Starting from 2023, during CMS Phase-2, the increased accelerator luminosity with the consequently increased number of simultaneous proton-proton collisions (pile-up) will pose significant new challenges to the CMS experiment. In order to keep and eventually improve the high performance of the current forward detectors, the installation of a new End-cap Calorimeter (EC) is foreseen. Particles traversing the EC, interact with its material producing complex showers of other particles. These particles may interact with sensors and release a certain amount of energy E at a time instant t. Sensors are arranged in a hexagonal-shaped pattern on more than 50 layers. Hence, for each energy deposit in a sensor, 3-D position and time information is available. In each event, more than 300,000 points, contribute to this cloud. Developing clustering algorithms requires a deep understanding of the evolution features in space and time. For this reason, a flexible and high-performance visualization framework is required, as the amount of memory and processing power required for drawing hits, and the hexagonal grid of sensors may exceed the resources available on a machine.
Experience with large data visualization