# DAGDeltaAlgorithm.cpp   [plain text]

```//===--- DAGDeltaAlgorithm.cpp - A DAG Minimization Algorithm --*- C++ -*--===//
//
//                     The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
//===----------------------------------------------------------------------===//
//
// The algorithm we use attempts to exploit the dependency information by
// minimizing top-down. We start by constructing an initial root set R, and
// then iteratively:
//
//   1. Minimize the set R using the test predicate:
//       P'(S) = P(S union pred*(S))
//
//   2. Extend R to R' = R union pred(R).
//
// until a fixed point is reached.
//
// The idea is that we want to quickly prune entire portions of the graph, so we
// try to find high-level nodes that can be eliminated with all of their
// dependents.
//
// FIXME: The current algorithm doesn't actually provide a strong guarantee
// about the minimality of the result. The problem is that after adding nodes to
// the required set, we no longer consider them for elimination. For strictly
// well formed predicates, this doesn't happen, but it commonly occurs in
// practice when there are unmodelled dependencies. I believe we can resolve
// this by allowing the required set to be minimized as well, but need more test
// cases first.
//
//===----------------------------------------------------------------------===//

#include "llvm/Support/Debug.h"
#include "llvm/Support/Format.h"
#include "llvm/Support/raw_ostream.h"
#include <algorithm>
#include <cassert>
#include <iterator>
#include <map>
using namespace llvm;

namespace {

class DAGDeltaAlgorithmImpl {
friend class DeltaActiveSetHelper;

public:
typedef DAGDeltaAlgorithm::change_ty change_ty;
typedef DAGDeltaAlgorithm::changeset_ty changeset_ty;
typedef DAGDeltaAlgorithm::changesetlist_ty changesetlist_ty;
typedef DAGDeltaAlgorithm::edge_ty edge_ty;

private:
typedef std::vector<change_ty>::iterator pred_iterator_ty;
typedef std::vector<change_ty>::iterator succ_iterator_ty;
typedef std::set<change_ty>::iterator pred_closure_iterator_ty;
typedef std::set<change_ty>::iterator succ_closure_iterator_ty;

DAGDeltaAlgorithm &DDA;

const changeset_ty &Changes;
const std::vector<edge_ty> &Dependencies;

std::vector<change_ty> Roots;

/// Cache of failed test results. Successful test results are never cached
/// since we always reduce following a success. We maintain an independent
/// cache from that used by the individual delta passes because we may get
/// hits across multiple individual delta invocations.
mutable std::set<changeset_ty> FailedTestsCache;

// FIXME: Gross.
std::map<change_ty, std::vector<change_ty> > Predecessors;
std::map<change_ty, std::vector<change_ty> > Successors;

std::map<change_ty, std::set<change_ty> > PredClosure;
std::map<change_ty, std::set<change_ty> > SuccClosure;

private:
pred_iterator_ty pred_begin(change_ty Node) {
assert(Predecessors.count(Node) && "Invalid node!");
return Predecessors[Node].begin();
}
pred_iterator_ty pred_end(change_ty Node) {
assert(Predecessors.count(Node) && "Invalid node!");
return Predecessors[Node].end();
}

pred_closure_iterator_ty pred_closure_begin(change_ty Node) {
assert(PredClosure.count(Node) && "Invalid node!");
return PredClosure[Node].begin();
}
pred_closure_iterator_ty pred_closure_end(change_ty Node) {
assert(PredClosure.count(Node) && "Invalid node!");
return PredClosure[Node].end();
}

succ_iterator_ty succ_begin(change_ty Node) {
assert(Successors.count(Node) && "Invalid node!");
return Successors[Node].begin();
}
succ_iterator_ty succ_end(change_ty Node) {
assert(Successors.count(Node) && "Invalid node!");
return Successors[Node].end();
}

succ_closure_iterator_ty succ_closure_begin(change_ty Node) {
assert(SuccClosure.count(Node) && "Invalid node!");
return SuccClosure[Node].begin();
}
succ_closure_iterator_ty succ_closure_end(change_ty Node) {
assert(SuccClosure.count(Node) && "Invalid node!");
return SuccClosure[Node].end();
}

void UpdatedSearchState(const changeset_ty &Changes,
const changesetlist_ty &Sets,
const changeset_ty &Required) {
DDA.UpdatedSearchState(Changes, Sets, Required);
}

/// ExecuteOneTest - Execute a single test predicate on the change set \arg S.
bool ExecuteOneTest(const changeset_ty &S) {
// Check dependencies invariant.
DEBUG({
for (changeset_ty::const_iterator it = S.begin(),
ie = S.end(); it != ie; ++it)
for (succ_iterator_ty it2 = succ_begin(*it),
ie2 = succ_end(*it); it2 != ie2; ++it2)
assert(S.count(*it2) && "Attempt to run invalid changeset!");
});

return DDA.ExecuteOneTest(S);
}

public:
DAGDeltaAlgorithmImpl(DAGDeltaAlgorithm &_DDA,
const changeset_ty &_Changes,
const std::vector<edge_ty> &_Dependencies);

changeset_ty Run();

/// GetTestResult - Get the test result for the active set \arg Changes with
/// \arg Required changes from the cache, executing the test if necessary.
///
/// \param Changes - The set of active changes being minimized, which should
/// have their pred closure included in the test.
/// \param Required - The set of changes which have previously been
/// established to be required.
/// \return - The test result.
bool GetTestResult(const changeset_ty &Changes, const changeset_ty &Required);
};

/// Helper object for minimizing an active set of changes.
class DeltaActiveSetHelper : public DeltaAlgorithm {
DAGDeltaAlgorithmImpl &DDAI;

const changeset_ty &Required;

protected:
/// UpdatedSearchState - Callback used when the search state changes.
virtual void UpdatedSearchState(const changeset_ty &Changes,
const changesetlist_ty &Sets) {
DDAI.UpdatedSearchState(Changes, Sets, Required);
}

virtual bool ExecuteOneTest(const changeset_ty &S) {
return DDAI.GetTestResult(S, Required);
}

public:
DeltaActiveSetHelper(DAGDeltaAlgorithmImpl &_DDAI,
const changeset_ty &_Required)
: DDAI(_DDAI), Required(_Required) {}
};

}

DAGDeltaAlgorithmImpl::DAGDeltaAlgorithmImpl(DAGDeltaAlgorithm &_DDA,
const changeset_ty &_Changes,
const std::vector<edge_ty>
&_Dependencies)
: DDA(_DDA),
Changes(_Changes),
Dependencies(_Dependencies)
{
for (changeset_ty::const_iterator it = Changes.begin(),
ie = Changes.end(); it != ie; ++it) {
Predecessors.insert(std::make_pair(*it, std::vector<change_ty>()));
Successors.insert(std::make_pair(*it, std::vector<change_ty>()));
}
for (std::vector<edge_ty>::const_iterator it = Dependencies.begin(),
ie = Dependencies.end(); it != ie; ++it) {
Predecessors[it->second].push_back(it->first);
Successors[it->first].push_back(it->second);
}

// Compute the roots.
for (changeset_ty::const_iterator it = Changes.begin(),
ie = Changes.end(); it != ie; ++it)
if (succ_begin(*it) == succ_end(*it))
Roots.push_back(*it);

// Pre-compute the closure of the successor relation.
std::vector<change_ty> Worklist(Roots.begin(), Roots.end());
while (!Worklist.empty()) {
change_ty Change = Worklist.back();
Worklist.pop_back();

std::set<change_ty> &ChangeSuccs = SuccClosure[Change];
for (pred_iterator_ty it = pred_begin(Change),
ie = pred_end(Change); it != ie; ++it) {
SuccClosure[*it].insert(Change);
SuccClosure[*it].insert(ChangeSuccs.begin(), ChangeSuccs.end());
Worklist.push_back(*it);
}
}

// Invert to form the predecessor closure map.
for (changeset_ty::const_iterator it = Changes.begin(),
ie = Changes.end(); it != ie; ++it)
PredClosure.insert(std::make_pair(*it, std::set<change_ty>()));
for (changeset_ty::const_iterator it = Changes.begin(),
ie = Changes.end(); it != ie; ++it)
for (succ_closure_iterator_ty it2 = succ_closure_begin(*it),
ie2 = succ_closure_end(*it); it2 != ie2; ++it2)
PredClosure[*it2].insert(*it);

// Dump useful debug info.
DEBUG({
llvm::errs() << "-- DAGDeltaAlgorithmImpl --\n";
llvm::errs() << "Changes: [";
for (changeset_ty::const_iterator it = Changes.begin(),
ie = Changes.end(); it != ie; ++it) {
if (it != Changes.begin()) llvm::errs() << ", ";
llvm::errs() << *it;

if (succ_begin(*it) != succ_end(*it)) {
llvm::errs() << "(";
for (succ_iterator_ty it2 = succ_begin(*it),
ie2 = succ_end(*it); it2 != ie2; ++it2) {
if (it2 != succ_begin(*it)) llvm::errs() << ", ";
llvm::errs() << "->" << *it2;
}
llvm::errs() << ")";
}
}
llvm::errs() << "]\n";

llvm::errs() << "Roots: [";
for (std::vector<change_ty>::const_iterator it = Roots.begin(),
ie = Roots.end(); it != ie; ++it) {
if (it != Roots.begin()) llvm::errs() << ", ";
llvm::errs() << *it;
}
llvm::errs() << "]\n";

llvm::errs() << "Predecessor Closure:\n";
for (changeset_ty::const_iterator it = Changes.begin(),
ie = Changes.end(); it != ie; ++it) {
llvm::errs() << format("  %-4d: [", *it);
for (pred_closure_iterator_ty it2 = pred_closure_begin(*it),
ie2 = pred_closure_end(*it); it2 != ie2; ++it2) {
if (it2 != pred_closure_begin(*it)) llvm::errs() << ", ";
llvm::errs() << *it2;
}
llvm::errs() << "]\n";
}

llvm::errs() << "Successor Closure:\n";
for (changeset_ty::const_iterator it = Changes.begin(),
ie = Changes.end(); it != ie; ++it) {
llvm::errs() << format("  %-4d: [", *it);
for (succ_closure_iterator_ty it2 = succ_closure_begin(*it),
ie2 = succ_closure_end(*it); it2 != ie2; ++it2) {
if (it2 != succ_closure_begin(*it)) llvm::errs() << ", ";
llvm::errs() << *it2;
}
llvm::errs() << "]\n";
}

llvm::errs() << "\n\n";
});
}

bool DAGDeltaAlgorithmImpl::GetTestResult(const changeset_ty &Changes,
const changeset_ty &Required) {
changeset_ty Extended(Required);
Extended.insert(Changes.begin(), Changes.end());
for (changeset_ty::const_iterator it = Changes.begin(),
ie = Changes.end(); it != ie; ++it)
Extended.insert(pred_closure_begin(*it), pred_closure_end(*it));

if (FailedTestsCache.count(Extended))
return false;

bool Result = ExecuteOneTest(Extended);
if (!Result)
FailedTestsCache.insert(Extended);

return Result;
}

DAGDeltaAlgorithm::changeset_ty
DAGDeltaAlgorithmImpl::Run() {
// The current set of changes we are minimizing, starting at the roots.
changeset_ty CurrentSet(Roots.begin(), Roots.end());

// The set of required changes.
changeset_ty Required;

// Iterate until the active set of changes is empty. Convergence is guaranteed
// assuming input was a DAG.
//
// Invariant:  CurrentSet intersect Required == {}
// Invariant:  Required == (Required union succ*(Required))
while (!CurrentSet.empty()) {
DEBUG({
llvm::errs() << "DAG_DD - " << CurrentSet.size() << " active changes, "
<< Required.size() << " required changes\n";
});

// Minimize the current set of changes.
DeltaActiveSetHelper Helper(*this, Required);
changeset_ty CurrentMinSet = Helper.Run(CurrentSet);

// Update the set of required changes. Since
//   CurrentMinSet subset CurrentSet
// and after the last iteration,
//   succ(CurrentSet) subset Required
// then
//   succ(CurrentMinSet) subset Required
// and our invariant on Required is maintained.
Required.insert(CurrentMinSet.begin(), CurrentMinSet.end());

// Replace the current set with the predecssors of the minimized set of
// active changes.
CurrentSet.clear();
for (changeset_ty::const_iterator it = CurrentMinSet.begin(),
ie = CurrentMinSet.end(); it != ie; ++it)
CurrentSet.insert(pred_begin(*it), pred_end(*it));

// FIXME: We could enforce CurrentSet intersect Required == {} here if we
// wanted to protect against cyclic graphs.
}

return Required;
}

DAGDeltaAlgorithm::changeset_ty
DAGDeltaAlgorithm::Run(const changeset_ty &Changes,
const std::vector<edge_ty> &Dependencies) {
return DAGDeltaAlgorithmImpl(*this, Changes, Dependencies).Run();
}
```