627 lines
26 KiB
C
627 lines
26 KiB
C
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//===- GIMatchTree.h - A decision tree to match GIMatchDag's --------------===//
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//
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// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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//
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//===----------------------------------------------------------------------===//
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#ifndef LLVM_UTILS_TABLEGEN_GIMATCHTREE_H
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#define LLVM_UTILS_TABLEGEN_GIMATCHTREE_H
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#include "GIMatchDag.h"
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#include "llvm/ADT/BitVector.h"
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namespace llvm {
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class raw_ostream;
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class GIMatchTreeBuilder;
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class GIMatchTreePartitioner;
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/// Describes the binding of a variable to the matched MIR
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class GIMatchTreeVariableBinding {
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/// The name of the variable described by this binding.
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StringRef Name;
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// The matched instruction it is bound to.
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unsigned InstrID;
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// The matched operand (if appropriate) it is bound to.
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Optional<unsigned> OpIdx;
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public:
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GIMatchTreeVariableBinding(StringRef Name, unsigned InstrID,
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Optional<unsigned> OpIdx = None)
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: Name(Name), InstrID(InstrID), OpIdx(OpIdx) {}
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bool isInstr() const { return !OpIdx.hasValue(); }
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StringRef getName() const { return Name; }
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unsigned getInstrID() const { return InstrID; }
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unsigned getOpIdx() const {
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assert(OpIdx.hasValue() && "Is not an operand binding");
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return *OpIdx;
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}
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};
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/// Associates a matchable with a leaf of the decision tree.
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class GIMatchTreeLeafInfo {
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public:
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using const_var_binding_iterator =
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std::vector<GIMatchTreeVariableBinding>::const_iterator;
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using UntestedPredicatesTy = SmallVector<const GIMatchDagPredicate *, 1>;
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using const_untested_predicates_iterator = UntestedPredicatesTy::const_iterator;
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protected:
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/// A name for the matchable. This is primarily for debugging.
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StringRef Name;
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/// Where rules have multiple roots, this is which root we're starting from.
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unsigned RootIdx;
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/// Opaque data the caller of the tree building code understands.
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void *Data;
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/// Has the decision tree covered every edge traversal? If it hasn't then this
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/// is an unrecoverable error indicating there's something wrong with the
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/// partitioners.
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bool IsFullyTraversed;
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/// Has the decision tree covered every predicate test? If it has, then
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/// subsequent matchables on the same leaf are unreachable. If it hasn't, the
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/// code that requested the GIMatchTree is responsible for finishing off any
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/// remaining predicates.
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bool IsFullyTested;
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/// The variable bindings associated with this leaf so far.
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std::vector<GIMatchTreeVariableBinding> VarBindings;
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/// Any predicates left untested by the time we reach this leaf.
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UntestedPredicatesTy UntestedPredicates;
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public:
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GIMatchTreeLeafInfo() { llvm_unreachable("Cannot default-construct"); }
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GIMatchTreeLeafInfo(StringRef Name, unsigned RootIdx, void *Data)
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: Name(Name), RootIdx(RootIdx), Data(Data), IsFullyTraversed(false),
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IsFullyTested(false) {}
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StringRef getName() const { return Name; }
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unsigned getRootIdx() const { return RootIdx; }
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template <class Ty> Ty *getTargetData() const {
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return static_cast<Ty *>(Data);
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}
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bool isFullyTraversed() const { return IsFullyTraversed; }
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void setIsFullyTraversed(bool V) { IsFullyTraversed = V; }
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bool isFullyTested() const { return IsFullyTested; }
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void setIsFullyTested(bool V) { IsFullyTested = V; }
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void bindInstrVariable(StringRef Name, unsigned InstrID) {
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VarBindings.emplace_back(Name, InstrID);
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}
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void bindOperandVariable(StringRef Name, unsigned InstrID, unsigned OpIdx) {
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VarBindings.emplace_back(Name, InstrID, OpIdx);
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}
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const_var_binding_iterator var_bindings_begin() const {
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return VarBindings.begin();
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}
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const_var_binding_iterator var_bindings_end() const {
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return VarBindings.end();
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}
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iterator_range<const_var_binding_iterator> var_bindings() const {
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return make_range(VarBindings.begin(), VarBindings.end());
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}
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iterator_range<const_untested_predicates_iterator> untested_predicates() const {
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return make_range(UntestedPredicates.begin(), UntestedPredicates.end());
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}
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void addUntestedPredicate(const GIMatchDagPredicate *P) {
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UntestedPredicates.push_back(P);
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}
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};
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/// The nodes of a decision tree used to perform the match.
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/// This will be used to generate the C++ code or state machine equivalent.
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///
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/// It should be noted that some nodes of this tree (most notably nodes handling
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/// def -> use edges) will need to iterate over several possible matches. As
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/// such, code generated from this will sometimes need to support backtracking.
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class GIMatchTree {
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using LeafVector = std::vector<GIMatchTreeLeafInfo>;
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/// The partitioner that has been chosen for this node. This may be nullptr if
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/// a partitioner hasn't been chosen yet or if the node is a leaf.
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std::unique_ptr<GIMatchTreePartitioner> Partitioner;
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/// All the leaves that are possible for this node of the tree.
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/// Note: This should be emptied after the tree is built when there are
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/// children but this currently isn't done to aid debuggability of the DOT
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/// graph for the decision tree.
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LeafVector PossibleLeaves;
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/// The children of this node. The index into this array must match the index
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/// chosen by the partitioner.
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std::vector<GIMatchTree> Children;
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void writeDOTGraphNode(raw_ostream &OS) const;
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void writeDOTGraphEdges(raw_ostream &OS) const;
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public:
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void writeDOTGraph(raw_ostream &OS) const;
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void setNumChildren(unsigned Num) { Children.resize(Num); }
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void addPossibleLeaf(const GIMatchTreeLeafInfo &V, bool IsFullyTraversed,
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bool IsFullyTested) {
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PossibleLeaves.push_back(V);
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PossibleLeaves.back().setIsFullyTraversed(IsFullyTraversed);
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PossibleLeaves.back().setIsFullyTested(IsFullyTested);
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}
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void dropLeavesAfter(size_t Length) {
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if (PossibleLeaves.size() > Length)
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PossibleLeaves.resize(Length);
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}
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void setPartitioner(std::unique_ptr<GIMatchTreePartitioner> &&V) {
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Partitioner = std::move(V);
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}
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GIMatchTreePartitioner *getPartitioner() const { return Partitioner.get(); }
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std::vector<GIMatchTree>::iterator children_begin() {
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return Children.begin();
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}
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std::vector<GIMatchTree>::iterator children_end() { return Children.end(); }
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iterator_range<std::vector<GIMatchTree>::iterator> children() {
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return make_range(children_begin(), children_end());
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}
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std::vector<GIMatchTree>::const_iterator children_begin() const {
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return Children.begin();
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}
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std::vector<GIMatchTree>::const_iterator children_end() const {
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return Children.end();
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}
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iterator_range<std::vector<GIMatchTree>::const_iterator> children() const {
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return make_range(children_begin(), children_end());
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}
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LeafVector::const_iterator possible_leaves_begin() const {
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return PossibleLeaves.begin();
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}
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LeafVector::const_iterator possible_leaves_end() const {
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return PossibleLeaves.end();
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}
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iterator_range<LeafVector::const_iterator>
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possible_leaves() const {
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return make_range(possible_leaves_begin(), possible_leaves_end());
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}
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LeafVector::iterator possible_leaves_begin() {
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return PossibleLeaves.begin();
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}
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LeafVector::iterator possible_leaves_end() {
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return PossibleLeaves.end();
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}
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iterator_range<LeafVector::iterator> possible_leaves() {
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return make_range(possible_leaves_begin(), possible_leaves_end());
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}
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};
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/// Record information that is known about the instruction bound to this ID and
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/// GIMatchDagInstrNode. Every rule gets its own set of
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/// GIMatchTreeInstrInfo to bind the shared IDs to an instr node in its
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/// DAG.
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///
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/// For example, if we know that there are 3 operands. We can record it here to
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/// elide duplicate checks.
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class GIMatchTreeInstrInfo {
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/// The instruction ID for the matched instruction.
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unsigned ID;
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/// The corresponding instruction node in the MatchDAG.
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const GIMatchDagInstr *InstrNode;
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public:
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GIMatchTreeInstrInfo(unsigned ID, const GIMatchDagInstr *InstrNode)
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: ID(ID), InstrNode(InstrNode) {}
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unsigned getID() const { return ID; }
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const GIMatchDagInstr *getInstrNode() const { return InstrNode; }
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};
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/// Record information that is known about the operand bound to this ID, OpIdx,
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/// and GIMatchDagInstrNode. Every rule gets its own set of
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/// GIMatchTreeOperandInfo to bind the shared IDs to an operand of an
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/// instr node from its DAG.
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///
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/// For example, if we know that there the operand is a register. We can record
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/// it here to elide duplicate checks.
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class GIMatchTreeOperandInfo {
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/// The corresponding instruction node in the MatchDAG that the operand
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/// belongs to.
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const GIMatchDagInstr *InstrNode;
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unsigned OpIdx;
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public:
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GIMatchTreeOperandInfo(const GIMatchDagInstr *InstrNode, unsigned OpIdx)
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: InstrNode(InstrNode), OpIdx(OpIdx) {}
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const GIMatchDagInstr *getInstrNode() const { return InstrNode; }
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unsigned getOpIdx() const { return OpIdx; }
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};
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/// Represent a leaf of the match tree and any working data we need to build the
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/// tree.
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///
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/// It's important to note that each rule can have multiple
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/// GIMatchTreeBuilderLeafInfo's since the partitioners do not always partition
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/// into mutually-exclusive partitions. For example:
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/// R1: (FOO ..., ...)
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/// R2: (oneof(FOO, BAR) ..., ...)
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/// will partition by opcode into two partitions FOO=>[R1, R2], and BAR=>[R2]
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///
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/// As an optimization, all instructions, edges, and predicates in the DAGs are
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/// numbered and tracked in BitVectors. As such, the GIMatchDAG must not be
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/// modified once construction of the tree has begun.
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class GIMatchTreeBuilderLeafInfo {
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protected:
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GIMatchTreeBuilder &Builder;
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GIMatchTreeLeafInfo Info;
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const GIMatchDag &MatchDag;
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/// The association between GIMatchDagInstr* and GIMatchTreeInstrInfo.
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/// The primary reason for this members existence is to allow the use of
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/// InstrIDToInfo.lookup() since that requires that the value is
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/// default-constructible.
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DenseMap<const GIMatchDagInstr *, GIMatchTreeInstrInfo> InstrNodeToInfo;
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/// The instruction information for a given ID in the context of this
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/// particular leaf.
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DenseMap<unsigned, GIMatchTreeInstrInfo *> InstrIDToInfo;
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/// The operand information for a given ID and OpIdx in the context of this
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/// particular leaf.
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DenseMap<std::pair<unsigned, unsigned>, GIMatchTreeOperandInfo>
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OperandIDToInfo;
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public:
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/// The remaining instrs/edges/predicates to visit
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BitVector RemainingInstrNodes;
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BitVector RemainingEdges;
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BitVector RemainingPredicates;
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// The remaining predicate dependencies for each predicate
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std::vector<BitVector> UnsatisfiedPredDepsForPred;
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/// The edges/predicates we can visit as a result of the declare*() calls we
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/// have already made. We don't need an instrs version since edges imply the
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/// instr.
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BitVector TraversableEdges;
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BitVector TestablePredicates;
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/// Map predicates from the DAG to their position in the DAG predicate
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/// iterators.
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DenseMap<GIMatchDagPredicate *, unsigned> PredicateIDs;
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/// Map predicate dependency edges from the DAG to their position in the DAG
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/// predicate dependency iterators.
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DenseMap<GIMatchDagPredicateDependencyEdge *, unsigned> PredicateDepIDs;
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public:
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GIMatchTreeBuilderLeafInfo(GIMatchTreeBuilder &Builder, StringRef Name,
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unsigned RootIdx, const GIMatchDag &MatchDag,
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void *Data);
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StringRef getName() const { return Info.getName(); }
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GIMatchTreeLeafInfo &getInfo() { return Info; }
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const GIMatchTreeLeafInfo &getInfo() const { return Info; }
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const GIMatchDag &getMatchDag() const { return MatchDag; }
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unsigned getRootIdx() const { return Info.getRootIdx(); }
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/// Has this DAG been fully traversed. This must be true by the time the tree
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/// builder finishes.
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bool isFullyTraversed() const {
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// We don't need UnsatisfiedPredDepsForPred because RemainingPredicates
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// can't be all-zero without satisfying all the dependencies. The same is
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// almost true for Edges and Instrs but it's possible to have Instrs without
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// Edges.
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return RemainingInstrNodes.none() && RemainingEdges.none();
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}
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/// Has this DAG been fully tested. This hould be true by the time the tree
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/// builder finishes but clients can finish any untested predicates left over
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/// if it's not true.
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bool isFullyTested() const {
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// We don't need UnsatisfiedPredDepsForPred because RemainingPredicates
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// can't be all-zero without satisfying all the dependencies. The same is
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// almost true for Edges and Instrs but it's possible to have Instrs without
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// Edges.
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return RemainingInstrNodes.none() && RemainingEdges.none() &&
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RemainingPredicates.none();
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}
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const GIMatchDagInstr *getInstr(unsigned Idx) const {
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return *(MatchDag.instr_nodes_begin() + Idx);
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}
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const GIMatchDagEdge *getEdge(unsigned Idx) const {
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return *(MatchDag.edges_begin() + Idx);
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}
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GIMatchDagEdge *getEdge(unsigned Idx) {
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return *(MatchDag.edges_begin() + Idx);
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}
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const GIMatchDagPredicate *getPredicate(unsigned Idx) const {
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return *(MatchDag.predicates_begin() + Idx);
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}
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iterator_range<llvm::BitVector::const_set_bits_iterator>
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untested_instrs() const {
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return RemainingInstrNodes.set_bits();
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}
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iterator_range<llvm::BitVector::const_set_bits_iterator>
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untested_edges() const {
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return RemainingEdges.set_bits();
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}
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iterator_range<llvm::BitVector::const_set_bits_iterator>
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untested_predicates() const {
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return RemainingPredicates.set_bits();
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}
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/// Bind an instr node to the given ID and clear any blocking dependencies
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/// that were waiting for it.
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void declareInstr(const GIMatchDagInstr *Instr, unsigned ID);
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/// Bind an operand to the given ID and OpIdx and clear any blocking
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/// dependencies that were waiting for it.
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void declareOperand(unsigned InstrID, unsigned OpIdx);
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GIMatchTreeInstrInfo *getInstrInfo(unsigned ID) const {
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return InstrIDToInfo.lookup(ID);
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}
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void dump(raw_ostream &OS) const {
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OS << "Leaf " << getName() << " for root #" << getRootIdx() << "\n";
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MatchDag.print(OS);
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for (const auto &I : InstrIDToInfo)
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OS << "Declared Instr #" << I.first << "\n";
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for (const auto &I : OperandIDToInfo)
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OS << "Declared Instr #" << I.first.first << ", Op #" << I.first.second
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<< "\n";
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OS << RemainingInstrNodes.count() << " untested instrs of "
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<< RemainingInstrNodes.size() << "\n";
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OS << RemainingEdges.count() << " untested edges of "
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<< RemainingEdges.size() << "\n";
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OS << RemainingPredicates.count() << " untested predicates of "
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<< RemainingPredicates.size() << "\n";
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OS << TraversableEdges.count() << " edges could be traversed\n";
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OS << TestablePredicates.count() << " predicates could be tested\n";
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}
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};
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/// The tree builder has a fairly tough job. It's purpose is to merge all the
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/// DAGs from the ruleset into a decision tree that walks all of them
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/// simultaneously and identifies the rule that was matched. In addition to
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/// that, it also needs to find the most efficient order to make decisions
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/// without violating any dependencies and ensure that every DAG covers every
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/// instr/edge/predicate.
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class GIMatchTreeBuilder {
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public:
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using LeafVec = std::vector<GIMatchTreeBuilderLeafInfo>;
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protected:
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/// The leaves that the resulting decision tree will distinguish.
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LeafVec Leaves;
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/// The tree node being constructed.
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GIMatchTree *TreeNode;
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/// The builders for each subtree resulting from the current decision.
|
||
|
std::vector<GIMatchTreeBuilder> SubtreeBuilders;
|
||
|
/// The possible partitioners we could apply right now.
|
||
|
std::vector<std::unique_ptr<GIMatchTreePartitioner>> Partitioners;
|
||
|
/// The next instruction ID to allocate when requested by the chosen
|
||
|
/// Partitioner.
|
||
|
unsigned NextInstrID;
|
||
|
|
||
|
/// Use any context we have stored to cull partitioners that only test things
|
||
|
/// we already know. At the time of writing, there's no need to do anything
|
||
|
/// here but it will become important once, for example, there is a
|
||
|
/// num-operands and an opcode partitioner. This is because applying an opcode
|
||
|
/// partitioner (usually) makes the number of operands known which makes
|
||
|
/// additional checking pointless.
|
||
|
void filterRedundantPartitioners();
|
||
|
|
||
|
/// Evaluate the available partioners and select the best one at the moment.
|
||
|
void evaluatePartitioners();
|
||
|
|
||
|
/// Construct the current tree node.
|
||
|
void runStep();
|
||
|
|
||
|
public:
|
||
|
GIMatchTreeBuilder(unsigned NextInstrID) : NextInstrID(NextInstrID) {}
|
||
|
GIMatchTreeBuilder(GIMatchTree *TreeNode, unsigned NextInstrID)
|
||
|
: TreeNode(TreeNode), NextInstrID(NextInstrID) {}
|
||
|
|
||
|
void addLeaf(StringRef Name, unsigned RootIdx, const GIMatchDag &MatchDag,
|
||
|
void *Data) {
|
||
|
Leaves.emplace_back(*this, Name, RootIdx, MatchDag, Data);
|
||
|
}
|
||
|
void addLeaf(const GIMatchTreeBuilderLeafInfo &L) { Leaves.push_back(L); }
|
||
|
void addPartitioner(std::unique_ptr<GIMatchTreePartitioner> P) {
|
||
|
Partitioners.push_back(std::move(P));
|
||
|
}
|
||
|
void addPartitionersForInstr(unsigned InstrIdx);
|
||
|
void addPartitionersForOperand(unsigned InstrID, unsigned OpIdx);
|
||
|
|
||
|
LeafVec &getPossibleLeaves() { return Leaves; }
|
||
|
|
||
|
unsigned allocInstrID() { return NextInstrID++; }
|
||
|
|
||
|
/// Construct the decision tree.
|
||
|
std::unique_ptr<GIMatchTree> run();
|
||
|
};
|
||
|
|
||
|
/// Partitioners are the core of the tree builder and are unfortunately rather
|
||
|
/// tricky to write.
|
||
|
class GIMatchTreePartitioner {
|
||
|
protected:
|
||
|
/// The partitions resulting from applying the partitioner to the possible
|
||
|
/// leaves. The keys must be consecutive integers starting from 0. This can
|
||
|
/// lead to some unfortunate situations where partitioners test a predicate
|
||
|
/// and use 0 for success and 1 for failure if the ruleset encounters a
|
||
|
/// success case first but is necessary to assign the partition to one of the
|
||
|
/// tree nodes children. As a result, you usually need some kind of
|
||
|
/// indirection to map the natural keys (e.g. ptrs/bools) to this linear
|
||
|
/// sequence. The values are a bitvector indicating which leaves belong to
|
||
|
/// this partition.
|
||
|
DenseMap<unsigned, BitVector> Partitions;
|
||
|
|
||
|
public:
|
||
|
virtual ~GIMatchTreePartitioner() {}
|
||
|
virtual std::unique_ptr<GIMatchTreePartitioner> clone() const = 0;
|
||
|
|
||
|
/// Determines which partitions the given leaves belong to. A leaf may belong
|
||
|
/// to multiple partitions in which case it will be duplicated during
|
||
|
/// applyForPartition().
|
||
|
///
|
||
|
/// This function can be rather complicated. A few particular things to be
|
||
|
/// aware of include:
|
||
|
/// * One leaf can be assigned to multiple partitions when there's some
|
||
|
/// ambiguity.
|
||
|
/// * Not all DAG's for the leaves may be able to perform the test. For
|
||
|
/// example, the opcode partitiioner must account for one DAG being a
|
||
|
/// superset of another such as [(ADD ..., ..., ...)], and [(MUL t, ...,
|
||
|
/// ...), (ADD ..., t, ...)]
|
||
|
/// * Attaching meaning to a particular partition index will generally not
|
||
|
/// work due to the '0, 1, ..., n' requirement. You might encounter cases
|
||
|
/// where only partition 1 is seen, leaving a missing 0.
|
||
|
/// * Finding a specific predicate such as the opcode predicate for a specific
|
||
|
/// instruction is non-trivial. It's often O(NumPredicates), leading to
|
||
|
/// O(NumPredicates*NumRules) when applied to the whole ruleset. The good
|
||
|
/// news there is that n is typically small thanks to predicate dependencies
|
||
|
/// limiting how many are testable at once. Also, with opcode and type
|
||
|
/// predicates being so frequent the value of m drops very fast too. It
|
||
|
/// wouldn't be terribly surprising to see a 10k ruleset drop down to an
|
||
|
/// average of 100 leaves per partition after a single opcode partitioner.
|
||
|
/// * The same goes for finding specific edges. The need to traverse them in
|
||
|
/// dependency order dramatically limits the search space at any given
|
||
|
/// moment.
|
||
|
/// * If you need to add a leaf to all partitions, make sure you don't forget
|
||
|
/// them when adding partitions later.
|
||
|
virtual void repartition(GIMatchTreeBuilder::LeafVec &Leaves) = 0;
|
||
|
|
||
|
/// Delegate the leaves for a given partition to the corresponding subbuilder,
|
||
|
/// update any recorded context for this partition (e.g. allocate instr id's
|
||
|
/// for instrs recorder by the current node), and clear any blocking
|
||
|
/// dependencies this partitioner resolved.
|
||
|
virtual void applyForPartition(unsigned PartitionIdx,
|
||
|
GIMatchTreeBuilder &Builder,
|
||
|
GIMatchTreeBuilder &SubBuilder) = 0;
|
||
|
|
||
|
/// Return a BitVector indicating which leaves should be transferred to the
|
||
|
/// specified partition. Note that the same leaf can be indicated for multiple
|
||
|
/// partitions.
|
||
|
BitVector getPossibleLeavesForPartition(unsigned Idx) {
|
||
|
const auto &I = Partitions.find(Idx);
|
||
|
assert(I != Partitions.end() && "Requested non-existant partition");
|
||
|
return I->second;
|
||
|
}
|
||
|
|
||
|
size_t getNumPartitions() const { return Partitions.size(); }
|
||
|
size_t getNumLeavesWithDupes() const {
|
||
|
size_t S = 0;
|
||
|
for (const auto &P : Partitions)
|
||
|
S += P.second.size();
|
||
|
return S;
|
||
|
}
|
||
|
|
||
|
/// Emit a brief description of the partitioner suitable for debug printing or
|
||
|
/// use in a DOT graph.
|
||
|
virtual void emitDescription(raw_ostream &OS) const = 0;
|
||
|
/// Emit a label for the given partition suitable for debug printing or use in
|
||
|
/// a DOT graph.
|
||
|
virtual void emitPartitionName(raw_ostream &OS, unsigned Idx) const = 0;
|
||
|
|
||
|
/// Emit a long description of how the partitioner partitions the leaves.
|
||
|
virtual void emitPartitionResults(raw_ostream &OS) const = 0;
|
||
|
|
||
|
/// Generate code to select between partitions based on the MIR being matched.
|
||
|
/// This is typically a switch statement that picks a partition index.
|
||
|
virtual void generatePartitionSelectorCode(raw_ostream &OS,
|
||
|
StringRef Indent) const = 0;
|
||
|
};
|
||
|
|
||
|
/// Partition according to the opcode of the instruction.
|
||
|
///
|
||
|
/// Numbers CodeGenInstr ptrs for use as partition ID's. One special partition,
|
||
|
/// nullptr, represents the case where the instruction isn't known.
|
||
|
///
|
||
|
/// * If the opcode can be tested and is a single opcode, create the partition
|
||
|
/// for that opcode and assign the leaf to it. This partition no longer needs
|
||
|
/// to test the opcode, and many details about the instruction will usually
|
||
|
/// become known (e.g. number of operands for non-variadic instrs) via the
|
||
|
/// CodeGenInstr ptr.
|
||
|
/// * (not implemented yet) If the opcode can be tested and is a choice of
|
||
|
/// opcodes, then the leaf can be treated like the single-opcode case but must
|
||
|
/// be added to all relevant partitions and not quite as much becomes known as
|
||
|
/// a result. That said, multiple-choice opcodes are likely similar enough
|
||
|
/// (because if they aren't then handling them together makes little sense)
|
||
|
/// that plenty still becomes known. The main implementation issue with this
|
||
|
/// is having a description to represent the commonality between instructions.
|
||
|
/// * If the opcode is not tested, the leaf must be added to all partitions
|
||
|
/// including the wildcard nullptr partition. What becomes known as a result
|
||
|
/// varies between partitions.
|
||
|
/// * If the instruction to be tested is not declared then add the leaf to all
|
||
|
/// partitions. This occurs when we encounter one rule that is a superset of
|
||
|
/// the other and we are still matching the remainder of the superset. The
|
||
|
/// result is that the cases that don't match the superset will match the
|
||
|
/// subset rule, while the ones that do match the superset will match either
|
||
|
/// (which one is algorithm dependent but will usually be the superset).
|
||
|
class GIMatchTreeOpcodePartitioner : public GIMatchTreePartitioner {
|
||
|
unsigned InstrID;
|
||
|
DenseMap<const CodeGenInstruction *, unsigned> InstrToPartition;
|
||
|
std::vector<const CodeGenInstruction *> PartitionToInstr;
|
||
|
std::vector<BitVector> TestedPredicates;
|
||
|
|
||
|
public:
|
||
|
GIMatchTreeOpcodePartitioner(unsigned InstrID) : InstrID(InstrID) {}
|
||
|
|
||
|
std::unique_ptr<GIMatchTreePartitioner> clone() const override {
|
||
|
return std::make_unique<GIMatchTreeOpcodePartitioner>(*this);
|
||
|
}
|
||
|
|
||
|
void emitDescription(raw_ostream &OS) const override {
|
||
|
OS << "MI[" << InstrID << "].getOpcode()";
|
||
|
}
|
||
|
|
||
|
void emitPartitionName(raw_ostream &OS, unsigned Idx) const override;
|
||
|
|
||
|
void repartition(GIMatchTreeBuilder::LeafVec &Leaves) override;
|
||
|
void applyForPartition(unsigned Idx, GIMatchTreeBuilder &SubBuilder,
|
||
|
GIMatchTreeBuilder &Builder) override;
|
||
|
|
||
|
void emitPartitionResults(raw_ostream &OS) const override;
|
||
|
|
||
|
void generatePartitionSelectorCode(raw_ostream &OS,
|
||
|
StringRef Indent) const override;
|
||
|
};
|
||
|
|
||
|
class GIMatchTreeVRegDefPartitioner : public GIMatchTreePartitioner {
|
||
|
unsigned NewInstrID = -1;
|
||
|
unsigned InstrID;
|
||
|
unsigned OpIdx;
|
||
|
std::vector<BitVector> TraversedEdges;
|
||
|
DenseMap<unsigned, unsigned> ResultToPartition;
|
||
|
std::vector<bool> PartitionToResult;
|
||
|
|
||
|
void addToPartition(bool Result, unsigned LeafIdx);
|
||
|
|
||
|
public:
|
||
|
GIMatchTreeVRegDefPartitioner(unsigned InstrID, unsigned OpIdx)
|
||
|
: InstrID(InstrID), OpIdx(OpIdx) {}
|
||
|
|
||
|
std::unique_ptr<GIMatchTreePartitioner> clone() const override {
|
||
|
return std::make_unique<GIMatchTreeVRegDefPartitioner>(*this);
|
||
|
}
|
||
|
|
||
|
void emitDescription(raw_ostream &OS) const override {
|
||
|
OS << "MI[" << NewInstrID << "] = getVRegDef(MI[" << InstrID
|
||
|
<< "].getOperand(" << OpIdx << "))";
|
||
|
}
|
||
|
|
||
|
void emitPartitionName(raw_ostream &OS, unsigned Idx) const override {
|
||
|
bool Result = PartitionToResult[Idx];
|
||
|
if (Result)
|
||
|
OS << "true";
|
||
|
else
|
||
|
OS << "false";
|
||
|
}
|
||
|
|
||
|
void repartition(GIMatchTreeBuilder::LeafVec &Leaves) override;
|
||
|
void applyForPartition(unsigned PartitionIdx, GIMatchTreeBuilder &Builder,
|
||
|
GIMatchTreeBuilder &SubBuilder) override;
|
||
|
void emitPartitionResults(raw_ostream &OS) const override;
|
||
|
|
||
|
void generatePartitionSelectorCode(raw_ostream &OS,
|
||
|
StringRef Indent) const override;
|
||
|
};
|
||
|
|
||
|
} // end namespace llvm
|
||
|
#endif // ifndef LLVM_UTILS_TABLEGEN_GIMATCHTREE_H
|