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Large-scale neuromorphic hardware platforms, specialized computer systems for energy efficient simulation of spiking neural networks, are being developed around the world, for example as part of the European Human Brain Project (HBP). Due to conceptual differences, a universal performance analysis of these systems in terms of runtime, accuracy and energy efficiency is non-trivial, yet indispensable for further hard-and software development. In this paper we describe a scalable benchmark baseddoi:10.3389/fncom.2017.00071 pmid:28878642 pmcid:PMC5572441 fatcat:twty25ev65fulcm3f6ftgotztu