dc.creator | Cámpora Pérez, Daniel Hugo | es |
dc.creator | Neufeld, Niko | es |
dc.creator | Riscos Núñez, Agustín | es |
dc.date.accessioned | 2021-04-26T09:37:07Z | |
dc.date.available | 2021-04-26T09:37:07Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Cámpora Pérez, D.H., Neufeld, N. y Riscos Núñez, A. (2019). A fast local algorithm for track reconstruction on parallel architectures. En IPDPSW 2019: IEEE International Parallel and Distributed Processing Symposium Workshops (698-707), Rio de Janeiro, Brazil: IEEE Computer Society. | |
dc.identifier.isbn | 978-1-7281-3510-6 | es |
dc.identifier.uri | https://hdl.handle.net/11441/107782 | |
dc.description.abstract | The reconstruction of particle trajectories, tracking,
is a central process in the reconstruction of particle collisions in
High Energy Physics detectors. At the LHCb detector in the
Large Hadron Collider, bunches of particles collide 30 million
times per second. These collisions produce about 109 particle
trajectories per second that need to be reconstructed in real time,
in order to filter and store data. Upcoming improvements in the
LHCb detector will deprecate the hardware filter in favour of a
full software filter, posing a computing challenge that requires a
renovation of current algorithms and the underlying hardware.
We present Search by triplet, a local tracking algorithm
optimized for parallel architectures. We design our algorithm
reducing Read-After-Write dependencies as well as conditional
branches, incrementing the potential for parallelization. We
analyze the complexity of our algorithm and validate our results.
We show the scaling of our algorithm for an increasing number
of collision events. We show sustained tests for our algorithm
sequence given a simulated dataflow. We develop CPU and GPU
implementations of our work, and hide the transmission times
between device and host by executing a multi-stream pipeline.
Our results provide a reliable basis for an informed assessment
on the feasibility of LHCb event reconstruction on parallel
architectures, enabling us to develop cost models for upcoming
technology upgrades. The created software infrastructure is
extensible and permits the addition of subsequent reconstruction
algorithms. | es |
dc.format | application/pdf | es |
dc.format.extent | 10 | es |
dc.language.iso | eng | es |
dc.publisher | IEEE Computer Society | es |
dc.relation.ispartof | IPDPSW 2019: IEEE International Parallel and Distributed Processing Symposium Workshops (2019), pp. 698-707. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.title | A fast local algorithm for track reconstruction on parallel architectures | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/submittedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial | es |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/8778210 | es |
dc.identifier.doi | 10.1109/IPDPSW.2019.00118 | es |
dc.contributor.group | Universidad de Sevilla. TIC193: Computación Natural | es |
dc.publication.initialPage | 698 | es |
dc.publication.endPage | 707 | es |
dc.eventtitle | IPDPSW 2019: IEEE International Parallel and Distributed Processing Symposium Workshops | es |
dc.eventinstitution | Rio de Janeiro, Brazil | es |
dc.relation.publicationplace | New York, USA | es |