Files
clang-p2996/mlir/lib/Analysis/TopologicalSortUtils.cpp
Christian Ulmann b00e0c1671 [MLIR][Analysis] Consolidate topological sort utilities (#92563)
This PR attempts to consolidate the different topological sort utilities
into one place. It adds them to the analysis folder because the
`SliceAnalysis` uses some of these.

There are now two different sorting strategies: 
1. Sort only according to SSA use-def chains
2. Sort while taking regions into account. This requires a much more
elaborate traversal and cannot be applied on graph regions that easily.

This additionally reimplements the region aware topological sorting
because the previous implementation had an exponential space complexity.

I'm open to suggestions on how to combine this further or how to fuse
the test passes.
2024-05-22 08:48:10 +02:00

286 lines
9.7 KiB
C++

//===- TopologicalSortUtils.cpp - Topological sort utilities --------------===//
//
// 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
//
//===----------------------------------------------------------------------===//
#include "mlir/Analysis/TopologicalSortUtils.h"
#include "mlir/IR/Block.h"
#include "mlir/IR/OpDefinition.h"
#include "mlir/IR/RegionGraphTraits.h"
#include "llvm/ADT/PostOrderIterator.h"
#include "llvm/ADT/SetVector.h"
using namespace mlir;
/// Return `true` if the given operation is ready to be scheduled.
static bool isOpReady(Operation *op, DenseSet<Operation *> &unscheduledOps,
function_ref<bool(Value, Operation *)> isOperandReady) {
// An operation is ready to be scheduled if all its operands are ready. An
// operation is ready if:
const auto isReady = [&](Value value) {
// - the user-provided callback marks it as ready,
if (isOperandReady && isOperandReady(value, op))
return true;
Operation *parent = value.getDefiningOp();
// - it is a block argument,
if (!parent)
return true;
// - or it is not defined by an unscheduled op (and also not nested within
// an unscheduled op).
do {
// Stop traversal when op under examination is reached.
if (parent == op)
return true;
if (unscheduledOps.contains(parent))
return false;
} while ((parent = parent->getParentOp()));
// No unscheduled op found.
return true;
};
// An operation is recursively ready to be scheduled of it and its nested
// operations are ready.
WalkResult readyToSchedule = op->walk([&](Operation *nestedOp) {
return llvm::all_of(nestedOp->getOperands(),
[&](Value operand) { return isReady(operand); })
? WalkResult::advance()
: WalkResult::interrupt();
});
return !readyToSchedule.wasInterrupted();
}
bool mlir::sortTopologically(
Block *block, llvm::iterator_range<Block::iterator> ops,
function_ref<bool(Value, Operation *)> isOperandReady) {
if (ops.empty())
return true;
// The set of operations that have not yet been scheduled.
DenseSet<Operation *> unscheduledOps;
// Mark all operations as unscheduled.
for (Operation &op : ops)
unscheduledOps.insert(&op);
Block::iterator nextScheduledOp = ops.begin();
Block::iterator end = ops.end();
bool allOpsScheduled = true;
while (!unscheduledOps.empty()) {
bool scheduledAtLeastOnce = false;
// Loop over the ops that are not sorted yet, try to find the ones "ready",
// i.e. the ones for which there aren't any operand produced by an op in the
// set, and "schedule" it (move it before the `nextScheduledOp`).
for (Operation &op :
llvm::make_early_inc_range(llvm::make_range(nextScheduledOp, end))) {
if (!isOpReady(&op, unscheduledOps, isOperandReady))
continue;
// Schedule the operation by moving it to the start.
unscheduledOps.erase(&op);
op.moveBefore(block, nextScheduledOp);
scheduledAtLeastOnce = true;
// Move the iterator forward if we schedule the operation at the front.
if (&op == &*nextScheduledOp)
++nextScheduledOp;
}
// If no operations were scheduled, give up and advance the iterator.
if (!scheduledAtLeastOnce) {
allOpsScheduled = false;
unscheduledOps.erase(&*nextScheduledOp);
++nextScheduledOp;
}
}
return allOpsScheduled;
}
bool mlir::sortTopologically(
Block *block, function_ref<bool(Value, Operation *)> isOperandReady) {
if (block->empty())
return true;
if (block->back().hasTrait<OpTrait::IsTerminator>())
return sortTopologically(block, block->without_terminator(),
isOperandReady);
return sortTopologically(block, *block, isOperandReady);
}
bool mlir::computeTopologicalSorting(
MutableArrayRef<Operation *> ops,
function_ref<bool(Value, Operation *)> isOperandReady) {
if (ops.empty())
return true;
// The set of operations that have not yet been scheduled.
DenseSet<Operation *> unscheduledOps;
// Mark all operations as unscheduled.
for (Operation *op : ops)
unscheduledOps.insert(op);
unsigned nextScheduledOp = 0;
bool allOpsScheduled = true;
while (!unscheduledOps.empty()) {
bool scheduledAtLeastOnce = false;
// Loop over the ops that are not sorted yet, try to find the ones "ready",
// i.e. the ones for which there aren't any operand produced by an op in the
// set, and "schedule" it (swap it with the op at `nextScheduledOp`).
for (unsigned i = nextScheduledOp; i < ops.size(); ++i) {
if (!isOpReady(ops[i], unscheduledOps, isOperandReady))
continue;
// Schedule the operation by moving it to the start.
unscheduledOps.erase(ops[i]);
std::swap(ops[i], ops[nextScheduledOp]);
scheduledAtLeastOnce = true;
++nextScheduledOp;
}
// If no operations were scheduled, just schedule the first op and continue.
if (!scheduledAtLeastOnce) {
allOpsScheduled = false;
unscheduledOps.erase(ops[nextScheduledOp++]);
}
}
return allOpsScheduled;
}
SetVector<Block *> mlir::getBlocksSortedByDominance(Region &region) {
// For each block that has not been visited yet (i.e. that has no
// predecessors), add it to the list as well as its successors.
SetVector<Block *> blocks;
for (Block &b : region) {
if (blocks.count(&b) == 0) {
llvm::ReversePostOrderTraversal<Block *> traversal(&b);
blocks.insert(traversal.begin(), traversal.end());
}
}
assert(blocks.size() == region.getBlocks().size() &&
"some blocks are not sorted");
return blocks;
}
namespace {
class TopoSortHelper {
public:
explicit TopoSortHelper(const SetVector<Operation *> &toSort)
: toSort(toSort) {}
/// Executes the topological sort of the operations this instance was
/// constructed with. This function will destroy the internal state of the
/// instance.
SetVector<Operation *> sort() {
if (toSort.size() <= 1) {
// Note: Creates a copy on purpose.
return toSort;
}
// First, find the root region to start the traversal through the IR. This
// additionally enriches the internal caches with all relevant ancestor
// regions and blocks.
Region *rootRegion = findCommonAncestorRegion();
assert(rootRegion && "expected all ops to have a common ancestor");
// Sort all elements in `toSort` by traversing the IR in the appropriate
// order.
SetVector<Operation *> result = topoSortRegion(*rootRegion);
assert(result.size() == toSort.size() &&
"expected all operations to be present in the result");
return result;
}
private:
/// Computes the closest common ancestor region of all operations in `toSort`.
Region *findCommonAncestorRegion() {
// Map to count the number of times a region was encountered.
DenseMap<Region *, size_t> regionCounts;
size_t expectedCount = toSort.size();
// Walk the region tree for each operation towards the root and add to the
// region count.
Region *res = nullptr;
for (Operation *op : toSort) {
Region *current = op->getParentRegion();
// Store the block as an ancestor block.
ancestorBlocks.insert(op->getBlock());
while (current) {
// Insert or update the count and compare it.
if (++regionCounts[current] == expectedCount) {
res = current;
break;
}
ancestorBlocks.insert(current->getParentOp()->getBlock());
current = current->getParentRegion();
}
}
auto firstRange = llvm::make_first_range(regionCounts);
ancestorRegions.insert(firstRange.begin(), firstRange.end());
return res;
}
/// Performs the dominance respecting IR walk to collect the topological order
/// of the operation to sort.
SetVector<Operation *> topoSortRegion(Region &rootRegion) {
using StackT = PointerUnion<Region *, Block *, Operation *>;
SetVector<Operation *> result;
// Stack that stores the different IR constructs to traverse.
SmallVector<StackT> stack;
stack.push_back(&rootRegion);
// Traverse the IR in a dominance respecting pre-order walk.
while (!stack.empty()) {
StackT current = stack.pop_back_val();
if (auto *region = dyn_cast<Region *>(current)) {
// A region's blocks need to be traversed in dominance order.
SetVector<Block *> sortedBlocks = getBlocksSortedByDominance(*region);
for (Block *block : llvm::reverse(sortedBlocks)) {
// Only add blocks to the stack that are ancestors of the operations
// to sort.
if (ancestorBlocks.contains(block))
stack.push_back(block);
}
continue;
}
if (auto *block = dyn_cast<Block *>(current)) {
// Add all of the blocks operations to the stack.
for (Operation &op : llvm::reverse(*block))
stack.push_back(&op);
continue;
}
auto *op = cast<Operation *>(current);
if (toSort.contains(op))
result.insert(op);
// Add all the subregions that are ancestors of the operations to sort.
for (Region &subRegion : op->getRegions())
if (ancestorRegions.contains(&subRegion))
stack.push_back(&subRegion);
}
return result;
}
/// Operations to sort.
const SetVector<Operation *> &toSort;
/// Set containing all the ancestor regions of the operations to sort.
DenseSet<Region *> ancestorRegions;
/// Set containing all the ancestor blocks of the operations to sort.
DenseSet<Block *> ancestorBlocks;
};
} // namespace
SetVector<Operation *>
mlir::topologicalSort(const SetVector<Operation *> &toSort) {
return TopoSortHelper(toSort).sort();
}