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Finally, how many efficiencies supercomputers have? And, what do they measure?
arXiv - CS - Performance Pub Date : 2020-01-05 , DOI: arxiv-2001.01266
J\'anos V\'egh

Using an extremely large number of processing elements in computing systems leads to unexpected phenomena, such as different efficiencies of the same system for different tasks, that cannot be explained in the frame of classical computing paradigm. The simple non-technical (but considering the temporal behavior of the components) model, introduced here, enables us to set up a frame and formalism, needed to explain those unexpected experiences around supercomputing. Introducing temporal behavior into computer science also explains why only the extreme scale computing enabled us to reveal the experienced limitations. The paper shows, that degradation of efficiency of parallelized sequential systems is a natural consequence of the classical computing paradigm, instead of being an engineering imperfectness. The workload, that supercomputers run, is much responsible for wasting energy, as well as limiting the size and type of tasks. Case studies provide insight, how different contributions compete for dominating the resulting payload performance of a computing system, and how enhancing the interconnection technology made computing+communication to dominate in defining the efficiency of supercomputers. Our model also enables to derive predictions about supercomputer performance limitations for the near future, as well as it provides hints for enhancing supercomputer components. Phenomena experienced in large-scale computing show interesting parallels with phenomena experienced in science, more than a century ago, and through their studying a modern science was developed.

中文翻译:

最后,超级计算机有多少效率?而且,他们测量什么?

在计算系统中使用极其大量的处理元件会导致意想不到的现象,例如同一系统对不同任务的效率不同,这在经典计算范式的框架中是无法解释的。此处介绍的简单的非技术性(但考虑到组件的时间行为)模型使我们能够建立一个框架和形式主义,以解释围绕超级计算的那些意外体验。将时间行为引入计算机科学也解释了为什么只有极端规模的计算才能让我们揭示所经历的局限性。该论文表明,并行化顺序系统的效率下降是经典计算范式的自然结果,而不是工程缺陷。超级计算机运行的工作负载,浪费能源,以及限制任务的规模和类型。案例研究提供了洞察力,不同的贡献如何竞争主导计算系统的最终有效载荷性能,以及增强互连技术如何使计算+通信在定义超级计算机的效率方面占主导地位。我们的模型还能够预测不久的将来超级计算机的性能限制,并为增强超级计算机组件提供提示。在大规模计算中经历的现象与一个多世纪前在科学中经历过的现象有着有趣的相似之处,通过他们的研究,现代科学得以发展。不同的贡献如何竞争主导计算系统的最终有效载荷性能,以及增强互连技术如何使计算+通信在定义超级计算机的效率方面占据主导地位。我们的模型还能够预测不久的将来超级计算机的性能限制,并为增强超级计算机组件提供提示。在大规模计算中经历的现象与一个多世纪前在科学中经历过的现象有着有趣的相似之处,通过他们的研究,现代科学得以发展。不同的贡献如何竞争主导计算系统的最终有效载荷性能,以及增强互连技术如何使计算+通信在定义超级计算机的效率方面占据主导地位。我们的模型还能够预测不久的将来超级计算机的性能限制,并为增强超级计算机组件提供提示。在大规模计算中经历的现象与一个多世纪前在科学中经历过的现象有着有趣的相似之处,通过他们的研究,现代科学得以发展。我们的模型还能够预测不久的将来超级计算机的性能限制,并为增强超级计算机组件提供提示。在大规模计算中经历的现象与一个多世纪前在科学中经历过的现象有着有趣的相似之处,通过他们的研究,现代科学得以发展。我们的模型还能够预测不久的将来超级计算机的性能限制,并为增强超级计算机组件提供提示。在大规模计算中经历的现象与一个多世纪前在科学中经历过的现象有着有趣的相似之处,通过他们的研究,现代科学得以发展。
更新日期:2020-09-29
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