12 results on '"Riscos-Núñez, Agustín"'
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2. Seeking computational efficiency boundaries: the Păun’s conjecture
- Author
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Orellana-Martín, David and Riscos-Núñez, Agustín
- Published
- 2020
- Full Text
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3. The role of integral membrane proteins in computational complexity theory
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Orellana-Martín, David, Martínez-del-Amor, Miguel Á., Valencia-Cabrera, Luis, Riscos-Núñez, Agustín, and Pérez-Jiménez, Mario J.
- Published
- 2018
- Full Text
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4. A New Strategy to Improve the Performance of PDP-Systems Simulators
- Author
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Graciani, Carmen, Martínez-del-Amor, Miguel A., Riscos-Núñez, Agustín, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Rozenberg, Grzegorz, editor, Salomaa, Arto, editor, Sempere, José M., editor, and Zandron, Claudio, editor
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- 2015
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5. On GPU-Oriented P Systems
- Author
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Martínez del Amor, Miguel Ángel, Orellana Martín, David, Riscos Núñez, Agustín, Pérez Jiménez, Mario de Jesús, Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial, and Universidad de Sevilla. TIC193: Computación Natural
- Subjects
P systems ,GPU ,Parallelism ,simulation - Abstract
Ministerio de Economía, Industria y Competitividad TIN2017-89842-P
- Published
- 2018
6. A Survey of Parallel Simulation of P Systems with GPUs
- Author
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Martínez del Amor, Miguel Ángel, Riscos Núñez, Agustín, Pérez Jiménez, Mario de Jesús, Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial, and Universidad de Sevilla. TIC193 : Computación Natural
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Parallel Computing ,P systems ,Membrane computing ,CUDA ,GPU computing - Abstract
P system simulators become essential for model verification and validation, since they reproduce the semantics of the models in an automatic way. For this reason, in the literature, many authors have proposed several simulation tools. However, in order to handle large instances in an efficient way, parallel simulators come into play. High Performance Computing is a research branch that brings efficient tools for scien- tific purposes. For decades, many parallel platforms and architectures have been designed, with the goal of accelerating compute-demanding applications. But it was 10 years ago, that this field was revolutionized with the dawn of GPU computing through CUDA. This technology allowed programmers to run general-purpose parallel code in GPUs, harnessing in a simplified manner the large amount of processors within a GPU. Many authors have chosen this technology for accelerating the simulation of their P system models. Recently, this topic has captured the attention of more researchers. Therefore, in this paper we survey the related work on GPU-based simulators for P systems, and its evolution over the time until today
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- 2017
7. Sevilla Carpets Revisited: Enriching the Membrane Computing Toolbox.
- Author
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Orellana-Martín, David, Graciani, Carmen, Macías-Ramos, Luis-Felipe, Martínez-del-Amor, Miguel Ángel, Riscos-Núñez, Agustín, Romero-Jiménez, Álvaro, and Valencia-Cabrera, Luis
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TOOLBOXES ,COMPUTATIONAL complexity ,GRAPHICS processing units ,SUBSET selection ,PROBLEM solving - Abstract
Sevilla carpets have already been used to compare different solutions of the Subset Sum problem: either designed in the framework of P systems with active membranes (both in the case of membrane division and membrane creation), and in the framework of tissue-like P systems with cell division. Recently, the degree of parallelism and other descriptive complexity details have been found to be relevant when designing parallel simulators running on GPUs. We present here a new way to use the information provided by Sevilla carpets in this context, and a script that allows to generate them automatically from P-Lingua files. [ABSTRACT FROM AUTHOR]
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- 2014
- Full Text
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8. A Look at the Descriptional Complexity of SNQ P Systems
- Author
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Păun, Andrei, Bîlbîe, Florin-Daniel, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Graciani, Carmen, editor, Riscos-Núñez, Agustín, editor, Păun, Gheorghe, editor, Rozenberg, Grzegorz, editor, and Salomaa, Arto, editor
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- 2018
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9. MAREX: A general purpose hardware architecture for membrane computing.
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Cascado-Caballero, Daniel, Diaz-del-Rio, Fernando, Cagigas-Muñiz, Daniel, Rios-Navarro, Antonio, Guisado-Lizar, Jose-Luis, Pérez-Hurtado, Ignacio, and Riscos-Núñez, Agustín
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LOGIC circuits , *PARALLEL computers , *PARALLEL processing , *HARDWARE - Abstract
Membrane computing is an unconventional computing paradigm that has gained much attention in recent decades because of its massively parallel character and its usefulness to build models of complex systems. However, until now, there was no generic hardware implementation of P systems. Computational frameworks to execute P systems up to this day rely on the simulation of the parallel working mechanisms of P systems by inherently sequential algorithms. Such algorithms can then be implemented as is or can be parallelized, up to a certain point, to run on parallel computers. However, this is not as efficient as a dedicated parallel hardware implementation. There have been ad hoc implementations of particular P systems for parallel hardware, but they lack to be problem-generic or they are not scalable enough to implement large P systems. In this paper, a first intrinsically parallel hardware architecture to implement generic P system models is introduced. It is designed to be straightforwardly implemented in programmable logic circuits like FPGAs. The feasibility and correct execution of our architecture has been verified by means of a simulator, and several simulation results for different P system examples have been analysed to foresee the pros and cons of this design. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
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10. Dendrite P systems.
- Author
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Peng, Hong, Bao, Tingting, Luo, Xiaohui, Wang, Jun, Song, Xiaoxiao, Riscos-Núñez, Agustín, and Pérez-Jiménez, Mario J.
- Subjects
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DENDRITES , *NEURONS - Abstract
It was recently found that dendrites are not just a passive channel. They can perform mixed computation of analog and digital signals, and therefore can be abstracted as information processors. Moreover, dendrites possess a feedback mechanism. Motivated by these computational and feedback characteristics, this article proposes a new variant of neural-like P systems, dendrite P (DeP) systems, where neurons simulate the computational function of dendrites and perform a firing–storing process instead of the storing–firing process in spiking neural P (SNP) systems. Moreover, the behavior of the neurons is characterized by dendrite rules that are abstracted by two characteristics of dendrites. Different from the usual firing rules in SNP systems, the firing of a dendrite rule is controlled by the states of the corresponding source neurons. Therefore, DeP systems can provide a collaborative control capability for neurons. We discuss the computational power of DeP systems. In particular, it is proven that DeP systems are Turing-universal number generating/accepting devices. Moreover, we construct a small universal DeP system consisting of 115 neurons for computing functions. • We consider dendrites as information processors. • We propose a new model, dendrite P systems (DeP systems, in short). • We prove that DeP systems are Turing-universal number generating/accepting devices. • We construct a small universal DeP system of 115 neurons for computing functions. [ABSTRACT FROM AUTHOR]
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- 2020
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11. Dynamic threshold neural P systems.
- Author
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Peng, Hong, Wang, Jun, Pérez-Jiménez, Mario J., and Riscos-Núñez, Agustín
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ARTIFICIAL neural networks , *NEUROMORPHICS , *NEURAL circuitry , *ACTION potentials , *ALGORITHMS - Abstract
Abstract Pulse coupled neural networks (PCNN, for short) are models abstracting the synchronization behavior observed experimentally for the cortical neurons in the visual cortex of a cat's brain, and the intersecting cortical model is a simplified version of the PCNN model. Membrane computing (MC) is a kind computation paradigm abstracted from the structure and functioning of biological cells that provide models working in cell-like mode, neural-like mode and tissue-like mode. Inspired from intersecting cortical model, this paper proposes a new kind of neural-like P systems, called dynamic threshold neural P systems (for short, DTNP systems). DTNP systems can be represented as a directed graph, where nodes are dynamic threshold neurons while arcs denote synaptic connections of these neurons. DTNP systems provide a kind of parallel computing models, they have two data units (feeding input unit and dynamic threshold unit) and the neuron firing mechanism is implemented by using a dynamic threshold mechanism. The Turing universality of DTNP systems as number accepting/generating devices is established. In addition, an universal DTNP system having 109 neurons for computing functions is constructed. Highlights • We propose a dynamic threshold neural P systems, inspired from intersecting cortical model. • We prove that Turing universality of dynamic threshold neural P systems as number accepting/generating devices. • We construct an universal dynamic threshold neural P system having 109 neurons for computing functions. [ABSTRACT FROM AUTHOR]
- Published
- 2019
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12. The framework of P systems applied to solve optimal watermarking problem.
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Peng, Hong, Wang, Jun, Pérez-Jiménez, Mario J., and Riscos-Núñez, Agustín
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DIGITAL watermarking , *PARALLEL programs (Computer programs) , *PARAMETER estimation , *SIMULATION methods & models , *CELL membranes , *INFORMATION sharing - Abstract
Abstract: Membrane computing (known as P systems) is a novel class of distributed parallel computing models inspired by the structure and functioning of living cells and organs, and its application to the real-world problems has become a hot topic in recent years. This paper discusses an interesting open problem in digital watermarking domain, optimal watermarking problem, and proposes a new optimal image watermarking method under the framework of P systems. A special membrane structure is designed and its cells as parallel computing units are used to find the optimal watermarking parameters for image blocks. Some cells use the position-velocity model to evolve watermarking parameters of image blocks, while another cell evaluates the objects in the system. In addition to the evolution rules, communication rules are used to exchange and share information between the cells. Simulation experiments on large image set compare the proposed framework with other existing watermarking methods and demonstrate its superiority. [Copyright &y& Elsevier]
- Published
- 2014
- Full Text
- View/download PDF
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