Branch data Line data Source code
# 1 : : // Copyright (c) 2012-2021 The Bitcoin Core developers
# 2 : : // Distributed under the MIT software license, see the accompanying
# 3 : : // file COPYING or http://www.opensource.org/licenses/mit-license.php.
# 4 : : #include <cuckoocache.h>
# 5 : : #include <random.h>
# 6 : : #include <script/sigcache.h>
# 7 : : #include <test/util/setup_common.h>
# 8 : :
# 9 : : #include <boost/test/unit_test.hpp>
# 10 : :
# 11 : : #include <deque>
# 12 : : #include <mutex>
# 13 : : #include <shared_mutex>
# 14 : : #include <thread>
# 15 : : #include <vector>
# 16 : :
# 17 : : /** Test Suite for CuckooCache
# 18 : : *
# 19 : : * 1. All tests should have a deterministic result (using insecure rand
# 20 : : * with deterministic seeds)
# 21 : : * 2. Some test methods are templated to allow for easier testing
# 22 : : * against new versions / comparing
# 23 : : * 3. Results should be treated as a regression test, i.e., did the behavior
# 24 : : * change significantly from what was expected. This can be OK, depending on
# 25 : : * the nature of the change, but requires updating the tests to reflect the new
# 26 : : * expected behavior. For example improving the hit rate may cause some tests
# 27 : : * using BOOST_CHECK_CLOSE to fail.
# 28 : : *
# 29 : : */
# 30 : : BOOST_AUTO_TEST_SUITE(cuckoocache_tests);
# 31 : :
# 32 : : /* Test that no values not inserted into the cache are read out of it.
# 33 : : *
# 34 : : * There are no repeats in the first 200000 insecure_GetRandHash calls
# 35 : : */
# 36 : : BOOST_AUTO_TEST_CASE(test_cuckoocache_no_fakes)
# 37 : 2 : {
# 38 : 2 : SeedInsecureRand(SeedRand::ZEROS);
# 39 : 2 : CuckooCache::cache<uint256, SignatureCacheHasher> cc{};
# 40 : 2 : size_t megabytes = 4;
# 41 : 2 : cc.setup_bytes(megabytes << 20);
# 42 [ + + ]: 200002 : for (int x = 0; x < 100000; ++x) {
# 43 : 200000 : cc.insert(InsecureRand256());
# 44 : 200000 : }
# 45 [ + + ]: 200002 : for (int x = 0; x < 100000; ++x) {
# 46 : 200000 : BOOST_CHECK(!cc.contains(InsecureRand256(), false));
# 47 : 200000 : }
# 48 : 2 : };
# 49 : :
# 50 : : /** This helper returns the hit rate when megabytes*load worth of entries are
# 51 : : * inserted into a megabytes sized cache
# 52 : : */
# 53 : : template <typename Cache>
# 54 : : static double test_cache(size_t megabytes, double load)
# 55 : 10 : {
# 56 : 10 : SeedInsecureRand(SeedRand::ZEROS);
# 57 : 10 : std::vector<uint256> hashes;
# 58 : 10 : Cache set{};
# 59 : 10 : size_t bytes = megabytes * (1 << 20);
# 60 : 10 : set.setup_bytes(bytes);
# 61 : 10 : uint32_t n_insert = static_cast<uint32_t>(load * (bytes / sizeof(uint256)));
# 62 : 10 : hashes.resize(n_insert);
# 63 [ + + ]: 812652 : for (uint32_t i = 0; i < n_insert; ++i) {
# 64 : 812642 : uint32_t* ptr = (uint32_t*)hashes[i].begin();
# 65 [ + + ]: 7313778 : for (uint8_t j = 0; j < 8; ++j)
# 66 : 6501136 : *(ptr++) = InsecureRand32();
# 67 : 812642 : }
# 68 : : /** We make a copy of the hashes because future optimizations of the
# 69 : : * cuckoocache may overwrite the inserted element, so the test is
# 70 : : * "future proofed".
# 71 : : */
# 72 : 10 : std::vector<uint256> hashes_insert_copy = hashes;
# 73 : : /** Do the insert */
# 74 [ + + ]: 10 : for (const uint256& h : hashes_insert_copy)
# 75 : 812642 : set.insert(h);
# 76 : : /** Count the hits */
# 77 : 10 : uint32_t count = 0;
# 78 [ + + ]: 10 : for (const uint256& h : hashes)
# 79 : 812642 : count += set.contains(h, false);
# 80 : 10 : double hit_rate = ((double)count) / ((double)n_insert);
# 81 : 10 : return hit_rate;
# 82 : 10 : }
# 83 : :
# 84 : : /** The normalized hit rate for a given load.
# 85 : : *
# 86 : : * The semantics are a little confusing, so please see the below
# 87 : : * explanation.
# 88 : : *
# 89 : : * Examples:
# 90 : : *
# 91 : : * 1. at load 0.5, we expect a perfect hit rate, so we multiply by
# 92 : : * 1.0
# 93 : : * 2. at load 2.0, we expect to see half the entries, so a perfect hit rate
# 94 : : * would be 0.5. Therefore, if we see a hit rate of 0.4, 0.4*2.0 = 0.8 is the
# 95 : : * normalized hit rate.
# 96 : : *
# 97 : : * This is basically the right semantics, but has a bit of a glitch depending on
# 98 : : * how you measure around load 1.0 as after load 1.0 your normalized hit rate
# 99 : : * becomes effectively perfect, ignoring freshness.
# 100 : : */
# 101 : : static double normalize_hit_rate(double hits, double load)
# 102 : 10 : {
# 103 : 10 : return hits * std::max(load, 1.0);
# 104 : 10 : }
# 105 : :
# 106 : : /** Check the hit rate on loads ranging from 0.1 to 1.6 */
# 107 : : BOOST_AUTO_TEST_CASE(cuckoocache_hit_rate_ok)
# 108 : 2 : {
# 109 : : /** Arbitrarily selected Hit Rate threshold that happens to work for this test
# 110 : : * as a lower bound on performance.
# 111 : : */
# 112 : 2 : double HitRateThresh = 0.98;
# 113 : 2 : size_t megabytes = 4;
# 114 [ + + ]: 12 : for (double load = 0.1; load < 2; load *= 2) {
# 115 : 10 : double hits = test_cache<CuckooCache::cache<uint256, SignatureCacheHasher>>(megabytes, load);
# 116 : 10 : BOOST_CHECK(normalize_hit_rate(hits, load) > HitRateThresh);
# 117 : 10 : }
# 118 : 2 : }
# 119 : :
# 120 : :
# 121 : : /** This helper checks that erased elements are preferentially inserted onto and
# 122 : : * that the hit rate of "fresher" keys is reasonable*/
# 123 : : template <typename Cache>
# 124 : : static void test_cache_erase(size_t megabytes)
# 125 : 2 : {
# 126 : 2 : double load = 1;
# 127 : 2 : SeedInsecureRand(SeedRand::ZEROS);
# 128 : 2 : std::vector<uint256> hashes;
# 129 : 2 : Cache set{};
# 130 : 2 : size_t bytes = megabytes * (1 << 20);
# 131 : 2 : set.setup_bytes(bytes);
# 132 : 2 : uint32_t n_insert = static_cast<uint32_t>(load * (bytes / sizeof(uint256)));
# 133 : 2 : hashes.resize(n_insert);
# 134 [ + + ]: 262146 : for (uint32_t i = 0; i < n_insert; ++i) {
# 135 : 262144 : uint32_t* ptr = (uint32_t*)hashes[i].begin();
# 136 [ + + ]: 2359296 : for (uint8_t j = 0; j < 8; ++j)
# 137 : 2097152 : *(ptr++) = InsecureRand32();
# 138 : 262144 : }
# 139 : : /** We make a copy of the hashes because future optimizations of the
# 140 : : * cuckoocache may overwrite the inserted element, so the test is
# 141 : : * "future proofed".
# 142 : : */
# 143 : 2 : std::vector<uint256> hashes_insert_copy = hashes;
# 144 : :
# 145 : : /** Insert the first half */
# 146 [ + + ]: 131074 : for (uint32_t i = 0; i < (n_insert / 2); ++i)
# 147 : 131072 : set.insert(hashes_insert_copy[i]);
# 148 : : /** Erase the first quarter */
# 149 [ + + ]: 65538 : for (uint32_t i = 0; i < (n_insert / 4); ++i)
# 150 : 65536 : BOOST_CHECK(set.contains(hashes[i], true));
# 151 : : /** Insert the second half */
# 152 [ + + ]: 131074 : for (uint32_t i = (n_insert / 2); i < n_insert; ++i)
# 153 : 131072 : set.insert(hashes_insert_copy[i]);
# 154 : :
# 155 : : /** elements that we marked as erased but are still there */
# 156 : 2 : size_t count_erased_but_contained = 0;
# 157 : : /** elements that we did not erase but are older */
# 158 : 2 : size_t count_stale = 0;
# 159 : : /** elements that were most recently inserted */
# 160 : 2 : size_t count_fresh = 0;
# 161 : :
# 162 [ + + ]: 65538 : for (uint32_t i = 0; i < (n_insert / 4); ++i)
# 163 : 65536 : count_erased_but_contained += set.contains(hashes[i], false);
# 164 [ + + ]: 65538 : for (uint32_t i = (n_insert / 4); i < (n_insert / 2); ++i)
# 165 : 65536 : count_stale += set.contains(hashes[i], false);
# 166 [ + + ]: 131074 : for (uint32_t i = (n_insert / 2); i < n_insert; ++i)
# 167 : 131072 : count_fresh += set.contains(hashes[i], false);
# 168 : :
# 169 : 2 : double hit_rate_erased_but_contained = double(count_erased_but_contained) / (double(n_insert) / 4.0);
# 170 : 2 : double hit_rate_stale = double(count_stale) / (double(n_insert) / 4.0);
# 171 : 2 : double hit_rate_fresh = double(count_fresh) / (double(n_insert) / 2.0);
# 172 : :
# 173 : : // Check that our hit_rate_fresh is perfect
# 174 : 2 : BOOST_CHECK_EQUAL(hit_rate_fresh, 1.0);
# 175 : : // Check that we have a more than 2x better hit rate on stale elements than
# 176 : : // erased elements.
# 177 : 2 : BOOST_CHECK(hit_rate_stale > 2 * hit_rate_erased_but_contained);
# 178 : 2 : }
# 179 : :
# 180 : : BOOST_AUTO_TEST_CASE(cuckoocache_erase_ok)
# 181 : 2 : {
# 182 : 2 : size_t megabytes = 4;
# 183 : 2 : test_cache_erase<CuckooCache::cache<uint256, SignatureCacheHasher>>(megabytes);
# 184 : 2 : }
# 185 : :
# 186 : : template <typename Cache>
# 187 : : static void test_cache_erase_parallel(size_t megabytes)
# 188 : 2 : {
# 189 : 2 : double load = 1;
# 190 : 2 : SeedInsecureRand(SeedRand::ZEROS);
# 191 : 2 : std::vector<uint256> hashes;
# 192 : 2 : Cache set{};
# 193 : 2 : size_t bytes = megabytes * (1 << 20);
# 194 : 2 : set.setup_bytes(bytes);
# 195 : 2 : uint32_t n_insert = static_cast<uint32_t>(load * (bytes / sizeof(uint256)));
# 196 : 2 : hashes.resize(n_insert);
# 197 [ + + ]: 262146 : for (uint32_t i = 0; i < n_insert; ++i) {
# 198 : 262144 : uint32_t* ptr = (uint32_t*)hashes[i].begin();
# 199 [ + + ]: 2359296 : for (uint8_t j = 0; j < 8; ++j)
# 200 : 2097152 : *(ptr++) = InsecureRand32();
# 201 : 262144 : }
# 202 : : /** We make a copy of the hashes because future optimizations of the
# 203 : : * cuckoocache may overwrite the inserted element, so the test is
# 204 : : * "future proofed".
# 205 : : */
# 206 : 2 : std::vector<uint256> hashes_insert_copy = hashes;
# 207 : 2 : std::shared_mutex mtx;
# 208 : :
# 209 : 2 : {
# 210 : : /** Grab lock to make sure we release inserts */
# 211 : 2 : std::unique_lock<std::shared_mutex> l(mtx);
# 212 : : /** Insert the first half */
# 213 [ + + ]: 131074 : for (uint32_t i = 0; i < (n_insert / 2); ++i)
# 214 : 131072 : set.insert(hashes_insert_copy[i]);
# 215 : 2 : }
# 216 : :
# 217 : : /** Spin up 3 threads to run contains with erase.
# 218 : : */
# 219 : 2 : std::vector<std::thread> threads;
# 220 : : /** Erase the first quarter */
# 221 [ + + ]: 8 : for (uint32_t x = 0; x < 3; ++x)
# 222 : : /** Each thread is emplaced with x copy-by-value
# 223 : : */
# 224 : 6 : threads.emplace_back([&, x] {
# 225 : 6 : std::shared_lock<std::shared_mutex> l(mtx);
# 226 : 6 : size_t ntodo = (n_insert/4)/3;
# 227 : 6 : size_t start = ntodo*x;
# 228 : 6 : size_t end = ntodo*(x+1);
# 229 [ + + ]: 65194 : for (uint32_t i = start; i < end; ++i) {
# 230 : 65188 : bool contains = set.contains(hashes[i], true);
# 231 : 65188 : assert(contains);
# 232 : 65188 : }
# 233 : 6 : });
# 234 : :
# 235 : : /** Wait for all threads to finish
# 236 : : */
# 237 [ + + ]: 2 : for (std::thread& t : threads)
# 238 : 6 : t.join();
# 239 : : /** Grab lock to make sure we observe erases */
# 240 : 2 : std::unique_lock<std::shared_mutex> l(mtx);
# 241 : : /** Insert the second half */
# 242 [ + + ]: 131074 : for (uint32_t i = (n_insert / 2); i < n_insert; ++i)
# 243 : 131072 : set.insert(hashes_insert_copy[i]);
# 244 : :
# 245 : : /** elements that we marked erased but that are still there */
# 246 : 2 : size_t count_erased_but_contained = 0;
# 247 : : /** elements that we did not erase but are older */
# 248 : 2 : size_t count_stale = 0;
# 249 : : /** elements that were most recently inserted */
# 250 : 2 : size_t count_fresh = 0;
# 251 : :
# 252 [ + + ]: 65538 : for (uint32_t i = 0; i < (n_insert / 4); ++i)
# 253 : 65536 : count_erased_but_contained += set.contains(hashes[i], false);
# 254 [ + + ]: 65538 : for (uint32_t i = (n_insert / 4); i < (n_insert / 2); ++i)
# 255 : 65536 : count_stale += set.contains(hashes[i], false);
# 256 [ + + ]: 131074 : for (uint32_t i = (n_insert / 2); i < n_insert; ++i)
# 257 : 131072 : count_fresh += set.contains(hashes[i], false);
# 258 : :
# 259 : 2 : double hit_rate_erased_but_contained = double(count_erased_but_contained) / (double(n_insert) / 4.0);
# 260 : 2 : double hit_rate_stale = double(count_stale) / (double(n_insert) / 4.0);
# 261 : 2 : double hit_rate_fresh = double(count_fresh) / (double(n_insert) / 2.0);
# 262 : :
# 263 : : // Check that our hit_rate_fresh is perfect
# 264 : 2 : BOOST_CHECK_EQUAL(hit_rate_fresh, 1.0);
# 265 : : // Check that we have a more than 2x better hit rate on stale elements than
# 266 : : // erased elements.
# 267 : 2 : BOOST_CHECK(hit_rate_stale > 2 * hit_rate_erased_but_contained);
# 268 : 2 : }
# 269 : : BOOST_AUTO_TEST_CASE(cuckoocache_erase_parallel_ok)
# 270 : 2 : {
# 271 : 2 : size_t megabytes = 4;
# 272 : 2 : test_cache_erase_parallel<CuckooCache::cache<uint256, SignatureCacheHasher>>(megabytes);
# 273 : 2 : }
# 274 : :
# 275 : :
# 276 : : template <typename Cache>
# 277 : : static void test_cache_generations()
# 278 : 2 : {
# 279 : : // This test checks that for a simulation of network activity, the fresh hit
# 280 : : // rate is never below 99%, and the number of times that it is worse than
# 281 : : // 99.9% are less than 1% of the time.
# 282 : 2 : double min_hit_rate = 0.99;
# 283 : 2 : double tight_hit_rate = 0.999;
# 284 : 2 : double max_rate_less_than_tight_hit_rate = 0.01;
# 285 : : // A cache that meets this specification is therefore shown to have a hit
# 286 : : // rate of at least tight_hit_rate * (1 - max_rate_less_than_tight_hit_rate) +
# 287 : : // min_hit_rate*max_rate_less_than_tight_hit_rate = 0.999*99%+0.99*1% == 99.89%
# 288 : : // hit rate with low variance.
# 289 : :
# 290 : : // We use deterministic values, but this test has also passed on many
# 291 : : // iterations with non-deterministic values, so it isn't "overfit" to the
# 292 : : // specific entropy in FastRandomContext(true) and implementation of the
# 293 : : // cache.
# 294 : 2 : SeedInsecureRand(SeedRand::ZEROS);
# 295 : :
# 296 : : // block_activity models a chunk of network activity. n_insert elements are
# 297 : : // added to the cache. The first and last n/4 are stored for removal later
# 298 : : // and the middle n/2 are not stored. This models a network which uses half
# 299 : : // the signatures of recently (since the last block) added transactions
# 300 : : // immediately and never uses the other half.
# 301 : 2 : struct block_activity {
# 302 : 2 : std::vector<uint256> reads;
# 303 : 2 : block_activity(uint32_t n_insert, Cache& c) : reads()
# 304 : 2620 : {
# 305 : 2620 : std::vector<uint256> inserts;
# 306 : 2620 : inserts.resize(n_insert);
# 307 : 2620 : reads.reserve(n_insert / 2);
# 308 [ + + ]: 2622620 : for (uint32_t i = 0; i < n_insert; ++i) {
# 309 : 2620000 : uint32_t* ptr = (uint32_t*)inserts[i].begin();
# 310 [ + + ]: 23580000 : for (uint8_t j = 0; j < 8; ++j)
# 311 : 20960000 : *(ptr++) = InsecureRand32();
# 312 : 2620000 : }
# 313 [ + + ]: 657620 : for (uint32_t i = 0; i < n_insert / 4; ++i)
# 314 : 655000 : reads.push_back(inserts[i]);
# 315 [ + + ]: 657620 : for (uint32_t i = n_insert - (n_insert / 4); i < n_insert; ++i)
# 316 : 655000 : reads.push_back(inserts[i]);
# 317 [ + + ]: 2620 : for (const auto& h : inserts)
# 318 : 2620000 : c.insert(h);
# 319 : 2620 : }
# 320 : 2 : };
# 321 : :
# 322 : 2 : const uint32_t BLOCK_SIZE = 1000;
# 323 : : // We expect window size 60 to perform reasonably given that each epoch
# 324 : : // stores 45% of the cache size (~472k).
# 325 : 2 : const uint32_t WINDOW_SIZE = 60;
# 326 : 2 : const uint32_t POP_AMOUNT = (BLOCK_SIZE / WINDOW_SIZE) / 2;
# 327 : 2 : const double load = 10;
# 328 : 2 : const size_t megabytes = 4;
# 329 : 2 : const size_t bytes = megabytes * (1 << 20);
# 330 : 2 : const uint32_t n_insert = static_cast<uint32_t>(load * (bytes / sizeof(uint256)));
# 331 : :
# 332 : 2 : std::vector<block_activity> hashes;
# 333 : 2 : Cache set{};
# 334 : 2 : set.setup_bytes(bytes);
# 335 : 2 : hashes.reserve(n_insert / BLOCK_SIZE);
# 336 : 2 : std::deque<block_activity> last_few;
# 337 : 2 : uint32_t out_of_tight_tolerance = 0;
# 338 : 2 : uint32_t total = n_insert / BLOCK_SIZE;
# 339 : : // we use the deque last_few to model a sliding window of blocks. at each
# 340 : : // step, each of the last WINDOW_SIZE block_activities checks the cache for
# 341 : : // POP_AMOUNT of the hashes that they inserted, and marks these erased.
# 342 [ + + ]: 2622 : for (uint32_t i = 0; i < total; ++i) {
# 343 [ + + ]: 2620 : if (last_few.size() == WINDOW_SIZE)
# 344 : 2500 : last_few.pop_front();
# 345 : 2620 : last_few.emplace_back(BLOCK_SIZE, set);
# 346 : 2620 : uint32_t count = 0;
# 347 [ + + ]: 2620 : for (auto& act : last_few)
# 348 [ + + ]: 1382940 : for (uint32_t k = 0; k < POP_AMOUNT; ++k) {
# 349 : 1229280 : count += set.contains(act.reads.back(), true);
# 350 : 1229280 : act.reads.pop_back();
# 351 : 1229280 : }
# 352 : : // We use last_few.size() rather than WINDOW_SIZE for the correct
# 353 : : // behavior on the first WINDOW_SIZE iterations where the deque is not
# 354 : : // full yet.
# 355 : 2620 : double hit = (double(count)) / (last_few.size() * POP_AMOUNT);
# 356 : : // Loose Check that hit rate is above min_hit_rate
# 357 : 2620 : BOOST_CHECK(hit > min_hit_rate);
# 358 : : // Tighter check, count number of times we are less than tight_hit_rate
# 359 : : // (and implicitly, greater than min_hit_rate)
# 360 : 2620 : out_of_tight_tolerance += hit < tight_hit_rate;
# 361 : 2620 : }
# 362 : : // Check that being out of tolerance happens less than
# 363 : : // max_rate_less_than_tight_hit_rate of the time
# 364 : 2 : BOOST_CHECK(double(out_of_tight_tolerance) / double(total) < max_rate_less_than_tight_hit_rate);
# 365 : 2 : }
# 366 : : BOOST_AUTO_TEST_CASE(cuckoocache_generations)
# 367 : 2 : {
# 368 : 2 : test_cache_generations<CuckooCache::cache<uint256, SignatureCacheHasher>>();
# 369 : 2 : }
# 370 : :
# 371 : : BOOST_AUTO_TEST_SUITE_END();
|
