Modeling and generation tools for large-scale, real-time embedded systems

High energy physics experiments require very large, real-time computation. Furthermore, the computers that implement on-line processing must be very reliable, due to the large cost of operating the facilities and the potential for loss of irreplaceable data. Standard, redundant fault tolerance approaches are not appropriate due to system costs (Fault handling is limited to 10% overhead). Adaptive, fault-mitigation approaches must be used instead. In this paper, we describe a set of tools for specifying and implementing user-defined adaptation algorithms, using model-based representation for specification and software synthesis for implementation.