Thanks! Quick question before I review it in more details: what is the performance characteristics of this patch compared to the others?
On Aug 27, 2012, at 11:35 AM, Richard Trieu <[email protected]> wrote: > Incorporated most of the suggestions into this patch. Still using a double > pass over the constants for the reasons outlined below. > > On Fri, Aug 17, 2012 at 10:00 PM, Ted Kremenek <[email protected]> wrote: > BTW, I wrote this two days ago. For some reason my mail client didn't send > it out until now. My apologies for the delay. > No worries. Had some issues that cropped up on template diffing that took my > time. > > On Aug 15, 2012, at 10:11 PM, Ted Kremenek <[email protected]> wrote: > >> On Aug 15, 2012, at 6:12 PM, Richard Trieu <[email protected]> wrote: >> >>> On Tue, Aug 14, 2012 at 9:48 PM, Ted Kremenek <[email protected]> wrote: >>> On Aug 14, 2012, at 2:32 PM, Richard Trieu <[email protected]> wrote: >>> >>>> At a high level, I honestly find this logic to be more complicated than I >>>> would have expected. The sorting seems unnecessary, and will report >>>> diagnostics in an unnatural order (first based on enum constant value, >>>> then on declaration order). A straight linear pass seems more naturally >>>> to me, and DenseMap is very efficient. >>>> Is there a comparison between the different containers in LLVM and the STL >>>> containers? >>> >>> This is a reasonable place to start: >>> >>> http://llvm.org/docs/ProgrammersManual.html#ds_map >>> >>> The key with DenseMap is that it is probed hashtable. There is one big >>> allocation for the entire table, instead of a bunch of buckets. When >>> applicable, it can be very fast, and feels like the right data structure to >>> use here. >>> >>> Duplicate enum detection, now with DenseMap. The DenseMap maps a int64_t >>> to a vector pointer. 0 and 1 were special keys for the DenseMap, so two >>> separate pointers special cased for them. The vectors pointers are stored >>> in another vector in declaration order. One pass is made over the enums to >>> find ones without initializers. These are used to create vectors. A >>> second pass through the enums populates the vectors. Finally, a pass over >>> the vector of vectors is used to generate all the warnings and notes. >>> >>> Run time is fairly consistent with the sorted vector implementation, which >>> is max %3 difference against control. >>> <duplicate-enum-densemap.patch> >> >> Thanks for working on this. My main concern is this patch now has a lot of >> unnecessary malloc() traffic, which will certainly slow it down. Comments >> inline: >> >>> + >>> +static int64_t GetInt64(const llvm::APSInt& Val) { >>> + return Val.isSigned() ? Val.getSExtValue() : Val.getZExtValue(); >>> +} >>> + >>> +struct DenseMapInfoint64_t { >>> + static int64_t getEmptyKey() { return 0; } >>> + static int64_t getTombstoneKey() { return 1; } >>> + static unsigned getHashValue(const int64_t Val) { >>> + return (unsigned)(Val * 37); >>> + } >>> + static bool isEqual(const int64_t& LHS, const int64_t& RHS) { >>> + return LHS == RHS; >>> + } >>> +}; >> >> This trait class doesn't look like it was actually used. The DenseMap below >> just uses the default trait for int64_t. >> >> I also still think we can so something a bit smarter here. What I think we >> need to distinguish between is whether or not a constant has appeared more >> than once. We're saving a bit of memory on the keys, but spending that >> savings elsewhere when we allocate the vectors unconditionally for each >> constant. >> >>> + >>> +// Emits a warning when an element is implicitly set a value that >>> +// a previous element has already been set to. >>> +static void CheckForDuplicateEnumValues(Sema &S, Decl **Elements, >>> + unsigned NumElements, EnumDecl >>> *Enum, >>> + QualType EnumType) { >>> + if (S.Diags.getDiagnosticLevel(diag::warn_duplicate_enum_values, >>> + Enum->getLocation()) == >>> + DiagnosticsEngine::Ignored) >>> + return; >>> + // Avoid anonymous enums >>> + if (!Enum->getIdentifier()) >>> + return; >>> + >>> + // Only check for small enums. >>> + if (Enum->getNumPositiveBits() > 63 || Enum->getNumNegativeBits() > 64) >>> + return; >>> + >>> + typedef llvm::SmallVector<EnumConstantDecl*, 4> SameValueVector; >>> + typedef llvm::DenseMap<int64_t, SameValueVector*> ValueToVectorMap; >>> + typedef llvm::SmallVector<SameValueVector*, 10> DoubleVector; >>> + ValueToVectorMap EnumMap; >>> + DoubleVector EnumVector; >>> + SameValueVector *ZeroVector = 0, *OneVector = 0; >> >> It took me a while to understand what this was doing, so I feel it could >> really benefit from a comment. This also appears to result in a ton of >> malloc traffic below. Here's my suggestion: >> >> typedef llvm::SmallVector<EnumConstantDecl*, 3> ECDVector; >> typedef llvm::SmallVector<ECDVector *, 3> DuplicatesVector; >> >> typedef llvm::PointerUnion<EnumConstantDecl*, ECDVector *> DeclOrVector; >> typedef llvm::DenseMap<int64_t, DeclOrVector> ValueToVectorMap; >> >> DuplicatesVector DupVector; >> ValueToVectorMap EnumMap; >> >> The trick here is that the DenseMap maps from a constant to the first >> EnumConstantDecl it encounters. Only if we encounter a second >> EnumConstantDecl with the same enum value do we pay the cost of allocating >> another vector. This will drastically optimize in the common case, as >> calling malloc() is really slow. Right now the code appears to be doing a >> malloc() for every enum constant, which is going to really penalize us here. >> >>> + >>> + for (unsigned i = 0; i < NumElements; ++i) { >>> + EnumConstantDecl *ECD = cast<EnumConstantDecl>(Elements[i]); >>> + if (!ECD) { >>> + for (DoubleVector::iterator I = EnumVector.begin(), E = >>> EnumVector.end(); >>> + I != E; ++I) >>> + delete *I; >>> + return; >>> + } >> >> I don't quite understand this loop through DoubleVector here, but it looks >> like logic in case we want to return early and cleanup. Is there a case >> where the EnumConstantDecl can be null? > > According to ActOnEnumBody, EnumConstantDecl is null if a diagnostic has > previously been emitted for the constant. Since the enum is possibly > ill-formed, skip checking it. >> >>> + >>> + if (ECD->getInitExpr()) >>> + continue; >>> + >>> + int64_t Val = GetInt64(ECD->getInitVal()); >>> + >> >> Looks good. >> >>> + if (Val == 0) { >>> + if (ZeroVector) continue; >>> + ZeroVector = new SameValueVector(); >>> + ZeroVector->push_back(ECD); >>> + EnumVector.push_back(ZeroVector); >>> + } else if (Val == 1) { >>> + if (OneVector) continue; >>> + OneVector = new SameValueVector(); >>> + OneVector->push_back(ECD); >>> + EnumVector.push_back(OneVector); >>> + } else { >>> + if (EnumMap.find(Val) != EnumMap.end()) >>> + continue; >>> + SameValueVector *ValueVector = new SameValueVector(); >>> + ValueVector->push_back(ECD); >>> + EnumVector.push_back(ValueVector); >>> + EnumMap.insert(std::make_pair(Val, ValueVector)); >> >> The "find()" followed by the "insert()" is wasteful. It results in two >> lookups to the hash table when we could have just used one. More on that >> later. >> >>> + } >>> + } >> >> IMO, this looks like a lot of complexity just to handle the fact that 0 and >> 1 are special values for the DenseMap. I don't really see this as the right >> tradeoff; the code is more complicated with marginal impact on memory usage >> or performance. >> >> If you humor me for a bit, consider using something else for the key, e.g.: >> >> struct DupKey { >> int64_t val; >> bool isTombstoneOrEmptyKey; >> }; >> >> The idea is if 'isTombStoneOrEmptyKey' is true, we can use val = 0 or val = >> 1 to represent empty keys or tombstone entries. Otherwise, it's an int64_t, >> with the full range of values. We can define a DenseMap trait to do the >> right thing. Yes, this costs a tiny bit more in storage, but it allows the >> data structure to handle the complete set of values in your domain, instead >> of resorting to complicating the core algorithm. What I see here now is the >> same code essentially duplicated twice, which makes it harder to read and >> more error prone. >> >> If we use DupKey as our key for the DenseMap, we can instead do something >> like this: >> >> DeclOrVector &entry = EnumMap[Val]; // Use default construction of >> 'entry'. >> // Is the first time we encountered this constant? >> if (entry.isNull()) { >> entry = ECD; >> continue; >> } >> // Is this the second time we encountered this constant? If so, >> // push the previous decl encountered and the one just encountered >> // to a vector of duplicates. >> if (EnumConstantDecl *D = entry.dyn_cast<EnumConstantDecl*>()) { >> ECDVector *Vec = new ECDVector(); >> Vec->push_back(D); >> Vec->push_back(ECD); >> >> // Update the entry to refer to the duplicates. >> entry = Vec; >> >> // Store the duplicates in a vector we can consult later for >> // quick emission of diagnostics. >> DupVector.push_back(Vec); >> >> // On to the next constant. >> continue; >> } >> // Is this the third (or greater) time we encountered the constant? If >> so, >> // continue to add it to the existing vector. >> ECDVector *Vec = entry.get<ECDVector*>(); >> Vec->push_back(ECD); >> >> >> With this code, we only allocate memory (beyond the DenseMap) when we >> encounter a duplicate that would be worth reporting. In the common case, >> this savings in malloc traffic should be noticeable. >> >> Notice also that I used: >> >> DeclOrVector &entry = EnumMap[Val]; // Use default construction of >> 'entry'. >> >> This results in a single lookup in the hashtable. Since we plan on adding a >> value for a key no matter what, by using this idiom we allow the DenseMap to >> default construct an entry if it doesn't exist. This results in a single >> hashtable lookup, from which we can modify the value in place. This is >> obviously faster than doing a hashtable lookup twice. >> >>> + >>> + for (unsigned i = 0; i < NumElements; ++i) { >>> + EnumConstantDecl *ECD = cast<EnumConstantDecl>(Elements[i]); >>> + if (!ValidDuplicateEnum(ECD, Enum)) >>> + continue; >>> + >>> + int64_t Val = GetInt64(ECD->getInitVal()); >>> + >>> + if (Val == 0) { >>> + if (!ZeroVector || *ZeroVector->begin() == ECD) >>> + continue; >>> + ZeroVector->push_back(ECD); >>> + } else if (Val == 1) { >>> + if (!OneVector || *OneVector->begin() == ECD) >>> + continue; >>> + OneVector->push_back(ECD); >>> + } else { >>> + ValueToVectorMap::iterator I = EnumMap.find(Val); >>> + if (I == EnumMap.end()) >>> + continue; >>> + SameValueVector *V = I->second; >>> + if (*V->begin() == ECD) >>> + continue; >>> + V->push_back(ECD); >>> + } >>> + } >> >> This second loop looks unnecessary. I think we can do everything we need to >> count duplicates with one loop. Of course the ValidDuplicateEnum() would >> need to be hoisted to the first loop. > > Using two traverses allows two things to happen. One, the first element in > the ECDVector will not have an initializer and will work with the warning. > Otherwise, the vector needs to be searched for a proper enum constant to use. > Two, it prevents unneeded creation of ECDVectors. If we have enum A { A1 = > 2, A2 = 2, A3 = 1, A4 = 1, A5}; vectors for values 1 and 2 are created using > a single pass while only a vector for 2 will be created using a double pass. >> >>> + >>> + for (DoubleVector::iterator DoubleVectorIter = EnumVector.begin(), >>> + DoubleVectorEnd = EnumVector.end(); >>> + DoubleVectorIter != DoubleVectorEnd; ++DoubleVectorIter) { >>> + SameValueVector *V = *DoubleVectorIter; >>> + if (V->size() == 1) >>> + continue; >>> + >>> + SameValueVector::iterator I = V->begin(); >>> + S.Diag((*I)->getLocation(), diag::warn_duplicate_enum_values) >>> + << (*I)->getName() << (*I)->getInitVal().toString(10) >>> + << (*I)->getSourceRange(); >>> + ++I; >>> + for (SameValueVector::iterator E = V->end(); I != E; ++I) >>> + S.Diag((*I)->getLocation(), diag::note_duplicate_element) >>> + << (*I)->getName() << (*I)->getInitVal().toString(10) >>> + << (*I)->getSourceRange(); >>> + delete V; >>> + } >> >> >> This is more or less the same, essentially it becomes: >> >> for (DuplicateVector::iterator I = DupVector.begin(), E = DupVector.end(); I >> != E; ++I) { >> ECDVector *Vec = *I; >> // do the diagnostic logic ... >> delete *I; >> } >> >> Note that with my suggestions the vector has size on order of the number of >> duplicate constants, not the number of total constants. If there are no >> duplicates, no work is required (including free'ing memory). >> >>> +} >>> + >>> void Sema::ActOnEnumBody(SourceLocation EnumLoc, SourceLocation LBraceLoc, >>> SourceLocation RBraceLoc, Decl *EnumDeclX, >>> Decl **Elements, unsigned NumElements, >>> @@ -10709,6 +10868,7 @@ >>> DeclsInPrototypeScope.push_back(Enum); >>> >>> CheckForUniqueEnumValues(*this, Elements, NumElements, Enum, EnumType); >>> + CheckForDuplicateEnumValues(*this, Elements, NumElements, Enum, >>> EnumType); >>> } >>> >>> Decl *Sema::ActOnFileScopeAsmDecl(Expr *expr, >> >> I know this may all be nit-picky, but I really think trying to reduce the >> malloc() traffic is worth looking at to get a real understanding of the >> performance improvement that can be found here. >> >> Thanks for forging ahead on this. >> _______________________________________________ >> cfe-commits mailing list >> [email protected] >> http://lists.cs.uiuc.edu/mailman/listinfo/cfe-commits > > > <duplicate-enum-densemap2.patch>
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