min = isl_set_dim_min(isl_set_copy(Set), i); 2293 isl_pw_aff *DimSize = isl_pw_aff_sub(Max, Min); 2294 DimSize = isl_pw_aff_add(DimSize, isl_pw_aff_copy(OneAff)); 2295 auto DimSizeExpr = isl_ast_build_expr_from_pw_aff(Build, DimSize); 2296 Expr = isl_ast_expr_mul(Expr, DimSizeExpr); 2297 } 2298 2299 isl_set_free(Set); 2300 isl_pw_aff_free(OneAff); 2301 2302 return Expr; 2303 } 2304 2305 /// Approximate a number of dynamic instructions executed by a given 2306 /// statement. 2307 /// 2308 /// @param Stmt The statement for which to compute the number of dynamic 2309 /// instructions. 2310 /// @param Build The isl ast build object to use for creating the ast 2311 /// expression. 2312 /// @returns An approximation of the number of dynamic instructions executed 2313 /// by @p Stmt. 2314 __isl_give isl_ast_expr *approxDynamicInst(ScopStmt &Stmt, 2315 __isl_keep isl_ast_build *Build) { 2316 auto Iterations = approxPointsInSet(Stmt.getDomain(), Build); 2317 2318 long InstCount = 0; 2319 2320 if (Stmt.isBlockStmt()) { 2321 auto *BB = Stmt.getBasicBlock(); 2322 InstCount = std::distance(BB->begin(), BB->end()); 2323 } else { 2324 auto *R = Stmt.getRegion(); 2325 2326 for (auto *BB : R->blocks()) { 2327 InstCount += std::distance(BB->begin(), BB->end()); 2328 } 2329 } 2330 2331 isl_val *InstVal = isl_val_int_from_si(S->getIslCtx(), InstCount); 2332 auto *InstExpr = isl_ast_expr_from_val(InstVal); 2333 return isl_ast_expr_mul(InstExpr, Iterations); 2334 } 2335 2336 /// Approximate dynamic instructions executed in scop. 2337 /// 2338 /// @param S The scop for which to approximate dynamic instructions. 2339 /// @param Build The isl ast build object to use for creating the ast 2340 /// expression. 2341 /// @returns An approximation of the number of dynamic instructions executed 2342 /// in @p S. 2343 __isl_give isl_ast_expr * 2344 getNumberOfIterations(Scop &S, __isl_keep isl_ast_build *Build) { 2345 isl_ast_expr *Instructions; 2346 2347 isl_val *Zero = isl_val_int_from_si(S.getIslCtx(), 0); 2348 Instructions = isl_ast_expr_from_val(Zero); 2349 2350 for (ScopStmt &Stmt : S) { 2351 isl_ast_expr *StmtInstructions = approxDynamicInst(Stmt, Build); 2352 Instructions = isl_ast_expr_add(Instructions, StmtInstructions); 2353 } 2354 return Instructions; 2355 } 2356 2357 /// Create a check that ensures sufficient compute in scop. 2358 /// 2359 /// @param S The scop for which to ensure sufficient compute. 2360 /// @param Build The isl ast build object to use for creating the ast 2361 /// expression. 2362 /// @returns An expression that evaluates to TRUE in case of sufficient 2363 /// compute and to FALSE, otherwise. 2364 __isl_give isl_ast_expr * 2365 createSufficientComputeCheck(Scop &S, __isl_keep isl_ast_build *Build) { 2366 auto Iterations = getNumberOfIterations(S, Build); 2367 auto *MinComputeVal = isl_val_int_from_si(S.getIslCtx(), MinCompute); 2368 auto *MinComputeExpr = isl_ast_expr_from_val(MinComputeVal); 2369 return isl_ast_expr_ge(Iterations, MinComputeExpr); 2370 } 2371 2372 /// Generate code for a given GPU AST described by @p Root. 2373 /// 2374 /// @param Root An isl_ast_node pointing to the root of the GPU AST. 2375 /// @param Prog The GPU Program to generate code for. 2376 void generateCode(__isl_take isl_ast_node *Root, gpu_prog *Prog) { 2377 ScopAnnotator Annotator; 2378 Annotator.buildAliasScopes(*S); 2379 2380 Region *R = &S->getRegion(); 2381 2382 simplifyRegion(R, DT, LI, RI); 2383 2384 BasicBlock *EnteringBB = R->getEnteringBlock(); 2385 2386 PollyIRBuilder Builder = createPollyIRBuilder(EnteringBB, Annotator); 2387 2388 GPUNodeBuilder NodeBuilder(Builder, Annotator, this, *DL, *LI, *SE, *DT, *S, 2389 Prog); 2390 2391 // Only build the run-time condition and parameters _after_ having 2392 // introduced the conditional branch. This is important as the conditional 2393 // branch will guard the original scop from new induction variables that 2394 // the SCEVExpander may introduce while code generating the parameters and 2395 // which may introduce scalar dependences that prevent us from correctly 2396 // code generating this scop. 2397 BasicBlock *StartBlock = 2398 executeScopConditionally(*S, this, Builder.getTrue()); 2399 2400 // TODO: Handle LICM 2401 auto SplitBlock = StartBlock->getSinglePredecessor(); 2402 Builder.SetInsertPoint(SplitBlock->getTerminator()); 2403 NodeBuilder.addParameters(S->getContext()); 2404 2405 isl_ast_build *Build = isl_ast_build_alloc(S->getIslCtx()); 2406 isl_ast_expr *Condition = IslAst::buildRunCondition(S, Build); 2407 isl_ast_expr *SufficientCompute = createSufficientComputeCheck(*S, Build); 2408 Condition = isl_ast_expr_and(Condition, SufficientCompute); 2409 isl_ast_build_free(Build); 2410 2411 Value *RTC = NodeBuilder.createRTC(Condition); 2412 Builder.GetInsertBlock()->getTerminator()->setOperand(0, RTC); 2413 2414 Builder.SetInsertPoint(&*StartBlock->begin()); 2415 2416 NodeBuilder.initializeAfterRTH(); 2417 NodeBuilder.create(Root); 2418 NodeBuilder.finalize(); 2419 2420 if (!NodeBuilder.BuildSuccessful) 2421 SplitBlock->getTerminator()->setOperand(0, Builder.getFalse()); 2422 } 2423 2424 bool runOnScop(Scop &CurrentScop) override { 2425 S = &CurrentScop; 2426 LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo(); 2427 DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree(); 2428 SE = &getAnalysis<ScalarEvolutionWrapperPass>().getSE(); 2429 DL = &S->getRegion().getEntry()->getParent()->getParent()->getDataLayout(); 2430 RI = &getAnalysis<RegionInfoPass>().getRegionInfo(); 2431 2432 // We currently do not support scops with invariant loads. 2433 if (S->hasInvariantAccesses()) 2434 return false; 2435 2436 auto PPCGScop = createPPCGScop(); 2437 auto PPCGProg = createPPCGProg(PPCGScop); 2438 auto PPCGGen = generateGPU(PPCGScop, PPCGProg); 2439 2440 if (PPCGGen->tree) 2441 generateCode(isl_ast_node_copy(PPCGGen->tree), PPCGProg); 2442 2443 freeOptions(PPCGScop); 2444 freePPCGGen(PPCGGen); 2445 gpu_prog_free(PPCGProg); 2446 ppcg_scop_free(PPCGScop); 2447 2448 return true; 2449 } 2450 2451 void printScop(raw_ostream &, Scop &) const override {} 2452 2453 void getAnalysisUsage(AnalysisUsage &AU) const override { 2454 AU.addRequired<DominatorTreeWrapperPass>(); 2455 AU.addRequired<RegionInfoPass>(); 2456 AU.addRequired<ScalarEvolutionWrapperPass>(); 2457 AU.addRequired<ScopDetection>(); 2458 AU.addRequired<ScopInfoRegionPass>(); 2459 AU.addRequired<LoopInfoWrapperPass>(); 2460 2461 AU.addPreserved<AAResultsWrapperPass>(); 2462 AU.addPreserved<BasicAAWrapperPass>(); 2463 AU.addPreserved<LoopInfoWrapperPass>(); 2464 AU.addPreserved<DominatorTreeWrapperPass>(); 2465 AU.addPreserved<GlobalsAAWrapperPass>(); 2466 AU.addPreserved<PostDominatorTreeWrapperPass>(); 2467 AU.addPreserved<ScopDetection>(); 2468 AU.addPreserved<ScalarEvolutionWrapperPass>(); 2469 AU.addPreserved<SCEVAAWrapperPass>(); 2470 2471 // FIXME: We do not yet add regions for the newly generated code to the 2472 // region tree. 2473 AU.addPreserved<RegionInfoPass>(); 2474 AU.addPreserved<ScopInfoRegionPass>(); 2475 } 2476 }; 2477 } 2478 2479 char PPCGCodeGeneration::ID = 1; 2480 2481 Pass *polly::createPPCGCodeGenerationPass() { return new PPCGCodeGeneration(); } 2482 2483 INITIALIZE_PASS_BEGIN(PPCGCodeGeneration, "polly-codegen-ppcg", 2484 "Polly - Apply PPCG translation to SCOP", false, false) 2485 INITIALIZE_PASS_DEPENDENCY(DependenceInfo); 2486 INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass); 2487 INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass); 2488 INITIALIZE_PASS_DEPENDENCY(RegionInfoPass); 2489 INITIALIZE_PASS_DEPENDENCY(ScalarEvolutionWrapperPass); 2490 INITIALIZE_PASS_DEPENDENCY(ScopDetection); 2491 INITIALIZE_PASS_END(PPCGCodeGeneration, "polly-codegen-ppcg", 2492 "Polly - Apply PPCG translation to SCOP", false, false) 2493