diff options
Diffstat (limited to 'src/bench/cluster_linearize.cpp')
| -rw-r--r-- | src/bench/cluster_linearize.cpp | 213 |
1 files changed, 177 insertions, 36 deletions
diff --git a/src/bench/cluster_linearize.cpp b/src/bench/cluster_linearize.cpp index de85741909..7d011975dd 100644 --- a/src/bench/cluster_linearize.cpp +++ b/src/bench/cluster_linearize.cpp @@ -4,7 +4,9 @@ #include <bench/bench.h> #include <cluster_linearize.h> +#include <test/util/cluster_linearize.h> #include <util/bitset.h> +#include <util/strencodings.h> #include <algorithm> #include <cassert> @@ -12,6 +14,7 @@ #include <vector> using namespace cluster_linearize; +using namespace util::hex_literals; namespace { @@ -25,7 +28,7 @@ DepGraph<SetType> MakeLinearGraph(ClusterIndex ntx) DepGraph<SetType> depgraph; for (ClusterIndex i = 0; i < ntx; ++i) { depgraph.AddTransaction({-int32_t(i), 1}); - if (i > 0) depgraph.AddDependency(i - 1, i); + if (i > 0) depgraph.AddDependencies(SetType::Singleton(i - 1), i); } return depgraph; } @@ -40,13 +43,13 @@ DepGraph<SetType> MakeWideGraph(ClusterIndex ntx) DepGraph<SetType> depgraph; for (ClusterIndex i = 0; i < ntx; ++i) { depgraph.AddTransaction({int32_t(i) + 1, 1}); - if (i > 0) depgraph.AddDependency(0, i); + if (i > 0) depgraph.AddDependencies(SetType::Singleton(0), i); } return depgraph; } -// Construct a difficult graph. These need at least sqrt(2^(n-1)) iterations in the best -// known algorithms (purely empirically determined). +// Construct a difficult graph. These need at least sqrt(2^(n-1)) iterations in the implemented +// algorithm (purely empirically determined). template<typename SetType> DepGraph<SetType> MakeHardGraph(ClusterIndex ntx) { @@ -67,19 +70,19 @@ DepGraph<SetType> MakeHardGraph(ClusterIndex ntx) depgraph.AddTransaction({1, 2}); } else if (i == 1) { depgraph.AddTransaction({14, 2}); - depgraph.AddDependency(0, 1); + depgraph.AddDependencies(SetType::Singleton(0), 1); } else if (i == 2) { depgraph.AddTransaction({6, 1}); - depgraph.AddDependency(2, 1); + depgraph.AddDependencies(SetType::Singleton(2), 1); } else if (i == 3) { depgraph.AddTransaction({5, 1}); - depgraph.AddDependency(2, 3); + depgraph.AddDependencies(SetType::Singleton(2), 3); } else if ((i & 1) == 0) { depgraph.AddTransaction({7, 1}); - depgraph.AddDependency(i - 1, i); + depgraph.AddDependencies(SetType::Singleton(i - 1), i); } else { depgraph.AddTransaction({5, 1}); - depgraph.AddDependency(i, 4); + depgraph.AddDependencies(SetType::Singleton(i), 4); } } else { // Even cluster size. @@ -95,33 +98,34 @@ DepGraph<SetType> MakeHardGraph(ClusterIndex ntx) depgraph.AddTransaction({1, 1}); } else if (i == 1) { depgraph.AddTransaction({3, 1}); - depgraph.AddDependency(0, 1); + depgraph.AddDependencies(SetType::Singleton(0), 1); } else if (i == 2) { depgraph.AddTransaction({1, 1}); - depgraph.AddDependency(0, 2); + depgraph.AddDependencies(SetType::Singleton(0), 2); } else if (i & 1) { depgraph.AddTransaction({4, 1}); - depgraph.AddDependency(i - 1, i); + depgraph.AddDependencies(SetType::Singleton(i - 1), i); } else { depgraph.AddTransaction({0, 1}); - depgraph.AddDependency(i, 3); + depgraph.AddDependencies(SetType::Singleton(i), 3); } } } return depgraph; } -/** Benchmark that does search-based candidate finding with 10000 iterations. +/** Benchmark that does search-based candidate finding with a specified number of iterations. * - * Its goal is measuring how much time every additional search iteration in linearization costs. + * Its goal is measuring how much time every additional search iteration in linearization costs, + * by running with a low and a high count, subtracting the results, and divided by the number + * iterations difference. */ template<typename SetType> -void BenchLinearizePerIterWorstCase(ClusterIndex ntx, benchmark::Bench& bench) +void BenchLinearizeWorstCase(ClusterIndex ntx, benchmark::Bench& bench, uint64_t iter_limit) { const auto depgraph = MakeHardGraph<SetType>(ntx); - const auto iter_limit = std::min<uint64_t>(10000, uint64_t{1} << (ntx / 2 - 1)); uint64_t rng_seed = 0; - bench.batch(iter_limit).unit("iters").run([&] { + bench.run([&] { SearchCandidateFinder finder(depgraph, rng_seed++); auto [candidate, iters_performed] = finder.FindCandidateSet(iter_limit, {}); assert(iters_performed == iter_limit); @@ -132,11 +136,12 @@ void BenchLinearizePerIterWorstCase(ClusterIndex ntx, benchmark::Bench& bench) * * Its goal is measuring how much time linearization may take without any search iterations. * - * If P is the resulting time of BenchLinearizePerIterWorstCase, and N is the resulting time of - * BenchLinearizeNoItersWorstCase*, then an invocation of Linearize with max_iterations=m should - * take no more than roughly N+m*P time. This may however be an overestimate, as the worst cases - * do not coincide (the ones that are worst for linearization without any search happen to be ones - * that do not need many search iterations). + * If P is the benchmarked per-iteration count (obtained by running BenchLinearizeWorstCase for a + * high and a low iteration count, subtracting them, and dividing by the difference in count), and + * N is the resulting time of BenchLinearizeNoItersWorstCase*, then an invocation of Linearize with + * max_iterations=m should take no more than roughly N+m*P time. This may however be an + * overestimate, as the worst cases do not coincide (the ones that are worst for linearization + * without any search happen to be ones that do not need many search iterations). * * This benchmark exercises a worst case for AncestorCandidateFinder, but for which improvement is * cheap. @@ -190,7 +195,7 @@ void BenchMergeLinearizationsWorstCase(ClusterIndex ntx, benchmark::Bench& bench DepGraph<SetType> depgraph; for (ClusterIndex i = 0; i < ntx; ++i) { depgraph.AddTransaction({i, 1}); - if (i) depgraph.AddDependency(0, i); + if (i) depgraph.AddDependencies(SetType::Singleton(0), i); } std::vector<ClusterIndex> lin1; std::vector<ClusterIndex> lin2; @@ -205,14 +210,57 @@ void BenchMergeLinearizationsWorstCase(ClusterIndex ntx, benchmark::Bench& bench }); } +template<size_t N> +void BenchLinearizeOptimally(benchmark::Bench& bench, const std::array<uint8_t, N>& serialized) +{ + // Determine how many transactions the serialized cluster has. + ClusterIndex num_tx{0}; + { + SpanReader reader{serialized}; + DepGraph<BitSet<128>> depgraph; + reader >> Using<DepGraphFormatter>(depgraph); + num_tx = depgraph.TxCount(); + assert(num_tx < 128); + } + + SpanReader reader{serialized}; + auto runner_fn = [&]<typename SetType>() noexcept { + DepGraph<SetType> depgraph; + reader >> Using<DepGraphFormatter>(depgraph); + uint64_t rng_seed = 0; + bench.run([&] { + auto res = Linearize(depgraph, /*max_iterations=*/10000000, rng_seed++); + assert(res.second); + }); + }; + + if (num_tx <= 32) { + runner_fn.template operator()<BitSet<32>>(); + } else if (num_tx <= 64) { + runner_fn.template operator()<BitSet<64>>(); + } else if (num_tx <= 96) { + runner_fn.template operator()<BitSet<96>>(); + } else if (num_tx <= 128) { + runner_fn.template operator()<BitSet<128>>(); + } else { + assert(false); + } +} + } // namespace -static void LinearizePerIter16TxWorstCase(benchmark::Bench& bench) { BenchLinearizePerIterWorstCase<BitSet<16>>(16, bench); } -static void LinearizePerIter32TxWorstCase(benchmark::Bench& bench) { BenchLinearizePerIterWorstCase<BitSet<32>>(32, bench); } -static void LinearizePerIter48TxWorstCase(benchmark::Bench& bench) { BenchLinearizePerIterWorstCase<BitSet<48>>(48, bench); } -static void LinearizePerIter64TxWorstCase(benchmark::Bench& bench) { BenchLinearizePerIterWorstCase<BitSet<64>>(64, bench); } -static void LinearizePerIter75TxWorstCase(benchmark::Bench& bench) { BenchLinearizePerIterWorstCase<BitSet<75>>(75, bench); } -static void LinearizePerIter99TxWorstCase(benchmark::Bench& bench) { BenchLinearizePerIterWorstCase<BitSet<99>>(99, bench); } +static void Linearize16TxWorstCase20Iters(benchmark::Bench& bench) { BenchLinearizeWorstCase<BitSet<16>>(16, bench, 20); } +static void Linearize16TxWorstCase120Iters(benchmark::Bench& bench) { BenchLinearizeWorstCase<BitSet<16>>(16, bench, 120); } +static void Linearize32TxWorstCase5000Iters(benchmark::Bench& bench) { BenchLinearizeWorstCase<BitSet<32>>(32, bench, 5000); } +static void Linearize32TxWorstCase15000Iters(benchmark::Bench& bench) { BenchLinearizeWorstCase<BitSet<32>>(32, bench, 15000); } +static void Linearize48TxWorstCase5000Iters(benchmark::Bench& bench) { BenchLinearizeWorstCase<BitSet<48>>(48, bench, 5000); } +static void Linearize48TxWorstCase15000Iters(benchmark::Bench& bench) { BenchLinearizeWorstCase<BitSet<48>>(48, bench, 15000); } +static void Linearize64TxWorstCase5000Iters(benchmark::Bench& bench) { BenchLinearizeWorstCase<BitSet<64>>(64, bench, 5000); } +static void Linearize64TxWorstCase15000Iters(benchmark::Bench& bench) { BenchLinearizeWorstCase<BitSet<64>>(64, bench, 15000); } +static void Linearize75TxWorstCase5000Iters(benchmark::Bench& bench) { BenchLinearizeWorstCase<BitSet<75>>(75, bench, 5000); } +static void Linearize75TxWorstCase15000Iters(benchmark::Bench& bench) { BenchLinearizeWorstCase<BitSet<75>>(75, bench, 15000); } +static void Linearize99TxWorstCase5000Iters(benchmark::Bench& bench) { BenchLinearizeWorstCase<BitSet<99>>(99, bench, 5000); } +static void Linearize99TxWorstCase15000Iters(benchmark::Bench& bench) { BenchLinearizeWorstCase<BitSet<99>>(99, bench, 15000); } static void LinearizeNoIters16TxWorstCaseAnc(benchmark::Bench& bench) { BenchLinearizeNoItersWorstCaseAnc<BitSet<16>>(16, bench); } static void LinearizeNoIters32TxWorstCaseAnc(benchmark::Bench& bench) { BenchLinearizeNoItersWorstCaseAnc<BitSet<32>>(32, bench); } @@ -242,12 +290,84 @@ static void MergeLinearizations64TxWorstCase(benchmark::Bench& bench) { BenchMer static void MergeLinearizations75TxWorstCase(benchmark::Bench& bench) { BenchMergeLinearizationsWorstCase<BitSet<75>>(75, bench); } static void MergeLinearizations99TxWorstCase(benchmark::Bench& bench) { BenchMergeLinearizationsWorstCase<BitSet<99>>(99, bench); } -BENCHMARK(LinearizePerIter16TxWorstCase, benchmark::PriorityLevel::HIGH); -BENCHMARK(LinearizePerIter32TxWorstCase, benchmark::PriorityLevel::HIGH); -BENCHMARK(LinearizePerIter48TxWorstCase, benchmark::PriorityLevel::HIGH); -BENCHMARK(LinearizePerIter64TxWorstCase, benchmark::PriorityLevel::HIGH); -BENCHMARK(LinearizePerIter75TxWorstCase, benchmark::PriorityLevel::HIGH); -BENCHMARK(LinearizePerIter99TxWorstCase, benchmark::PriorityLevel::HIGH); +// The following example clusters were constructed by replaying historical mempool activity, and +// selecting for ones that take many iterations (after the introduction of some but not all +// linearization algorithm optimizations). + +/* 2023-05-05T23:12:21Z 71, 521780, 543141,*/ +static constexpr auto BENCH_EXAMPLE_00 = "801081a5360092239efc6201810982ab58029b6b98c86803800eed7804800ecb7e058f2f878778068030d43407853e81902a08962a81d176098010b6620a8010b2280b8010da3a0c9f069da9580d800db11e0e9d719ad37a0f967897ed5210990e99fc0e11812c81982012804685823e0f0a893982b6040a10804682c146110a6e80db5c120a8010819806130a8079858f0c140a8054829a120c12803483a1760c116f81843c0d11718189000e11800d81ac2c0f11800d81e50e10117181c77c1111822e87f2601012815983d17211127180f2121212811584a21e1312800e80d1781412813c83e81815126f80ef5016126f80ff6c16126f80f66017126e80fd541812800d81942a1912800e80dd781a12800d81f96c1b12805282e7581b127180fd721c1271a918230b805fc11a220d8118a15a2d036f80e5002011817684d8241e346f80e1181c37805082fc04260024800d81f8621734803382b354270b12805182ca2e162f800e80d52e0d32803dc360201b850e818c400b318c49808a5a290210805181d65823142a800d81a34e0850800e81fb3c0851886994fc0a280b00082c805482d208032e28805e83ba380059801081cd4a0159811884f770002e0015e17280e49024300a0000000000000031803dcb48014200"_hex_u8; +/* 2023-12-06T09:30:01Z 81, 141675, 647053,*/ +static constexpr auto BENCH_EXAMPLE_01 = "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"_hex_u8; +/* 2023-04-04T00:26:50Z 90, 99930, 529375,*/ +static constexpr auto BENCH_EXAMPLE_02 = "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"_hex_u8; +/* 2023-05-08T15:51:59Z 87, 76869, 505222,*/ +static constexpr auto BENCH_EXAMPLE_03 = "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"_hex_u8; +/* 2023-05-01T19:32:10Z 35, 55747, 504128,*/ +static constexpr auto BENCH_EXAMPLE_04 = "801af95c00801af72801801af95c02873e85f2180202873e85f2180202873e85f21802028018fb2802068018fb2803068018fb2804068018fb2805068018fb2806068018fb2807068018fb2808068018fb2809068018fb280a068018fb280a058018fb280b058018fb280c058018fb280d058018fb280e058018fb280f058018fb2810058018fb2811058018fb2812058018fb2813058018fb2814058018fb2815058018fb2815048018fb2816048018fb2817048018fb2818048018fb2819048018fb281a048018fb281b04810d80d9481f00000100"_hex_u8; +/* 2023-02-27T17:06:38Z 60, 55680, 502749,*/ +static constexpr auto BENCH_EXAMPLE_05 = "b5108ab56600b26d89f85601b07383b01602b22683c96003b34a83d82e04b12f83b53a05b20e83c75a066e80840a06068040be0007066fb10608066fb2120906800eba320a06842b80b05a0a066eff420b067199300b068124c3140c0680618085180d066faa1c0e068010b4440f068051af541006800da1781106857881946812066eee1613068052b31014068324808d361506806180885c150671b03216066ef11017068052b63218066ef3521806803f80865419066e93441a068035a13e1b0680628085181c06806ec4481d068117e72c1e06719c721f068077c42420068159808d1821066eef0c21058010b90022056f9908230571993024058010b00a25058010b00a260580608087402705803fc10027068032b42828068051b6322906800db11e212a8324808d361933803ff400192f826381a7141a2f8032ac08152a800db54c044e8323808d3630010002018158d84000042d821cea12002807853580d462002d01891181d022002e00"_hex_u8; +/* 2023-04-20T22:25:49Z 99, 49100, 578622,*/ +static constexpr auto BENCH_EXAMPLE_06 = "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"_hex_u8; +/* 2023-06-05T19:56:12Z 52, 44896, 540514,*/ +static constexpr auto BENCH_EXAMPLE_07 = "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"_hex_u8; +/* 2023-12-05T23:48:44Z 69, 44283, 586734,*/ +static constexpr auto BENCH_EXAMPLE_08 = "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"_hex_u8; +/* 2023-04-14T19:36:52Z 77, 20418, 501117,*/ +static constexpr auto BENCH_EXAMPLE_09 = "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"_hex_u8; +/* 2023-11-07T17:59:35Z 48, 4792, 498995,*/ +static constexpr auto BENCH_EXAMPLE_10 = "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"_hex_u8; +/* 2023-11-16T10:47:08Z 77, 473962, 486863,*/ +static constexpr auto BENCH_EXAMPLE_11 = "801980c06000801980c06001801980c06002801980c06003801980c06004801980c06005801980c06006801980c06007801980c06008801980c06009801980c0600a801980c0600b801980c0600c801980c0600d801980c0600e801980c0600f801980c060108019d12c11800f80b1601111800f80b1601111801080b1601111800f80b160100e800f80b160100f801980c060110f800f80b160140d801180b1601111801180b160100d801180b160120c801180b1600f10801180b1600f11801980c0601011800f80b160140e800f80b160110f801980c060170a801180b1601210801980c060140f800f80b1601311801980c0602005801180b1601f07800f80b1601b0c800fca7c1611812081f9601638812081f9601637812081fb001636801080b160142f801980c0600e2a801080b1600f2a801180b1600d25801980c0600e25800f80b1600d27801980c0600e27801980c0600d27801180b1600e26812080b1500c27812081f960201025812081f960200f27812081fc201d101c812081fc201d101d812081fc201d0f1f812081fc201d0f20812081f9601b1016800f80b1600a35800f80b1600a36800f80b1600e32801080b160122f812081f960280040812081fc20121d1b812081f960112713812081f960160d37812081fc20140d2b812081f960130d2d812081fc20130c2c812081fb001b0157812081fb001a0245812081fc20140030812081fc20092747812081fb000b152500"_hex_u8; +/* 2023-10-06T20:44:09Z 40, 341438, 341438,*/ +static constexpr auto BENCH_EXAMPLE_12 = "80318f4c0080318f4c0180318f4c0280318f4c0380318f4c0480318f4c0580318f4c0680318f4c078033a57807078033a57807078033a57807078033a57807078033a57807078033a57807078033a57807078033a578070780318f4c0e0180318f4c0d0380318f4c0c0580318f4c0b078033a57803128033a57803128033a57803128033a578031280318f4c0412810b9c28140300810c9c281303028033a57802188033a57802188033a5780218810c9c280b01108033a578001c810c9c2807050f8033a578001b810c98040700158033a578001c810c98040301158033a5780019806ca1240101118033a578001300"_hex_u8; +/* 2023-11-15T21:40:46Z 96, 23608, 138286,*/ +static constexpr auto BENCH_EXAMPLE_13 = "8060829f4000b157bab07a01b27cc2b16802b22fbce54603826480a95804803da81a05bc7bcac93806800de55207800daf0608805bc71809805bc7180a800d9d4a0b805bbc700c8152d7180d805bb9380e850a8886260f800d80d33410bf38d3d55011b41dc4eb6012bd70d2ce2e138d3596af7812137180cd501313805e81f7281413718092001513803d81f90016136e8b916c1713801081861a17106e80cd2a18106f80cc3c19106e80cf161911800d80fe781b107180d87c1c106e80fb081d10803e8286701d11800d81c4781f10804082a6002010801081912e21107180ff0021116e81da4a2310850b8b864023116e89db3224116e84ff7e2610897c95993427106f80bb1a240b803581c272250b8032828c10260b6e80d42a270b804082b35a280b800d80fe3e290b805cc0282312821d8697022b0b6e8add562c0b805281c8063007811883f1082313800d80fe3e24137180c9142513800d8380102613803382c00e2713805eb32228136e8494542913800e8186742913806082b74c2a1380528285782b13800d818f7a2c136e84a5562d1380508286702e136f80a46e3e04803f8191364102805481ad4c3d076e809a5a3e077180fe4032136e838b7233138c4790cf384106853584ab624206805b80932a4801806280966c48028168ef04400b7181bd524903806282db5c375b9316acbf703a599c68c5a454385c6e81d63e364a6f80ff64334e817485a6784f023171819536234e800d81826e1e498053829a12420018834c87cb14291d2e840e8bc94c1d2825800d81b7220368811783fe0e271f1f811783e758380f001ecd55809edf6e56000000003a815984ba76008010d54d80aebb4e2c22000000000000002c807682f150007a00"_hex_u8; +/* 2023-12-06T09:18:20Z 93, 68130, 122830,*/ +static constexpr auto BENCH_EXAMPLE_14 = "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"_hex_u8; +/* 2023-12-14T02:02:29Z 55, 247754, 247754,*/ +static constexpr auto BENCH_EXAMPLE_15 = "801980c06000801980c06001801980c06002801980c06003801980c06004801980c06005801980c06006801980c06007801980c06008801980c06009801980c0600a801980c0600b801980c0600c801980c0600d801980c0600e801180b1600e0e801180b1600e0e801180b1600e0e801180b1600e0e801180b1600e0e801180b1600e0e801180b1600d07801180b1600f06801180b1600c0a801180b1600f08801180b1600c0c801180b1600c0d801180b1600c0e801180b160100b801180b1601309812081fc200e2a812081fc200e29812081fc200e28812081fc200e0e18812081fc200e0e17801980c060042e812081fc200e0d07812081fc200e0d08812081fc200e0c0a812081fc200e0d0a801980c060081e812081fc200f0c0c812081fc200f0c0d812081fc200f0c0e801180b160083a801180b1600426801980c0600b20801980c0600a22812081fc200f0b30801180b160022b801180b160022b812081fc20062422812081fc2006220b812081fc200c0a1e812081fc2012041a00"_hex_u8; +/* 2023-12-14T15:17:20Z 76, 102600, 103935,*/ +static constexpr auto BENCH_EXAMPLE_16 = "801980c06000801980c06001801980c06002801980c06003801980c06004801180b1600404801180b1600404801180b1600404801980c0600504801980c0600802801980c0600803801180b1600704801980c0600804801280b1600804812081fc200810812081fc20080f812081fc20080e801180b160080c800f80b160080d801980c060090d801180b160090e801980c0600a0e812181fc200a0c801180b1600a0d812181fd400a0c801980c0600a1c801980c0600916801180b1600719801180b160061b801980c0600d15801980c0600717812081fc200718801980c0600716801180b160072d801180b1600722801180b1600525801980c060091b801980c060071e801080b160071f801280b160061d812081fc20063a812181f960160815801280b1600525801980c0600625801180b1600626801980c0600726801980c0600536801180b160032b801980c060042b801280b160032d801980c060033e801180b160043e812181fc20100c27801080b160042f801980c0600342801180b1600442812081fc20150d25800f80b1600245812081fd40120619812081fc20040243812081fc20120c2c812081fd40120a1d812181fb00100623812081fc20030347812081fc20072126801980c0600236812081fc20040d2b812081fc20120328801980c0600237801180b1600337812081fc20052230801180b1600239812081fc2008242c812081fd4005112d812081fb00070b32812081f96011034700"_hex_u8; +/* 2023-12-15T07:12:29Z 98, 112693, 112730,*/ +static constexpr auto BENCH_EXAMPLE_17 = "801980c06000801980c06001801980c06002801980c06003801980c06004801980c06005801980c06006801180b1600606801180b1600606801180b1600606801180b1600606801280b1600606801180b1600606801180b1600606801980c0600d00801980c0600b03801980c0600b04801980c0600f01812081fc200a16812081fc200a15812081fc200a14812081fc200a13812081fd400a12812181fc200a11812181fc200a0f801180b1600a10801180b1600a10801980c0600a10801180b1600b10801180b1600b10801980c0600621801980c0600915801980c060041b801180b160051b801980c0600f12801980c0600f13801980c0600d15801980c0600c17801980c060072e800f80b160082e812181fc200d150e801980c0600922801180b1600923801980c0600823801180b1600623801180b1600a20801180b1600e1c801180b1600b20801180b1600b21801980c0600a3e800f80b1600b3e801980c0600931801180b1600a31812181fc20140325801180b1600a30801180b160054c801180b160043b801980c0600336812181fc200253812081f960090944812081fc2007003c801980c0600339801180b1600433801980c0600453801980c0600340801980c060033d801080b160043d812081f960070854801980c060045a801180b160055a801180b1600545801980c0600643801980c0600641801280b1600739801180b1600562812081fc20121f27812181fc20210137812181fc2016112f801980c0600259801980c0600156812181fc20053a31801180b160025c801180b1600257801980c0600357812081fc200d2d1e812181fc20102444812181fc20035a801180b160035b801980c0600751812181fc2007392a812181fc20025f801980c060045e801180b1600350812081fc20070f6f801180b1600263812181fc201b1322812181fc2011283b812081fc2002442100"_hex_u8; +/* 2023-12-16T02:25:33Z 99, 112399, 112399,*/ +static constexpr auto BENCH_EXAMPLE_18 = "801980c06000801980c06001801980c06002801980c06003801980c06004801980c06005801980c06006801980c06007801180b16008801180b16009801180b1600a801180b1600a0a801180b1600a0a801180b1600a0a801180b1600a0a801980c0600d06801180b1600b09801980c0601005801180b1600c0a801980c0600d0a801980c0601106801180b1600e0a801980c0601207801980c0601207801180b160100a812081e668100a812081e668100a812081e668100a801980c0601407801980c0601606812081fc201226812081fc201225812081fc201224812081fc201223801180b1600e21801980c0600b1e801180b1600c1e801180b1601316801980c060091b801980c0601312801980c0600a1c801180b160190e801180b1601315801180b1600e1b801180b1601713801180b1600f1c801980c0600d34801980c0600d30801980c060102e801980c060122d801980c0600b2a801980c0600b2a801980c0600b2b801180b1601122801180b1600e26801180b1601025801180b1600f26812081fc20280032812081fc20270034812081fc20250034801180b1600d4b801980c0600d457a809a000d46801980c0601044801980c0600e46801180b1600f43801180b160123f801180b160123e801180b1601130801180b1601131801180b1601131812081fc20230a36801980c0600a5a801180b1600a5b801980c0600a5b801180b1600b5b801980c0600b5a801180b1600f57801180b1600d3f801980c0600669801980c0600568801980c0600466801180b1600945801180b1600649801180b1600945812081fc2018234b812081fc20142534812081fc20142532812081fc20142530801180b160074d801180b1600a4b801180b1600a4a812081fc20221662812081fc200c0472812081fc20072e42812081fc20062c23812081fc20100572812081fc200f036c812081fc2001345100"_hex_u8; +/* 2023-03-31T19:24:02Z 78, 90393, 152832,*/ +static constexpr auto BENCH_EXAMPLE_19 = "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"_hex_u8; + +static void LinearizeOptimallyExample00(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_00); } +static void LinearizeOptimallyExample01(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_01); } +static void LinearizeOptimallyExample02(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_02); } +static void LinearizeOptimallyExample03(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_03); } +static void LinearizeOptimallyExample04(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_04); } +static void LinearizeOptimallyExample05(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_05); } +static void LinearizeOptimallyExample06(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_06); } +static void LinearizeOptimallyExample07(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_07); } +static void LinearizeOptimallyExample08(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_08); } +static void LinearizeOptimallyExample09(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_09); } +static void LinearizeOptimallyExample10(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_10); } +static void LinearizeOptimallyExample11(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_11); } +static void LinearizeOptimallyExample12(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_12); } +static void LinearizeOptimallyExample13(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_13); } +static void LinearizeOptimallyExample14(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_14); } +static void LinearizeOptimallyExample15(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_15); } +static void LinearizeOptimallyExample16(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_16); } +static void LinearizeOptimallyExample17(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_17); } +static void LinearizeOptimallyExample18(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_18); } +static void LinearizeOptimallyExample19(benchmark::Bench& bench) { BenchLinearizeOptimally(bench, BENCH_EXAMPLE_19); } + +BENCHMARK(Linearize16TxWorstCase20Iters, benchmark::PriorityLevel::HIGH); +BENCHMARK(Linearize16TxWorstCase120Iters, benchmark::PriorityLevel::HIGH); +BENCHMARK(Linearize32TxWorstCase5000Iters, benchmark::PriorityLevel::HIGH); +BENCHMARK(Linearize32TxWorstCase15000Iters, benchmark::PriorityLevel::HIGH); +BENCHMARK(Linearize48TxWorstCase5000Iters, benchmark::PriorityLevel::HIGH); +BENCHMARK(Linearize48TxWorstCase15000Iters, benchmark::PriorityLevel::HIGH); +BENCHMARK(Linearize64TxWorstCase5000Iters, benchmark::PriorityLevel::HIGH); +BENCHMARK(Linearize64TxWorstCase15000Iters, benchmark::PriorityLevel::HIGH); +BENCHMARK(Linearize75TxWorstCase5000Iters, benchmark::PriorityLevel::HIGH); +BENCHMARK(Linearize75TxWorstCase15000Iters, benchmark::PriorityLevel::HIGH); +BENCHMARK(Linearize99TxWorstCase5000Iters, benchmark::PriorityLevel::HIGH); +BENCHMARK(Linearize99TxWorstCase15000Iters, benchmark::PriorityLevel::HIGH); BENCHMARK(LinearizeNoIters16TxWorstCaseAnc, benchmark::PriorityLevel::HIGH); BENCHMARK(LinearizeNoIters32TxWorstCaseAnc, benchmark::PriorityLevel::HIGH); @@ -276,3 +396,24 @@ BENCHMARK(MergeLinearizations48TxWorstCase, benchmark::PriorityLevel::HIGH); BENCHMARK(MergeLinearizations64TxWorstCase, benchmark::PriorityLevel::HIGH); BENCHMARK(MergeLinearizations75TxWorstCase, benchmark::PriorityLevel::HIGH); BENCHMARK(MergeLinearizations99TxWorstCase, benchmark::PriorityLevel::HIGH); + +BENCHMARK(LinearizeOptimallyExample00, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample01, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample02, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample03, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample04, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample05, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample06, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample07, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample08, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample09, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample10, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample11, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample12, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample13, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample14, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample15, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample16, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample17, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample18, benchmark::PriorityLevel::HIGH); +BENCHMARK(LinearizeOptimallyExample19, benchmark::PriorityLevel::HIGH); |