生物神经微电路在多核系统上的仿真

I. Muntean, M. Joldos
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引用次数: 4

摘要

我们的研究重点是识别和量化多核并行化策略对峰值神经网络模拟结果稳定性的影响。为了研究生物神经元和突触的行为,我们研究了基于Open mp的峰值响应模型和峰值时间依赖可塑性的实现。底层的神经微电路具有小世界拓扑结构。仿真策略为同步仿真策略。我们遵循的软件开发方法利用了系统单元测试和持续集成,为我们提供了一种验证模拟结果的各种扰动的方法。我们对具有不同多核处理器的系统进行了调查。我们的模拟器的处理速度(峰值/秒)随着内核数量的增加而扩展得很好,但是当在模拟中使用系统的所有内核时,并行效率是中等的(例如,12个内核时为0.57)。这项工作的主要成果有两个方面:一方面,所提出的并行仿真策略显示出一种动态行为,而不受多核特定技术的使用的影响。另一方面,我们分析了在我们的多核模拟方法中遇到的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simulation of Biological Neural Microcircuits on Multi-core Systems
Our research focuses on the identification and quantification of the impact that multi-core parallelization strategies have on the stability of the result of spiking neural networks simulations. We investigated Open MP-based implementations of the Spike Response Model and Spike Time-Dependent Plasticity for studying behaviors of biological neurons and synapses. The underlying neural microcircuits have small-world topologies. The simulation strategy is a synchronous one. The software development methodology we follow makes use of systematic unit testing and continuous integration, giving us a way to verify various perturbations of simulation results. We carried out investigations on systems having different multi-core processors. The processing speed (spikes/second) of our simulator scales well with the number of cores, but the parallel efficiency is moderate when all cores of the system are used in the simulation (0.57 for 12 cores e.g.). The primary outcomes of this work are twofold: One the one hand, the proposed parallel simulation strategies show a dynamic behavior unaltered by the use of multi-core specific technologies. On the other hand, we analyze issues met in our approach to multi-core simulations.
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