activity
20182021
collaborators

7 papers

hep-ex2021

Parallelizing the Unpacking and Clustering of Detector Data for Reconstruction of Charged Particle Tracks on Multi-core CPUs and Many-core GPUs

Giuseppe Cerati, Peter Elmer, Brian Gravelle +14

We present results from parallelizing the unpacking and clustering steps of the raw data from the silicon strip modules for reconstruction of charged particle tracks. Throughput is…

physics.ins-det2020

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…

physics.ins-det2020

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…

physics.ins-det2020

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…

physics.ins-det2019

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…

physics.ins-det2019

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…