James Pivarski

According to our database, James Pivarski authored at least 25 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Potential of the Julia Programming Language for High Energy Physics Computing.

Jonas Eschle, Tamás Gál, Mosè Giordano, Philippe Gras, Benedikt Hegner, Lukas Heinrich, Uwe Hernandez Acosta, Stefan Kluth, Jerry (Jiahong) Ling, Pere Mato, Mikhail Mikhasenko, Alexander Moreno Briceño, Jim Pivarski, Konstantinos Samaras-Tsakiris, Oliver Schulz, Graeme Andrew Stewart, Jan Strube, Vassil Vassilev

Comput. Softw. Big Sci., December, 2023

Awkward Just-In-Time (JIT) Compilation: A Developer's Experience.

Ianna Osborne, Jim Pivarski, Ioana Ifrim, Angus Hollands, Henry Schreiner

CoRR, 2023

The Awkward World of Python and C++.

Manasvi Goyal, Ianna Osborne, Jim Pivarski

CoRR, 2023

Using a DSL to read ROOT TTrees faster in Uproot.

Aryan Roy, Jim Pivarski

CoRR, 2023

Awkward to RDataFrame and back.

Ianna Osborne, Jim Pivarski

CoRR, 2023

2022

An array-oriented Python interface for FastJet.

Aryan Roy, Jim Pivarski, Chad Wells Freer

CoRR, 2022

Awkward Packaging: building Scikit-HEP.

Henry Schreiner, Jim Pivarski, Eduardo Rodrigues

Proceedings of the 21st Python in Science Conference 2022, 2022

2021

AwkwardForth: accelerating Uproot with an internal DSL.

Jim Pivarski, Ianna Osborne, Pratyush Das, David Lange, Peter Elmer

CoRR, 2021

2020

Coffea - Columnar Object Framework For Effective Analysis.

Nicholas Smith, Lindsey Gray, Matteo Cremonesi, Bo Jayatilaka, Oliver Gutsche, Allison Hall, Kevin Pedro, Maria Acosta Flechas, Andrew Melo, Stefano Belforte, Jim Pivarski

CoRR, 2020

Awkward Arrays in Python, C++, and Numba.

Jim Pivarski, Peter Elmer, David Lange

CoRR, 2020

Boost-histogram: High-Performance Histograms as Objects.

Henry Schreiner, Hans Dembinski, Shuo Liu, Jim Pivarski

Proceedings of the 19th Python in Science Conference 2020 (SciPy 2020), Virtual Conference, July 6, 2020

Awkward Array: JSON-like data, NumPy-like idioms.

Jim Pivarski, Ianna Osborne, Pratyush Das, Anish Biswas, Peter Elmer

Proceedings of the 19th Python in Science Conference 2020 (SciPy 2020), Virtual Conference, July 6, 2020

2019

Using Big Data Technologies for HEP Analysis.

Matteo Cremonesi, Claudio Bellini, Bianny Bian, Luca Canali, Vasileios Dimakopoulos, Peter Elmer, Ian Fisk, Maria Girone, Oliver Gutsche, Siew-Yan Hoh, Bo Jayatilaka, Viktor Khristenko, Andrea Luiselli, Andrew Melo, Evangelos Motesnitsalis, Dominick Olivito, Jacopo Pazzini, Jim Pivarski, Alexey Svyatkovskiy, Marco Zanetti

CoRR, 2019

2018

Machine Learning in High Energy Physics Community White Paper.

Kim Albertsson, Piero Altoe, Dustin Anderson, Michael Andrews, Juan Pedro Araque Espinosa, Adam Aurisano, Laurent Basara, Adrian Bevan, Wahid Bhimji, Daniele Bonacorsi, Paolo Calafiura, Mario Campanelli, Louis Capps, Federico Carminati, Stefano Carrazza, Taylor Childers, Elias Coniavitis, Kyle Cranmer, Claire David, Douglas Davis, Javier M. Duarte, Martin Erdmann, Jonas Eschle, Amir Farbin, Matthew Feickert, Nuno Filipe Castro, Conor Fitzpatrick, Michele Floris, Alessandra Forti, Jordi Garra-Tico, Jochen Gemmler, Maria Girone, Paul Glaysher, Sergei Gleyzer, Vladimir V. Gligorov, Tobias Golling, Jonas Graw, Lindsey Gray, Dick Greenwood, Thomas Hacker, John Harvey, Benedikt Hegner, Lukas Heinrich, Ben Hooberman, Johannes Junggeburth, Michael Kagan, Meghan Kane, Konstantin Kanishchev, Przemyslaw Karpinski, Zahari Kassabov, Gaurav Kaul, Dorian Kcira, Thomas Keck, Alexei Klimentov, Jim Kowalkowski, Luke Kreczko, Alexander Kurepin, Rob Kutschke, Valentin Kuznetsov, Nicolas Köhler, Igor Lakomov, Kevin Lannon, Mario Lassnig, Antonio Limosani, Gilles Louppe, Aashrita Mangu, Pere Mato, Narain Meenakshi, Helge Meinhard, Dario Menasce, Lorenzo Moneta, Seth Moortgat, Mark S. Neubauer, Harvey B. Newman, Hans Pabst, Michela Paganini, Manfred Paulini, Gabriel N. Perdue, Uzziel Perez, Attilio Picazio, Jim Pivarski, Harrison Prosper, Fernanda Psihas, Alexander Radovic, Ryan Reece, Aurelius Rinkevicius, Eduardo Rodrigues, Jamal Rorie, David Rousseau, Aaron Sauers, Steven Schramm, Ariel Schwartzman, Horst Severini, Paul Seyfert, Filip Siroky, Konstantin Skazytkin, Mike Sokoloff, Graeme Andrew Stewart, Bob Stienen, Ian Stockdale, Giles Chatham Strong, Savannah Thais, Karen Tomko, Eli Upfal, Emanuele Usai, Andrey Ustyuzhanin, Martin Vala, Sofia Vallecorsa, Mauro Verzetti, Xavier Vilasís-Cardona, Jean-Roch Vlimant, Ilija Vukotic, Sean-Jiun Wang, Gordon Watts, Michael Williams, Wenjing Wu, Stefan Wunsch, Omar Zapata

CoRR, 2018

Tintenfisch: File System Namespace Schemas and Generators.

Michael A. Sevilla, Reza Nasirigerdeh, Carlos Maltzahn, Jeff LeFevre, Noah Watkins, Peter Alvaro, Margaret Lawson, Jay F. Lofstead, Jim Pivarski

Proceedings of the 10th USENIX Workshop on Hot Topics in Storage and File Systems, 2018

2017

The Matsu Wheel: a reanalysis framework for Earth satellite imagery in data commons.

Maria T. Patterson, Nikolas Anderson, Collin Bennett, Jacob Bruggemann, Robert L. Grossman, Matthew Handy, Vuong Ly, Daniel J. Mandl, Shane Pederson, James Pivarski, Ray Powell, Jonathan Spring, Walt Wells, John Xia

Int. J. Data Sci. Anal., 2017

Optimizing ROOT IO For Analysis.

Brian Bockelman, Zhe Zhang, Jim Pivarski

CoRR, 2017

Toward real-time data query systems in HEP.

Jim Pivarski, David Lange, Thanat Jatuphattharachat

CoRR, 2017

CMS Analysis and Data Reduction with Apache Spark.

Oliver Gutsche, Luca Canali, Illia Cremer, Matteo Cremonesi, Peter Elmer, Ian Fisk, Maria Girone, Bo Jayatilaka, Jim Kowalkowski, Viktor Khristenko, Evangelos Motesnitsalis, Jim Pivarski, Saba Sehrish, Kacper Surdy, Alexey Svyatkovskiy

CoRR, 2017

Fast Access to Columnar, Hierarchical Data via Code Transformation.

Jim Pivarski, Peter Elmer, Brian Bockelman, Zhe Zhang

CoRR, 2017

Big Data in HEP: A comprehensive use case study.

Oliver Gutsche, Matteo Cremonesi, Peter Elmer, Bo Jayatilaka, Jim Kowalkowski, Jim Pivarski, Saba Sehrish, Cristina Mantilla Suarez, Alexey Svyatkovskiy, Nhan Tran

CoRR, 2017

Fast access to columnar, hierarchically nested data via code transformation.

Jim Pivarski, Peter Elmer, Brian Bockelman, Zhe Zhang

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016

The Matsu Wheel: A Cloud-based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery.

Maria T. Patterson, Nikolas Anderson, Collin Bennett, Jacob Bruggemann, Robert L. Grossman, Matthew Handy, Vuong Ly, Dan Mandl, Shane Pederson, Jim Pivarski, Ray Powell, Jonathan Spring, Walt Wells

CoRR, 2016

Deploying Analytics with the Portable Format for Analytics (PFA).

Jim Pivarski, Collin Bennett, Robert L. Grossman

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

The Matsu Wheel: A Cloud-Based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery.

Maria T. Patterson, Nikolas Anderson, Collin Bennett, Jacob Bruggemann, Robert L. Grossman, Matthew Handy, Vuong Ly, Daniel J. Mandl, Shane Pederson, James Pivarski, Ray Powell, Jonathan Spring, Walt Wells, John Xia

Proceedings of the Second IEEE International Conference on Big Data Computing Service and Applications, 2016