Study of the retina algorithm on FPGA for fast tracking

作     者：Zi-Xuan Song Wen-Di Deng Gilles De Lentdecker Guang-Ming Huang Hua Pei Yi-Fan Yang Dong Wang Frederic Robert 

作者机构：Central China Normal UniversityWuhan 430079China Universite libre de BruxellesAv.F.Roosevelt 501050 BrusselsBelgium 

出 版 物：《Nuclear Science and Techniques》 (核技术（英文）)

年 卷 期：2019年第30卷第8期

页      面：84-91页

核心收录：

学科分类：08[工学] 0827[工学-核科学与技术] 

基　　金：supported by the National Key Research and Development Program of China(No.2016YFE0100900) Fundamental Research Funds for the central universities(No.2018YBZZ082) National Science Funds of China(No.11505074) Belgian FRS-FNRS 

主　　题：Fast tracking Field programmable gate array Trigger 

摘      要：Real-time track reconstruction in high-energy physics experiments at colliders running at high luminosity is very challenging for trigger systems. To perform pattern recognition and track fitting, artificial retina or Hough transformation algorithms have been introduced to the field typically implemented on state-of-the-art field programmable gate array(FPGA) devices. In this paper, we report on two FPGA implementations of the retina algorithm: one using a mixed Floating-Point core and the other using Fixed-Point and Look-Up Table, and detailed measurements of the retina performance are investigated and compared. So far, the retina has mainly been used in a detector configuration comprising parallel planes, and the goal of our work is to study the hardware implementation of the retina algorithm and estimate the possibility of using such a method in a real experiment.