15 citations · 65 across the 12 of their papers we have counts for
8 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…
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…
Kalman filter tracking on parallel architectures
Giuseppe Cerati, Peter Elmer, Slava Krutelyov +8
Limits on power dissipation have pushed CPUs to grow in parallel processing capabilities rather than clock rate, leading to the rise of "manycore" or GPU-like processors. In order…
Kalman-Filter-Based Particle Tracking on Parallel Architectures at Hadron Colliders
Giuseppe Cerati, Peter Elmer, Steven Lantz +6
Power density constraints are limiting the performance improvements of modern CPUs. To address this we have seen the introduction of lower-power, multi-core processors such as GPGP…