Speaker
Dr
Niklaus Berger
(Institute for High Energy Physics, Beijing)
Description
Partial wave analysis is an important tool for determining resonance properties in hadron spectroscopy. For large data samples however, the un-binned likelihood fits employed are computationally very expensive. At the Beijing Spectrometer (BES) III experiment, an increase in statistics compared to earlier experiments of up to two orders of magnitude is expected. In order to allow for a timely analysis of these datasets, additional computing power with short turnover times has to be made available.
It turns out that graphics processing units (GPUs) originally developed for 3D computer games have an architecture of massively parallel single instruction multiple data floating point units that is almost ideally suited for the algorithms employed in partial wave analysis. We have implemented a framework for tensor manipulation and partial wave fits called GPUPWA, harnessing the power of GPUs based on the Brook+ framework for general purpose computing on graphics processing units. GPUPWA simplifies the coding of amplitudes in the covariant tensor formalism and other tedious and error-prone tasks involved in partial wave analyses. The user can write a program in pure C++ whilst the GPUPWA classes handle computations on the GPU, memory transfers, caching and other technical details. In conjunction with a recent graphics processor, the framework provides a significant speedup of the partial wave fit compared to legacy FORTRAN code.
Summary
In order to speed up computationally very extensive partial wave analyses, we have created a framework that harnesses the power of modern graphics processors.
| Presentation type (oral | poster) | Oral |
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Primary author
Dr
Niklaus Berger
(Institute for High Energy Physics, Beijing)
Co-authors
Dr
Beijiang Liu
(Hong Kong Uiversity and Chinese University of Hong Kong)
Mr
Jike Wang
(Institute for High Energy Physics, Beijing)
