A Python upgrade to the GooFit package for parallel fitting

Henry Schreiner; Himadri Pandey; Michael D Sokoloff; Bradley Hittle; Karen Tomko; Christoph Hasse

doi:10.1051/epjconf/201921405006

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Proceedings

Open Access

EPJ Web of Conferences 214, 05006 (2019)
https://doi.org/10.1051/epjconf/201921405006

A Python upgrade to the GooFit package for parallel fitting

Henry Schreiner¹^*, Himadri Pandey¹, Michael D Sokoloff¹, Bradley Hittle², Karen Tomko² and Christoph Hasse³

¹ University of Cincinnati, Cincinnati, Ohio, USA
² Ohio Supercomputer Center, Columbus Ohio, USA
³ CERN / Technische Universität Dortmund (DE), Dortmund Germany

^* e-mail: henry.fredrick.schreiner@cern.ch

Published online: 17 September 2019

Abstract

The GooFit highly parallel fitting package for GPUs and CPUs has been substantially upgraded in the past year. Python bindings have been added to allow simple access to the fitting configuration, setup, and execution. A Python tool to write custom GooFit code given a (compact and elegant) MINT3/AmpGen amplitude description allows the corresponding C++ code to be written quickly and correctly. New PDFs have been added. The most recent release was built on top of the December 2017 2.0 release that added easier builds, new platforms, and a more robust and efficient underlying function evaluation engine.

© The Authors, published by EDP Sciences, 2019

This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.