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//===-- Implementation header for qsort utilities ---------------*- C++ -*-===// | ||
// | ||
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. | ||
// See https://llvm.org/LICENSE.txt for license information. | ||
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception | ||
// | ||
//===----------------------------------------------------------------------===// | ||
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#ifndef LLVM_LIBC_SRC_STDLIB_QSORT_PIVOT_H | ||
#define LLVM_LIBC_SRC_STDLIB_QSORT_PIVOT_H | ||
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#include <stdint.h> | ||
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namespace LIBC_NAMESPACE_DECL { | ||
namespace internal { | ||
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// Recursively select a pseudomedian if above this threshold. | ||
constexpr size_t PSEUDO_MEDIAN_REC_THRESHOLD = 64; | ||
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// Selects a pivot from `array`. Algorithm taken from glidesort by Orson Peters. | ||
// | ||
// This chooses a pivot by sampling an adaptive amount of points, approximating | ||
// the quality of a median of sqrt(n) elements. | ||
template <typename A, typename F> | ||
size_t choose_pivot(const A &array, const F &is_less) { | ||
const size_t len = array.len(); | ||
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if (len < 8) { | ||
return 0; | ||
} | ||
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const size_t len_div_8 = len / 8; | ||
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const size_t a = 0; // [0, floor(n/8)) | ||
const size_t b = len_div_8 * 4; // [4*floor(n/8), 5*floor(n/8)) | ||
const size_t c = len_div_8 * 7; // [7*floor(n/8), 8*floor(n/8)) | ||
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if (len < PSEUDO_MEDIAN_REC_THRESHOLD) | ||
return median3(array, a, b, c, is_less); | ||
else | ||
return median3_rec(array, a, b, c, len_div_8, is_less); | ||
} | ||
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// Calculates an approximate median of 3 elements from sections a, b, c, or | ||
// recursively from an approximation of each, if they're large enough. By | ||
// dividing the size of each section by 8 when recursing we have logarithmic | ||
// recursion depth and overall sample from f(n) = 3*f(n/8) -> f(n) = | ||
// O(n^(log(3)/log(8))) ~= O(n^0.528) elements. | ||
template <typename A, typename F> | ||
size_t median3_rec(const A &array, size_t a, size_t b, size_t c, size_t n, | ||
const F &is_less) { | ||
if (n * 8 >= PSEUDO_MEDIAN_REC_THRESHOLD) { | ||
const size_t n8 = n / 8; | ||
a = median3_rec(array, a, a + (n8 * 4), a + (n8 * 7), n8, is_less); | ||
b = median3_rec(array, b, b + (n8 * 4), b + (n8 * 7), n8, is_less); | ||
c = median3_rec(array, c, c + (n8 * 4), c + (n8 * 7), n8, is_less); | ||
} | ||
return median3(array, a, b, c, is_less); | ||
} | ||
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/// Calculates the median of 3 elements. | ||
template <typename A, typename F> | ||
size_t median3(const A &array, size_t a, size_t b, size_t c, const F &is_less) { | ||
const void *a_ptr = array.get(a); | ||
const void *b_ptr = array.get(b); | ||
const void *c_ptr = array.get(c); | ||
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const bool x = is_less(a_ptr, b_ptr); | ||
const bool y = is_less(a_ptr, c_ptr); | ||
if (x == y) { | ||
// If x=y=0 then b, c <= a. In this case we want to return max(b, c). | ||
// If x=y=1 then a < b, c. In this case we want to return min(b, c). | ||
// By toggling the outcome of b < c using XOR x we get this behavior. | ||
const bool z = is_less(b_ptr, c_ptr); | ||
return z ^ x ? c : b; | ||
} else { | ||
// Either c <= a < b or b <= a < c, thus a is our median. | ||
return a; | ||
} | ||
} | ||
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} // namespace internal | ||
} // namespace LIBC_NAMESPACE_DECL | ||
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#endif // LLVM_LIBC_SRC_STDLIB_QSORT_PIVOT_H |
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