The Jagiellonian-PET (J-PET) collaboration is developing a prototype TOF-PET detector based on long polymer scintillators. This novel approach exploits the excellent time properties of the plastic scintillators, which permit very precise time measurements. The very fast, FPGA-based front-end electronics and the data acquisition system, as well as, low- and high-level reconstruction algorithms were specially developed to be used with the J-PET scanner. The TOF-PET data processing and reconstruction are time and resource demanding operations, especially in case of a large acceptance detector, which works in triggerless data acquisition mode. In this article, we discuss the parallel computing methods applied to optimize the data processing for the J-PET detector. We begin with general concepts of parallel computing and then we discuss several applications of those techniques in the J-PET data processing.
Cite
@article{arxiv.1508.02751,
title = {Processing optimization with parallel computing for the J-PET tomography scanner},
author = {W. Krzemień and M. Bała and T. Bednarski and P. Białas and E. Czerwiński and A. Gajos and M. Gorgol and B. Jasińska and D. Kamińska and Ł. Kapłon and G. Korcyl and P. Kowalski and T. Kozik and E. Kubicz and Sz. Niedźwiecki and M. Pałka and L. Raczyński and Z. Rudy and O. Rundel and N. G. Sharma and M. Silarski and A. Słomski and K. Stola and A. Strzelecki and D. Trybek and Anna Wieczorek and W. Wiślicki and M. Zieliński and B. K. Zgardzińska and P. Moskal},
journal= {arXiv preprint arXiv:1508.02751},
year = {2016}
}