Neil Henning | 6641657 | 2018-10-08 15:49:19 +0000 | [diff] [blame] | 1 | //===-- AMDGPUAtomicOptimizer.cpp -----------------------------------------===// |
| 2 | // |
Chandler Carruth | 2946cd7 | 2019-01-19 08:50:56 +0000 | [diff] [blame] | 3 | // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. |
| 4 | // See https://llvm.org/LICENSE.txt for license information. |
| 5 | // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception |
Neil Henning | 6641657 | 2018-10-08 15:49:19 +0000 | [diff] [blame] | 6 | // |
| 7 | //===----------------------------------------------------------------------===// |
| 8 | // |
| 9 | /// \file |
| 10 | /// This pass optimizes atomic operations by using a single lane of a wavefront |
| 11 | /// to perform the atomic operation, thus reducing contention on that memory |
| 12 | /// location. |
| 13 | // |
| 14 | //===----------------------------------------------------------------------===// |
| 15 | |
| 16 | #include "AMDGPU.h" |
| 17 | #include "AMDGPUSubtarget.h" |
| 18 | #include "llvm/Analysis/LegacyDivergenceAnalysis.h" |
| 19 | #include "llvm/CodeGen/TargetPassConfig.h" |
| 20 | #include "llvm/IR/IRBuilder.h" |
| 21 | #include "llvm/IR/InstVisitor.h" |
| 22 | #include "llvm/Transforms/Utils/BasicBlockUtils.h" |
| 23 | |
| 24 | #define DEBUG_TYPE "amdgpu-atomic-optimizer" |
| 25 | |
| 26 | using namespace llvm; |
| 27 | |
| 28 | namespace { |
| 29 | |
| 30 | enum DPP_CTRL { |
| 31 | DPP_ROW_SR1 = 0x111, |
| 32 | DPP_ROW_SR2 = 0x112, |
| 33 | DPP_ROW_SR4 = 0x114, |
| 34 | DPP_ROW_SR8 = 0x118, |
| 35 | DPP_WF_SR1 = 0x138, |
| 36 | DPP_ROW_BCAST15 = 0x142, |
| 37 | DPP_ROW_BCAST31 = 0x143 |
| 38 | }; |
| 39 | |
| 40 | struct ReplacementInfo { |
| 41 | Instruction *I; |
| 42 | Instruction::BinaryOps Op; |
| 43 | unsigned ValIdx; |
| 44 | bool ValDivergent; |
| 45 | }; |
| 46 | |
| 47 | class AMDGPUAtomicOptimizer : public FunctionPass, |
| 48 | public InstVisitor<AMDGPUAtomicOptimizer> { |
| 49 | private: |
| 50 | SmallVector<ReplacementInfo, 8> ToReplace; |
| 51 | const LegacyDivergenceAnalysis *DA; |
| 52 | const DataLayout *DL; |
| 53 | DominatorTree *DT; |
| 54 | bool HasDPP; |
Neil Henning | 233a02d | 2018-11-05 12:04:48 +0000 | [diff] [blame] | 55 | bool IsPixelShader; |
Neil Henning | 6641657 | 2018-10-08 15:49:19 +0000 | [diff] [blame] | 56 | |
| 57 | void optimizeAtomic(Instruction &I, Instruction::BinaryOps Op, |
| 58 | unsigned ValIdx, bool ValDivergent) const; |
| 59 | |
| 60 | void setConvergent(CallInst *const CI) const; |
| 61 | |
| 62 | public: |
| 63 | static char ID; |
| 64 | |
| 65 | AMDGPUAtomicOptimizer() : FunctionPass(ID) {} |
| 66 | |
| 67 | bool runOnFunction(Function &F) override; |
| 68 | |
| 69 | void getAnalysisUsage(AnalysisUsage &AU) const override { |
| 70 | AU.addPreserved<DominatorTreeWrapperPass>(); |
| 71 | AU.addRequired<LegacyDivergenceAnalysis>(); |
| 72 | AU.addRequired<TargetPassConfig>(); |
| 73 | } |
| 74 | |
| 75 | void visitAtomicRMWInst(AtomicRMWInst &I); |
| 76 | void visitIntrinsicInst(IntrinsicInst &I); |
| 77 | }; |
| 78 | |
| 79 | } // namespace |
| 80 | |
| 81 | char AMDGPUAtomicOptimizer::ID = 0; |
| 82 | |
| 83 | char &llvm::AMDGPUAtomicOptimizerID = AMDGPUAtomicOptimizer::ID; |
| 84 | |
| 85 | bool AMDGPUAtomicOptimizer::runOnFunction(Function &F) { |
| 86 | if (skipFunction(F)) { |
| 87 | return false; |
| 88 | } |
| 89 | |
| 90 | DA = &getAnalysis<LegacyDivergenceAnalysis>(); |
| 91 | DL = &F.getParent()->getDataLayout(); |
| 92 | DominatorTreeWrapperPass *const DTW = |
| 93 | getAnalysisIfAvailable<DominatorTreeWrapperPass>(); |
| 94 | DT = DTW ? &DTW->getDomTree() : nullptr; |
| 95 | const TargetPassConfig &TPC = getAnalysis<TargetPassConfig>(); |
| 96 | const TargetMachine &TM = TPC.getTM<TargetMachine>(); |
| 97 | const GCNSubtarget &ST = TM.getSubtarget<GCNSubtarget>(F); |
| 98 | HasDPP = ST.hasDPP(); |
Neil Henning | 233a02d | 2018-11-05 12:04:48 +0000 | [diff] [blame] | 99 | IsPixelShader = F.getCallingConv() == CallingConv::AMDGPU_PS; |
Neil Henning | 6641657 | 2018-10-08 15:49:19 +0000 | [diff] [blame] | 100 | |
| 101 | visit(F); |
| 102 | |
| 103 | const bool Changed = !ToReplace.empty(); |
| 104 | |
| 105 | for (ReplacementInfo &Info : ToReplace) { |
| 106 | optimizeAtomic(*Info.I, Info.Op, Info.ValIdx, Info.ValDivergent); |
| 107 | } |
| 108 | |
| 109 | ToReplace.clear(); |
| 110 | |
| 111 | return Changed; |
| 112 | } |
| 113 | |
| 114 | void AMDGPUAtomicOptimizer::visitAtomicRMWInst(AtomicRMWInst &I) { |
| 115 | // Early exit for unhandled address space atomic instructions. |
| 116 | switch (I.getPointerAddressSpace()) { |
| 117 | default: |
| 118 | return; |
| 119 | case AMDGPUAS::GLOBAL_ADDRESS: |
| 120 | case AMDGPUAS::LOCAL_ADDRESS: |
| 121 | break; |
| 122 | } |
| 123 | |
| 124 | Instruction::BinaryOps Op; |
| 125 | |
| 126 | switch (I.getOperation()) { |
| 127 | default: |
| 128 | return; |
| 129 | case AtomicRMWInst::Add: |
| 130 | Op = Instruction::Add; |
| 131 | break; |
| 132 | case AtomicRMWInst::Sub: |
| 133 | Op = Instruction::Sub; |
| 134 | break; |
| 135 | } |
| 136 | |
| 137 | const unsigned PtrIdx = 0; |
| 138 | const unsigned ValIdx = 1; |
| 139 | |
| 140 | // If the pointer operand is divergent, then each lane is doing an atomic |
| 141 | // operation on a different address, and we cannot optimize that. |
| 142 | if (DA->isDivergent(I.getOperand(PtrIdx))) { |
| 143 | return; |
| 144 | } |
| 145 | |
| 146 | const bool ValDivergent = DA->isDivergent(I.getOperand(ValIdx)); |
| 147 | |
| 148 | // If the value operand is divergent, each lane is contributing a different |
| 149 | // value to the atomic calculation. We can only optimize divergent values if |
| 150 | // we have DPP available on our subtarget, and the atomic operation is 32 |
| 151 | // bits. |
| 152 | if (ValDivergent && (!HasDPP || (DL->getTypeSizeInBits(I.getType()) != 32))) { |
| 153 | return; |
| 154 | } |
| 155 | |
| 156 | // If we get here, we can optimize the atomic using a single wavefront-wide |
| 157 | // atomic operation to do the calculation for the entire wavefront, so |
| 158 | // remember the instruction so we can come back to it. |
| 159 | const ReplacementInfo Info = {&I, Op, ValIdx, ValDivergent}; |
| 160 | |
| 161 | ToReplace.push_back(Info); |
| 162 | } |
| 163 | |
| 164 | void AMDGPUAtomicOptimizer::visitIntrinsicInst(IntrinsicInst &I) { |
| 165 | Instruction::BinaryOps Op; |
| 166 | |
| 167 | switch (I.getIntrinsicID()) { |
| 168 | default: |
| 169 | return; |
| 170 | case Intrinsic::amdgcn_buffer_atomic_add: |
| 171 | case Intrinsic::amdgcn_struct_buffer_atomic_add: |
| 172 | case Intrinsic::amdgcn_raw_buffer_atomic_add: |
| 173 | Op = Instruction::Add; |
| 174 | break; |
| 175 | case Intrinsic::amdgcn_buffer_atomic_sub: |
| 176 | case Intrinsic::amdgcn_struct_buffer_atomic_sub: |
| 177 | case Intrinsic::amdgcn_raw_buffer_atomic_sub: |
| 178 | Op = Instruction::Sub; |
| 179 | break; |
| 180 | } |
| 181 | |
| 182 | const unsigned ValIdx = 0; |
| 183 | |
| 184 | const bool ValDivergent = DA->isDivergent(I.getOperand(ValIdx)); |
| 185 | |
| 186 | // If the value operand is divergent, each lane is contributing a different |
| 187 | // value to the atomic calculation. We can only optimize divergent values if |
| 188 | // we have DPP available on our subtarget, and the atomic operation is 32 |
| 189 | // bits. |
| 190 | if (ValDivergent && (!HasDPP || (DL->getTypeSizeInBits(I.getType()) != 32))) { |
| 191 | return; |
| 192 | } |
| 193 | |
| 194 | // If any of the other arguments to the intrinsic are divergent, we can't |
| 195 | // optimize the operation. |
| 196 | for (unsigned Idx = 1; Idx < I.getNumOperands(); Idx++) { |
| 197 | if (DA->isDivergent(I.getOperand(Idx))) { |
| 198 | return; |
| 199 | } |
| 200 | } |
| 201 | |
| 202 | // If we get here, we can optimize the atomic using a single wavefront-wide |
| 203 | // atomic operation to do the calculation for the entire wavefront, so |
| 204 | // remember the instruction so we can come back to it. |
| 205 | const ReplacementInfo Info = {&I, Op, ValIdx, ValDivergent}; |
| 206 | |
| 207 | ToReplace.push_back(Info); |
| 208 | } |
| 209 | |
| 210 | void AMDGPUAtomicOptimizer::optimizeAtomic(Instruction &I, |
| 211 | Instruction::BinaryOps Op, |
| 212 | unsigned ValIdx, |
| 213 | bool ValDivergent) const { |
| 214 | LLVMContext &Context = I.getContext(); |
| 215 | |
| 216 | // Start building just before the instruction. |
| 217 | IRBuilder<> B(&I); |
| 218 | |
Neil Henning | 233a02d | 2018-11-05 12:04:48 +0000 | [diff] [blame] | 219 | // If we are in a pixel shader, because of how we have to mask out helper |
| 220 | // lane invocations, we need to record the entry and exit BB's. |
| 221 | BasicBlock *PixelEntryBB = nullptr; |
| 222 | BasicBlock *PixelExitBB = nullptr; |
| 223 | |
| 224 | // If we're optimizing an atomic within a pixel shader, we need to wrap the |
| 225 | // entire atomic operation in a helper-lane check. We do not want any helper |
| 226 | // lanes that are around only for the purposes of derivatives to take part |
| 227 | // in any cross-lane communication, and we use a branch on whether the lane is |
| 228 | // live to do this. |
| 229 | if (IsPixelShader) { |
| 230 | // Record I's original position as the entry block. |
| 231 | PixelEntryBB = I.getParent(); |
| 232 | |
| 233 | Value *const Cond = B.CreateIntrinsic(Intrinsic::amdgcn_ps_live, {}, {}); |
| 234 | Instruction *const NonHelperTerminator = |
| 235 | SplitBlockAndInsertIfThen(Cond, &I, false, nullptr, DT, nullptr); |
| 236 | |
| 237 | // Record I's new position as the exit block. |
| 238 | PixelExitBB = I.getParent(); |
| 239 | |
| 240 | I.moveBefore(NonHelperTerminator); |
| 241 | B.SetInsertPoint(&I); |
| 242 | } |
| 243 | |
Neil Henning | 6641657 | 2018-10-08 15:49:19 +0000 | [diff] [blame] | 244 | Type *const Ty = I.getType(); |
| 245 | const unsigned TyBitWidth = DL->getTypeSizeInBits(Ty); |
| 246 | Type *const VecTy = VectorType::get(B.getInt32Ty(), 2); |
| 247 | |
| 248 | // This is the value in the atomic operation we need to combine in order to |
| 249 | // reduce the number of atomic operations. |
| 250 | Value *const V = I.getOperand(ValIdx); |
| 251 | |
| 252 | // We need to know how many lanes are active within the wavefront, and we do |
| 253 | // this by getting the exec register, which tells us all the lanes that are |
| 254 | // active. |
| 255 | MDNode *const RegName = |
| 256 | llvm::MDNode::get(Context, llvm::MDString::get(Context, "exec")); |
| 257 | Value *const Metadata = llvm::MetadataAsValue::get(Context, RegName); |
| 258 | CallInst *const Exec = |
| 259 | B.CreateIntrinsic(Intrinsic::read_register, {B.getInt64Ty()}, {Metadata}); |
| 260 | setConvergent(Exec); |
| 261 | |
| 262 | // We need to know how many lanes are active within the wavefront that are |
| 263 | // below us. If we counted each lane linearly starting from 0, a lane is |
| 264 | // below us only if its associated index was less than ours. We do this by |
| 265 | // using the mbcnt intrinsic. |
| 266 | Value *const BitCast = B.CreateBitCast(Exec, VecTy); |
| 267 | Value *const ExtractLo = B.CreateExtractElement(BitCast, B.getInt32(0)); |
| 268 | Value *const ExtractHi = B.CreateExtractElement(BitCast, B.getInt32(1)); |
| 269 | CallInst *const PartialMbcnt = B.CreateIntrinsic( |
| 270 | Intrinsic::amdgcn_mbcnt_lo, {}, {ExtractLo, B.getInt32(0)}); |
| 271 | CallInst *const Mbcnt = B.CreateIntrinsic(Intrinsic::amdgcn_mbcnt_hi, {}, |
| 272 | {ExtractHi, PartialMbcnt}); |
| 273 | |
| 274 | Value *const MbcntCast = B.CreateIntCast(Mbcnt, Ty, false); |
| 275 | |
| 276 | Value *LaneOffset = nullptr; |
| 277 | Value *NewV = nullptr; |
| 278 | |
| 279 | // If we have a divergent value in each lane, we need to combine the value |
| 280 | // using DPP. |
| 281 | if (ValDivergent) { |
| 282 | // First we need to set all inactive invocations to 0, so that they can |
| 283 | // correctly contribute to the final result. |
| 284 | CallInst *const SetInactive = B.CreateIntrinsic( |
| 285 | Intrinsic::amdgcn_set_inactive, Ty, {V, B.getIntN(TyBitWidth, 0)}); |
| 286 | setConvergent(SetInactive); |
| 287 | NewV = SetInactive; |
| 288 | |
| 289 | const unsigned Iters = 6; |
| 290 | const unsigned DPPCtrl[Iters] = {DPP_ROW_SR1, DPP_ROW_SR2, |
| 291 | DPP_ROW_SR4, DPP_ROW_SR8, |
| 292 | DPP_ROW_BCAST15, DPP_ROW_BCAST31}; |
| 293 | const unsigned RowMask[Iters] = {0xf, 0xf, 0xf, 0xf, 0xa, 0xc}; |
| 294 | |
| 295 | // This loop performs an inclusive scan across the wavefront, with all lanes |
| 296 | // active (by using the WWM intrinsic). |
| 297 | for (unsigned Idx = 0; Idx < Iters; Idx++) { |
| 298 | CallInst *const DPP = B.CreateIntrinsic(Intrinsic::amdgcn_mov_dpp, Ty, |
| 299 | {NewV, B.getInt32(DPPCtrl[Idx]), |
| 300 | B.getInt32(RowMask[Idx]), |
| 301 | B.getInt32(0xf), B.getFalse()}); |
| 302 | setConvergent(DPP); |
| 303 | Value *const WWM = B.CreateIntrinsic(Intrinsic::amdgcn_wwm, Ty, DPP); |
| 304 | |
| 305 | NewV = B.CreateBinOp(Op, NewV, WWM); |
| 306 | NewV = B.CreateIntrinsic(Intrinsic::amdgcn_wwm, Ty, NewV); |
| 307 | } |
| 308 | |
| 309 | // NewV has returned the inclusive scan of V, but for the lane offset we |
| 310 | // require an exclusive scan. We do this by shifting the values from the |
| 311 | // entire wavefront right by 1, and by setting the bound_ctrl (last argument |
| 312 | // to the intrinsic below) to true, we can guarantee that 0 will be shifted |
| 313 | // into the 0'th invocation. |
| 314 | CallInst *const DPP = |
| 315 | B.CreateIntrinsic(Intrinsic::amdgcn_mov_dpp, {Ty}, |
| 316 | {NewV, B.getInt32(DPP_WF_SR1), B.getInt32(0xf), |
| 317 | B.getInt32(0xf), B.getTrue()}); |
| 318 | setConvergent(DPP); |
| 319 | LaneOffset = B.CreateIntrinsic(Intrinsic::amdgcn_wwm, Ty, DPP); |
| 320 | |
| 321 | // Read the value from the last lane, which has accumlated the values of |
| 322 | // each active lane in the wavefront. This will be our new value with which |
| 323 | // we will provide to the atomic operation. |
| 324 | if (TyBitWidth == 64) { |
| 325 | Value *const ExtractLo = B.CreateTrunc(NewV, B.getInt32Ty()); |
| 326 | Value *const ExtractHi = |
| 327 | B.CreateTrunc(B.CreateLShr(NewV, B.getInt64(32)), B.getInt32Ty()); |
| 328 | CallInst *const ReadLaneLo = B.CreateIntrinsic( |
| 329 | Intrinsic::amdgcn_readlane, {}, {ExtractLo, B.getInt32(63)}); |
| 330 | setConvergent(ReadLaneLo); |
| 331 | CallInst *const ReadLaneHi = B.CreateIntrinsic( |
| 332 | Intrinsic::amdgcn_readlane, {}, {ExtractHi, B.getInt32(63)}); |
| 333 | setConvergent(ReadLaneHi); |
| 334 | Value *const PartialInsert = B.CreateInsertElement( |
| 335 | UndefValue::get(VecTy), ReadLaneLo, B.getInt32(0)); |
| 336 | Value *const Insert = |
| 337 | B.CreateInsertElement(PartialInsert, ReadLaneHi, B.getInt32(1)); |
| 338 | NewV = B.CreateBitCast(Insert, Ty); |
| 339 | } else if (TyBitWidth == 32) { |
| 340 | CallInst *const ReadLane = B.CreateIntrinsic(Intrinsic::amdgcn_readlane, |
| 341 | {}, {NewV, B.getInt32(63)}); |
| 342 | setConvergent(ReadLane); |
| 343 | NewV = ReadLane; |
| 344 | } else { |
| 345 | llvm_unreachable("Unhandled atomic bit width"); |
| 346 | } |
| 347 | } else { |
| 348 | // Get the total number of active lanes we have by using popcount. |
| 349 | Instruction *const Ctpop = B.CreateUnaryIntrinsic(Intrinsic::ctpop, Exec); |
| 350 | Value *const CtpopCast = B.CreateIntCast(Ctpop, Ty, false); |
| 351 | |
| 352 | // Calculate the new value we will be contributing to the atomic operation |
| 353 | // for the entire wavefront. |
| 354 | NewV = B.CreateMul(V, CtpopCast); |
| 355 | LaneOffset = B.CreateMul(V, MbcntCast); |
| 356 | } |
| 357 | |
| 358 | // We only want a single lane to enter our new control flow, and we do this |
| 359 | // by checking if there are any active lanes below us. Only one lane will |
| 360 | // have 0 active lanes below us, so that will be the only one to progress. |
| 361 | Value *const Cond = B.CreateICmpEQ(MbcntCast, B.getIntN(TyBitWidth, 0)); |
| 362 | |
| 363 | // Store I's original basic block before we split the block. |
| 364 | BasicBlock *const EntryBB = I.getParent(); |
| 365 | |
| 366 | // We need to introduce some new control flow to force a single lane to be |
| 367 | // active. We do this by splitting I's basic block at I, and introducing the |
| 368 | // new block such that: |
| 369 | // entry --> single_lane -\ |
| 370 | // \------------------> exit |
| 371 | Instruction *const SingleLaneTerminator = |
| 372 | SplitBlockAndInsertIfThen(Cond, &I, false, nullptr, DT, nullptr); |
| 373 | |
| 374 | // Move the IR builder into single_lane next. |
| 375 | B.SetInsertPoint(SingleLaneTerminator); |
| 376 | |
| 377 | // Clone the original atomic operation into single lane, replacing the |
| 378 | // original value with our newly created one. |
| 379 | Instruction *const NewI = I.clone(); |
| 380 | B.Insert(NewI); |
| 381 | NewI->setOperand(ValIdx, NewV); |
| 382 | |
| 383 | // Move the IR builder into exit next, and start inserting just before the |
| 384 | // original instruction. |
| 385 | B.SetInsertPoint(&I); |
| 386 | |
| 387 | // Create a PHI node to get our new atomic result into the exit block. |
| 388 | PHINode *const PHI = B.CreatePHI(Ty, 2); |
| 389 | PHI->addIncoming(UndefValue::get(Ty), EntryBB); |
| 390 | PHI->addIncoming(NewI, SingleLaneTerminator->getParent()); |
| 391 | |
| 392 | // We need to broadcast the value who was the lowest active lane (the first |
| 393 | // lane) to all other lanes in the wavefront. We use an intrinsic for this, |
| 394 | // but have to handle 64-bit broadcasts with two calls to this intrinsic. |
| 395 | Value *BroadcastI = nullptr; |
| 396 | |
| 397 | if (TyBitWidth == 64) { |
| 398 | Value *const ExtractLo = B.CreateTrunc(PHI, B.getInt32Ty()); |
| 399 | Value *const ExtractHi = |
| 400 | B.CreateTrunc(B.CreateLShr(PHI, B.getInt64(32)), B.getInt32Ty()); |
| 401 | CallInst *const ReadFirstLaneLo = |
| 402 | B.CreateIntrinsic(Intrinsic::amdgcn_readfirstlane, {}, ExtractLo); |
| 403 | setConvergent(ReadFirstLaneLo); |
| 404 | CallInst *const ReadFirstLaneHi = |
| 405 | B.CreateIntrinsic(Intrinsic::amdgcn_readfirstlane, {}, ExtractHi); |
| 406 | setConvergent(ReadFirstLaneHi); |
| 407 | Value *const PartialInsert = B.CreateInsertElement( |
| 408 | UndefValue::get(VecTy), ReadFirstLaneLo, B.getInt32(0)); |
| 409 | Value *const Insert = |
| 410 | B.CreateInsertElement(PartialInsert, ReadFirstLaneHi, B.getInt32(1)); |
| 411 | BroadcastI = B.CreateBitCast(Insert, Ty); |
| 412 | } else if (TyBitWidth == 32) { |
| 413 | CallInst *const ReadFirstLane = |
| 414 | B.CreateIntrinsic(Intrinsic::amdgcn_readfirstlane, {}, PHI); |
| 415 | setConvergent(ReadFirstLane); |
| 416 | BroadcastI = ReadFirstLane; |
| 417 | } else { |
| 418 | llvm_unreachable("Unhandled atomic bit width"); |
| 419 | } |
| 420 | |
| 421 | // Now that we have the result of our single atomic operation, we need to |
| 422 | // get our individual lane's slice into the result. We use the lane offset we |
| 423 | // previously calculated combined with the atomic result value we got from the |
| 424 | // first lane, to get our lane's index into the atomic result. |
| 425 | Value *const Result = B.CreateBinOp(Op, BroadcastI, LaneOffset); |
| 426 | |
Neil Henning | 233a02d | 2018-11-05 12:04:48 +0000 | [diff] [blame] | 427 | if (IsPixelShader) { |
| 428 | // Need a final PHI to reconverge to above the helper lane branch mask. |
| 429 | B.SetInsertPoint(PixelExitBB->getFirstNonPHI()); |
| 430 | |
| 431 | PHINode *const PHI = B.CreatePHI(Ty, 2); |
| 432 | PHI->addIncoming(UndefValue::get(Ty), PixelEntryBB); |
| 433 | PHI->addIncoming(Result, I.getParent()); |
| 434 | I.replaceAllUsesWith(PHI); |
| 435 | } else { |
| 436 | // Replace the original atomic instruction with the new one. |
| 437 | I.replaceAllUsesWith(Result); |
| 438 | } |
Neil Henning | 6641657 | 2018-10-08 15:49:19 +0000 | [diff] [blame] | 439 | |
| 440 | // And delete the original. |
| 441 | I.eraseFromParent(); |
| 442 | } |
| 443 | |
| 444 | void AMDGPUAtomicOptimizer::setConvergent(CallInst *const CI) const { |
| 445 | CI->addAttribute(AttributeList::FunctionIndex, Attribute::Convergent); |
| 446 | } |
| 447 | |
| 448 | INITIALIZE_PASS_BEGIN(AMDGPUAtomicOptimizer, DEBUG_TYPE, |
| 449 | "AMDGPU atomic optimizations", false, false) |
| 450 | INITIALIZE_PASS_DEPENDENCY(LegacyDivergenceAnalysis) |
| 451 | INITIALIZE_PASS_DEPENDENCY(TargetPassConfig) |
| 452 | INITIALIZE_PASS_END(AMDGPUAtomicOptimizer, DEBUG_TYPE, |
| 453 | "AMDGPU atomic optimizations", false, false) |
| 454 | |
| 455 | FunctionPass *llvm::createAMDGPUAtomicOptimizerPass() { |
| 456 | return new AMDGPUAtomicOptimizer(); |
| 457 | } |