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fast random bool in C++
#include <algorithm>
#include <chrono>
#include <iostream>
#include <random>
#define LIKELY(x) __builtin_expect((x), 1)
#define UNLIKELY(x) __builtin_expect((x), 0)
#define NO_INLINE __attribute__((noinline))
// extremely fast random number generator that also produces very high quality random.
// see PractRand: http://pracrand.sourceforge.net/PractRand.txt
class sfc64 {
public:
using result_type = uint64_t;
static constexpr uint64_t(min)() { return 0; }
static constexpr uint64_t(max)() { return UINT64_C(-1); }
sfc64() : sfc64(std::random_device{}()) {}
explicit sfc64(uint64_t seed) : m_a(seed), m_b(seed), m_c(seed), m_counter(1) {
for (int i = 0; i < 12; ++i) {
operator()();
}
}
uint64_t operator()() noexcept {
auto const tmp = m_a + m_b + m_counter++;
m_a = m_b ^ (m_b >> right_shift);
m_b = m_c + (m_c << left_shift);
m_c = rotl(m_c, rotation) + tmp;
return tmp;
}
private:
template <typename T> T rotl(T const x, int k) { return (x << k) | (x >> (8 * sizeof(T) - k)); }
static constexpr int rotation = 24;
static constexpr int right_shift = 11;
static constexpr int left_shift = 3;
uint64_t m_a;
uint64_t m_b;
uint64_t m_c;
uint64_t m_counter;
};
// Probably the simplest correct implementation of random bool.
// Also one of the slowest variant.
class UniformDistribution {
public:
template <typename Rng> bool operator()(Rng &rng) {
return std::uniform_int_distribution<>{0, 1}(rng);
}
};
// bounded() is a highly optimized way to produce unbiased bounded random numbers.
// It's not really fast when just used for bool though.
class BoundedOperator {
public:
template <typename Rng> uint64_t bounded(Rng &rng, uint64_t boundExcluded) {
#ifdef __SIZEOF_INT128__
// fastest solution I could find
// 1.78746 ns/op total
using u128 = unsigned __int128;
u128 m = u128(std::uniform_int_distribution<uint64_t>{}(rng)) * u128(boundExcluded);
uint64_t l = (uint64_t)m;
if (l < boundExcluded) {
uint64_t t = (0 - boundExcluded) % boundExcluded;
while (l < t) {
m = u128(rng()) * u128(boundExcluded);
l = (uint64_t)m;
}
}
return m >> 64;
#else
// java's method usually needs only 1 modulus, faster than OpenBSD's method or pcg's.
// also faster than std::shuffle's method. 9.73759 ns/op total
// 7.02644 ns/op for std::random_shuffle which uses this.
uint64_t x, r;
do {
x = rng();
r = x % boundExcluded;
} while (x - r > (0 - boundExcluded));
return r;
#endif
}
template <typename Rng> bool operator()(Rng &rng) { return bounded(rng, 2); }
};
// Unbiased, but very slow. bernoulli_distribution is too generic for this.
class BernoulliDistribution {
public:
template <typename Rng> bool operator()(Rng &rng) { return m_dist(rng); }
private:
std::bernoulli_distribution m_dist;
};
// Biased if the rng does not give random numbers in [0, 2^x].
class BinaryAnd {
public:
template <typename Rng> bool operator()(Rng &rng) { return rng() & 1; }
};
// unbiased
template <typename U = uint64_t> class BinaryAndUnbiased {
public:
template <typename Rng> bool operator()(Rng &rng) {
return (std::uniform_int_distribution<U>{}(rng)) & 1;
}
};
// Unbiased & quite fast but requires 16byte on 64bit platforms.
template <typename U = uint64_t> class RandomizerWithCounterT {
public:
template <typename Rng> bool operator()(Rng &rng) {
if (UNLIKELY(0 == m_counter)) {
m_rand = std::uniform_int_distribution<U>{}(rng);
m_counter = sizeof(m_rand) * 8;
}
return (m_rand >> --m_counter) & 1;
}
private:
U m_rand = 0;
int m_counter = 0;
};
// Unbiased & quite fast but requires 16byte on 64bit platforms.
template <typename U = uint64_t> class RandomizerWithCounter2 {
public:
template <typename Rng> bool operator()(Rng &rng) {
auto b = m_counter & s_mask;
if (UNLIKELY(0 == b)) {
m_rand = std::uniform_int_distribution<U>{}(rng);
}
++m_counter;
return (m_rand >> b) & 1;
}
private:
static constexpr U s_mask = sizeof(U) * 8 - 1;
U m_rand = 0;
uint_fast8_t m_counter = 0;
};
// Unbiased, fastest variant. Gets rid of the counter by sacrificing 1 bit of randomness.
// UNLIKELY macro seems important for clang++.
template <typename U = uint64_t> class RandomizerWithShiftT {
public:
template <typename Rng> bool operator()(Rng &rng) {
if (UNLIKELY(1 == m_rand)) {
m_rand = std::uniform_int_distribution<U>{}(rng) | s_mask_left1;
}
bool const ret = m_rand & 1;
m_rand >>= 1;
return ret;
}
private:
static constexpr const U s_mask_left1 = U(1) << (sizeof(U) * 8 - 1);
U m_rand = 1;
};
template <typename U = size_t> class RandomizerWithShiftMaxSize {
public:
template <typename Rng> bool operator()(Rng &rng) {
if (UNLIKELY(1 == m_rand)) {
m_rand = std::uniform_int_distribution<U>{0, s_mask_left1 - 1}(rng) | s_mask_left1;
}
bool const ret = m_rand & 1;
m_rand >>= 1;
return ret;
}
private:
static constexpr const U s_mask_left1 = U(1) << (sizeof(U) * 8 - 1);
U m_rand = 1;
};
template <typename U = uint64_t> class RandomizerWithShiftTNoLikely {
public:
template <typename Rng> bool operator()(Rng &rng) {
if (1 == m_rand) {
m_rand = std::uniform_int_distribution<U>{}(rng) | (U(1) << (sizeof(U) * 8 - 1));
}
bool const ret = m_rand & 1;
m_rand >>= 1;
return ret;
}
private:
U m_rand = 1;
};
// fastest variant for 4x unrolled loop
template <typename U = uint64_t> class RandomizerWithCounterShiftT {
public:
template <typename Rng> bool operator()(Rng &rng) {
if (UNLIKELY(0 == m_counter)) {
m_rand = std::uniform_int_distribution<U>{}(rng);
m_counter = sizeof(U) * 8;
}
--m_counter;
bool ret = m_rand & 1;
m_rand >>= 1;
return ret;
}
private:
U m_rand;
int m_counter = 0;
};
template <typename U> class RandomizerWithMaskShift {
public:
template <typename Rng> bool operator()(Rng &rng) {
if (UNLIKELY(0 == m_mask)) {
m_rand = std::uniform_int_distribution<U>{}(rng);
m_mask = 1;
}
bool ret = m_rand & m_mask;
m_mask <<= 1;
return ret;
}
private:
U m_rand;
U m_mask = 0;
};
template <typename U> class RandomizerWithRotl {
public:
template <typename Rng> bool operator()(Rng &rng) {
if (UNLIKELY(1 == m_mask)) {
m_rand = std::uniform_int_distribution<U>{}(rng);
}
m_mask = rotl(m_mask, 1);
return m_rand & m_mask;
}
private:
U m_rand;
U m_mask = 1;
};
template <typename B, typename Rng>
NO_INLINE void benchU4(size_t iters, const char *rng_name, const char *method_name) {
size_t loops = iters / 4;
size_t s = 0;
std::vector<double> times;
for (size_t i = 0; i < 7; ++i) {
Rng rng{123};
B b;
auto t_start = std::chrono::high_resolution_clock::now();
for (size_t t = 0; t < loops; ++t) {
if (b(rng)) {
++s;
}
if (b(rng)) {
++s;
}
if (b(rng)) {
++s;
}
if (b(rng)) {
++s;
}
}
auto t_end = std::chrono::high_resolution_clock::now();
auto t_sec = std::chrono::duration<double>(t_end - t_start).count();
times.push_back(t_sec / iters * 1e9);
}
std::sort(times.begin(), times.end());
for (auto t : times) {
std::cout << t << "; ";
}
std::cout << sizeof(B) << "; \"" << method_name << "\"; \"" << rng_name << "\"; 4; " << s
<< std::endl;
}
template <typename B, typename Rng>
NO_INLINE void benchU1(size_t iters, const char *rng_name, const char *method_name) {
size_t s = 0;
std::vector<double> times;
for (size_t i = 0; i < 7; ++i) {
Rng rng{123};
B b;
auto t_start = std::chrono::high_resolution_clock::now();
for (size_t t = 0; t < iters; ++t) {
if (b(rng)) {
++s;
}
}
auto t_end = std::chrono::high_resolution_clock::now();
auto t_sec = std::chrono::duration<double>(t_end - t_start).count();
times.push_back(t_sec / iters * 1e9);
}
std::sort(times.begin(), times.end());
for (auto t : times) {
std::cout << t << "; ";
}
std::cout << sizeof(B) << "; \"" << method_name << "\"; \"" << rng_name << "\"; 1; " << s
<< std::endl;
}
template <typename Rng> void bench(size_t iters, const char *rng_name) {
benchU1<RandomizerWithCounterT<uint64_t>, Rng>(iters, rng_name,
"RandomizerWithCounterT<uint64_t>");
benchU4<RandomizerWithCounterT<uint64_t>, Rng>(iters, rng_name,
"RandomizerWithCounterT<uint64_t>");
benchU1<BinaryAndUnbiased<uint64_t>, Rng>(iters, rng_name, "BinaryAndUnbiased<uint64_t>");
benchU4<BinaryAndUnbiased<uint64_t>, Rng>(iters, rng_name, "BinaryAndUnbiased<uint64_t>");
benchU1<RandomizerWithShiftT<uint64_t>, Rng>(iters, rng_name, "RandomizerWithShiftT<uint64_t>");
benchU4<RandomizerWithShiftT<uint64_t>, Rng>(iters, rng_name, "RandomizerWithShiftT<uint64_t>");
benchU1<RandomizerWithShiftMaxSize<uint64_t>, Rng>(iters, rng_name,
"RandomizerWithShiftMaxSize<uint64_t>");
benchU4<RandomizerWithShiftMaxSize<uint64_t>, Rng>(iters, rng_name,
"RandomizerWithShiftMaxSize<uint64_t>");
benchU1<RandomizerWithMaskShift<uint64_t>, Rng>(iters, rng_name,
"RandomizerWithMaskShift<uint64_t>");
benchU4<RandomizerWithMaskShift<uint64_t>, Rng>(iters, rng_name,
"RandomizerWithMaskShift<uint64_t>");
benchU1<RandomizerWithRotl<uint64_t>, Rng>(iters, rng_name, "RandomizerWithRotl<uint64_t>");
benchU4<RandomizerWithRotl<uint64_t>, Rng>(iters, rng_name, "RandomizerWithRotl<uint64_t>");
benchU1<RandomizerWithCounter2<uint64_t>, Rng>(iters, rng_name,
"RandomizerWithCounter2<uint64_t>");
benchU4<RandomizerWithCounter2<uint64_t>, Rng>(iters, rng_name,
"RandomizerWithCounter2<uint64_t>");
benchU1<RandomizerWithShiftTNoLikely<uint64_t>, Rng>(iters, rng_name,
"RandomizerWithShiftTNoLikely<uint64_t>");
benchU4<RandomizerWithShiftTNoLikely<uint64_t>, Rng>(iters, rng_name,
"RandomizerWithShiftTNoLikely<uint64_t>");
benchU1<RandomizerWithCounterShiftT<uint64_t>, Rng>(iters, rng_name,
"RandomizerWithCounterShiftT<uint64_t>");
benchU4<RandomizerWithCounterShiftT<uint64_t>, Rng>(iters, rng_name,
"RandomizerWithCounterShiftT<uint64_t>");
benchU1<BinaryAnd, Rng>(iters, rng_name, "BinaryAnd");
benchU4<BinaryAnd, Rng>(iters, rng_name, "BinaryAnd");
benchU1<BoundedOperator, Rng>(iters, rng_name, "BoundedOperator");
benchU4<BoundedOperator, Rng>(iters, rng_name, "BoundedOperator");
benchU1<BernoulliDistribution, Rng>(iters, rng_name, "BernoulliDistribution");
benchU4<BernoulliDistribution, Rng>(iters, rng_name, "BernoulliDistribution");
benchU1<UniformDistribution, Rng>(iters, rng_name, "UniformDistribution");
benchU4<UniformDistribution, Rng>(iters, rng_name, "UniformDistribution");
}
int main(int, char **) {
size_t iters = UINT64_C(1'000'000'000);
bench<sfc64>(iters, "sfc64");
bench<std::mt19937>(iters, "std::mt19937");
bench<std::mt19937_64>(iters, "std::mt19937_64");
}
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