On Tue, Aug 28, 2012 at 6:21 PM, Ted Kremenek <[email protected]> wrote:
> Hi Richard, > > If I read these numbers correctly, the hash table algorithm (with O(n) > performance) takes about 1.6-2% percent more than the control for runs 1-3, > and hardly anything noticeable for the clang code base. Were runs 1-3 used > in your earlier measurements, > Yes, these are the same runs I have been using. I earlier did some more runs with smaller files, but the improvements to this warning made the differences too small to detect, so they were dropped. > where the sorting-based approach took about ~4% longer (or is that not the > correct number)? > That is correct. The fastest sorting-based reached 4% difference. > Just wanted an idea of where we are compared to the earlier measurements. > > Ted > > On Aug 28, 2012, at 3:53 PM, Richard Trieu <[email protected]> wrote: > > Timing information: > Three clangs were run, clang with no changes (control), duplicate enum > with PointerUnion (most recent patch), duplicate enum with DenseMap without > PointerUnion (next most recent patch). Each run with -fsyntax-only and > -Wduplicate-enum for modified clangs. Runs 1, 2, and 3 are files with only > enums. Run 4 is a preprocessed Clang. > > Key: > name: Average (Min-Max) > > Run1: > Control: 13.763 (13.66-14.14) > PointerUnion: 14.046 (13.94-14.16) > DenseMap: 14.304 (14.24-14.39) > > Run2: > Control: 20.189 (20.1-20.31) > PointerUnion: 20.514 (20.37-20.6) > DenseMap: 20.635 (20.56-20.7) > > Run3: > Control: 26.715 (26.66-26.8) > PointerUnion: 26.928 (26.8-27.12) > DenseMap: 27.13 (27.05-27.22) > > Run4: > Control: 29.686 (28.98-30.39) > PointerUnion: 29.706 (28.73-30.69) > DenseMap: 29.952 (29.3-30.63) > > On Tue, Aug 28, 2012 at 2:12 PM, Ted Kremenek <[email protected]> wrote: > >> How fast? (particularly compared to the first implementation, and >> relative to -fsyntax-only) >> >> On Aug 28, 2012, at 11:48 AM, Richard Trieu <[email protected]> wrote: >> >> New patch with PointerUnion and DenseMap is slightly faster than the >> previous DenseMap patch. >> >> On Mon, Aug 27, 2012 at 9:51 PM, Ted Kremenek <[email protected]> wrote: >> >>> 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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