We present OctopuScheduler, the first generalized on-chip scheduling framework for the accelerated inference of non-spiking deep neural networks (DNNs) on the neuromorphic hardware platform SpiNNaker2. The goal of OctopuScheduler is to flexibly support a wide variety of state-of-the-art DNN architectures for different domains, moving from an application-specific custom implementation to a generally applicable framework, simplifying the access to the SpiNNaker2 platform. The on-chip scheduling approach allows to minimize communication latencies with the host, completely controlling the execution of layers for convolutional neural networks (CNNs) and transformer architectures within a single chip.OctopuScheduler as a scheduling framework for classical deep neural networks has the potential to unlock experimentation with large-scale hybrid deep and spiking neural network (SNN) architectures, event-based computing and neuromorphic modifications of classical state-of-the-art DNN architectures on the neuromorphic multi-processor system-on-chip (MPSoC) SpiNNaker2.