2016-10-05 22:58:47 +02:00
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// Copyright (c) 2016 Jeremy Rubin
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// Distributed under the MIT software license, see the accompanying
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// file COPYING or http://www.opensource.org/licenses/mit-license.php.
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2017-08-26 01:56:53 +02:00
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#ifndef BITCOIN_CUCKOOCACHE_H
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#define BITCOIN_CUCKOOCACHE_H
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2016-10-05 22:58:47 +02:00
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#include <array>
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#include <atomic>
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#include <cmath>
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2019-11-29 20:18:24 +01:00
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#include <cstring>
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2016-10-05 22:58:47 +02:00
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#include <memory>
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2019-11-29 20:18:24 +01:00
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#include <utility>
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2016-10-05 22:58:47 +02:00
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#include <vector>
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/** namespace CuckooCache provides high performance cache primitives
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*
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* Summary:
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*
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* 1) bit_packed_atomic_flags is bit-packed atomic flags for garbage collection
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*
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* 2) cache is a cache which is performant in memory usage and lookup speed. It
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* is lockfree for erase operations. Elements are lazily erased on the next
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* insert.
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*/
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namespace CuckooCache
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{
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/** bit_packed_atomic_flags implements a container for garbage collection flags
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* that is only thread unsafe on calls to setup. This class bit-packs collection
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* flags for memory efficiency.
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*
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* All operations are std::memory_order_relaxed so external mechanisms must
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* ensure that writes and reads are properly synchronized.
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*
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* On setup(n), all bits up to n are marked as collected.
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*
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* Under the hood, because it is an 8-bit type, it makes sense to use a multiple
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* of 8 for setup, but it will be safe if that is not the case as well.
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*
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*/
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class bit_packed_atomic_flags
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{
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std::unique_ptr<std::atomic<uint8_t>[]> mem;
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public:
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/** No default constructor as there must be some size */
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bit_packed_atomic_flags() = delete;
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/**
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* bit_packed_atomic_flags constructor creates memory to sufficiently
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* keep track of garbage collection information for size entries.
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*
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* @param size the number of elements to allocate space for
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*
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* @post bit_set, bit_unset, and bit_is_set function properly forall x. x <
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* size
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* @post All calls to bit_is_set (without subsequent bit_unset) will return
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* true.
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*/
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2017-08-01 12:22:41 +02:00
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explicit bit_packed_atomic_flags(uint32_t size)
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2016-10-05 22:58:47 +02:00
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{
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// pad out the size if needed
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size = (size + 7) / 8;
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mem.reset(new std::atomic<uint8_t>[size]);
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for (uint32_t i = 0; i < size; ++i)
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mem[i].store(0xFF);
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};
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/** setup marks all entries and ensures that bit_packed_atomic_flags can store
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* at least size entries
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*
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* @param b the number of elements to allocate space for
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* @post bit_set, bit_unset, and bit_is_set function properly forall x. x <
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* b
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* @post All calls to bit_is_set (without subsequent bit_unset) will return
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* true.
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*/
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inline void setup(uint32_t b)
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{
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bit_packed_atomic_flags d(b);
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std::swap(mem, d.mem);
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}
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/** bit_set sets an entry as discardable.
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*
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* @param s the index of the entry to bit_set.
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* @post immediately subsequent call (assuming proper external memory
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* ordering) to bit_is_set(s) == true.
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*
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*/
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inline void bit_set(uint32_t s)
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{
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mem[s >> 3].fetch_or(1 << (s & 7), std::memory_order_relaxed);
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}
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/** bit_unset marks an entry as something that should not be overwritten
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*
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* @param s the index of the entry to bit_unset.
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* @post immediately subsequent call (assuming proper external memory
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* ordering) to bit_is_set(s) == false.
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*/
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inline void bit_unset(uint32_t s)
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{
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mem[s >> 3].fetch_and(~(1 << (s & 7)), std::memory_order_relaxed);
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}
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/** bit_is_set queries the table for discardability at s
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*
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* @param s the index of the entry to read.
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* @returns if the bit at index s was set.
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* */
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inline bool bit_is_set(uint32_t s) const
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{
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return (1 << (s & 7)) & mem[s >> 3].load(std::memory_order_relaxed);
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}
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};
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/** cache implements a cache with properties similar to a cuckoo-set
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*
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* The cache is able to hold up to (~(uint32_t)0) - 1 elements.
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*
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* Read Operations:
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* - contains(*, false)
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*
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* Read+Erase Operations:
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* - contains(*, true)
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*
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* Erase Operations:
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* - allow_erase()
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*
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* Write Operations:
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* - setup()
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* - setup_bytes()
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* - insert()
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* - please_keep()
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*
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* Synchronization Free Operations:
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* - invalid()
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* - compute_hashes()
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*
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* User Must Guarantee:
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*
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* 1) Write Requires synchronized access (e.g., a lock)
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* 2) Read Requires no concurrent Write, synchronized with the last insert.
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* 3) Erase requires no concurrent Write, synchronized with last insert.
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* 4) An Erase caller must release all memory before allowing a new Writer.
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*
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*
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* Note on function names:
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* - The name "allow_erase" is used because the real discard happens later.
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* - The name "please_keep" is used because elements may be erased anyways on insert.
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*
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* @tparam Element should be a movable and copyable type
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* @tparam Hash should be a function/callable which takes a template parameter
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* hash_select and an Element and extracts a hash from it. Should return
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2017-01-12 19:16:31 +01:00
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* high-entropy uint32_t hashes for `Hash h; h<0>(e) ... h<7>(e)`.
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2016-10-05 22:58:47 +02:00
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*/
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template <typename Element, typename Hash>
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class cache
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{
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private:
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/** table stores all the elements */
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std::vector<Element> table;
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/** size stores the total available slots in the hash table */
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uint32_t size;
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/** The bit_packed_atomic_flags array is marked mutable because we want
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* garbage collection to be allowed to occur from const methods */
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mutable bit_packed_atomic_flags collection_flags;
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/** epoch_flags tracks how recently an element was inserted into
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* the cache. true denotes recent, false denotes not-recent. See insert()
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* method for full semantics.
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*/
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mutable std::vector<bool> epoch_flags;
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2017-06-20 00:57:31 +02:00
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/** epoch_heuristic_counter is used to determine when an epoch might be aged
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2016-10-05 22:58:47 +02:00
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* & an expensive scan should be done. epoch_heuristic_counter is
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* decremented on insert and reset to the new number of inserts which would
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* cause the epoch to reach epoch_size when it reaches zero.
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*/
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uint32_t epoch_heuristic_counter;
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/** epoch_size is set to be the number of elements supposed to be in a
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2017-06-20 00:57:31 +02:00
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* epoch. When the number of non-erased elements in an epoch
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2016-10-05 22:58:47 +02:00
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* exceeds epoch_size, a new epoch should be started and all
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* current entries demoted. epoch_size is set to be 45% of size because
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* we want to keep load around 90%, and we support 3 epochs at once --
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* one "dead" which has been erased, one "dying" which has been marked to be
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* erased next, and one "living" which new inserts add to.
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*/
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uint32_t epoch_size;
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/** depth_limit determines how many elements insert should try to replace.
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* Should be set to log2(n)*/
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uint8_t depth_limit;
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/** hash_function is a const instance of the hash function. It cannot be
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* static or initialized at call time as it may have internal state (such as
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* a nonce).
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* */
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const Hash hash_function;
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/** compute_hashes is convenience for not having to write out this
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* expression everywhere we use the hash values of an Element.
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*
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2017-06-12 01:39:04 +02:00
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* We need to map the 32-bit input hash onto a hash bucket in a range [0, size) in a
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* manner which preserves as much of the hash's uniformity as possible. Ideally
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* this would be done by bitmasking but the size is usually not a power of two.
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*
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* The naive approach would be to use a mod -- which isn't perfectly uniform but so
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* long as the hash is much larger than size it is not that bad. Unfortunately,
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* mod/division is fairly slow on ordinary microprocessors (e.g. 90-ish cycles on
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* haswell, ARM doesn't even have an instruction for it.); when the divisor is a
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* constant the compiler will do clever tricks to turn it into a multiply+add+shift,
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* but size is a run-time value so the compiler can't do that here.
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*
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* One option would be to implement the same trick the compiler uses and compute the
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* constants for exact division based on the size, as described in "{N}-bit Unsigned
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* Division via {N}-bit Multiply-Add" by Arch D. Robison in 2005. But that code is
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* somewhat complicated and the result is still slower than other options:
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*
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* Instead we treat the 32-bit random number as a Q32 fixed-point number in the range
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* [0,1) and simply multiply it by the size. Then we just shift the result down by
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2018-03-18 15:26:45 +01:00
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* 32-bits to get our bucket number. The result has non-uniformity the same as a
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2017-06-12 01:39:04 +02:00
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* mod, but it is much faster to compute. More about this technique can be found at
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* http://lemire.me/blog/2016/06/27/a-fast-alternative-to-the-modulo-reduction/
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*
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* The resulting non-uniformity is also more equally distributed which would be
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* advantageous for something like linear probing, though it shouldn't matter
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* one way or the other for a cuckoo table.
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*
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* The primary disadvantage of this approach is increased intermediate precision is
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* required but for a 32-bit random number we only need the high 32 bits of a
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* 32*32->64 multiply, which means the operation is reasonably fast even on a
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* typical 32-bit processor.
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*
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2016-10-05 22:58:47 +02:00
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* @param e the element whose hashes will be returned
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* @returns std::array<uint32_t, 8> of deterministic hashes derived from e
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*/
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inline std::array<uint32_t, 8> compute_hashes(const Element& e) const
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{
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2018-03-27 00:37:20 +02:00
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return {{(uint32_t)(((uint64_t)hash_function.template operator()<0>(e) * (uint64_t)size) >> 32),
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(uint32_t)(((uint64_t)hash_function.template operator()<1>(e) * (uint64_t)size) >> 32),
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(uint32_t)(((uint64_t)hash_function.template operator()<2>(e) * (uint64_t)size) >> 32),
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(uint32_t)(((uint64_t)hash_function.template operator()<3>(e) * (uint64_t)size) >> 32),
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(uint32_t)(((uint64_t)hash_function.template operator()<4>(e) * (uint64_t)size) >> 32),
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(uint32_t)(((uint64_t)hash_function.template operator()<5>(e) * (uint64_t)size) >> 32),
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(uint32_t)(((uint64_t)hash_function.template operator()<6>(e) * (uint64_t)size) >> 32),
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(uint32_t)(((uint64_t)hash_function.template operator()<7>(e) * (uint64_t)size) >> 32)}};
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2016-10-05 22:58:47 +02:00
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}
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/* end
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* @returns a constexpr index that can never be inserted to */
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constexpr uint32_t invalid() const
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{
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return ~(uint32_t)0;
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}
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/** allow_erase marks the element at index n as discardable. Threadsafe
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* without any concurrent insert.
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* @param n the index to allow erasure of
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*/
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inline void allow_erase(uint32_t n) const
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{
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collection_flags.bit_set(n);
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}
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/** please_keep marks the element at index n as an entry that should be kept.
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* Threadsafe without any concurrent insert.
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* @param n the index to prioritize keeping
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*/
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inline void please_keep(uint32_t n) const
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{
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collection_flags.bit_unset(n);
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}
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/** epoch_check handles the changing of epochs for elements stored in the
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* cache. epoch_check should be run before every insert.
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*
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* First, epoch_check decrements and checks the cheap heuristic, and then does
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* a more expensive scan if the cheap heuristic runs out. If the expensive
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2017-01-18 16:15:37 +01:00
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* scan succeeds, the epochs are aged and old elements are allow_erased. The
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2016-10-05 22:58:47 +02:00
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* cheap heuristic is reset to retrigger after the worst case growth of the
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* current epoch's elements would exceed the epoch_size.
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*/
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void epoch_check()
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{
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if (epoch_heuristic_counter != 0) {
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--epoch_heuristic_counter;
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return;
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}
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// count the number of elements from the latest epoch which
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// have not been erased.
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uint32_t epoch_unused_count = 0;
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for (uint32_t i = 0; i < size; ++i)
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epoch_unused_count += epoch_flags[i] &&
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!collection_flags.bit_is_set(i);
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// If there are more non-deleted entries in the current epoch than the
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// epoch size, then allow_erase on all elements in the old epoch (marked
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// false) and move all elements in the current epoch to the old epoch
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// but do not call allow_erase on their indices.
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if (epoch_unused_count >= epoch_size) {
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for (uint32_t i = 0; i < size; ++i)
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if (epoch_flags[i])
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epoch_flags[i] = false;
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else
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allow_erase(i);
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epoch_heuristic_counter = epoch_size;
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} else
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// reset the epoch_heuristic_counter to next do a scan when worst
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// case behavior (no intermittent erases) would exceed epoch size,
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// with a reasonable minimum scan size.
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// Ordinarily, we would have to sanity check std::min(epoch_size,
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// epoch_unused_count), but we already know that `epoch_unused_count
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// < epoch_size` in this branch
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epoch_heuristic_counter = std::max(1u, std::max(epoch_size / 16,
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epoch_size - epoch_unused_count));
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}
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public:
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/** You must always construct a cache with some elements via a subsequent
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* call to setup or setup_bytes, otherwise operations may segfault.
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*/
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cache() : table(), size(), collection_flags(0), epoch_flags(),
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epoch_heuristic_counter(), epoch_size(), depth_limit(0), hash_function()
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{
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}
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/** setup initializes the container to store no more than new_size
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2017-01-12 19:16:31 +01:00
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* elements.
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2016-10-05 22:58:47 +02:00
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*
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* setup should only be called once.
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*
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* @param new_size the desired number of elements to store
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* @returns the maximum number of elements storable
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**/
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uint32_t setup(uint32_t new_size)
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{
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// depth_limit must be at least one otherwise errors can occur.
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depth_limit = static_cast<uint8_t>(std::log2(static_cast<float>(std::max((uint32_t)2, new_size))));
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2017-01-12 19:16:31 +01:00
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size = std::max<uint32_t>(2, new_size);
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2016-10-05 22:58:47 +02:00
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table.resize(size);
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collection_flags.setup(size);
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epoch_flags.resize(size);
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// Set to 45% as described above
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epoch_size = std::max((uint32_t)1, (45 * size) / 100);
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// Initially set to wait for a whole epoch
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epoch_heuristic_counter = epoch_size;
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return size;
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}
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/** setup_bytes is a convenience function which accounts for internal memory
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* usage when deciding how many elements to store. It isn't perfect because
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* it doesn't account for any overhead (struct size, MallocUsage, collection
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* and epoch flags). This was done to simplify selecting a power of two
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* size. In the expected use case, an extra two bits per entry should be
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* negligible compared to the size of the elements.
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*
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* @param bytes the approximate number of bytes to use for this data
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* structure.
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* @returns the maximum number of elements storable (see setup()
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* documentation for more detail)
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*/
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uint32_t setup_bytes(size_t bytes)
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{
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return setup(bytes/sizeof(Element));
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}
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/** insert loops at most depth_limit times trying to insert a hash
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* at various locations in the table via a variant of the Cuckoo Algorithm
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* with eight hash locations.
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*
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* It drops the last tried element if it runs out of depth before
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* encountering an open slot.
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*
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* Thus
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*
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* insert(x);
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* return contains(x, false);
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*
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* is not guaranteed to return true.
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*
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* @param e the element to insert
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* @post one of the following: All previously inserted elements and e are
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* now in the table, one previously inserted element is evicted from the
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* table, the entry attempted to be inserted is evicted.
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*
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*/
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inline void insert(Element e)
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{
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epoch_check();
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uint32_t last_loc = invalid();
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bool last_epoch = true;
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std::array<uint32_t, 8> locs = compute_hashes(e);
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// Make sure we have not already inserted this element
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// If we have, make sure that it does not get deleted
|
2018-06-18 07:58:28 +02:00
|
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for (const uint32_t loc : locs)
|
2016-10-05 22:58:47 +02:00
|
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if (table[loc] == e) {
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please_keep(loc);
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epoch_flags[loc] = last_epoch;
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|
return;
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|
}
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|
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|
for (uint8_t depth = 0; depth < depth_limit; ++depth) {
|
|
|
|
// First try to insert to an empty slot, if one exists
|
2018-06-18 07:58:28 +02:00
|
|
|
for (const uint32_t loc : locs) {
|
2016-10-05 22:58:47 +02:00
|
|
|
if (!collection_flags.bit_is_set(loc))
|
|
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|
continue;
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|
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table[loc] = std::move(e);
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|
|
|
please_keep(loc);
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epoch_flags[loc] = last_epoch;
|
|
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|
return;
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|
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|
}
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|
/** Swap with the element at the location that was
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* not the last one looked at. Example:
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*
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|
* 1) On first iteration, last_loc == invalid(), find returns last, so
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* last_loc defaults to locs[0].
|
|
|
|
* 2) On further iterations, where last_loc == locs[k], last_loc will
|
2017-01-18 16:15:37 +01:00
|
|
|
* go to locs[k+1 % 8], i.e., next of the 8 indices wrapping around
|
2016-10-05 22:58:47 +02:00
|
|
|
* to 0 if needed.
|
|
|
|
*
|
|
|
|
* This prevents moving the element we just put in.
|
|
|
|
*
|
|
|
|
* The swap is not a move -- we must switch onto the evicted element
|
|
|
|
* for the next iteration.
|
|
|
|
*/
|
|
|
|
last_loc = locs[(1 + (std::find(locs.begin(), locs.end(), last_loc) - locs.begin())) & 7];
|
|
|
|
std::swap(table[last_loc], e);
|
|
|
|
// Can't std::swap a std::vector<bool>::reference and a bool&.
|
|
|
|
bool epoch = last_epoch;
|
|
|
|
last_epoch = epoch_flags[last_loc];
|
|
|
|
epoch_flags[last_loc] = epoch;
|
|
|
|
|
|
|
|
// Recompute the locs -- unfortunately happens one too many times!
|
|
|
|
locs = compute_hashes(e);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
/* contains iterates through the hash locations for a given element
|
|
|
|
* and checks to see if it is present.
|
|
|
|
*
|
|
|
|
* contains does not check garbage collected state (in other words,
|
|
|
|
* garbage is only collected when the space is needed), so:
|
|
|
|
*
|
|
|
|
* insert(x);
|
|
|
|
* if (contains(x, true))
|
|
|
|
* return contains(x, false);
|
|
|
|
* else
|
|
|
|
* return true;
|
|
|
|
*
|
|
|
|
* executed on a single thread will always return true!
|
|
|
|
*
|
|
|
|
* This is a great property for re-org performance for example.
|
|
|
|
*
|
|
|
|
* contains returns a bool set true if the element was found.
|
|
|
|
*
|
|
|
|
* @param e the element to check
|
|
|
|
* @param erase
|
|
|
|
*
|
|
|
|
* @post if erase is true and the element is found, then the garbage collect
|
|
|
|
* flag is set
|
|
|
|
* @returns true if the element is found, false otherwise
|
|
|
|
*/
|
|
|
|
inline bool contains(const Element& e, const bool erase) const
|
|
|
|
{
|
|
|
|
std::array<uint32_t, 8> locs = compute_hashes(e);
|
2018-06-18 07:58:28 +02:00
|
|
|
for (const uint32_t loc : locs)
|
2016-10-05 22:58:47 +02:00
|
|
|
if (table[loc] == e) {
|
|
|
|
if (erase)
|
|
|
|
allow_erase(loc);
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
};
|
|
|
|
} // namespace CuckooCache
|
|
|
|
|
2017-08-26 01:56:53 +02:00
|
|
|
#endif // BITCOIN_CUCKOOCACHE_H
|