Open AccessAn Overview of Hardware Implementation of Membrane Computing Models
Author(s) -
Gexiang Zhang,
Zeyi Shang,
Sergey Verlan,
Miguel Ángel Martínez del Amor,
Chengxun Yuan,
Luis ValenciaCabrera,
Mario J. Pérez–Jiménez
Publication year - 2020
Publication title -
acm computing surveys
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.079
H-Index - 163
eISSN - 1557-7341
pISSN - 0360-0300
DOI - 10.1145/3402456
Subject(s) - computer science , cuda , field programmable gate array , massively parallel , parallel computing , implementation , computer architecture , membrane computing , parallelism (grammar) , reconfigurable computing , general purpose computing on graphics processing units , field (mathematics) , computational science , embedded system , theoretical computer science , software engineering , graphics , operating system , mathematics , pure mathematics
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.
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