most citedImproving the Efficiency of a Deep Reinforcement Learning-Based Power Management System for HPC Clusters Using Curriculum Learning

6 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

2 papers

cs.DC2025

SPARS: A Reinforcement Learning-Enabled Simulator for Power Management in HPC Job Scheduling

Muhammad Alfian Amrizal, Raka Satya Prasasta, Santana Yuda Pradata +3

High-performance computing (HPC) systems consume enormous amounts of energy, with idle nodes as a major source of energy waste. Powering down idle nodes can mitigate this problem,…

cs.DC2025★ 6 cited

Improving the Efficiency of a Deep Reinforcement Learning-Based Power Management System for HPC Clusters Using Curriculum Learning

Thomas Budiarjo, Santana Yuda Pradata, Kadek Gemilang Santiyuda +3

High energy consumption remains a key challenge in high-performance computing (HPC) systems, which often feature hundreds or thousands of nodes drawing substantial power even in id…