Generation of pseudo-random numbers

Practical methods for generating acceptable random numbers from a variety of probability distributions which are frequently encountered in engineering applications are described. The speed, accuracy, and guarantee of statistical randomness of the various methods are discussed

Algorithms for randomness in the behavioral sciences: A tutorial

Simulations and experiments frequently demand the generation of random numbera that have specific distributions. This article describes which distributions should be used for the most cammon problems and gives algorithms to generate the numbers.It is also shown that a commonly used permutation algorithm (Nilsson, 1978) is deficient

Perspectives for Monte Carlo simulations on the CNN Universal Machine

Possibilities for performing stochastic simulations on the analog and fully parallelized Cellular Neural Network Universal Machine (CNN-UM) are investigated. By using a chaotic cellular automaton perturbed with the natural noise of the CNN-UM chip, a realistic binary random number generator is built. As a specific example for Monte Carlo type simulations, we use this random number generator and a CNN template to study the classical site-percolation problem on the ACE16K chip. The study reveals that the analog and parallel architecture of the CNN-UM is very appropriate for stochastic simulations on lattice models. The natural trend for increasing the number of cells and local memories on the CNN-UM chip will definitely favor in the near future the CNN-UM architecture for such problems.Comment: 14 pages, 6 figure

Mixing multi-core CPUs and GPUs for scientific simulation software

Recent technological and economic developments have led to widespread availability of multi-core CPUs and specialist accelerator processors such as graphical processing units (GPUs). The accelerated computational performance possible from these devices can be very high for some applications paradigms. Software languages and systems such as NVIDIA's CUDA and Khronos consortium's open compute language (OpenCL) support a number of individual parallel application programming paradigms. To scale up the performance of some complex systems simulations, a hybrid of multi-core CPUs for coarse-grained parallelism and very many core GPUs for data parallelism is necessary. We describe our use of hybrid applica- tions using threading approaches and multi-core CPUs to control independent GPU devices. We present speed-up data and discuss multi-threading software issues for the applications level programmer and o er some suggested areas for language development and integration between coarse-grained and ne-grained multi-thread systems. We discuss results from three common simulation algorithmic areas including: partial di erential equations; graph cluster metric calculations and random number generation. We report on programming experiences and selected performance for these algorithms on: single and multiple GPUs; multi-core CPUs; a CellBE; and using OpenCL. We discuss programmer usability issues and the outlook and trends in multi-core programming for scienti c applications developers

Chip and Skim: cloning EMV cards with the pre-play attack

EMV, also known as "Chip and PIN", is the leading system for card payments worldwide. It is used throughout Europe and much of Asia, and is starting to be introduced in North America too. Payment cards contain a chip so they can execute an authentication protocol. This protocol requires point-of-sale (POS) terminals or ATMs to generate a nonce, called the unpredictable number, for each transaction to ensure it is fresh. We have discovered that some EMV implementers have merely used counters, timestamps or home-grown algorithms to supply this number. This exposes them to a "pre-play" attack which is indistinguishable from card cloning from the standpoint of the logs available to the card-issuing bank, and can be carried out even if it is impossible to clone a card physically (in the sense of extracting the key material and loading it into another card). Card cloning is the very type of fraud that EMV was supposed to prevent. We describe how we detected the vulnerability, a survey methodology we developed to chart the scope of the weakness, evidence from ATM and terminal experiments in the field, and our implementation of proof-of-concept attacks. We found flaws in widely-used ATMs from the largest manufacturers. We can now explain at least some of the increasing number of frauds in which victims are refused refunds by banks which claim that EMV cards cannot be cloned and that a customer involved in a dispute must therefore be mistaken or complicit. Pre-play attacks may also be carried out by malware in an ATM or POS terminal, or by a man-in-the-middle between the terminal and the acquirer. We explore the design and implementation mistakes that enabled the flaw to evade detection until now: shortcomings of the EMV specification, of the EMV kernel certification process, of implementation testing, formal analysis, or monitoring customer complaints. Finally we discuss countermeasures

Supercomputers, Monte Carlo simulation and regression analysis

Monte Carlo Technique;Supercomputer;computer science