Optimization of energy and emissions in high-performance grid computing data centres

At an early stage of information and communications technology and high-performance computing, performance and reliability were two important factors in research and development. It was highly essential that the hardware was able to function adequately, performing strategic operations. Energy consumption was not considered as a serious topic, since the technical characteristics of hardware and software were limited and the amount of computing nodes in a computing cluster, i.e., a data centre was small. Gradually the situation has evolved a lot: nowadays there are multiple data centres located in geographically diverse locations and the software has become more complex. Modern data centres are equipped with a large amount of computing nodes having vast computing power. However, all this progress has not come without a price, since more computing power equals more total power consumption. Consequently, energy consumption has become a major topic nowadays. This work presents two algorithms for optimizing energy and emissions in high-performance grid computing, in which multiple data centres are interconnected to each other. The algorithms are validated in a simulation environment by comparing them to standard round-robin algorithm. Our simulation experiments show that the solution is able to reduce energy consumption and emissions drastically without increase in job turnaround or wait time.