Author/Authors :
Belosloudtsev، نويسنده , , D. and Bertin، نويسنده , , P. and Bock، نويسنده , , R.K. and Boucard، نويسنده , , P. and Dِrsing، نويسنده , , V. and Kammel، نويسنده , , P. and Khabarov، نويسنده , , S. and Klefenz، نويسنده , , F. and Krischer، نويسنده , , W. and Kugel، نويسنده , , A. and Lundheim، نويسنده , , L. and Mنnner، نويسنده , , R. and Moll، نويسنده , , L. and Noffz، نويسنده , , K.H. and Reinsch، نويسنده , , A. and Ronein، نويسنده , , D. and Shand، نويسنده , , M. and Vuillemin، نويسنده , , J. and Zoz، نويسنده , , R.، نويسنده ,
Abstract :
The future Large Hadron Collider (LHC), to be built at CERN, presents among other technological challenges a formidable problem of real-time data analysis. At a primary event rate of 40 MHz, a multi-stage trigger system has to analyze data to decide which is the fraction of events that should be preserved on permanent storage for further analysis. We report on implementations of local algorithms for feature extraction as part of triggering, using the detectors of the proposed ATLAS experiment as a model. The algorithms were implemented for a decision frequency of 100 kHz, on different data-driven programmable devices based on structures of field-programmable gate arrays and memories. The implementations were demonstrated at full speed with emulated input, and were also integrated into a prototype detector running in a test beam at CERN, in June 1994.
