Data driven processor 'Vertex Trigger' for B experiments

Data Driven Processors (DDP's) are specialized computation engines configured to solve specific numerical problems, such as vertex reconstruction. The architecture of the DDP which is the subject of this talk was designed and implemented by W. Sippach and B.C. Knapp at Nevis Lab. in the early 1980's. This particular implementation allows multiple parallel streams of data to provide input to a heterogenous collection of simple operators whose interconnection form an algorithm. The local data flow control allows this device to execute algorithms extremely quickly provided that care is taken in the layout of the algorithm. I/O rates of several hundred megabytes/second are routinely achieved thus making DDP's attractive candidates for complex online calculations. The original question was open-quote can a DDP reconstruct tracks in a Silicon Vertex Detector, find events with a separated vertex and do it fast enough to be used as an online trigger?close-quote Restating this inquiry as three questions and describing the answers to the questions will be the subject of this talk. The three specific questions are: (1) Can an algorithm be found which reconstructs tracks in a planar geometry and no magnetic field; (2) Can separated vertices be recognized in some way; (3) Can the algorithm be implemented in the Nevis-UMass and DDP and execute in 10-20 μs?