mersenne-twister

问题 Looking for a thread safe random generator I found a mersenne twister generator class that the author says if thread safe: http://www.umiacs.umd.edu/~yangcj/mtrnd.html But after studying the code I cannot see were it is safe thread. There are no locks of any kind or anything resembling a lock variable in there. Is this implementation really thread safe? If so what is the magic? 回答1: It appears to be thread-safe in the sense that two different MersenneTwist objects can be used concurrently.

问题 Looking for a thread safe random generator I found a mersenne twister generator class that the author says if thread safe: http://www.umiacs.umd.edu/~yangcj/mtrnd.html But after studying the code I cannot see were it is safe thread. There are no locks of any kind or anything resembling a lock variable in there. Is this implementation really thread safe? If so what is the magic? 回答1: It appears to be thread-safe in the sense that two different MersenneTwist objects can be used concurrently.

来源： https://stackoverflow.com/questions/62538942/generate-the-same-sequence-of-random-numbers-in-c-from-a-given-seed

来源： https://stackoverflow.com/questions/62538942/generate-the-same-sequence-of-random-numbers-in-c-from-a-given-seed

来源： https://stackoverflow.com/questions/32329263/is-there-a-c11-csprng

来源： https://stackoverflow.com/questions/32329263/is-there-a-c11-csprng

问题 #include <random> int f() { std::random_device seeder; std::mt19937 engine(seeder()); std::uniform_int_distribution<int> dist(1, 6); return dist(engine); } Can multiple threads call this function safely? Is the function thread safe? It is reduntant to call std::random_device seeder; and std::mt19937 engine(seeder()); every time? 回答1: No C++ std type uses global data in a non-thread-safe way. Two unrelated instances of such a type can be accessed in different threads. By default, one instance

问题 Using C++11's random module, I encountered an odd performance drop when using std::mt19937 (32 and 64bit versions) in combination with a uniform_real_distribution (float or double, doesn't matter). Compared to a g++ compile, it's more than an order of magnitude slower! The culprit isn't just the mt generator, as it's fast with a uniform_int_distribution . And it isn't a general flaw in the uniform_real_distribution since that's fast with other generators like default_random_engine . Just that

问题 Using C++11's random module, I encountered an odd performance drop when using std::mt19937 (32 and 64bit versions) in combination with a uniform_real_distribution (float or double, doesn't matter). Compared to a g++ compile, it's more than an order of magnitude slower! The culprit isn't just the mt generator, as it's fast with a uniform_int_distribution . And it isn't a general flaw in the uniform_real_distribution since that's fast with other generators like default_random_engine . Just that

问题 I have a short piece of code which runs the Mersenne Twister PRNG and it works great: std::random_device randDev; std::mt19937 twister(randDev()); std::uniform_int_distribution<int> dist(0,99); for (int i = 0; i < 10; i++) { std::cout << dist(twister) << std::endl; } It outputs ten random numbers. However if I put the exact same code into a function: #include <random> int getRand(const int& A, const int& B) { std::random_device randDev; std::mt19937 twister(randDev()); std::uniform_int