scholarly journals Evaluation of Pseudo-Random Number Generation on GPU Cards

Computation ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 142
Author(s):  
Tair Askar ◽  
Bekdaulet Shukirgaliyev ◽  
Martin Lukac ◽  
Ernazar Abdikamalov
Keyword(s):  
Random Number ◽  
Numerical Test ◽  
Random Number Generation ◽  
Setup Time ◽  
Random Number Generators ◽  
Uniform Distributions ◽  
Pseudo Random Number ◽  
Application Programming ◽  
Nvidia Gpu ◽  
Opposing Effects

Monte Carlo methods rely on sequences of random numbers to obtain solutions to many problems in science and engineering. In this work, we evaluate the performance of different pseudo-random number generators (PRNGs) of the Curand library on a number of modern Nvidia GPU cards. As a numerical test, we generate pseudo-random number (PRN) sequences and obtain non-uniform distributions using the acceptance-rejection method. We consider GPU, CPU, and hybrid CPU/GPU implementations. For the GPU, we additionally consider two different implementations using the host and device application programming interfaces (API). We study how the performance depends on implementation parameters, including the number of threads per block and the number of blocks per streaming multiprocessor. To achieve the fastest performance, one has to minimize the time consumed by PRNG seed setup and state update. The duration of seed setup time increases with the number of threads, while PRNG state update decreases. Hence, the fastest performance is achieved by the optimal balance of these opposing effects.

scholarly journals The Possibility of Uniform Pseudo-random Number Generation by a Group of Humans

2018 ◽  
Author(s):  
Samuel Toluwalope Ogunjo ◽  
Emmanuel Jesuyon Dansu ◽  
Oluwagbenga Olukanye-David ◽  
Ibiyinka Agboola Fuwape
Keyword(s):  
Test Score ◽  
Random Number ◽  
Statistical Tests ◽  
Random Number Generation ◽  
Random Numbers ◽  
Significant Relation ◽  
Random Number Generators ◽  
Number Generation ◽  
Pseudo Random Number ◽  
University Of Technology

The ability of humans to generate numbers that are really random has always been a subject of debate. This paper investigated the possibility for a group of humans to serve as random number generators. A total of 2344 students, who were not pre-informed to avoid bias, from different faculties within the Federal University of Technology Akure were asked to chose a random number between 1 and 10. Using various statistical tests, we sought answers to the possibility of predictors like participant’s test score, gender, age and school influencing their choice of random numbers. We discovered that the numbers generated are highly random and chaotic despite number 1 being the most selected number across all predictors that was considered. Our study found that gender, test score, age did not significantly influence the choice of number while faculty showed a significant relation α < 0.05.

Pseudo-random number generation based on digit isolation referenced to entropy buffers

SIMULATION ◽  
2021 ◽  
pp. 003754972110544
Author(s):  
Joseph D. Richardson
Keyword(s):  
Gold Standard ◽  
Random Number ◽  
Statistical Tests ◽  
Random Number Generation ◽  
The Other ◽  
Double Precision ◽  
Random Number Generators ◽  
Dual Nature ◽  
Pseudo Random Number ◽  
Empirical Performance

Unpredictable pseudo-random number generators (PRNGs) are presented based on dissociated components with only coincidental interaction. The first components involve pointers taken from series of floating point numbers (float streams) arising from arithmetic. The pointers are formed by isolating generalized digits sufficiently far from the most significant digits in the float streams and may be combined into multi-digit pointers. The pointers indicate draw locations from the second component which are entropy decks having one or more cards corresponding to the elements used to assemble random numbers. Like playing cards, decks are cut and riffle-shuffled based on rules using digits appearing in the simulations. The various ordering states of the cards provide entropy to the PRNGs. The dual nature of the PRNGs is novel since they can operate either entirely on pointer variability to fixed decks or on shuffling variability using fixed pointer locations. Each component, pointers and dynamic entropy, is dissociated from the other and independently shown to pass stringent statistical tests with the other held as fixed; a “gold standard” mode involves changing the coincidental interaction between these two strong emulators of randomness by either cutting or shuffling prior to each draw. Gold standard modes may be useful in cryptography and in assessing tests themselves. One PRNG contains [Formula: see text] states in the entropy pool, another generates integers approximately 50% faster than the Advanced Encryption Standard (AES) PRNG with similar empirical performance, and a third generates full double-precision floats at speeds comparable to unsigned integer rates of the AES PRNG.

Hardware implementation of pseudo-random number generators based on chaotic maps

2017 ◽  
Vol 90 (3) ◽  
pp. 1661-1670 ◽  
Author(s):  
Luis Gerardo de la Fraga ◽  
Esteban Torres-Pérez ◽  
Esteban Tlelo-Cuautle ◽  
Cuauhtemoc Mancillas-López
Keyword(s):  
Hardware Implementation ◽  
Random Number ◽  
Chaotic Maps ◽  
Random Number Generators ◽  
Pseudo Random Number

scholarly journals Problem of uniqueness in the renewal process generated by the uniform distribution

1992 ◽  
Vol 5 (4) ◽  
pp. 291-305 ◽  
Author(s):  
D. Ugrin-Šparac
Keyword(s):  
Integral Representation ◽  
Uniform Distribution ◽  
Gamma Function ◽  
Renewal Process ◽  
Random Number ◽  
Discrete Distribution ◽  
Inverse Image ◽  
Random Number Generators ◽  
Pseudo Random Number

The renewal process generated by the uniform distribution, when interpreted as a transformation of the uniform distribution into a discrete distribution, gives rise to the question of uniqueness of the inverse image. The paper deals with a particular problem from the described domain, that arose in the construction of a complex stochastic test intended to evaluate pseudo-random number generators. The connection of the treated problem with the question of a unique integral representation of Gamma-function is also mentioned.

scholarly journals Influence of Experiment Design in GPA Investigating with Respect to PRNGs

MENDEL ◽  
2018 ◽  
Vol 24 (2) ◽  
Author(s):  
Tomas Brandejsky
Keyword(s):  
Genetic Programming ◽  
Random Number ◽  
Experiment Design ◽  
Parallel Execution ◽  
Random Number Generators ◽  
Pseudo Random Number ◽  
Programming Algorithms

This paper analyses the influence of experiment parameters onto the reliability of experiments with genetic programming algorithms. The paper is focused on the required number of experiments and especially on the influence of parallel execution which affect not only the order of thread execution but also behaviors of pseudo random number generators, which frequently do not respect recommendation of C++11 standard and are not implemented as thread safe. The observations and the effect of the suggested improvements are demonstrated on results of 720,000 experiments.

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