/* * 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 #include using std::uint64_t; using std::memset; using std::memcpy; /* This is xoshiro512++ 1.0, one of our all-purpose, rock-solid generators. It has excellent (about 1ns) speed, a state (512 bits) that is large enough for any parallel application, and it passes all tests we are aware of. For generating just floating-point numbers, xoshiro512+ is even faster. The state must be seeded so that it is not everywhere zero. If you have a 64-bit seed, we suggest to seed a splitmix64 generator and use its output to fill s. */ static inline uint64_t rotl(const uint64_t x, int k) { return (x << k) | (x >> (64 - k)); } static uint64_t s[8]; uint64_t next(void) { const uint64_t result = rotl(s[0] + s[2], 17) + s[2]; const uint64_t t = s[1] << 11; s[2] ^= s[0]; s[5] ^= s[1]; s[1] ^= s[2]; s[7] ^= s[3]; s[3] ^= s[4]; s[4] ^= s[5]; s[0] ^= s[6]; s[6] ^= s[7]; s[6] ^= t; s[7] = rotl(s[7], 21); return result; } /* This is the jump function for the generator. It is equivalent to 2^256 calls to next(); it can be used to generate 2^256 non-overlapping subsequences for parallel computations. */ void jump(void) { static const uint64_t JUMP[] = { 0x33ed89b6e7a353f9, 0x760083d7955323be, 0x2837f2fbb5f22fae, 0x4b8c5674d309511c, 0xb11ac47a7ba28c25, 0xf1be7667092bcc1c, 0x53851efdb6df0aaf, 0x1ebbc8b23eaf25db }; uint64_t t[sizeof s / sizeof *s]; memset(t, 0, sizeof t); for(std::size_t i = 0; i < sizeof JUMP / sizeof *JUMP; i++) for(int b = 0; b < 64; b++) { if (JUMP[i] & UINT64_C(1) << b) for(std::size_t w = 0; w < sizeof s / sizeof *s; w++) t[w] ^= s[w]; next(); } memcpy(s, t, sizeof s); } /* This is the long-jump function for the generator. It is equivalent to 2^384 calls to next(); it can be used to generate 2^128 starting points, from each of which jump() will generate 2^128 non-overlapping subsequences for parallel distributed computations. */ void long_jump(void) { static const uint64_t LONG_JUMP[] = { 0x11467fef8f921d28, 0xa2a819f2e79c8ea8, 0xa8299fc284b3959a, 0xb4d347340ca63ee1, 0x1cb0940bedbff6ce, 0xd956c5c4fa1f8e17, 0x915e38fd4eda93bc, 0x5b3ccdfa5d7daca5 }; uint64_t t[sizeof s / sizeof *s]; memset(t, 0, sizeof t); for(std::size_t i = 0; i < sizeof LONG_JUMP / sizeof *LONG_JUMP; i++) for(int b = 0; b < 64; b++) { if (LONG_JUMP[i] & UINT64_C(1) << b) for(std::size_t w = 0; w < sizeof s / sizeof *s; w++) t[w] ^= s[w]; next(); } memcpy(s, t, sizeof s); } void test_no_seed() { // Default initialized to contain splitmix64 values boost::random::xoshiro512pp 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::xoshiro512pp 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::xoshiro512pp 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::xoshiro512pp 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(); }