Go Green Radio Astronomy: Approximate Computing Perspective: Opportunities and Challenges: POSTER

Syed Ghayoor Abbas Gillani; Andre B.J. Kokkeler

doi:10.1145/3310273.3323427

Go Green Radio Astronomy: Approximate Computing Perspective: Opportunities and Challenges: POSTER

Syed Ghayoor Abbas Gillani, Andre B.J. Kokkeler

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

Modern radio telescopes require highly energy/power-efficient computing systems. Signal processing pipelines of such radio telescopes are dominated by accumulation based iterative processes. As the input signal received at a radio telescope is regarded as Gaussian noise, employing approximate computing looks promising. Therefore, we present opportunities and challenges offered by the approximate computing paradigm to achieve the required efficiency targets.

Original language	English
Title of host publication	16th ACM International Conference on Computing Frontiers
Publisher	Association for Computing Machinery (ACM)
Pages	300-301
ISBN (Electronic)	978-1-4503-6685-4
DOIs	https://doi.org/10.1145/3310273.3323427
Publication status	Published - 2019
Event	16th ACM International Conference on Computing Frontiers 2019 - Alghero, Italy Duration: 30 Apr 2019 → 2 May 2019 Conference number: 16 http://www.computingfrontiers.org/2019/

Conference

Conference	16th ACM International Conference on Computing Frontiers 2019
Abbreviated title	CF 2019
Country/Territory	Italy
City	Alghero
Period	30/04/19 → 2/05/19
Internet address	http://www.computingfrontiers.org/2019/

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10.1145/3310273.3323427

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title = "Go Green Radio Astronomy: Approximate Computing Perspective: Opportunities and Challenges: POSTER",

abstract = "Modern radio telescopes require highly energy/power-efficient computing systems. Signal processing pipelines of such radio telescopes are dominated by accumulation based iterative processes. As the input signal received at a radio telescope is regarded as Gaussian noise, employing approximate computing looks promising. Therefore, we present opportunities and challenges offered by the approximate computing paradigm to achieve the required efficiency targets.",

author = "Gillani, {Syed Ghayoor Abbas} and Kokkeler, {Andre B.J.}",

year = "2019",

doi = "10.1145/3310273.3323427",

language = "English",

pages = "300--301",

booktitle = "16th ACM International Conference on Computing Frontiers",

publisher = "Association for Computing Machinery (ACM)",

address = "United States",

note = "16th ACM International Conference on Computing Frontiers 2019, CF 2019 ; Conference date: 30-04-2019 Through 02-05-2019",

url = "http://www.computingfrontiers.org/2019/",

}

Gillani, SGA & Kokkeler, ABJ 2019, Go Green Radio Astronomy: Approximate Computing Perspective: Opportunities and Challenges: POSTER. in 16th ACM International Conference on Computing Frontiers. Association for Computing Machinery (ACM), pp. 300-301, 16th ACM International Conference on Computing Frontiers 2019, Alghero, Italy, 30/04/19. https://doi.org/10.1145/3310273.3323427

Go Green Radio Astronomy: Approximate Computing Perspective: Opportunities and Challenges: POSTER. / Gillani, Syed Ghayoor Abbas; Kokkeler, Andre B.J.

16th ACM International Conference on Computing Frontiers. Association for Computing Machinery (ACM), 2019. p. 300-301.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Gillani, Syed Ghayoor Abbas

AU - Kokkeler, Andre B.J.

N1 - Conference code: 16

PY - 2019

Y1 - 2019

N2 - Modern radio telescopes require highly energy/power-efficient computing systems. Signal processing pipelines of such radio telescopes are dominated by accumulation based iterative processes. As the input signal received at a radio telescope is regarded as Gaussian noise, employing approximate computing looks promising. Therefore, we present opportunities and challenges offered by the approximate computing paradigm to achieve the required efficiency targets.

AB - Modern radio telescopes require highly energy/power-efficient computing systems. Signal processing pipelines of such radio telescopes are dominated by accumulation based iterative processes. As the input signal received at a radio telescope is regarded as Gaussian noise, employing approximate computing looks promising. Therefore, we present opportunities and challenges offered by the approximate computing paradigm to achieve the required efficiency targets.

U2 - 10.1145/3310273.3323427

DO - 10.1145/3310273.3323427

M3 - Conference contribution

SP - 300

EP - 301

BT - 16th ACM International Conference on Computing Frontiers

PB - Association for Computing Machinery (ACM)

T2 - 16th ACM International Conference on Computing Frontiers 2019

Y2 - 30 April 2019 through 2 May 2019

ER -

Go Green Radio Astronomy: Approximate Computing Perspective: Opportunities and Challenges: POSTER

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