ADT: Add DAGDeltaAlgorithm, which is a DAG minimization algorithm built on top of the standard 'delta debugging' algorithm.

- This can give substantial speedups in the delta process for inputs we can construct dependency information for.

git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@105612 91177308-0d34-0410-b5e6-96231b3b80d8
This commit is contained in:
Daniel Dunbar 2010-06-08 16:21:22 +00:00
parent 4741c701a4
commit 73c6031a25
4 changed files with 553 additions and 0 deletions

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//===--- DAGDeltaAlgorithm.h - A DAG Minimization Algorithm ----*- C++ -*--===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//===----------------------------------------------------------------------===//
#ifndef LLVM_ADT_DAGDELTAALGORITHM_H
#define LLVM_ADT_DAGDELTAALGORITHM_H
#include <vector>
#include <set>
namespace llvm {
/// DAGDeltaAlgorithm - Implements a "delta debugging" algorithm for minimizing
/// directed acyclic graphs using a predicate function.
///
/// The result of the algorithm is a subset of the input change set which is
/// guaranteed to satisfy the predicate, assuming that the input set did. For
/// well formed predicates, the result set is guaranteed to be such that
/// removing any single element not required by the dependencies on the other
/// elements would falsify the predicate.
///
/// The DAG should be used to represent dependencies in the changes which are
/// likely to hold across the predicate function. That is, for a particular
/// changeset S and predicate P:
///
/// P(S) => P(S union pred(S))
///
/// The minization algorithm uses this dependency information to attempt to
/// eagerly prune large subsets of changes. As with \see DeltaAlgorithm, the DAG
/// is not required to satisfy this property, but the algorithm will run
/// substantially fewer tests with appropriate dependencies. \see DeltaAlgorithm
/// for more information on the properties which the predicate function itself
/// should satisfy.
class DAGDeltaAlgorithm {
public:
typedef unsigned change_ty;
typedef std::pair<change_ty, change_ty> edge_ty;
// FIXME: Use a decent data structure.
typedef std::set<change_ty> changeset_ty;
typedef std::vector<changeset_ty> changesetlist_ty;
public:
/// Run - Minimize the DAG formed by the \arg Changes vertices and the \arg
/// Dependencies edges by executing \see ExecuteOneTest() on subsets of
/// changes and returning the smallest set which still satisfies the test
/// predicate and the input \arg Dependencies.
///
/// \param Changes The list of changes.
///
/// \param Dependencies The list of dependencies amongst changes. For each
/// (x,y) in \arg Dependencies, both x and y must be in \arg Changes. The
/// minimization algorithm guarantees that for each tested changed set S, x
/// \in S implies y \in S. It is an error to have cyclic dependencies.
changeset_ty Run(const changeset_ty &Changes,
const std::vector<edge_ty> &Dependencies);
/// UpdatedSearchState - Callback used when the search state changes.
virtual void UpdatedSearchState(const changeset_ty &Changes,
const changesetlist_ty &Sets,
const changeset_ty &Required) {}
/// ExecuteOneTest - Execute a single test predicate on the change set \arg S.
virtual bool ExecuteOneTest(const changeset_ty &S) = 0;
};
} // end namespace llvm
#endif

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@ -8,6 +8,7 @@ add_llvm_library(LLVMSupport
ConstantRange.cpp
Debug.cpp
DeltaAlgorithm.cpp
DAGDeltaAlgorithm.cpp
Dwarf.cpp
ErrorHandling.cpp
FileUtilities.cpp

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//===--- DAGDeltaAlgorithm.cpp - A DAG Minimization Algorithm --*- C++ -*--===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//===----------------------------------------------------------------------===//
//
// 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/ADT/DAGDeltaAlgorithm.h"
#include "llvm/ADT/DeltaAlgorithm.h"
#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::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();
}

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//===- llvm/unittest/ADT/DAGDeltaAlgorithmTest.cpp ------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
#include "gtest/gtest.h"
#include "llvm/ADT/DAGDeltaAlgorithm.h"
#include <algorithm>
#include <cstdarg>
using namespace llvm;
namespace std {
static std::ostream &operator<<(std::ostream &OS,
const std::set<unsigned> &S) {
OS << "{";
for (std::set<unsigned>::const_iterator it = S.begin(),
ie = S.end(); it != ie; ++it) {
if (it != S.begin())
OS << ",";
OS << *it;
}
OS << "}";
return OS;
}
}
namespace {
typedef DAGDeltaAlgorithm::edge_ty edge_ty;
class FixedDAGDeltaAlgorithm : public DAGDeltaAlgorithm {
changeset_ty FailingSet;
unsigned NumTests;
protected:
virtual bool ExecuteOneTest(const changeset_ty &Changes) {
++NumTests;
return std::includes(Changes.begin(), Changes.end(),
FailingSet.begin(), FailingSet.end());
}
public:
FixedDAGDeltaAlgorithm(const changeset_ty &_FailingSet)
: FailingSet(_FailingSet),
NumTests(0) {}
unsigned getNumTests() const { return NumTests; }
};
std::set<unsigned> fixed_set(unsigned N, ...) {
std::set<unsigned> S;
va_list ap;
va_start(ap, N);
for (unsigned i = 0; i != N; ++i)
S.insert(va_arg(ap, unsigned));
va_end(ap);
return S;
}
std::set<unsigned> range(unsigned Start, unsigned End) {
std::set<unsigned> S;
while (Start != End)
S.insert(Start++);
return S;
}
std::set<unsigned> range(unsigned N) {
return range(0, N);
}
TEST(DAGDeltaAlgorithmTest, Basic) {
std::vector<edge_ty> Deps;
// Dependencies:
// 1 - 3
Deps.clear();
Deps.push_back(std::make_pair(3, 1));
// P = {3,5,7} \in S,
// [0, 20),
// should minimize to {1,3,5,7} in a reasonable number of tests.
FixedDAGDeltaAlgorithm FDA(fixed_set(3, 3, 5, 7));
EXPECT_EQ(fixed_set(4, 1, 3, 5, 7), FDA.Run(range(20), Deps));
EXPECT_GE(46U, FDA.getNumTests());
// Dependencies:
// 0 - 1
// \- 2 - 3
// \- 4
Deps.clear();
Deps.push_back(std::make_pair(1, 0));
Deps.push_back(std::make_pair(2, 0));
Deps.push_back(std::make_pair(4, 0));
Deps.push_back(std::make_pair(3, 2));
// This is a case where we must hold required changes.
//
// P = {1,3} \in S,
// [0, 5),
// should minimize to {0,1,2,3} in a small number of tests.
FixedDAGDeltaAlgorithm FDA2(fixed_set(2, 1, 3));
EXPECT_EQ(fixed_set(4, 0, 1, 2, 3), FDA2.Run(range(5), Deps));
EXPECT_GE(9U, FDA2.getNumTests());
// This is a case where we should quickly prune part of the tree.
//
// P = {4} \in S,
// [0, 5),
// should minimize to {0,4} in a small number of tests.
FixedDAGDeltaAlgorithm FDA3(fixed_set(1, 4));
EXPECT_EQ(fixed_set(2, 0, 4), FDA3.Run(range(5), Deps));
EXPECT_GE(6U, FDA3.getNumTests());
}
}