Action: A New Metric for Evaluating the Energy Efficiency on High Performance Computing Platforms (ranked on Green500 List)

The need for new and more reliable metrics is always in demand. In this paper, a new metric is proposed for the evaluation of high performance computing platforms in conjunction with their energy consumption. The aim of the new metric is to reliably compare different HPC systems concerning their energy efficiency. The metric provides a mean to rank supercomputers of similar capabilities, avoiding the misleading results of metrics like performance-per-watt, currently used for ranking systems, as in the Green500 list, where systems with totally different sizes and capabilities are ranked consecutively. An example of this misuse for two adjacent systems in the Green500 list, is discussed. A comparative study for the energy efficiency of three high performance computing platforms, with different architectures, using the proposed metric is presented.

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Measuring and tuning energy efficiency on large scale high performance computing platforms.

10.2172/1035312 ◽

2011 ◽

Cited By ~ 1

Author(s):

James H., III Laros

Keyword(s):

Energy Efficiency ◽

High Performance Computing ◽

High Performance ◽

Large Scale ◽

Computing Platforms ◽

Performance Computing

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Energy conscious scheduling with controlled threshold for precedence-constrained tasks on heterogeneous clusters

Concurrent Engineering ◽

10.1177/1063293x16679001 ◽

2016 ◽

Vol 25 (3) ◽

pp. 276-286 ◽

Cited By ~ 5

Author(s):

Nirmal Kaur ◽

Savina Bansal ◽

Rakesh Kumar Bansal

Keyword(s):

Energy Consumption ◽

High Performance Computing ◽

High Performance ◽

Scheduling Algorithm ◽

Voltage Scaling ◽

Dynamic Voltage Scaling ◽

Heterogeneous Cluster ◽

Dynamic Voltage ◽

Computing Platforms ◽

Performance Computing

Efficient task scheduling of concurrent tasks is one of the primary requirements for high-performance computing platforms. Recent advances in high-performance computing have resulted in widespread performance improvement though at the cost of increased energy consumption and other system resources. In this article, an energy conscious scheduling algorithm with controlled threshold has been developed for precedence-constrained tasks on heterogeneous cluster, which aims at lower makespan along with reduced energy consumption. Energy conscious scheduling with controlled threshold algorithm combines the benefits of dynamic voltage scaling with controlled threshold-based duplication strategy to achieve its objectives. Effectiveness of the proposed algorithm is analyzed in comparison with available duplication- and non-duplication-based scheduling algorithms (with and without dynamic voltage scaling approach) to ascertain its performance and energy consumption. Exhaustive simulation results on random and real-world graphs demonstrate that energy conscious scheduling algorithm with controlled threshold has the potential to reduce energy consumption and makespan.

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