An Efficient Parallel Implementation of CPU Scheduling Algorithms Using Data Parallel Algorithms

Suvigya Agrawal, Aishwarya Yadav, Disha Parwani, Veena Mayya

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Modern graphics processors provide high processing power, and furthermore, frameworks like CUDA increase their usability as high-performance co-processors for general-purpose computing. The Graphical Processing Units (GPUs) can be easily programmed using CUDA. This paper presents an efficient parallel implementation of CPU scheduling algorithms on modern The Graphical Processing Units (GPUs). The proposed method achieves high speed by efficiently exploiting the data parallelism computing of the The Graphical Processing Units (GPUs).

Original languageEnglish
Title of host publicationInternational Conference on Advanced Computing Networking and Informatics - ICANI-2018
EditorsRaj Kamal, Pramod S. Nair, Michael Henshaw
PublisherSpringer Verlag
Pages429-438
Number of pages10
ISBN (Print)9789811326721
DOIs
Publication statusPublished - 01-01-2019
Externally publishedYes
EventInternational Conference on Advanced Computing, Networking and Informatics, ICANI 2018 - Indore, India
Duration: 22-02-201824-02-2018

Publication series

NameAdvances in Intelligent Systems and Computing
Volume870
ISSN (Print)2194-5357

Conference

ConferenceInternational Conference on Advanced Computing, Networking and Informatics, ICANI 2018
CountryIndia
CityIndore
Period22-02-1824-02-18

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Agrawal, S., Yadav, A., Parwani, D., & Mayya, V. (2019). An Efficient Parallel Implementation of CPU Scheduling Algorithms Using Data Parallel Algorithms. In R. Kamal, P. S. Nair, & M. Henshaw (Eds.), International Conference on Advanced Computing Networking and Informatics - ICANI-2018 (pp. 429-438). (Advances in Intelligent Systems and Computing; Vol. 870). Springer Verlag. https://doi.org/10.1007/978-981-13-2673-8_45