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Evolutionary algorithms (EAs) are increasingly implemented on graphics processing units (GPUs) to leverage parallel processing capabilities for enhanced efficiency. However, existing studies largely emphasize the raw speedup obtained by…

Neural and Evolutionary Computing · Computer Science 2026-01-28 Xinmeng Yu , Tao Jiang , Ran Cheng , Yaochu Jin , Kay Chen Tan

With the growing model size, deep neural networks (DNN) are increasingly trained over massive GPU accelerators, which demands a proper parallelization plan that transforms a DNN model into fine-grained tasks and then schedules them to GPUs…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-01-24 Zhiqi Lin , Youshan Miao , Guodong Liu , Xiaoxiang Shi , Quanlu Zhang , Fan Yang , Saeed Maleki , Yi Zhu , Xu Cao , Cheng Li , Mao Yang , Lintao Zhang , Lidong Zhou

We discuss the computational complexity of solving linear programming problems by means of an analog computer. The latter is modeled by a dynamical system which converges to the optimal vertex solution. We analyze various probability…

Other Condensed Matter · Physics 2007-05-23 Yaniv S. Avizrats , Joshua Feinberg , Shmuel Fishman

It is imperative for testing to determine if the components within large-scale software systems operate functionally. Interaction testing involves designing a suite of tests, which guarantees to detect a fault if one exists among a small…

Neural and Evolutionary Computing · Computer Science 2020-02-14 Ryan E. Dougherty

The research community continues to seek increasingly more advanced synthetic data generators to reliably evaluate the strengths and limitations of machine learning methods. This work aims to increase the availability of datasets…

Machine Learning · Computer Science 2026-01-30 Joanna Komorniczak

Genetic Programming (GP) is known to suffer from the burden of being computationally expensive by design. While, over the years, many techniques have been developed to mitigate this issue, data vectorization, in particular, is arguably…

Neural and Evolutionary Computing · Computer Science 2021-06-23 Francisco Baeta , João Correia , Tiago Martins , Penousal Machado

Some recent studies have suggested using GANs for numeric data generation such as to generate data for completing the imbalanced numeric data. Considering the significant difference between the dimensions of the numeric data and images, as…

Machine Learning · Computer Science 2020-05-11 Wei Wang , Chuang Wang , Tao Cui , Yue Li

GANs have two competing modules: the generator module is trained to generate new examples, and the discriminator module is trained to discriminate real examples from generated examples. The training procedure of GAN is modeled as a finitely…

Machine Learning · Computer Science 2022-09-29 Ch. Sobhan Babu , Ravindra Guravannavar , Arvind Hulgeri

There have been extensive works dealing with genetic algorithms (GAs) for seeking optimal solutions of shop scheduling problems. Due to the NP hardness, the time cost is always heavy. With the development of high performance computing (HPC)…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-04-09 Jia Luo , Didier El Baz

With the number of fully-sequenced genomes now well over a hundred it has become possible to start investigating if there are any quantitative regularities in the genetic make-up of genomes. In (physics/0307001), I originally showed that…

Genomics · Quantitative Biology 2007-05-23 Erik van Nimwegen

The search for similar genetic sequences is one of the main bioinformatics tasks. The genetic sequences data banks are growing exponentially and the searching techniques that use linear time are not capable to do the search in the required…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-07-13 Felipe Albrecht

We are interested in the design of generative networks. The training of these mathematical structures is mostly performed with the help of adversarial (min-max) optimization problems. We propose a simple methodology for constructing such…

Machine Learning · Computer Science 2021-07-16 Kalliopi Basioti , George V. Moustakides

In this paper, we study a parallel version of Galton-Watson processes for the random generation of tree-shaped structures. Random trees are useful in many situations (testing, binary search, simulation of physics phenomena,...) as attests…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-06-22 Olivier Bodini , Camille Coti , Julien David

We present two adaptive schemes for dynamically choosing the number of parallel instances in parallel evolutionary algorithms. This includes the choice of the offspring population size in a (1+$\lambda$) EA as a special case. Our schemes…

Data Structures and Algorithms · Computer Science 2011-03-03 Jörg Lässig , Dirk Sudholt

Single-cell experiments have revealed cell-to-cell variability in generation times and growth rates for genetically identical cells. Theoretical models relating the fluctuating generation times of single cells to the population growth rate…

Populations and Evolution · Quantitative Biology 2020-01-15 Jie Lin , Ariel Amir

Usage of multiprocessor and multicore computers implies parallel programming. Tools for preparing parallel programs include parallel languages and libraries as well as parallelizing compilers and convertors that can perform automatic…

Mathematical Software · Computer Science 2022-12-12 Pavel Telegin , Anton Baranov , Boris Shabanov , Artem Tikhomirov

Genetic programming and artificial life systems commonly employ tag-matching schemes to determine interactions between model components. However, the implications of criteria used to determine affinity between tags with respect to…

Neural and Evolutionary Computing · Computer Science 2023-10-10 Matthew Andres Moreno , Alexander Lalejini , Charles Ofria

In the recent years it can be observed increasing popularity of parallel processing using multi-core processors, local clusters, GPU and others. Moreover, currently one of the main requirements the IT users is the reduction of maintaining…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-04-05 Łukasz P. Olech , Jan Kwiatkowski

We evolve binary mux-6 trees for up to 100000 generations evolving some programs with more than a hundred million nodes. Our unbounded Long-Term Evolution Experiment LTEE GP appears not to evolve building blocks but does suggests a limit to…

Neural and Evolutionary Computing · Computer Science 2017-03-27 W. B. Langdon

With the number of sequenced genomes now over one hundred, and the availability of rough functional annotations for a substantial proportion of their genes, it has become possible to study the statistics of gene content across genomes. Here…

Biological Physics · Physics 2007-05-23 Erik van Nimwegen