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Auto merge of #118490 - Nadrieril:arena-alloc-matrix, r=nnethercote
Exhaustiveness: allocate memory better Exhaustiveness is a recursive algorithm that allocates a bunch of slices at every step. Let's see if I can improve performance by improving allocations. Already just using `Vec::with_capacity` is showing impressive improvements on my local measurements. r? `@ghost`
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@ -197,23 +197,24 @@ impl<T> TypedArena<T> {
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start_ptr
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}
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/// Allocates the elements of this iterator into a contiguous slice in the `TypedArena`.
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///
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/// Note: for reasons of reentrancy and panic safety we collect into a `SmallVec<[_; 8]>` before
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/// storing the elements in the arena.
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#[inline]
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pub fn alloc_from_iter<I: IntoIterator<Item = T>>(&self, iter: I) -> &mut [T] {
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// This implementation is entirely separate to
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// `DroplessIterator::alloc_from_iter`, even though conceptually they
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// are the same.
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// Despite the similarlty with `DroplessArena`, we cannot reuse their fast case. The reason
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// is subtle: these arenas are reentrant. In other words, `iter` may very well be holding a
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// reference to `self` and adding elements to the arena during iteration.
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//
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// `DroplessIterator` (in the fast case) writes elements from the
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// iterator one at a time into the allocated memory. That's easy
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// because the elements don't implement `Drop`. But for `TypedArena`
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// they do implement `Drop`, which means that if the iterator panics we
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// could end up with some allocated-but-uninitialized elements, which
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// will then cause UB in `TypedArena::drop`.
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// For this reason, if we pre-allocated any space for the elements of this iterator, we'd
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// have to track that some uninitialized elements are followed by some initialized elements,
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// else we might accidentally drop uninitialized memory if something panics or if the
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// iterator doesn't fill all the length we expected.
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//
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// Instead we use an approach where any iterator panic will occur
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// before the memory is allocated. This function is much less hot than
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// `DroplessArena::alloc_from_iter`, so it doesn't need to be
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// hyper-optimized.
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// So we collect all the elements beforehand, which takes care of reentrancy and panic
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// safety. This function is much less hot than `DroplessArena::alloc_from_iter`, so it
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// doesn't need to be hyper-optimized.
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assert!(mem::size_of::<T>() != 0);
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let mut vec: SmallVec<[_; 8]> = iter.into_iter().collect();
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@ -485,8 +486,9 @@ impl DroplessArena {
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/// # Safety
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///
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/// The caller must ensure that `mem` is valid for writes up to
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/// `size_of::<T>() * len`.
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/// The caller must ensure that `mem` is valid for writes up to `size_of::<T>() * len`, and that
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/// that memory stays allocated and not shared for the lifetime of `self`. This must hold even
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/// if `iter.next()` allocates onto `self`.
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#[inline]
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unsafe fn write_from_iter<T, I: Iterator<Item = T>>(
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&self,
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@ -516,6 +518,8 @@ impl DroplessArena {
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#[inline]
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pub fn alloc_from_iter<T, I: IntoIterator<Item = T>>(&self, iter: I) -> &mut [T] {
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// Warning: this function is reentrant: `iter` could hold a reference to `&self` and
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// allocate additional elements while we're iterating.
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let iter = iter.into_iter();
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assert!(mem::size_of::<T>() != 0);
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assert!(!mem::needs_drop::<T>());
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@ -524,7 +528,7 @@ impl DroplessArena {
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match size_hint {
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(min, Some(max)) if min == max => {
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// We know the exact number of elements the iterator will produce here
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// We know the exact number of elements the iterator expects to produce here.
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let len = min;
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if len == 0 {
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@ -532,10 +536,15 @@ impl DroplessArena {
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}
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let mem = self.alloc_raw(Layout::array::<T>(len).unwrap()) as *mut T;
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// SAFETY: `write_from_iter` doesn't touch `self`. It only touches the slice we just
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// reserved. If the iterator panics or doesn't output `len` elements, this will
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// leave some unallocated slots in the arena, which is fine because we do not call
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// `drop`.
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unsafe { self.write_from_iter(iter, len, mem) }
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}
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(_, _) => {
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outline(move || -> &mut [T] {
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// Takes care of reentrancy.
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let mut vec: SmallVec<[_; 8]> = iter.collect();
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if vec.is_empty() {
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return &mut [];
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@ -599,9 +599,9 @@ impl<'p, 'tcx> PatStack<'p, 'tcx> {
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// an or-pattern. Panics if `self` is empty.
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fn expand_or_pat<'a>(&'a self) -> impl Iterator<Item = PatStack<'p, 'tcx>> + Captures<'a> {
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self.head().flatten_or_pat().into_iter().map(move |pat| {
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let mut new_pats = smallvec![pat];
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new_pats.extend_from_slice(&self.pats[1..]);
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PatStack { pats: new_pats }
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let mut new = self.clone();
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new.pats[0] = pat;
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new
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})
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}
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@ -732,18 +732,11 @@ impl<'p, 'tcx> Matrix<'p, 'tcx> {
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}
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/// Build a new matrix from an iterator of `MatchArm`s.
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fn new<'a>(
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cx: &MatchCheckCtxt<'p, 'tcx>,
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iter: impl Iterator<Item = &'a MatchArm<'p, 'tcx>>,
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scrut_ty: Ty<'tcx>,
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) -> Self
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where
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'p: 'a,
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{
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fn new(cx: &MatchCheckCtxt<'p, 'tcx>, arms: &[MatchArm<'p, 'tcx>], scrut_ty: Ty<'tcx>) -> Self {
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let wild_pattern = cx.pattern_arena.alloc(DeconstructedPat::wildcard(scrut_ty, DUMMY_SP));
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let wildcard_row = PatStack::from_pattern(wild_pattern);
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let mut matrix = Matrix { rows: vec![], wildcard_row };
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for (row_id, arm) in iter.enumerate() {
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let mut matrix = Matrix { rows: Vec::with_capacity(arms.len()), wildcard_row };
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for (row_id, arm) in arms.iter().enumerate() {
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let v = MatrixRow {
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pats: PatStack::from_pattern(arm.pat),
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parent_row: row_id, // dummy, we won't read it
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@ -806,7 +799,7 @@ impl<'p, 'tcx> Matrix<'p, 'tcx> {
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ctor: &Constructor<'tcx>,
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) -> Matrix<'p, 'tcx> {
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let wildcard_row = self.wildcard_row.pop_head_constructor(pcx, ctor);
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let mut matrix = Matrix { rows: vec![], wildcard_row };
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let mut matrix = Matrix { rows: Vec::new(), wildcard_row };
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for (i, row) in self.rows().enumerate() {
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if ctor.is_covered_by(pcx, row.head().ctor()) {
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let new_row = row.pop_head_constructor(pcx, ctor, i);
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@ -1386,7 +1379,7 @@ pub(crate) fn compute_match_usefulness<'p, 'tcx>(
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arms: &[MatchArm<'p, 'tcx>],
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scrut_ty: Ty<'tcx>,
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) -> UsefulnessReport<'p, 'tcx> {
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let mut matrix = Matrix::new(cx, arms.iter(), scrut_ty);
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let mut matrix = Matrix::new(cx, arms, scrut_ty);
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let non_exhaustiveness_witnesses =
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compute_exhaustiveness_and_reachability(cx, &mut matrix, true);
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