[Flang][OpenMP] Implement workdistribute construct lowering #140523
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✅ With the latest revision this PR passed the C/C++ code formatter. |
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I am not sure the using rewrite patterns is suitable here - mainly because we have a list of transformations we know we need to do in what order so there is no need to involve patterns which add additional overhead and complexity (guarding against matching again etc, making sure the order is correct). That's how the LowerWorkshare pass is implemented. |
Thanks @ivanradanov for feedback. Have updated PR, removing the rewrite patterns. |
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@llvm/pr-subscribers-flang-fir-hlfir @llvm/pr-subscribers-flang-openmp Author: Chaitanya (skc7) ChangesPre-requiste PRs: This PR introduces a new pass "lower-workdistribute" which identifies parallel ops inside workdistribute region and moves them to new omp. target region. This pass implements following rewrites and optimisations: After the pattern match and rewrite, omp.target is moved under omp.target_data region and then only moves the parallelize ops to new omp.target region and moves all other ops to host. The work in this PR is C-P and updated from @ivanradanov commits from coexecute implementation: Patch is 58.11 KiB, truncated to 20.00 KiB below, full version: https://github.com/llvm/llvm-project/pull/140523.diff 10 Files Affected:
diff --git a/flang/include/flang/Optimizer/OpenMP/Passes.td b/flang/include/flang/Optimizer/OpenMP/Passes.td
index 704faf0ccd856..743b6d381ed42 100644
--- a/flang/include/flang/Optimizer/OpenMP/Passes.td
+++ b/flang/include/flang/Optimizer/OpenMP/Passes.td
@@ -93,6 +93,10 @@ def LowerWorkshare : Pass<"lower-workshare", "::mlir::ModuleOp"> {
let summary = "Lower workshare construct";
}
+def LowerWorkdistribute : Pass<"lower-workdistribute", "::mlir::ModuleOp"> {
+ let summary = "Lower workdistribute construct";
+}
+
def GenericLoopConversionPass
: Pass<"omp-generic-loop-conversion", "mlir::func::FuncOp"> {
let summary = "Converts OpenMP generic `omp.loop` to semantically "
diff --git a/flang/lib/Optimizer/OpenMP/CMakeLists.txt b/flang/lib/Optimizer/OpenMP/CMakeLists.txt
index e31543328a9f9..cd746834741f9 100644
--- a/flang/lib/Optimizer/OpenMP/CMakeLists.txt
+++ b/flang/lib/Optimizer/OpenMP/CMakeLists.txt
@@ -7,6 +7,7 @@ add_flang_library(FlangOpenMPTransforms
MapsForPrivatizedSymbols.cpp
MapInfoFinalization.cpp
MarkDeclareTarget.cpp
+ LowerWorkdistribute.cpp
LowerWorkshare.cpp
LowerNontemporal.cpp
diff --git a/flang/lib/Optimizer/OpenMP/LowerWorkdistribute.cpp b/flang/lib/Optimizer/OpenMP/LowerWorkdistribute.cpp
new file mode 100644
index 0000000000000..0885efc716db4
--- /dev/null
+++ b/flang/lib/Optimizer/OpenMP/LowerWorkdistribute.cpp
@@ -0,0 +1,901 @@
+//===- LowerWorkshare.cpp - special cases for bufferization -------===//
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+//===----------------------------------------------------------------------===//
+//
+// This file implements the lowering and optimisations of omp.workdistribute.
+//
+//===----------------------------------------------------------------------===//
+
+#include "flang/Optimizer/Builder/FIRBuilder.h"
+#include "flang/Optimizer/Dialect/FIRDialect.h"
+#include "flang/Optimizer/Dialect/FIROps.h"
+#include "flang/Optimizer/Dialect/FIRType.h"
+#include "flang/Optimizer/HLFIR/Passes.h"
+#include "flang/Optimizer/OpenMP/Utils.h"
+#include "flang/Optimizer/Transforms/Passes.h"
+#include "mlir/Analysis/SliceAnalysis.h"
+#include "mlir/Dialect/OpenMP/OpenMPDialect.h"
+#include "mlir/IR/Builders.h"
+#include "mlir/IR/Value.h"
+#include "mlir/Transforms/DialectConversion.h"
+#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
+#include "mlir/Transforms/RegionUtils.h"
+#include "llvm/Frontend/OpenMP/OMPConstants.h"
+#include <mlir/Dialect/Arith/IR/Arith.h>
+#include <mlir/Dialect/LLVMIR/LLVMTypes.h>
+#include <mlir/Dialect/Utils/IndexingUtils.h>
+#include <mlir/IR/BlockSupport.h>
+#include <mlir/IR/BuiltinOps.h>
+#include <mlir/IR/Diagnostics.h>
+#include <mlir/IR/IRMapping.h>
+#include <mlir/IR/PatternMatch.h>
+#include <mlir/Interfaces/SideEffectInterfaces.h>
+#include <mlir/Support/LLVM.h>
+#include <optional>
+#include <variant>
+
+namespace flangomp {
+#define GEN_PASS_DEF_LOWERWORKDISTRIBUTE
+#include "flang/Optimizer/OpenMP/Passes.h.inc"
+} // namespace flangomp
+
+#define DEBUG_TYPE "lower-workdistribute"
+
+using namespace mlir;
+
+namespace {
+
+static bool isRuntimeCall(Operation *op) {
+ if (auto callOp = dyn_cast<fir::CallOp>(op)) {
+ auto callee = callOp.getCallee();
+ if (!callee)
+ return false;
+ auto *func = op->getParentOfType<ModuleOp>().lookupSymbol(*callee);
+ if (func->getAttr(fir::FIROpsDialect::getFirRuntimeAttrName()))
+ return true;
+ }
+ return false;
+}
+
+/// This is the single source of truth about whether we should parallelize an
+/// operation nested in an omp.execute region.
+static bool shouldParallelize(Operation *op) {
+ if (llvm::any_of(op->getResults(),
+ [](OpResult v) -> bool { return !v.use_empty(); }))
+ return false;
+ // We will parallelize unordered loops - these come from array syntax
+ if (auto loop = dyn_cast<fir::DoLoopOp>(op)) {
+ auto unordered = loop.getUnordered();
+ if (!unordered)
+ return false;
+ return *unordered;
+ }
+ if (isRuntimeCall(op)) {
+ return true;
+ }
+ // We cannot parallise anything else
+ return false;
+}
+
+template <typename T>
+static T getPerfectlyNested(Operation *op) {
+ if (op->getNumRegions() != 1)
+ return nullptr;
+ auto ®ion = op->getRegion(0);
+ if (region.getBlocks().size() != 1)
+ return nullptr;
+ auto *block = ®ion.front();
+ auto *firstOp = &block->front();
+ if (auto nested = dyn_cast<T>(firstOp))
+ if (firstOp->getNextNode() == block->getTerminator())
+ return nested;
+ return nullptr;
+}
+
+/// If B() and D() are parallelizable,
+///
+/// omp.teams {
+/// omp.workdistribute {
+/// A()
+/// B()
+/// C()
+/// D()
+/// E()
+/// }
+/// }
+///
+/// becomes
+///
+/// A()
+/// omp.teams {
+/// omp.workdistribute {
+/// B()
+/// }
+/// }
+/// C()
+/// omp.teams {
+/// omp.workdistribute {
+/// D()
+/// }
+/// }
+/// E()
+
+static bool FissionWorkdistribute(omp::WorkdistributeOp workdistribute) {
+ OpBuilder rewriter(workdistribute);
+ auto loc = workdistribute->getLoc();
+ auto teams = dyn_cast<omp::TeamsOp>(workdistribute->getParentOp());
+ if (!teams) {
+ emitError(loc, "workdistribute not nested in teams\n");
+ return false;
+ }
+ if (workdistribute.getRegion().getBlocks().size() != 1) {
+ emitError(loc, "workdistribute with multiple blocks\n");
+ return false;
+ }
+ if (teams.getRegion().getBlocks().size() != 1) {
+ emitError(loc, "teams with multiple blocks\n");
+ return false;
+ }
+
+ auto *teamsBlock = &teams.getRegion().front();
+ bool changed = false;
+ // Move the ops inside teams and before workdistribute outside.
+ IRMapping irMapping;
+ llvm::SmallVector<Operation *> teamsHoisted;
+ for (auto &op : teams.getOps()) {
+ if (&op == workdistribute) {
+ break;
+ }
+ if (shouldParallelize(&op)) {
+ emitError(loc, "teams has parallelize ops before first workdistribute\n");
+ return false;
+ } else {
+ rewriter.setInsertionPoint(teams);
+ rewriter.clone(op, irMapping);
+ teamsHoisted.push_back(&op);
+ changed = true;
+ }
+ }
+ for (auto *op : llvm::reverse(teamsHoisted)) {
+ op->replaceAllUsesWith(irMapping.lookup(op));
+ op->erase();
+ }
+
+ // While we have unhandled operations in the original workdistribute
+ auto *workdistributeBlock = &workdistribute.getRegion().front();
+ auto *terminator = workdistributeBlock->getTerminator();
+ while (&workdistributeBlock->front() != terminator) {
+ rewriter.setInsertionPoint(teams);
+ IRMapping mapping;
+ llvm::SmallVector<Operation *> hoisted;
+ Operation *parallelize = nullptr;
+ for (auto &op : workdistribute.getOps()) {
+ if (&op == terminator) {
+ break;
+ }
+ if (shouldParallelize(&op)) {
+ parallelize = &op;
+ break;
+ } else {
+ rewriter.clone(op, mapping);
+ hoisted.push_back(&op);
+ changed = true;
+ }
+ }
+
+ for (auto *op : llvm::reverse(hoisted)) {
+ op->replaceAllUsesWith(mapping.lookup(op));
+ op->erase();
+ }
+
+ if (parallelize && hoisted.empty() &&
+ parallelize->getNextNode() == terminator)
+ break;
+ if (parallelize) {
+ auto newTeams = rewriter.cloneWithoutRegions(teams);
+ auto *newTeamsBlock = rewriter.createBlock(
+ &newTeams.getRegion(), newTeams.getRegion().begin(), {}, {});
+ for (auto arg : teamsBlock->getArguments())
+ newTeamsBlock->addArgument(arg.getType(), arg.getLoc());
+ auto newWorkdistribute = rewriter.create<omp::WorkdistributeOp>(loc);
+ rewriter.create<omp::TerminatorOp>(loc);
+ rewriter.createBlock(&newWorkdistribute.getRegion(),
+ newWorkdistribute.getRegion().begin(), {}, {});
+ auto *cloned = rewriter.clone(*parallelize);
+ parallelize->replaceAllUsesWith(cloned);
+ parallelize->erase();
+ rewriter.create<omp::TerminatorOp>(loc);
+ changed = true;
+ }
+ }
+ return changed;
+}
+
+/// If fir.do_loop is present inside teams workdistribute
+///
+/// omp.teams {
+/// omp.workdistribute {
+/// fir.do_loop unoredered {
+/// ...
+/// }
+/// }
+/// }
+///
+/// Then, its lowered to
+///
+/// omp.teams {
+/// omp.parallel {
+/// omp.distribute {
+/// omp.wsloop {
+/// omp.loop_nest
+/// ...
+/// }
+/// }
+/// }
+/// }
+
+static void genParallelOp(Location loc, OpBuilder &rewriter, bool composite) {
+ auto parallelOp = rewriter.create<mlir::omp::ParallelOp>(loc);
+ parallelOp.setComposite(composite);
+ rewriter.createBlock(¶llelOp.getRegion());
+ rewriter.setInsertionPoint(rewriter.create<mlir::omp::TerminatorOp>(loc));
+ return;
+}
+
+static void genDistributeOp(Location loc, OpBuilder &rewriter, bool composite) {
+ mlir::omp::DistributeOperands distributeClauseOps;
+ auto distributeOp =
+ rewriter.create<mlir::omp::DistributeOp>(loc, distributeClauseOps);
+ distributeOp.setComposite(composite);
+ auto distributeBlock = rewriter.createBlock(&distributeOp.getRegion());
+ rewriter.setInsertionPointToStart(distributeBlock);
+ return;
+}
+
+static void
+genLoopNestClauseOps(OpBuilder &rewriter, fir::DoLoopOp loop,
+ mlir::omp::LoopNestOperands &loopNestClauseOps) {
+ assert(loopNestClauseOps.loopLowerBounds.empty() &&
+ "Loop nest bounds were already emitted!");
+ loopNestClauseOps.loopLowerBounds.push_back(loop.getLowerBound());
+ loopNestClauseOps.loopUpperBounds.push_back(loop.getUpperBound());
+ loopNestClauseOps.loopSteps.push_back(loop.getStep());
+ loopNestClauseOps.loopInclusive = rewriter.getUnitAttr();
+}
+
+static void genWsLoopOp(mlir::OpBuilder &rewriter, fir::DoLoopOp doLoop,
+ const mlir::omp::LoopNestOperands &clauseOps,
+ bool composite) {
+
+ auto wsloopOp = rewriter.create<mlir::omp::WsloopOp>(doLoop.getLoc());
+ wsloopOp.setComposite(composite);
+ rewriter.createBlock(&wsloopOp.getRegion());
+
+ auto loopNestOp =
+ rewriter.create<mlir::omp::LoopNestOp>(doLoop.getLoc(), clauseOps);
+
+ // Clone the loop's body inside the loop nest construct using the
+ // mapped values.
+ rewriter.cloneRegionBefore(doLoop.getRegion(), loopNestOp.getRegion(),
+ loopNestOp.getRegion().begin());
+ Block *clonedBlock = &loopNestOp.getRegion().back();
+ mlir::Operation *terminatorOp = clonedBlock->getTerminator();
+
+ // Erase fir.result op of do loop and create yield op.
+ if (auto resultOp = dyn_cast<fir::ResultOp>(terminatorOp)) {
+ rewriter.setInsertionPoint(terminatorOp);
+ rewriter.create<mlir::omp::YieldOp>(doLoop->getLoc());
+ // rewriter.erase(terminatorOp);
+ terminatorOp->erase();
+ }
+ return;
+}
+
+static bool WorkdistributeDoLower(omp::WorkdistributeOp workdistribute) {
+ OpBuilder rewriter(workdistribute);
+ auto doLoop = getPerfectlyNested<fir::DoLoopOp>(workdistribute);
+ auto wdLoc = workdistribute->getLoc();
+ if (doLoop && shouldParallelize(doLoop)) {
+ assert(doLoop.getReduceOperands().empty());
+ genParallelOp(wdLoc, rewriter, true);
+ genDistributeOp(wdLoc, rewriter, true);
+ mlir::omp::LoopNestOperands loopNestClauseOps;
+ genLoopNestClauseOps(rewriter, doLoop, loopNestClauseOps);
+ genWsLoopOp(rewriter, doLoop, loopNestClauseOps, true);
+ workdistribute.erase();
+ return true;
+ }
+ return false;
+}
+
+/// If A() and B () are present inside teams workdistribute
+///
+/// omp.teams {
+/// omp.workdistribute {
+/// A()
+/// B()
+/// }
+/// }
+///
+/// Then, its lowered to
+///
+/// A()
+/// B()
+///
+
+static bool TeamsWorkdistributeToSingleOp(omp::TeamsOp teamsOp) {
+ auto workdistributeOp = getPerfectlyNested<omp::WorkdistributeOp>(teamsOp);
+ if (!workdistributeOp)
+ return false;
+ // Get the block containing teamsOp (the parent block).
+ Block *parentBlock = teamsOp->getBlock();
+ Block &workdistributeBlock = *workdistributeOp.getRegion().begin();
+ auto insertPoint = Block::iterator(teamsOp);
+ // Get the range of operations to move (excluding the terminator).
+ auto workdistributeBegin = workdistributeBlock.begin();
+ auto workdistributeEnd = workdistributeBlock.getTerminator()->getIterator();
+ // Move the operations from workdistribute block to before teamsOp.
+ parentBlock->getOperations().splice(insertPoint,
+ workdistributeBlock.getOperations(),
+ workdistributeBegin, workdistributeEnd);
+ // Erase the now-empty workdistributeOp.
+ workdistributeOp.erase();
+ Block &teamsBlock = *teamsOp.getRegion().begin();
+ // Check if only the terminator remains and erase teams op.
+ if (teamsBlock.getOperations().size() == 1 &&
+ teamsBlock.getTerminator() != nullptr) {
+ teamsOp.erase();
+ }
+ return true;
+}
+
+struct SplitTargetResult {
+ omp::TargetOp targetOp;
+ omp::TargetDataOp dataOp;
+};
+
+/// If multiple workdistribute are nested in a target regions, we will need to
+/// split the target region, but we want to preserve the data semantics of the
+/// original data region and avoid unnecessary data movement at each of the
+/// subkernels - we split the target region into a target_data{target}
+/// nest where only the outer one moves the data
+std::optional<SplitTargetResult> splitTargetData(omp::TargetOp targetOp,
+ RewriterBase &rewriter) {
+ auto loc = targetOp->getLoc();
+ if (targetOp.getMapVars().empty()) {
+ LLVM_DEBUG(llvm::dbgs()
+ << DEBUG_TYPE << " target region has no data maps\n");
+ return std::nullopt;
+ }
+
+ SmallVector<omp::MapInfoOp> mapInfos;
+ for (auto opr : targetOp.getMapVars()) {
+ auto mapInfo = cast<omp::MapInfoOp>(opr.getDefiningOp());
+ mapInfos.push_back(mapInfo);
+ }
+
+ rewriter.setInsertionPoint(targetOp);
+ SmallVector<Value> innerMapInfos;
+ SmallVector<Value> outerMapInfos;
+
+ for (auto mapInfo : mapInfos) {
+ auto originalMapType =
+ (llvm::omp::OpenMPOffloadMappingFlags)(mapInfo.getMapType());
+ auto originalCaptureType = mapInfo.getMapCaptureType();
+ llvm::omp::OpenMPOffloadMappingFlags newMapType;
+ mlir::omp::VariableCaptureKind newCaptureType;
+
+ if (originalCaptureType == mlir::omp::VariableCaptureKind::ByCopy) {
+ newMapType = originalMapType;
+ newCaptureType = originalCaptureType;
+ } else if (originalCaptureType == mlir::omp::VariableCaptureKind::ByRef) {
+ newMapType = llvm::omp::OpenMPOffloadMappingFlags::OMP_MAP_NONE;
+ newCaptureType = originalCaptureType;
+ outerMapInfos.push_back(mapInfo);
+ } else {
+ llvm_unreachable("Unhandled case");
+ }
+ auto innerMapInfo = cast<omp::MapInfoOp>(rewriter.clone(*mapInfo));
+ innerMapInfo.setMapTypeAttr(rewriter.getIntegerAttr(
+ rewriter.getIntegerType(64, false),
+ static_cast<
+ std::underlying_type_t<llvm::omp::OpenMPOffloadMappingFlags>>(
+ newMapType)));
+ innerMapInfo.setMapCaptureType(newCaptureType);
+ innerMapInfos.push_back(innerMapInfo.getResult());
+ }
+
+ rewriter.setInsertionPoint(targetOp);
+ auto device = targetOp.getDevice();
+ auto ifExpr = targetOp.getIfExpr();
+ auto deviceAddrVars = targetOp.getHasDeviceAddrVars();
+ auto devicePtrVars = targetOp.getIsDevicePtrVars();
+ auto targetDataOp = rewriter.create<omp::TargetDataOp>(
+ loc, device, ifExpr, outerMapInfos, deviceAddrVars, devicePtrVars);
+ auto taregtDataBlock = rewriter.createBlock(&targetDataOp.getRegion());
+ rewriter.create<mlir::omp::TerminatorOp>(loc);
+ rewriter.setInsertionPointToStart(taregtDataBlock);
+
+ auto newTargetOp = rewriter.create<omp::TargetOp>(
+ targetOp.getLoc(), targetOp.getAllocateVars(),
+ targetOp.getAllocatorVars(), targetOp.getBareAttr(),
+ targetOp.getDependKindsAttr(), targetOp.getDependVars(),
+ targetOp.getDevice(), targetOp.getHasDeviceAddrVars(),
+ targetOp.getHostEvalVars(), targetOp.getIfExpr(),
+ targetOp.getInReductionVars(), targetOp.getInReductionByrefAttr(),
+ targetOp.getInReductionSymsAttr(), targetOp.getIsDevicePtrVars(),
+ innerMapInfos, targetOp.getNowaitAttr(), targetOp.getPrivateVars(),
+ targetOp.getPrivateSymsAttr(), targetOp.getPrivateNeedsBarrierAttr(),
+ targetOp.getThreadLimit(), targetOp.getPrivateMapsAttr());
+ rewriter.inlineRegionBefore(targetOp.getRegion(), newTargetOp.getRegion(),
+ newTargetOp.getRegion().begin());
+
+ rewriter.replaceOp(targetOp, newTargetOp);
+ return SplitTargetResult{cast<omp::TargetOp>(newTargetOp), targetDataOp};
+}
+
+static std::optional<std::tuple<Operation *, bool, bool>>
+getNestedOpToIsolate(omp::TargetOp targetOp) {
+ if (targetOp.getRegion().empty())
+ return std::nullopt;
+ auto *targetBlock = &targetOp.getRegion().front();
+ for (auto &op : *targetBlock) {
+ bool first = &op == &*targetBlock->begin();
+ bool last = op.getNextNode() == targetBlock->getTerminator();
+ if (first && last)
+ return std::nullopt;
+
+ if (isa<omp::TeamsOp, omp::ParallelOp>(&op))
+ return {{&op, first, last}};
+ }
+ return std::nullopt;
+}
+
+struct TempOmpVar {
+ omp::MapInfoOp from, to;
+};
+
+static bool isPtr(Type ty) {
+ return isa<fir::ReferenceType>(ty) || isa<LLVM::LLVMPointerType>(ty);
+}
+
+static Type getPtrTypeForOmp(Type ty) {
+ if (isPtr(ty))
+ return LLVM::LLVMPointerType::get(ty.getContext());
+ else
+ return fir::LLVMPointerType::get(ty);
+}
+
+static TempOmpVar allocateTempOmpVar(Location loc, Type ty,
+ RewriterBase &rewriter) {
+ MLIRContext &ctx = *ty.getContext();
+ Value alloc;
+ Type allocType;
+ auto llvmPtrTy = LLVM::LLVMPointerType::get(&ctx);
+ if (isPtr(ty)) {
+ Type intTy = rewriter.getI32Type();
+ auto one = rewriter.create<LLVM::ConstantOp>(loc, intTy, 1);
+ allocType = llvmPtrTy;
+ alloc = rewriter.create<LLVM::AllocaOp>(loc, llvmPtrTy, allocType, one);
+ allocType = intTy;
+ } else {
+ allocType = ty;
+ alloc = rewriter.create<fir::AllocaOp>(loc, allocType);
+ }
+ auto getMapInfo = [&](uint64_t mappingFlags, const char *name) {
+ return rewriter.create<omp::MapInfoOp>(
+ loc, alloc.getType(), alloc, TypeAttr::get(allocType),
+ rewriter.getIntegerAttr(rewriter.getIntegerType(64, /*isSigned=*/false),
+ mappingFlags),
+ rewriter.getAttr<omp::VariableCaptureKindAttr>(
+ omp::VariableCaptureKind::ByRef),
+ /*varPtrPtr=*/Value{},
+ /*members=*/SmallVector<Value>{},
+ /*member_index=*/mlir::ArrayAttr{},
+ /*bounds=*/ValueRange(),
+ /*mapperId=*/mlir::FlatSymbolRefAttr(),
+ /*name=*/rewriter.getStringAttr(name), rewriter.getBoolAttr(false));
+ };
+ uint64_t mapFrom =
+ static_cast<std::underlying_type_t<llvm::omp::OpenMPOffloadMappingFlags>>(
+ llvm::omp::OpenMPOffloadMappingFlags::OMP_MAP_FROM);
+ uint64_t mapTo =
+ static_cast<std::underlying_type_t<llvm::omp::OpenMPOffloadMappingFlags>>(
+ llvm::omp::OpenMPOffloadMappingFlags::OMP_MAP_TO);
+ auto mapInfoFrom = getMapInfo(mapFrom, "__flang_workdistribute_from");
+ auto mapInfoTo = getMapInfo(mapTo, "__flang_workdistribute_to");
+ return TempOmpVar{mapInfoFrom, mapInfoTo};
+};
+
+static bool usedOutsideSplit(Value v, Operation *split) {
+ if (!split)
+ return false;
+ auto targetOp = cast<omp::TargetOp>(split->getParentOp());
+ auto *targetBlock = &targetOp.getRegion().front();
+ for (auto *user : v.getUsers()) {
+ while (user->getBlock() != targetBlock) {
+ user = user->getParentOp();
+ }
+ if (!user->isBeforeInBlock(split))
+ return true;
+ }
+ return false;
+};
+
+static bool isRecomputableAfterFission(Operation *op, Operation *splitBefore) {
+ if (isa<fir::DeclareOp>(op))
+ return true;
+
+ llvm::SmallVector<MemoryEffects::EffectInstance> effects;
+ MemoryEffectOpInterface interface = dyn_cast<MemoryEffectOpInterface>(op);
+ if (!interface) {
+ return false;
+ }
+ interface.getEffects(effects);
+ if (effects.empty())
+ return true;
+ return false;
+}
+
+...
[truncated]
|
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@llvm/pr-subscribers-mlir Author: Chaitanya (skc7) ChangesPre-requiste PRs: This PR introduces a new pass "lower-workdistribute" which identifies parallel ops inside workdistribute region and moves them to new omp. target region. This pass implements following rewrites and optimisations: After the pattern match and rewrite, omp.target is moved under omp.target_data region and then only moves the parallelize ops to new omp.target region and moves all other ops to host. The work in this PR is C-P and updated from @ivanradanov commits from coexecute implementation: Patch is 58.11 KiB, truncated to 20.00 KiB below, full version: https://github.com/llvm/llvm-project/pull/140523.diff 10 Files Affected:
diff --git a/flang/include/flang/Optimizer/OpenMP/Passes.td b/flang/include/flang/Optimizer/OpenMP/Passes.td
index 704faf0ccd856..743b6d381ed42 100644
--- a/flang/include/flang/Optimizer/OpenMP/Passes.td
+++ b/flang/include/flang/Optimizer/OpenMP/Passes.td
@@ -93,6 +93,10 @@ def LowerWorkshare : Pass<"lower-workshare", "::mlir::ModuleOp"> {
let summary = "Lower workshare construct";
}
+def LowerWorkdistribute : Pass<"lower-workdistribute", "::mlir::ModuleOp"> {
+ let summary = "Lower workdistribute construct";
+}
+
def GenericLoopConversionPass
: Pass<"omp-generic-loop-conversion", "mlir::func::FuncOp"> {
let summary = "Converts OpenMP generic `omp.loop` to semantically "
diff --git a/flang/lib/Optimizer/OpenMP/CMakeLists.txt b/flang/lib/Optimizer/OpenMP/CMakeLists.txt
index e31543328a9f9..cd746834741f9 100644
--- a/flang/lib/Optimizer/OpenMP/CMakeLists.txt
+++ b/flang/lib/Optimizer/OpenMP/CMakeLists.txt
@@ -7,6 +7,7 @@ add_flang_library(FlangOpenMPTransforms
MapsForPrivatizedSymbols.cpp
MapInfoFinalization.cpp
MarkDeclareTarget.cpp
+ LowerWorkdistribute.cpp
LowerWorkshare.cpp
LowerNontemporal.cpp
diff --git a/flang/lib/Optimizer/OpenMP/LowerWorkdistribute.cpp b/flang/lib/Optimizer/OpenMP/LowerWorkdistribute.cpp
new file mode 100644
index 0000000000000..0885efc716db4
--- /dev/null
+++ b/flang/lib/Optimizer/OpenMP/LowerWorkdistribute.cpp
@@ -0,0 +1,901 @@
+//===- LowerWorkshare.cpp - special cases for bufferization -------===//
+//
+// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+//
+//===----------------------------------------------------------------------===//
+//
+// This file implements the lowering and optimisations of omp.workdistribute.
+//
+//===----------------------------------------------------------------------===//
+
+#include "flang/Optimizer/Builder/FIRBuilder.h"
+#include "flang/Optimizer/Dialect/FIRDialect.h"
+#include "flang/Optimizer/Dialect/FIROps.h"
+#include "flang/Optimizer/Dialect/FIRType.h"
+#include "flang/Optimizer/HLFIR/Passes.h"
+#include "flang/Optimizer/OpenMP/Utils.h"
+#include "flang/Optimizer/Transforms/Passes.h"
+#include "mlir/Analysis/SliceAnalysis.h"
+#include "mlir/Dialect/OpenMP/OpenMPDialect.h"
+#include "mlir/IR/Builders.h"
+#include "mlir/IR/Value.h"
+#include "mlir/Transforms/DialectConversion.h"
+#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
+#include "mlir/Transforms/RegionUtils.h"
+#include "llvm/Frontend/OpenMP/OMPConstants.h"
+#include <mlir/Dialect/Arith/IR/Arith.h>
+#include <mlir/Dialect/LLVMIR/LLVMTypes.h>
+#include <mlir/Dialect/Utils/IndexingUtils.h>
+#include <mlir/IR/BlockSupport.h>
+#include <mlir/IR/BuiltinOps.h>
+#include <mlir/IR/Diagnostics.h>
+#include <mlir/IR/IRMapping.h>
+#include <mlir/IR/PatternMatch.h>
+#include <mlir/Interfaces/SideEffectInterfaces.h>
+#include <mlir/Support/LLVM.h>
+#include <optional>
+#include <variant>
+
+namespace flangomp {
+#define GEN_PASS_DEF_LOWERWORKDISTRIBUTE
+#include "flang/Optimizer/OpenMP/Passes.h.inc"
+} // namespace flangomp
+
+#define DEBUG_TYPE "lower-workdistribute"
+
+using namespace mlir;
+
+namespace {
+
+static bool isRuntimeCall(Operation *op) {
+ if (auto callOp = dyn_cast<fir::CallOp>(op)) {
+ auto callee = callOp.getCallee();
+ if (!callee)
+ return false;
+ auto *func = op->getParentOfType<ModuleOp>().lookupSymbol(*callee);
+ if (func->getAttr(fir::FIROpsDialect::getFirRuntimeAttrName()))
+ return true;
+ }
+ return false;
+}
+
+/// This is the single source of truth about whether we should parallelize an
+/// operation nested in an omp.execute region.
+static bool shouldParallelize(Operation *op) {
+ if (llvm::any_of(op->getResults(),
+ [](OpResult v) -> bool { return !v.use_empty(); }))
+ return false;
+ // We will parallelize unordered loops - these come from array syntax
+ if (auto loop = dyn_cast<fir::DoLoopOp>(op)) {
+ auto unordered = loop.getUnordered();
+ if (!unordered)
+ return false;
+ return *unordered;
+ }
+ if (isRuntimeCall(op)) {
+ return true;
+ }
+ // We cannot parallise anything else
+ return false;
+}
+
+template <typename T>
+static T getPerfectlyNested(Operation *op) {
+ if (op->getNumRegions() != 1)
+ return nullptr;
+ auto ®ion = op->getRegion(0);
+ if (region.getBlocks().size() != 1)
+ return nullptr;
+ auto *block = ®ion.front();
+ auto *firstOp = &block->front();
+ if (auto nested = dyn_cast<T>(firstOp))
+ if (firstOp->getNextNode() == block->getTerminator())
+ return nested;
+ return nullptr;
+}
+
+/// If B() and D() are parallelizable,
+///
+/// omp.teams {
+/// omp.workdistribute {
+/// A()
+/// B()
+/// C()
+/// D()
+/// E()
+/// }
+/// }
+///
+/// becomes
+///
+/// A()
+/// omp.teams {
+/// omp.workdistribute {
+/// B()
+/// }
+/// }
+/// C()
+/// omp.teams {
+/// omp.workdistribute {
+/// D()
+/// }
+/// }
+/// E()
+
+static bool FissionWorkdistribute(omp::WorkdistributeOp workdistribute) {
+ OpBuilder rewriter(workdistribute);
+ auto loc = workdistribute->getLoc();
+ auto teams = dyn_cast<omp::TeamsOp>(workdistribute->getParentOp());
+ if (!teams) {
+ emitError(loc, "workdistribute not nested in teams\n");
+ return false;
+ }
+ if (workdistribute.getRegion().getBlocks().size() != 1) {
+ emitError(loc, "workdistribute with multiple blocks\n");
+ return false;
+ }
+ if (teams.getRegion().getBlocks().size() != 1) {
+ emitError(loc, "teams with multiple blocks\n");
+ return false;
+ }
+
+ auto *teamsBlock = &teams.getRegion().front();
+ bool changed = false;
+ // Move the ops inside teams and before workdistribute outside.
+ IRMapping irMapping;
+ llvm::SmallVector<Operation *> teamsHoisted;
+ for (auto &op : teams.getOps()) {
+ if (&op == workdistribute) {
+ break;
+ }
+ if (shouldParallelize(&op)) {
+ emitError(loc, "teams has parallelize ops before first workdistribute\n");
+ return false;
+ } else {
+ rewriter.setInsertionPoint(teams);
+ rewriter.clone(op, irMapping);
+ teamsHoisted.push_back(&op);
+ changed = true;
+ }
+ }
+ for (auto *op : llvm::reverse(teamsHoisted)) {
+ op->replaceAllUsesWith(irMapping.lookup(op));
+ op->erase();
+ }
+
+ // While we have unhandled operations in the original workdistribute
+ auto *workdistributeBlock = &workdistribute.getRegion().front();
+ auto *terminator = workdistributeBlock->getTerminator();
+ while (&workdistributeBlock->front() != terminator) {
+ rewriter.setInsertionPoint(teams);
+ IRMapping mapping;
+ llvm::SmallVector<Operation *> hoisted;
+ Operation *parallelize = nullptr;
+ for (auto &op : workdistribute.getOps()) {
+ if (&op == terminator) {
+ break;
+ }
+ if (shouldParallelize(&op)) {
+ parallelize = &op;
+ break;
+ } else {
+ rewriter.clone(op, mapping);
+ hoisted.push_back(&op);
+ changed = true;
+ }
+ }
+
+ for (auto *op : llvm::reverse(hoisted)) {
+ op->replaceAllUsesWith(mapping.lookup(op));
+ op->erase();
+ }
+
+ if (parallelize && hoisted.empty() &&
+ parallelize->getNextNode() == terminator)
+ break;
+ if (parallelize) {
+ auto newTeams = rewriter.cloneWithoutRegions(teams);
+ auto *newTeamsBlock = rewriter.createBlock(
+ &newTeams.getRegion(), newTeams.getRegion().begin(), {}, {});
+ for (auto arg : teamsBlock->getArguments())
+ newTeamsBlock->addArgument(arg.getType(), arg.getLoc());
+ auto newWorkdistribute = rewriter.create<omp::WorkdistributeOp>(loc);
+ rewriter.create<omp::TerminatorOp>(loc);
+ rewriter.createBlock(&newWorkdistribute.getRegion(),
+ newWorkdistribute.getRegion().begin(), {}, {});
+ auto *cloned = rewriter.clone(*parallelize);
+ parallelize->replaceAllUsesWith(cloned);
+ parallelize->erase();
+ rewriter.create<omp::TerminatorOp>(loc);
+ changed = true;
+ }
+ }
+ return changed;
+}
+
+/// If fir.do_loop is present inside teams workdistribute
+///
+/// omp.teams {
+/// omp.workdistribute {
+/// fir.do_loop unoredered {
+/// ...
+/// }
+/// }
+/// }
+///
+/// Then, its lowered to
+///
+/// omp.teams {
+/// omp.parallel {
+/// omp.distribute {
+/// omp.wsloop {
+/// omp.loop_nest
+/// ...
+/// }
+/// }
+/// }
+/// }
+
+static void genParallelOp(Location loc, OpBuilder &rewriter, bool composite) {
+ auto parallelOp = rewriter.create<mlir::omp::ParallelOp>(loc);
+ parallelOp.setComposite(composite);
+ rewriter.createBlock(¶llelOp.getRegion());
+ rewriter.setInsertionPoint(rewriter.create<mlir::omp::TerminatorOp>(loc));
+ return;
+}
+
+static void genDistributeOp(Location loc, OpBuilder &rewriter, bool composite) {
+ mlir::omp::DistributeOperands distributeClauseOps;
+ auto distributeOp =
+ rewriter.create<mlir::omp::DistributeOp>(loc, distributeClauseOps);
+ distributeOp.setComposite(composite);
+ auto distributeBlock = rewriter.createBlock(&distributeOp.getRegion());
+ rewriter.setInsertionPointToStart(distributeBlock);
+ return;
+}
+
+static void
+genLoopNestClauseOps(OpBuilder &rewriter, fir::DoLoopOp loop,
+ mlir::omp::LoopNestOperands &loopNestClauseOps) {
+ assert(loopNestClauseOps.loopLowerBounds.empty() &&
+ "Loop nest bounds were already emitted!");
+ loopNestClauseOps.loopLowerBounds.push_back(loop.getLowerBound());
+ loopNestClauseOps.loopUpperBounds.push_back(loop.getUpperBound());
+ loopNestClauseOps.loopSteps.push_back(loop.getStep());
+ loopNestClauseOps.loopInclusive = rewriter.getUnitAttr();
+}
+
+static void genWsLoopOp(mlir::OpBuilder &rewriter, fir::DoLoopOp doLoop,
+ const mlir::omp::LoopNestOperands &clauseOps,
+ bool composite) {
+
+ auto wsloopOp = rewriter.create<mlir::omp::WsloopOp>(doLoop.getLoc());
+ wsloopOp.setComposite(composite);
+ rewriter.createBlock(&wsloopOp.getRegion());
+
+ auto loopNestOp =
+ rewriter.create<mlir::omp::LoopNestOp>(doLoop.getLoc(), clauseOps);
+
+ // Clone the loop's body inside the loop nest construct using the
+ // mapped values.
+ rewriter.cloneRegionBefore(doLoop.getRegion(), loopNestOp.getRegion(),
+ loopNestOp.getRegion().begin());
+ Block *clonedBlock = &loopNestOp.getRegion().back();
+ mlir::Operation *terminatorOp = clonedBlock->getTerminator();
+
+ // Erase fir.result op of do loop and create yield op.
+ if (auto resultOp = dyn_cast<fir::ResultOp>(terminatorOp)) {
+ rewriter.setInsertionPoint(terminatorOp);
+ rewriter.create<mlir::omp::YieldOp>(doLoop->getLoc());
+ // rewriter.erase(terminatorOp);
+ terminatorOp->erase();
+ }
+ return;
+}
+
+static bool WorkdistributeDoLower(omp::WorkdistributeOp workdistribute) {
+ OpBuilder rewriter(workdistribute);
+ auto doLoop = getPerfectlyNested<fir::DoLoopOp>(workdistribute);
+ auto wdLoc = workdistribute->getLoc();
+ if (doLoop && shouldParallelize(doLoop)) {
+ assert(doLoop.getReduceOperands().empty());
+ genParallelOp(wdLoc, rewriter, true);
+ genDistributeOp(wdLoc, rewriter, true);
+ mlir::omp::LoopNestOperands loopNestClauseOps;
+ genLoopNestClauseOps(rewriter, doLoop, loopNestClauseOps);
+ genWsLoopOp(rewriter, doLoop, loopNestClauseOps, true);
+ workdistribute.erase();
+ return true;
+ }
+ return false;
+}
+
+/// If A() and B () are present inside teams workdistribute
+///
+/// omp.teams {
+/// omp.workdistribute {
+/// A()
+/// B()
+/// }
+/// }
+///
+/// Then, its lowered to
+///
+/// A()
+/// B()
+///
+
+static bool TeamsWorkdistributeToSingleOp(omp::TeamsOp teamsOp) {
+ auto workdistributeOp = getPerfectlyNested<omp::WorkdistributeOp>(teamsOp);
+ if (!workdistributeOp)
+ return false;
+ // Get the block containing teamsOp (the parent block).
+ Block *parentBlock = teamsOp->getBlock();
+ Block &workdistributeBlock = *workdistributeOp.getRegion().begin();
+ auto insertPoint = Block::iterator(teamsOp);
+ // Get the range of operations to move (excluding the terminator).
+ auto workdistributeBegin = workdistributeBlock.begin();
+ auto workdistributeEnd = workdistributeBlock.getTerminator()->getIterator();
+ // Move the operations from workdistribute block to before teamsOp.
+ parentBlock->getOperations().splice(insertPoint,
+ workdistributeBlock.getOperations(),
+ workdistributeBegin, workdistributeEnd);
+ // Erase the now-empty workdistributeOp.
+ workdistributeOp.erase();
+ Block &teamsBlock = *teamsOp.getRegion().begin();
+ // Check if only the terminator remains and erase teams op.
+ if (teamsBlock.getOperations().size() == 1 &&
+ teamsBlock.getTerminator() != nullptr) {
+ teamsOp.erase();
+ }
+ return true;
+}
+
+struct SplitTargetResult {
+ omp::TargetOp targetOp;
+ omp::TargetDataOp dataOp;
+};
+
+/// If multiple workdistribute are nested in a target regions, we will need to
+/// split the target region, but we want to preserve the data semantics of the
+/// original data region and avoid unnecessary data movement at each of the
+/// subkernels - we split the target region into a target_data{target}
+/// nest where only the outer one moves the data
+std::optional<SplitTargetResult> splitTargetData(omp::TargetOp targetOp,
+ RewriterBase &rewriter) {
+ auto loc = targetOp->getLoc();
+ if (targetOp.getMapVars().empty()) {
+ LLVM_DEBUG(llvm::dbgs()
+ << DEBUG_TYPE << " target region has no data maps\n");
+ return std::nullopt;
+ }
+
+ SmallVector<omp::MapInfoOp> mapInfos;
+ for (auto opr : targetOp.getMapVars()) {
+ auto mapInfo = cast<omp::MapInfoOp>(opr.getDefiningOp());
+ mapInfos.push_back(mapInfo);
+ }
+
+ rewriter.setInsertionPoint(targetOp);
+ SmallVector<Value> innerMapInfos;
+ SmallVector<Value> outerMapInfos;
+
+ for (auto mapInfo : mapInfos) {
+ auto originalMapType =
+ (llvm::omp::OpenMPOffloadMappingFlags)(mapInfo.getMapType());
+ auto originalCaptureType = mapInfo.getMapCaptureType();
+ llvm::omp::OpenMPOffloadMappingFlags newMapType;
+ mlir::omp::VariableCaptureKind newCaptureType;
+
+ if (originalCaptureType == mlir::omp::VariableCaptureKind::ByCopy) {
+ newMapType = originalMapType;
+ newCaptureType = originalCaptureType;
+ } else if (originalCaptureType == mlir::omp::VariableCaptureKind::ByRef) {
+ newMapType = llvm::omp::OpenMPOffloadMappingFlags::OMP_MAP_NONE;
+ newCaptureType = originalCaptureType;
+ outerMapInfos.push_back(mapInfo);
+ } else {
+ llvm_unreachable("Unhandled case");
+ }
+ auto innerMapInfo = cast<omp::MapInfoOp>(rewriter.clone(*mapInfo));
+ innerMapInfo.setMapTypeAttr(rewriter.getIntegerAttr(
+ rewriter.getIntegerType(64, false),
+ static_cast<
+ std::underlying_type_t<llvm::omp::OpenMPOffloadMappingFlags>>(
+ newMapType)));
+ innerMapInfo.setMapCaptureType(newCaptureType);
+ innerMapInfos.push_back(innerMapInfo.getResult());
+ }
+
+ rewriter.setInsertionPoint(targetOp);
+ auto device = targetOp.getDevice();
+ auto ifExpr = targetOp.getIfExpr();
+ auto deviceAddrVars = targetOp.getHasDeviceAddrVars();
+ auto devicePtrVars = targetOp.getIsDevicePtrVars();
+ auto targetDataOp = rewriter.create<omp::TargetDataOp>(
+ loc, device, ifExpr, outerMapInfos, deviceAddrVars, devicePtrVars);
+ auto taregtDataBlock = rewriter.createBlock(&targetDataOp.getRegion());
+ rewriter.create<mlir::omp::TerminatorOp>(loc);
+ rewriter.setInsertionPointToStart(taregtDataBlock);
+
+ auto newTargetOp = rewriter.create<omp::TargetOp>(
+ targetOp.getLoc(), targetOp.getAllocateVars(),
+ targetOp.getAllocatorVars(), targetOp.getBareAttr(),
+ targetOp.getDependKindsAttr(), targetOp.getDependVars(),
+ targetOp.getDevice(), targetOp.getHasDeviceAddrVars(),
+ targetOp.getHostEvalVars(), targetOp.getIfExpr(),
+ targetOp.getInReductionVars(), targetOp.getInReductionByrefAttr(),
+ targetOp.getInReductionSymsAttr(), targetOp.getIsDevicePtrVars(),
+ innerMapInfos, targetOp.getNowaitAttr(), targetOp.getPrivateVars(),
+ targetOp.getPrivateSymsAttr(), targetOp.getPrivateNeedsBarrierAttr(),
+ targetOp.getThreadLimit(), targetOp.getPrivateMapsAttr());
+ rewriter.inlineRegionBefore(targetOp.getRegion(), newTargetOp.getRegion(),
+ newTargetOp.getRegion().begin());
+
+ rewriter.replaceOp(targetOp, newTargetOp);
+ return SplitTargetResult{cast<omp::TargetOp>(newTargetOp), targetDataOp};
+}
+
+static std::optional<std::tuple<Operation *, bool, bool>>
+getNestedOpToIsolate(omp::TargetOp targetOp) {
+ if (targetOp.getRegion().empty())
+ return std::nullopt;
+ auto *targetBlock = &targetOp.getRegion().front();
+ for (auto &op : *targetBlock) {
+ bool first = &op == &*targetBlock->begin();
+ bool last = op.getNextNode() == targetBlock->getTerminator();
+ if (first && last)
+ return std::nullopt;
+
+ if (isa<omp::TeamsOp, omp::ParallelOp>(&op))
+ return {{&op, first, last}};
+ }
+ return std::nullopt;
+}
+
+struct TempOmpVar {
+ omp::MapInfoOp from, to;
+};
+
+static bool isPtr(Type ty) {
+ return isa<fir::ReferenceType>(ty) || isa<LLVM::LLVMPointerType>(ty);
+}
+
+static Type getPtrTypeForOmp(Type ty) {
+ if (isPtr(ty))
+ return LLVM::LLVMPointerType::get(ty.getContext());
+ else
+ return fir::LLVMPointerType::get(ty);
+}
+
+static TempOmpVar allocateTempOmpVar(Location loc, Type ty,
+ RewriterBase &rewriter) {
+ MLIRContext &ctx = *ty.getContext();
+ Value alloc;
+ Type allocType;
+ auto llvmPtrTy = LLVM::LLVMPointerType::get(&ctx);
+ if (isPtr(ty)) {
+ Type intTy = rewriter.getI32Type();
+ auto one = rewriter.create<LLVM::ConstantOp>(loc, intTy, 1);
+ allocType = llvmPtrTy;
+ alloc = rewriter.create<LLVM::AllocaOp>(loc, llvmPtrTy, allocType, one);
+ allocType = intTy;
+ } else {
+ allocType = ty;
+ alloc = rewriter.create<fir::AllocaOp>(loc, allocType);
+ }
+ auto getMapInfo = [&](uint64_t mappingFlags, const char *name) {
+ return rewriter.create<omp::MapInfoOp>(
+ loc, alloc.getType(), alloc, TypeAttr::get(allocType),
+ rewriter.getIntegerAttr(rewriter.getIntegerType(64, /*isSigned=*/false),
+ mappingFlags),
+ rewriter.getAttr<omp::VariableCaptureKindAttr>(
+ omp::VariableCaptureKind::ByRef),
+ /*varPtrPtr=*/Value{},
+ /*members=*/SmallVector<Value>{},
+ /*member_index=*/mlir::ArrayAttr{},
+ /*bounds=*/ValueRange(),
+ /*mapperId=*/mlir::FlatSymbolRefAttr(),
+ /*name=*/rewriter.getStringAttr(name), rewriter.getBoolAttr(false));
+ };
+ uint64_t mapFrom =
+ static_cast<std::underlying_type_t<llvm::omp::OpenMPOffloadMappingFlags>>(
+ llvm::omp::OpenMPOffloadMappingFlags::OMP_MAP_FROM);
+ uint64_t mapTo =
+ static_cast<std::underlying_type_t<llvm::omp::OpenMPOffloadMappingFlags>>(
+ llvm::omp::OpenMPOffloadMappingFlags::OMP_MAP_TO);
+ auto mapInfoFrom = getMapInfo(mapFrom, "__flang_workdistribute_from");
+ auto mapInfoTo = getMapInfo(mapTo, "__flang_workdistribute_to");
+ return TempOmpVar{mapInfoFrom, mapInfoTo};
+};
+
+static bool usedOutsideSplit(Value v, Operation *split) {
+ if (!split)
+ return false;
+ auto targetOp = cast<omp::TargetOp>(split->getParentOp());
+ auto *targetBlock = &targetOp.getRegion().front();
+ for (auto *user : v.getUsers()) {
+ while (user->getBlock() != targetBlock) {
+ user = user->getParentOp();
+ }
+ if (!user->isBeforeInBlock(split))
+ return true;
+ }
+ return false;
+};
+
+static bool isRecomputableAfterFission(Operation *op, Operation *splitBefore) {
+ if (isa<fir::DeclareOp>(op))
+ return true;
+
+ llvm::SmallVector<MemoryEffects::EffectInstance> effects;
+ MemoryEffectOpInterface interface = dyn_cast<MemoryEffectOpInterface>(op);
+ if (!interface) {
+ return false;
+ }
+ interface.getEffects(effects);
+ if (effects.empty())
+ return true;
+ return false;
+}
+
+...
[truncated]
|
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| // omp.target { teams { workdistribute { ... } } } is well formed | ||
| // and fails for function calls that don't have lowering implemented yet. | ||
| static bool | ||
| VerifyTargetTeamsWorkdistribute(omp::WorkdistributeOp workdistribute) { |
There was a problem hiding this comment.
Is the capitalization intended? I thought the coding style is uncapitalized for functions (also applies to other functions in the file)
Suggested change
| VerifyTargetTeamsWorkdistribute(omp::WorkdistributeOp workdistribute) { | |
| verifyTargetTeamsWorkdistribute(omp::WorkdistributeOp workdistribute) { |
There was a problem hiding this comment.
Thanks for feedback. This was unintentional typo. Fixed for all the function names aswell.
| if (isa<fir::DeclareOp>(op)) | ||
| return true; | ||
|
|
||
| llvm::SmallVector<MemoryEffects::EffectInstance> effects; |
There was a problem hiding this comment.
Should we reuse isMemoryEffectFree() here?
| namespace { | ||
|
|
||
| // The isRuntimeCall function is a utility designed to determine | ||
| // if a given operation is a call to a Fortran-specific runtime function. |
There was a problem hiding this comment.
Should the comments here be doc comments? (/// instead of //) (also applies to other functions).
There was a problem hiding this comment.
Was unaware of this comment style. Fixed this for entire pass.
| // } | ||
| // } | ||
| // } | ||
|
|
| } | ||
| if (shouldParallelize(&op)) { | ||
| emitError(loc, "teams has parallelize ops before first workdistribute\n"); | ||
| return false; |
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I think this is an error that cannot be recovered from so maybe this function should return ErrorOr<bool> or something like that to correctly catch the error in the Pass and signalPassFailure
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This shouldn't be an error. It's legal to have intervening code in teams before workdistribute.
There was a problem hiding this comment.
As per spec "The workdistribute construct must be a closely nested construct inside a teams construct"
AFAIU, no other parallelizable operations could be present between teams and workdistribute.
There was a problem hiding this comment.
Closely nested construct means that there shouldn't be any construct nested between teams and workdistribute, not that there can't be any construct in teams other than distribute.
teams {
parallel { // wrong
workdistribute {}
}
}
teams {
parallel { // ok
}
workdistribute {
}
}
| auto teams = dyn_cast<omp::TeamsOp>(workdistribute->getParentOp()); | ||
| if (!teams) { | ||
| emitError(loc, "workdistribute not nested in teams\n"); | ||
| return false; |
There was a problem hiding this comment.
Same as the other ErrorOr<bool> comment.
There was a problem hiding this comment.
Thanks again for feedback on this. Used FailureOr<> in the pass to emit errors and fail.
| return false; | ||
| } else { | ||
| workdistribute.emitError() << "Non-runtime fir.call lowering not " | ||
| "supported in workdistribute yet."; |
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The error message says not supported yet, but I think this is something that should never happen if our pipeline is sound. (workdistribute should never have non-rt calls in it)
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Fixed it. We already detect any user-defined functions in semantics checks. Test : workdistribute01.f90
| }; | ||
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| // moveToHost method clones all the ops from target region outside of it. | ||
| // It hoists runtime functions and replaces them with omp vesions. |
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replaces them with omp vesions
Typo and also is this description outdated? For assign we seem to codegen an assign implementation and not replace with an omp version of the runtime function.
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Updated description.
For Array to array assignments, __FortranAAsign is replaced with omp.target_memcpy.
For scalar assignment to array, workdistributeRuntimeCallLower handles lowering of __FortranAAsign .
kparzysz
reviewed
Oct 8, 2025
| return false; | ||
| return *unordered; | ||
| } | ||
| // We cannot parallise anything else. |
| } | ||
| if (shouldParallelize(&op)) { | ||
| emitError(loc, "teams has parallelize ops before first workdistribute\n"); | ||
| return false; |
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This shouldn't be an error. It's legal to have intervening code in teams before workdistribute.
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| omp::TargetOp targetOp; | ||
| // Get the target op parent of teams | ||
| targetOp = dyn_cast<omp::TargetOp>(teams->getParentOp()); |
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Unused.
Also, teams doesn't have to be nested inside a target, it can be a top-level construct.
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Removed this unused code. fissionWorkdistribute shouldn't be dependent on parent target op to teams. Thanks.
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| // A() | ||
| // omp.teams { | ||
| // omp.workdistribute { | ||
| // B() | ||
| // } | ||
| // } | ||
| // C() | ||
| // omp.teams { | ||
| // omp.workdistribute { | ||
| // D() | ||
| // } | ||
| // } | ||
| // E() |
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I'm not sure if splitting teams is the right thing to do. Even then, it should be an optimization rather than a part of lowering. We should be able to generate code for workdistribute without splitting teams.
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I spoke with Michael and it seems that this is necessary for correctness. If that's the case, disregard my previous comment.
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This implementation of splitting teams is by following the paper "Automatic Parallelization and OpenMP Offloadingof Fortran Array Notation"
AFAIU, in OpenMP, every for loop that's intended to be parallelized, would be under its own teams construct like "teams parallel distribute for".
Single teams could have multiple do_loops like below and need to rethink strategy on how to handle such scenarios without splitting teams.
teams {
workdistribute {
fir.do_loop unordered {}
fir.do_loop unordered {}
}
}
ivanradanov
reviewed
Oct 8, 2025
| } | ||
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| // This is the single source of truth about whether we should parallelize an | ||
| // operation nested in an omp.workdistribute region. |
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Maybe add a comment that this parallelize here refers to the divide into units of work from the standard.
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This PR introduces a new pass "lower-workdistribute"
Fortran array statements are lowered to fir as fir.do_loop unordered. "lower-workdistribute" pass works mainly on identifying "fir.do_loop unordered" that is nested in target{teams{workdistribute{fir.do_loop unordered}}} and lowers it to target{teams{parallel{wsloop{loop_nest}}}}. It hoists all the other ops outside target region. Relaces heap allocation on target with omp.target_allocmem and deallocation with omp.target_freemem from host. Also replaces runtime function "Assign" with omp.target_memcpy from host.
This pass implements following rewrites and optimisations:
The work in this PR is C-P and updated from @ivanradanov commits from coexecute implementation:
flang_workdistribute_iwomp_2024
Paper related to this work by @ivanradanov "Automatic Parallelization and OpenMP Offloadingof Fortran Array Notation"