An Efficient Parallel Implementation of CPU Scheduling Algorithms Using Data Parallel Algorithms
| Autor: | Suvigya Agrawal, Disha Parwani, Aishwarya Yadav, Veena Mayya |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
010304 chemical physics
business.industry Data parallelism Computer science Parallel algorithm Usability 02 engineering and technology ComputerSystemsOrganization_PROCESSORARCHITECTURES 01 natural sciences Power (physics) CUDA 0103 physical sciences 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Graphics business Algorithm ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | International Conference on Advanced Computing Networking and Informatics ISBN: 9789811326721 |
| DOI: | 10.1007/978-981-13-2673-8_45 |
| Popis: | 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). |
| Databáze: | OpenAIRE |
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