Abstract
The online Data Acquisition system of the Compact Muon Solenoid (CMS) experiment at CERN’s Large Hadron Collider is designed to collect data corresponding to a single collision of particles, referred to as an event, from about 500 detector Front-Ends. Each of those Front-Ends delivers event-fragments of an average size of 2 KB at a rate of 100 kHz. The event-fragments are statically distributed (usually in round robin fashion) between 8 identical computing farms, which construct the whole events. In this paper we present experimental results of employing a distributed, asynchronous load scheduling algorithm in place of the static event allocation mechanism. The research focuses in particular on balancing the event flow in case of degradations in computing power or network throughput. The discussed studies prove that the proposed method meets the requirements of CMS experiment and has a positive impact on the resource utilization and overall fault tolerance.
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References
The CMS collaboration et al: The CMS experiment at the CERN LHC. JINST 3, 1–5, 261–282 (2008)
Bauer, G., et al.: The Terabit/s Super-Fragment Builder and Trigger Throttling System for the Compact Muon Solenoid Experiment at CERN. IEEE Transactions on Nuclear Science 55, 190–197 (2008)
Clos, C.: A study of non-blocking switching networks. Bell System Technical Journal 32, 406–424 (1952)
Cohen, D., et al.: Myrinet: a gigabit-per-second local area network. IEEE Micro 15(10), 29–36 (1995)
Darema, F.: The SPMD Model: Past, Present and Future. In: Cotronis, Y., Dongarra, J. (eds.) Euro PVM/MPI 2001. LNCS, vol. 2131, p. 1. Springer, Heidelberg (2001)
Veeravalli, B., Ghose, D., Robertazzi, T.G.: Divisible Load Theory: A New Paradigm for Load Scheduling in Distributed Systems. Cluster Computing 6, 7–17 (2003)
Jia, J., Veeravalli, B., Weissman, J.: Scheduling Multisource Divisible Loads. IEEE Transactions on Parallel and Distributed Systems 99, 520–531 (2009)
Yu, D., Robertazzi, T.: Multi-Source Grid Scheduling for Divisible Loads. In: 40th IEEE Annual Conference on Information Sciences and Systems, Princeton, pp. 188–191 (2006)
Vandelli, W., et al.: The ATLAS Event Builder. IEEE Transactions on Nuclear Science 55, 3556–3562 (2008)
Alessio, F., et al.: The LHCb Readout System and Real-Time Event Management. IEEE Transactions on Nuclear Science 57, 663–668 (2010)
Simon, M.: Fault Tolerant Data Acquisition through Dynamic Load Balancing. In: 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW), Anchorage, pp. 2049–2052 (2011)
European Organizasion for Nuclear Research (CERN), http://cms-ru-builder.web.cern.ch/cms-ru-builder/RUBUILDER_G_V1_12_0.pdf
Baurer, G., et al.: Studies of future readout links for the CMS experiment. J. Phys.: Conf. Ser. 331, 22004–22009 (2011)
Fonlupt, C., Marquet, P., Dekeyser, J.-l.: Data-Parallel Load Balancing Strategies. Parallel Computing 24, 1665–1684 (1996)
Simon, M., Sakulin, H., Kozielski, S.: Studies on load metric and communication for a load balancing algorithm in a distributed data acquisition system. J. Phys.: Conf. Ser. 331, 22040–22046 (2011)
Osman, A., Ammar, H.: Dynamic Load Balancing Strategies for Parallel Computers. Sci. Ann. Comput. Sci. 11, 110–120 (2002)
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Simon, M., Sakulin, H., Kozielski, S. (2013). Experimental Results of Dynamic Load Scheduling in the CMS Data Acquisition System. In: Kwiecień, A., Gaj, P., Stera, P. (eds) Computer Networks. CN 2013. Communications in Computer and Information Science, vol 370. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38865-1_2
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DOI: https://doi.org/10.1007/978-3-642-38865-1_2
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