The payload performance of conventional computing systems, from single processors to supercomputers, reached its limits the nature enables. Both the growing demand to cope with "big data" (based on, or assisted by, artificial intelligence) and the interest in understanding the operation of our brain more completely, stimulated the efforts to build biology-mimicking computing systems from inexpensive conventional components and build different ("neuromorphic") computing systems. On one side, those systems require an unusually large number of processors, which introduces performance limitations and nonlinear scaling. On the other side, the neuronal operation drastically differs from the conventional workloads. The conventional computing (including both its mathematical background and physical implementation) is based on assuming instant interaction, while the biological neuronal systems have a "spatiotemporal" behavior. This difference alone makes imitating biological behavior in technical implementation hard. Besides, the recent issues in computing called the attention to that the temporal behavior is a general feature of computing systems, too. Some of their effects in both biological and technical systems were already noticed. Nevertheless, handling of those issues is incomplete/improper. Introducing temporal logic, based on the Minkowski transform, gives quantitative insight into the operation of both kinds of computing systems, furthermore provides a natural explanation of decades-old empirical phenomena. Without considering their temporal behavior correctly, neither effective implementation nor a true imitation of biological neural systems are possible.

中文翻译：

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关于仿生计算系统中的时空行为

传统计算系统的有效载荷性能，从单处理器到超级计算机，都达到了自然允许的极限。应对“大数据”（基于或由人工智能辅助）不断增长的需求以及对更全面了解我们大脑运作的兴趣，都刺激了从廉价的传统组件构建仿生计算系统的努力和构建不同的（“神经形态”）计算系统。一方面，这些系统需要异常多的处理器，这会带来性能限制和非线性扩展。另一方面，神经元操作与传统工作负载截然不同。传统计算（包括其数学背景和物理实现）基于假设即时交互，而生物神经元系统具有“时空”行为。仅这种差异就使得在技术实现中模仿生物行为变得困难。此外，最近的计算问题引起了人们的注意，即时间行为也是计算系统的一般特征。它们在生物和技术系统中的一些影响已经被注意到。然而，对这些问题的处理是不完整/不正确的。引入基于 Minkowski 变换的时间逻辑，可以定量地了解两种计算系统的运行情况，此外还为几十年前的经验现象提供了自然的解释。