Abstract
The brain is naturally a parallel and distributed system. Reverse engineering a cognitive brain is considered to be a grand challenge. In this paper, we present the parallel brain simulator (PBS), a parallel and distributed platform for modeling the cognitive brain at multiple scales. Inspired by large-scale graph computation, PBS can be considered as a universal parallel execution engine, which is aimed at reducing the complexity of distributed programming and providing an easy to use programmable platform for computational neuroscientists and artificial intelligence researchers for modeling and simulation of large-scale neural networks. As illustrative examples and validations, three brain-inspired neural networks which are built on PBS are introduced, including the 1:1 human hippocampus network, the 1:1 mouse whole-brain network and the CASIA brain simulator built for cognitive robotics. We deploy PBS on both commodity clusters and supercomputers, and a scalable performance is achieved. In addition, we provide evaluations on the scalability and performance of both lumped synapse-based simulation and non-lumped synapse-based simulation with different data-graph distribution methods to show the effectiveness and usability of the PBS platform.
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BrainBo: http://bii.ia.ac.cn/brainbo.html.
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Funding
This study was funded by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB02060007) and Beijing Municipal Science and Technology Commission (Z151100000915070).
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Xin Liu, Yi Zeng, Tielin Zhang, and Bo Xu declare that they have no conflict of interest.
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All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2008 (5). Additional informed consent was obtained from all patients for which identifying information is included in this article.
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This article does not contain any studies with human or animal subjects performed by the any of the authors.
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Xin Liu and Yi Zeng contributed equally to this work and serve as co-first authors.
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Liu, X., Zeng, Y., Zhang, T. et al. Parallel Brain Simulator: A Multi-scale and Parallel Brain-Inspired Neural Network Modeling and Simulation Platform. Cogn Comput 8, 967–981 (2016). https://doi.org/10.1007/s12559-016-9411-y
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DOI: https://doi.org/10.1007/s12559-016-9411-y