Analysis Towards Energy-Aware Image-based In Situ Visualization on the Fugaku

Abstract

Energy efficiency has become a serious concern when running applications on HPC systems. Although these systems were designed to mainly run simulation codes as fast as possible, due to the ever-increasing size of the simulation outputs, the in situ visualization has gained increasing attention. In situ visualization uses the same HPC system to execute a part or even the entire visualization processing, and there are currently a variety of tools and libraries, that facilitate domain scientists to integrate them with their simulation codes. Among different approaches, image- and video-based in situ visualization has been widely adopted as an effective approach for the subsequent offline visual analysis. In this approach, a large number of renderings are required at every visualization time step and can consume a considerable computational resource. Fugaku adopted PowerAPI which enables the users to set the power mode for their jobs. However, simulation and visualization codes may have different processing behaviors requiring different power settings for obtaining the most energy-efficient runnings. In this work, we tried to shed light on the energy efficiency of the visualization portion that was not considered before. We investigated the computational cost and energy consumption of some rendering techniques by using the PowerAPI and KVS (Kyoto Visualization System) on the Fugaku, and hope that the obtained findings will be useful for potential users looking to run in situ visualization on the Fugaku and other PowerAPI-enabled HPC systems.