Abstract
Abstract The Jagiellonian Positron Emission Tomograph (J-PET) collaboration is developing a prototype time of flight (TOF)-positron emission tomograph (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 field programmable gate array (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 the case of a large acceptance detector that 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.
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