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