The coming age of pervasive data processing

Jan S. Rellermeyer; Sobhan Omranian Khorasani; Dan  Graur; Apourva  Parthasarathy

doi:10.1109/ISPDC.2019.00011

The coming age of pervasive data processing

Jan S. Rellermeyer, Sobhan Omranian Khorasani, Dan Graur, Apourva Parthasarathy

Data-Intensive Systems

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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Abstract

Emerging Big Data analytics and machine learning applications require a significant amount of computational power. While there exists a plethora of large-scale data processing frameworks which thrive in handling the various complexities of data-intensive workloads, the ever-increasing demand of applications have made us reconsider the traditional ways of scaling (e.g., scale-out) and seek new opportunities for improving the performance. In order to prepare for an era where data collection and processing occur on a wide range of devices, from powerful HPC machines to small embedded devices, it is crucial to investigate and eliminate the potential sources of inefficiency in the current state of the art platforms. In this paper, we address the current and upcoming challenges of pervasive data processing and present directions for designing the next generation of large-scale data processing systems.

Original language	English
Title of host publication	2019 18th International Symposium on Parallel and Distributed Computing (ISPDC)
Subtitle of host publication	Proceedings
Editors	Alexandru Iosup, Florin Pop, Radu Prodan, Alexandru Uta
Publisher	IEEE
Pages	58-65
Number of pages	8
ISBN (Electronic)	978-1-7281-3801-5
ISBN (Print)	978-1-7281-3802-2
DOIs	https://doi.org/10.1109/ISPDC.2019.00011
Publication status	Published - 2019
Event	18th International Symposium on Parallel and Distributed Computing, ISPDC 2019 - Amsterdam, Netherlands Duration: 5 Jun 2019 → 7 Jun 2019

Conference

Conference	18th International Symposium on Parallel and Distributed Computing, ISPDC 2019
Country/Territory	Netherlands
City	Amsterdam
Period	5/06/19 → 7/06/19

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care

Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

Big Data
Machine Learning
Systems
Performance
Efficiency

Access to Document

10.1109/ISPDC.2019.00011

08790842Final published version, 1.51 MB

Cite this

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title = "The coming age of pervasive data processing",

abstract = "Emerging Big Data analytics and machine learning applications require a significant amount of computational power. While there exists a plethora of large-scale data processing frameworks which thrive in handling the various complexities of data-intensive workloads, the ever-increasing demand of applications have made us reconsider the traditional ways of scaling (e.g., scale-out) and seek new opportunities for improving the performance. In order to prepare for an era where data collection and processing occur on a wide range of devices, from powerful HPC machines to small embedded devices, it is crucial to investigate and eliminate the potential sources of inefficiency in the current state of the art platforms. In this paper, we address the current and upcoming challenges of pervasive data processing and present directions for designing the next generation of large-scale data processing systems.",

keywords = "Big Data, Machine Learning, Systems, Performance, Efficiency",

author = "Rellermeyer, {Jan S.} and {Omranian Khorasani}, Sobhan and Dan Graur and Apourva Parthasarathy",

note = "Green Open Access added to TU Delft Institutional Repository {\textquoteleft}You share, we take care!{\textquoteright} – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.; 18th International Symposium on Parallel and Distributed Computing, ISPDC 2019 ; Conference date: 05-06-2019 Through 07-06-2019",

year = "2019",

doi = "10.1109/ISPDC.2019.00011",

language = "English",

isbn = "978-1-7281-3802-2",

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publisher = "IEEE",

address = "United States",

}

Rellermeyer, JS, Omranian Khorasani, S, Graur, D & Parthasarathy, A 2019, The coming age of pervasive data processing. in A Iosup, F Pop, R Prodan & A Uta (eds), 2019 18th International Symposium on Parallel and Distributed Computing (ISPDC): Proceedings., 8790842, IEEE, pp. 58-65, 18th International Symposium on Parallel and Distributed Computing, ISPDC 2019, Amsterdam, Netherlands, 5/06/19. https://doi.org/10.1109/ISPDC.2019.00011

The coming age of pervasive data processing. / Rellermeyer, Jan S.; Omranian Khorasani, Sobhan; Graur, Dan et al.
2019 18th International Symposium on Parallel and Distributed Computing (ISPDC): Proceedings. ed. / Alexandru Iosup; Florin Pop; Radu Prodan; Alexandru Uta. IEEE, 2019. p. 58-65 8790842.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AU - Graur, Dan

AU - Parthasarathy, Apourva

N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2019

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N2 - Emerging Big Data analytics and machine learning applications require a significant amount of computational power. While there exists a plethora of large-scale data processing frameworks which thrive in handling the various complexities of data-intensive workloads, the ever-increasing demand of applications have made us reconsider the traditional ways of scaling (e.g., scale-out) and seek new opportunities for improving the performance. In order to prepare for an era where data collection and processing occur on a wide range of devices, from powerful HPC machines to small embedded devices, it is crucial to investigate and eliminate the potential sources of inefficiency in the current state of the art platforms. In this paper, we address the current and upcoming challenges of pervasive data processing and present directions for designing the next generation of large-scale data processing systems.

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KW - Machine Learning

KW - Systems

KW - Performance

KW - Efficiency

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Y2 - 5 June 2019 through 7 June 2019

ER -

The coming age of pervasive data processing

Abstract

Conference

Bibliographical note

Keywords

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