5 papers · 1 filter
Speeding up Particle Track Reconstruction using a Parallel Kalman Filter Algorithm
Steven Lantz, Kevin McDermott, Michael Reid +16
One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is determining the trajectory of charged particles during event…
Reconstruction of Charged Particle Tracks in Realistic Detector Geometry Using a Vectorized and Parallelized Kalman Filter Algorithm
Giuseppe Cerati, Peter Elmer, Brian Gravelle +14
One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is finding and fitting particle tracks during event reconstruct…
Reconstruction for Liquid Argon TPC Neutrino Detectors Using Parallel Architectures
Sophie Berkman, Giuseppe Cerati, Brian Gravelle +3
Neutrinos are particles that interact rarely, so identifying them requires large detectors which produce lots of data. Processing this data with the computing power available is be…
Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Architectures with the CMS Detector
Giuseppe Cerati, Peter Elmer, Brian Gravelle +12
In the High-Luminosity Large Hadron Collider (HL-LHC), one of the most challenging computational problems is expected to be finding and fitting charged-particle tracks during event…
Speeding up Particle Track Reconstruction in the CMS Detector using a Vectorized and Parallelized Kalman Filter Algorithm
Giuseppe Cerati, Peter Elmer, Brian Gravelle +13
Building particle tracks is the most computationally intense step of event reconstruction at the LHC. With the increased instantaneous luminosity and associated increase in pileup…