Adagio: making DVS practical for complex HPC applications
Adagio: making DVS practical for complex HPC applications
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DOI：
10.1145/1542275.1542340
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发表时间：
2009-06
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影响因子：
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通讯作者：
B. Rountree;D. Lowenthal;B. Supinski;M. Schulz;Vincent W. Freeh;T. Bletsch
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作者：
B. Rountree;D. Lowenthal;B. Supinski;M. Schulz;Vincent W. Freeh;T. Bletsch
在高性能计算中，功率和能量是一阶设计约束。目前使用动态电压缩放（DVS）的研究依赖于以增加的执行时间来节省能源，这对于大多数高性能计算应用来说是不可接受的。我们介绍了Adagio，这是一种新颖的运行时系统，通过在实现显著节能的同时仅产生可忽略不计的延迟，使DVS适用于复杂的、现实世界的科学应用。Adagio改进并扩展了以前最先进的算法，将从静态减少能量的CPU调度中学到的经验教训与用于松弛预测的新颖运行时机制相结合。我们展示了使用Adagio对两个现实世界程序（UMT2K和ParaDiS）以及NAS并行基准套件的结果。虽然不需要修改应用程序源代码，但Adagio为UMT2K和ParaDiS分别提供了8%和20%的系统总能源节约，而执行时间的增加不到1%。
Power and energy are first-order design constraints in high performance computing. Current research using dynamic voltage scaling (DVS) relies on trading increased execution time for energy savings, which is unacceptable for most high performance computing applications. We present Adagio, a novel runtime system that makes DVS practical for complex, real-world scientific applications by incurring only negligible delay while achieving significant energy savings. Adagio improves and extends previous state-of-the-art algorithms by combining the lessons learned from static energy-reducing CPU scheduling with a novel runtime mechanism for slack prediction. We present results using Adagio for two real-world programs, UMT2K and ParaDiS, along with the NAS Parallel Benchmark suite. While requiring no modification to the application source code, Adagio provides total system energy savings of 8% and 20% for UMT2K and ParaDiS, respectively, with less than 1% increase in execution time.