@techreport{oai:ipsj.ixsq.nii.ac.jp:00210011,
 author = {Jiacheng, Zhou and Keiichiro, Fukazawa and Hiroshi, Nakashima and Jiacheng, Zhou and Keiichiro, Fukazawa and Hiroshi, Nakashima},
 issue = {13},
 month = {Mar},
 note = {Modern CPUs suffer from power efficiency heterogeneity, which can result in additional energy cost or performance loss. On the other hand, future supercomputers are expected to be power constraint. This report focuses on energy aware scheduling algorithms target on two situations. In single-node situation, workload consists of various single-node jobs, Combinatorial Optimization Algorithm saves energy by calculating a local optimal allocation plan with KM algorithm. In multi-node situation, power cap causes load unbalancing in multi-node jobs. Sliding Window Algorithm targets on reducing such unbalancing by sliding window. Proposed algorithms are evaluated in the simulation and real supercomputer environment. In single-node situation, Combinatorial Optimization Algorithm achieved up to 2.92% saving. For the multi-node situation, workload is designed based on real historic workload, and up to 5.36% saving was achieved by Sliding Window Algorithm., Modern CPUs suffer from power efficiency heterogeneity, which can result in additional energy cost or performance loss. On the other hand, future supercomputers are expected to be power constraint. This report focuses on energy aware scheduling algorithms target on two situations. In single-node situation, workload consists of various single-node jobs, Combinatorial Optimization Algorithm saves energy by calculating a local optimal allocation plan with KM algorithm. In multi-node situation, power cap causes load unbalancing in multi-node jobs. Sliding Window Algorithm targets on reducing such unbalancing by sliding window. Proposed algorithms are evaluated in the simulation and real supercomputer environment. In single-node situation, Combinatorial Optimization Algorithm achieved up to 2.92% saving. For the multi-node situation, workload is designed based on real historic workload, and up to 5.36% saving was achieved by Sliding Window Algorithm.},
 title = {Energy Aware Scheduler of Single/Multi-node Jobs Exploiting Node Heterogeneity},
 year = {2021}
}