EPJ Web of Conferences (Jan 2019)

A Python upgrade to the GooFit package for parallel fitting

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

DOI
https://doi.org/10.1051/epjconf/201921405006
Journal volume & issue
Vol. 214
p. 05006

Abstract

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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.