132 citations · 467 across the 24 of their papers we have counts for
3 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…
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…