FPGA implementation of neighborhood-of-four cellular automata random number generators

Shackleford, Barry; Tanaka, Mieko; Carter, Richard J.; Snider, Greg

doi:10.1145/503062.503064

Cited by 15 publications

(24 citation statements)

References 10 publications

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“…Each application imposes different statistical and performance requirements to PRNGs but most implementations trade the randomness quality and the associated computational complexity to produce them. Several studies have shown that CA are an alternative technique for PRNG, being one of the main motivations the good randomness and their hardware-friendly nature: CAs are simple, regular, locally interconnected, and modular structures [2]. In this paper, the analysis of two CA-based PRNGs (two-dimensional CA, transition functions, and the number of neighbors) is presented and used to propose a new CA configuration with improved randomness quality.…”

Section: Introductionmentioning

confidence: 99%

“…An homogeneous assymetric connections CA proposed in [2], conceptually shown on the left in Figure 1, presents good randomness quality based on a 2D grid of 8x8 cells with periodic toroid boundary conditions. The connectivity rules for a given cell is as follows {2n2w, c, n2e, 2se}.…”

Section: Introductionmentioning

confidence: 99%

“…1. Two-dimensional CA-based PRNGs: an homogeneous (left) and no-homogeneus (rigth), see [2] and [1], respectively, for details.…”

Section: Introductionmentioning

confidence: 99%

“…The rule of a cell is then given by the 6-bit string xcnwse and just four different transition rules were used. Since stochastic heuristic search techniques were used to design the above cited PRNGs, there is no guarantee that the reported results are optimal and hence better 2D CAs cannot be constructed by modifying some parameters [1,2]. Under this observation, in this paper, we evaluate the nature of 4-neighbor neighborship as a mean to improve the randomness quality.…”

Section: Introductionmentioning

confidence: 99%

“…Under this observation, in this paper, we evaluate the nature of 4-neighbor neighborship as a mean to improve the randomness quality. A 2D CA configuration that keeps most of the parameters proposed in [2] was used, except that different assymetric 4-neighbor neighborhoods were explored [3]. The four neighbors were restricted to be located in a 5 × 5 area around a center cell in order to reduce the searching space.…”

Section: Introductionmentioning

confidence: 99%

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Comparison between 2D cellular automata based pseudorandom number generators

Torres-Huitzil

Delgadillo-Escobar

2012

IEICE Electron. Express

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Pseudorandom number generators (PRNGs) should satisfy two main criteria, high randomness quality and fast computation of a sequence of numbers. In this paper, a comparative study of twodimensional Cellular Automata (CA) based PRNGs is performed to evaluate the randomness quality and the hardware constraints involved in terms of configuration parameters such as, transition rules, neighborhoods and bit extraction schemes. Experimental results show that CA-based PRNGs present good randomness quality using standard test suites, and they are well suited for parallel implementations in Field Programmable Gate Array (FPGA) technology taking advantage of the on-chip fine-grain and distributed computational resources. Keywords: Cellular automata, pseudorandom numbers, FPGA Classification: Electron devices, circuits, and systems References[1] M. Tomassini, M. Sipper, and M. Perrenoud, "On the generation of highquality random numbers by two-dimensional cellular automata," IEEE Trans.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…1. Two-dimensional CA-based PRNGs: an homogeneous (left) and no-homogeneus (rigth), see [2] and [1], respectively, for details.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Comparison between 2D cellular automata based pseudorandom number generators

Torres-Huitzil

Delgadillo-Escobar

2012

IEICE Electron. Express

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Using parallelization and hardware concurrency to improve the performance of a genetic algorithm

Tirumalai

Ricks

Woodbury

2006

Concurrency and Computation

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SUMMARYGenetic algorithms (GAs) are powerful tools for solving many problems requiring the search of a solution space having both local and global optima. The main drawback for GAs is the long execution time normally required for convergence to a solution. This paper discusses three different techniques that can be applied to GAs to improve overall execution time. A serial software implementation of a GA designed to solve a task scheduling problem is used as the basis for this research. The execution time of this implementation is then improved by exploiting the natural parallelism present in the algorithm using a multiprocessor. Additional performance improvements are provided by implementing the original serial software GA in dedicated reconfigurable hardware using a pipelined architecture. Finally, an advanced hardware implementation is presented in which both pipelining and duplicated hardware modules are used to provide additional concurrency leading to further performance improvements.

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On the Implementation of a Margolus Neighborhood Cellular Automata on FPGA

Cerdá

Gadea

Herrero

et al. 2003

Field Programmable Logic and Application

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Abstract. Margolus neighborhood is the easiest form of designing Cellular Automata Rules with features such as invertibility or particle conserving. In this paper we propose two different implementations of systems based on this neighborhood: The first one corresponds to a classical RAM-based implementation, while the second, based on concurrent cells, is useful for smaller systems in which time is a critical parameter. This implementation has the feature that the evolution of all the cells in the design is performed in the same clock cycle.

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FPGA implementation of neighborhood-of-four cellular automata random number generators

Cited by 15 publications

References 10 publications

Comparison between 2D cellular automata based pseudorandom number generators

Comparison between 2D cellular automata based pseudorandom number generators

Using parallelization and hardware concurrency to improve the performance of a genetic algorithm

On the Implementation of a Margolus Neighborhood Cellular Automata on FPGA

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