4.7 Article

An Overview of Hardware Implementation of Membrane Computing Models

期刊

ACM COMPUTING SURVEYS
卷 53, 期 4, 页码 -

出版社

ASSOC COMPUTING MACHINERY
DOI: 10.1145/3402456

关键词

Membrane computing; P systems; hardware implementation; field programmable gate array (FPGA); compute unified device architecture (CUDA); graphic processing unit (GPU)

资金

  1. National Natural Science Foundation of China [61972324, 61672437, 61702428]
  2. Beijing Advanced Innovation Center for Intelligent Robots and Systems [2019IRS14]
  3. Artificial Intelligence Key Laboratory of Sichuan Province [2019RYJ06]
  4. New Generation Artificial Intelligence Science and Technology Major Project of Sichuan Province [2018GZDZX0043]
  5. Sichuan Science and Technology Program [2018GZ0086]
  6. MABICAP [TIN2017-89842-P]
  7. Fondo Europeo de Desarrollo Regional (FEDER) of the European Union
  8. Ministerio de Economia, Industria y Competitividad (MINECO) of Spain, through the Agencia Estatal de Investigacion (AEI)

向作者/读者索取更多资源

TThe 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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