Partial wave analysis using graphics processing units

Abstract

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. The user writes 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 speed-up of the partial wave fit by more than two orders of magnitude compared to legacy FORTRAN code.