Energy-efficient computations on a group of clusters

The problem of scheduling parallel tasks on a group of geographically distributed clusters optimizing energy-efficiency of computations is considered. Some scheduling algorithms are proposed and experimentally investigated. Methods for reducing the energy consumption of a uniform computer cluster due to flexible control strategies of the node states (waking them up or shutting down) and of the execution order of the awaiting tasks are considered. A software system developed in the Institute for System Programming of the Russian Academy of Sciences (ISP RAS) for the dynamic control of nodes in order to reduce the energy consumption is described. Several strategies for controlling the states of the nodes are proposed and investigated. Our simulation showed that when the average density of tasks is 0.5, the energy saving is about 10%. When the density of the flow of tasks decreases, the effect of using the proposed system drastically increases: when the average density is 0.3, the saving is 30%; when the average density is 0.2, the saving is 50%; and when the average density is 0.1, the saving is 70%.