Hierarchical Machine Learning Model Enhanced with Whale Optimization Algorithm for Predicting High Performance Computing Job Run Times

Accurate prediction of job run times is critical for optimal resource utilization in high performance computing systems. This study presents a hierarchical approach using XGBoost model for job runtime prediction, integrating classification and regression, optimized by Whale Optimization Algorithm.

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Publication Details

Published
2024-12-18
DOI
https://doi.org/10.1109/hipcw63042.2024.00081
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Hierarchical Machine Learning Model Enhanced with Whale Optimization Algorithm for Predicting High Performance Computing Job Run Times

Data Mining and Machine Learning Applications
article

Hierarchical Machine Learning Model Enhanced with Whale Optimization Algorithm for Predicting High Performance Computing Job Run Times

article en

Abstract

Accurate prediction of job run times is critical for optimal resource utilization in high performance computing systems. This study presents a hierarchical approach using XGBoost model for job runtime prediction, integrating classification and regression, optimized by Whale Optimization Algorithm.

Homi Bhabha National Institute (IN), Indira Gandhi Centre for Atomic Research (IN)
Decent work and economic growth
Openalex Percentile: Top 56%
Data Mining and Machine Learning Applications
DOISourceOpenAlex
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Hierarchical Machine Learning Model Enhanced with Whale Optimization Algorithm for Predicting High Performance Computing Job Run Times · (2024) | TGRS Research Map | TGRS