Speaker
Description
Electrons are one of the key particles that are detected by the CMS experiment and are reconstructed using the CMS software (CMSSW). Reconstructing electrons in CMSSW is a computational intensive task that is split into several steps, seeding being the most time consuming one. During the electron seeding process, the collection of tracker hits (seeds) is significantly reduced by selecting only seeds that are compatible with a hypothesized electron trajectory. This contribution will describe the process of redesigning the electron seeding algorithm in a parallelizable way that will exploit the massive parallelism that GPUs can offer. The new algorithm code base is implemented using the Alpaka library, a performance portability library that allows having a single code base for execution on different types of hardware.
