Hardware preprocessing for the H1-Level 2 neural network trigger upgrade

Author

Prévotet, J.C. ; Denby, B. ; Fent, J. ; Fröchtenicht, W. ; Garda, P. ; Granado, B. ; Haberer, W. ; Grindhammer, G. ; Janauschek, L. ; Kiesling, C. ; Kobler, T. ; Koblitz, B. ; Nellen, G. ; Schmidt, S. ; Tzamariudaki, E. ; Udluft, S.

Author_Institution

Lab. des Instruments et Systemes d´´Ile de France, Paris, France

Volume

49

Issue

2

fYear

2002

fDate

4/1/2002 12:00:00 AM

Firstpage

362

Lastpage

368

Abstract

The H1-Level 2 neural network trigger has been running successfully at Deutsches Elektronen Synchrotron (DESY) for four years. In order to provide increased selectivity at the higher luminosity planned for the HERA upgrade, an improved "intelligent" preprocessing has been devised. This system extracts complementary physics information from the Level 1 trigger stream and furnishes it to the L2 neural network in order to improve its decision. A new preprocessing board (the Data Distribution Board Version 2-DDB2) is currently being designed at the Max Planck Institute for Physics, Munich, Germany, in order to implement the necessary algorithms in fast field programmable gate arrays (FPGA), taking advantage of parallelism and pipelined structures in order to meet the timing requirement of 8 μs. We present the different algorithmic steps and report on the current status of the DDB2 hardware upgrade

Keywords

data acquisition; electron accelerators; field programmable gate arrays; high energy physics instrumentation computing; neural nets; nuclear electronics; readout electronics; storage rings; timing circuits; trigger circuits; 8 mus; DDB2; DESY; Deutsches Elektronen Synchrotron; FPGA; H1-level 2 neural network trigger upgrade; data distribution board version 2; fast field programmable gate arrays; hardware preprocessing; higher luminosity; intelligent preprocessing; pipelined structures; timing; trigger circuits; Algorithm design and analysis; Data mining; Detectors; Field programmable gate arrays; Neural network hardware; Neural networks; Physics; Synchrotrons; Timing; Trigger circuits;

fLanguage

English

Journal_Title

Nuclear Science, IEEE Transactions on

Publisher

ieee

ISSN

0018-9499

Type

jour

DOI

10.1109/TNS.2002.1003738

Filename

1003738