Speaker
Description
The mkFit algorithm offers an implementation of the Kalman filter-based track reconstruction algorithm that exploits both thread- and data-level parallelism. mkFit has been adopted by the CMS collaboration as the main track building algorithm for both the Run-3 offline and online track reconstruction, and it has been to speed up track building by 3.5x on average, while retaining or improving the physics performance. The reconstructed tracks are eventually fitted using legacy algorithms. As a consequence of the speedup in track building from mkFit, track fitting has now become a comparably significant component of the overall tracking time. Given the increased demands of the High-Luminosity Large Hadron Collider (HL-LHC), further speedup can be obtained via the extension of mkFit to the fitting task. Initial measurements of mkFit-based fitting within several CMS HL-LHC High Level Trigger (HLT) configurations demonstrate a speedup of about 4x for this task, showing promise for the mkFit fitting to be deployed in both HLT and offline track reconstruction during Run 4 of the LHC. We present preliminary results of track reconstruction using mkFit for track fitting, based on CMS Phase-2 realistic simulations.