  Neuromorphic systems open up opportunities to enlarge the explorative space
for computational research. However, it is often challenging to unite
efficiency and usability. This work presents the software aspects of this
endeavor for the BrainScaleS-2 system, a hybrid accelerated neuromorphic
hardware architecture based on physical modeling. We introduce key aspects of
the BrainScaleS-2 Operating System: experiment workflow, API layering, software
design, and platform operation. We present use cases to discuss and derive
requirements for the software and showcase the implementation. The focus lies
on novel system and software features such as multi-compartmental neurons, fast
re-configuration for hardware-in-the-loop training, applications for the
embedded processors, the non-spiking operation mode, interactive platform
access, and sustainable hardware/software co-development. Finally, we discuss
further developments in terms of hardware scale-up, system usability and
efficiency.
