The study of a prototype of the second-level triggering system for ope
ration at LHC conditions is addressed by means of a parallel machine i
mplementation. The 16 node transputer based machine uses a fast digita
l signal processor acting as a coprocessor for optimizing signal proce
ssing applications. A C-language development environment is used for r
unning: all applications at ultimate speed. The implementation is base
d on information supplied by four detectors and includes two phases of
system operation: feature extraction and global decision. Feature ext
raction for calorimeters and global decision processing are performed
by means of neural networks. Preprocessing and neural network paramete
rs rest in memory and the activation function is implemented using a l
ook up table. Simulated data for the second-level trigger operation ar
e used for performance evaluation.