GAP(GPU Application Project): real time applications for High Energy Physics and Medical Imaging.
by
Matteo Bauce(Sapienza Università di Roma, INFN Sezione di Roma)
→
Europe/Rome
Aula Conversi (Dipartimento di Fisica - Ed. G.Marconi)
Aula Conversi
Dipartimento di Fisica - Ed. G.Marconi
Description
We present results of investigation on the possible applications of Graphic Processing Units in high-energy physics and medical diagnostic, carried out within the context of the GAP project. The aim of the GAP project is the deployment of Graphic Processing Units (GPU) in real-time applications, ranging from online event selection (trigger) in high-energy physics experiments to medical imaging reconstruction. The final goal of the project is to demonstrate that GPUs can have a positive impact in sectors different for rate, bandwidth, and computational intensity. As a study case we consider the trigger system of particle physics experiment such as NA62 and Atlas, two different combination of event complexity and processing latency requirements. A fast and selective trigger algorithm represents an important ingredient for the upcoming LHC upgrades and future experiments.
In a similar way, GPU can be a really powerful tool to increase the performances of medical imaging techniques, such as NMR, PET and CT. High-resolution image reconstruction techniques are based on computationally intense algorithms, that can be easily parallelized. The implementation of these on GPUs can significantly reduce the processing time, making them suitable for the use in realtime diagnostic.
