Distributed and Parallel Computing Systems
Open access
Peer reviewed
Abstract
Abstract
Large-scale parallel and distributed systems are becoming increasingly vulnerable to failures and energy efficiency is one of the most important limitations in the high-performance computing environment. This paper introduces a dynamic framework for energy-efficient reliability management which is based on lightweight monitoring, hierarchical fault recovery, and dynamic decision making in terms of checkpointing, replication, and task migration. The proposed framework is a dynamic, reliable-energy balanced model through the use of three complementary algorithms of ERARO, HLARO, and RACIO in a closed-loop running system. Experimental validation of cluster-based MPI workload reveals that the framework minimizes energy use, restricts execution overhead and retains a high recovery efficiency which provides a viable and scalable solution to the current HPC and distributed systems.
Direct answer
What can I do from this paper page?
Use this page to scan "Adaptive runtime framework for energy-efficient fault tolerance in large-scale distributed and high-performance computing systems" quickly: start with the summary and abstract, then check the authors, source, topics, and related papers. From here, open Scollr to follow Distributed and Parallel Computing Systems research, save the paper, or map adjacent work.
Research areas
Follow related topics
Citation
BibTeX
@article{Kanimozhi2026Adaptive,
title = {Adaptive runtime framework for energy-efficient fault tolerance in large-scale distributed and high-performance computing systems},
author = {R. Kanimozhi and C Selvarathi and Sandra Johnson},
journal = {Scientific Reports},
year = {2026},
doi = {10.1038/s41598-026-64842-9},
url = {https://doi.org/10.1038/s41598-026-64842-9}
}FAQ
Using this paper in a discovery workflow
How do I find related work for this paper?
Use the related papers and topic links on this page as starting points. In Scollr, you can also open the paper and build a literature map around its references, citing papers, and related work.
How can I keep up with new Distributed and Parallel Computing Systems research papers?
Follow Distributed and Parallel Computing Systems research in Scollr. New papers from the topic flow into a personalized feed, and you can save useful studies to revisit later.
Can I cite this paper from this page?
This page includes a static BibTeX block for Adaptive runtime framework for energy-efficient fault tolerance in large-scale distributed and high-performance computing systems. Always verify the DOI, source, and publication details against the publisher record before submitting a manuscript.
Follow this research in Scollr
Follow the topics and authors behind this paper, save useful studies, and build a literature map when you are ready to go deeper.
Get the app