2011/06/30 by Mihai Niculescu, Niculescu, Mihai, I. S. Zgură +1
Computer Science · Physics and Astronomy · #Computational Physics (physics.comp-ph) #Distributed #Distributed and Parallel Computing Systems #FOS: Computer and information sciences #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex) #Parallel #Parallel Computing and Optimization Techniques #Particle physics theoretical and experimental studies #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.1106.6217
openalex publication_date 2011/06/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
One of the main challenges in Heavy Energy Physics is to make fast analysis of high amount of experimental and simulated data. At LHC-CERN one p-p event is approximate 1 Mb in size. The time taken to analyze the data and obtain fast results depends on high computational power. The main advantage of using GPU(Graphic Processor Unit) programming over traditional CPU one is that graphical cards bring a lot of computing power at a very low price. Today a huge number of application(scientific, financial etc) began to be ported or developed for GPU, including Monte Carlo tools or data analysis tools for High Energy Physics. In this paper, we'll present current status and trends in HEP using GPU.