Auto merge of #129587 - Voultapher:opt-for-size-variants-of-sort-impls, r=cuviper

Add `optimize_for_size` variants for stable and unstable sort as well as select_nth_unstable

- Stable sort uses a simple merge-sort that re-uses the existing - rather gnarly - merge function.
- Unstable sort jumps directly to the branchless heapsort fallback.
- select_nth_unstable jumps directly to the median_of_medians fallback, which is augmented with a custom tiny smallsort and partition impl.

Some code is duplicated but de-duplication would bring it's own problems. For example `swap_if_less` is critical for performance, if the sorting networks don't inline it perf drops drastically, however `#[inline(always)]` is also a poor fit, if the provided comparison function is huge, it gives the compiler an out to only instantiate `swap_if_less` once and call it. Another aspect that would suffer when making `swap_if_less` pub, is having to cfg out dozens of functions in in smallsort module.

Part of https://github.com/rust-lang/rust/issues/125612

r​? `@Kobzol`
This commit is contained in:
bors 2024-09-24 18:48:08 +00:00
commit 363ae41883
8 changed files with 202 additions and 59 deletions

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@ -7,6 +7,7 @@
//! better performance than one would get using heapsort as fallback.
use crate::mem::{self, SizedTypeProperties};
#[cfg(not(feature = "optimize_for_size"))]
use crate::slice::sort::shared::pivot::choose_pivot;
use crate::slice::sort::shared::smallsort::insertion_sort_shift_left;
use crate::slice::sort::unstable::quicksort::partition;
@ -40,7 +41,13 @@ where
let min_idx = min_index(v, &mut is_less).unwrap();
v.swap(min_idx, index);
} else {
partition_at_index_loop(v, index, None, &mut is_less);
cfg_if! {
if #[cfg(feature = "optimize_for_size")] {
median_of_medians(v, &mut is_less, index);
} else {
partition_at_index_loop(v, index, None, &mut is_less);
}
}
}
let (left, right) = v.split_at_mut(index);
@ -53,6 +60,7 @@ where
// most once, it doesn't make sense to use something more sophisticated than insertion-sort.
const INSERTION_SORT_THRESHOLD: usize = 16;
#[cfg(not(feature = "optimize_for_size"))]
fn partition_at_index_loop<'a, T, F>(
mut v: &'a mut [T],
mut index: usize,
@ -169,6 +177,7 @@ fn median_of_medians<T, F: FnMut(&T, &T) -> bool>(mut v: &mut [T], is_less: &mut
if v.len() >= 2 {
insertion_sort_shift_left(v, 1, is_less);
}
return;
}

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@ -1,3 +1,5 @@
#![cfg_attr(feature = "optimize_for_size", allow(dead_code))]
use crate::marker::Freeze;
pub(crate) mod pivot;

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@ -378,7 +378,12 @@ where
/// Swap two values in the slice pointed to by `v_base` at the position `a_pos` and `b_pos` if the
/// value at position `b_pos` is less than the one at position `a_pos`.
pub unsafe fn swap_if_less<T, F>(v_base: *mut T, a_pos: usize, b_pos: usize, is_less: &mut F)
///
/// Purposefully not marked `#[inline]`, despite us wanting it to be inlined for integers like
/// types. `is_less` could be a huge function and we want to give the compiler an option to
/// not inline this function. For the same reasons that this function is very perf critical
/// it should be in the same module as the functions that use it.
unsafe fn swap_if_less<T, F>(v_base: *mut T, a_pos: usize, b_pos: usize, is_less: &mut F)
where
F: FnMut(&T, &T) -> bool,
{

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@ -1,15 +1,24 @@
//! This module contains the entry points for `slice::sort`.
#[cfg(not(feature = "optimize_for_size"))]
use crate::cmp;
use crate::intrinsics;
use crate::mem::{self, MaybeUninit, SizedTypeProperties};
#[cfg(not(feature = "optimize_for_size"))]
use crate::slice::sort::shared::smallsort::{
SMALL_SORT_GENERAL_SCRATCH_LEN, StableSmallSortTypeImpl, insertion_sort_shift_left,
};
use crate::{cmp, intrinsics};
pub(crate) mod drift;
pub(crate) mod merge;
#[cfg(not(feature = "optimize_for_size"))]
pub(crate) mod drift;
#[cfg(not(feature = "optimize_for_size"))]
pub(crate) mod quicksort;
#[cfg(feature = "optimize_for_size")]
pub(crate) mod tiny;
/// Stable sort called driftsort by Orson Peters and Lukas Bergdoll.
/// Design document:
/// <https://github.com/Voultapher/sort-research-rs/blob/main/writeup/driftsort_introduction/text.md>
@ -30,25 +39,53 @@ pub fn sort<T, F: FnMut(&T, &T) -> bool, BufT: BufGuard<T>>(v: &mut [T], is_less
return;
}
// More advanced sorting methods than insertion sort are faster if called in
// a hot loop for small inputs, but for general-purpose code the small
// binary size of insertion sort is more important. The instruction cache in
// modern processors is very valuable, and for a single sort call in general
// purpose code any gains from an advanced method are cancelled by i-cache
// misses during the sort, and thrashing the i-cache for surrounding code.
const MAX_LEN_ALWAYS_INSERTION_SORT: usize = 20;
if intrinsics::likely(len <= MAX_LEN_ALWAYS_INSERTION_SORT) {
insertion_sort_shift_left(v, 1, is_less);
return;
}
cfg_if! {
if #[cfg(any(feature = "optimize_for_size", target_pointer_width = "16"))] {
let alloc_len = len / 2;
driftsort_main::<T, F, BufT>(v, is_less);
cfg_if! {
if #[cfg(target_pointer_width = "16")] {
let heap_buf = BufT::with_capacity(alloc_len);
let scratch = heap_buf.as_uninit_slice_mut();
} else {
// For small inputs 4KiB of stack storage suffices, which allows us to avoid
// calling the (de-)allocator. Benchmarks showed this was quite beneficial.
let mut stack_buf = AlignedStorage::<T, 4096>::new();
let stack_scratch = stack_buf.as_uninit_slice_mut();
let mut heap_buf;
let scratch = if stack_scratch.len() >= alloc_len {
stack_scratch
} else {
heap_buf = BufT::with_capacity(alloc_len);
heap_buf.as_uninit_slice_mut()
};
}
}
tiny::mergesort(v, scratch, is_less);
} else {
// More advanced sorting methods than insertion sort are faster if called in
// a hot loop for small inputs, but for general-purpose code the small
// binary size of insertion sort is more important. The instruction cache in
// modern processors is very valuable, and for a single sort call in general
// purpose code any gains from an advanced method are cancelled by i-cache
// misses during the sort, and thrashing the i-cache for surrounding code.
const MAX_LEN_ALWAYS_INSERTION_SORT: usize = 20;
if intrinsics::likely(len <= MAX_LEN_ALWAYS_INSERTION_SORT) {
insertion_sort_shift_left(v, 1, is_less);
return;
}
driftsort_main::<T, F, BufT>(v, is_less);
}
}
}
/// See [`sort`]
///
/// Deliberately don't inline the main sorting routine entrypoint to ensure the
/// inlined insertion sort i-cache footprint remains minimal.
#[cfg(not(feature = "optimize_for_size"))]
#[inline(never)]
fn driftsort_main<T, F: FnMut(&T, &T) -> bool, BufT: BufGuard<T>>(v: &mut [T], is_less: &mut F) {
// By allocating n elements of memory we can ensure the entire input can

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@ -0,0 +1,41 @@
//! Binary-size optimized mergesort inspired by https://github.com/voultapher/tiny-sort-rs.
use crate::mem::MaybeUninit;
use crate::ptr;
use crate::slice::sort::stable::merge;
/// Tiny recursive top-down merge sort optimized for binary size. It has no adaptiveness whatsoever,
/// no run detection, etc.
#[inline(always)]
pub fn mergesort<T, F: FnMut(&T, &T) -> bool>(
v: &mut [T],
scratch: &mut [MaybeUninit<T>],
is_less: &mut F,
) {
let len = v.len();
if len > 2 {
let mid = len / 2;
// SAFETY: mid is in-bounds.
unsafe {
// Sort the left half recursively.
mergesort(v.get_unchecked_mut(..mid), scratch, is_less);
// Sort the right half recursively.
mergesort(v.get_unchecked_mut(mid..), scratch, is_less);
}
merge::merge(v, scratch, mid, is_less);
} else if len == 2 {
// SAFETY: We checked the len, the pointers we create are valid and don't overlap.
unsafe {
let v_base = v.as_mut_ptr();
let v_a = v_base;
let v_b = v_base.add(1);
if is_less(&*v_b, &*v_a) {
ptr::swap_nonoverlapping(v_a, v_b, 1);
}
}
}
}

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@ -1,46 +1,46 @@
//! This module contains a branchless heapsort as fallback for unstable quicksort.
use crate::{intrinsics, ptr};
use crate::{cmp, intrinsics, ptr};
/// Sorts `v` using heapsort, which guarantees *O*(*n* \* log(*n*)) worst-case.
///
/// Never inline this, it sits the main hot-loop in `recurse` and is meant as unlikely algorithmic
/// fallback.
///
/// SAFETY: The caller has to guarantee that `v.len()` >= 2.
#[inline(never)]
pub(crate) unsafe fn heapsort<T, F>(v: &mut [T], is_less: &mut F)
pub(crate) fn heapsort<T, F>(v: &mut [T], is_less: &mut F)
where
F: FnMut(&T, &T) -> bool,
{
// SAFETY: See function safety.
unsafe {
intrinsics::assume(v.len() >= 2);
let len = v.len();
// Build the heap in linear time.
for i in (0..v.len() / 2).rev() {
sift_down(v, i, is_less);
}
// Pop maximal elements from the heap.
for i in (1..v.len()).rev() {
for i in (0..len + len / 2).rev() {
let sift_idx = if i >= len {
i - len
} else {
v.swap(0, i);
sift_down(&mut v[..i], 0, is_less);
0
};
// SAFETY: The above calculation ensures that `sift_idx` is either 0 or
// `(len..(len + (len / 2))) - len`, which simplifies to `0..(len / 2)`.
// This guarantees the required `sift_idx <= len`.
unsafe {
sift_down(&mut v[..cmp::min(i, len)], sift_idx, is_less);
}
}
}
// This binary heap respects the invariant `parent >= child`.
//
// SAFETY: The caller has to guarantee that node < `v.len()`.
#[inline(never)]
// SAFETY: The caller has to guarantee that `node <= v.len()`.
#[inline(always)]
unsafe fn sift_down<T, F>(v: &mut [T], mut node: usize, is_less: &mut F)
where
F: FnMut(&T, &T) -> bool,
{
// SAFETY: See function safety.
unsafe {
intrinsics::assume(node < v.len());
intrinsics::assume(node <= v.len());
}
let len = v.len();
@ -69,9 +69,7 @@ where
break;
}
// Swap `node` with the greater child, move one step down, and continue sifting. This
// could be ptr::swap_nonoverlapping but that adds a significant amount of binary-size.
ptr::swap(v_base.add(node), v_base.add(child));
ptr::swap_nonoverlapping(v_base.add(node), v_base.add(child), 1);
}
node = child;

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@ -2,7 +2,9 @@
use crate::intrinsics;
use crate::mem::SizedTypeProperties;
#[cfg(not(feature = "optimize_for_size"))]
use crate::slice::sort::shared::find_existing_run;
#[cfg(not(feature = "optimize_for_size"))]
use crate::slice::sort::shared::smallsort::insertion_sort_shift_left;
pub(crate) mod heapsort;
@ -28,25 +30,32 @@ pub fn sort<T, F: FnMut(&T, &T) -> bool>(v: &mut [T], is_less: &mut F) {
return;
}
// More advanced sorting methods than insertion sort are faster if called in
// a hot loop for small inputs, but for general-purpose code the small
// binary size of insertion sort is more important. The instruction cache in
// modern processors is very valuable, and for a single sort call in general
// purpose code any gains from an advanced method are cancelled by i-cache
// misses during the sort, and thrashing the i-cache for surrounding code.
const MAX_LEN_ALWAYS_INSERTION_SORT: usize = 20;
if intrinsics::likely(len <= MAX_LEN_ALWAYS_INSERTION_SORT) {
insertion_sort_shift_left(v, 1, is_less);
return;
}
cfg_if! {
if #[cfg(any(feature = "optimize_for_size", target_pointer_width = "16"))] {
heapsort::heapsort(v, is_less);
} else {
// More advanced sorting methods than insertion sort are faster if called in
// a hot loop for small inputs, but for general-purpose code the small
// binary size of insertion sort is more important. The instruction cache in
// modern processors is very valuable, and for a single sort call in general
// purpose code any gains from an advanced method are cancelled by i-cache
// misses during the sort, and thrashing the i-cache for surrounding code.
const MAX_LEN_ALWAYS_INSERTION_SORT: usize = 20;
if intrinsics::likely(len <= MAX_LEN_ALWAYS_INSERTION_SORT) {
insertion_sort_shift_left(v, 1, is_less);
return;
}
ipnsort(v, is_less);
ipnsort(v, is_less);
}
}
}
/// See [`sort`]
///
/// Deliberately don't inline the main sorting routine entrypoint to ensure the
/// inlined insertion sort i-cache footprint remains minimal.
#[cfg(not(feature = "optimize_for_size"))]
#[inline(never)]
fn ipnsort<T, F>(v: &mut [T], is_less: &mut F)
where

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@ -1,8 +1,12 @@
//! This module contains an unstable quicksort and two partition implementations.
use crate::mem::{self, ManuallyDrop};
#[cfg(not(feature = "optimize_for_size"))]
use crate::slice::sort::shared::pivot::choose_pivot;
#[cfg(not(feature = "optimize_for_size"))]
use crate::slice::sort::shared::smallsort::UnstableSmallSortTypeImpl;
#[cfg(not(feature = "optimize_for_size"))]
use crate::slice::sort::unstable::heapsort;
use crate::{intrinsics, ptr};
/// Sorts `v` recursively.
@ -11,6 +15,7 @@ use crate::{intrinsics, ptr};
///
/// `limit` is the number of allowed imbalanced partitions before switching to `heapsort`. If zero,
/// this function will immediately switch to heapsort.
#[cfg(not(feature = "optimize_for_size"))]
pub(crate) fn quicksort<'a, T, F>(
mut v: &'a mut [T],
mut ancestor_pivot: Option<&'a T>,
@ -28,10 +33,7 @@ pub(crate) fn quicksort<'a, T, F>(
// If too many bad pivot choices were made, simply fall back to heapsort in order to
// guarantee `O(N x log(N))` worst-case.
if limit == 0 {
// SAFETY: We assume the `small_sort` threshold is at least 1.
unsafe {
crate::slice::sort::unstable::heapsort::heapsort(v, is_less);
}
heapsort::heapsort(v, is_less);
return;
}
@ -98,13 +100,15 @@ where
return 0;
}
// Allows for panic-free code-gen by proving this property to the compiler.
if pivot >= len {
intrinsics::abort();
}
// Place the pivot at the beginning of slice.
v.swap(0, pivot);
// SAFETY: We checked that `pivot` is in-bounds.
unsafe {
// Place the pivot at the beginning of slice.
v.swap_unchecked(0, pivot);
}
let (pivot, v_without_pivot) = v.split_at_mut(1);
// Assuming that Rust generates noalias LLVM IR we can be sure that a partition function
@ -118,8 +122,15 @@ where
// compile-time by only instantiating the code that is needed. Idea by Frank Steffahn.
let num_lt = (const { inst_partition::<T, F>() })(v_without_pivot, pivot, is_less);
// Place the pivot between the two partitions.
v.swap(0, num_lt);
if num_lt >= len {
intrinsics::abort();
}
// SAFETY: We checked that `num_lt` is in-bounds.
unsafe {
// Place the pivot between the two partitions.
v.swap_unchecked(0, num_lt);
}
num_lt
}
@ -129,7 +140,13 @@ const fn inst_partition<T, F: FnMut(&T, &T) -> bool>() -> fn(&mut [T], &T, &mut
if mem::size_of::<T>() <= MAX_BRANCHLESS_PARTITION_SIZE {
// Specialize for types that are relatively cheap to copy, where branchless optimizations
// have large leverage e.g. `u64` and `String`.
partition_lomuto_branchless_cyclic::<T, F>
cfg_if! {
if #[cfg(feature = "optimize_for_size")] {
partition_lomuto_branchless_simple::<T, F>
} else {
partition_lomuto_branchless_cyclic::<T, F>
}
}
} else {
partition_hoare_branchy_cyclic::<T, F>
}
@ -215,6 +232,7 @@ where
}
}
#[cfg(not(feature = "optimize_for_size"))]
struct PartitionState<T> {
// The current element that is being looked at, scans left to right through slice.
right: *mut T,
@ -225,6 +243,7 @@ struct PartitionState<T> {
gap: GapGuardRaw<T>,
}
#[cfg(not(feature = "optimize_for_size"))]
fn partition_lomuto_branchless_cyclic<T, F>(v: &mut [T], pivot: &T, is_less: &mut F) -> usize
where
F: FnMut(&T, &T) -> bool,
@ -316,6 +335,27 @@ where
}
}
#[cfg(feature = "optimize_for_size")]
fn partition_lomuto_branchless_simple<T, F: FnMut(&T, &T) -> bool>(
v: &mut [T],
pivot: &T,
is_less: &mut F,
) -> usize {
let mut left = 0;
for right in 0..v.len() {
// SAFETY: `left` can at max be incremented by 1 each loop iteration, which implies that
// left <= right and that both are in-bounds.
unsafe {
let right_is_lt = is_less(v.get_unchecked(right), pivot);
v.swap_unchecked(left, right);
left += right_is_lt as usize;
}
}
left
}
struct GapGuard<T> {
pos: *mut T,
value: ManuallyDrop<T>,
@ -333,11 +373,13 @@ impl<T> Drop for GapGuard<T> {
/// Ideally this wouldn't be needed and we could just use the regular GapGuard.
/// See comment in [`partition_lomuto_branchless_cyclic`].
#[cfg(not(feature = "optimize_for_size"))]
struct GapGuardRaw<T> {
pos: *mut T,
value: *mut T,
}
#[cfg(not(feature = "optimize_for_size"))]
impl<T> Drop for GapGuardRaw<T> {
fn drop(&mut self) {
// SAFETY: `self` MUST be constructed in a way that makes copying the gap value into