/* * Copyright Matt Borland 2025. * Distributed under the Boost Software License, Version 1.0. (See * accompanying file LICENSE_1_0.txt or copy at * http://www.boost.org/LICENSE_1_0.txt) * * This file copies and pastes the original code for comparison under the following license * * Written in 2019 by David Blackman and Sebastiano Vigna (vigna@acm.org) * * To the extent possible under law, the author has dedicated all copyright * and related and neighboring rights to this software to the public domain * worldwide. * * Permission to use, copy, modify, and/or distribute this software for any * purpose with or without fee is hereby granted. * * THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES * WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF * MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR * ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES * WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN * ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR * IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. */ #include #include #include #include using std::uint32_t; /* This is xoshiro128** 1.1, one of our 32-bit all-purpose, rock-solid generators. It has excellent speed, a state size (128 bits) that is large enough for mild parallelism, and it passes all tests we are aware of. Note that version 1.0 had mistakenly s[0] instead of s[1] as state word passed to the scrambler. For generating just single-precision (i.e., 32-bit) floating-point numbers, xoshiro128+ is even faster. The state must be seeded so that it is not everywhere zero. */ static inline uint32_t rotl(const uint32_t x, int k) { return (x << k) | (x >> (32 - k)); } static uint32_t s[4]; uint32_t next(void) { const uint32_t result = rotl(s[1] * 5, 7) * 9; const uint32_t t = s[1] << 9; s[2] ^= s[0]; s[3] ^= s[1]; s[1] ^= s[2]; s[0] ^= s[3]; s[2] ^= t; s[3] = rotl(s[3], 11); return result; } /* This is the jump function for the generator. It is equivalent to 2^64 calls to next(); it can be used to generate 2^64 non-overlapping subsequences for parallel computations. */ void jump(void) { static const uint32_t JUMP[] = { 0x8764000b, 0xf542d2d3, 0x6fa035c3, 0x77f2db5b }; uint32_t s0 = 0; uint32_t s1 = 0; uint32_t s2 = 0; uint32_t s3 = 0; for(int i = 0; i < sizeof JUMP / sizeof *JUMP; i++) for(int b = 0; b < 32; b++) { if (JUMP[i] & UINT32_C(1) << b) { s0 ^= s[0]; s1 ^= s[1]; s2 ^= s[2]; s3 ^= s[3]; } next(); } s[0] = s0; s[1] = s1; s[2] = s2; s[3] = s3; } /* This is the long-jump function for the generator. It is equivalent to 2^96 calls to next(); it can be used to generate 2^32 starting points, from each of which jump() will generate 2^32 non-overlapping subsequences for parallel distributed computations. */ void long_jump(void) { static const uint32_t LONG_JUMP[] = { 0xb523952e, 0x0b6f099f, 0xccf5a0ef, 0x1c580662 }; uint32_t s0 = 0; uint32_t s1 = 0; uint32_t s2 = 0; uint32_t s3 = 0; for(int i = 0; i < sizeof LONG_JUMP / sizeof *LONG_JUMP; i++) for(int b = 0; b < 32; b++) { if (LONG_JUMP[i] & UINT32_C(1) << b) { s0 ^= s[0]; s1 ^= s[1]; s2 ^= s[2]; s3 ^= s[3]; } next(); } s[0] = s0; s[1] = s1; s[2] = s2; s[3] = s3; } void test_no_seed() { // Default initialized to contain splitmix64 values boost::random::xoshiro128mm boost_rng; for (int i {}; i < 10000; ++i) { boost_rng(); } boost::random::splitmix64 gen; for (auto& i : s) { i = gen(); } for (int i {}; i < 10000; ++i) { next(); } const auto final_state = boost_rng.state(); for (std::size_t i {}; i < final_state.size(); ++i) { BOOST_TEST_EQ(final_state[i], s[i]); } } void test_basic_seed() { // Default initialized to contain splitmix64 values boost::random::xoshiro128mm boost_rng(42ULL); for (int i {}; i < 10000; ++i) { boost_rng(); } boost::random::splitmix64 gen(42ULL); for (auto& i : s) { i = gen(); } for (int i {}; i < 10000; ++i) { next(); } const auto final_state = boost_rng.state(); for (std::size_t i {}; i < final_state.size(); ++i) { BOOST_TEST_EQ(final_state[i], s[i]); } } void test_jump() { // Default initialized to contain splitmix64 values boost::random::xoshiro128mm boost_rng; for (int i {}; i < 10000; ++i) { boost_rng(); } boost::random::splitmix64 gen; for (auto& i : s) { i = gen(); } for (int i {}; i < 10000; ++i) { next(); } boost_rng.jump(); jump(); const auto final_state = boost_rng.state(); for (std::size_t i {}; i < final_state.size(); ++i) { BOOST_TEST_EQ(final_state[i], s[i]); } } void test_long_jump() { // Default initialized to contain splitmix64 values boost::random::xoshiro128mm boost_rng; for (int i {}; i < 10000; ++i) { boost_rng(); } boost::random::splitmix64 gen; for (auto& i : s) { i = gen(); } for (int i {}; i < 10000; ++i) { next(); } boost_rng.long_jump(); long_jump(); const auto final_state = boost_rng.state(); for (std::size_t i {}; i < final_state.size(); ++i) { BOOST_TEST_EQ(final_state[i], s[i]); } } int main() { test_no_seed(); test_basic_seed(); test_jump(); test_long_jump(); return boost::report_errors(); }