The IceProd framework: Distributed data processing for the IceCube neutrino observatory

/ Authors

M. Aartsen, R. Abbasi, M. Ackermann, Jenni Adams, J. Aguilar, M. Ahlers, D. Altmann, C. A. A. Delgado, J. Auffenberg, X. Bai

and 277 more authors

Michael F. Baker, S. Barwick, Volker Baum, R. Bay, J. Beatty, J. Tjus, K. Becker, S. Benzvi, P. Berghaus, D. Berley, E. Bernardini, A. Bernhard, D. Besson, G. Binder, D. Bindig, M. Bissok, E. Blaufuss, J. Blumenthal, D. Boersma, C. Bohm, D. Bose, S. Böser, O. Botner, L. Brayeur, H. Bretz, Anthony M. Brown, R. Bruijn, J. Casey, M. Casier, D. Chirkin, A. Christov, B. Christy, K. Clark, L. Classen, F. Clevermann, S. Coenders, S. Cohen, D. Cowen, Angel H. Cruz Silva, M. Danninger, J. Daughhetee, James C. Davis, M. Day, C. Clercq, S. Ridder, P. Desiati, K. D. Vries, M. With, T. DeYoung, J. C. Díaz-Vélez, M. Dunkman, R. Eagan, B. Eberhardt, B. Eichmann, J. Eisch, S. Euler, P. Evenson, O. Fadiran, A. Fazely, A. Fedynitch, J. Feintzeig, T. Feusels, K. Filimonov, C. Finley, T. Fischer-Wasels, S. Flis, A. Franckowiak, K. Frantzen, T. Fuchs, T. Gaisser, J. Gallagher, L. Gerhardt, L. Gladstone, T. Glüsenkamp, A. Goldschmidt, G. Golup, Javier G. González, J. Goodman, D. Góra, D. Grandmont, D. Grant, P. Gretskov, J. Groh, A. Groß, C. Ha, A. H. Ismail, P. Hallen, A. Hallgren, F. Halzen, K. Hanson, D. Hebecker, D. Heereman, D. Heinen, K. Helbing, R. Hellauer, S. Hickford, G. Hill, K. Hoffman, R. Hoffmann, A. Homeier, K. Hoshina, F. Huang, W. Huelsnitz, P. Hulth, K. Hultqvist, S. Hussain, A. Ishihara, E. Jacobi, J. Jacobsen, K. Jagielski, G. Japaridze, K. Jero, O. Jlelati, B. Kaminsky, A. Kappes, T. Karg, A. Karle, M. Kauer, J. Kelley, J. Kiryluk, J. Kläs, S. Klein, J. Köhne, G. Kohnen, H. Kolanoski, L. Köpke, C. Kopper, S. Kopper, D. Koskinen, M. Kowalski, M. Krasberg, A. Kriesten, K. Krings, G. Kroll, J. Kunnen, N. Kurahashi, T. Kuwabara, M. Labare, H. Landsman, M. Larson, M. Lesiak-Bzdak, M. Leuermann, J. Leute, J. Lünemann, Oscar A. Macías-Ramírez, J. Madsen, G. Maggi, R. Maruyama, K. Mase, H. Matis, F. McNally, K. Meagher, M. Merck, G. M. Arévalo, T. Meures, S. Miarecki, E. Middell, N. Milke, J. Miller, L. Mohrmann, T. Montaruli, R. Morse, R. Nahnhauer, U. Naumann, H. Niederhausen, S. Nowicki, D. Nygren, A. Obertacke, S. Odrowski, A. Olivas, A. Omairat, A. Murchadha, L. Paul, J. Pepper, C. D. L. Heros, C. Pfendner, D. Pieloth, E. Pinat, J. Posselt, P. Price, G. Przybylski, M. Quinnan, L. Rädel, Ian Rae, M. Rameez, K. Rawlins, P. Redl, R. Reimann, E. Resconi, W. Rhode, M. Ribordy, M. Richman, B. Riedel, J. Rodrigues, C. Rott, T. Ruhe, B. Ruzybayev, D. Ryckbosch, S. M. Saba, H. Sander, J. Santander, S. Sarkar, K. Schatto, F. Scheriau, T. Schmidt, M. Schmitz, S. Schoenen, S. Schöneberg, A. Schönwald, A. Schukraft, L. Schulte, D. Schultz, O. Schulz, D. Seckel, Yolanda Sestayo de la Cerra, S. Seunarine, R. Shanidze, C. Sheremata, Miles W. E. Smith, D. Soldin, G. Spiczak, C. Spiering, M. Stamatikos, T. Stanev, N. Stanisha, Alexander Stasik, T. Stezelberger, R. Stokstad, A. Stößl, E. Strahler, R. Ström, N. Strotjohann, G. Sullivan, H. Taavola, I. Taboada, A. Tamburro, A. Tepe, S. Ter-Antonyan, G. Tesic, S. Tilav, P. Toale, M. Tobin, S. Toscano, M. Tselengidou, E. Unger, M. Usner, S. Vallecorsa, N. Eijndhoven, A. Overloop, J. Santen, M. Vehring, M. Voge, M. Vraeghe, C. Walck, T. Waldenmaier, M. Wallraff, C. Weaver, M. Wellons, C. Wendt, S. Westerhoff, N. Whitehorn, K. Wiebe, C. Wiebusch, Dawn R. Williams, H. Wissing, M. Wolf, T. R. Wood, K. Woschnagg, Donglian Xu, Xianwu Xu, Juan Pablo Yáñez Garza, G. Yodh, S. Yoshida, P. Zarzhitsky, J. Ziemann, S. Zierke, M. Zoll

/ Abstract

IceCube is a one-gigaton instrument located at the geographic South Pole, designed to detect cosmic neutrinos, iden- tify the particle nature of dark matter, and study high-energy neutrinos themselves. Simulation of the IceCube detector and processing of data require a significant amount of computational resources. IceProd is a distributed management system based on Python, XML-RPC and GridFTP. It is driven by a central database in order to coordinate and admin- ister production of simulations and processing of data produced by the IceCube detector. IceProd runs as a separate layer on top of other middleware and can take advantage of a variety of computing resources, including grids and batch systems such as CREAM, Condor, and PBS. This is accomplished by a set of dedicated daemons that process job submission in a coordinated fashion through the use of middleware plugins that serve to abstract the details of job submission and job management from the framework.

Journal: J. Parallel Distributed Comput.

DOI: 10.1016/j.jpdc.2014.08.001