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clusterlin: improve heuristic to decide split transaction (optimization)

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Empirically, this approach seems to be more efficient in common real-life
clusters, and does not change the worst case.

Co-Authored-By: Suhas Daftuar <sdaftuar@gmail.com>
This commit is contained in:
Pieter Wuille 2024-05-09 13:45:38 -04:00
parent 71f2629398
commit bd044356ed
2 changed files with 56 additions and 2 deletions
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21
src/bench/cluster_linearize.cpp
View file

@ -324,6 +324,17 @@ static constexpr auto BENCH_EXAMPLE_12 = "80318f4c0080318f4c0180318f4c0280318f4c
static constexpr auto BENCH_EXAMPLE_13 = "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"_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 = "800dd042008028b13c018028b13c028028b13c038029b13c048029b13c058029b13c0680299948078029b13c088029b13c09802899480a802899480b8028b13c0c80299e700d802899480e802999480f8029b13c10802999481180299948128028b13c138029b13c1480289e701580289948168028b13c1780289948188028994819802899481a802999481b802999481c802899481d802999481e8028b13c1f8029b13c20802999482180299948228028b13c2380298c242480289948258029b13c2680288c242780298c242880299e70298f5a80ea762a824780aa00292a82038090402429813fcf00152a8203809040142a813ff700112982038090402d002d813ff70028002c8203809040270024824780aa00270025820380904025002882038090401e022a82038090401d042782038090401c01298203809040190029813ff700170028813ff700140128807b9258120128841280f6402c01002e82038090402b00062b820380904027000031813ff70011192d82038090401d000129851981a9403a0000003b82038090400c182e813ff7000b0f2982038090401314141b807b925805192b84568190001121000334807bdd400149824780aa00001f2a813ff700003d0b8203809040050d1915807bdd4001498728828f400b010004050501000a050c851981a9400104050b061a0400"_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); }
@ -339,6 +350,11 @@ static void LinearizeOptimallyExample11(benchmark::Bench& bench) { BenchLineariz
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);
@ -396,3 +412,8 @@ 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);

37
src/cluster_linearize.h
View file

@ -828,8 +828,41 @@ public:
if (m_sorted_depgraph.FeeRate(first) <= best.feerate) return;
}
// Pick the first undecided transaction as the one to split on.
const ClusterIndex split = first;
// Decide which transaction to split on. Splitting is how new work items are added, and
// how progress is made. One split transaction is chosen among the queue item's
// undecided ones, and:
// - A work item is (potentially) added with that transaction plus its remaining
// descendants excluded (removed from the und set).
// - A work item is (potentially) added with that transaction plus its remaining
// ancestors included (added to the inc set).
//
// To decide what to split on, consider the undecided ancestors of the highest
// individual feerate undecided transaction. Pick the one which reduces the search space
// most. Let I(t) be the size of the undecided set after including t, and E(t) the size
// of the undecided set after excluding t. Then choose the split transaction t such
// that 2^I(t) + 2^E(t) is minimal, tie-breaking by highest individual feerate for t.
ClusterIndex split = 0;
const auto select = elem.und & m_sorted_depgraph.Ancestors(first);
Assume(select.Any());
std::optional<std::pair<ClusterIndex, ClusterIndex>> split_counts;
for (auto t : select) {
// Call max = max(I(t), E(t)) and min = min(I(t), E(t)). Let counts = {max,min}.
// Sorting by the tuple counts is equivalent to sorting by 2^I(t) + 2^E(t). This
// expression is equal to 2^max + 2^min = 2^max * (1 + 1/2^(max - min)). The second
// factor (1 + 1/2^(max - min)) there is in (1,2]. Thus increasing max will always
// increase it, even when min decreases. Because of this, we can first sort by max.
std::pair<ClusterIndex, ClusterIndex> counts{
(elem.und - m_sorted_depgraph.Ancestors(t)).Count(),
(elem.und - m_sorted_depgraph.Descendants(t)).Count()};
if (counts.first < counts.second) std::swap(counts.first, counts.second);
// Remember the t with the lowest counts.
if (!split_counts.has_value() || counts < *split_counts) {
split = t;
split_counts = counts;
}
}
// Since there was at least one transaction in select, we must always find one.
Assume(split_counts.has_value());
// Add a work item corresponding to exclusion of the split transaction.
const auto& desc = m_sorted_depgraph.Descendants(split);