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Title: Expressing Parallelism with ROOT

Abstract

The need for processing the ever-increasing amount of data generated by the LHC experiments in a more efficient way has motivated ROOT to further develop its support for parallelism. Such support is being tackled both for shared-memory and distributed-memory environments. The incarnations of the aforementioned parallelism are multi-threading, multi-processing and cluster-wide executions. In the area of multi-threading, we discuss the new implicit parallelism and related interfaces, as well as the new building blocks to safely operate with ROOT objects in a multi-threaded environment. Regarding multi-processing, we review the new MultiProc framework, comparing it with similar tools (e.g. multiprocessing module in Python). Finally, as an alternative to PROOF for cluster-wide executions, we introduce the efforts on integrating ROOT with state-of-the-art distributed data processing technologies like Spark, both in terms of programming model and runtime design (with EOS as one of the main components). For all the levels of parallelism, we discuss, based on real-life examples and measurements, how our proposals can increase the productivity of scientists.

Authors:
 [1];  [1];  [1];  [1];  [1];  [1];  [1];  [2]
  1. CERN
  2. Fermilab
Publication Date:
Research Org.:
Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
OSTI Identifier:
1415642
Report Number(s):
FERMILAB-CONF-16-738-CD
1638554
DOE Contract Number:  
AC02-07CH11359
Resource Type:
Conference
Resource Relation:
Journal Name: J.Phys.Conf.Ser.; Journal Volume: 898; Journal Issue: 7; Conference: 22nd International Conference on Computing in High Energy and Nuclear Physics, San Francisco, CA, 10/10-10/14/2016
Country of Publication:
United States
Language:
English

Citation Formats

Piparo, D., Tejedor, E., Guiraud, E., Ganis, G., Mato, P., Moneta, L., Valls Pla, X., and Canal, P. Expressing Parallelism with ROOT. United States: N. p., 2017. Web. doi:10.1088/1742-6596/898/7/072022.
Piparo, D., Tejedor, E., Guiraud, E., Ganis, G., Mato, P., Moneta, L., Valls Pla, X., & Canal, P. Expressing Parallelism with ROOT. United States. doi:10.1088/1742-6596/898/7/072022.
Piparo, D., Tejedor, E., Guiraud, E., Ganis, G., Mato, P., Moneta, L., Valls Pla, X., and Canal, P. Wed . "Expressing Parallelism with ROOT". United States. doi:10.1088/1742-6596/898/7/072022. https://www.osti.gov/servlets/purl/1415642.
@article{osti_1415642,
title = {Expressing Parallelism with ROOT},
author = {Piparo, D. and Tejedor, E. and Guiraud, E. and Ganis, G. and Mato, P. and Moneta, L. and Valls Pla, X. and Canal, P.},
abstractNote = {The need for processing the ever-increasing amount of data generated by the LHC experiments in a more efficient way has motivated ROOT to further develop its support for parallelism. Such support is being tackled both for shared-memory and distributed-memory environments. The incarnations of the aforementioned parallelism are multi-threading, multi-processing and cluster-wide executions. In the area of multi-threading, we discuss the new implicit parallelism and related interfaces, as well as the new building blocks to safely operate with ROOT objects in a multi-threaded environment. Regarding multi-processing, we review the new MultiProc framework, comparing it with similar tools (e.g. multiprocessing module in Python). Finally, as an alternative to PROOF for cluster-wide executions, we introduce the efforts on integrating ROOT with state-of-the-art distributed data processing technologies like Spark, both in terms of programming model and runtime design (with EOS as one of the main components). For all the levels of parallelism, we discuss, based on real-life examples and measurements, how our proposals can increase the productivity of scientists.},
doi = {10.1088/1742-6596/898/7/072022},
journal = {J.Phys.Conf.Ser.},
number = 7,
volume = 898,
place = {United States},
year = {Wed Nov 22 00:00:00 EST 2017},
month = {Wed Nov 22 00:00:00 EST 2017}
}

Conference:
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