High-level frameworks for spiking neural networks are a key factor for fast prototyping and efficient development of complex algorithms. Such frameworks have emerged in the last years for traditional computers, but programming neuromorphic hardware is still a challenge. Often low level programming with knowledge about the hardware of the neuromorphic chip is required. The PeleNet framework aims to simplify reservoir computing for the neuromorphic hardware Loihi. It is build on top of the NxSDK from Intel and is written in Python. The framework manages weight matrices, parameters and probes. In particular, it provides an automatic and efficient distribution of networks over several cores and chips. With this, the user is not confronted with technical details and can concentrate on experiments.

翻译：神经神经网络的高级框架是快速原型和复杂算法有效发展的一个关键因素。这种框架是过去几年中传统计算机出现的,但编程神经形态硬件仍是一项挑战。通常需要了解神经形态芯片硬件的低层次程序。PeelNet框架旨在简化神经形态硬件Loihi的储油层计算。这个框架建立在Intel NxSDK之上,以Python书写。这个框架管理重量矩阵、参数和探测器。特别是,它为几个核心和芯片提供自动和高效的网络分布。因此,用户没有遇到技术细节,可以集中研究实验。