Auto merge of #111673 - cjgillot:dominator-preprocess, r=cjgillot,tmiasko

Preprocess and cache dominator tree

Preprocessing dominators has a very strong effect for https://github.com/rust-lang/rust/pull/111344.
That pass checks that assignments dominate their uses repeatedly. Using the unprocessed dominator tree caused a quadratic runtime (number of bbs x depth of the dominator tree).

This PR also caches the dominator tree and the pre-processed dominators in the MIR cfg cache.

Rebase of https://github.com/rust-lang/rust/pull/107157
cc `@tmiasko`

compiler/rustc_mir_transform/src/coverage/graph.rs

@@ -9,6 +9,7 @@ use rustc_index::{IndexSlice, IndexVec};
 use rustc_middle::mir::coverage::*;
 use rustc_middle::mir::{self, BasicBlock, BasicBlockData, Terminator, TerminatorKind};
 
+use std::cmp::Ordering;
 use std::ops::{Index, IndexMut};
 
 const ID_SEPARATOR: &str = ",";
@@ -212,8 +213,12 @@ impl CoverageGraph {
     }
 
     #[inline(always)]
-    pub fn dominators(&self) -> &Dominators<BasicCoverageBlock> {
-        self.dominators.as_ref().unwrap()
+    pub fn rank_partial_cmp(
+        &self,
+        a: BasicCoverageBlock,
+        b: BasicCoverageBlock,
+    ) -> Option<Ordering> {
+        self.dominators.as_ref().unwrap().rank_partial_cmp(a, b)
     }
 }
 
@@ -650,26 +655,6 @@ pub(super) fn find_loop_backedges(
     let mut backedges = IndexVec::from_elem_n(Vec::<BasicCoverageBlock>::new(), num_bcbs);
 
     // Identify loops by their backedges.
-    //
-    // The computational complexity is bounded by: n(s) x d where `n` is the number of
-    // `BasicCoverageBlock` nodes (the simplified/reduced representation of the CFG derived from the
-    // MIR); `s` is the average number of successors per node (which is most likely less than 2, and
-    // independent of the size of the function, so it can be treated as a constant);
-    // and `d` is the average number of dominators per node.
-    //
-    // The average number of dominators depends on the size and complexity of the function, and
-    // nodes near the start of the function's control flow graph typically have less dominators
-    // than nodes near the end of the CFG. Without doing a detailed mathematical analysis, I
-    // think the resulting complexity has the characteristics of O(n log n).
-    //
-    // The overall complexity appears to be comparable to many other MIR transform algorithms, and I
-    // don't expect that this function is creating a performance hot spot, but if this becomes an
-    // issue, there may be ways to optimize the `dominates` algorithm (as indicated by an
-    // existing `FIXME` comment in that code), or possibly ways to optimize it's usage here, perhaps
-    // by keeping track of results for visited `BasicCoverageBlock`s if they can be used to short
-    // circuit downstream `dominates` checks.
-    //
-    // For now, that kind of optimization seems unnecessarily complicated.
     for (bcb, _) in basic_coverage_blocks.iter_enumerated() {
         for &successor in &basic_coverage_blocks.successors[bcb] {
             if basic_coverage_blocks.dominates(successor, bcb) {

compiler/rustc_mir_transform/src/coverage/spans.rs

@@ -344,7 +344,7 @@ impl<'a, 'tcx> CoverageSpans<'a, 'tcx> {
                         // before the dominated equal spans). When later comparing two spans in
                         // order, the first will either dominate the second, or they will have no
                         // dominator relationship.
-                        self.basic_coverage_blocks.dominators().rank_partial_cmp(a.bcb, b.bcb)
+                        self.basic_coverage_blocks.rank_partial_cmp(a.bcb, b.bcb)
                     }
                 } else {
                     // Sort hi() in reverse order so shorter spans are attempted after longer spans.

compiler/rustc_mir_transform/src/ctfe_limit.rs

@@ -47,7 +47,7 @@ fn has_back_edge(
         return false;
     }
     // Check if any of the dominators of the node are also the node's successor.
-    doms.dominators(node).any(|dom| node_data.terminator().successors().any(|succ| succ == dom))
+    node_data.terminator().successors().any(|succ| doms.dominates(succ, node))
 }
 
 fn insert_counter(basic_block_data: &mut BasicBlockData<'_>) {

compiler/rustc_mir_transform/src/ssa.rs

@@ -31,11 +31,11 @@ pub struct SsaLocals {
 /// We often encounter MIR bodies with 1 or 2 basic blocks. In those cases, it's unnecessary to
 /// actually compute dominators, we can just compare block indices because bb0 is always the first
 /// block, and in any body all other blocks are always dominated by bb0.
-struct SmallDominators {
-    inner: Option<Dominators<BasicBlock>>,
+struct SmallDominators<'a> {
+    inner: Option<&'a Dominators<BasicBlock>>,
 }
 
-impl SmallDominators {
+impl SmallDominators<'_> {
     fn dominates(&self, first: Location, second: Location) -> bool {
         if first.block == second.block {
             first.statement_index <= second.statement_index
@@ -198,14 +198,14 @@ enum LocationExtended {
     Arg,
 }
 
-struct SsaVisitor {
-    dominators: SmallDominators,
+struct SsaVisitor<'a> {
+    dominators: SmallDominators<'a>,
     assignments: IndexVec<Local, Set1<LocationExtended>>,
     assignment_order: Vec<Local>,
     direct_uses: IndexVec<Local, u32>,
 }
 
-impl<'tcx> Visitor<'tcx> for SsaVisitor {
+impl<'tcx> Visitor<'tcx> for SsaVisitor<'_> {
     fn visit_local(&mut self, local: Local, ctxt: PlaceContext, loc: Location) {
         match ctxt {
             PlaceContext::MutatingUse(MutatingUseContext::Projection)