git / moonbite-core / src/test/cuckoocache_tests.cpp · raw

// Copyright (c) 2012-2020 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 <deque>#include <random.h>#include <script/sigcache.h>#include <test/util/setup_common.h>#include <thread>/** 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, i.e., 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. * */BOOST_AUTO_TEST_SUITE(cuckoocache_tests);/* 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){    SeedInsecureRand(SeedRand::ZEROS);    CuckooCache::cache<uint256, SignatureCacheHasher> cc{};    size_t megabytes = 4;    cc.setup_bytes(megabytes << 20);    for (int x = 0; x < 100000; ++x) {        cc.insert(InsecureRand256());    }    for (int x = 0; x < 100000; ++x) {        BOOST_CHECK(!cc.contains(InsecureRand256(), false));    }};/** This helper returns the hit rate when megabytes*load worth of entries are * inserted into a megabytes sized cache */template <typename Cache>static double test_cache(size_t megabytes, double load){    SeedInsecureRand(SeedRand::ZEROS);    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++) = InsecureRand32();    }    /** 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 (const uint256& h : hashes_insert_copy)        set.insert(h);    /** Count the hits */    uint32_t count = 0;    for (const 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. */static 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 1.6 */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 = 4;    for (double load = 0.1; load < 2; load *= 2) {        double hits = test_cache<CuckooCache::cache<uint256, SignatureCacheHasher>>(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>static void test_cache_erase(size_t megabytes){    double load = 1;    SeedInsecureRand(SeedRand::ZEROS);    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++) = InsecureRand32();    }    /** 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)        BOOST_CHECK(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 as erased but 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 = 4;    test_cache_erase<CuckooCache::cache<uint256, SignatureCacheHasher>>(megabytes);}template <typename Cache>static void test_cache_erase_parallel(size_t megabytes){    double load = 1;    SeedInsecureRand(SeedRand::ZEROS);    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++) = InsecureRand32();    }    /** 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) {                bool contains = set.contains(hashes[i], true);                assert(contains);            }        });    /** 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 = 4;    test_cache_erase_parallel<CuckooCache::cache<uint256, SignatureCacheHasher>>(megabytes);}template <typename Cache>static 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.    SeedInsecureRand(SeedRand::ZEROS);    // block_activity models a chunk of network activity. n_insert elements are    // added 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++) = InsecureRand32();            }            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 (const auto& h : inserts)                c.insert(h);        }    };    const uint32_t BLOCK_SIZE = 1000;    // 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 = 4;    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 implicitly, 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, SignatureCacheHasher>>();}BOOST_AUTO_TEST_SUITE_END();