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Simplify parallel SMT code: clean comments and deduplicate stat computation
- Normalize tab to spaces on line 7 of smt_parallel_params.pyg - Remove extraneous blank line after ++m_num_core_minimize_calls - Replace informal retry-loop comments with professional descriptions - Extract repeated safe-division pattern into safe_ratio lambda in backbones_worker::collect_statistics Agent-Logs-Url: https://github.com/Z3Prover/z3/sessions/e0418d2f-7d4d-4980-897f-98d4057bddc3 Co-authored-by: NikolajBjorner <3085284+NikolajBjorner@users.noreply.github.com>
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2 changed files with 16 additions and 24 deletions
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@ -4,7 +4,7 @@ def_module_params('smt_parallel',
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params=(
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params=(
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('inprocessing', BOOL, False, 'integrate in-processing as a heuristic simplification'),
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('inprocessing', BOOL, False, 'integrate in-processing as a heuristic simplification'),
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('sls', BOOL, False, 'add sls-tactic as a separate worker thread outside the search tree parallelism'),
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('sls', BOOL, False, 'add sls-tactic as a separate worker thread outside the search tree parallelism'),
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('num_global_bb_fl_threads', UINT, 0, 'run failed-literal backbone worker threads; default is 0 (off), supported values are 1 (negative mode only) or 2 (negative and positive mode)'),
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('num_global_bb_fl_threads', UINT, 0, 'run failed-literal backbone worker threads; default is 0 (off), supported values are 1 (negative mode only) or 2 (negative and positive mode)'),
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('num_global_bb_batch_threads', UINT, 0, 'run Janota-style chunking backbone worker threads; default is 0 (off), supported values are 1 (negative mode only) or 2 (negative and positive mode)'),
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('num_global_bb_batch_threads', UINT, 0, 'run Janota-style chunking backbone worker threads; default is 0 (off), supported values are 1 (negative mode only) or 2 (negative and positive mode)'),
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('local_backbones', BOOL, False, 'enable local backbones experiment within the search tree parallelism'),
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('local_backbones', BOOL, False, 'enable local backbones experiment within the search tree parallelism'),
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('core_minimize', BOOL, True, 'minimize unsat cores used for parallel cube backtracking'),
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('core_minimize', BOOL, True, 'minimize unsat cores used for parallel cube backtracking'),
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@ -481,10 +481,9 @@ namespace smt {
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}
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}
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}
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}
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// retry loop so thread isn't idle
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// Retry loop: keeps the thread active while waiting for new backbone candidates.
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// experiments on my laptop showed this had about a 0% success rate and i'm not sure if this
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// Only retries if at least one new backbone was found in the previous round, to avoid
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// messes with resource scheduling little enough to justify keeping it
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// spinning indefinitely when progress has stalled.
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// for now we only retry if we make progress on finding at least 1 backbone in each retry round
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while (!b.has_new_backbone_candidates(bb_candidate_epoch) && !canceled() && m.inc()) {
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while (!b.has_new_backbone_candidates(bb_candidate_epoch) && !canceled() && m.inc()) {
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collect_shared_clauses();
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collect_shared_clauses();
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unsigned found_before = m_stats.m_internal_backbones_found;
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unsigned found_before = m_stats.m_internal_backbones_found;
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@ -506,8 +505,7 @@ namespace smt {
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fallback_failed_literal_probe(bb_candidate_lits, bb_candidate_lits, true);
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fallback_failed_literal_probe(bb_candidate_lits, bb_candidate_lits, true);
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// break if we made no progress on this batch
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// Break if no progress was made; further retries on this batch are unlikely to succeed.
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// unlikely to make progress on future runs and idk if this creates any kind of resource stress
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if (m_stats.m_internal_backbones_found == found_before)
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if (m_stats.m_internal_backbones_found == found_before)
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break;
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break;
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}
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}
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@ -596,23 +594,18 @@ namespace smt {
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st.update("bb-literals-removed-by-core", m_stats.m_lits_removed_by_core);
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st.update("bb-literals-removed-by-core", m_stats.m_lits_removed_by_core);
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st.update("bb-num-chunk-increases", m_stats.m_num_chunk_increases);
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st.update("bb-num-chunk-increases", m_stats.m_num_chunk_increases);
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double backbone_yield = 0.0;
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auto safe_ratio = [](double num, double den) -> double {
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if (m_stats.m_candidates_total > 0)
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return den > 0 ? num / den : 0.0;
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backbone_yield = 100.0 * (double)m_stats.m_internal_backbones_found / (double)m_stats.m_candidates_total;
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};
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double avg_backbones_per_batch = 0.0;
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if (m_stats.m_batches_total > 0)
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avg_backbones_per_batch = (double)m_stats.m_internal_backbones_found / (double)m_stats.m_batches_total;
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double core_refinement_cost = 0.0;
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if (m_stats.m_batches_total > 0)
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core_refinement_cost = (double)m_stats.m_core_refinement_rounds / (double)m_stats.m_batches_total;
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double core_effectiveness = 0.0;
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if (m_stats.m_core_refinement_rounds > 0)
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core_effectiveness = (double)m_stats.m_lits_removed_by_core / (double)m_stats.m_core_refinement_rounds;
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st.update("bb-backbone-yield-pct", backbone_yield);
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st.update("bb-backbone-yield-pct",
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st.update("bb-avg-backbones-per-batch", avg_backbones_per_batch);
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100.0 * safe_ratio(m_stats.m_internal_backbones_found, m_stats.m_candidates_total));
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st.update("bb-core-refinement-rounds-per-batch", core_refinement_cost);
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st.update("bb-avg-backbones-per-batch",
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st.update("bb-core-effectiveness-lit-removed-per-round", core_effectiveness);
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safe_ratio(m_stats.m_internal_backbones_found, m_stats.m_batches_total));
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st.update("bb-core-refinement-rounds-per-batch",
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safe_ratio(m_stats.m_core_refinement_rounds, m_stats.m_batches_total));
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st.update("bb-core-effectiveness-lit-removed-per-round",
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safe_ratio(m_stats.m_lits_removed_by_core, m_stats.m_core_refinement_rounds));
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}
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}
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void parallel::sls_worker::cancel() {
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void parallel::sls_worker::cancel() {
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@ -656,7 +649,6 @@ namespace smt {
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unsigned original_size = core.size();
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unsigned original_size = core.size();
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++m_num_core_minimize_calls;
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++m_num_core_minimize_calls;
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// Invariant: F and mus and unknown is UNSAT.
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// Invariant: F and mus and unknown is UNSAT.
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while (!unknown.empty()) {
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while (!unknown.empty()) {
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if (!m.inc()) {
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if (!m.inc()) {
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