ИСТИНА

The effective mastering of extremely parallel HPC system is impossible without deep understanding of all internal processes and behavior of the whole diversity of the components: computing processors and nodes, memory usage, interconnect, storage, whole software stack, cooling and so forth in detail. There are numerous visualization tools that provide information on certain components and system as a whole, but most of them have severe issues that limit appliance in real life, thus becoming inacceptable for the future system scales. Predefined monitoring systems and data sources, lack of dynamic on-the-fly reconfiguration, inflexible visualization and screening options are among most popular issues. The proposed approach to monitoring data processing resolves the majority of known problems providing a scalable and flexible solution based on any available monitoring systems and other data sources. The approach implementation is successfully used in every-day practice of the largest in Russia supercomputer center of Moscow State University.