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20172022
most citedParallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

9 citations · 9 across the 2 of their papers we have counts for

collaborators

5 papers

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-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…

physics.comp-ph20179 cited

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Processors and GPUs

Giuseppe Cerati, Peter Elmer, Slava Krutelyov +9

For over a decade now, physical and energy constraints have limited clock speed improvements in commodity microprocessors. Instead, chipmakers have been pushed into producing lower…