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duplicate SpecialInputs fix, added tunable input threshold #871

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duplicate SpecialInputs fix, added tunable input threshold #871

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50 changes: 9 additions & 41 deletions lib/Infer/Pruning.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -47,6 +47,10 @@ namespace {
static llvm::cl::opt<bool> EnableBB("souper-dataflow-pruning-bb",
llvm::cl::desc("Prune with bivalent-bits analysis (default=true)"),
llvm::cl::init(true));

static llvm::cl::opt<int> InputThreshold("souper-dataflow-pruning-threshold",
llvm::cl::desc("Threshold for how many inputs pruning should try (default=10)"),
llvm::cl::init(10));
}

namespace souper {
Expand Down Expand Up @@ -237,14 +241,13 @@ bool PruningManager::isInfeasible(souper::Inst *RHS,
bool FoundNonTopAnalysisResult = false;
ForcedValueAnalysis FVA(RHS);
for (int I = 0; I < InputVals.size(); ++I) {
if (I > 9 && !FoundNonTopAnalysisResult) {
if (I >= InputThreshold && !FoundNonTopAnalysisResult) {
break;
// Give up if first 10 known bits and constant range results
// are all TOP.
// TODO: Maybe figure out a better way to determine if an RHS
// is not amenable to dataflow analysis. (example : x + HOLE)
// TODO: Maybe tune this threshold, or make it user controllable
// N = 10 results in a 2x performance boost for a 5% increase in
// Threshold = 10 results in a 2x performance boost for a 5% increase in
// the final number of guesses.
// Might make sense to make this threshold depend on the RHS
}
Expand Down Expand Up @@ -757,7 +760,7 @@ std::vector<ValueCache> PruningManager::generateInputSets(
std::vector<ValueCache> InputSets;

ValueCache Cache;

// input tests 0,1,-1,smin,smax are added here
constexpr unsigned PermutedLimit = 15;
std::string specialInputs = "abcde";
std::unordered_set<std::string> Visited;
Expand All @@ -778,45 +781,10 @@ std::vector<ValueCache> PruningManager::generateInputSets(
}
} while (std::next_permutation(specialInputs.begin(), specialInputs.end()));


for (auto &&I : Inputs) {
if (I->K == souper::Inst::Var)
Cache[I] = {llvm::APInt(I->Width, 0)};
}
if (isInputValid(Cache))
InputSets.push_back(Cache);

for (auto &&I : Inputs) {
if (I->K == souper::Inst::Var)
Cache[I] = {llvm::APInt(I->Width, 1)};
}
if (isInputValid(Cache))
InputSets.push_back(Cache);

for (auto &&I : Inputs) {
if (I->K == souper::Inst::Var)
Cache[I] = {llvm::APInt(I->Width, -1)};
}
if (isInputValid(Cache))
InputSets.push_back(Cache);

for (auto &&I : Inputs) {
if (I->K == souper::Inst::Var)
Cache[I] = {llvm::APInt::getSignedMaxValue(I->Width)};
}
if (isInputValid(Cache))
InputSets.push_back(Cache);

for (auto &&I : Inputs) {
if (I->K == souper::Inst::Var)
Cache[I] = {llvm::APInt::getSignedMinValue(I->Width)};
}
if (isInputValid(Cache))
InputSets.push_back(Cache);

// generate random inputs
constexpr int MaxTries = 100;
constexpr int NumLargeInputs = 5;
std::srand(0);
std::srand(0);//std::srand(0) is intentional. We want a diverse set of deterministic inputs, and not random ones.
int i, m;
for (i = 0, m = 0; i < NumLargeInputs && m < MaxTries; ++m ) {
for (auto &&I : Inputs) {
Expand Down