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llvm-mirror/include/llvm/CodeGen/MachinePipeliner.h
Marianne Mailhot-Sarrasin 214897b9a5 [Pipeliner] Fixed optimization remarks and debug dumps Initiation
Interval value

The II value was incremented before exiting the loop, and therefor when
used in the optimization remarks and debug dumps it did not reflect the
initiation interval actually used in Schedule.

Differential Revision: https://reviews.llvm.org/D95692
2021-02-17 12:28:37 -05:00

602 lines
21 KiB
C++

//===- MachinePipeliner.h - Machine Software Pipeliner Pass -------------===//
//
// 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
//
//===----------------------------------------------------------------------===//
//
// An implementation of the Swing Modulo Scheduling (SMS) software pipeliner.
//
// Software pipelining (SWP) is an instruction scheduling technique for loops
// that overlap loop iterations and exploits ILP via a compiler transformation.
//
// Swing Modulo Scheduling is an implementation of software pipelining
// that generates schedules that are near optimal in terms of initiation
// interval, register requirements, and stage count. See the papers:
//
// "Swing Modulo Scheduling: A Lifetime-Sensitive Approach", by J. Llosa,
// A. Gonzalez, E. Ayguade, and M. Valero. In PACT '96 Proceedings of the 1996
// Conference on Parallel Architectures and Compilation Techiniques.
//
// "Lifetime-Sensitive Modulo Scheduling in a Production Environment", by J.
// Llosa, E. Ayguade, A. Gonzalez, M. Valero, and J. Eckhardt. In IEEE
// Transactions on Computers, Vol. 50, No. 3, 2001.
//
// "An Implementation of Swing Modulo Scheduling With Extensions for
// Superblocks", by T. Lattner, Master's Thesis, University of Illinois at
// Urbana-Champaign, 2005.
//
//
// The SMS algorithm consists of three main steps after computing the minimal
// initiation interval (MII).
// 1) Analyze the dependence graph and compute information about each
// instruction in the graph.
// 2) Order the nodes (instructions) by priority based upon the heuristics
// described in the algorithm.
// 3) Attempt to schedule the nodes in the specified order using the MII.
//
//===----------------------------------------------------------------------===//
#ifndef LLVM_CODEGEN_MACHINEPIPELINER_H
#define LLVM_CODEGEN_MACHINEPIPELINER_H
#include "llvm/CodeGen/MachineDominators.h"
#include "llvm/CodeGen/MachineOptimizationRemarkEmitter.h"
#include "llvm/CodeGen/RegisterClassInfo.h"
#include "llvm/CodeGen/ScheduleDAGInstrs.h"
#include "llvm/CodeGen/TargetInstrInfo.h"
#include "llvm/InitializePasses.h"
namespace llvm {
class AAResults;
class NodeSet;
class SMSchedule;
extern cl::opt<bool> SwpEnableCopyToPhi;
/// The main class in the implementation of the target independent
/// software pipeliner pass.
class MachinePipeliner : public MachineFunctionPass {
public:
MachineFunction *MF = nullptr;
MachineOptimizationRemarkEmitter *ORE = nullptr;
const MachineLoopInfo *MLI = nullptr;
const MachineDominatorTree *MDT = nullptr;
const InstrItineraryData *InstrItins;
const TargetInstrInfo *TII = nullptr;
RegisterClassInfo RegClassInfo;
bool disabledByPragma = false;
unsigned II_setByPragma = 0;
#ifndef NDEBUG
static int NumTries;
#endif
/// Cache the target analysis information about the loop.
struct LoopInfo {
MachineBasicBlock *TBB = nullptr;
MachineBasicBlock *FBB = nullptr;
SmallVector<MachineOperand, 4> BrCond;
MachineInstr *LoopInductionVar = nullptr;
MachineInstr *LoopCompare = nullptr;
};
LoopInfo LI;
static char ID;
MachinePipeliner() : MachineFunctionPass(ID) {
initializeMachinePipelinerPass(*PassRegistry::getPassRegistry());
}
bool runOnMachineFunction(MachineFunction &MF) override;
void getAnalysisUsage(AnalysisUsage &AU) const override;
private:
void preprocessPhiNodes(MachineBasicBlock &B);
bool canPipelineLoop(MachineLoop &L);
bool scheduleLoop(MachineLoop &L);
bool swingModuloScheduler(MachineLoop &L);
void setPragmaPipelineOptions(MachineLoop &L);
};
/// This class builds the dependence graph for the instructions in a loop,
/// and attempts to schedule the instructions using the SMS algorithm.
class SwingSchedulerDAG : public ScheduleDAGInstrs {
MachinePipeliner &Pass;
/// The minimum initiation interval between iterations for this schedule.
unsigned MII = 0;
/// The maximum initiation interval between iterations for this schedule.
unsigned MAX_II = 0;
/// Set to true if a valid pipelined schedule is found for the loop.
bool Scheduled = false;
MachineLoop &Loop;
LiveIntervals &LIS;
const RegisterClassInfo &RegClassInfo;
unsigned II_setByPragma = 0;
/// A toplogical ordering of the SUnits, which is needed for changing
/// dependences and iterating over the SUnits.
ScheduleDAGTopologicalSort Topo;
struct NodeInfo {
int ASAP = 0;
int ALAP = 0;
int ZeroLatencyDepth = 0;
int ZeroLatencyHeight = 0;
NodeInfo() = default;
};
/// Computed properties for each node in the graph.
std::vector<NodeInfo> ScheduleInfo;
enum OrderKind { BottomUp = 0, TopDown = 1 };
/// Computed node ordering for scheduling.
SetVector<SUnit *> NodeOrder;
using NodeSetType = SmallVector<NodeSet, 8>;
using ValueMapTy = DenseMap<unsigned, unsigned>;
using MBBVectorTy = SmallVectorImpl<MachineBasicBlock *>;
using InstrMapTy = DenseMap<MachineInstr *, MachineInstr *>;
/// Instructions to change when emitting the final schedule.
DenseMap<SUnit *, std::pair<unsigned, int64_t>> InstrChanges;
/// We may create a new instruction, so remember it because it
/// must be deleted when the pass is finished.
DenseMap<MachineInstr*, MachineInstr *> NewMIs;
/// Ordered list of DAG postprocessing steps.
std::vector<std::unique_ptr<ScheduleDAGMutation>> Mutations;
/// Helper class to implement Johnson's circuit finding algorithm.
class Circuits {
std::vector<SUnit> &SUnits;
SetVector<SUnit *> Stack;
BitVector Blocked;
SmallVector<SmallPtrSet<SUnit *, 4>, 10> B;
SmallVector<SmallVector<int, 4>, 16> AdjK;
// Node to Index from ScheduleDAGTopologicalSort
std::vector<int> *Node2Idx;
unsigned NumPaths;
static unsigned MaxPaths;
public:
Circuits(std::vector<SUnit> &SUs, ScheduleDAGTopologicalSort &Topo)
: SUnits(SUs), Blocked(SUs.size()), B(SUs.size()), AdjK(SUs.size()) {
Node2Idx = new std::vector<int>(SUs.size());
unsigned Idx = 0;
for (const auto &NodeNum : Topo)
Node2Idx->at(NodeNum) = Idx++;
}
~Circuits() { delete Node2Idx; }
/// Reset the data structures used in the circuit algorithm.
void reset() {
Stack.clear();
Blocked.reset();
B.assign(SUnits.size(), SmallPtrSet<SUnit *, 4>());
NumPaths = 0;
}
void createAdjacencyStructure(SwingSchedulerDAG *DAG);
bool circuit(int V, int S, NodeSetType &NodeSets, bool HasBackedge = false);
void unblock(int U);
};
struct CopyToPhiMutation : public ScheduleDAGMutation {
void apply(ScheduleDAGInstrs *DAG) override;
};
public:
SwingSchedulerDAG(MachinePipeliner &P, MachineLoop &L, LiveIntervals &lis,
const RegisterClassInfo &rci, unsigned II)
: ScheduleDAGInstrs(*P.MF, P.MLI, false), Pass(P), Loop(L), LIS(lis),
RegClassInfo(rci), II_setByPragma(II), Topo(SUnits, &ExitSU) {
P.MF->getSubtarget().getSMSMutations(Mutations);
if (SwpEnableCopyToPhi)
Mutations.push_back(std::make_unique<CopyToPhiMutation>());
}
void schedule() override;
void finishBlock() override;
/// Return true if the loop kernel has been scheduled.
bool hasNewSchedule() { return Scheduled; }
/// Return the earliest time an instruction may be scheduled.
int getASAP(SUnit *Node) { return ScheduleInfo[Node->NodeNum].ASAP; }
/// Return the latest time an instruction my be scheduled.
int getALAP(SUnit *Node) { return ScheduleInfo[Node->NodeNum].ALAP; }
/// The mobility function, which the number of slots in which
/// an instruction may be scheduled.
int getMOV(SUnit *Node) { return getALAP(Node) - getASAP(Node); }
/// The depth, in the dependence graph, for a node.
unsigned getDepth(SUnit *Node) { return Node->getDepth(); }
/// The maximum unweighted length of a path from an arbitrary node to the
/// given node in which each edge has latency 0
int getZeroLatencyDepth(SUnit *Node) {
return ScheduleInfo[Node->NodeNum].ZeroLatencyDepth;
}
/// The height, in the dependence graph, for a node.
unsigned getHeight(SUnit *Node) { return Node->getHeight(); }
/// The maximum unweighted length of a path from the given node to an
/// arbitrary node in which each edge has latency 0
int getZeroLatencyHeight(SUnit *Node) {
return ScheduleInfo[Node->NodeNum].ZeroLatencyHeight;
}
/// Return true if the dependence is a back-edge in the data dependence graph.
/// Since the DAG doesn't contain cycles, we represent a cycle in the graph
/// using an anti dependence from a Phi to an instruction.
bool isBackedge(SUnit *Source, const SDep &Dep) {
if (Dep.getKind() != SDep::Anti)
return false;
return Source->getInstr()->isPHI() || Dep.getSUnit()->getInstr()->isPHI();
}
bool isLoopCarriedDep(SUnit *Source, const SDep &Dep, bool isSucc = true);
/// The distance function, which indicates that operation V of iteration I
/// depends on operations U of iteration I-distance.
unsigned getDistance(SUnit *U, SUnit *V, const SDep &Dep) {
// Instructions that feed a Phi have a distance of 1. Computing larger
// values for arrays requires data dependence information.
if (V->getInstr()->isPHI() && Dep.getKind() == SDep::Anti)
return 1;
return 0;
}
void applyInstrChange(MachineInstr *MI, SMSchedule &Schedule);
void fixupRegisterOverlaps(std::deque<SUnit *> &Instrs);
/// Return the new base register that was stored away for the changed
/// instruction.
unsigned getInstrBaseReg(SUnit *SU) {
DenseMap<SUnit *, std::pair<unsigned, int64_t>>::iterator It =
InstrChanges.find(SU);
if (It != InstrChanges.end())
return It->second.first;
return 0;
}
void addMutation(std::unique_ptr<ScheduleDAGMutation> Mutation) {
Mutations.push_back(std::move(Mutation));
}
static bool classof(const ScheduleDAGInstrs *DAG) { return true; }
private:
void addLoopCarriedDependences(AAResults *AA);
void updatePhiDependences();
void changeDependences();
unsigned calculateResMII();
unsigned calculateRecMII(NodeSetType &RecNodeSets);
void findCircuits(NodeSetType &NodeSets);
void fuseRecs(NodeSetType &NodeSets);
void removeDuplicateNodes(NodeSetType &NodeSets);
void computeNodeFunctions(NodeSetType &NodeSets);
void registerPressureFilter(NodeSetType &NodeSets);
void colocateNodeSets(NodeSetType &NodeSets);
void checkNodeSets(NodeSetType &NodeSets);
void groupRemainingNodes(NodeSetType &NodeSets);
void addConnectedNodes(SUnit *SU, NodeSet &NewSet,
SetVector<SUnit *> &NodesAdded);
void computeNodeOrder(NodeSetType &NodeSets);
void checkValidNodeOrder(const NodeSetType &Circuits) const;
bool schedulePipeline(SMSchedule &Schedule);
bool computeDelta(MachineInstr &MI, unsigned &Delta);
MachineInstr *findDefInLoop(Register Reg);
bool canUseLastOffsetValue(MachineInstr *MI, unsigned &BasePos,
unsigned &OffsetPos, unsigned &NewBase,
int64_t &NewOffset);
void postprocessDAG();
/// Set the Minimum Initiation Interval for this schedule attempt.
void setMII(unsigned ResMII, unsigned RecMII);
/// Set the Maximum Initiation Interval for this schedule attempt.
void setMAX_II();
};
/// A NodeSet contains a set of SUnit DAG nodes with additional information
/// that assigns a priority to the set.
class NodeSet {
SetVector<SUnit *> Nodes;
bool HasRecurrence = false;
unsigned RecMII = 0;
int MaxMOV = 0;
unsigned MaxDepth = 0;
unsigned Colocate = 0;
SUnit *ExceedPressure = nullptr;
unsigned Latency = 0;
public:
using iterator = SetVector<SUnit *>::const_iterator;
NodeSet() = default;
NodeSet(iterator S, iterator E) : Nodes(S, E), HasRecurrence(true) {
Latency = 0;
for (unsigned i = 0, e = Nodes.size(); i < e; ++i) {
DenseMap<SUnit *, unsigned> SuccSUnitLatency;
for (const SDep &Succ : Nodes[i]->Succs) {
auto SuccSUnit = Succ.getSUnit();
if (!Nodes.count(SuccSUnit))
continue;
unsigned CurLatency = Succ.getLatency();
unsigned MaxLatency = 0;
if (SuccSUnitLatency.count(SuccSUnit))
MaxLatency = SuccSUnitLatency[SuccSUnit];
if (CurLatency > MaxLatency)
SuccSUnitLatency[SuccSUnit] = CurLatency;
}
for (auto SUnitLatency : SuccSUnitLatency)
Latency += SUnitLatency.second;
}
}
bool insert(SUnit *SU) { return Nodes.insert(SU); }
void insert(iterator S, iterator E) { Nodes.insert(S, E); }
template <typename UnaryPredicate> bool remove_if(UnaryPredicate P) {
return Nodes.remove_if(P);
}
unsigned count(SUnit *SU) const { return Nodes.count(SU); }
bool hasRecurrence() { return HasRecurrence; };
unsigned size() const { return Nodes.size(); }
bool empty() const { return Nodes.empty(); }
SUnit *getNode(unsigned i) const { return Nodes[i]; };
void setRecMII(unsigned mii) { RecMII = mii; };
void setColocate(unsigned c) { Colocate = c; };
void setExceedPressure(SUnit *SU) { ExceedPressure = SU; }
bool isExceedSU(SUnit *SU) { return ExceedPressure == SU; }
int compareRecMII(NodeSet &RHS) { return RecMII - RHS.RecMII; }
int getRecMII() { return RecMII; }
/// Summarize node functions for the entire node set.
void computeNodeSetInfo(SwingSchedulerDAG *SSD) {
for (SUnit *SU : *this) {
MaxMOV = std::max(MaxMOV, SSD->getMOV(SU));
MaxDepth = std::max(MaxDepth, SSD->getDepth(SU));
}
}
unsigned getLatency() { return Latency; }
unsigned getMaxDepth() { return MaxDepth; }
void clear() {
Nodes.clear();
RecMII = 0;
HasRecurrence = false;
MaxMOV = 0;
MaxDepth = 0;
Colocate = 0;
ExceedPressure = nullptr;
}
operator SetVector<SUnit *> &() { return Nodes; }
/// Sort the node sets by importance. First, rank them by recurrence MII,
/// then by mobility (least mobile done first), and finally by depth.
/// Each node set may contain a colocate value which is used as the first
/// tie breaker, if it's set.
bool operator>(const NodeSet &RHS) const {
if (RecMII == RHS.RecMII) {
if (Colocate != 0 && RHS.Colocate != 0 && Colocate != RHS.Colocate)
return Colocate < RHS.Colocate;
if (MaxMOV == RHS.MaxMOV)
return MaxDepth > RHS.MaxDepth;
return MaxMOV < RHS.MaxMOV;
}
return RecMII > RHS.RecMII;
}
bool operator==(const NodeSet &RHS) const {
return RecMII == RHS.RecMII && MaxMOV == RHS.MaxMOV &&
MaxDepth == RHS.MaxDepth;
}
bool operator!=(const NodeSet &RHS) const { return !operator==(RHS); }
iterator begin() { return Nodes.begin(); }
iterator end() { return Nodes.end(); }
void print(raw_ostream &os) const;
#if !defined(NDEBUG) || defined(LLVM_ENABLE_DUMP)
LLVM_DUMP_METHOD void dump() const;
#endif
};
// 16 was selected based on the number of ProcResource kinds for all
// existing Subtargets, so that SmallVector don't need to resize too often.
static const int DefaultProcResSize = 16;
class ResourceManager {
private:
const MCSubtargetInfo *STI;
const MCSchedModel &SM;
const bool UseDFA;
std::unique_ptr<DFAPacketizer> DFAResources;
/// Each processor resource is associated with a so-called processor resource
/// mask. This vector allows to correlate processor resource IDs with
/// processor resource masks. There is exactly one element per each processor
/// resource declared by the scheduling model.
llvm::SmallVector<uint64_t, DefaultProcResSize> ProcResourceMasks;
llvm::SmallVector<uint64_t, DefaultProcResSize> ProcResourceCount;
public:
ResourceManager(const TargetSubtargetInfo *ST)
: STI(ST), SM(ST->getSchedModel()), UseDFA(ST->useDFAforSMS()),
ProcResourceMasks(SM.getNumProcResourceKinds(), 0),
ProcResourceCount(SM.getNumProcResourceKinds(), 0) {
if (UseDFA)
DFAResources.reset(ST->getInstrInfo()->CreateTargetScheduleState(*ST));
initProcResourceVectors(SM, ProcResourceMasks);
}
void initProcResourceVectors(const MCSchedModel &SM,
SmallVectorImpl<uint64_t> &Masks);
/// Check if the resources occupied by a MCInstrDesc are available in
/// the current state.
bool canReserveResources(const MCInstrDesc *MID) const;
/// Reserve the resources occupied by a MCInstrDesc and change the current
/// state to reflect that change.
void reserveResources(const MCInstrDesc *MID);
/// Check if the resources occupied by a machine instruction are available
/// in the current state.
bool canReserveResources(const MachineInstr &MI) const;
/// Reserve the resources occupied by a machine instruction and change the
/// current state to reflect that change.
void reserveResources(const MachineInstr &MI);
/// Reset the state
void clearResources();
};
/// This class represents the scheduled code. The main data structure is a
/// map from scheduled cycle to instructions. During scheduling, the
/// data structure explicitly represents all stages/iterations. When
/// the algorithm finshes, the schedule is collapsed into a single stage,
/// which represents instructions from different loop iterations.
///
/// The SMS algorithm allows negative values for cycles, so the first cycle
/// in the schedule is the smallest cycle value.
class SMSchedule {
private:
/// Map from execution cycle to instructions.
DenseMap<int, std::deque<SUnit *>> ScheduledInstrs;
/// Map from instruction to execution cycle.
std::map<SUnit *, int> InstrToCycle;
/// Keep track of the first cycle value in the schedule. It starts
/// as zero, but the algorithm allows negative values.
int FirstCycle = 0;
/// Keep track of the last cycle value in the schedule.
int LastCycle = 0;
/// The initiation interval (II) for the schedule.
int InitiationInterval = 0;
/// Target machine information.
const TargetSubtargetInfo &ST;
/// Virtual register information.
MachineRegisterInfo &MRI;
ResourceManager ProcItinResources;
public:
SMSchedule(MachineFunction *mf)
: ST(mf->getSubtarget()), MRI(mf->getRegInfo()), ProcItinResources(&ST) {}
void reset() {
ScheduledInstrs.clear();
InstrToCycle.clear();
FirstCycle = 0;
LastCycle = 0;
InitiationInterval = 0;
}
/// Set the initiation interval for this schedule.
void setInitiationInterval(int ii) { InitiationInterval = ii; }
/// Return the initiation interval for this schedule.
int getInitiationInterval() const { return InitiationInterval; }
/// Return the first cycle in the completed schedule. This
/// can be a negative value.
int getFirstCycle() const { return FirstCycle; }
/// Return the last cycle in the finalized schedule.
int getFinalCycle() const { return FirstCycle + InitiationInterval - 1; }
/// Return the cycle of the earliest scheduled instruction in the dependence
/// chain.
int earliestCycleInChain(const SDep &Dep);
/// Return the cycle of the latest scheduled instruction in the dependence
/// chain.
int latestCycleInChain(const SDep &Dep);
void computeStart(SUnit *SU, int *MaxEarlyStart, int *MinLateStart,
int *MinEnd, int *MaxStart, int II, SwingSchedulerDAG *DAG);
bool insert(SUnit *SU, int StartCycle, int EndCycle, int II);
/// Iterators for the cycle to instruction map.
using sched_iterator = DenseMap<int, std::deque<SUnit *>>::iterator;
using const_sched_iterator =
DenseMap<int, std::deque<SUnit *>>::const_iterator;
/// Return true if the instruction is scheduled at the specified stage.
bool isScheduledAtStage(SUnit *SU, unsigned StageNum) {
return (stageScheduled(SU) == (int)StageNum);
}
/// Return the stage for a scheduled instruction. Return -1 if
/// the instruction has not been scheduled.
int stageScheduled(SUnit *SU) const {
std::map<SUnit *, int>::const_iterator it = InstrToCycle.find(SU);
if (it == InstrToCycle.end())
return -1;
return (it->second - FirstCycle) / InitiationInterval;
}
/// Return the cycle for a scheduled instruction. This function normalizes
/// the first cycle to be 0.
unsigned cycleScheduled(SUnit *SU) const {
std::map<SUnit *, int>::const_iterator it = InstrToCycle.find(SU);
assert(it != InstrToCycle.end() && "Instruction hasn't been scheduled.");
return (it->second - FirstCycle) % InitiationInterval;
}
/// Return the maximum stage count needed for this schedule.
unsigned getMaxStageCount() {
return (LastCycle - FirstCycle) / InitiationInterval;
}
/// Return the instructions that are scheduled at the specified cycle.
std::deque<SUnit *> &getInstructions(int cycle) {
return ScheduledInstrs[cycle];
}
bool isValidSchedule(SwingSchedulerDAG *SSD);
void finalizeSchedule(SwingSchedulerDAG *SSD);
void orderDependence(SwingSchedulerDAG *SSD, SUnit *SU,
std::deque<SUnit *> &Insts);
bool isLoopCarried(SwingSchedulerDAG *SSD, MachineInstr &Phi);
bool isLoopCarriedDefOfUse(SwingSchedulerDAG *SSD, MachineInstr *Def,
MachineOperand &MO);
void print(raw_ostream &os) const;
void dump() const;
};
} // end namespace llvm
#endif // LLVM_CODEGEN_MACHINEPIPELINER_H