Shared Memory Transport for ALFA

The high data rates expected for the next generation of particle physics experiments (e.g.: new experiments at FAIR/GSI and the upgrade of CERN experiments) call for dedicated attention with respect to design of the needed computing infrastructure. The common ALICE-FAIR framework ALFA is a modern so...

Full description

Bibliographic Details
Main Authors: Rybalchenko Alexey, Klein Dennis, Al-Turany Mohammad, Kollegger Thorsten
Format: Article
Language:English
Published: EDP Sciences 2019-01-01
Series:EPJ Web of Conferences
Online Access:https://www.epj-conferences.org/articles/epjconf/pdf/2019/19/epjconf_chep2018_05029.pdf
id doaj-3dea84d029a74bc6ab9d8df734e2e676
record_format Article
spelling doaj-3dea84d029a74bc6ab9d8df734e2e6762021-08-02T14:18:59ZengEDP SciencesEPJ Web of Conferences2100-014X2019-01-012140502910.1051/epjconf/201921405029epjconf_chep2018_05029Shared Memory Transport for ALFARybalchenko AlexeyKlein DennisAl-Turany MohammadKollegger ThorstenThe high data rates expected for the next generation of particle physics experiments (e.g.: new experiments at FAIR/GSI and the upgrade of CERN experiments) call for dedicated attention with respect to design of the needed computing infrastructure. The common ALICE-FAIR framework ALFA is a modern software layer, that serves as a platform for simulation, reconstruction and analysis of particle physics experiments. Beside standard services needed for simulation and reconstruction of particle physics experiments, ALFA also provides tools for data transport, configuration and deployment. The FairMQ module in ALFA offers building blocks for creating distributed software components (processes) that communicate between each other via message passing. The abstract "message passing" interface in FairMQ has at the moment three implementations: ZeroMQ, nanomsg and shared memory. The newly developed shared memory transport will be presented, that provides significant per-formance benefits for transferring large data chunks between components on the same node. The implementation in FairMQ allows users to switch between the different transports via a trivial configuration change. The design decisions, im-plementation details and performance numbers of the shared memory transport in FairMQ/ALFA will be highlighted.https://www.epj-conferences.org/articles/epjconf/pdf/2019/19/epjconf_chep2018_05029.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Rybalchenko Alexey
Klein Dennis
Al-Turany Mohammad
Kollegger Thorsten
spellingShingle Rybalchenko Alexey
Klein Dennis
Al-Turany Mohammad
Kollegger Thorsten
Shared Memory Transport for ALFA
EPJ Web of Conferences
author_facet Rybalchenko Alexey
Klein Dennis
Al-Turany Mohammad
Kollegger Thorsten
author_sort Rybalchenko Alexey
title Shared Memory Transport for ALFA
title_short Shared Memory Transport for ALFA
title_full Shared Memory Transport for ALFA
title_fullStr Shared Memory Transport for ALFA
title_full_unstemmed Shared Memory Transport for ALFA
title_sort shared memory transport for alfa
publisher EDP Sciences
series EPJ Web of Conferences
issn 2100-014X
publishDate 2019-01-01
description The high data rates expected for the next generation of particle physics experiments (e.g.: new experiments at FAIR/GSI and the upgrade of CERN experiments) call for dedicated attention with respect to design of the needed computing infrastructure. The common ALICE-FAIR framework ALFA is a modern software layer, that serves as a platform for simulation, reconstruction and analysis of particle physics experiments. Beside standard services needed for simulation and reconstruction of particle physics experiments, ALFA also provides tools for data transport, configuration and deployment. The FairMQ module in ALFA offers building blocks for creating distributed software components (processes) that communicate between each other via message passing. The abstract "message passing" interface in FairMQ has at the moment three implementations: ZeroMQ, nanomsg and shared memory. The newly developed shared memory transport will be presented, that provides significant per-formance benefits for transferring large data chunks between components on the same node. The implementation in FairMQ allows users to switch between the different transports via a trivial configuration change. The design decisions, im-plementation details and performance numbers of the shared memory transport in FairMQ/ALFA will be highlighted.
url https://www.epj-conferences.org/articles/epjconf/pdf/2019/19/epjconf_chep2018_05029.pdf
work_keys_str_mv AT rybalchenkoalexey sharedmemorytransportforalfa
AT kleindennis sharedmemorytransportforalfa
AT alturanymohammad sharedmemorytransportforalfa
AT kolleggerthorsten sharedmemorytransportforalfa
_version_ 1721231308842074112