Explanipedia

Exploring code portability solutions for HEP with a particle tracking test code Open

Hammad Ather, S. Berkman, G. B. Cerati, M. J. Kortelainen, Ka Hei Martin Kwok , et al. · 2024

Traditionally, high energy physics (HEP) experiments have relied on x86 CPUs for the majority of their significant computing needs. As the field looks ahead to the next generation of experiments such as DUNE and the High-Luminosity LHC, th…

Exploring code portability solutions for HEP with a particle tracking test code Open

Hammad Ather, S. Berkman, G. B. Cerati, M. J. Kortelainen, Ka Hei Martin Kwok , et al. · 2024

Traditionally, high energy physics (HEP) experiments have relied on x86 CPUs for the majority of their significant computing needs. As the field looks ahead to the next generation of experiments such as DUNE and the High-Luminosity LHC, th…

Generalizing mkFit and its Application to HL-LHC Open

G. B. Cerati, P. Elmer, P. Gartung, L. Giannini, M. J. Kortelainen , et al. · 2024

mkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both threadand data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offline …

Generalizing mkFit and its Application to HL-LHC Open

G. B. Cerati, P. Elmer, P. Gartung, L. Giannini, M. J. Kortelainen , et al. · 2023

mkFit is an implementation of the Kalman filter-based track reconstruction algorithm that exploits both thread- and data-level parallelism. In the past few years the project transitioned from the R&D phase to deployment in the Run-3 offlin…

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

G. B. Cerati, P. Elmer, Brian Gravelle, M. J. Kortelainen, V. Krutelyov , et al. · 2021

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 further improved by concurrently processing multiple event…

Reconstruction of Charged Particle Tracks in Realistic Detector Geometry Using a Vectorized and Parallelized Kalman Filter Algorithm Open

G. B. Cerati, P. Elmer, Brian Gravelle, M. J. Kortelainen, V. Krutelyov , et al. · 2020

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 reconstruction. Algorithms used at the LHC today rely on Kalman filter…

Reconstruction of Charged Particle Tracks in Realistic Detector Geometry Using a Vectorized and Parallelized Kalman Filter Algorithm Open

G. B. Cerati, P. Elmer, Brian Gravelle, M. J. Kortelainen, V. Krutelyov , et al. · 2019

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 reconstruction. Algorithms used at the LHC today rely on Kalman filter…

Speeding up Particle Track Reconstruction in the CMS Detector using a Vectorized and Parallelized Kalman Filter Algorithm Open

G. B. Cerati, P. Elmer, Brian Gravelle, M. J. Kortelainen, V. Krutelyov , et al. · 2019

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 expected from the High-Luminosity LHC, the computational ch…

Speeding up Particle Track Reconstruction in the CMS Detector using a\n Vectorized and Parallelized Kalman Filter Algorithm Open

G. B. Cerati, P. Elmer, Brian Gravelle, M. J. Kortelainen, V. Krutelyov , et al. · 2019

Building particle tracks is the most computationally intense step of event\nreconstruction at the LHC. With the increased instantaneous luminosity and\nassociated increase in pileup expected from the High-Luminosity LHC, the\ncomputational…

Parallelized and Vectorized Tracking Using Kalman Filters with CMS Detector Geometry and Events Open

G. B. Cerati, P. Elmer, Brian Gravelle, M. J. Kortelainen, V. Krutelyov , et al. · 2018

The High-Luminosity Large Hadron Collider at CERN will be characterized by greater pileup of events and higher occupancy, making the track reconstruction even more computationally demanding. Existing algorithms at the LHC are based on Kalm…

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Architectures Open

G. B. Cerati, P. Elmer, Slava Krutelyov, Steven Lantz, Matthieu Lefèbvre , et al. · 2018

Faced with physical and energy density limitations on clock speed, contemporary microprocessor designers have increasingly turned to on-chip parallelism for performance gains. Algorithms should accordingly be designed with ample amounts of…

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on\n Many-Core Architectures Open

G. B. Cerati, P. Elmer, Slava Krutelyov, Steven Lantz, Matthieu Lefèbvre , et al. · 2017

Faced with physical and energy density limitations on clock speed,\ncontemporary microprocessor designers have increasingly turned to on-chip\nparallelism for performance gains. Algorithms should accordingly be designed\nwith ample amounts…

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

G. B. Cerati, P. Elmer, Slava Krutelyov, Steven Lantz, Matthieu Lefèbvre , et al. · 2017

For over a decade now, physical and energy constraints have limited clock\nspeed improvements in commodity microprocessors. Instead, chipmakers have been\npushed into producing lower-power, multi-core processors such as GPGPU, ARM and\nInt…

Kalman Filter Tracking on Parallel Architectures Open

G. B. Cerati, P. Elmer, Slava Krutelyov, Steven Lantz, Matthieu Lefèbvre , et al. · 2016

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 GPGPU, ARM and Intel MIC. In order to achieve the theoretical p…

Kalman Filter Tracking on Parallel Architectures Open

G. B. Cerati, P. Elmer, Steven Lantz, K. Mcdermott, Dan Riley , et al. · 2015

Power density constraints are limiting the performance improvements of modern\nCPUs. To address this we have seen the introduction of lower-power, multi-core\nprocessors, but the future will be even more exciting. In order to stay within\n…

Traditional Tracking with Kalman Filter on Parallel Architectures Open

G. B. Cerati, P. Elmer, Steven Lantz, I. Macneill, K. Mcdermott , et al. · 2015

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 future will be even more exciting. In order to stay within th…

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