The first-generation of BrainScaleS, also referred to as BrainScaleS-1, is a neuromorphic system for emulating large-scale networks of spiking neurons. Following a "physical modeling" principle, its VLSI circuits are designed to emulate the dynamics of biological examples: analog circuits implement neurons and synapses with time constants that arise from their electronic components' intrinsic properties. It operates in continuous time, with dynamics typically matching an acceleration factor of 10000 compared to the biological regime. A fault-tolerant design allows it to achieve wafer-scale integration despite unavoidable analog variability and component failures. In this paper, we present the commissioning process of a BrainScaleS-1 wafer module, providing a short description of the system's physical components, illustrating the steps taken during its assembly and the measures taken to operate it. Furthermore, we reflect on the system's development process and the lessons learned to conclude with a demonstration of its functionality by emulating a wafer-scale synchronous firing chain, the largest spiking network emulation ran with analog components and individual synapses to date.
翻译:BrainScaleS的第一代,也称为BrainScaleS-1,是一种神经形态学系统,可模拟大规模的脉冲神经元网络。其VLSI电路按照“物理建模”原理设计,模拟生物样本的动力学:模拟电路使用时间常数实现具有由其电子组件固有特性产生的时间常数的神经元和突触。它在连续时间中运作,其动态通常与生物体制相比达到10000倍的加速度因子。容错设计使其在避免不可避免的模拟变异和组件故障的情况下实现了晶片尺度的集成。在本文中,我们介绍了BrainScaleS-1晶片模块的投入过程,提供了系统物理组件的简短描述,说明了其组装和运行的步骤和措施。此外,我们还反思了系统的开发过程和所学到的经验教训,并通过模拟一个晶片规模的同步射击链来演示其功能,这是到目前为止使用模拟组件和单个突触运行的最大脉冲网络仿真。