Since the beginning of information processing by electronic components, the nervous system has served as a metaphor for the organization of computational primitives. Brain-inspired computing today encompasses a class of approaches ranging from using novel nano-devices for computation to research into large-scale neuromorphic architectures, such as TrueNorth, SpiNNaker, BrainScaleS, Tianjic, and Loihi. While implementation details differ, spiking neural networks -- sometimes referred to as the third generation of neural networks -- are the common abstraction used to model computation with such systems. Here we describe the second generation of the BrainScaleS neuromorphic architecture, emphasizing applications enabled by this architecture. It combines a custom analog accelerator core supporting the accelerated physical emulation of bio-inspired spiking neural network primitives with a tightly coupled digital processor and a digital event-routing network.
翻译:自电子元件信息处理开始以来,神经系统一直作为计算原始体组织的一种比喻。今天,脑动计算包含一系列方法,从使用新的纳米装置进行计算到研究大型神经形态结构,如TueNorth、Spinnaker、BrainSeasy、Tianjic和Loihi。虽然实施细节不同,但神经网络(有时被称为第三代神经网络)是用来模拟这些系统计算的共同抽象。这里我们描述了第二代脑空间系统神经形态结构,强调这一结构所促成的应用。它将一种定制的模拟加速物理模拟生物激励型神经网络原始体与紧密结合的数字处理器和数字事件路径网络结合起来。