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clusterlin: split up OptimizeStep (refactor)

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This commit is contained in:
Pieter Wuille 2026-01-23 23:06:32 -05:00
parent cbd684a471
commit dcf458ffb9
1 changed files with 60 additions and 42 deletions
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102
src/cluster_linearize.h
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@ -974,6 +974,54 @@ private:
MergeSequence<true>(child_idx);
}
/** Determine the next chunk to optimize, or INVALID_SET_IDX if none. */
SetIdx PickChunkToOptimize() noexcept
{
while (!m_suboptimal_chunks.empty()) {
// Pop an entry from the potentially-suboptimal chunk queue.
SetIdx chunk_idx = m_suboptimal_chunks.front();
m_suboptimal_chunks.pop_front();
if (m_chunk_idxs[chunk_idx]) return chunk_idx;
// If what was popped is not currently a chunk, continue. This may
// happen when a split chunk merges in Improve() with one or more existing chunks that
// are themselves on the suboptimal queue already.
}
return INVALID_SET_IDX;
}
/** Find a (parent, child) dependency to deactivate in chunk_idx, or (-1, -1) if none. */
std::pair<TxIdx, TxIdx> PickDependencyToSplit(SetIdx chunk_idx) noexcept
{
Assume(m_chunk_idxs[chunk_idx]);
auto& chunk_info = m_set_info[chunk_idx];
// Remember the best dependency {par, chl} seen so far.
std::pair<TxIdx, TxIdx> candidate_dep = {TxIdx(-1), TxIdx(-1)};
uint64_t candidate_tiebreak = 0;
// Iterate over all transactions.
for (auto tx_idx : chunk_info.transactions) {
const auto& tx_data = m_tx_data[tx_idx];
// Iterate over all active child dependencies of the transaction.
for (auto child_idx : tx_data.children) {
if (tx_data.dep_top_idx[child_idx] == INVALID_SET_IDX) continue;
auto& dep_top_info = m_set_info[tx_data.dep_top_idx[child_idx]];
// Skip if this dependency is ineligible (the top chunk that would be created
// does not have higher feerate than the chunk it is currently part of).
auto cmp = FeeRateCompare(dep_top_info.feerate, chunk_info.feerate);
if (cmp <= 0) continue;
// Generate a random tiebreak for this dependency, and reject it if its tiebreak
// is worse than the best so far. This means that among all eligible
// dependencies, a uniformly random one will be chosen.
uint64_t tiebreak = m_rng.rand64();
if (tiebreak < candidate_tiebreak) continue;
// Remember this as our (new) candidate dependency.
candidate_dep = {tx_idx, child_idx};
candidate_tiebreak = tiebreak;
}
}
return candidate_dep;
}
public:
/** Construct a spanning forest for the given DepGraph, with every transaction in its own chunk
* (not topological). */
@ -1077,50 +1125,20 @@ public:
/** Try to improve the forest. Returns false if it is optimal, true otherwise. */
bool OptimizeStep() noexcept
{
while (!m_suboptimal_chunks.empty()) {
// Pop an entry from the potentially-suboptimal chunk queue.
SetIdx chunk_idx = m_suboptimal_chunks.front();
m_suboptimal_chunks.pop_front();
auto& chunk_info = m_set_info[chunk_idx];
// If what was popped is not currently a chunk, continue. This may
// happen when a split chunk merges in Improve() with one or more existing chunks that
// are themselves on the suboptimal queue already.
if (!m_chunk_idxs[chunk_idx]) continue;
// Remember the best dependency {par, chl} seen so far.
std::pair<TxIdx, TxIdx> candidate_dep = {TxIdx(-1), TxIdx(-1)};
uint64_t candidate_tiebreak = 0;
// Iterate over all transactions.
for (auto tx_idx : chunk_info.transactions) {
const auto& tx_data = m_tx_data[tx_idx];
// Iterate over all active child dependencies of the transaction.
for (auto child_idx : tx_data.children) {
if (tx_data.dep_top_idx[child_idx] == INVALID_SET_IDX) continue;
auto& dep_top_info = m_set_info[tx_data.dep_top_idx[child_idx]];
// Skip if this dependency is ineligible (the top chunk that would be created
// does not have higher feerate than the chunk it is currently part of).
auto cmp = FeeRateCompare(dep_top_info.feerate, chunk_info.feerate);
if (cmp <= 0) continue;
// Generate a random tiebreak for this dependency, and reject it if its tiebreak
// is worse than the best so far. This means that among all eligible
// dependencies, a uniformly random one will be chosen.
uint64_t tiebreak = m_rng.rand64();
if (tiebreak < candidate_tiebreak) continue;
// Remember this as our (new) candidate dependency.
candidate_dep = {tx_idx, child_idx};
candidate_tiebreak = tiebreak;
}
}
// If a candidate with positive gain was found, deactivate it and then make the state
// topological again with a sequence of merges.
if (candidate_dep.first != TxIdx(-1)) {
Improve(candidate_dep.first, candidate_dep.second);
}
// Stop processing for now, even if nothing was activated, as the loop above may have
// had a nontrivial cost.
auto chunk_idx = PickChunkToOptimize();
if (chunk_idx == INVALID_SET_IDX) {
// No improvable chunk was found, we are done.
return false;
}
auto [parent_idx, child_idx] = PickDependencyToSplit(chunk_idx);
if (parent_idx == TxIdx(-1)) {
// Nothing to improve in chunk_idx. Need to continue with other chunks, if any.
return !m_suboptimal_chunks.empty();
}
// No improvable chunk was found, we are done.
return false;
// Deactivate the found dependency and then make the state topological again with a
// sequence of merges.
Improve(parent_idx, child_idx);
return true;
}
/** Initialize data structure for minimizing the chunks. Can only be called if state is known