Random numbers are widely used in today’s modern applications. In C we use rand(), srand() and in C++ it is std::rand(), std::srand(). Since C++11, we can use the Mersenne Twister random generators; mt19937 (std::mt19937) for 32-bit applications and mt19937_64 (std::mt19937_64) for 64-bit applications. Modern C++ allows us to use both old and new random generators. In this post, we explain what are the differences between rand(), std::rand(), std::mt19937(), std::mt19937_64().
Table of Contents
What is a random number and rand() in C and C++?
A random number is a number that is randomly chosen in a given range. It is statistically impossible to predict future values based on past or present values and they are uniformly distributed over a defined interval or set.
The rand() is a C function defined in <stdlib.h> and std::rand() is a C++ function defined in the <cstdlib> header. Both are the same and are used to generate pseudo-random numbers in the range of 0 to RAND_MAX. Here is the definition in the <cstdlib> header.
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using _CSTD rand; |
In C we use rand(), srand() and in C++ we use std::rand(), std::srand() they use a Linear Congruential Generator. While they are added to <cstdlib> to make modern C++ compatible, there a more modern random number generator algorithms, such as Mersenne Twister algorithm.
How can we use rand() in C?
Here is a simple C example to generate a random number between 0 to 100,
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#include <stdio.h> #include <stdlib.h> int main () { printf("Random Number:%d\n", rand()%100); getchar(); return(0); } |
How can we use std::rand() in C++?
Here is a simple C++ example to generate a random number between 0 to 100,
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#include <iostream> #include <cstdlib> int main() { std::cout << "Random Number:%d\n", std::rand()%100); system("pause"); return(0); } |
What is Mersenne Twister Algorithm in programming?
A Mersenne prime is a prime number used in mathematics that is a number of the form Mn = 2n − 1 where the n is an integer. The Mersenne Twister is a pseudorandom number generator where the period length is chosen to be a Mersenne Prime. It was developed by Makoto Matsumoto in 1997.
Since C++11, the Mersenne Twister mathematical number generator is implemented as a random generator number, it is defined in <random> header as a std::mersenne_twister_engine that is a random number engine based on Mersenne Twister algorithm.
What is std::mt19937 random number generator in modern C++?
In modern C++, there are more useful and modern random number generators. These are std::mt19937 and std::mt19937_64. The std::mt19937 is a 32-bit Mersenne Twister by Matsumoto and Nishimura in 1998, and std::mt19937_64 is a 64-bit Mersenne Twister by Matsumoto and Nishimura in 2000.
The std::mt19937 is a random number generator defined in <random> header in C++17 standard and beyond, producing 32-bit pseudo-random numbers by using the Mersenne Twister algorithm with a state size of 19937 bits. This is why it is called mt19937 and there is a 64-bit version called mt19937_64. Both are defined as an instantiation of the mersenne_twister_engine. Now let’s see their definitions.
Since C++11, mt19937 is defined as below,
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typedef mersenne_twister_engine<unsigned int, 32, 624, 397, 31, 0x9908b0df, 11, 0xffffffff, 7, 0x9d2c5680, 15, 0xefc60000, 18, 1812433253> mt19937; |
Since C++11, mt19937_64 is defined as below,
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typedef mersenne_twister_engine<_ULonglong, 64, 312, 156, 31, 0xb5026f5aa96619e9ULL, 29, 0x5555555555555555ULL, 17, 0x71d67fffeda60000ULL, 37, 0xfff7eee000000000ULL, 43, 6364136223846793005ULL> mt19937_64; |
Is there a simple example to use std::mt19937 in modern C++?
Here is a simple example to use std::mt19937,
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#include <iostream> #include <random> #include <ctime> int main() { std::mt19937 rnd( std::time(nullptr) ); std::cout << "32bit Random MT Number:" << rnd() << std::endl; system("pause"); return 0; } |
What are the differences between std::rand() and std::mt19937 in modern C++?
As you see we define both rand and mt19937 above. Now let’s list their differences between them.
| rand | std::rand | std::mt19937 | std::mt19937_64 | |
| Generator Type | Linear Congruential | Linear Congruential | Mersenne Twister | Mersenne Twister |
| Defined Header | stdlib.h | cstdlib | random | random |
| Used In | C and C++ | C++ | C++11 | C++11 |
| Bits | 16-bit | 16-bit or 32-bit | 32-bit | 64-bit |
| Minimum Number | 0 | 0 | 0 | 0 |
| Maximum Number | 32767 | 32767 or 2147483647 | 4123659995 | 9981545732273789042 |
| Min, Max Number Definition | 0 RAND_MAX | 0 RAND_MAX | .min() .max() | .min() .max() |
| Seeding New Generator | srand() | std::srand() | .seed() | .seed() |
| Modern or Classic | classic C | modern C++ | modern C++ | modern C++ |
| Return type | int | int | uint_fast32_t | uint_fast64_t |
| Recommended in C++? | No | No | Yes | Yes |
| Random Period | Shorter | Shorter | Longer | Much longer |
| Randomness | Low | Low | High | High |
| Quality of the Random Sequence | No guarantee | No guarantee | Good | Good |
| Using with Iterators and Containers | No | Hard to use and Slow | Easy and Fast | Easy and Useful in 64bit |
| Safety | Not safe | Not safe | Safe | Safe |
| Coding | Easy | hard to remember it’s header name | hard to remember its name cuz of 19937 | hard to remember its name cuz of 19937_64 |
For more details about this feature in C++11 standard, please see these papers; p0205r1
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