Methodology of measurement for energy consumption of applications

Costa, Georges Da; Hlavacs, Helmut

doi:10.1109/grid.2010.5697987

Cited by 35 publications

(18 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…More recently, Da Costa et al [6] have presented a methodology of measurement of the energy consumption of a single process application running on a standard PC. They defined a set of per process and system-wide variables to demonstrate their accuracy in measuring the energy consumption of a given process using multivariate regression.…”

Section: Power/energy Estimation Using Hardware Performance Countersmentioning

confidence: 99%

“…In studies such as [6][7][8][9][10][11][12] efforts have been devoted to model or estimate the power usage of individual applications or workloads. These studies monitor the use of system's component (in particular the processor and memory) during the workload execution via hardware performance counters and correlate them with the power consumed by the system when running that workload to derive a power model.…”

Section: Power/energy Estimation Using Hardware Performance Countersmentioning

confidence: 99%

See 1 more Smart Citation

Exploiting performance counters to predict and improve energy performance of HPC systems

Chetsa

Lefèvre

Pierson

et al. 2014

Future Generation Computer Systems

View full text Add to dashboard Cite

International audienceHardware monitoring through performance counters is available on almost all modern processors. Although these counters are originally designed for performance tuning, they have also been used for evaluating power consumption. We propose two approaches for modelling and understanding the behaviour of high performance computing (HPC) systems relying on hardware monitoring counters. We evaluate the effectiveness of our system modelling approach considering both optimizing the energy usage of HPC systems and predicting HPC applications’ energy consumption as target objectives. Although hardware monitoring counters are used for modelling the system, other methods–including partial phase recognition and cross platform energy prediction–are used for energy optimization and prediction. Experimental results for energy prediction demonstrate that we can accurately predict the peak energy consumption of an application on a target platform; whereas, results for energy optimization indicate that with no a priori knowledge of workloads sharing the platform we can save up to 24% of the overall HPC system’s energy consumption under benchmarks and real-life workloads

show abstract

Section: Power/energy Estimation Using Hardware Performance Countersmentioning

confidence: 99%

Section: Power/energy Estimation Using Hardware Performance Countersmentioning

confidence: 99%

Exploiting performance counters to predict and improve energy performance of HPC systems

Chetsa

Lefèvre

Pierson

et al. 2014

Future Generation Computer Systems

View full text Add to dashboard Cite

show abstract

“…In CoolEmAll we use an application level estimator based on performance counters, model specific registers (MSR) and system information. It has been shown that calibrated linear models can provide estimation to generic applications with an accuracy error smaller than 10% [41,40]. Performance counters (PC) are CPU counters that quantify the number of events done by the processor per core, e.g.…”

Section: Power Modelmentioning

confidence: 99%

Energy-efficient, thermal-aware modeling and simulation of data centers: The CoolEmAll approach and evaluation results

et al. 2015

Self Cite

View full text Add to dashboard Cite

show abstract

“…In large scale distributed systems, such offline analysis with apriori consumption models do not exist so far. Techniques like [10] start to dynamically relate a set of observed elements on the system to actual power consumption: Performance counters, load average, memory usage, etc. can be mathematically related to power consumption using linear regression techniques for instance.…”

Section: Software Levelmentioning

confidence: 99%

Energy: A New Criteria for Performances in Large Scale Distributed Systems

Pierson

2011

Performance Evaluation of Computer and Communication Systems. Milestones and Future Challenges

View full text Add to dashboard Cite

Abstract. In the framework of the workshop "Performance Evaluation of Computer and Communication Systems: Milestones and Future Challenges", this paper proposes to address the emerging criteria of energy. Used since a long time in embedded systems where battery operated devices needed a careful handling, the energy metric is taking a large momentum in the last years on large scale systems where thousands of nodes collaborate to serve high end infrastructures like web servers, clouds and grids.

show abstract

Methodology of measurement for energy consumption of applications

Cited by 35 publications

References 3 publications

Exploiting performance counters to predict and improve energy performance of HPC systems

Exploiting performance counters to predict and improve energy performance of HPC systems

Energy-efficient, thermal-aware modeling and simulation of data centers: The CoolEmAll approach and evaluation results

Energy: A New Criteria for Performances in Large Scale Distributed Systems

Contact Info

Product

Resources

About