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Changing computing paradigms towards power efficiency

机译:改变计算范式以提高能效

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摘要

Power awareness is fast becoming immensely important in computing, ranging from the traditional high-performance computing applications to the new generation of data centric workloads. In this work, we describe our efforts towards a powerefficient computing paradigm that combines lowand high-precision arithmetic.We showcase our ideas for the widely used kernel of solving systems of linear equations that finds numerous applications in scientific and engineering disciplines as well as in large-scale data analytics, statistics and machine learning. Towards this goal, we developed tools for the seamless power profiling of applications at a finegrain level. In addition, we verify here previous work on post-FLOPS/W metrics and show that these can shed much more light in the power/energy profile of important applications.
机译:从传统的高性能计算应用程序到新一代以数据为中心的工作负载,电源意识在计算中正变得越来越重要。在这项工作中,我们描述了我们致力于将低端和高精度算术相结合的高效计算范例的努力。我们展示了关于广泛使用的线性方程组求解核心的思想,该思想在科学和工程学科以及大型学科中都有大量应用规模的数据分析,统计和机器学习。为了实现这一目标,我们开发了用于在细粒度级别对应用程序进行无缝电源配置的工具。此外,我们在这里验证了先前关于FLOPS / W指标的工作,并表明这些可以为重要应用的功率/能量分布图提供更多启示。

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