Kahn process networks
distributed model of computation
A Kahn process network (KPN, or process network) is a distributed model of computation in which a group of deterministic sequential processes communicate through unbounded first in, first out channels. The model requires that reading from a channel is blocking while writing is non-blocking. Due to these key restrictions, the resulting process network exhibits deterministic behavior that does not depend on the timing of computation nor on communication delays.
Kahn process networks were originally developed for modeling parallel programs, but have proven convenient for modeling embedded systems, high-performance computing systems, signal processing systems, stream processing systems, dataflow programming languages, and other computational tasks. KPNs were introduced by Gilles Kahn in 1974.
Execution model
KPN is a common model for describing signal processing systems where infinite streams of data are incrementally transformed by processes executing in sequence or parallel. Despite parallel processes, multitasking or parallelism are not required for executing this model.
In a KPN, processes communicate via unbounded FIFO channels. Processes read and write atomic data elements, alternatively called tokens, from and to channels. Writing to a channel is non-blocking, i.e.
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