Kahn process network

Kahn process networks (KPNs, or process networks) is a distributed model of computation (MoC) where a group of deterministic sequential processes are communicating through unbounded FIFO channels. The resulting process network exhibits deterministic behavior that does not depend on the various computation or communication delays. The model was originally developed for modeling distributed systems but has proven its convenience for modeling signal processing systems. As such, KPNs have found many applications in modeling embedded systems, high-performance computing systems, and other computational tasks. KPNs were first introduced by Gilles Kahn.

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, or alternatively called tokens, from and to channels. Writing to a channel is non-blocking, i.e. it always succeeds and does not stall the process, while reading from a channel is blocking, i.e. a process that reads from an empty channel will stall and can only continue when the channel contains sufficient data items (tokens). Processes are not allowed to test an input channel for existence of tokens without consuming them. A FIFO cannot be consumed by multiple processes, nor can multiple processes produce to a single FIFO. Given a specific input (token) history for a process, the process must be deterministic so that it always produces the same outputs (tokens). Timing or execution order of processes must not affect the result and therefore testing input channels for tokens is forbidden.

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