Assessing FIFO and Round Robin Scheduling:Effects on Data Pipeline Performance and Energy Usage

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Hauptverfasser: Choudhury, Malobika Roy, Mehrotra, Akshat
Format: Preprint
Veröffentlicht: 2024
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author Choudhury, Malobika Roy
Mehrotra, Akshat
author_facet Choudhury, Malobika Roy
Mehrotra, Akshat
contents In the case of compute-intensive machine learning, efficient operating system scheduling is crucial for performance and energy efficiency. This paper conducts a comparative study over FIFO(First-In-First-Out) and RR(Round-Robin) scheduling policies with the application of real-time machine learning training processes and data pipelines on Ubuntu-based systems. Knowing a few patterns of CPU usage and energy consumption, we identify which policy (the exclusive or the shared) provides higher performance and/or lower energy consumption for typical modern workloads. Results of this study would help in providing better operating system schedulers for modern systems like Ubuntu, working to improve performance and reducing energy consumption in compute intensive workloads.
format Preprint
id arxiv_https___arxiv_org_abs_2409_15704
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Assessing FIFO and Round Robin Scheduling:Effects on Data Pipeline Performance and Energy Usage
Choudhury, Malobika Roy
Mehrotra, Akshat
Operating Systems
In the case of compute-intensive machine learning, efficient operating system scheduling is crucial for performance and energy efficiency. This paper conducts a comparative study over FIFO(First-In-First-Out) and RR(Round-Robin) scheduling policies with the application of real-time machine learning training processes and data pipelines on Ubuntu-based systems. Knowing a few patterns of CPU usage and energy consumption, we identify which policy (the exclusive or the shared) provides higher performance and/or lower energy consumption for typical modern workloads. Results of this study would help in providing better operating system schedulers for modern systems like Ubuntu, working to improve performance and reducing energy consumption in compute intensive workloads.
title Assessing FIFO and Round Robin Scheduling:Effects on Data Pipeline Performance and Energy Usage
topic Operating Systems
url https://arxiv.org/abs/2409.15704