//! 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::marker::PhantomData; use std::mem::{self, MaybeUninit}; use std::ptr;
/// When dropped, copies from `src` into `dest`. #[must_use] struct CopyOnDrop<'a, T> {
src: *const T,
dest: *mut T, /// `src` is often a local pointer here, make sure we have appropriate /// PhantomData so that dropck can protect us.
marker: PhantomData<&'a mut T>,
}
impl<'a, T> CopyOnDrop<'a, T> { /// Construct from a source pointer and a destination /// Assumes dest lives longer than src, since there is no easy way to /// copy down lifetime information from another pointer unsafefn new(src: &'a T, dest: *mut T) -> Self {
CopyOnDrop {
src,
dest,
marker: PhantomData,
}
}
}
impl<T> Drop for CopyOnDrop<'_, T> { fn drop(&mutself) { // SAFETY: This is a helper class. // Please refer to its usage for correctness. // Namely, one must be sure that `src` and `dst` does not overlap as required by `ptr::copy_nonoverlapping`. 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(); // SAFETY: The unsafe operations below involves indexing without a bounds check (by offsetting a // pointer) and copying memory (`ptr::copy_nonoverlapping`). // // a. Indexing: // 1. We checked the size of the array to >=2. // 2. All the indexing that we will do is always between {0 <= index < len} at most. // // b. Memory copying // 1. We are obtaining pointers to references which are guaranteed to be valid. // 2. They cannot overlap because we obtain pointers to difference indices of the slice. // Namely, `i` and `i-1`. // 3. If the slice is properly aligned, the elements are properly aligned. // It is the caller's responsibility to make sure the slice is properly aligned. // // See comments below for further detail. 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 tmp = mem::ManuallyDrop::new(ptr::read(v.get_unchecked(0))); let v = v.as_mut_ptr(); letmut hole = CopyOnDrop::new(&*tmp, v.add(1));
ptr::copy_nonoverlapping(v.add(1), v.add(0), 1);
for i in2..len { if !is_less(&*v.add(i), &*tmp) { break;
}
// Move `i`-th element one place to the left, thus shifting the hole to the right.
ptr::copy_nonoverlapping(v.add(i), v.add(i - 1), 1);
hole.dest = v.add(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(); // SAFETY: The unsafe operations below involves indexing without a bound check (by offsetting a // pointer) and copying memory (`ptr::copy_nonoverlapping`). // // a. Indexing: // 1. We checked the size of the array to >= 2. // 2. All the indexing that we will do is always between `0 <= index < len-1` at most. // // b. Memory copying // 1. We are obtaining pointers to references which are guaranteed to be valid. // 2. They cannot overlap because we obtain pointers to difference indices of the slice. // Namely, `i` and `i+1`. // 3. If the slice is properly aligned, the elements are properly aligned. // It is the caller's responsibility to make sure the slice is properly aligned. // // See comments below for further detail. 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 tmp = mem::ManuallyDrop::new(ptr::read(v.get_unchecked(len - 1))); let v = v.as_mut_ptr(); letmut hole = CopyOnDrop::new(&*tmp, v.add(len - 2));
ptr::copy_nonoverlapping(v.add(len - 2), v.add(len - 1), 1);
for i in (0..len - 2).rev() { if !is_less(&*tmp, &*v.add(i)) { break;
}
// Move `i`-th element one place to the right, thus shifting the hole to the left.
ptr::copy_nonoverlapping(v.add(i), v.add(i + 1), 1);
hole.dest = v.add(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(); letmut i = 1;
for _ in0..MAX_STEPS { // SAFETY: We already explicitly did the bound checking with `i < len`. // All our subsequent indexing is only in the range `0 <= index < len` 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 { returntrue;
}
// Don't shift elements on short arrays, that has a performance cost. if len < SHORTEST_SHIFTING { returnfalse;
}
// 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 in1..v.len() {
shift_tail(&mut v[..i + 1], 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`. letmut child = 2 * node + 1; if child >= v.len() { break;
}
// Stop if the invariant holds at `node`. if !is_less(&v[node], &v[child]) { break;
}
// Swap `node` with the greater child, move one step down, and continue sifting.
v.swap(node, child);
node = child;
}
};
// 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]: https://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.add(block_l)`). letmut l = v.as_mut_ptr(); letmut block_l = BLOCK; letmut start_l = ptr::null_mut(); letmut end_l = ptr::null_mut(); letmut offsets_l = [MaybeUninit::<u8>::uninit(); BLOCK];
// The current block on the right side (from `r.sub(block_r)` to `r`). // SAFETY: The documentation for .add() specifically mention that `vec.as_ptr().add(vec.len())` is always safe` letmut r = unsafe { l.add(v.len()) }; letmut block_r = BLOCK; letmut start_r = ptr::null_mut(); letmut end_r = ptr::null_mut(); letmut offsets_r = [MaybeUninit::<u8>::uninit(); BLOCK];
// FIXME: When we get VLAs, try creating one array of length `min(v.len(), 2 * BLOCK)` rather // than two fixed-size arrays of length `BLOCK`. VLAs might be more cache-efficient.
// 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); // FIXME: this should *likely* use `offset_from`, but more // investigation is needed (including running tests in miri). // TODO unstable: (r.addr() - l.addr()) / mem::size_of::<T>()
(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). letmut 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;
} elseif start_r < end_r {
block_l = rem;
} else { // There were the same number of elements to switch on both blocks during the last // iteration, so there are no remaining elements on either block. Cover the remaining // items with roughly equally-sized blocks.
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. // TODO unstable: start_l = MaybeUninit::slice_as_mut_ptr(&mut offsets_l);
start_l = offsets_l.as_mut_ptr() as *mut u8;
end_l = start_l; letmut elem = l;
for i in0..block_l { // SAFETY: The unsafety operations below involve the usage of the `offset`. // According to the conditions required by the function, we satisfy them because: // 1. `offsets_l` is stack-allocated, and thus considered separate allocated object. // 2. The function `is_less` returns a `bool`. // Casting a `bool` will never overflow `isize`. // 3. We have guaranteed that `block_l` will be `<= BLOCK`. // Plus, `end_l` was initially set to the begin pointer of `offsets_` which was declared on the stack. // Thus, we know that even in the worst case (all invocations of `is_less` returns false) we will only be at most 1 byte pass the end. // Another unsafety operation here is dereferencing `elem`. // However, `elem` was initially the begin pointer to the slice which is always valid. 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. // TODO unstable: start_r = MaybeUninit::slice_as_mut_ptr(&mut offsets_r);
start_r = offsets_r.as_mut_ptr() as *mut u8;
end_r = start_r; letmut elem = r;
for i in0..block_r { // SAFETY: The unsafety operations below involve the usage of the `offset`. // According to the conditions required by the function, we satisfy them because: // 1. `offsets_r` is stack-allocated, and thus considered separate allocated object. // 2. The function `is_less` returns a `bool`. // Casting a `bool` will never overflow `isize`. // 3. We have guaranteed that `block_r` will be `<= BLOCK`. // Plus, `end_r` was initially set to the begin pointer of `offsets_` which was declared on the stack. // Thus, we know that even in the worst case (all invocations of `is_less` returns true) we will only be at most 1 byte pass the end. // Another unsafety operation here is dereferencing `elem`. // However, `elem` was initially `1 * sizeof(T)` past the end and we decrement it by `1 * sizeof(T)` before accessing it. // Plus, `block_r` was asserted to be less than `BLOCK` and `elem` will therefore at most be pointing to the beginning of the slice. 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 = Ord::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.
// SAFETY: The use of `ptr::read` is valid because there is at least one element in // both `offsets_l` and `offsets_r`, so `left!` is a valid pointer to read from. // // The uses of `left!` involve calls to `offset` on `l`, which points to the // beginning of `v`. All the offsets pointed-to by `start_l` are at most `block_l`, so // these `offset` calls are safe as all reads are within the block. The same argument // applies for the uses of `right!`. // // The calls to `start_l.offset` are valid because there are at most `count-1` of them, // plus the final one at the end of the unsafe block, where `count` is the minimum number // of collected offsets in `offsets_l` and `offsets_r`, so there is no risk of there not // being enough elements. The same reasoning applies to the calls to `start_r.offset`. // // The calls to `copy_nonoverlapping` are safe because `left!` and `right!` are guaranteed // not to overlap, and are valid because of the reasoning above. unsafe { let tmp = ptr::read(left!());
ptr::copy_nonoverlapping(right!(), left!(), 1);
if start_l == end_l { // All out-of-order elements in the left block were moved. Move to the next block.
// block-width-guarantee // SAFETY: if `!is_done` then the slice width is guaranteed to be at least `2*BLOCK` wide. There // are at most `BLOCK` elements in `offsets_l` because of its size, so the `offset` operation is // safe. Otherwise, the debug assertions in the `is_done` case guarantee that // `width(l, r) == block_l + block_r`, namely, that the block sizes have been adjusted to account // for the smaller number of remaining elements.
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.
// SAFETY: Same argument as [block-width-guarantee]. Either this is a full block `2*BLOCK`-wide, // or `block_r` has been adjusted for the last handful of elements.
r = unsafe { r.offset(-(block_r as isize)) };
}
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 its remaining out-of-order elements to the far right.
debug_assert_eq!(width(l, r), block_l); while start_l < end_l { // remaining-elements-safety // SAFETY: while the loop condition holds there are still elements in `offsets_l`, so it // is safe to point `end_l` to the previous element. // // The `ptr::swap` is safe if both its arguments are valid for reads and writes: // - Per the debug assert above, the distance between `l` and `r` is `block_l` // elements, so there can be at most `block_l` remaining offsets between `start_l` // and `end_l`. This means `r` will be moved at most `block_l` steps back, which // makes the `r.offset` calls valid (at that point `l == r`). // - `offsets_l` contains valid offsets into `v` collected during the partitioning of // the last block, so the `l.offset` calls are valid. 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)
} elseif start_r < end_r { // The right block remains. // Move its remaining out-of-order elements to the far left.
debug_assert_eq!(width(l, r), block_r); while start_r < end_r { // SAFETY: See the reasoning in [remaining-elements-safety]. 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.
// SAFETY: `pivot` is a reference to the first element of `v`, so `ptr::read` is safe. let tmp = mem::ManuallyDrop::new(unsafe { ptr::read(pivot) }); let _pivot_guard = unsafe { CopyOnDrop::new(&*tmp, pivot) }; let pivot = &*tmp;
// Find the first pair of out-of-order elements. letmut l = 0; letmut r = v.len();
// SAFETY: The unsafety below involves indexing an array. // For the first one: We already do the bounds checking here with `l < r`. // For the second one: We initially have `l == 0` and `r == v.len()` and we checked that `l < r` at every indexing operation. // From here we know that `r` must be at least `r == l` which was shown to be valid from the first one. unsafe { // Find the first element greater than 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,
)
// `_pivot_guard` 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. // SAFETY: The pointer here is valid because it is obtained from a reference to a slice. let tmp = mem::ManuallyDrop::new(unsafe { ptr::read(pivot) }); let _pivot_guard = unsafe { CopyOnDrop::new(&*tmp, pivot) }; let pivot = &*tmp;
// Now partition the slice. letmut l = 0; letmut r = v.len(); loop { // SAFETY: The unsafety below involves indexing an array. // For the first one: We already do the bounds checking here with `l < r`. // For the second one: We initially have `l == 0` and `r == v.len()` and we checked that `l < r` at every indexing operation. // From here we know that `r` must be at least `r == l` which was shown to be valid from the first one. unsafe { // Find the first element greater than 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; let ptr = v.as_mut_ptr();
ptr::swap(ptr.add(l), ptr.add(r));
l += 1;
}
}
// We found `l` elements equal to the pivot. Add 1 to account for the pivot itself.
l + 1
// `_pivot_guard` 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. letmut random = len as u32; letmut gen_u32 = || {
random ^= random << 13;
random ^= random >> 17;
random ^= random << 5;
random
}; letmut gen_usize = || { if usize::BITS <= 32 {
gen_u32() as usize
} else {
(((gen_u32() as u64) << 32) | (gen_u32() as u64)) 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 in0..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]`. letmut 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. #[allow(clippy::identity_op)] letmut a = len / 4 * 1; letmut b = len / 4 * 2; letmut c = len / 4 * 3;
// Counts the total number of swaps we are about to perform while sorting indices. letmut swaps = 0;
if len >= 8 { // Swaps indices so that `v[a] <= v[b]`. // SAFETY: `len >= 8` so there are at least two elements in the neighborhoods of // `a`, `b` and `c`. This means the three calls to `sort_adjacent` result in // corresponding calls to `sort3` with valid 3-item neighborhoods around each // pointer, which in turn means the calls to `sort2` are done with valid // references. Thus the `v.get_unchecked` calls are safe, as is the `ptr::swap` // call. letmut 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]`. letmut 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`. letmut 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: u32) 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. letmut was_balanced = true; // True if the last partitioning didn't shuffle elements (the slice was already partitioned). letmut 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. iflet 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 = Ord::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 Ord::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 = usize::BITS - v.len().leading_zeros();
recurse(v, &is_less, None, limit);
}
#[cfg(test)] mod tests { usesuper::heapsort; use rand::distributions::Uniform; use rand::{thread_rng, Rng};
#[test] fn test_heapsort() { let rng = &mut thread_rng();
for len in (0..25).chain(500..501) { for &modulus in &[5, 10, 100] { let dist = Uniform::new(0, modulus); for _ in0..100 { let v: Vec<i32> = rng.sample_iter(&dist).take(len).collect();
// Test heapsort using `<` operator. letmut tmp = v.clone();
heapsort(&mut tmp, &|a, b| a < b);
assert!(tmp.windows(2).all(|w| w[0] <= w[1]));
// Test heapsort using `>` operator. letmut 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. letmut v: Vec<_> = (0..100).collect();
heapsort(&mut v, &|_, _| thread_rng().gen());
heapsort(&mut v, &|a, b| a < b);
for (i, &entry) in v.iter().enumerate() {
assert_eq!(entry, i);
}
}
}
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