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超越Amdahl定律的冒险:如何在大规模驱动服务器和超级计算机设计中进行功率性能测量和建模

Adventures Beyond Amdahl's Law: How Power-Performance Measurement and Modeling at Scale Drive Server and Supercomputer Design

  • 摘要: Amdahl定律(阿姆达尔定律)意味着并行性是有限的,其潜在的加速比也是如此。Amdahl的贡献具有开创性,同时也非常重要,它让其他从事并行处理的学者更清晰地说明为什么大规模系统对我们的未来至关重要,以及它们如何从根本上提供了超越Amdahl预测的加速比的机会。在二十一世纪初,与Amdahl极为相似地,我们预测了由于功率的限制而导致的大规模系统的严峻后果。尽管我们早期的研究经常被忽视,部分学者仍清楚地意识到:功率终将限制性能。在本文的回顾中,我们讨论了大规模功率性能测量和建模是如何在长达10多年里推动了服务器和超级计算机的设计。这些技术带来的影响在当前是毫无争议的,我们讨论了它们之间的联系、局限性,以及业界继续获得性能提升所必需的其它研究方向。

     

    Abstract: Amdahl’s Law painted a bleak picture for large-scale computing. The implication was that parallelism was limited and therefore so was potential speedup. While Amdahl’s contribution was seminal and important, it drove others vested in parallel processing to define more clearly why large-scale systems are critical to our future and how they fundamentally provide opportunities for speedup beyond Amdahl’s predictions. In the early 2000s, much like Amdahl, we predicted dire consequences for large-scale systems due to power limits. While our early work was often dismissed, the implications were clear to some: power would ultimately limit performance. In this retrospective, we discuss how power-performance measurement and modeling at scale led to contributions that have driven server and supercomputer design for more than a decade. While the influence of these techniques is now indisputable, we discuss their connections, limits and additional research directions necessary to continue the performance gains our industry is accustomed to.

     

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