HiAER-Spike软件-硬件可重构平台：大规模事件驱动神经形态计算
HiAER-Spike Software-Hardware Reconfigurable Platform for Event-Driven Neuromorphic Computing at Scale
AI总结：
HiAER-Spike平台支持执行多达1.6亿神经元和400亿突触的大型脉冲神经网络，通过模块化可重构架构实现高效事件驱动计算，提供Python接口简化神经网络配置与执行。
摘要：
本文介绍了HiAER-Spike，一个模块化、可重构的事件驱动神经形态计算平台，可执行多达1.6亿神经元和400亿突触的大型脉冲神经网络，其架构优化了运行时大规模并行处理和分层地址事件路由（HiAER），支持稀疏连接和活动的高效处理，适用于边缘和云计算。该系统提供Python接口，屏蔽硬件细节，简化通用脉冲神经网络的配置与执行。平台通过网页门户向社区开放，展示了在CIFAR-10、DVS事件手势、MNIST和Pong任务上的事件驱动视觉能力。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
