Parallel track reconstruction in CMS using the cellular automaton approach

Funke, Daniel; Hauth, T.; Innocente, V.; Quast, G.; Sanders, Peter; Schieferdecker, Dennis

doi:10.1088/1742-6596/513/5/052010

Cited by 20 publications

(22 citation statements)

References 3 publications

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“…Several improvements to the iterative tracking algorithm were possible thanks to the new Pixel detector. Among those improvements, the finding of the pixel seeds based on the Cellular Automaton (CA) technique [5] can be considered one of the most relevant: hit pairs are formed between detector layers; pair compatibility with respect to the interaction point is checked; hit triplets or quadruplets used for seeding are formed from compatible pairs. The improvements in the tracking efficiencies and in the fake rate obtained with the new detector setup and improved algorithms are shown in Fig.…”

Section: Trackingmentioning

confidence: 99%

CMS event reconstruction status in Run 2

Perrotta

2019

EPJ Web Conf.

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LHC Run2 began in April 2015 with the restart of the collisions in the CERN Large Hadron Collider. In the perspective of the offline event reconstruction, the most relevant detector updates appeared in 2017: the upgrade of the Pixel Detector, with the insertion of an additional layer closer to the beams, and the improved photodetectors and readout chips for the Endcap Hadron Calorimeter, which allow a finer longitudinal segmentation. The long shutdown between Run1 and Run2 was instrumental in the optimization of the reconstruction code and for the introduction of new algorithms to mitigate sensitivity to increased pileup, especially to out-of-time contribution with the advent of 25 ns separation between collisions compared to 50 ns in Run1. Such an optimization continued in the following years, when the reconstruction code of CMS evolved together with the improving of the performance of the LHC. The current status of the reconstruction software of the CMS experiment is described here, with emphasis on some of the recently integrated developments.

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Section: Trackingmentioning

confidence: 99%

CMS event reconstruction status in Run 2

Perrotta

2019

EPJ Web Conf.

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“…HEP applications are in general not yet capable of using them, however many preliminary studies have been done [18][19][20][21][22][23][24][25] and a few specific applications are leading the way [26][27][28][29]. Several groups have investigated the use of low power mobile processors (e.g.…”

Section: Processor Technologymentioning

confidence: 99%

Power-aware Applications for Scientific Cluster and Distributed

Elmer¹

2014

Proceedings of International Symposium on Grids and Clouds (ISGC) 2014 — PoS(ISGC2014)

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The aggregate power use of computing hardware is an important cost factor in scientific cluster and distributed computing systems. The Worldwide LHC Computing Grid (WLCG) is a major example of such a distributed computing system, used primarily for high throughput computing (HTC) applications. It has a computing capacity and power consumption rivaling that of the largest supercomputers. The computing capacity required from this system is also expected to grow over the next decade. Optimizing the power utilization and cost of such systems is thus of great interest. A number of trends currently underway will provide new opportunities for power-aware optimizations. We discuss how power-aware software applications and scheduling might be used to reduce power consumption, both as autonomous entities and as part of a (globally) distributed system. As concrete examples of computing centers we provide information on the large HEP-focused Tier-1 at FNAL, and the Tigress High Performance Computing Center at Princeton University, which provides HPC resources in a university context.

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“…The track-finding algorithms used in Belle II are built on the experiment's modular software framework [4] and can be combined for an optimal overall performance. The algorithms use both local and global track-finding methods based on cellular automaton [5,6,7,8] and Legendre transformation [9], respectively, as well as combinatorial Kalman filter (CKF) approaches [10,11,12,13]. A specific feature of the Belle II tracking is a heavy use of multivariate methods, based on the gradient boosted decision tree implementation provided by the FastBDT package [14], to improve background filtering and track-candidate search.…”

Section: Introductionmentioning

confidence: 99%

Track finding at Belle II

Bertacchi

Bilka

Braun

et al. 2021

Computer Physics Communications

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This paper describes the track-finding algorithm that is used for event reconstruction in the Belle II experiment operating at the SuperKEKB B-factory in Tsukuba, Japan. The algorithm is designed to balance the requirements of a high efficiency to find charged particles with a good track parameter resolution, a low rate of spurious tracks, and a reasonable demand on CPU resources. The software is implemented in a flexible, modular manner and employs a diverse selection of global and local track-finding algorithms to achieve an optimal performance.

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Parallel track reconstruction in CMS using the cellular automaton approach

Cited by 20 publications

References 3 publications

CMS event reconstruction status in Run 2

CMS event reconstruction status in Run 2

Power-aware Applications for Scientific Cluster and Distributed

Track finding at Belle II

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