Adding upstream version 86.0.1.upstream/86.0.1upstream

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

4 files changed, 2914 insertions, 0 deletions

diff --git a/third_party/rust/rayon/src/slice/mergesort.rs b/third_party/rust/rayon/src/slice/mergesort.rs
new file mode 100644
index 0000000000..a007cae80b
--- /dev/null
+++ b/third_party/rust/rayon/src/slice/mergesort.rs
@@ -0,0 +1,763 @@
+//! Parallel merge sort.
+//!
+//! This implementation is copied verbatim from `std::slice::sort` and then parallelized.
+//! The only difference from the original is that the sequential `mergesort` returns
+//! `MergesortResult` and leaves descending arrays intact.
+
+use crate::iter::*;
+use crate::slice::ParallelSliceMut;
+use std::mem;
+use std::mem::size_of;
+use std::ptr;
+use std::slice;
+
+unsafe fn get_and_increment<T>(ptr: &mut *mut T) -> *mut T {
+    let old = *ptr;
+    *ptr = ptr.offset(1);
+    old
+}
+
+unsafe fn decrement_and_get<T>(ptr: &mut *mut T) -> *mut T {
+    *ptr = ptr.offset(-1);
+    *ptr
+}
+
+/// When dropped, copies from `src` into `dest` a sequence of length `len`.
+struct CopyOnDrop<T> {
+    src: *mut T,
+    dest: *mut T,
+    len: usize,
+}
+
+impl<T> Drop for CopyOnDrop<T> {
+    fn drop(&mut self) {
+        unsafe {
+            ptr::copy_nonoverlapping(self.src, self.dest, self.len);
+        }
+    }
+}
+
+/// Inserts `v[0]` into pre-sorted sequence `v[1..]` so that whole `v[..]` becomes sorted.
+///
+/// This is the integral subroutine of insertion sort.
+fn insert_head<T, F>(v: &mut [T], is_less: &F)
+where
+    F: Fn(&T, &T) -> bool,
+{
+    if v.len() >= 2 && is_less(&v[1], &v[0]) {
+        unsafe {
+            // There are three ways to implement insertion here:
+            //
+            // 1. Swap adjacent elements until the first one gets to its final destination.
+            //    However, this way we copy data around more than is necessary. If elements are big
+            //    structures (costly to copy), this method will be slow.
+            //
+            // 2. Iterate until the right place for the first element is found. Then shift the
+            //    elements succeeding it to make room for it and finally place it into the
+            //    remaining hole. This is a good method.
+            //
+            // 3. Copy the first element into a temporary variable. Iterate until the right place
+            //    for it is found. As we go along, copy every traversed element into the slot
+            //    preceding it. Finally, copy data from the temporary variable into the remaining
+            //    hole. This method is very good. Benchmarks demonstrated slightly better
+            //    performance than with the 2nd method.
+            //
+            // All methods were benchmarked, and the 3rd showed best results. So we chose that one.
+            let mut tmp = NoDrop {
+                value: Some(ptr::read(&v[0])),
+            };
+
+            // Intermediate state of the insertion process is always tracked by `hole`, which
+            // serves two purposes:
+            // 1. Protects integrity of `v` from panics in `is_less`.
+            // 2. Fills the remaining hole in `v` in the end.
+            //
+            // Panic safety:
+            //
+            // If `is_less` panics at any point during the process, `hole` will get dropped and
+            // fill the hole in `v` with `tmp`, thus ensuring that `v` still holds every object it
+            // initially held exactly once.
+            let mut hole = InsertionHole {
+                src: tmp.value.as_mut().unwrap(),
+                dest: &mut v[1],
+            };
+            ptr::copy_nonoverlapping(&v[1], &mut v[0], 1);
+
+            for i in 2..v.len() {
+                if !is_less(&v[i], tmp.value.as_ref().unwrap()) {
+                    break;
+                }
+                ptr::copy_nonoverlapping(&v[i], &mut v[i - 1], 1);
+                hole.dest = &mut v[i];
+            }
+            // `hole` gets dropped and thus copies `tmp` into the remaining hole in `v`.
+        }
+    }
+
+    // Holds a value, but never drops it.
+    struct NoDrop<T> {
+        value: Option<T>,
+    }
+
+    impl<T> Drop for NoDrop<T> {
+        fn drop(&mut self) {
+            mem::forget(self.value.take());
+        }
+    }
+
+    // When dropped, copies from `src` into `dest`.
+    struct InsertionHole<T> {
+        src: *mut T,
+        dest: *mut T,
+    }
+
+    impl<T> Drop for InsertionHole<T> {
+        fn drop(&mut self) {
+            unsafe {
+                ptr::copy_nonoverlapping(self.src, self.dest, 1);
+            }
+        }
+    }
+}
+
+/// Merges non-decreasing runs `v[..mid]` and `v[mid..]` using `buf` as temporary storage, and
+/// stores the result into `v[..]`.
+///
+/// # Safety
+///
+/// The two slices must be non-empty and `mid` must be in bounds. Buffer `buf` must be long enough
+/// to hold a copy of the shorter slice. Also, `T` must not be a zero-sized type.
+unsafe fn merge<T, F>(v: &mut [T], mid: usize, buf: *mut T, is_less: &F)
+where
+    F: Fn(&T, &T) -> bool,
+{
+    let len = v.len();
+    let v = v.as_mut_ptr();
+    let v_mid = v.add(mid);
+    let v_end = v.add(len);
+
+    // The merge process first copies the shorter run into `buf`. Then it traces the newly copied
+    // run and the longer run forwards (or backwards), comparing their next unconsumed elements and
+    // copying the lesser (or greater) one into `v`.
+    //
+    // As soon as the shorter run is fully consumed, the process is done. If the longer run gets
+    // consumed first, then we must copy whatever is left of the shorter run into the remaining
+    // hole in `v`.
+    //
+    // Intermediate state of the process is always tracked by `hole`, which serves two purposes:
+    // 1. Protects integrity of `v` from panics in `is_less`.
+    // 2. Fills the remaining hole in `v` if the longer run gets consumed first.
+    //
+    // Panic safety:
+    //
+    // If `is_less` panics at any point during the process, `hole` will get dropped and fill the
+    // hole in `v` with the unconsumed range in `buf`, thus ensuring that `v` still holds every
+    // object it initially held exactly once.
+    let mut hole;
+
+    if mid <= len - mid {
+        // The left run is shorter.
+        ptr::copy_nonoverlapping(v, buf, mid);
+        hole = MergeHole {
+            start: buf,
+            end: buf.add(mid),
+            dest: v,
+        };
+
+        // Initially, these pointers point to the beginnings of their arrays.
+        let left = &mut hole.start;
+        let mut right = v_mid;
+        let out = &mut hole.dest;
+
+        while *left < hole.end && right < v_end {
+            // Consume the lesser side.
+            // If equal, prefer the left run to maintain stability.
+            let to_copy = if is_less(&*right, &**left) {
+                get_and_increment(&mut right)
+            } else {
+                get_and_increment(left)
+            };
+            ptr::copy_nonoverlapping(to_copy, get_and_increment(out), 1);
+        }
+    } else {
+        // The right run is shorter.
+        ptr::copy_nonoverlapping(v_mid, buf, len - mid);
+        hole = MergeHole {
+            start: buf,
+            end: buf.add(len - mid),
+            dest: v_mid,
+        };
+
+        // Initially, these pointers point past the ends of their arrays.
+        let left = &mut hole.dest;
+        let right = &mut hole.end;
+        let mut out = v_end;
+
+        while v < *left && buf < *right {
+            // Consume the greater side.
+            // If equal, prefer the right run to maintain stability.
+            let to_copy = if is_less(&*right.offset(-1), &*left.offset(-1)) {
+                decrement_and_get(left)
+            } else {
+                decrement_and_get(right)
+            };
+            ptr::copy_nonoverlapping(to_copy, decrement_and_get(&mut out), 1);
+        }
+    }
+    // Finally, `hole` gets dropped. If the shorter run was not fully consumed, whatever remains of
+    // it will now be copied into the hole in `v`.
+
+    // When dropped, copies the range `start..end` into `dest..`.
+    struct MergeHole<T> {
+        start: *mut T,
+        end: *mut T,
+        dest: *mut T,
+    }
+
+    impl<T> Drop for MergeHole<T> {
+        fn drop(&mut self) {
+            // `T` is not a zero-sized type, so it's okay to divide by its size.
+            let len = (self.end as usize - self.start as usize) / size_of::<T>();
+            unsafe {
+                ptr::copy_nonoverlapping(self.start, self.dest, len);
+            }
+        }
+    }
+}
+
+/// The result of merge sort.
+#[must_use]
+#[derive(Clone, Copy, PartialEq, Eq)]
+enum MergesortResult {
+    /// The slice has already been sorted.
+    NonDescending,
+    /// The slice has been descending and therefore it was left intact.
+    Descending,
+    /// The slice was sorted.
+    Sorted,
+}
+
+/// A sorted run that starts at index `start` and is of length `len`.
+#[derive(Clone, Copy)]
+struct Run {
+    start: usize,
+    len: usize,
+}
+
+/// Examines the stack of runs and identifies the next pair of runs to merge. More specifically,
+/// if `Some(r)` is returned, that means `runs[r]` and `runs[r + 1]` must be merged next. If the
+/// algorithm should continue building a new run instead, `None` is returned.
+///
+/// TimSort is infamous for its buggy implementations, as described here:
+/// http://envisage-project.eu/timsort-specification-and-verification/
+///
+/// The gist of the story is: we must enforce the invariants on the top four runs on the stack.
+/// Enforcing them on just top three is not sufficient to ensure that the invariants will still
+/// hold for *all* runs in the stack.
+///
+/// This function correctly checks invariants for the top four runs. Additionally, if the top
+/// run starts at index 0, it will always demand a merge operation until the stack is fully
+/// collapsed, in order to complete the sort.
+#[inline]
+fn collapse(runs: &[Run]) -> Option<usize> {
+    let n = runs.len();
+
+    if n >= 2
+        && (runs[n - 1].start == 0
+            || runs[n - 2].len <= runs[n - 1].len
+            || (n >= 3 && runs[n - 3].len <= runs[n - 2].len + runs[n - 1].len)
+            || (n >= 4 && runs[n - 4].len <= runs[n - 3].len + runs[n - 2].len))
+    {
+        if n >= 3 && runs[n - 3].len < runs[n - 1].len {
+            Some(n - 3)
+        } else {
+            Some(n - 2)
+        }
+    } else {
+        None
+    }
+}
+
+/// Sorts a slice using merge sort, unless it is already in descending order.
+///
+/// This function doesn't modify the slice if it is already non-descending or descending.
+/// Otherwise, it sorts the slice into non-descending order.
+///
+/// This merge sort borrows some (but not all) ideas from TimSort, which is described in detail
+/// [here](http://svn.python.org/projects/python/trunk/Objects/listsort.txt).
+///
+/// The algorithm identifies strictly descending and non-descending subsequences, which are called
+/// natural runs. There is a stack of pending runs yet to be merged. Each newly found run is pushed
+/// onto the stack, and then some pairs of adjacent runs are merged until these two invariants are
+/// satisfied:
+///
+/// 1. for every `i` in `1..runs.len()`: `runs[i - 1].len > runs[i].len`
+/// 2. for every `i` in `2..runs.len()`: `runs[i - 2].len > runs[i - 1].len + runs[i].len`
+///
+/// The invariants ensure that the total running time is `O(n log n)` worst-case.
+///
+/// # Safety
+///
+/// The argument `buf` is used as a temporary buffer and must be at least as long as `v`.
+unsafe fn mergesort<T, F>(v: &mut [T], buf: *mut T, is_less: &F) -> MergesortResult
+where
+    T: Send,
+    F: Fn(&T, &T) -> bool + Sync,
+{
+    // Very short runs are extended using insertion sort to span at least this many elements.
+    const MIN_RUN: usize = 10;
+
+    let len = v.len();
+
+    // In order to identify natural runs in `v`, we traverse it backwards. That might seem like a
+    // strange decision, but consider the fact that merges more often go in the opposite direction
+    // (forwards). According to benchmarks, merging forwards is slightly faster than merging
+    // backwards. To conclude, identifying runs by traversing backwards improves performance.
+    let mut runs = vec![];
+    let mut end = len;
+    while end > 0 {
+        // Find the next natural run, and reverse it if it's strictly descending.
+        let mut start = end - 1;
+
+        if start > 0 {
+            start -= 1;
+
+            if is_less(v.get_unchecked(start + 1), v.get_unchecked(start)) {
+                while start > 0 && is_less(v.get_unchecked(start), v.get_unchecked(start - 1)) {
+                    start -= 1;
+                }
+
+                // If this descending run covers the whole slice, return immediately.
+                if start == 0 && end == len {
+                    return MergesortResult::Descending;
+                } else {
+                    v[start..end].reverse();
+                }
+            } else {
+                while start > 0 && !is_less(v.get_unchecked(start), v.get_unchecked(start - 1)) {
+                    start -= 1;
+                }
+
+                // If this non-descending run covers the whole slice, return immediately.
+                if end - start == len {
+                    return MergesortResult::NonDescending;
+                }
+            }
+        }
+
+        // Insert some more elements into the run if it's too short. Insertion sort is faster than
+        // merge sort on short sequences, so this significantly improves performance.
+        while start > 0 && end - start < MIN_RUN {
+            start -= 1;
+            insert_head(&mut v[start..end], &is_less);
+        }
+
+        // Push this run onto the stack.
+        runs.push(Run {
+            start,
+            len: end - start,
+        });
+        end = start;
+
+        // Merge some pairs of adjacent runs to satisfy the invariants.
+        while let Some(r) = collapse(&runs) {
+            let left = runs[r + 1];
+            let right = runs[r];
+            merge(
+                &mut v[left.start..right.start + right.len],
+                left.len,
+                buf,
+                &is_less,
+            );
+
+            runs[r] = Run {
+                start: left.start,
+                len: left.len + right.len,
+            };
+            runs.remove(r + 1);
+        }
+    }
+
+    // Finally, exactly one run must remain in the stack.
+    debug_assert!(runs.len() == 1 && runs[0].start == 0 && runs[0].len == len);
+
+    // The original order of the slice was neither non-descending nor descending.
+    MergesortResult::Sorted
+}
+
+////////////////////////////////////////////////////////////////////////////
+// Everything above this line is copied from `std::slice::sort` (with very minor tweaks).
+// Everything below this line is parallelization.
+////////////////////////////////////////////////////////////////////////////
+
+/// Splits two sorted slices so that they can be merged in parallel.
+///
+/// Returns two indices `(a, b)` so that slices `left[..a]` and `right[..b]` come before
+/// `left[a..]` and `right[b..]`.
+fn split_for_merge<T, F>(left: &[T], right: &[T], is_less: &F) -> (usize, usize)
+where
+    F: Fn(&T, &T) -> bool,
+{
+    let left_len = left.len();
+    let right_len = right.len();
+
+    if left_len >= right_len {
+        let left_mid = left_len / 2;
+
+        // Find the first element in `right` that is greater than or equal to `left[left_mid]`.
+        let mut a = 0;
+        let mut b = right_len;
+        while a < b {
+            let m = a + (b - a) / 2;
+            if is_less(&right[m], &left[left_mid]) {
+                a = m + 1;
+            } else {
+                b = m;
+            }
+        }
+
+        (left_mid, a)
+    } else {
+        let right_mid = right_len / 2;
+
+        // Find the first element in `left` that is greater than `right[right_mid]`.
+        let mut a = 0;
+        let mut b = left_len;
+        while a < b {
+            let m = a + (b - a) / 2;
+            if is_less(&right[right_mid], &left[m]) {
+                b = m;
+            } else {
+                a = m + 1;
+            }
+        }
+
+        (a, right_mid)
+    }
+}
+
+/// Merges slices `left` and `right` in parallel and stores the result into `dest`.
+///
+/// # Safety
+///
+/// The `dest` pointer must have enough space to store the result.
+///
+/// Even if `is_less` panics at any point during the merge process, this function will fully copy
+/// all elements from `left` and `right` into `dest` (not necessarily in sorted order).
+unsafe fn par_merge<T, F>(left: &mut [T], right: &mut [T], dest: *mut T, is_less: &F)
+where
+    T: Send,
+    F: Fn(&T, &T) -> bool + Sync,
+{
+    // Slices whose lengths sum up to this value are merged sequentially. This number is slightly
+    // larger than `CHUNK_LENGTH`, and the reason is that merging is faster than merge sorting, so
+    // merging needs a bit coarser granularity in order to hide the overhead of Rayon's task
+    // scheduling.
+    const MAX_SEQUENTIAL: usize = 5000;
+
+    let left_len = left.len();
+    let right_len = right.len();
+
+    // Intermediate state of the merge process, which serves two purposes:
+    // 1. Protects integrity of `dest` from panics in `is_less`.
+    // 2. Copies the remaining elements as soon as one of the two sides is exhausted.
+    //
+    // Panic safety:
+    //
+    // If `is_less` panics at any point during the merge process, `s` will get dropped and copy the
+    // remaining parts of `left` and `right` into `dest`.
+    let mut s = State {
+        left_start: left.as_mut_ptr(),
+        left_end: left.as_mut_ptr().add(left_len),
+        right_start: right.as_mut_ptr(),
+        right_end: right.as_mut_ptr().add(right_len),
+        dest,
+    };
+
+    if left_len == 0 || right_len == 0 || left_len + right_len < MAX_SEQUENTIAL {
+        while s.left_start < s.left_end && s.right_start < s.right_end {
+            // Consume the lesser side.
+            // If equal, prefer the left run to maintain stability.
+            let to_copy = if is_less(&*s.right_start, &*s.left_start) {
+                get_and_increment(&mut s.right_start)
+            } else {
+                get_and_increment(&mut s.left_start)
+            };
+            ptr::copy_nonoverlapping(to_copy, get_and_increment(&mut s.dest), 1);
+        }
+    } else {
+        // Function `split_for_merge` might panic. If that happens, `s` will get destructed and copy
+        // the whole `left` and `right` into `dest`.
+        let (left_mid, right_mid) = split_for_merge(left, right, is_less);
+        let (left_l, left_r) = left.split_at_mut(left_mid);
+        let (right_l, right_r) = right.split_at_mut(right_mid);
+
+        // Prevent the destructor of `s` from running. Rayon will ensure that both calls to
+        // `par_merge` happen. If one of the two calls panics, they will ensure that elements still
+        // get copied into `dest_left` and `dest_right``.
+        mem::forget(s);
+
+        // Convert the pointers to `usize` because `*mut T` is not `Send`.
+        let dest_l = dest as usize;
+        let dest_r = dest.add(left_l.len() + right_l.len()) as usize;
+        rayon_core::join(
+            || par_merge(left_l, right_l, dest_l as *mut T, is_less),
+            || par_merge(left_r, right_r, dest_r as *mut T, is_less),
+        );
+    }
+    // Finally, `s` gets dropped if we used sequential merge, thus copying the remaining elements
+    // all at once.
+
+    // When dropped, copies arrays `left_start..left_end` and `right_start..right_end` into `dest`,
+    // in that order.
+    struct State<T> {
+        left_start: *mut T,
+        left_end: *mut T,
+        right_start: *mut T,
+        right_end: *mut T,
+        dest: *mut T,
+    }
+
+    impl<T> Drop for State<T> {
+        fn drop(&mut self) {
+            let size = size_of::<T>();
+            let left_len = (self.left_end as usize - self.left_start as usize) / size;
+            let right_len = (self.right_end as usize - self.right_start as usize) / size;
+
+            // Copy array `left`, followed by `right`.
+            unsafe {
+                ptr::copy_nonoverlapping(self.left_start, self.dest, left_len);
+                self.dest = self.dest.add(left_len);
+                ptr::copy_nonoverlapping(self.right_start, self.dest, right_len);
+            }
+        }
+    }
+}
+
+/// Recursively merges pre-sorted chunks inside `v`.
+///
+/// Chunks of `v` are stored in `chunks` as intervals (inclusive left and exclusive right bound).
+/// Argument `buf` is an auxiliary buffer that will be used during the procedure.
+/// If `into_buf` is true, the result will be stored into `buf`, otherwise it will be in `v`.
+///
+/// # Safety
+///
+/// The number of chunks must be positive and they must be adjacent: the right bound of each chunk
+/// must equal the left bound of the following chunk.
+///
+/// The buffer must be at least as long as `v`.
+unsafe fn recurse<T, F>(
+    v: *mut T,
+    buf: *mut T,
+    chunks: &[(usize, usize)],
+    into_buf: bool,
+    is_less: &F,
+) where
+    T: Send,
+    F: Fn(&T, &T) -> bool + Sync,
+{
+    let len = chunks.len();
+    debug_assert!(len > 0);
+
+    // Base case of the algorithm.
+    // If only one chunk is remaining, there's no more work to split and merge.
+    if len == 1 {
+        if into_buf {
+            // Copy the chunk from `v` into `buf`.
+            let (start, end) = chunks[0];
+            let src = v.add(start);
+            let dest = buf.add(start);
+            ptr::copy_nonoverlapping(src, dest, end - start);
+        }
+        return;
+    }
+
+    // Split the chunks into two halves.
+    let (start, _) = chunks[0];
+    let (mid, _) = chunks[len / 2];
+    let (_, end) = chunks[len - 1];
+    let (left, right) = chunks.split_at(len / 2);
+
+    // After recursive calls finish we'll have to merge chunks `(start, mid)` and `(mid, end)` from
+    // `src` into `dest`. If the current invocation has to store the result into `buf`, we'll
+    // merge chunks from `v` into `buf`, and viceversa.
+    //
+    // Recursive calls flip `into_buf` at each level of recursion. More concretely, `par_merge`
+    // merges chunks from `buf` into `v` at the first level, from `v` into `buf` at the second
+    // level etc.
+    let (src, dest) = if into_buf { (v, buf) } else { (buf, v) };
+
+    // Panic safety:
+    //
+    // If `is_less` panics at any point during the recursive calls, the destructor of `guard` will
+    // be executed, thus copying everything from `src` into `dest`. This way we ensure that all
+    // chunks are in fact copied into `dest`, even if the merge process doesn't finish.
+    let guard = CopyOnDrop {
+        src: src.add(start),
+        dest: dest.add(start),
+        len: end - start,
+    };
+
+    // Convert the pointers to `usize` because `*mut T` is not `Send`.
+    let v = v as usize;
+    let buf = buf as usize;
+    rayon_core::join(
+        || recurse(v as *mut T, buf as *mut T, left, !into_buf, is_less),
+        || recurse(v as *mut T, buf as *mut T, right, !into_buf, is_less),
+    );
+
+    // Everything went all right - recursive calls didn't panic.
+    // Forget the guard in order to prevent its destructor from running.
+    mem::forget(guard);
+
+    // Merge chunks `(start, mid)` and `(mid, end)` from `src` into `dest`.
+    let src_left = slice::from_raw_parts_mut(src.add(start), mid - start);
+    let src_right = slice::from_raw_parts_mut(src.add(mid), end - mid);
+    par_merge(src_left, src_right, dest.add(start), is_less);
+}
+
+/// Sorts `v` using merge sort in parallel.
+///
+/// The algorithm is stable, allocates memory, and `O(n log n)` worst-case.
+/// The allocated temporary buffer is of the same length as is `v`.
+pub(super) fn par_mergesort<T, F>(v: &mut [T], is_less: F)
+where
+    T: Send,
+    F: Fn(&T, &T) -> bool + Sync,
+{
+    // Slices of up to this length get sorted using insertion sort in order to avoid the cost of
+    // buffer allocation.
+    const MAX_INSERTION: usize = 20;
+    // The length of initial chunks. This number is as small as possible but so that the overhead
+    // of Rayon's task scheduling is still negligible.
+    const CHUNK_LENGTH: usize = 2000;
+
+    // Sorting has no meaningful behavior on zero-sized types.
+    if size_of::<T>() == 0 {
+        return;
+    }
+
+    let len = v.len();
+
+    // Short slices get sorted in-place via insertion sort to avoid allocations.
+    if len <= MAX_INSERTION {
+        if len >= 2 {
+            for i in (0..len - 1).rev() {
+                insert_head(&mut v[i..], &is_less);
+            }
+        }
+        return;
+    }
+
+    // Allocate a buffer to use as scratch memory. We keep the length 0 so we can keep in it
+    // shallow copies of the contents of `v` without risking the dtors running on copies if
+    // `is_less` panics.
+    let mut buf = Vec::<T>::with_capacity(len);
+    let buf = buf.as_mut_ptr();
+
+    // If the slice is not longer than one chunk would be, do sequential merge sort and return.
+    if len <= CHUNK_LENGTH {
+        let res = unsafe { mergesort(v, buf, &is_less) };
+        if res == MergesortResult::Descending {
+            v.reverse();
+        }
+        return;
+    }
+
+    // Split the slice into chunks and merge sort them in parallel.
+    // However, descending chunks will not be sorted - they will be simply left intact.
+    let mut iter = {
+        // Convert the pointer to `usize` because `*mut T` is not `Send`.
+        let buf = buf as usize;
+
+        v.par_chunks_mut(CHUNK_LENGTH)
+            .with_max_len(1)
+            .enumerate()
+            .map(|(i, chunk)| {
+                let l = CHUNK_LENGTH * i;
+                let r = l + chunk.len();
+                unsafe {
+                    let buf = (buf as *mut T).add(l);
+                    (l, r, mergesort(chunk, buf, &is_less))
+                }
+            })
+            .collect::<Vec<_>>()
+            .into_iter()
+            .peekable()
+    };
+
+    // Now attempt to concatenate adjacent chunks that were left intact.
+    let mut chunks = Vec::with_capacity(iter.len());
+
+    while let Some((a, mut b, res)) = iter.next() {
+        // If this chunk was not modified by the sort procedure...
+        if res != MergesortResult::Sorted {
+            while let Some(&(x, y, r)) = iter.peek() {
+                // If the following chunk is of the same type and can be concatenated...
+                if r == res && (r == MergesortResult::Descending) == is_less(&v[x], &v[x - 1]) {
+                    // Concatenate them.
+                    b = y;
+                    iter.next();
+                } else {
+                    break;
+                }
+            }
+        }
+
+        // Descending chunks must be reversed.
+        if res == MergesortResult::Descending {
+            v[a..b].reverse();
+        }
+
+        chunks.push((a, b));
+    }
+
+    // All chunks are properly sorted.
+    // Now we just have to merge them together.
+    unsafe {
+        recurse(v.as_mut_ptr(), buf, &chunks, false, &is_less);
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::split_for_merge;
+    use rand::distributions::Uniform;
+    use rand::{thread_rng, Rng};
+
+    #[test]
+    fn test_split_for_merge() {
+        fn check(left: &[u32], right: &[u32]) {
+            let (l, r) = split_for_merge(left, right, &|&a, &b| a < b);
+            assert!(left[..l]
+                .iter()
+                .all(|&x| right[r..].iter().all(|&y| x <= y)));
+            assert!(right[..r].iter().all(|&x| left[l..].iter().all(|&y| x < y)));
+        }
+
+        check(&[1, 2, 2, 2, 2, 3], &[1, 2, 2, 2, 2, 3]);
+        check(&[1, 2, 2, 2, 2, 3], &[]);
+        check(&[], &[1, 2, 2, 2, 2, 3]);
+
+        let mut rng = thread_rng();
+
+        for _ in 0..100 {
+            let limit: u32 = rng.gen_range(1, 21);
+            let left_len: usize = rng.gen_range(0, 20);
+            let right_len: usize = rng.gen_range(0, 20);
+
+            let mut left = rng
+                .sample_iter(&Uniform::new(0, limit))
+                .take(left_len)
+                .collect::<Vec<_>>();
+            let mut right = rng
+                .sample_iter(&Uniform::new(0, limit))
+                .take(right_len)
+                .collect::<Vec<_>>();
+
+            left.sort();
+            right.sort();
+            check(&left, &right);
+        }
+    }
+}
diff --git a/third_party/rust/rayon/src/slice/mod.rs b/third_party/rust/rayon/src/slice/mod.rs
new file mode 100644
index 0000000000..b80125f549
--- /dev/null
+++ b/third_party/rust/rayon/src/slice/mod.rs
@@ -0,0 +1,1203 @@
+//! Parallel iterator types for [slices][std::slice]
+//!
+//! You will rarely need to interact with this module directly unless you need
+//! to name one of the iterator types.
+//!
+//! [std::slice]: https://doc.rust-lang.org/stable/std/slice/
+
+mod mergesort;
+mod quicksort;
+
+mod test;
+
+use self::mergesort::par_mergesort;
+use self::quicksort::par_quicksort;
+use crate::iter::plumbing::*;
+use crate::iter::*;
+use crate::split_producer::*;
+use std::cmp;
+use std::cmp::Ordering;
+use std::fmt::{self, Debug};
+
+use super::math::div_round_up;
+
+/// Parallel extensions for slices.
+pub trait ParallelSlice<T: Sync> {
+    /// Returns a plain slice, which is used to implement the rest of the
+    /// parallel methods.
+    fn as_parallel_slice(&self) -> &[T];
+
+    /// Returns a parallel iterator over subslices separated by elements that
+    /// match the separator.
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// use rayon::prelude::*;
+    /// let smallest = [1, 2, 3, 0, 2, 4, 8, 0, 3, 6, 9]
+    ///     .par_split(|i| *i == 0)
+    ///     .map(|numbers| numbers.iter().min().unwrap())
+    ///     .min();
+    /// assert_eq!(Some(&1), smallest);
+    /// ```
+    fn par_split<P>(&self, separator: P) -> Split<'_, T, P>
+    where
+        P: Fn(&T) -> bool + Sync + Send,
+    {
+        Split {
+            slice: self.as_parallel_slice(),
+            separator,
+        }
+    }
+
+    /// Returns a parallel iterator over all contiguous windows of length
+    /// `window_size`. The windows overlap.
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// use rayon::prelude::*;
+    /// let windows: Vec<_> = [1, 2, 3].par_windows(2).collect();
+    /// assert_eq!(vec![[1, 2], [2, 3]], windows);
+    /// ```
+    fn par_windows(&self, window_size: usize) -> Windows<'_, T> {
+        Windows {
+            window_size,
+            slice: self.as_parallel_slice(),
+        }
+    }
+
+    /// Returns a parallel iterator over at most `chunk_size` elements of
+    /// `self` at a time. The chunks do not overlap.
+    ///
+    /// If the number of elements in the iterator is not divisible by
+    /// `chunk_size`, the last chunk may be shorter than `chunk_size`.  All
+    /// other chunks will have that exact length.
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// use rayon::prelude::*;
+    /// let chunks: Vec<_> = [1, 2, 3, 4, 5].par_chunks(2).collect();
+    /// assert_eq!(chunks, vec![&[1, 2][..], &[3, 4], &[5]]);
+    /// ```
+    fn par_chunks(&self, chunk_size: usize) -> Chunks<'_, T> {
+        assert!(chunk_size != 0, "chunk_size must not be zero");
+        Chunks {
+            chunk_size,
+            slice: self.as_parallel_slice(),
+        }
+    }
+
+    /// Returns a parallel iterator over `chunk_size` elements of
+    /// `self` at a time. The chunks do not overlap.
+    ///
+    /// If `chunk_size` does not divide the length of the slice, then the
+    /// last up to `chunk_size-1` elements will be omitted and can be
+    /// retrieved from the remainder function of the iterator.
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// use rayon::prelude::*;
+    /// let chunks: Vec<_> = [1, 2, 3, 4, 5].par_chunks_exact(2).collect();
+    /// assert_eq!(chunks, vec![&[1, 2][..], &[3, 4]]);
+    /// ```
+    fn par_chunks_exact(&self, chunk_size: usize) -> ChunksExact<'_, T> {
+        assert!(chunk_size != 0, "chunk_size must not be zero");
+        let slice = self.as_parallel_slice();
+        let rem = slice.len() % chunk_size;
+        let len = slice.len() - rem;
+        let (fst, snd) = slice.split_at(len);
+        ChunksExact {
+            chunk_size,
+            slice: fst,
+            rem: snd,
+        }
+    }
+}
+
+impl<T: Sync> ParallelSlice<T> for [T] {
+    #[inline]
+    fn as_parallel_slice(&self) -> &[T] {
+        self
+    }
+}
+
+/// Parallel extensions for mutable slices.
+pub trait ParallelSliceMut<T: Send> {
+    /// Returns a plain mutable slice, which is used to implement the rest of
+    /// the parallel methods.
+    fn as_parallel_slice_mut(&mut self) -> &mut [T];
+
+    /// Returns a parallel iterator over mutable subslices separated by
+    /// elements that match the separator.
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// use rayon::prelude::*;
+    /// let mut array = [1, 2, 3, 0, 2, 4, 8, 0, 3, 6, 9];
+    /// array.par_split_mut(|i| *i == 0)
+    ///      .for_each(|slice| slice.reverse());
+    /// assert_eq!(array, [3, 2, 1, 0, 8, 4, 2, 0, 9, 6, 3]);
+    /// ```
+    fn par_split_mut<P>(&mut self, separator: P) -> SplitMut<'_, T, P>
+    where
+        P: Fn(&T) -> bool + Sync + Send,
+    {
+        SplitMut {
+            slice: self.as_parallel_slice_mut(),
+            separator,
+        }
+    }
+
+    /// Returns a parallel iterator over at most `chunk_size` elements of
+    /// `self` at a time. The chunks are mutable and do not overlap.
+    ///
+    /// If the number of elements in the iterator is not divisible by
+    /// `chunk_size`, the last chunk may be shorter than `chunk_size`.  All
+    /// other chunks will have that exact length.
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// use rayon::prelude::*;
+    /// let mut array = [1, 2, 3, 4, 5];
+    /// array.par_chunks_mut(2)
+    ///      .for_each(|slice| slice.reverse());
+    /// assert_eq!(array, [2, 1, 4, 3, 5]);
+    /// ```
+    fn par_chunks_mut(&mut self, chunk_size: usize) -> ChunksMut<'_, T> {
+        assert!(chunk_size != 0, "chunk_size must not be zero");
+        ChunksMut {
+            chunk_size,
+            slice: self.as_parallel_slice_mut(),
+        }
+    }
+
+    /// Returns a parallel iterator over `chunk_size` elements of
+    /// `self` at a time. The chunks are mutable and do not overlap.
+    ///
+    /// If `chunk_size` does not divide the length of the slice, then the
+    /// last up to `chunk_size-1` elements will be omitted and can be
+    /// retrieved from the remainder function of the iterator.
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// use rayon::prelude::*;
+    /// let mut array = [1, 2, 3, 4, 5];
+    /// array.par_chunks_exact_mut(3)
+    ///      .for_each(|slice| slice.reverse());
+    /// assert_eq!(array, [3, 2, 1, 4, 5]);
+    /// ```
+    fn par_chunks_exact_mut(&mut self, chunk_size: usize) -> ChunksExactMut<'_, T> {
+        assert!(chunk_size != 0, "chunk_size must not be zero");
+        let slice = self.as_parallel_slice_mut();
+        let rem = slice.len() % chunk_size;
+        let len = slice.len() - rem;
+        let (fst, snd) = slice.split_at_mut(len);
+        ChunksExactMut {
+            chunk_size,
+            slice: fst,
+            rem: snd,
+        }
+    }
+
+    /// Sorts the slice in parallel.
+    ///
+    /// This sort is stable (i.e. does not reorder equal elements) and `O(n log n)` worst-case.
+    ///
+    /// When applicable, unstable sorting is preferred because it is generally faster than stable
+    /// sorting and it doesn't allocate auxiliary memory.
+    /// See [`par_sort_unstable`](#method.par_sort_unstable).
+    ///
+    /// # Current implementation
+    ///
+    /// The current algorithm is an adaptive merge sort inspired by
+    /// [timsort](https://en.wikipedia.org/wiki/Timsort).
+    /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of
+    /// two or more sorted sequences concatenated one after another.
+    ///
+    /// Also, it allocates temporary storage the same size as `self`, but for very short slices a
+    /// non-allocating insertion sort is used instead.
+    ///
+    /// In order to sort the slice in parallel, the slice is first divided into smaller chunks and
+    /// all chunks are sorted in parallel. Then, adjacent chunks that together form non-descending
+    /// or descending runs are concatenated. Finally, the remaining chunks are merged together using
+    /// parallel subdivision of chunks and parallel merge operation.
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// use rayon::prelude::*;
+    ///
+    /// let mut v = [-5, 4, 1, -3, 2];
+    ///
+    /// v.par_sort();
+    /// assert_eq!(v, [-5, -3, 1, 2, 4]);
+    /// ```
+    fn par_sort(&mut self)
+    where
+        T: Ord,
+    {
+        par_mergesort(self.as_parallel_slice_mut(), T::lt);
+    }
+
+    /// Sorts the slice in parallel with a comparator function.
+    ///
+    /// This sort is stable (i.e. does not reorder equal elements) and `O(n log n)` worst-case.
+    ///
+    /// When applicable, unstable sorting is preferred because it is generally faster than stable
+    /// sorting and it doesn't allocate auxiliary memory.
+    /// See [`par_sort_unstable_by`](#method.par_sort_unstable_by).
+    ///
+    /// # Current implementation
+    ///
+    /// The current algorithm is an adaptive merge sort inspired by
+    /// [timsort](https://en.wikipedia.org/wiki/Timsort).
+    /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of
+    /// two or more sorted sequences concatenated one after another.
+    ///
+    /// Also, it allocates temporary storage the same size as `self`, but for very short slices a
+    /// non-allocating insertion sort is used instead.
+    ///
+    /// In order to sort the slice in parallel, the slice is first divided into smaller chunks and
+    /// all chunks are sorted in parallel. Then, adjacent chunks that together form non-descending
+    /// or descending runs are concatenated. Finally, the remaining chunks are merged together using
+    /// parallel subdivision of chunks and parallel merge operation.
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// use rayon::prelude::*;
+    ///
+    /// let mut v = [5, 4, 1, 3, 2];
+    /// v.par_sort_by(|a, b| a.cmp(b));
+    /// assert_eq!(v, [1, 2, 3, 4, 5]);
+    ///
+    /// // reverse sorting
+    /// v.par_sort_by(|a, b| b.cmp(a));
+    /// assert_eq!(v, [5, 4, 3, 2, 1]);
+    /// ```
+    fn par_sort_by<F>(&mut self, compare: F)
+    where
+        F: Fn(&T, &T) -> Ordering + Sync,
+    {
+        par_mergesort(self.as_parallel_slice_mut(), |a, b| {
+            compare(a, b) == Ordering::Less
+        });
+    }
+
+    /// Sorts the slice in parallel with a key extraction function.
+    ///
+    /// This sort is stable (i.e. does not reorder equal elements) and `O(n log n)` worst-case.
+    ///
+    /// When applicable, unstable sorting is preferred because it is generally faster than stable
+    /// sorting and it doesn't allocate auxiliary memory.
+    /// See [`par_sort_unstable_by_key`](#method.par_sort_unstable_by_key).
+    ///
+    /// # Current implementation
+    ///
+    /// The current algorithm is an adaptive merge sort inspired by
+    /// [timsort](https://en.wikipedia.org/wiki/Timsort).
+    /// It is designed to be very fast in cases where the slice is nearly sorted, or consists of
+    /// two or more sorted sequences concatenated one after another.
+    ///
+    /// Also, it allocates temporary storage the same size as `self`, but for very short slices a
+    /// non-allocating insertion sort is used instead.
+    ///
+    /// In order to sort the slice in parallel, the slice is first divided into smaller chunks and
+    /// all chunks are sorted in parallel. Then, adjacent chunks that together form non-descending
+    /// or descending runs are concatenated. Finally, the remaining chunks are merged together using
+    /// parallel subdivision of chunks and parallel merge operation.
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// use rayon::prelude::*;
+    ///
+    /// let mut v = [-5i32, 4, 1, -3, 2];
+    ///
+    /// v.par_sort_by_key(|k| k.abs());
+    /// assert_eq!(v, [1, 2, -3, 4, -5]);
+    /// ```
+    fn par_sort_by_key<B, F>(&mut self, f: F)
+    where
+        B: Ord,
+        F: Fn(&T) -> B + Sync,
+    {
+        par_mergesort(self.as_parallel_slice_mut(), |a, b| f(a).lt(&f(b)));
+    }
+
+    /// Sorts the slice in parallel, but may not preserve the order of equal elements.
+    ///
+    /// This sort is unstable (i.e. may reorder equal elements), in-place (i.e. does not allocate),
+    /// and `O(n log n)` worst-case.
+    ///
+    /// # Current implementation
+    ///
+    /// The current algorithm is based on Orson Peters' [pattern-defeating quicksort][pdqsort],
+    /// which is a quicksort variant designed to be very fast on certain kinds of patterns,
+    /// sometimes achieving linear time. It is randomized but deterministic, and falls back to
+    /// heapsort on degenerate inputs.
+    ///
+    /// It is generally faster than stable sorting, except in a few special cases, e.g. when the
+    /// slice consists of several concatenated sorted sequences.
+    ///
+    /// All quicksorts work in two stages: partitioning into two halves followed by recursive
+    /// calls. The partitioning phase is sequential, but the two recursive calls are performed in
+    /// parallel.
+    ///
+    /// [pdqsort]: https://github.com/orlp/pdqsort
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// use rayon::prelude::*;
+    ///
+    /// let mut v = [-5, 4, 1, -3, 2];
+    ///
+    /// v.par_sort_unstable();
+    /// assert_eq!(v, [-5, -3, 1, 2, 4]);
+    /// ```
+    fn par_sort_unstable(&mut self)
+    where
+        T: Ord,
+    {
+        par_quicksort(self.as_parallel_slice_mut(), T::lt);
+    }
+
+    /// Sorts the slice in parallel with a comparator function, but may not preserve the order of
+    /// equal elements.
+    ///
+    /// This sort is unstable (i.e. may reorder equal elements), in-place (i.e. does not allocate),
+    /// and `O(n log n)` worst-case.
+    ///
+    /// # Current implementation
+    ///
+    /// The current algorithm is based on Orson Peters' [pattern-defeating quicksort][pdqsort],
+    /// which is a quicksort variant designed to be very fast on certain kinds of patterns,
+    /// sometimes achieving linear time. It is randomized but deterministic, and falls back to
+    /// heapsort on degenerate inputs.
+    ///
+    /// It is generally faster than stable sorting, except in a few special cases, e.g. when the
+    /// slice consists of several concatenated sorted sequences.
+    ///
+    /// All quicksorts work in two stages: partitioning into two halves followed by recursive
+    /// calls. The partitioning phase is sequential, but the two recursive calls are performed in
+    /// parallel.
+    ///
+    /// [pdqsort]: https://github.com/orlp/pdqsort
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// use rayon::prelude::*;
+    ///
+    /// let mut v = [5, 4, 1, 3, 2];
+    /// v.par_sort_unstable_by(|a, b| a.cmp(b));
+    /// assert_eq!(v, [1, 2, 3, 4, 5]);
+    ///
+    /// // reverse sorting
+    /// v.par_sort_unstable_by(|a, b| b.cmp(a));
+    /// assert_eq!(v, [5, 4, 3, 2, 1]);
+    /// ```
+    fn par_sort_unstable_by<F>(&mut self, compare: F)
+    where
+        F: Fn(&T, &T) -> Ordering + Sync,
+    {
+        par_quicksort(self.as_parallel_slice_mut(), |a, b| {
+            compare(a, b) == Ordering::Less
+        });
+    }
+
+    /// Sorts the slice in parallel with a key extraction function, but may not preserve the order
+    /// of equal elements.
+    ///
+    /// This sort is unstable (i.e. may reorder equal elements), in-place (i.e. does not allocate),
+    /// and `O(n log n)` worst-case.
+    ///
+    /// # Current implementation
+    ///
+    /// The current algorithm is based on Orson Peters' [pattern-defeating quicksort][pdqsort],
+    /// which is a quicksort variant designed to be very fast on certain kinds of patterns,
+    /// sometimes achieving linear time. It is randomized but deterministic, and falls back to
+    /// heapsort on degenerate inputs.
+    ///
+    /// It is generally faster than stable sorting, except in a few special cases, e.g. when the
+    /// slice consists of several concatenated sorted sequences.
+    ///
+    /// All quicksorts work in two stages: partitioning into two halves followed by recursive
+    /// calls. The partitioning phase is sequential, but the two recursive calls are performed in
+    /// parallel.
+    ///
+    /// [pdqsort]: https://github.com/orlp/pdqsort
+    ///
+    /// # Examples
+    ///
+    /// ```
+    /// use rayon::prelude::*;
+    ///
+    /// let mut v = [-5i32, 4, 1, -3, 2];
+    ///
+    /// v.par_sort_unstable_by_key(|k| k.abs());
+    /// assert_eq!(v, [1, 2, -3, 4, -5]);
+    /// ```
+    fn par_sort_unstable_by_key<B, F>(&mut self, f: F)
+    where
+        B: Ord,
+        F: Fn(&T) -> B + Sync,
+    {
+        par_quicksort(self.as_parallel_slice_mut(), |a, b| f(a).lt(&f(b)));
+    }
+}
+
+impl<T: Send> ParallelSliceMut<T> for [T] {
+    #[inline]
+    fn as_parallel_slice_mut(&mut self) -> &mut [T] {
+        self
+    }
+}
+
+impl<'data, T: Sync + 'data> IntoParallelIterator for &'data [T] {
+    type Item = &'data T;
+    type Iter = Iter<'data, T>;
+
+    fn into_par_iter(self) -> Self::Iter {
+        Iter { slice: self }
+    }
+}
+
+impl<'data, T: Sync + 'data> IntoParallelIterator for &'data Vec<T> {
+    type Item = &'data T;
+    type Iter = Iter<'data, T>;
+
+    fn into_par_iter(self) -> Self::Iter {
+        Iter { slice: self }
+    }
+}
+
+impl<'data, T: Send + 'data> IntoParallelIterator for &'data mut [T] {
+    type Item = &'data mut T;
+    type Iter = IterMut<'data, T>;
+
+    fn into_par_iter(self) -> Self::Iter {
+        IterMut { slice: self }
+    }
+}
+
+impl<'data, T: Send + 'data> IntoParallelIterator for &'data mut Vec<T> {
+    type Item = &'data mut T;
+    type Iter = IterMut<'data, T>;
+
+    fn into_par_iter(self) -> Self::Iter {
+        IterMut { slice: self }
+    }
+}
+
+/// Parallel iterator over immutable items in a slice
+#[derive(Debug)]
+pub struct Iter<'data, T: Sync> {
+    slice: &'data [T],
+}
+
+impl<'data, T: Sync> Clone for Iter<'data, T> {
+    fn clone(&self) -> Self {
+        Iter { ..*self }
+    }
+}
+
+impl<'data, T: Sync + 'data> ParallelIterator for Iter<'data, T> {
+    type Item = &'data T;
+
+    fn drive_unindexed<C>(self, consumer: C) -> C::Result
+    where
+        C: UnindexedConsumer<Self::Item>,
+    {
+        bridge(self, consumer)
+    }
+
+    fn opt_len(&self) -> Option<usize> {
+        Some(self.len())
+    }
+}
+
+impl<'data, T: Sync + 'data> IndexedParallelIterator for Iter<'data, T> {
+    fn drive<C>(self, consumer: C) -> C::Result
+    where
+        C: Consumer<Self::Item>,
+    {
+        bridge(self, consumer)
+    }
+
+    fn len(&self) -> usize {
+        self.slice.len()
+    }
+
+    fn with_producer<CB>(self, callback: CB) -> CB::Output
+    where
+        CB: ProducerCallback<Self::Item>,
+    {
+        callback.callback(IterProducer { slice: self.slice })
+    }
+}
+
+struct IterProducer<'data, T: Sync> {
+    slice: &'data [T],
+}
+
+impl<'data, T: 'data + Sync> Producer for IterProducer<'data, T> {
+    type Item = &'data T;
+    type IntoIter = ::std::slice::Iter<'data, T>;
+
+    fn into_iter(self) -> Self::IntoIter {
+        self.slice.iter()
+    }
+
+    fn split_at(self, index: usize) -> (Self, Self) {
+        let (left, right) = self.slice.split_at(index);
+        (IterProducer { slice: left }, IterProducer { slice: right })
+    }
+}
+
+/// Parallel iterator over immutable non-overlapping chunks of a slice
+#[derive(Debug)]
+pub struct Chunks<'data, T: Sync> {
+    chunk_size: usize,
+    slice: &'data [T],
+}
+
+impl<'data, T: Sync> Clone for Chunks<'data, T> {
+    fn clone(&self) -> Self {
+        Chunks { ..*self }
+    }
+}
+
+impl<'data, T: Sync + 'data> ParallelIterator for Chunks<'data, T> {
+    type Item = &'data [T];
+
+    fn drive_unindexed<C>(self, consumer: C) -> C::Result
+    where
+        C: UnindexedConsumer<Self::Item>,
+    {
+        bridge(self, consumer)
+    }
+
+    fn opt_len(&self) -> Option<usize> {
+        Some(self.len())
+    }
+}
+
+impl<'data, T: Sync + 'data> IndexedParallelIterator for Chunks<'data, T> {
+    fn drive<C>(self, consumer: C) -> C::Result
+    where
+        C: Consumer<Self::Item>,
+    {
+        bridge(self, consumer)
+    }
+
+    fn len(&self) -> usize {
+        div_round_up(self.slice.len(), self.chunk_size)
+    }
+
+    fn with_producer<CB>(self, callback: CB) -> CB::Output
+    where
+        CB: ProducerCallback<Self::Item>,
+    {
+        callback.callback(ChunksProducer {
+            chunk_size: self.chunk_size,
+            slice: self.slice,
+        })
+    }
+}
+
+struct ChunksProducer<'data, T: Sync> {
+    chunk_size: usize,
+    slice: &'data [T],
+}
+
+impl<'data, T: 'data + Sync> Producer for ChunksProducer<'data, T> {
+    type Item = &'data [T];
+    type IntoIter = ::std::slice::Chunks<'data, T>;
+
+    fn into_iter(self) -> Self::IntoIter {
+        self.slice.chunks(self.chunk_size)
+    }
+
+    fn split_at(self, index: usize) -> (Self, Self) {
+        let elem_index = cmp::min(index * self.chunk_size, self.slice.len());
+        let (left, right) = self.slice.split_at(elem_index);
+        (
+            ChunksProducer {
+                chunk_size: self.chunk_size,
+                slice: left,
+            },
+            ChunksProducer {
+                chunk_size: self.chunk_size,
+                slice: right,
+            },
+        )
+    }
+}
+
+/// Parallel iterator over immutable non-overlapping chunks of a slice
+#[derive(Debug)]
+pub struct ChunksExact<'data, T: Sync> {
+    chunk_size: usize,
+    slice: &'data [T],
+    rem: &'data [T],
+}
+
+impl<'data, T: Sync> ChunksExact<'data, T> {
+    /// Return the remainder of the original slice that is not going to be
+    /// returned by the iterator. The returned slice has at most `chunk_size-1`
+    /// elements.
+    pub fn remainder(&self) -> &'data [T] {
+        self.rem
+    }
+}
+
+impl<'data, T: Sync> Clone for ChunksExact<'data, T> {
+    fn clone(&self) -> Self {
+        ChunksExact { ..*self }
+    }
+}
+
+impl<'data, T: Sync + 'data> ParallelIterator for ChunksExact<'data, T> {
+    type Item = &'data [T];
+
+    fn drive_unindexed<C>(self, consumer: C) -> C::Result
+    where
+        C: UnindexedConsumer<Self::Item>,
+    {
+        bridge(self, consumer)
+    }
+
+    fn opt_len(&self) -> Option<usize> {
+        Some(self.len())
+    }
+}
+
+impl<'data, T: Sync + 'data> IndexedParallelIterator for ChunksExact<'data, T> {
+    fn drive<C>(self, consumer: C) -> C::Result
+    where
+        C: Consumer<Self::Item>,
+    {
+        bridge(self, consumer)
+    }
+
+    fn len(&self) -> usize {
+        self.slice.len() / self.chunk_size
+    }
+
+    fn with_producer<CB>(self, callback: CB) -> CB::Output
+    where
+        CB: ProducerCallback<Self::Item>,
+    {
+        callback.callback(ChunksExactProducer {
+            chunk_size: self.chunk_size,
+            slice: self.slice,
+        })
+    }
+}
+
+struct ChunksExactProducer<'data, T: Sync> {
+    chunk_size: usize,
+    slice: &'data [T],
+}
+
+impl<'data, T: 'data + Sync> Producer for ChunksExactProducer<'data, T> {
+    type Item = &'data [T];
+    type IntoIter = ::std::slice::ChunksExact<'data, T>;
+
+    fn into_iter(self) -> Self::IntoIter {
+        self.slice.chunks_exact(self.chunk_size)
+    }
+
+    fn split_at(self, index: usize) -> (Self, Self) {
+        let elem_index = index * self.chunk_size;
+        let (left, right) = self.slice.split_at(elem_index);
+        (
+            ChunksExactProducer {
+                chunk_size: self.chunk_size,
+                slice: left,
+            },
+            ChunksExactProducer {
+                chunk_size: self.chunk_size,
+                slice: right,
+            },
+        )
+    }
+}
+
+/// Parallel iterator over immutable overlapping windows of a slice
+#[derive(Debug)]
+pub struct Windows<'data, T: Sync> {
+    window_size: usize,
+    slice: &'data [T],
+}
+
+impl<'data, T: Sync> Clone for Windows<'data, T> {
+    fn clone(&self) -> Self {
+        Windows { ..*self }
+    }
+}
+
+impl<'data, T: Sync + 'data> ParallelIterator for Windows<'data, T> {
+    type Item = &'data [T];
+
+    fn drive_unindexed<C>(self, consumer: C) -> C::Result
+    where
+        C: UnindexedConsumer<Self::Item>,
+    {
+        bridge(self, consumer)
+    }
+
+    fn opt_len(&self) -> Option<usize> {
+        Some(self.len())
+    }
+}
+
+impl<'data, T: Sync + 'data> IndexedParallelIterator for Windows<'data, T> {
+    fn drive<C>(self, consumer: C) -> C::Result
+    where
+        C: Consumer<Self::Item>,
+    {
+        bridge(self, consumer)
+    }
+
+    fn len(&self) -> usize {
+        assert!(self.window_size >= 1);
+        self.slice.len().saturating_sub(self.window_size - 1)
+    }
+
+    fn with_producer<CB>(self, callback: CB) -> CB::Output
+    where
+        CB: ProducerCallback<Self::Item>,
+    {
+        callback.callback(WindowsProducer {
+            window_size: self.window_size,
+            slice: self.slice,
+        })
+    }
+}
+
+struct WindowsProducer<'data, T: Sync> {
+    window_size: usize,
+    slice: &'data [T],
+}
+
+impl<'data, T: 'data + Sync> Producer for WindowsProducer<'data, T> {
+    type Item = &'data [T];
+    type IntoIter = ::std::slice::Windows<'data, T>;
+
+    fn into_iter(self) -> Self::IntoIter {
+        self.slice.windows(self.window_size)
+    }
+
+    fn split_at(self, index: usize) -> (Self, Self) {
+        let left_index = cmp::min(self.slice.len(), index + (self.window_size - 1));
+        let left = &self.slice[..left_index];
+        let right = &self.slice[index..];
+        (
+            WindowsProducer {
+                window_size: self.window_size,
+                slice: left,
+            },
+            WindowsProducer {
+                window_size: self.window_size,
+                slice: right,
+            },
+        )
+    }
+}
+
+/// Parallel iterator over mutable items in a slice
+#[derive(Debug)]
+pub struct IterMut<'data, T: Send> {
+    slice: &'data mut [T],
+}
+
+impl<'data, T: Send + 'data> ParallelIterator for IterMut<'data, T> {
+    type Item = &'data mut T;
+
+    fn drive_unindexed<C>(self, consumer: C) -> C::Result
+    where
+        C: UnindexedConsumer<Self::Item>,
+    {
+        bridge(self, consumer)
+    }
+
+    fn opt_len(&self) -> Option<usize> {
+        Some(self.len())
+    }
+}
+
+impl<'data, T: Send + 'data> IndexedParallelIterator for IterMut<'data, T> {
+    fn drive<C>(self, consumer: C) -> C::Result
+    where
+        C: Consumer<Self::Item>,
+    {
+        bridge(self, consumer)
+    }
+
+    fn len(&self) -> usize {
+        self.slice.len()
+    }
+
+    fn with_producer<CB>(self, callback: CB) -> CB::Output
+    where
+        CB: ProducerCallback<Self::Item>,
+    {
+        callback.callback(IterMutProducer { slice: self.slice })
+    }
+}
+
+struct IterMutProducer<'data, T: Send> {
+    slice: &'data mut [T],
+}
+
+impl<'data, T: 'data + Send> Producer for IterMutProducer<'data, T> {
+    type Item = &'data mut T;
+    type IntoIter = ::std::slice::IterMut<'data, T>;
+
+    fn into_iter(self) -> Self::IntoIter {
+        self.slice.iter_mut()
+    }
+
+    fn split_at(self, index: usize) -> (Self, Self) {
+        let (left, right) = self.slice.split_at_mut(index);
+        (
+            IterMutProducer { slice: left },
+            IterMutProducer { slice: right },
+        )
+    }
+}
+
+/// Parallel iterator over mutable non-overlapping chunks of a slice
+#[derive(Debug)]
+pub struct ChunksMut<'data, T: Send> {
+    chunk_size: usize,
+    slice: &'data mut [T],
+}
+
+impl<'data, T: Send + 'data> ParallelIterator for ChunksMut<'data, T> {
+    type Item = &'data mut [T];
+
+    fn drive_unindexed<C>(self, consumer: C) -> C::Result
+    where
+        C: UnindexedConsumer<Self::Item>,
+    {
+        bridge(self, consumer)
+    }
+
+    fn opt_len(&self) -> Option<usize> {
+        Some(self.len())
+    }
+}
+
+impl<'data, T: Send + 'data> IndexedParallelIterator for ChunksMut<'data, T> {
+    fn drive<C>(self, consumer: C) -> C::Result
+    where
+        C: Consumer<Self::Item>,
+    {
+        bridge(self, consumer)
+    }
+
+    fn len(&self) -> usize {
+        div_round_up(self.slice.len(), self.chunk_size)
+    }
+
+    fn with_producer<CB>(self, callback: CB) -> CB::Output
+    where
+        CB: ProducerCallback<Self::Item>,
+    {
+        callback.callback(ChunksMutProducer {
+            chunk_size: self.chunk_size,
+            slice: self.slice,
+        })
+    }
+}
+
+struct ChunksMutProducer<'data, T: Send> {
+    chunk_size: usize,
+    slice: &'data mut [T],
+}
+
+impl<'data, T: 'data + Send> Producer for ChunksMutProducer<'data, T> {
+    type Item = &'data mut [T];
+    type IntoIter = ::std::slice::ChunksMut<'data, T>;
+
+    fn into_iter(self) -> Self::IntoIter {
+        self.slice.chunks_mut(self.chunk_size)
+    }
+
+    fn split_at(self, index: usize) -> (Self, Self) {
+        let elem_index = cmp::min(index * self.chunk_size, self.slice.len());
+        let (left, right) = self.slice.split_at_mut(elem_index);
+        (
+            ChunksMutProducer {
+                chunk_size: self.chunk_size,
+                slice: left,
+            },
+            ChunksMutProducer {
+                chunk_size: self.chunk_size,
+                slice: right,
+            },
+        )
+    }
+}
+
+/// Parallel iterator over mutable non-overlapping chunks of a slice
+#[derive(Debug)]
+pub struct ChunksExactMut<'data, T: Send> {
+    chunk_size: usize,
+    slice: &'data mut [T],
+    rem: &'data mut [T],
+}
+
+impl<'data, T: Send> ChunksExactMut<'data, T> {
+    /// Return the remainder of the original slice that is not going to be
+    /// returned by the iterator. The returned slice has at most `chunk_size-1`
+    /// elements.
+    ///
+    /// Note that this has to consume `self` to return the original lifetime of
+    /// the data, which prevents this from actually being used as a parallel
+    /// iterator since that also consumes. This method is provided for parity
+    /// with `std::iter::ChunksExactMut`, but consider calling `remainder()` or
+    /// `take_remainder()` as alternatives.
+    pub fn into_remainder(self) -> &'data mut [T] {
+        self.rem
+    }
+
+    /// Return the remainder of the original slice that is not going to be
+    /// returned by the iterator. The returned slice has at most `chunk_size-1`
+    /// elements.
+    ///
+    /// Consider `take_remainder()` if you need access to the data with its
+    /// original lifetime, rather than borrowing through `&mut self` here.
+    pub fn remainder(&mut self) -> &mut [T] {
+        self.rem
+    }
+
+    /// Return the remainder of the original slice that is not going to be
+    /// returned by the iterator. The returned slice has at most `chunk_size-1`
+    /// elements. Subsequent calls will return an empty slice.
+    pub fn take_remainder(&mut self) -> &'data mut [T] {
+        std::mem::replace(&mut self.rem, &mut [])
+    }
+}
+
+impl<'data, T: Send + 'data> ParallelIterator for ChunksExactMut<'data, T> {
+    type Item = &'data mut [T];
+
+    fn drive_unindexed<C>(self, consumer: C) -> C::Result
+    where
+        C: UnindexedConsumer<Self::Item>,
+    {
+        bridge(self, consumer)
+    }
+
+    fn opt_len(&self) -> Option<usize> {
+        Some(self.len())
+    }
+}
+
+impl<'data, T: Send + 'data> IndexedParallelIterator for ChunksExactMut<'data, T> {
+    fn drive<C>(self, consumer: C) -> C::Result
+    where
+        C: Consumer<Self::Item>,
+    {
+        bridge(self, consumer)
+    }
+
+    fn len(&self) -> usize {
+        self.slice.len() / self.chunk_size
+    }
+
+    fn with_producer<CB>(self, callback: CB) -> CB::Output
+    where
+        CB: ProducerCallback<Self::Item>,
+    {
+        callback.callback(ChunksExactMutProducer {
+            chunk_size: self.chunk_size,
+            slice: self.slice,
+        })
+    }
+}
+
+struct ChunksExactMutProducer<'data, T: Send> {
+    chunk_size: usize,
+    slice: &'data mut [T],
+}
+
+impl<'data, T: 'data + Send> Producer for ChunksExactMutProducer<'data, T> {
+    type Item = &'data mut [T];
+    type IntoIter = ::std::slice::ChunksExactMut<'data, T>;
+
+    fn into_iter(self) -> Self::IntoIter {
+        self.slice.chunks_exact_mut(self.chunk_size)
+    }
+
+    fn split_at(self, index: usize) -> (Self, Self) {
+        let elem_index = index * self.chunk_size;
+        let (left, right) = self.slice.split_at_mut(elem_index);
+        (
+            ChunksExactMutProducer {
+                chunk_size: self.chunk_size,
+                slice: left,
+            },
+            ChunksExactMutProducer {
+                chunk_size: self.chunk_size,
+                slice: right,
+            },
+        )
+    }
+}
+
+/// Parallel iterator over slices separated by a predicate
+pub struct Split<'data, T, P> {
+    slice: &'data [T],
+    separator: P,
+}
+
+impl<'data, T, P: Clone> Clone for Split<'data, T, P> {
+    fn clone(&self) -> Self {
+        Split {
+            separator: self.separator.clone(),
+            ..*self
+        }
+    }
+}
+
+impl<'data, T: Debug, P> Debug for Split<'data, T, P> {
+    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+        f.debug_struct("Split").field("slice", &self.slice).finish()
+    }
+}
+
+impl<'data, T, P> ParallelIterator for Split<'data, T, P>
+where
+    P: Fn(&T) -> bool + Sync + Send,
+    T: Sync,
+{
+    type Item = &'data [T];
+
+    fn drive_unindexed<C>(self, consumer: C) -> C::Result
+    where
+        C: UnindexedConsumer<Self::Item>,
+    {
+        let producer = SplitProducer::new(self.slice, &self.separator);
+        bridge_unindexed(producer, consumer)
+    }
+}
+
+/// Implement support for `SplitProducer`.
+impl<'data, T, P> Fissile<P> for &'data [T]
+where
+    P: Fn(&T) -> bool,
+{
+    fn length(&self) -> usize {
+        self.len()
+    }
+
+    fn midpoint(&self, end: usize) -> usize {
+        end / 2
+    }
+
+    fn find(&self, separator: &P, start: usize, end: usize) -> Option<usize> {
+        self[start..end].iter().position(separator)
+    }
+
+    fn rfind(&self, separator: &P, end: usize) -> Option<usize> {
+        self[..end].iter().rposition(separator)
+    }
+
+    fn split_once(self, index: usize) -> (Self, Self) {
+        let (left, right) = self.split_at(index);
+        (left, &right[1..]) // skip the separator
+    }
+
+    fn fold_splits<F>(self, separator: &P, folder: F, skip_last: bool) -> F
+    where
+        F: Folder<Self>,
+        Self: Send,
+    {
+        let mut split = self.split(separator);
+        if skip_last {
+            split.next_back();
+        }
+        folder.consume_iter(split)
+    }
+}
+
+/// Parallel iterator over mutable slices separated by a predicate
+pub struct SplitMut<'data, T, P> {
+    slice: &'data mut [T],
+    separator: P,
+}
+
+impl<'data, T: Debug, P> Debug for SplitMut<'data, T, P> {
+    fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
+        f.debug_struct("SplitMut")
+            .field("slice", &self.slice)
+            .finish()
+    }
+}
+
+impl<'data, T, P> ParallelIterator for SplitMut<'data, T, P>
+where
+    P: Fn(&T) -> bool + Sync + Send,
+    T: Send,
+{
+    type Item = &'data mut [T];
+
+    fn drive_unindexed<C>(self, consumer: C) -> C::Result
+    where
+        C: UnindexedConsumer<Self::Item>,
+    {
+        let producer = SplitProducer::new(self.slice, &self.separator);
+        bridge_unindexed(producer, consumer)
+    }
+}
+
+/// Implement support for `SplitProducer`.
+impl<'data, T, P> Fissile<P> for &'data mut [T]
+where
+    P: Fn(&T) -> bool,
+{
+    fn length(&self) -> usize {
+        self.len()
+    }
+
+    fn midpoint(&self, end: usize) -> usize {
+        end / 2
+    }
+
+    fn find(&self, separator: &P, start: usize, end: usize) -> Option<usize> {
+        self[start..end].iter().position(separator)
+    }
+
+    fn rfind(&self, separator: &P, end: usize) -> Option<usize> {
+        self[..end].iter().rposition(separator)
+    }
+
+    fn split_once(self, index: usize) -> (Self, Self) {
+        let (left, right) = self.split_at_mut(index);
+        (left, &mut right[1..]) // skip the separator
+    }
+
+    fn fold_splits<F>(self, separator: &P, folder: F, skip_last: bool) -> F
+    where
+        F: Folder<Self>,
+        Self: Send,
+    {
+        let mut split = self.split_mut(separator);
+        if skip_last {
+            split.next_back();
+        }
+        folder.consume_iter(split)
+    }
+}
diff --git a/third_party/rust/rayon/src/slice/quicksort.rs b/third_party/rust/rayon/src/slice/quicksort.rs
new file mode 100644
index 0000000000..b985073514
--- /dev/null
+++ b/third_party/rust/rayon/src/slice/quicksort.rs
@@ -0,0 +1,800 @@
+//! Parallel quicksort.
+//!
+//! This implementation is copied verbatim from `std::slice::sort_unstable` and then parallelized.
+//! The only difference from the original is that calls to `recurse` are executed in parallel using
+//! `rayon_core::join`.
+
+use std::cmp;
+use std::mem;
+use std::ptr;
+
+/// When dropped, takes the value out of `Option` and writes it into `dest`.
+///
+/// This allows us to safely read the pivot into a stack-allocated variable for efficiency, and
+/// write it back into the slice after partitioning. This way we ensure that the write happens
+/// even if `is_less` panics in the meantime.
+struct WriteOnDrop<T> {
+    value: Option<T>,
+    dest: *mut T,
+}
+
+impl<T> Drop for WriteOnDrop<T> {
+    fn drop(&mut self) {
+        unsafe {
+            ptr::write(self.dest, self.value.take().unwrap());
+        }
+    }
+}
+
+/// Holds a value, but never drops it.
+struct NoDrop<T> {
+    value: Option<T>,
+}
+
+impl<T> Drop for NoDrop<T> {
+    fn drop(&mut self) {
+        mem::forget(self.value.take());
+    }
+}
+
+/// When dropped, copies from `src` into `dest`.
+struct CopyOnDrop<T> {
+    src: *mut T,
+    dest: *mut T,
+}
+
+impl<T> Drop for CopyOnDrop<T> {
+    fn drop(&mut self) {
+        unsafe {
+            ptr::copy_nonoverlapping(self.src, self.dest, 1);
+        }
+    }
+}
+
+/// Shifts the first element to the right until it encounters a greater or equal element.
+fn shift_head<T, F>(v: &mut [T], is_less: &F)
+where
+    F: Fn(&T, &T) -> bool,
+{
+    let len = v.len();
+    unsafe {
+        // If the first two elements are out-of-order...
+        if len >= 2 && is_less(v.get_unchecked(1), v.get_unchecked(0)) {
+            // Read the first element into a stack-allocated variable. If a following comparison
+            // operation panics, `hole` will get dropped and automatically write the element back
+            // into the slice.
+            let mut tmp = NoDrop {
+                value: Some(ptr::read(v.get_unchecked(0))),
+            };
+            let mut hole = CopyOnDrop {
+                src: tmp.value.as_mut().unwrap(),
+                dest: v.get_unchecked_mut(1),
+            };
+            ptr::copy_nonoverlapping(v.get_unchecked(1), v.get_unchecked_mut(0), 1);
+
+            for i in 2..len {
+                if !is_less(v.get_unchecked(i), tmp.value.as_ref().unwrap()) {
+                    break;
+                }
+
+                // Move `i`-th element one place to the left, thus shifting the hole to the right.
+                ptr::copy_nonoverlapping(v.get_unchecked(i), v.get_unchecked_mut(i - 1), 1);
+                hole.dest = v.get_unchecked_mut(i);
+            }
+            // `hole` gets dropped and thus copies `tmp` into the remaining hole in `v`.
+        }
+    }
+}
+
+/// Shifts the last element to the left until it encounters a smaller or equal element.
+fn shift_tail<T, F>(v: &mut [T], is_less: &F)
+where
+    F: Fn(&T, &T) -> bool,
+{
+    let len = v.len();
+    unsafe {
+        // If the last two elements are out-of-order...
+        if len >= 2 && is_less(v.get_unchecked(len - 1), v.get_unchecked(len - 2)) {
+            // Read the last element into a stack-allocated variable. If a following comparison
+            // operation panics, `hole` will get dropped and automatically write the element back
+            // into the slice.
+            let mut tmp = NoDrop {
+                value: Some(ptr::read(v.get_unchecked(len - 1))),
+            };
+            let mut hole = CopyOnDrop {
+                src: tmp.value.as_mut().unwrap(),
+                dest: v.get_unchecked_mut(len - 2),
+            };
+            ptr::copy_nonoverlapping(v.get_unchecked(len - 2), v.get_unchecked_mut(len - 1), 1);
+
+            for i in (0..len - 2).rev() {
+                if !is_less(&tmp.value.as_ref().unwrap(), v.get_unchecked(i)) {
+                    break;
+                }
+
+                // Move `i`-th element one place to the right, thus shifting the hole to the left.
+                ptr::copy_nonoverlapping(v.get_unchecked(i), v.get_unchecked_mut(i + 1), 1);
+                hole.dest = v.get_unchecked_mut(i);
+            }
+            // `hole` gets dropped and thus copies `tmp` into the remaining hole in `v`.
+        }
+    }
+}
+
+/// Partially sorts a slice by shifting several out-of-order elements around.
+///
+/// Returns `true` if the slice is sorted at the end. This function is `O(n)` worst-case.
+#[cold]
+fn partial_insertion_sort<T, F>(v: &mut [T], is_less: &F) -> bool
+where
+    F: Fn(&T, &T) -> bool,
+{
+    // Maximum number of adjacent out-of-order pairs that will get shifted.
+    const MAX_STEPS: usize = 5;
+    // If the slice is shorter than this, don't shift any elements.
+    const SHORTEST_SHIFTING: usize = 50;
+
+    let len = v.len();
+    let mut i = 1;
+
+    for _ in 0..MAX_STEPS {
+        unsafe {
+            // Find the next pair of adjacent out-of-order elements.
+            while i < len && !is_less(v.get_unchecked(i), v.get_unchecked(i - 1)) {
+                i += 1;
+            }
+        }
+
+        // Are we done?
+        if i == len {
+            return true;
+        }
+
+        // Don't shift elements on short arrays, that has a performance cost.
+        if len < SHORTEST_SHIFTING {
+            return false;
+        }
+
+        // Swap the found pair of elements. This puts them in correct order.
+        v.swap(i - 1, i);
+
+        // Shift the smaller element to the left.
+        shift_tail(&mut v[..i], is_less);
+        // Shift the greater element to the right.
+        shift_head(&mut v[i..], is_less);
+    }
+
+    // Didn't manage to sort the slice in the limited number of steps.
+    false
+}
+
+/// Sorts a slice using insertion sort, which is `O(n^2)` worst-case.
+fn insertion_sort<T, F>(v: &mut [T], is_less: &F)
+where
+    F: Fn(&T, &T) -> bool,
+{
+    for i in 1..v.len() {
+        shift_tail(&mut v[..=i], is_less);
+    }
+}
+
+/// Sorts `v` using heapsort, which guarantees `O(n log n)` worst-case.
+#[cold]
+fn heapsort<T, F>(v: &mut [T], is_less: &F)
+where
+    F: Fn(&T, &T) -> bool,
+{
+    // This binary heap respects the invariant `parent >= child`.
+    let sift_down = |v: &mut [T], mut node| {
+        loop {
+            // Children of `node`:
+            let left = 2 * node + 1;
+            let right = 2 * node + 2;
+
+            // Choose the greater child.
+            let greater = if right < v.len() && is_less(&v[left], &v[right]) {
+                right
+            } else {
+                left
+            };
+
+            // Stop if the invariant holds at `node`.
+            if greater >= v.len() || !is_less(&v[node], &v[greater]) {
+                break;
+            }
+
+            // Swap `node` with the greater child, move one step down, and continue sifting.
+            v.swap(node, greater);
+            node = greater;
+        }
+    };
+
+    // Build the heap in linear time.
+    for i in (0..v.len() / 2).rev() {
+        sift_down(v, i);
+    }
+
+    // Pop maximal elements from the heap.
+    for i in (1..v.len()).rev() {
+        v.swap(0, i);
+        sift_down(&mut v[..i], 0);
+    }
+}
+
+/// Partitions `v` into elements smaller than `pivot`, followed by elements greater than or equal
+/// to `pivot`.
+///
+/// Returns the number of elements smaller than `pivot`.
+///
+/// Partitioning is performed block-by-block in order to minimize the cost of branching operations.
+/// This idea is presented in the [BlockQuicksort][pdf] paper.
+///
+/// [pdf]: http://drops.dagstuhl.de/opus/volltexte/2016/6389/pdf/LIPIcs-ESA-2016-38.pdf
+fn partition_in_blocks<T, F>(v: &mut [T], pivot: &T, is_less: &F) -> usize
+where
+    F: Fn(&T, &T) -> bool,
+{
+    // Number of elements in a typical block.
+    const BLOCK: usize = 128;
+
+    // The partitioning algorithm repeats the following steps until completion:
+    //
+    // 1. Trace a block from the left side to identify elements greater than or equal to the pivot.
+    // 2. Trace a block from the right side to identify elements smaller than the pivot.
+    // 3. Exchange the identified elements between the left and right side.
+    //
+    // We keep the following variables for a block of elements:
+    //
+    // 1. `block` - Number of elements in the block.
+    // 2. `start` - Start pointer into the `offsets` array.
+    // 3. `end` - End pointer into the `offsets` array.
+    // 4. `offsets - Indices of out-of-order elements within the block.
+
+    // The current block on the left side (from `l` to `l.offset(block_l)`).
+    let mut l = v.as_mut_ptr();
+    let mut block_l = BLOCK;
+    let mut start_l = ptr::null_mut();
+    let mut end_l = ptr::null_mut();
+    let mut offsets_l = [0u8; BLOCK];
+
+    // The current block on the right side (from `r.offset(-block_r)` to `r`).
+    let mut r = unsafe { l.add(v.len()) };
+    let mut block_r = BLOCK;
+    let mut start_r = ptr::null_mut();
+    let mut end_r = ptr::null_mut();
+    let mut offsets_r = [0u8; BLOCK];
+
+    // Returns the number of elements between pointers `l` (inclusive) and `r` (exclusive).
+    fn width<T>(l: *mut T, r: *mut T) -> usize {
+        assert!(mem::size_of::<T>() > 0);
+        (r as usize - l as usize) / mem::size_of::<T>()
+    }
+
+    loop {
+        // We are done with partitioning block-by-block when `l` and `r` get very close. Then we do
+        // some patch-up work in order to partition the remaining elements in between.
+        let is_done = width(l, r) <= 2 * BLOCK;
+
+        if is_done {
+            // Number of remaining elements (still not compared to the pivot).
+            let mut rem = width(l, r);
+            if start_l < end_l || start_r < end_r {
+                rem -= BLOCK;
+            }
+
+            // Adjust block sizes so that the left and right block don't overlap, but get perfectly
+            // aligned to cover the whole remaining gap.
+            if start_l < end_l {
+                block_r = rem;
+            } else if start_r < end_r {
+                block_l = rem;
+            } else {
+                block_l = rem / 2;
+                block_r = rem - block_l;
+            }
+            debug_assert!(block_l <= BLOCK && block_r <= BLOCK);
+            debug_assert!(width(l, r) == block_l + block_r);
+        }
+
+        if start_l == end_l {
+            // Trace `block_l` elements from the left side.
+            start_l = offsets_l.as_mut_ptr();
+            end_l = offsets_l.as_mut_ptr();
+            let mut elem = l;
+
+            for i in 0..block_l {
+                unsafe {
+                    // Branchless comparison.
+                    *end_l = i as u8;
+                    end_l = end_l.offset(!is_less(&*elem, pivot) as isize);
+                    elem = elem.offset(1);
+                }
+            }
+        }
+
+        if start_r == end_r {
+            // Trace `block_r` elements from the right side.
+            start_r = offsets_r.as_mut_ptr();
+            end_r = offsets_r.as_mut_ptr();
+            let mut elem = r;
+
+            for i in 0..block_r {
+                unsafe {
+                    // Branchless comparison.
+                    elem = elem.offset(-1);
+                    *end_r = i as u8;
+                    end_r = end_r.offset(is_less(&*elem, pivot) as isize);
+                }
+            }
+        }
+
+        // Number of out-of-order elements to swap between the left and right side.
+        let count = cmp::min(width(start_l, end_l), width(start_r, end_r));
+
+        if count > 0 {
+            macro_rules! left {
+                () => {
+                    l.offset(*start_l as isize)
+                };
+            }
+            macro_rules! right {
+                () => {
+                    r.offset(-(*start_r as isize) - 1)
+                };
+            }
+
+            // Instead of swapping one pair at the time, it is more efficient to perform a cyclic
+            // permutation. This is not strictly equivalent to swapping, but produces a similar
+            // result using fewer memory operations.
+            unsafe {
+                let tmp = ptr::read(left!());
+                ptr::copy_nonoverlapping(right!(), left!(), 1);
+
+                for _ in 1..count {
+                    start_l = start_l.offset(1);
+                    ptr::copy_nonoverlapping(left!(), right!(), 1);
+                    start_r = start_r.offset(1);
+                    ptr::copy_nonoverlapping(right!(), left!(), 1);
+                }
+
+                ptr::copy_nonoverlapping(&tmp, right!(), 1);
+                mem::forget(tmp);
+                start_l = start_l.offset(1);
+                start_r = start_r.offset(1);
+            }
+        }
+
+        if start_l == end_l {
+            // All out-of-order elements in the left block were moved. Move to the next block.
+            l = unsafe { l.add(block_l) };
+        }
+
+        if start_r == end_r {
+            // All out-of-order elements in the right block were moved. Move to the previous block.
+            r = unsafe { r.sub(block_r) };
+        }
+
+        if is_done {
+            break;
+        }
+    }
+
+    // All that remains now is at most one block (either the left or the right) with out-of-order
+    // elements that need to be moved. Such remaining elements can be simply shifted to the end
+    // within their block.
+
+    if start_l < end_l {
+        // The left block remains.
+        // Move it's remaining out-of-order elements to the far right.
+        debug_assert_eq!(width(l, r), block_l);
+        while start_l < end_l {
+            unsafe {
+                end_l = end_l.offset(-1);
+                ptr::swap(l.offset(*end_l as isize), r.offset(-1));
+                r = r.offset(-1);
+            }
+        }
+        width(v.as_mut_ptr(), r)
+    } else if start_r < end_r {
+        // The right block remains.
+        // Move it's remaining out-of-order elements to the far left.
+        debug_assert_eq!(width(l, r), block_r);
+        while start_r < end_r {
+            unsafe {
+                end_r = end_r.offset(-1);
+                ptr::swap(l, r.offset(-(*end_r as isize) - 1));
+                l = l.offset(1);
+            }
+        }
+        width(v.as_mut_ptr(), l)
+    } else {
+        // Nothing else to do, we're done.
+        width(v.as_mut_ptr(), l)
+    }
+}
+
+/// Partitions `v` into elements smaller than `v[pivot]`, followed by elements greater than or
+/// equal to `v[pivot]`.
+///
+/// Returns a tuple of:
+///
+/// 1. Number of elements smaller than `v[pivot]`.
+/// 2. True if `v` was already partitioned.
+fn partition<T, F>(v: &mut [T], pivot: usize, is_less: &F) -> (usize, bool)
+where
+    F: Fn(&T, &T) -> bool,
+{
+    let (mid, was_partitioned) = {
+        // Place the pivot at the beginning of slice.
+        v.swap(0, pivot);
+        let (pivot, v) = v.split_at_mut(1);
+        let pivot = &mut pivot[0];
+
+        // Read the pivot into a stack-allocated variable for efficiency. If a following comparison
+        // operation panics, the pivot will be automatically written back into the slice.
+        let write_on_drop = WriteOnDrop {
+            value: unsafe { Some(ptr::read(pivot)) },
+            dest: pivot,
+        };
+        let pivot = write_on_drop.value.as_ref().unwrap();
+
+        // Find the first pair of out-of-order elements.
+        let mut l = 0;
+        let mut r = v.len();
+        unsafe {
+            // Find the first element greater then or equal to the pivot.
+            while l < r && is_less(v.get_unchecked(l), pivot) {
+                l += 1;
+            }
+
+            // Find the last element smaller that the pivot.
+            while l < r && !is_less(v.get_unchecked(r - 1), pivot) {
+                r -= 1;
+            }
+        }
+
+        (
+            l + partition_in_blocks(&mut v[l..r], pivot, is_less),
+            l >= r,
+        )
+
+        // `write_on_drop` goes out of scope and writes the pivot (which is a stack-allocated
+        // variable) back into the slice where it originally was. This step is critical in ensuring
+        // safety!
+    };
+
+    // Place the pivot between the two partitions.
+    v.swap(0, mid);
+
+    (mid, was_partitioned)
+}
+
+/// Partitions `v` into elements equal to `v[pivot]` followed by elements greater than `v[pivot]`.
+///
+/// Returns the number of elements equal to the pivot. It is assumed that `v` does not contain
+/// elements smaller than the pivot.
+fn partition_equal<T, F>(v: &mut [T], pivot: usize, is_less: &F) -> usize
+where
+    F: Fn(&T, &T) -> bool,
+{
+    // Place the pivot at the beginning of slice.
+    v.swap(0, pivot);
+    let (pivot, v) = v.split_at_mut(1);
+    let pivot = &mut pivot[0];
+
+    // Read the pivot into a stack-allocated variable for efficiency. If a following comparison
+    // operation panics, the pivot will be automatically written back into the slice.
+    let write_on_drop = WriteOnDrop {
+        value: unsafe { Some(ptr::read(pivot)) },
+        dest: pivot,
+    };
+    let pivot = write_on_drop.value.as_ref().unwrap();
+
+    // Now partition the slice.
+    let mut l = 0;
+    let mut r = v.len();
+    loop {
+        unsafe {
+            // Find the first element greater that the pivot.
+            while l < r && !is_less(pivot, v.get_unchecked(l)) {
+                l += 1;
+            }
+
+            // Find the last element equal to the pivot.
+            while l < r && is_less(pivot, v.get_unchecked(r - 1)) {
+                r -= 1;
+            }
+
+            // Are we done?
+            if l >= r {
+                break;
+            }
+
+            // Swap the found pair of out-of-order elements.
+            r -= 1;
+            ptr::swap(v.get_unchecked_mut(l), v.get_unchecked_mut(r));
+            l += 1;
+        }
+    }
+
+    // We found `l` elements equal to the pivot. Add 1 to account for the pivot itself.
+    l + 1
+
+    // `write_on_drop` goes out of scope and writes the pivot (which is a stack-allocated variable)
+    // back into the slice where it originally was. This step is critical in ensuring safety!
+}
+
+/// Scatters some elements around in an attempt to break patterns that might cause imbalanced
+/// partitions in quicksort.
+#[cold]
+fn break_patterns<T>(v: &mut [T]) {
+    let len = v.len();
+    if len >= 8 {
+        // Pseudorandom number generator from the "Xorshift RNGs" paper by George Marsaglia.
+        let mut random = len as u32;
+        let mut gen_u32 = || {
+            random ^= random << 13;
+            random ^= random >> 17;
+            random ^= random << 5;
+            random
+        };
+        let mut gen_usize = || {
+            if mem::size_of::<usize>() <= 4 {
+                gen_u32() as usize
+            } else {
+                ((u64::from(gen_u32()) << 32) | u64::from(gen_u32())) as usize
+            }
+        };
+
+        // Take random numbers modulo this number.
+        // The number fits into `usize` because `len` is not greater than `isize::MAX`.
+        let modulus = len.next_power_of_two();
+
+        // Some pivot candidates will be in the nearby of this index. Let's randomize them.
+        let pos = len / 4 * 2;
+
+        for i in 0..3 {
+            // Generate a random number modulo `len`. However, in order to avoid costly operations
+            // we first take it modulo a power of two, and then decrease by `len` until it fits
+            // into the range `[0, len - 1]`.
+            let mut other = gen_usize() & (modulus - 1);
+
+            // `other` is guaranteed to be less than `2 * len`.
+            if other >= len {
+                other -= len;
+            }
+
+            v.swap(pos - 1 + i, other);
+        }
+    }
+}
+
+/// Chooses a pivot in `v` and returns the index and `true` if the slice is likely already sorted.
+///
+/// Elements in `v` might be reordered in the process.
+fn choose_pivot<T, F>(v: &mut [T], is_less: &F) -> (usize, bool)
+where
+    F: Fn(&T, &T) -> bool,
+{
+    // Minimum length to choose the median-of-medians method.
+    // Shorter slices use the simple median-of-three method.
+    const SHORTEST_MEDIAN_OF_MEDIANS: usize = 50;
+    // Maximum number of swaps that can be performed in this function.
+    const MAX_SWAPS: usize = 4 * 3;
+
+    let len = v.len();
+
+    // Three indices near which we are going to choose a pivot.
+    let mut a = len / 4 * 1;
+    let mut b = len / 4 * 2;
+    let mut c = len / 4 * 3;
+
+    // Counts the total number of swaps we are about to perform while sorting indices.
+    let mut swaps = 0;
+
+    if len >= 8 {
+        // Swaps indices so that `v[a] <= v[b]`.
+        let mut sort2 = |a: &mut usize, b: &mut usize| unsafe {
+            if is_less(v.get_unchecked(*b), v.get_unchecked(*a)) {
+                ptr::swap(a, b);
+                swaps += 1;
+            }
+        };
+
+        // Swaps indices so that `v[a] <= v[b] <= v[c]`.
+        let mut sort3 = |a: &mut usize, b: &mut usize, c: &mut usize| {
+            sort2(a, b);
+            sort2(b, c);
+            sort2(a, b);
+        };
+
+        if len >= SHORTEST_MEDIAN_OF_MEDIANS {
+            // Finds the median of `v[a - 1], v[a], v[a + 1]` and stores the index into `a`.
+            let mut sort_adjacent = |a: &mut usize| {
+                let tmp = *a;
+                sort3(&mut (tmp - 1), a, &mut (tmp + 1));
+            };
+
+            // Find medians in the neighborhoods of `a`, `b`, and `c`.
+            sort_adjacent(&mut a);
+            sort_adjacent(&mut b);
+            sort_adjacent(&mut c);
+        }
+
+        // Find the median among `a`, `b`, and `c`.
+        sort3(&mut a, &mut b, &mut c);
+    }
+
+    if swaps < MAX_SWAPS {
+        (b, swaps == 0)
+    } else {
+        // The maximum number of swaps was performed. Chances are the slice is descending or mostly
+        // descending, so reversing will probably help sort it faster.
+        v.reverse();
+        (len - 1 - b, true)
+    }
+}
+
+/// Sorts `v` recursively.
+///
+/// If the slice had a predecessor in the original array, it is specified as `pred`.
+///
+/// `limit` is the number of allowed imbalanced partitions before switching to `heapsort`. If zero,
+/// this function will immediately switch to heapsort.
+fn recurse<'a, T, F>(mut v: &'a mut [T], is_less: &F, mut pred: Option<&'a mut T>, mut limit: usize)
+where
+    T: Send,
+    F: Fn(&T, &T) -> bool + Sync,
+{
+    // Slices of up to this length get sorted using insertion sort.
+    const MAX_INSERTION: usize = 20;
+    // If both partitions are up to this length, we continue sequentially. This number is as small
+    // as possible but so that the overhead of Rayon's task scheduling is still negligible.
+    const MAX_SEQUENTIAL: usize = 2000;
+
+    // True if the last partitioning was reasonably balanced.
+    let mut was_balanced = true;
+    // True if the last partitioning didn't shuffle elements (the slice was already partitioned).
+    let mut was_partitioned = true;
+
+    loop {
+        let len = v.len();
+
+        // Very short slices get sorted using insertion sort.
+        if len <= MAX_INSERTION {
+            insertion_sort(v, is_less);
+            return;
+        }
+
+        // If too many bad pivot choices were made, simply fall back to heapsort in order to
+        // guarantee `O(n log n)` worst-case.
+        if limit == 0 {
+            heapsort(v, is_less);
+            return;
+        }
+
+        // If the last partitioning was imbalanced, try breaking patterns in the slice by shuffling
+        // some elements around. Hopefully we'll choose a better pivot this time.
+        if !was_balanced {
+            break_patterns(v);
+            limit -= 1;
+        }
+
+        // Choose a pivot and try guessing whether the slice is already sorted.
+        let (pivot, likely_sorted) = choose_pivot(v, is_less);
+
+        // If the last partitioning was decently balanced and didn't shuffle elements, and if pivot
+        // selection predicts the slice is likely already sorted...
+        if was_balanced && was_partitioned && likely_sorted {
+            // Try identifying several out-of-order elements and shifting them to correct
+            // positions. If the slice ends up being completely sorted, we're done.
+            if partial_insertion_sort(v, is_less) {
+                return;
+            }
+        }
+
+        // If the chosen pivot is equal to the predecessor, then it's the smallest element in the
+        // slice. Partition the slice into elements equal to and elements greater than the pivot.
+        // This case is usually hit when the slice contains many duplicate elements.
+        if let Some(ref p) = pred {
+            if !is_less(p, &v[pivot]) {
+                let mid = partition_equal(v, pivot, is_less);
+
+                // Continue sorting elements greater than the pivot.
+                v = &mut { v }[mid..];
+                continue;
+            }
+        }
+
+        // Partition the slice.
+        let (mid, was_p) = partition(v, pivot, is_less);
+        was_balanced = cmp::min(mid, len - mid) >= len / 8;
+        was_partitioned = was_p;
+
+        // Split the slice into `left`, `pivot`, and `right`.
+        let (left, right) = { v }.split_at_mut(mid);
+        let (pivot, right) = right.split_at_mut(1);
+        let pivot = &mut pivot[0];
+
+        if cmp::max(left.len(), right.len()) <= MAX_SEQUENTIAL {
+            // Recurse into the shorter side only in order to minimize the total number of recursive
+            // calls and consume less stack space. Then just continue with the longer side (this is
+            // akin to tail recursion).
+            if left.len() < right.len() {
+                recurse(left, is_less, pred, limit);
+                v = right;
+                pred = Some(pivot);
+            } else {
+                recurse(right, is_less, Some(pivot), limit);
+                v = left;
+            }
+        } else {
+            // Sort the left and right half in parallel.
+            rayon_core::join(
+                || recurse(left, is_less, pred, limit),
+                || recurse(right, is_less, Some(pivot), limit),
+            );
+            break;
+        }
+    }
+}
+
+/// Sorts `v` using pattern-defeating quicksort in parallel.
+///
+/// The algorithm is unstable, in-place, and `O(n log n)` worst-case.
+pub(super) fn par_quicksort<T, F>(v: &mut [T], is_less: F)
+where
+    T: Send,
+    F: Fn(&T, &T) -> bool + Sync,
+{
+    // Sorting has no meaningful behavior on zero-sized types.
+    if mem::size_of::<T>() == 0 {
+        return;
+    }
+
+    // Limit the number of imbalanced partitions to `floor(log2(len)) + 1`.
+    let limit = mem::size_of::<usize>() * 8 - v.len().leading_zeros() as usize;
+
+    recurse(v, &is_less, None, limit);
+}
+
+#[cfg(test)]
+mod tests {
+    use super::heapsort;
+    use rand::distributions::Uniform;
+    use rand::{thread_rng, Rng};
+
+    #[test]
+    fn test_heapsort() {
+        let rng = thread_rng();
+
+        for len in (0..25).chain(500..501) {
+            for &modulus in &[5, 10, 100] {
+                let dist = Uniform::new(0, modulus);
+                for _ in 0..100 {
+                    let v: Vec<i32> = rng.sample_iter(&dist).take(len).collect();
+
+                    // Test heapsort using `<` operator.
+                    let mut tmp = v.clone();
+                    heapsort(&mut tmp, &|a, b| a < b);
+                    assert!(tmp.windows(2).all(|w| w[0] <= w[1]));
+
+                    // Test heapsort using `>` operator.
+                    let mut tmp = v.clone();
+                    heapsort(&mut tmp, &|a, b| a > b);
+                    assert!(tmp.windows(2).all(|w| w[0] >= w[1]));
+                }
+            }
+        }
+
+        // Sort using a completely random comparison function.
+        // This will reorder the elements *somehow*, but won't panic.
+        let mut v: Vec<_> = (0..100).collect();
+        heapsort(&mut v, &|_, _| thread_rng().gen());
+        heapsort(&mut v, &|a, b| a < b);
+
+        for i in 0..v.len() {
+            assert_eq!(v[i], i);
+        }
+    }
+}
diff --git a/third_party/rust/rayon/src/slice/test.rs b/third_party/rust/rayon/src/slice/test.rs
new file mode 100644
index 0000000000..97de7d8ed3
--- /dev/null
+++ b/third_party/rust/rayon/src/slice/test.rs
@@ -0,0 +1,148 @@
+#![cfg(test)]
+
+use crate::prelude::*;
+use rand::distributions::Uniform;
+use rand::seq::SliceRandom;
+use rand::{thread_rng, Rng};
+use std::cmp::Ordering::{Equal, Greater, Less};
+
+macro_rules! sort {
+    ($f:ident, $name:ident) => {
+        #[test]
+        fn $name() {
+            let mut rng = thread_rng();
+
+            for len in (0..25).chain(500..501) {
+                for &modulus in &[5, 10, 100] {
+                    let dist = Uniform::new(0, modulus);
+                    for _ in 0..100 {
+                        let v: Vec<i32> = rng.sample_iter(&dist).take(len).collect();
+
+                        // Test sort using `<` operator.
+                        let mut tmp = v.clone();
+                        tmp.$f(|a, b| a.cmp(b));
+                        assert!(tmp.windows(2).all(|w| w[0] <= w[1]));
+
+                        // Test sort using `>` operator.
+                        let mut tmp = v.clone();
+                        tmp.$f(|a, b| b.cmp(a));
+                        assert!(tmp.windows(2).all(|w| w[0] >= w[1]));
+                    }
+                }
+            }
+
+            // Test sort with many duplicates.
+            for &len in &[1_000, 10_000, 100_000] {
+                for &modulus in &[5, 10, 100, 10_000] {
+                    let dist = Uniform::new(0, modulus);
+                    let mut v: Vec<i32> = rng.sample_iter(&dist).take(len).collect();
+
+                    v.$f(|a, b| a.cmp(b));
+                    assert!(v.windows(2).all(|w| w[0] <= w[1]));
+                }
+            }
+
+            // Test sort with many pre-sorted runs.
+            for &len in &[1_000, 10_000, 100_000] {
+                let len_dist = Uniform::new(0, len);
+                for &modulus in &[5, 10, 1000, 50_000] {
+                    let dist = Uniform::new(0, modulus);
+                    let mut v: Vec<i32> = rng.sample_iter(&dist).take(len).collect();
+
+                    v.sort();
+                    v.reverse();
+
+                    for _ in 0..5 {
+                        let a = rng.sample(&len_dist);
+                        let b = rng.sample(&len_dist);
+                        if a < b {
+                            v[a..b].reverse();
+                        } else {
+                            v.swap(a, b);
+                        }
+                    }
+
+                    v.$f(|a, b| a.cmp(b));
+                    assert!(v.windows(2).all(|w| w[0] <= w[1]));
+                }
+            }
+
+            // Sort using a completely random comparison function.
+            // This will reorder the elements *somehow*, but won't panic.
+            let mut v: Vec<_> = (0..100).collect();
+            v.$f(|_, _| *[Less, Equal, Greater].choose(&mut thread_rng()).unwrap());
+            v.$f(|a, b| a.cmp(b));
+            for i in 0..v.len() {
+                assert_eq!(v[i], i);
+            }
+
+            // Should not panic.
+            [0i32; 0].$f(|a, b| a.cmp(b));
+            [(); 10].$f(|a, b| a.cmp(b));
+            [(); 100].$f(|a, b| a.cmp(b));
+
+            let mut v = [0xDEAD_BEEFu64];
+            v.$f(|a, b| a.cmp(b));
+            assert!(v == [0xDEAD_BEEF]);
+        }
+    };
+}
+
+sort!(par_sort_by, test_par_sort);
+sort!(par_sort_unstable_by, test_par_sort_unstable);
+
+#[test]
+fn test_par_sort_stability() {
+    for len in (2..25).chain(500..510).chain(50_000..50_010) {
+        for _ in 0..10 {
+            let mut counts = [0; 10];
+
+            // Create a vector like [(6, 1), (5, 1), (6, 2), ...],
+            // where the first item of each tuple is random, but
+            // the second item represents which occurrence of that
+            // number this element is, i.e. the second elements
+            // will occur in sorted order.
+            let mut rng = thread_rng();
+            let mut v: Vec<_> = (0..len)
+                .map(|_| {
+                    let n: usize = rng.gen_range(0, 10);
+                    counts[n] += 1;
+                    (n, counts[n])
+                })
+                .collect();
+
+            // Only sort on the first element, so an unstable sort
+            // may mix up the counts.
+            v.par_sort_by(|&(a, _), &(b, _)| a.cmp(&b));
+
+            // This comparison includes the count (the second item
+            // of the tuple), so elements with equal first items
+            // will need to be ordered with increasing
+            // counts... i.e. exactly asserting that this sort is
+            // stable.
+            assert!(v.windows(2).all(|w| w[0] <= w[1]));
+        }
+    }
+}
+
+#[test]
+fn test_par_chunks_exact_remainder() {
+    let v: &[i32] = &[0, 1, 2, 3, 4];
+    let c = v.par_chunks_exact(2);
+    assert_eq!(c.remainder(), &[4]);
+    assert_eq!(c.len(), 2);
+}
+
+#[test]
+fn test_par_chunks_exact_mut_remainder() {
+    let v: &mut [i32] = &mut [0, 1, 2, 3, 4];
+    let mut c = v.par_chunks_exact_mut(2);
+    assert_eq!(c.remainder(), &[4]);
+    assert_eq!(c.len(), 2);
+    assert_eq!(c.into_remainder(), &[4]);
+
+    let mut c = v.par_chunks_exact_mut(2);
+    assert_eq!(c.take_remainder(), &[4]);
+    assert_eq!(c.take_remainder(), &[]);
+    assert_eq!(c.len(), 2);
+}