The local circuitry of the mammalian brain is a focus of the search for generic computational principles because it is largely conserved across species and modalities. In 2014 a model was proposed representing all neurons and synapses of the stereotypical cortical microcircuit below $1\,\text{mm}^2$ of brain surface. The model reproduces fundamental features of brain activity but its impact remained limited because of its computational demands. For theory and simulation, however, the model was a breakthrough because it removes uncertainties of downscaling, and larger models are less densely connected. This sparked a race in the neuromorphic computing community and the model became a de facto standard benchmark. Within a few years real-time performance was reached and surpassed at significantly reduced energy consumption. We review how the computational challenge was tackled by different simulation technologies and derive guidelines for the next generation of benchmarks and other domains of science.

翻译：哺乳动物大脑的局部回路是探索通用计算原理的焦点，因为它在不同物种和模态间高度保守。2014年，一个模型被提出，该模型代表了大脑表面$1\,\text{mm}^2$以下典型皮层微回路的所有神经元和突触。该模型重现了大脑活动的基本特征，但由于其计算需求巨大，其影响力一直有限。然而对于理论和模拟而言，该模型是一个突破，因为它消除了缩放过程中的不确定性，且更大模型的连接密度更低。这引发了神经形态计算社区的一场竞赛，该模型已成为事实上的标准基准。在几年内，实时性能得以实现并超越，同时能耗显著降低。我们回顾了不同模拟技术如何应对这一计算挑战，并为下一代基准测试及其他科学领域推导指导原则。