Browse Source
0.1467dac4eAdd unit tests for the CuckooCache (Jeremy Rubin)c9e69fbAdd CuckooCache implementation and replace the sigcache map_type with it (Jeremy Rubin)
Pieter Wuille
8 years ago
7 changed files with 901 additions and 41 deletions
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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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#ifndef _BITCOIN_CUCKOOCACHE_H_ |
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#define _BITCOIN_CUCKOOCACHE_H_ |
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#include <array> |
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#include <algorithm> |
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#include <atomic> |
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#include <cstring> |
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#include <cmath> |
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#include <memory> |
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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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bit_packed_atomic_flags(uint32_t size) |
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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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* high-entropy hashes for `Hash h; h<0>(e) ... h<7>(e)`. |
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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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/** epoch_heuristic_counter is used to determine when a epoch might be aged
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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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* epoch. When the number of non-erased elements in a epoch |
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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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/** hash_mask should be set to appropriately mask out a hash such that every
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* masked hash is [0,size), eg, if floor(log2(size)) == 20, then hash_mask |
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* should be (1<<20)-1 |
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*/ |
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uint32_t hash_mask; |
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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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* @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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return {{hash_function.template operator()<0>(e) & hash_mask, |
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hash_function.template operator()<1>(e) & hash_mask, |
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hash_function.template operator()<2>(e) & hash_mask, |
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hash_function.template operator()<3>(e) & hash_mask, |
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hash_function.template operator()<4>(e) & hash_mask, |
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hash_function.template operator()<5>(e) & hash_mask, |
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hash_function.template operator()<6>(e) & hash_mask, |
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hash_function.template operator()<7>(e) & hash_mask}}; |
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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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* scan suceeds, the epochs are aged and old elements are allow_erased. The |
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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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* elements. setup rounds down to a power of two size. |
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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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size = 1 << depth_limit; |
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hash_mask = size-1; |
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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
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for (uint32_t loc : locs) |
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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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for (uint8_t depth = 0; depth < depth_limit; ++depth) { |
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// First try to insert to an empty slot, if one exists
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for (uint32_t loc : locs) { |
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if (!collection_flags.bit_is_set(loc)) |
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continue; |
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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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/** 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]. |
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* 2) On further iterations, where last_loc == locs[k], last_loc will |
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* go to locs[k+1 % 8], i.e., next of the 8 indicies wrapping around |
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* to 0 if needed. |
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* |
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* This prevents moving the element we just put in. |
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* |
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* The swap is not a move -- we must switch onto the evicted element |
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* for the next iteration. |
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*/ |
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last_loc = locs[(1 + (std::find(locs.begin(), locs.end(), last_loc) - locs.begin())) & 7]; |
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std::swap(table[last_loc], e); |
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// Can't std::swap a std::vector<bool>::reference and a bool&.
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bool epoch = last_epoch; |
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last_epoch = epoch_flags[last_loc]; |
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epoch_flags[last_loc] = epoch; |
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// Recompute the locs -- unfortunately happens one too many times!
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locs = compute_hashes(e); |
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} |
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} |
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/* contains iterates through the hash locations for a given element
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* and checks to see if it is present. |
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* |
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* contains does not check garbage collected state (in other words, |
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* garbage is only collected when the space is needed), so: |
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* |
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* insert(x); |
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* if (contains(x, true)) |
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* return contains(x, false); |
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* else |
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* return true; |
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* |
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* executed on a single thread will always return true! |
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* |
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* This is a great property for re-org performance for example. |
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* |
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* contains returns a bool set true if the element was found. |
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* |
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* @param e the element to check |
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* @param erase |
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* |
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* @post if erase is true and the element is found, then the garbage collect |
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* flag is set |
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* @returns true if the element is found, false otherwise |
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*/ |
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inline bool contains(const Element& e, const bool erase) const |
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{ |
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std::array<uint32_t, 8> locs = compute_hashes(e); |
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for (uint32_t loc : locs) |
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if (table[loc] == e) { |
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if (erase) |
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allow_erase(loc); |
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return true; |
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} |
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return false; |
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} |
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}; |
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} // namespace CuckooCache
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#endif |
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@ -0,0 +1,394 @@
@@ -0,0 +1,394 @@
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// Copyright (c) 2012-2016 The Bitcoin Core developers
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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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#include <boost/test/unit_test.hpp> |
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#include "cuckoocache.h" |
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#include "test/test_bitcoin.h" |
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#include "random.h" |
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#include <thread> |
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#include <boost/thread.hpp> |
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/** Test Suite for CuckooCache
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* |
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* 1) All tests should have a deterministic result (using insecure rand |
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* with deterministic seeds) |
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* 2) Some test methods are templated to allow for easier testing |
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* against new versions / comparing |
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* 3) Results should be treated as a regression test, ie, did the behavior |
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* change significantly from what was expected. This can be OK, depending on |
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* the nature of the change, but requires updating the tests to reflect the new |
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* expected behavior. For example improving the hit rate may cause some tests |
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* using BOOST_CHECK_CLOSE to fail. |
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* |
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*/ |
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FastRandomContext insecure_rand(true); |
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BOOST_AUTO_TEST_SUITE(cuckoocache_tests); |
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/** insecure_GetRandHash fills in a uint256 from insecure_rand
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*/ |
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void insecure_GetRandHash(uint256& t) |
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{ |
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uint32_t* ptr = (uint32_t*)t.begin(); |
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for (uint8_t j = 0; j < 8; ++j) |
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*(ptr++) = insecure_rand.rand32(); |
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} |
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/** Definition copied from /src/script/sigcache.cpp
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*/ |
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class uint256Hasher |
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{ |
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public: |
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template <uint8_t hash_select> |
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uint32_t operator()(const uint256& key) const |
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{ |
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static_assert(hash_select <8, "SignatureCacheHasher only has 8 hashes available."); |
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uint32_t u; |
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std::memcpy(&u, key.begin() + 4 * hash_select, 4); |
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return u; |
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} |
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}; |
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|
||||
/* Test that no values not inserted into the cache are read out of it.
|
||||
* |
||||
* There are no repeats in the first 200000 insecure_GetRandHash calls |
||||
*/ |
||||
BOOST_AUTO_TEST_CASE(test_cuckoocache_no_fakes) |
||||
{ |
||||
insecure_rand = FastRandomContext(true); |
||||
CuckooCache::cache<uint256, uint256Hasher> cc{}; |
||||
cc.setup_bytes(32 << 20); |
||||
uint256 v; |
||||
for (int x = 0; x < 100000; ++x) { |
||||
insecure_GetRandHash(v); |
||||
cc.insert(v); |
||||
} |
||||
for (int x = 0; x < 100000; ++x) { |
||||
insecure_GetRandHash(v); |
||||
BOOST_CHECK(!cc.contains(v, false)); |
||||
} |
||||
}; |
||||
|
||||
/** This helper returns the hit rate when megabytes*load worth of entries are
|
||||
* inserted into a megabytes sized cache |
||||
*/ |
||||
template <typename Cache> |
||||
double test_cache(size_t megabytes, double load) |
||||
{ |
||||
insecure_rand = FastRandomContext(true); |
||||
std::vector<uint256> hashes; |
||||
Cache set{}; |
||||
size_t bytes = megabytes * (1 << 20); |
||||
set.setup_bytes(bytes); |
||||
uint32_t n_insert = static_cast<uint32_t>(load * (bytes / sizeof(uint256))); |
||||
hashes.resize(n_insert); |
||||
for (uint32_t i = 0; i < n_insert; ++i) { |
||||
uint32_t* ptr = (uint32_t*)hashes[i].begin(); |
||||
for (uint8_t j = 0; j < 8; ++j) |
||||
*(ptr++) = insecure_rand.rand32(); |
||||
} |
||||
/** We make a copy of the hashes because future optimizations of the
|
||||
* cuckoocache may overwrite the inserted element, so the test is |
||||
* "future proofed". |
||||
*/ |
||||
std::vector<uint256> hashes_insert_copy = hashes; |
||||
/** Do the insert */ |
||||
for (uint256& h : hashes_insert_copy) |
||||
set.insert(h); |
||||
/** Count the hits */ |
||||
uint32_t count = 0; |
||||
for (uint256& h : hashes) |
||||
count += set.contains(h, false); |
||||
double hit_rate = ((double)count) / ((double)n_insert); |
||||
return hit_rate; |
||||
} |
||||
|
||||
/** The normalized hit rate for a given load.
|
||||
* |
||||
* The semantics are a little confusing, so please see the below |
||||
* explanation. |
||||
* |
||||
* Examples: |
||||
* |
||||
* 1) at load 0.5, we expect a perfect hit rate, so we multiply by |
||||
* 1.0 |
||||
* 2) at load 2.0, we expect to see half the entries, so a perfect hit rate |
||||
* would be 0.5. Therefore, if we see a hit rate of 0.4, 0.4*2.0 = 0.8 is the |
||||
* normalized hit rate. |
||||
* |
||||
* This is basically the right semantics, but has a bit of a glitch depending on |
||||
* how you measure around load 1.0 as after load 1.0 your normalized hit rate |
||||
* becomes effectively perfect, ignoring freshness. |
||||
*/ |
||||
double normalize_hit_rate(double hits, double load) |
||||
{ |
||||
return hits * std::max(load, 1.0); |
||||
} |
||||
|
||||
/** Check the hit rate on loads ranging from 0.1 to 2.0 */ |
||||
BOOST_AUTO_TEST_CASE(cuckoocache_hit_rate_ok) |
||||
{ |
||||
/** Arbitrarily selected Hit Rate threshold that happens to work for this test
|
||||
* as a lower bound on performance. |
||||
*/ |
||||
double HitRateThresh = 0.98; |
||||
size_t megabytes = 32; |
||||
for (double load = 0.1; load < 2; load *= 2) { |
||||
double hits = test_cache<CuckooCache::cache<uint256, uint256Hasher>>(megabytes, load); |
||||
BOOST_CHECK(normalize_hit_rate(hits, load) > HitRateThresh); |
||||
} |
||||
} |
||||
|
||||
|
||||
/** This helper checks that erased elements are preferentially inserted onto and
|
||||
* that the hit rate of "fresher" keys is reasonable*/ |
||||
template <typename Cache> |
||||
void test_cache_erase(size_t megabytes) |
||||
{ |
||||
double load = 1; |
||||
insecure_rand = FastRandomContext(true); |
||||
std::vector<uint256> hashes; |
||||
Cache set{}; |
||||
size_t bytes = megabytes * (1 << 20); |
||||
set.setup_bytes(bytes); |
||||
uint32_t n_insert = static_cast<uint32_t>(load * (bytes / sizeof(uint256))); |
||||
hashes.resize(n_insert); |
||||
for (uint32_t i = 0; i < n_insert; ++i) { |
||||
uint32_t* ptr = (uint32_t*)hashes[i].begin(); |
||||
for (uint8_t j = 0; j < 8; ++j) |
||||
*(ptr++) = insecure_rand.rand32(); |
||||
} |
||||
/** We make a copy of the hashes because future optimizations of the
|
||||
* cuckoocache may overwrite the inserted element, so the test is |
||||
* "future proofed". |
||||
*/ |
||||
std::vector<uint256> hashes_insert_copy = hashes; |
||||
|
||||
/** Insert the first half */ |
||||
for (uint32_t i = 0; i < (n_insert / 2); ++i) |
||||
set.insert(hashes_insert_copy[i]); |
||||
/** Erase the first quarter */ |
||||
for (uint32_t i = 0; i < (n_insert / 4); ++i) |
||||
set.contains(hashes[i], true); |
||||
/** Insert the second half */ |
||||
for (uint32_t i = (n_insert / 2); i < n_insert; ++i) |
||||
set.insert(hashes_insert_copy[i]); |
||||
|
||||
/** elements that we marked erased but that are still there */ |
||||
size_t count_erased_but_contained = 0; |
||||
/** elements that we did not erase but are older */ |
||||
size_t count_stale = 0; |
||||
/** elements that were most recently inserted */ |
||||
size_t count_fresh = 0; |
||||
|
||||
for (uint32_t i = 0; i < (n_insert / 4); ++i) |
||||
count_erased_but_contained += set.contains(hashes[i], false); |
||||
for (uint32_t i = (n_insert / 4); i < (n_insert / 2); ++i) |
||||
count_stale += set.contains(hashes[i], false); |
||||
for (uint32_t i = (n_insert / 2); i < n_insert; ++i) |
||||
count_fresh += set.contains(hashes[i], false); |
||||
|
||||
double hit_rate_erased_but_contained = double(count_erased_but_contained) / (double(n_insert) / 4.0); |
||||
double hit_rate_stale = double(count_stale) / (double(n_insert) / 4.0); |
||||
double hit_rate_fresh = double(count_fresh) / (double(n_insert) / 2.0); |
||||
|
||||
// Check that our hit_rate_fresh is perfect
|
||||
BOOST_CHECK_EQUAL(hit_rate_fresh, 1.0); |
||||
// Check that we have a more than 2x better hit rate on stale elements than
|
||||
// erased elements.
|
||||
BOOST_CHECK(hit_rate_stale > 2 * hit_rate_erased_but_contained); |
||||
} |
||||
|
||||
BOOST_AUTO_TEST_CASE(cuckoocache_erase_ok) |
||||
{ |
||||
size_t megabytes = 32; |
||||
test_cache_erase<CuckooCache::cache<uint256, uint256Hasher>>(megabytes); |
||||
} |
||||
|
||||
template <typename Cache> |
||||
void test_cache_erase_parallel(size_t megabytes) |
||||
{ |
||||
double load = 1; |
||||
insecure_rand = FastRandomContext(true); |
||||
std::vector<uint256> hashes; |
||||
Cache set{}; |
||||
size_t bytes = megabytes * (1 << 20); |
||||
set.setup_bytes(bytes); |
||||
uint32_t n_insert = static_cast<uint32_t>(load * (bytes / sizeof(uint256))); |
||||
hashes.resize(n_insert); |
||||
for (uint32_t i = 0; i < n_insert; ++i) { |
||||
uint32_t* ptr = (uint32_t*)hashes[i].begin(); |
||||
for (uint8_t j = 0; j < 8; ++j) |
||||
*(ptr++) = insecure_rand.rand32(); |
||||
} |
||||
/** We make a copy of the hashes because future optimizations of the
|
||||
* cuckoocache may overwrite the inserted element, so the test is |
||||
* "future proofed". |
||||
*/ |
||||
std::vector<uint256> hashes_insert_copy = hashes; |
||||
boost::shared_mutex mtx; |
||||
|
||||
{ |
||||
/** Grab lock to make sure we release inserts */ |
||||
boost::unique_lock<boost::shared_mutex> l(mtx); |
||||
/** Insert the first half */ |
||||
for (uint32_t i = 0; i < (n_insert / 2); ++i) |
||||
set.insert(hashes_insert_copy[i]); |
||||
} |
||||
|
||||
/** Spin up 3 threads to run contains with erase.
|
||||
*/ |
||||
std::vector<std::thread> threads; |
||||
/** Erase the first quarter */ |
||||
for (uint32_t x = 0; x < 3; ++x) |
||||
/** Each thread is emplaced with x copy-by-value
|
||||
*/ |
||||
threads.emplace_back([&, x] { |
||||
boost::shared_lock<boost::shared_mutex> l(mtx); |
||||
size_t ntodo = (n_insert/4)/3; |
||||
size_t start = ntodo*x; |
||||
size_t end = ntodo*(x+1); |
||||
for (uint32_t i = start; i < end; ++i) |
||||
set.contains(hashes[i], true); |
||||
}); |
||||
|
||||
/** Wait for all threads to finish
|
||||
*/ |
||||
for (std::thread& t : threads) |
||||
t.join(); |
||||
/** Grab lock to make sure we observe erases */ |
||||
boost::unique_lock<boost::shared_mutex> l(mtx); |
||||
/** Insert the second half */ |
||||
for (uint32_t i = (n_insert / 2); i < n_insert; ++i) |
||||
set.insert(hashes_insert_copy[i]); |
||||
|
||||
/** elements that we marked erased but that are still there */ |
||||
size_t count_erased_but_contained = 0; |
||||
/** elements that we did not erase but are older */ |
||||
size_t count_stale = 0; |
||||
/** elements that were most recently inserted */ |
||||
size_t count_fresh = 0; |
||||
|
||||
for (uint32_t i = 0; i < (n_insert / 4); ++i) |
||||
count_erased_but_contained += set.contains(hashes[i], false); |
||||
for (uint32_t i = (n_insert / 4); i < (n_insert / 2); ++i) |
||||
count_stale += set.contains(hashes[i], false); |
||||
for (uint32_t i = (n_insert / 2); i < n_insert; ++i) |
||||
count_fresh += set.contains(hashes[i], false); |
||||
|
||||
double hit_rate_erased_but_contained = double(count_erased_but_contained) / (double(n_insert) / 4.0); |
||||
double hit_rate_stale = double(count_stale) / (double(n_insert) / 4.0); |
||||
double hit_rate_fresh = double(count_fresh) / (double(n_insert) / 2.0); |
||||
|
||||
// Check that our hit_rate_fresh is perfect
|
||||
BOOST_CHECK_EQUAL(hit_rate_fresh, 1.0); |
||||
// Check that we have a more than 2x better hit rate on stale elements than
|
||||
// erased elements.
|
||||
BOOST_CHECK(hit_rate_stale > 2 * hit_rate_erased_but_contained); |
||||
} |
||||
BOOST_AUTO_TEST_CASE(cuckoocache_erase_parallel_ok) |
||||
{ |
||||
size_t megabytes = 32; |
||||
test_cache_erase_parallel<CuckooCache::cache<uint256, uint256Hasher>>(megabytes); |
||||
} |
||||
|
||||
|
||||
template <typename Cache> |
||||
void test_cache_generations() |
||||
{ |
||||
// This test checks that for a simulation of network activity, the fresh hit
|
||||
// rate is never below 99%, and the number of times that it is worse than
|
||||
// 99.9% are less than 1% of the time.
|
||||
double min_hit_rate = 0.99; |
||||
double tight_hit_rate = 0.999; |
||||
double max_rate_less_than_tight_hit_rate = 0.01; |
||||
// A cache that meets this specification is therefore shown to have a hit
|
||||
// rate of at least tight_hit_rate * (1 - max_rate_less_than_tight_hit_rate) +
|
||||
// min_hit_rate*max_rate_less_than_tight_hit_rate = 0.999*99%+0.99*1% == 99.89%
|
||||
// hit rate with low variance.
|
||||
|
||||
// We use deterministic values, but this test has also passed on many
|
||||
// iterations with non-deterministic values, so it isn't "overfit" to the
|
||||
// specific entropy in FastRandomContext(true) and implementation of the
|
||||
// cache.
|
||||
insecure_rand = FastRandomContext(true); |
||||
|
||||
// block_activity models a chunk of network activity. n_insert elements are
|
||||
// adde to the cache. The first and last n/4 are stored for removal later
|
||||
// and the middle n/2 are not stored. This models a network which uses half
|
||||
// the signatures of recently (since the last block) added transactions
|
||||
// immediately and never uses the other half.
|
||||
struct block_activity { |
||||
std::vector<uint256> reads; |
||||
block_activity(uint32_t n_insert, Cache& c) : reads() |
||||
{ |
||||
std::vector<uint256> inserts; |
||||
inserts.resize(n_insert); |
||||
reads.reserve(n_insert / 2); |
||||
for (uint32_t i = 0; i < n_insert; ++i) { |
||||
uint32_t* ptr = (uint32_t*)inserts[i].begin(); |
||||
for (uint8_t j = 0; j < 8; ++j) |
||||
*(ptr++) = insecure_rand.rand32(); |
||||
} |
||||
for (uint32_t i = 0; i < n_insert / 4; ++i) |
||||
reads.push_back(inserts[i]); |
||||
for (uint32_t i = n_insert - (n_insert / 4); i < n_insert; ++i) |
||||
reads.push_back(inserts[i]); |
||||
for (auto h : inserts) |
||||
c.insert(h); |
||||
} |
||||
}; |
||||
|
||||
const uint32_t BLOCK_SIZE = 10000; |
||||
// We expect window size 60 to perform reasonably given that each epoch
|
||||
// stores 45% of the cache size (~472k).
|
||||
const uint32_t WINDOW_SIZE = 60; |
||||
const uint32_t POP_AMOUNT = (BLOCK_SIZE / WINDOW_SIZE) / 2; |
||||
const double load = 10; |
||||
const size_t megabytes = 32; |
||||
const size_t bytes = megabytes * (1 << 20); |
||||
const uint32_t n_insert = static_cast<uint32_t>(load * (bytes / sizeof(uint256))); |
||||
|
||||
std::vector<block_activity> hashes; |
||||
Cache set{}; |
||||
set.setup_bytes(bytes); |
||||
hashes.reserve(n_insert / BLOCK_SIZE); |
||||
std::deque<block_activity> last_few; |
||||
uint32_t out_of_tight_tolerance = 0; |
||||
uint32_t total = n_insert / BLOCK_SIZE; |
||||
// we use the deque last_few to model a sliding window of blocks. at each
|
||||
// step, each of the last WINDOW_SIZE block_activities checks the cache for
|
||||
// POP_AMOUNT of the hashes that they inserted, and marks these erased.
|
||||
for (uint32_t i = 0; i < total; ++i) { |
||||
if (last_few.size() == WINDOW_SIZE) |
||||
last_few.pop_front(); |
||||
last_few.emplace_back(BLOCK_SIZE, set); |
||||
uint32_t count = 0; |
||||
for (auto& act : last_few) |
||||
for (uint32_t k = 0; k < POP_AMOUNT; ++k) { |
||||
count += set.contains(act.reads.back(), true); |
||||
act.reads.pop_back(); |
||||
} |
||||
// We use last_few.size() rather than WINDOW_SIZE for the correct
|
||||
// behavior on the first WINDOW_SIZE iterations where the deque is not
|
||||
// full yet.
|
||||
double hit = (double(count)) / (last_few.size() * POP_AMOUNT); |
||||
// Loose Check that hit rate is above min_hit_rate
|
||||
BOOST_CHECK(hit > min_hit_rate); |
||||
// Tighter check, count number of times we are less than tight_hit_rate
|
||||
// (and implicityly, greater than min_hit_rate)
|
||||
out_of_tight_tolerance += hit < tight_hit_rate; |
||||
} |
||||
// Check that being out of tolerance happens less than
|
||||
// max_rate_less_than_tight_hit_rate of the time
|
||||
BOOST_CHECK(double(out_of_tight_tolerance) / double(total) < max_rate_less_than_tight_hit_rate); |
||||
} |
||||
BOOST_AUTO_TEST_CASE(cuckoocache_generations) |
||||
{ |
||||
test_cache_generations<CuckooCache::cache<uint256, uint256Hasher>>(); |
||||
} |
||||
|
||||
BOOST_AUTO_TEST_SUITE_END(); |
||||
Loading…
Reference in new issue