Abstract
Spiking neural P systems (in short, SN P systems) is a class of distributed parallel computing models. Parallel computation of matrix operations has been supported on some new computing devices such as GPU, which provides a promising way to simulate the parallel computation of SN P systems. In this paper a matrix representation method of parallel computation for SN P systems is developed. In firing mechanism of SN P systems, the delay factor plays the role of controlling the receiving of spikes in neurons and the opportunity of emitting the spikes after the firing. In order to achieve the parallel computation of SN P systems, several matrices or vectors are introduced to decompose the firing mechanism of neurons. The parallel computation procedure of SN P systems can be achieved by the operations of the matrices or vectors. Two examples are used to illustrate the parallel computation procedure using the matrix operations.
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Acknowledgements
This work was partially supported by the National Natural Science Foundation of China (No. 61472328), Research Fund of Sichuan Science and Technology Project (No. 2015HH0057) and the key equipment project of Sichuan Provincial Economic and Information Committee (No. [2014]128), China.
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Hu, J., Chen, G., Peng, H., Wang, J., Huang, X., Luo, X. (2016). Matrix Representation of Parallel Computation for Spiking Neural P Systems. In: Gong, M., Pan, L., Song, T., Zhang, G. (eds) Bio-inspired Computing – Theories and Applications. BIC-TA 2016. Communications in Computer and Information Science, vol 681. Springer, Singapore. https://doi.org/10.1007/978-981-10-3611-8_18
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