HiAER-Spike: Hardware-Software Co-Design for Large-Scale Reconfigurable Event-Driven Neuromorphic Computing

Gwenevere Frank; Gopabandhu Hota; Keli Wang; Abhinav Uppal; Omowuyi Olajide; Kenneth Yoshimoto; Leif Gibb; Qingbo Wang; Johannes Leugering; Stephen Deiss; Gert Cauwenberghs

arXiv · 2504.03671

HiAER-Spike: Hardware-Software Co-Design for Large-Scale Reconfigurable Event-Driven Neuromorphic Computing

Gwenevere Frank·Gopabandhu Hota·Keli Wang·Abhinav Uppal·Omowuyi Olajide·Kenneth Yoshimoto·Leif Gibb·Qingbo Wang·Johannes Leugering·Stephen Deiss·Gert Cauwenberghs

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Abstract

In this work, we present HiAER-Spike, a modular, reconfigurable, event-driven neuromorphic computing platform designed to execute large spiking neural networks with up to 160 million neurons and 40 billion synapses - roughly twice the neurons of a mouse brain at faster-than real-time. This system, which is currently under construction at the UC San Diego Supercomputing Center, comprises a co-designed hard- and software stack that is optimized for run-time massively parallel processing and hierarchical address-event routing (HiAER) of spikes while promoting memory-efficient network storage and execution. Our architecture efficiently handles both sparse connectivity and sparse activity for robust and low-latency event-driven inference for both edge and cloud computing. A Python programming interface to HiAER-Spike, agnostic to hardware-level detail, shields the user from complexity in the configuration and execution of general spiking neural networks with virtually no constraints in topology. The system is made easily available over a web portal for use by the wider community. In the following we provide an overview of the hard- and software stack, explain the underlying design principles, demonstrate some of the system's capabilities and solicit feedback from the broader neuromorphic community.

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Gwenevere Frank, Gopabandhu Hota, Keli Wang, Abhinav Uppal, Omowuyi Olajide, Kenneth Yoshimoto, Leif Gibb, Qingbo Wang, Johannes Leugering, Stephen Deiss, Gert Cauwenberghs. 2025-03-20. HiAER-Spike: Hardware-Software Co-Design for Large-Scale Reconfigurable Event-Driven Neuromorphic Computing. https://arxiv.org/abs/2504.03671

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