PARAGRAPH: Phase-Aware Resource Demand Profiling for HPDA/HPC Jobs
Ivo Rohwer, Nikolas Roman Herbst, Maximilian Schwinger, Peter Friedl, Michael Stephan, Samuel Kounev · 2025
The processing of large amounts of data in central high performance data analytics (HPDA) systems is playing an increasingly important role in science and business. However, many HPDA systems exhibit a low utilization of their available resources during normal operation. An important reason for this underutilization is that too many resources are reserved for individual jobs. This is often a consequence of the common practice of reserving a uniform amount of resources such as CPU or memory for the entire execution time of a job. Given that many data intensive (DI) jobs consist of different phases with different resource demands, resources are normally reserved according to the demand of the most resource-intensive phase. This results in more resources being reserved over a long period of time than are actually needed.