Run-Time Interoperability Between Neuronal Network Simulators Based on the MUSIC Framework
Run-Time Interoperability Between Neuronal Network Simulators Based on the MUSIC Framework
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DOI：
10.1007/s12021-010-9064-z
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发表时间：
2010-03-01
期刊：
影响因子：
3
通讯作者：
Ekeberg, Orjan
中科院分区：
文献类型：
--
作者：
Djurfeldt, Mikael;Hjorth, Johannes;Ekeberg, Orjan
音乐是一种标准API，允许大规模神经元模拟器在运行时在并行计算机中交换数据。该API的试点实施已被发布为开源。我们提供从两种不同类型的Nest and Moose的神经元网络模拟器的音乐接口实现的经验。执行了涉及两个模拟器的皮质 - 纹状体网络模型的多模拟，这表明音乐如何在为不同模拟器编写的模型之间促进互操作性，以及如何将它们重新使用以构建较大的模型系统。基准测试表明，音乐飞行员实施提供了具有良好缩放的群集计算机中有效的数据传输。我们得出的结论是，音乐实现了设计目标，即适应现有的模拟器使用音乐应该很容易。此外，由于音乐API可以实现应用程序的独立性，因此可以根据模拟时间步长或模块之间的连接拓扑来构建多个仿真，而无需将组件彼此改编而成。
MUSIC is a standard API allowing large scale neuron simulators to exchange data within a parallel computer during runtime. A pilot implementation of this API has been released as open source. We provide experiences from the implementation of MUSIC interfaces for two neuronal network simulators of different kinds, NEST and MOOSE. A multi-simulation of a cortico-striatal network model involving both simulators is performed, demonstrating how MUSIC can promote inter-operability between models written for different simulators and how these can be re-used to build a larger model system. Benchmarks show that the MUSIC pilot implementation provides efficient data transfer in a cluster computer with good scaling. We conclude that MUSIC fulfills the design goal that it should be simple to adapt existing simulators to use MUSIC. In addition, since the MUSIC API enforces independence of the applications, the multi-simulation could be built from pluggable component modules without adaptation of the components to each other in terms of simulation time-step or topology of connections between the modules.