Performance and Quality of Random Number Generators
نویسندگان
چکیده
Random number generation continues to be a critical component in much of computational science and the tradeoff between quality and computational performance is a key issue for many numerical simulations. We review the performance and statistical quality of some well known algorithms for generating pseudo random numbers. Graphical Processing Units (GPUs) are a powerful platform for accelerating computational performance of simulations and random numbers can be generated directly within GPU code or from hosting CPU code. We consider an alternative approach using high quality and genuinely “random” deviates generated using a Quantum device and we report on how such a PCI bus device can be linked to a CPU program. We discuss computational performance and statistical quality tradeoffs of this architectural model for Monte Carlo simulations such as the Ising system.
منابع مشابه
Design of low power random number generators for quantum-dot cellular automata
Quantum-dot cellular automata (QCA) are a promising nanotechnology to implement digital circuits at the nanoscale. Devices based on QCA have the advantages of faster speed, lower power consumption, and greatly reduced sizes. In this paper, we are presented the circuits, which generate random numbers in QCA. Random numbers have many uses in science, art, statistics, cryptography, gaming, gambli...
متن کاملDesign of low power random number generators for quantum-dot cellular automata
Quantum-dot cellular automata (QCA) are a promising nanotechnology to implement digital circuits at the nanoscale. Devices based on QCA have the advantages of faster speed, lower power consumption, and greatly reduced sizes. In this paper, we are presented the circuits, which generate random numbers in QCA. Random numbers have many uses in science, art, statistics, cryptography, gaming, gambli...
متن کاملA Family of Hybrid Random Number Generators with Adjustable Quality and Speed
Conventional random number generators provide the speed but not necessarily the high quality output streams needed for large-scale stochastic simulations. Cryptographically-based generators, on the other hand, provide superior quality output but are often deemed too slow to be practical for use in large simulations. We combine these two approaches to construct a family of hybrid generators that...
متن کاملSccs-746 Tests of Random Number Generators Using Ising Model Simulations
Large-scale Monte Carlo simulations require high-quality random number generators to ensure correct results. The contrapositive of this statement is also true – the quality of random number generators can be tested by using them in large-scale Monte Carlo simulations. We have tested many commonly-used random number generators with high precision Monte Carlo simulations of the 2-d Ising model us...
متن کاملTests of random number generators using Ising model simulations
Large-scale Monte Carlo simulations require high-quality random number generators to ensure correct results. The contrapositive of this statement is also true – the quality of random number generators can be tested by using them in large-scale Monte Carlo simulations. We have tested many commonly-used random number generators with high precision Monte Carlo simulations of the 2-d Ising model us...
متن کاملSensitiveness of Evolutionary Algorithms to the Random Number Generator
This article presents an empirical study of the impact of the change of the Random Number Generator over the performance of four Evolutionary Algorithms: Particle Swarm Optimisation, Differential Evolution, Genetic Algorithm and Firefly Algorithm. Random Number Generators are a key piece in the production of e-science, including optimisation problems by Evolutionary Algorithms. However, Random ...
متن کامل