ИСТИНА

Resource planning efficiency of HPC-systems is usually de- fined as the utilization of its resources. The number of queued jobs in most modern supercomputer complexes is much bigger than the num- ber of jobs executed at the same moment of time. That high demand and the evolution of widely-used planning algorithms, which can boost utilization up to 0,95 - 1, allow system administrators to more properly manage computational resources and not only meet the needs of cluster owners in maximizing utilization, but also improve customer experience. We conducted a research of the two largest CIS supercomputer systems (Lomonosov and Lomonosov-2) usage history and proposed a new multi- metrics definition of resource planning efficiency concept. In this article, our goal was to compare both approaches and explain why the increased demand for computational resources poses new challenges to the cre- ators of resource planning algorithms and how the proposed approach will improve customer service. Discussed multi-metrics efficiency estima- tion approach is a part of a bigger project, which aims to provide full jobs scheduling eco-system. We examined general architecture of this en- vironment , which will allow to qualitatively change the system settings of the supercomputer job scheduler on the fly and adapt to the changing flow of jobs.