A job shaping strategy to accomodate workload traces under varying resource management policies

Supercomputers play a pivotal role in advancing research and development across diverse scientific and engineering domains. However, configuring resource management in these systems to ensure maximum productivity and cost-effectiveness is a challenge. Workload simulation emerges as a crucial tool in this context, offering a mechanism to explore resource management configurations in the presence of expected user behaviors. This paper focuses on a specific requirement for simulation-based optimization applied to tuning resource management configurations: the need for simulators that are both precise and efficient. This paper introduces a job shaping strategy to accommodate real workload traces under varying resource management policies in discrete-event RMS simulations. Our findings from evaluating the proposed strategy on a real-world case study suggest that job shaping allows effectively capturing changes in system behavior, regardless of whether some of the real workload traces used as input to the simulation are incompatible with the simulated policies.