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A random seed (or seed state, or just seed) is a number (or vector) used to initialize a pseudorandom number generator. A pseudorandom number generator's number sequence is completely determined by the seed: thus, if a pseudorandom number generator is later reinitialized with the same seed, it will produce the same sequence of numbers.
If a full derandomization is desired, a completely deterministic simulation proceeds by replacing the random input to the randomized algorithm with the pseudorandom string produced by the pseudorandom generator. The simulation does this for all possible seeds and averages the output of the various runs of the randomized algorithm in a suitable way.
Different models can be generated by changing both deterministic parameters and a random seed. In computing, procedural generation is a method of creating data algorithmically as opposed to manually, typically through a combination of human-generated content and algorithms coupled with computer-generated randomness and processing power.
It is acceptable to pad the seeds with zeros to the left in order to create an even valued n-digit number (e.g. 540 → 0540). For a generator of n-digit numbers, the period can be no longer than 8 n. If the middle n digits are all zeroes, the generator then outputs zeroes forever. If the first half of a number in the sequence is zeroes, the ...
Intuitively, an extractor takes a weakly random n-bit input and a short, uniformly random seed and produces an m-bit output that looks uniformly random. The aim is to have a low d {\displaystyle d} (i.e. to use as little uniform randomness as possible) and as high an m {\displaystyle m} as possible (i.e. to get out as many close-to-random bits ...
An astrophysical Monte Carlo simulator examined the time to generate 10 7 64-bit random numbers using RDRAND on a quad-core Intel i7-3740 QM processor. They found that a C implementation of RDRAND ran about 2× slower than the default random number generator in C, and about 20× slower than the Mersenne Twister.
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The serpentine system (also called snake seeding) is a method employed in the organization of a competition to define the seeded teams and arrange them in pools. The n ranked teams that will be involved in the tournament are distributed in m pools according to the following algorithm: