A Python']Python upgrade to the GooFit package for parallel fitting

被引：1
|
作者：
Schreiner, Henry [1 ]
Pandey, Himadri [1 ]
Sokoloff, Michael D. [1 ]
Hittle, Bradley [2 ]
Tomko, Karen [2 ]
Hasse, Christoph [3 ]
机构：
[1] Univ Cincinnati, Cincinnati, OH 45221 USA
[2] Ohio Supercomp Ctr, Columbus, OH USA
[3] Tech Univ Dortmund DE, CERN, Dortmund, Germany
来源：
23RD INTERNATIONAL CONFERENCE ON COMPUTING IN HIGH ENERGY AND NUCLEAR PHYSICS (CHEP 2018) | 2019年 / 214卷
关键词：
D O I：
10.1051/epjconf/201921405006
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
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页数：7
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