Runtime Energy Savings Based on Machine Learning Models for Multicore Applications

ISSN Print: 2327-5219
ISSN Online: 2327-5227
www.scirp.net/journal/jcc
E-mail: [email protected]

Citations

"Runtime Energy Savings Based on Machine Learning Models for Multicore Applications"
written by Vaibhav Sundriyal, Masha Sosonkina,
published by Journal of Computer and Communications, Vol.10 No.6, 2022

has been cited by the following article(s):

[1]	Time Series Models for Predicting Application GPU Utilization and Power Draw Based on Trace Data
	2024

[2]	Runtime Power Allocation Based on Multi-GPU Utilization in GAMESS
	Journal of Computer …, 2022

[1]	Hybrid Learning Framework for Explainable Cardiovascular Disease Detection IEEE Access, 2025 DOI:10.1109/ACCESS.2025.3591241

[2]	Time Series Models for Predicting Application GPU Utilization and Power Draw Journal of Computer and Communications, 2025 DOI:10.4236/jcc.2025.1312004

[3]	FCUFS: Core-Level Frequency Tuning for Energy Optimization on Intel Processors 2024 IEEE International Conference on Cluster Computing (CLUSTER), 2024 DOI:10.1109/CLUSTER59578.2024.00026

[4]	Performance Portability of Electron Repulsion Integrals and Their Related Methods across Peta to Exascale Architectures SC24-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, 2024 DOI:10.1109/SCW63240.2024.00244