[InstCombine] Signed saturation patterns
[llvm-core.git] / include / llvm / ADT / SparseSet.h
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1 //===- llvm/ADT/SparseSet.h - Sparse set ------------------------*- C++ -*-===//
2 //
3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
4 // See https://llvm.org/LICENSE.txt for license information.
5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
6 //
7 //===----------------------------------------------------------------------===//
8 //
9 // This file defines the SparseSet class derived from the version described in
10 // Briggs, Torczon, "An efficient representation for sparse sets", ACM Letters
11 // on Programming Languages and Systems, Volume 2 Issue 1-4, March-Dec. 1993.
13 // A sparse set holds a small number of objects identified by integer keys from
14 // a moderately sized universe. The sparse set uses more memory than other
15 // containers in order to provide faster operations.
17 //===----------------------------------------------------------------------===//
19 #ifndef LLVM_ADT_SPARSESET_H
20 #define LLVM_ADT_SPARSESET_H
22 #include "llvm/ADT/STLExtras.h"
23 #include "llvm/ADT/SmallVector.h"
24 #include "llvm/Support/Allocator.h"
25 #include <cassert>
26 #include <cstdint>
27 #include <cstdlib>
28 #include <limits>
29 #include <utility>
31 namespace llvm {
33 /// SparseSetValTraits - Objects in a SparseSet are identified by keys that can
34 /// be uniquely converted to a small integer less than the set's universe. This
35 /// class allows the set to hold values that differ from the set's key type as
36 /// long as an index can still be derived from the value. SparseSet never
37 /// directly compares ValueT, only their indices, so it can map keys to
38 /// arbitrary values. SparseSetValTraits computes the index from the value
39 /// object. To compute the index from a key, SparseSet uses a separate
40 /// KeyFunctorT template argument.
41 ///
42 /// A simple type declaration, SparseSet<Type>, handles these cases:
43 /// - unsigned key, identity index, identity value
44 /// - unsigned key, identity index, fat value providing getSparseSetIndex()
45 ///
46 /// The type declaration SparseSet<Type, UnaryFunction> handles:
47 /// - unsigned key, remapped index, identity value (virtual registers)
48 /// - pointer key, pointer-derived index, identity value (node+ID)
49 /// - pointer key, pointer-derived index, fat value with getSparseSetIndex()
50 ///
51 /// Only other, unexpected cases require specializing SparseSetValTraits.
52 ///
53 /// For best results, ValueT should not require a destructor.
54 ///
55 template<typename ValueT>
56 struct SparseSetValTraits {
57 static unsigned getValIndex(const ValueT &Val) {
58 return Val.getSparseSetIndex();
62 /// SparseSetValFunctor - Helper class for selecting SparseSetValTraits. The
63 /// generic implementation handles ValueT classes which either provide
64 /// getSparseSetIndex() or specialize SparseSetValTraits<>.
65 ///
66 template<typename KeyT, typename ValueT, typename KeyFunctorT>
67 struct SparseSetValFunctor {
68 unsigned operator()(const ValueT &Val) const {
69 return SparseSetValTraits<ValueT>::getValIndex(Val);
73 /// SparseSetValFunctor<KeyT, KeyT> - Helper class for the common case of
74 /// identity key/value sets.
75 template<typename KeyT, typename KeyFunctorT>
76 struct SparseSetValFunctor<KeyT, KeyT, KeyFunctorT> {
77 unsigned operator()(const KeyT &Key) const {
78 return KeyFunctorT()(Key);
82 /// SparseSet - Fast set implmentation for objects that can be identified by
83 /// small unsigned keys.
84 ///
85 /// SparseSet allocates memory proportional to the size of the key universe, so
86 /// it is not recommended for building composite data structures. It is useful
87 /// for algorithms that require a single set with fast operations.
88 ///
89 /// Compared to DenseSet and DenseMap, SparseSet provides constant-time fast
90 /// clear() and iteration as fast as a vector. The find(), insert(), and
91 /// erase() operations are all constant time, and typically faster than a hash
92 /// table. The iteration order doesn't depend on numerical key values, it only
93 /// depends on the order of insert() and erase() operations. When no elements
94 /// have been erased, the iteration order is the insertion order.
95 ///
96 /// Compared to BitVector, SparseSet<unsigned> uses 8x-40x more memory, but
97 /// offers constant-time clear() and size() operations as well as fast
98 /// iteration independent on the size of the universe.
99 ///
100 /// SparseSet contains a dense vector holding all the objects and a sparse
101 /// array holding indexes into the dense vector. Most of the memory is used by
102 /// the sparse array which is the size of the key universe. The SparseT
103 /// template parameter provides a space/speed tradeoff for sets holding many
104 /// elements.
106 /// When SparseT is uint32_t, find() only touches 2 cache lines, but the sparse
107 /// array uses 4 x Universe bytes.
109 /// When SparseT is uint8_t (the default), find() touches up to 2+[N/256] cache
110 /// lines, but the sparse array is 4x smaller. N is the number of elements in
111 /// the set.
113 /// For sets that may grow to thousands of elements, SparseT should be set to
114 /// uint16_t or uint32_t.
116 /// @tparam ValueT The type of objects in the set.
117 /// @tparam KeyFunctorT A functor that computes an unsigned index from KeyT.
118 /// @tparam SparseT An unsigned integer type. See above.
120 template<typename ValueT,
121 typename KeyFunctorT = identity<unsigned>,
122 typename SparseT = uint8_t>
123 class SparseSet {
124 static_assert(std::numeric_limits<SparseT>::is_integer &&
125 !std::numeric_limits<SparseT>::is_signed,
126 "SparseT must be an unsigned integer type");
128 using KeyT = typename KeyFunctorT::argument_type;
129 using DenseT = SmallVector<ValueT, 8>;
130 using size_type = unsigned;
131 DenseT Dense;
132 SparseT *Sparse = nullptr;
133 unsigned Universe = 0;
134 KeyFunctorT KeyIndexOf;
135 SparseSetValFunctor<KeyT, ValueT, KeyFunctorT> ValIndexOf;
137 public:
138 using value_type = ValueT;
139 using reference = ValueT &;
140 using const_reference = const ValueT &;
141 using pointer = ValueT *;
142 using const_pointer = const ValueT *;
144 SparseSet() = default;
145 SparseSet(const SparseSet &) = delete;
146 SparseSet &operator=(const SparseSet &) = delete;
147 ~SparseSet() { free(Sparse); }
149 /// setUniverse - Set the universe size which determines the largest key the
150 /// set can hold. The universe must be sized before any elements can be
151 /// added.
153 /// @param U Universe size. All object keys must be less than U.
155 void setUniverse(unsigned U) {
156 // It's not hard to resize the universe on a non-empty set, but it doesn't
157 // seem like a likely use case, so we can add that code when we need it.
158 assert(empty() && "Can only resize universe on an empty map");
159 // Hysteresis prevents needless reallocations.
160 if (U >= Universe/4 && U <= Universe)
161 return;
162 free(Sparse);
163 // The Sparse array doesn't actually need to be initialized, so malloc
164 // would be enough here, but that will cause tools like valgrind to
165 // complain about branching on uninitialized data.
166 Sparse = static_cast<SparseT*>(safe_calloc(U, sizeof(SparseT)));
167 Universe = U;
170 // Import trivial vector stuff from DenseT.
171 using iterator = typename DenseT::iterator;
172 using const_iterator = typename DenseT::const_iterator;
174 const_iterator begin() const { return Dense.begin(); }
175 const_iterator end() const { return Dense.end(); }
176 iterator begin() { return Dense.begin(); }
177 iterator end() { return Dense.end(); }
179 /// empty - Returns true if the set is empty.
181 /// This is not the same as BitVector::empty().
183 bool empty() const { return Dense.empty(); }
185 /// size - Returns the number of elements in the set.
187 /// This is not the same as BitVector::size() which returns the size of the
188 /// universe.
190 size_type size() const { return Dense.size(); }
192 /// clear - Clears the set. This is a very fast constant time operation.
194 void clear() {
195 // Sparse does not need to be cleared, see find().
196 Dense.clear();
199 /// findIndex - Find an element by its index.
201 /// @param Idx A valid index to find.
202 /// @returns An iterator to the element identified by key, or end().
204 iterator findIndex(unsigned Idx) {
205 assert(Idx < Universe && "Key out of range");
206 const unsigned Stride = std::numeric_limits<SparseT>::max() + 1u;
207 for (unsigned i = Sparse[Idx], e = size(); i < e; i += Stride) {
208 const unsigned FoundIdx = ValIndexOf(Dense[i]);
209 assert(FoundIdx < Universe && "Invalid key in set. Did object mutate?");
210 if (Idx == FoundIdx)
211 return begin() + i;
212 // Stride is 0 when SparseT >= unsigned. We don't need to loop.
213 if (!Stride)
214 break;
216 return end();
219 /// find - Find an element by its key.
221 /// @param Key A valid key to find.
222 /// @returns An iterator to the element identified by key, or end().
224 iterator find(const KeyT &Key) {
225 return findIndex(KeyIndexOf(Key));
228 const_iterator find(const KeyT &Key) const {
229 return const_cast<SparseSet*>(this)->findIndex(KeyIndexOf(Key));
232 /// count - Returns 1 if this set contains an element identified by Key,
233 /// 0 otherwise.
235 size_type count(const KeyT &Key) const {
236 return find(Key) == end() ? 0 : 1;
239 /// insert - Attempts to insert a new element.
241 /// If Val is successfully inserted, return (I, true), where I is an iterator
242 /// pointing to the newly inserted element.
244 /// If the set already contains an element with the same key as Val, return
245 /// (I, false), where I is an iterator pointing to the existing element.
247 /// Insertion invalidates all iterators.
249 std::pair<iterator, bool> insert(const ValueT &Val) {
250 unsigned Idx = ValIndexOf(Val);
251 iterator I = findIndex(Idx);
252 if (I != end())
253 return std::make_pair(I, false);
254 Sparse[Idx] = size();
255 Dense.push_back(Val);
256 return std::make_pair(end() - 1, true);
259 /// array subscript - If an element already exists with this key, return it.
260 /// Otherwise, automatically construct a new value from Key, insert it,
261 /// and return the newly inserted element.
262 ValueT &operator[](const KeyT &Key) {
263 return *insert(ValueT(Key)).first;
266 ValueT pop_back_val() {
267 // Sparse does not need to be cleared, see find().
268 return Dense.pop_back_val();
271 /// erase - Erases an existing element identified by a valid iterator.
273 /// This invalidates all iterators, but erase() returns an iterator pointing
274 /// to the next element. This makes it possible to erase selected elements
275 /// while iterating over the set:
277 /// for (SparseSet::iterator I = Set.begin(); I != Set.end();)
278 /// if (test(*I))
279 /// I = Set.erase(I);
280 /// else
281 /// ++I;
283 /// Note that end() changes when elements are erased, unlike std::list.
285 iterator erase(iterator I) {
286 assert(unsigned(I - begin()) < size() && "Invalid iterator");
287 if (I != end() - 1) {
288 *I = Dense.back();
289 unsigned BackIdx = ValIndexOf(Dense.back());
290 assert(BackIdx < Universe && "Invalid key in set. Did object mutate?");
291 Sparse[BackIdx] = I - begin();
293 // This depends on SmallVector::pop_back() not invalidating iterators.
294 // std::vector::pop_back() doesn't give that guarantee.
295 Dense.pop_back();
296 return I;
299 /// erase - Erases an element identified by Key, if it exists.
301 /// @param Key The key identifying the element to erase.
302 /// @returns True when an element was erased, false if no element was found.
304 bool erase(const KeyT &Key) {
305 iterator I = find(Key);
306 if (I == end())
307 return false;
308 erase(I);
309 return true;
313 } // end namespace llvm
315 #endif // LLVM_ADT_SPARSESET_H