Evaluating parallel architectures for two real-time applications with 100 kHz repetition rate (hadron collider data)

In the context of research and development activities for future hadron colliders, competitive implementations of real-time algorithms for feature extraction have been made on various forms of commercial pipelined and parallel architectures. The algorithms used for benchmarking serve for decision making and are of relative complexity; they are required to run with a repetition rate of 100 kHz on data sets of kilobyte size. Results are reported and discussed in detail. Among the commercially available architectures, pipelined image processing systems can compete with custom-designed architectures. General-purpose processors with systolic mesh connectivity can also be used. Massively parallel systems of the SIMD type (many processors executing the same program on different data) are less suitable in the presently marketed form. >