HiAER-Spike Software-Hardware Reconfigurable Platform for Event-Driven Neuromorphic Computing at Scale

TL;DR

HiAER-Spike is a large-scale, reconfigurable neuromorphic platform that efficiently executes massive spiking neural networks with low latency, suitable for edge and cloud applications, and accessible via a user-friendly web portal.

Contribution

This work introduces HiAER-Spike, a novel modular hardware-software platform capable of running extremely large spiking neural networks at scale and speed, with a user-friendly interface.

Findings

Supports up to 160 million neurons and 40 billion synapses.

Demonstrates real-time event-driven inference on vision and gesture tasks.

Provides an accessible platform for neuromorphic computing research.

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, assembled at the UC San Diego Supercomputer 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. The 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 minimal 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. Examples are shown demonstrating HiAER-Spike's capabilities for event-driven vision on benchmark CIFAR-10, DVS event-based gesture, MNIST, and Pong tasks.