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Influence of YARN schedulers on power consumption and processing time for various big data benchmarks

Drypczewski Krzysztof, Proficz Jerzy, Stepnowski Andrzej

TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk

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2018

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Vol. 22, No 4

303--312

EN

Climate change caused by human activities can influence the lives of everybody on the planet. The environmental concerns must be taken into consideration by all fields of study includingICT. Green Computing aims to reduce negative effects of IT on the environment while, at the same time, maintaining all of the possible benefits it provides. Several Big Data platforms like Apache Spark or YARN have become widely used in analytics and High-Performance Computing systems due to the reliability and usability of Map Reduce implementations. The authors research the power consumption and energy efficiency of Hadoop YARN schedulers using Apache Spark under three different workloads. The test cases include: sorting large binary files,counting unique words in large text files and processing satellite imagery from the Sentinel-2mission. The presented results show small (2%–11%) but distinct differences in the power consumption of FIFO and FAIR schedulers.

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Probabilistic and Fuzzy Process Classifiers for Operating Systems Scheduler

Bagchi S.

Fundamenta Informaticae

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2016

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Vol. 145, nr 4

405--427

EN

The schedulers residing in kernel of Operating Systems employ patterns of resource affinities of concurrent processes in order to make scheduling decisions. The scheduling decisions affect overall resource utilization in a system. Moreover, the resource affinity patterns of a process may not be possible to profile statically in all cases. This paper proposes a novel probabilistic estimation model and a classifier algorithm to queuing processes based on respective resource affinities. The proposed model follows probabilistic estimation using execution traces, which can be either online or statically profiled. The algorithm tracks the resource affinities of processes based on periodic estimation and classifies the processes accordingly for scheduling. The effects of variations of estimation periods are investigated and fuzzy refinements are introduced. Experimental results indicate that the classifier algorithm successfully determines resource affinities of a set of processes online. However, the algorithm can determine inherent affinity pattern of a process in the presence of uniform distribution having enhanced IO frequency.

3

Data intensive scientific analysis with grid computing

Terzo O., Mossucca L., Cucca M., Notarpietro R.

International Journal of Applied Mathematics and Computer Science

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2011

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Vol. 21, no 2

219-228

EN

At the end of September 2009, a new Italian GPS receiver for radio occultation was launched from the Satish Dhawan Space Center (Sriharikota, India) on the Indian Remote Sensing OCEANSAT-2 satellite. The Italian Space Agency has established a set of Italian universities and research centers to implement the overall processing radio occultation chain. After a brief description of the adopted algorithms, which can be used to characterize the temperature, pressure and humidity, the contribution will focus on a method for automatic processing these data, based on the use of a distributed architecture. This paper aims at being a possible application of grid computing for scientific research.

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Linux Scheduler Improvement for Time Demanding Network Applications, Running on Communication Platform Systems

Hasse M., Nowicki K.

Journal of Telecommunications and Information Technology

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2009

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nr 2

63-69

EN

Communication platform systems as, e.g., advanced telecommunication computing architecture (ATCA) standard blades located in standardized chassis, provides high level communication services between system peripherals. Each ATCA blade brings dedicated functionality to the system but can as well exist as separated host responsible for servicing set of task. According to platform philosophy these parts of system can be quite independent against another solutions provided by competitors. Each system design can be different and can face with many computer systems design problems. One of the most difficult design problems to solve is system integration with a set of components running on different operating system levels. This paper presents Linux scheduler improvement possibility to make user space application classified as time demanding (required to be serviced by CPU in given amount of time) running in user space together with complicated kernel software structure in the system.