  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.
