Techniques of evolutionary computation generally require significant computational resources to solve non-trivial problems of interest. Increases in computing power can be realized either by using a faster computer or by parallelizing the application. Techniques of evolutionary computation are especially amenable to parallelization. This paper describes how to build a 10-node Beowulf-style parallel computer system for $18,000 that delivers about a half peta-flop (1015 floating-point operations) per day on runs of genetic programming. Each of the 10 nodes of the system contains a 533 MHz Alpha processor and runs with the Linux operating system. This amount of computational power is sufficient to yield solutions (within a couple of days per p...
The rapid increase in performance of mass market commodity microprocessors and significant disparity...
Many optimization problems have complex search space, which either increase the solving problem time...
Lecture #1: From Evolution Theory to Evolutionary Computation. Evolutionary computation is a subfiel...
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use bette...
Recent years have witnessed the emergence of a huge number of parallel computer architectures. Almos...
There is a lack of a programming free solution which can run a distributed genetic algorithm in para...
In this paper, we describe our work to investigate how much cyclic graph based Genetic Programming (...
Evolutionary algorithms (EAs) are modern techniques for searching complex spaces for on optimum [11]...
The field of FPGA design is ever-growing due to costs being lower than that of ASICs, as well as the...
This paper proposes that a parallel implementa-tion of the genetic algorithm (GA) on the Internet wi...
An advanced system of parallel computation was developed. The system is comprised of multiple softwa...
In this article an experience of the utilization of PRC (Public Resource Computation) in research p...
'Evolutionary algorithms' is the collective name for a group of relatively new stochastic search alg...
Abstract- In this paper we propose the implementation of a massively parallel GP model in hardware i...
Mathematica has proven itself to be a suitable platform on which to develop prototype Genetic Progr...
The rapid increase in performance of mass market commodity microprocessors and significant disparity...
Many optimization problems have complex search space, which either increase the solving problem time...
Lecture #1: From Evolution Theory to Evolutionary Computation. Evolutionary computation is a subfiel...
As genetic algorithms (GAs) are used to solve harder problems, it is becoming necessary to use bette...
Recent years have witnessed the emergence of a huge number of parallel computer architectures. Almos...
There is a lack of a programming free solution which can run a distributed genetic algorithm in para...
In this paper, we describe our work to investigate how much cyclic graph based Genetic Programming (...
Evolutionary algorithms (EAs) are modern techniques for searching complex spaces for on optimum [11]...
The field of FPGA design is ever-growing due to costs being lower than that of ASICs, as well as the...
This paper proposes that a parallel implementa-tion of the genetic algorithm (GA) on the Internet wi...
An advanced system of parallel computation was developed. The system is comprised of multiple softwa...
In this article an experience of the utilization of PRC (Public Resource Computation) in research p...
'Evolutionary algorithms' is the collective name for a group of relatively new stochastic search alg...
Abstract- In this paper we propose the implementation of a massively parallel GP model in hardware i...
Mathematica has proven itself to be a suitable platform on which to develop prototype Genetic Progr...
The rapid increase in performance of mass market commodity microprocessors and significant disparity...
Many optimization problems have complex search space, which either increase the solving problem time...
Lecture #1: From Evolution Theory to Evolutionary Computation. Evolutionary computation is a subfiel...