422 citations · 1.3k across the 38 of their papers we have counts for
10 papers · 1 filter
Improving tracking algorithms with machine learning: a case for line-segment tracking at the High Luminosity LHC
Jonathan Guiang, Slava Krutelyov, Manos Vourliotis +10
In this work, we present a study on ways that tracking algorithms can be improved with machine learning (ML). We base this study on the line segment tracking (LST) algorithm that w…
Segment Linking: A Highly Parallelizable Track Reconstruction Algorithm for HL-LHC
Philip Chang, Peter Elmer, Yanxi Gu +9
The High Luminosity upgrade of the Large Hadron Collider (HL-LHC) will produce particle collisions with up to 200 simultaneous proton-proton interactions. These unprecedented condi…
Line Segment Tracking in the HL-LHC
Gavin Niendorf, Tres Reid, Peter Wittich +9
The major challenge posed by the high instantaneous luminosity in the High Luminosity LHC (HL-LHC) motivates efficient and fast reconstruction of charged particle tracks in a high…
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…
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…
Kalman Filter Tracking on Parallel Architectures
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, but the fut…
Traditional Tracking with Kalman Filter on Parallel Architectures
Giuseppe Cerati, Peter Elmer, Steven Lantz +7
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, but the fu…