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Merge #8895: Better SigCache Implementation

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67dac4e Add unit tests for the CuckooCache (Jeremy Rubin)
c9e69fb Add CuckooCache implementation and replace the sigcache map_type with it (Jeremy Rubin)
This commit is contained in:
Pieter Wuille 2016-12-14 17:48:56 -08:00
parent b68685a16a 67dac4e193
commit b83264d9c7
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7 changed files with 902 additions and 42 deletions
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1
src/Makefile.test.include
View file

@ -53,6 +53,7 @@ BITCOIN_TESTS =\
test/coins_tests.cpp \
test/compress_tests.cpp \
test/crypto_tests.cpp \
test/cuckoocache_tests.cpp \
test/DoS_tests.cpp \
test/getarg_tests.cpp \
test/hash_tests.cpp \

457
src/cuckoocache.h Normal file
View file

@ -0,0 +1,457 @@
// Copyright (c) 2016 Jeremy Rubin
// Distributed under the MIT software license, see the accompanying
// file COPYING or http://www.opensource.org/licenses/mit-license.php.
#ifndef _BITCOIN_CUCKOOCACHE_H_
#define _BITCOIN_CUCKOOCACHE_H_
#include <array>
#include <algorithm>
#include <atomic>
#include <cstring>
#include <cmath>
#include <memory>
#include <vector>
/** namespace CuckooCache provides high performance cache primitives
*
* Summary:
*
* 1) bit_packed_atomic_flags is bit-packed atomic flags for garbage collection
*
* 2) cache is a cache which is performant in memory usage and lookup speed. It
* is lockfree for erase operations. Elements are lazily erased on the next
* insert.
*/
namespace CuckooCache
{
/** bit_packed_atomic_flags implements a container for garbage collection flags
* that is only thread unsafe on calls to setup. This class bit-packs collection
* flags for memory efficiency.
*
* All operations are std::memory_order_relaxed so external mechanisms must
* ensure that writes and reads are properly synchronized.
*
* On setup(n), all bits up to n are marked as collected.
*
* Under the hood, because it is an 8-bit type, it makes sense to use a multiple
* of 8 for setup, but it will be safe if that is not the case as well.
*
*/
class bit_packed_atomic_flags
{
std::unique_ptr<std::atomic<uint8_t>[]> mem;
public:
/** No default constructor as there must be some size */
bit_packed_atomic_flags() = delete;
/**
* bit_packed_atomic_flags constructor creates memory to sufficiently
* keep track of garbage collection information for size entries.
*
* @param size the number of elements to allocate space for
*
* @post bit_set, bit_unset, and bit_is_set function properly forall x. x <
* size
* @post All calls to bit_is_set (without subsequent bit_unset) will return
* true.
*/
bit_packed_atomic_flags(uint32_t size)
{
// pad out the size if needed
size = (size + 7) / 8;
mem.reset(new std::atomic<uint8_t>[size]);
for (uint32_t i = 0; i < size; ++i)
mem[i].store(0xFF);
};
/** setup marks all entries and ensures that bit_packed_atomic_flags can store
* at least size entries
*
* @param b the number of elements to allocate space for
* @post bit_set, bit_unset, and bit_is_set function properly forall x. x <
* b
* @post All calls to bit_is_set (without subsequent bit_unset) will return
* true.
*/
inline void setup(uint32_t b)
{
bit_packed_atomic_flags d(b);
std::swap(mem, d.mem);
}
/** bit_set sets an entry as discardable.
*
* @param s the index of the entry to bit_set.
* @post immediately subsequent call (assuming proper external memory
* ordering) to bit_is_set(s) == true.
*
*/
inline void bit_set(uint32_t s)
{
mem[s >> 3].fetch_or(1 << (s & 7), std::memory_order_relaxed);
}
/** bit_unset marks an entry as something that should not be overwritten
*
* @param s the index of the entry to bit_unset.
* @post immediately subsequent call (assuming proper external memory
* ordering) to bit_is_set(s) == false.
*/
inline void bit_unset(uint32_t s)
{
mem[s >> 3].fetch_and(~(1 << (s & 7)), std::memory_order_relaxed);
}
/** bit_is_set queries the table for discardability at s
*
* @param s the index of the entry to read.
* @returns if the bit at index s was set.
* */
inline bool bit_is_set(uint32_t s) const
{
return (1 << (s & 7)) & mem[s >> 3].load(std::memory_order_relaxed);
}
};
/** cache implements a cache with properties similar to a cuckoo-set
*
* The cache is able to hold up to (~(uint32_t)0) - 1 elements.
*
* Read Operations:
* - contains(*, false)
*
* Read+Erase Operations:
* - contains(*, true)
*
* Erase Operations:
* - allow_erase()
*
* Write Operations:
* - setup()
* - setup_bytes()
* - insert()
* - please_keep()
*
* Synchronization Free Operations:
* - invalid()
* - compute_hashes()
*
* User Must Guarantee:
*
* 1) Write Requires synchronized access (e.g., a lock)
* 2) Read Requires no concurrent Write, synchronized with the last insert.
* 3) Erase requires no concurrent Write, synchronized with last insert.
* 4) An Erase caller must release all memory before allowing a new Writer.
*
*
* Note on function names:
* - The name "allow_erase" is used because the real discard happens later.
* - The name "please_keep" is used because elements may be erased anyways on insert.
*
* @tparam Element should be a movable and copyable type
* @tparam Hash should be a function/callable which takes a template parameter
* hash_select and an Element and extracts a hash from it. Should return
* high-entropy hashes for `Hash h; h<0>(e) ... h<7>(e)`.
*/
template <typename Element, typename Hash>
class cache
{
private:
/** table stores all the elements */
std::vector<Element> table;
/** size stores the total available slots in the hash table */
uint32_t size;
/** The bit_packed_atomic_flags array is marked mutable because we want
* garbage collection to be allowed to occur from const methods */
mutable bit_packed_atomic_flags collection_flags;
/** epoch_flags tracks how recently an element was inserted into
* the cache. true denotes recent, false denotes not-recent. See insert()
* method for full semantics.
*/
mutable std::vector<bool> epoch_flags;
/** epoch_heuristic_counter is used to determine when a epoch might be aged
* & an expensive scan should be done. epoch_heuristic_counter is
* decremented on insert and reset to the new number of inserts which would
* cause the epoch to reach epoch_size when it reaches zero.
*/
uint32_t epoch_heuristic_counter;
/** epoch_size is set to be the number of elements supposed to be in a
* epoch. When the number of non-erased elements in a epoch
* exceeds epoch_size, a new epoch should be started and all
* current entries demoted. epoch_size is set to be 45% of size because
* we want to keep load around 90%, and we support 3 epochs at once --
* one "dead" which has been erased, one "dying" which has been marked to be
* erased next, and one "living" which new inserts add to.
*/
uint32_t epoch_size;
/** hash_mask should be set to appropriately mask out a hash such that every
* masked hash is [0,size), eg, if floor(log2(size)) == 20, then hash_mask
* should be (1<<20)-1
*/
uint32_t hash_mask;
/** depth_limit determines how many elements insert should try to replace.
* Should be set to log2(n)*/
uint8_t depth_limit;
/** hash_function is a const instance of the hash function. It cannot be
* static or initialized at call time as it may have internal state (such as
* a nonce).
* */
const Hash hash_function;
/** compute_hashes is convenience for not having to write out this
* expression everywhere we use the hash values of an Element.
*
* @param e the element whose hashes will be returned
* @returns std::array<uint32_t, 8> of deterministic hashes derived from e
*/
inline std::array<uint32_t, 8> compute_hashes(const Element& e) const
{
return {{hash_function.template operator()<0>(e) & hash_mask,
hash_function.template operator()<1>(e) & hash_mask,
hash_function.template operator()<2>(e) & hash_mask,
hash_function.template operator()<3>(e) & hash_mask,
hash_function.template operator()<4>(e) & hash_mask,
hash_function.template operator()<5>(e) & hash_mask,
hash_function.template operator()<6>(e) & hash_mask,
hash_function.template operator()<7>(e) & hash_mask}};
}
/* end
* @returns a constexpr index that can never be inserted to */
constexpr uint32_t invalid() const
{
return ~(uint32_t)0;
}
/** allow_erase marks the element at index n as discardable. Threadsafe
* without any concurrent insert.
* @param n the index to allow erasure of
*/
inline void allow_erase(uint32_t n) const
{
collection_flags.bit_set(n);
}
/** please_keep marks the element at index n as an entry that should be kept.
* Threadsafe without any concurrent insert.
* @param n the index to prioritize keeping
*/
inline void please_keep(uint32_t n) const
{
collection_flags.bit_unset(n);
}
/** epoch_check handles the changing of epochs for elements stored in the
* cache. epoch_check should be run before every insert.
*
* First, epoch_check decrements and checks the cheap heuristic, and then does
* a more expensive scan if the cheap heuristic runs out. If the expensive
* scan suceeds, the epochs are aged and old elements are allow_erased. The
* cheap heuristic is reset to retrigger after the worst case growth of the
* current epoch's elements would exceed the epoch_size.
*/
void epoch_check()
{
if (epoch_heuristic_counter != 0) {
--epoch_heuristic_counter;
return;
}
// count the number of elements from the latest epoch which
// have not been erased.
uint32_t epoch_unused_count = 0;
for (uint32_t i = 0; i < size; ++i)
epoch_unused_count += epoch_flags[i] &&
!collection_flags.bit_is_set(i);
// If there are more non-deleted entries in the current epoch than the
// epoch size, then allow_erase on all elements in the old epoch (marked
// false) and move all elements in the current epoch to the old epoch
// but do not call allow_erase on their indices.
if (epoch_unused_count >= epoch_size) {
for (uint32_t i = 0; i < size; ++i)
if (epoch_flags[i])
epoch_flags[i] = false;
else
allow_erase(i);
epoch_heuristic_counter = epoch_size;
} else
// reset the epoch_heuristic_counter to next do a scan when worst
// case behavior (no intermittent erases) would exceed epoch size,
// with a reasonable minimum scan size.
// Ordinarily, we would have to sanity check std::min(epoch_size,
// epoch_unused_count), but we already know that `epoch_unused_count
// < epoch_size` in this branch
epoch_heuristic_counter = std::max(1u, std::max(epoch_size / 16,
epoch_size - epoch_unused_count));
}
public:
/** You must always construct a cache with some elements via a subsequent
* call to setup or setup_bytes, otherwise operations may segfault.
*/
cache() : table(), size(), collection_flags(0), epoch_flags(),
epoch_heuristic_counter(), epoch_size(), depth_limit(0), hash_function()
{
}
/** setup initializes the container to store no more than new_size
* elements. setup rounds down to a power of two size.
*
* setup should only be called once.
*
* @param new_size the desired number of elements to store
* @returns the maximum number of elements storable
**/
uint32_t setup(uint32_t new_size)
{
// depth_limit must be at least one otherwise errors can occur.
depth_limit = static_cast<uint8_t>(std::log2(static_cast<float>(std::max((uint32_t)2, new_size))));
size = 1 << depth_limit;
hash_mask = size-1;
table.resize(size);
collection_flags.setup(size);
epoch_flags.resize(size);
// Set to 45% as described above
epoch_size = std::max((uint32_t)1, (45 * size) / 100);
// Initially set to wait for a whole epoch
epoch_heuristic_counter = epoch_size;
return size;
}
/** setup_bytes is a convenience function which accounts for internal memory
* usage when deciding how many elements to store. It isn't perfect because
* it doesn't account for any overhead (struct size, MallocUsage, collection
* and epoch flags). This was done to simplify selecting a power of two
* size. In the expected use case, an extra two bits per entry should be
* negligible compared to the size of the elements.
*
* @param bytes the approximate number of bytes to use for this data
* structure.
* @returns the maximum number of elements storable (see setup()
* documentation for more detail)
*/
uint32_t setup_bytes(size_t bytes)
{
return setup(bytes/sizeof(Element));
}
/** insert loops at most depth_limit times trying to insert a hash
* at various locations in the table via a variant of the Cuckoo Algorithm
* with eight hash locations.
*
* It drops the last tried element if it runs out of depth before
* encountering an open slot.
*
* Thus
*
* insert(x);
* return contains(x, false);
*
* is not guaranteed to return true.
*
* @param e the element to insert
* @post one of the following: All previously inserted elements and e are
* now in the table, one previously inserted element is evicted from the
* table, the entry attempted to be inserted is evicted.
*
*/
inline void insert(Element e)
{
epoch_check();
uint32_t last_loc = invalid();
bool last_epoch = true;
std::array<uint32_t, 8> locs = compute_hashes(e);
// Make sure we have not already inserted this element
// If we have, make sure that it does not get deleted
for (uint32_t loc : locs)
if (table[loc] == e) {
please_keep(loc);
epoch_flags[loc] = last_epoch;
return;
}
for (uint8_t depth = 0; depth < depth_limit; ++depth) {
// First try to insert to an empty slot, if one exists
for (uint32_t loc : locs) {
if (!collection_flags.bit_is_set(loc))
continue;
table[loc] = std::move(e);
please_keep(loc);
epoch_flags[loc] = last_epoch;
return;
}
/** Swap with the element at the location that was
* not the last one looked at. Example:
*
* 1) On first iteration, last_loc == invalid(), find returns last, so
* last_loc defaults to locs[0].
* 2) On further iterations, where last_loc == locs[k], last_loc will
* go to locs[k+1 % 8], i.e., next of the 8 indicies wrapping around
* 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);
for (uint32_t loc : locs)
if (table[loc] == e) {
if (erase)
allow_erase(loc);
return true;
}
return false;
}
};
} // namespace CuckooCache
#endif

2
src/init.cpp
View file

@ -1103,6 +1103,8 @@ bool AppInitMain(boost::thread_group& threadGroup, CScheduler& scheduler)
LogPrintf("Using config file %s\n", GetConfigFile(GetArg("-conf", BITCOIN_CONF_FILENAME)).string());
LogPrintf("Using at most %i connections (%i file descriptors available)\n", nMaxConnections, nFD);
InitSignatureCache();
LogPrintf("Using %u threads for script verification\n", nScriptCheckThreads);
if (nScriptCheckThreads) {
for (int i=0; i<nScriptCheckThreads-1; i++)

79
src/script/sigcache.cpp
View file

@ -11,20 +11,29 @@
#include "uint256.h"
#include "util.h"
#include "cuckoocache.h"
#include <boost/thread.hpp>
#include <boost/unordered_set.hpp>
namespace {
/**
* We're hashing a nonce into the entries themselves, so we don't need extra
* blinding in the set hash computation.
*
* This may exhibit platform endian dependent behavior but because these are
* nonced hashes (random) and this state is only ever used locally it is safe.
* All that matters is local consistency.
*/
class CSignatureCacheHasher
class SignatureCacheHasher
{
public:
size_t operator()(const uint256& key) const {
return key.GetCheapHash();
template <uint8_t hash_select>
uint32_t operator()(const uint256& key) const
{
static_assert(hash_select <8, "SignatureCacheHasher only has 8 hashes available.");
uint32_t u;
std::memcpy(&u, key.begin()+4*hash_select, 4);
return u;
}
};
@ -38,11 +47,10 @@ class CSignatureCache
private:
//! Entries are SHA256(nonce || signature hash || public key || signature):
uint256 nonce;
typedef boost::unordered_set<uint256, CSignatureCacheHasher> map_type;
typedef CuckooCache::cache<uint256, SignatureCacheHasher> map_type;
map_type setValid;
boost::shared_mutex cs_sigcache;
public:
CSignatureCache()
{
@ -56,58 +64,51 @@ public:
}
bool
Get(const uint256& entry)
Get(const uint256& entry, const bool erase)
{
boost::shared_lock<boost::shared_mutex> lock(cs_sigcache);
return setValid.count(entry);
return setValid.contains(entry, erase);
}
void Erase(const uint256& entry)
void Set(uint256& entry)
{
boost::unique_lock<boost::shared_mutex> lock(cs_sigcache);
setValid.erase(entry);
}
void Set(const uint256& entry)
{
size_t nMaxCacheSize = GetArg("-maxsigcachesize", DEFAULT_MAX_SIG_CACHE_SIZE) * ((size_t) 1 << 20);
if (nMaxCacheSize <= 0) return;
boost::unique_lock<boost::shared_mutex> lock(cs_sigcache);
while (memusage::DynamicUsage(setValid) > nMaxCacheSize)
{
map_type::size_type s = GetRand(setValid.bucket_count());
map_type::local_iterator it = setValid.begin(s);
if (it != setValid.end(s)) {
setValid.erase(*it);
}
}
setValid.insert(entry);
}
uint32_t setup_bytes(size_t n)
{
return setValid.setup_bytes(n);
}
};
/* In previous versions of this code, signatureCache was a local static variable
* in CachingTransactionSignatureChecker::VerifySignature. We initialize
* signatureCache outside of VerifySignature to avoid the atomic operation per
* call overhead associated with local static variables even though
* signatureCache could be made local to VerifySignature.
*/
static CSignatureCache signatureCache;
}
// To be called once in AppInit2/TestingSetup to initialize the signatureCache
void InitSignatureCache()
{
size_t nMaxCacheSize = GetArg("-maxsigcachesize", DEFAULT_MAX_SIG_CACHE_SIZE) * ((size_t) 1 << 20);
if (nMaxCacheSize <= 0) return;
size_t nElems = signatureCache.setup_bytes(nMaxCacheSize);
LogPrintf("Using %zu MiB out of %zu requested for signature cache, able to store %zu elements\n",
(nElems*sizeof(uint256)) >>20, nMaxCacheSize>>20, nElems);
}
bool CachingTransactionSignatureChecker::VerifySignature(const std::vector<unsigned char>& vchSig, const CPubKey& pubkey, const uint256& sighash) const
{
static CSignatureCache signatureCache;
uint256 entry;
signatureCache.ComputeEntry(entry, sighash, vchSig, pubkey);
if (signatureCache.Get(entry)) {
if (!store) {
signatureCache.Erase(entry);
}
if (signatureCache.Get(entry, !store))
return true;
}
if (!TransactionSignatureChecker::VerifySignature(vchSig, pubkey, sighash))
return false;
if (store) {
if (store)
signatureCache.Set(entry);
}
return true;
}

9
src/script/sigcache.h
View file

@ -10,9 +10,10 @@
#include <vector>
// DoS prevention: limit cache size to less than 40MB (over 500000
// entries on 64-bit systems).
static const unsigned int DEFAULT_MAX_SIG_CACHE_SIZE = 40;
// DoS prevention: limit cache size to 32MB (over 1000000 entries on 64-bit
// systems). Due to how we count cache size, actual memory usage is slightly
// more (~32.25 MB)
static const unsigned int DEFAULT_MAX_SIG_CACHE_SIZE = 32;
class CPubKey;
@ -27,4 +28,6 @@ public:
bool VerifySignature(const std::vector<unsigned char>& vchSig, const CPubKey& vchPubKey, const uint256& sighash) const;
};
void InitSignatureCache();
#endif // BITCOIN_SCRIPT_SIGCACHE_H

394
src/test/cuckoocache_tests.cpp Normal file
View file

@ -0,0 +1,394 @@
// Copyright (c) 2012-2016 The Bitcoin Core developers
// Distributed under the MIT software license, see the accompanying
// file COPYING or http://www.opensource.org/licenses/mit-license.php.
#include <boost/test/unit_test.hpp>
#include "cuckoocache.h"
#include "test/test_bitcoin.h"
#include "random.h"
#include <thread>
#include <boost/thread.hpp>
/** Test Suite for CuckooCache
*
* 1) All tests should have a deterministic result (using insecure rand
* with deterministic seeds)
* 2) Some test methods are templated to allow for easier testing
* against new versions / comparing
* 3) Results should be treated as a regression test, ie, did the behavior
* change significantly from what was expected. This can be OK, depending on
* the nature of the change, but requires updating the tests to reflect the new
* expected behavior. For example improving the hit rate may cause some tests
* using BOOST_CHECK_CLOSE to fail.
*
*/
FastRandomContext insecure_rand(true);
BOOST_AUTO_TEST_SUITE(cuckoocache_tests);
/** insecure_GetRandHash fills in a uint256 from insecure_rand
*/
void insecure_GetRandHash(uint256& t)
{
uint32_t* ptr = (uint32_t*)t.begin();
for (uint8_t j = 0; j < 8; ++j)
*(ptr++) = insecure_rand.rand32();
}
/** Definition copied from /src/script/sigcache.cpp
*/
class uint256Hasher
{
public:
template <uint8_t hash_select>
uint32_t operator()(const uint256& key) const
{
static_assert(hash_select <8, "SignatureCacheHasher only has 8 hashes available.");
uint32_t u;
std::memcpy(&u, key.begin() + 4 * hash_select, 4);
return u;
}
};
/* 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();

2
src/test/test_bitcoin.cpp
View file

@ -20,6 +20,7 @@
#include "ui_interface.h"
#include "rpc/server.h"
#include "rpc/register.h"
#include "script/sigcache.h"
#include "test/testutil.h"
@ -40,6 +41,7 @@ BasicTestingSetup::BasicTestingSetup(const std::string& chainName)
ECC_Start();
SetupEnvironment();
SetupNetworking();
InitSignatureCache();
fPrintToDebugLog = false; // don't want to write to debug.log file
fCheckBlockIndex = true;
SelectParams(chainName);