An Overview of Hardware Implementation of Membrane Computing Models

Author:

Zhang Gexiang1ORCID,Shang Zeyi2,Verlan Sergey3,Martínez-del-Amor Miguel Á.4,Yuan Chengxun5,Valencia-Cabrera Luis4,Pérez-Jiménez Mario J.4

Affiliation:

1. Chengdu University of Technology, China and Southwest Jiaotong University, Chengdu, China

2. Southwest Jiaotong University, China and Université Paris-Est Créteil Val de Marne, France

3. Université Paris-Est Créteil Val de Marne, France

4. Universidad de Sevilla, Spain

5. Southwest Jiaotong University, China

Abstract

The model of membrane computing, also known under the name of P systems, is a bio-inspired large-scale parallel computing paradigm having a good potential for the design of massively parallel algorithms. For its implementation it is very natural to choose hardware platforms that have important inherent parallelism, such as field-programmable gate arrays (FPGAs) or compute unified device architecture (CUDA)-enabled graphic processing units (GPUs). This article performs an overview of all existing approaches of hardware implementation in the area of P systems. The quantitative and qualitative attributes of FPGA-based implementations and CUDA-enabled GPU-based simulations are compared to evaluate the two methodologies.

Funder

New Generation Artificial Intelligence Science and Technology Major Project of Sichuan Province

National Natural Science Foundation of China

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

Reference119 articles.

1. Rick Merritt. 2017. Roadmap Says CMOS Ends ~2024. IRDS points to chip stacks new architectures. Retrieved from https://web.archive.org/web/20170324022546/ https://www.eetimes.com/document.asp?doc_id=1331517. Rick Merritt. 2017. Roadmap Says CMOS Ends ~2024. IRDS points to chip stacks new architectures. Retrieved from https://web.archive.org/web/20170324022546/ https://www.eetimes.com/document.asp?doc_id=1331517.

2. Evolving by Maximizing the Number of Rules: Complexity Study

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