Библиотека PRAND: генерация параллельных потоков случайных чисел для расчетов Монте-Карло с использованием GPU
Libraries RNGSSELIB и PRAND for the parallel generation of pseudo-random numbers in Monte Carlo simulations was developed. RNGSSELIB library contains realization based on the SSE extensionin the modern CPU, and PRAND library contains the generators using CUDA version 5.0 and later.
We present optimization guidelines and implementations of cryptographic hash functions GOST R 34.11-94 and GOST R 34.11-2012. Results for x86_64 CPUs and NVIDIA CUDA-capable GPUs are provided for our and several other well-known implementations. It is shown that the new standard may be twice as fast as the old one on modern CPUs, but it may be slower on embedded devices and GPUs. The results given for our implementation are the fastest among all the tested implementations on both platforms.
An approach is described to implementation of the Method of Four Russians for reducing the dense matrices over GF(2) to row echelon form using the NVIDIA CUDA platform. Estimates of the algorithm running time and recommendations on choosing the algorithm parameters are given. It is shown that the developed implementation is most effective in comparison with the existing solutions for matrices of a size 2^17 x 2^17.
This article aims to provides a theoretical overview of social stock exchanges, as innovative tools of social investment attracting. In the article we define functions of SSEs, its main features and compare SSEs with traditional stock exchanges.
This proceedings publication is a compilation of selected contributions from the “Third International Conference on the Dynamics of Information Systems” which took place at the University of Florida, Gainesville, February 16–18, 2011. The purpose of this conference was to bring together scientists and engineers from industry, government, and academia in order to exchange new discoveries and results in a broad range of topics relevant to the theory and practice of dynamics of information systems. Dynamics of Information Systems: Mathematical Foundation presents state-of-the art research and is intended for graduate students and researchers interested in some of the most recent discoveries in information theory and dynamical systems. Scientists in other disciplines may also benefit from the applications of new developments to their own area of study.