Loading...
Please wait, while we are loading the content...
Similar Documents
A Simple Generalization of Kahn's Principle to Indeterminate Dataflow Networks (1990)
| Content Provider | CiteSeerX |
|---|---|
| Author | Stark, Eugene W. |
| Description | Kahn's principle states that if each process in a dataflow network computes a continuous input/output function, then so does the entire network. Moreover, in that case the function computed by the network is the least fixed point of a continuous functional determined by the structure of the network and the functions computed by the individual processes. Previous attempts to generalize this principle in a straightforward way to "indeterminate" networks, in which processes need not compute functions, have been either too complex or have failed to give results consistent with operational semantics. In this paper, we give a simple, direct generalization of Kahn's fixed-point principle to a large class of indeterminate dataflow networks, and we prove that results obtained by the generalized principle are in agreement with a natural operational semantics. 1 Introduction Dataflow networks are a parallel programming paradigm in which a collection of concurrently and asynchronously executing s... |
| File Format | |
| Language | English |
| Publisher | Springer-Verlag |
| Publisher Date | 1990-01-01 |
| Publisher Institution | Semantics for Concurrency, Leicester |
| Access Restriction | Open |
| Subject Keyword | Previous Attempt Parallel Programming Paradigm Fixed-point Principle Entire Network Natural Operational Semantics Large Class Principle State Dataflow Network Fixed Point Continuous Functional Simple Generalization Direct Generalization Indeterminate Network Indeterminate Dataflow Network Generalized Principle Operational Semantics Straightforward Way Continuous Input Output Function Introduction Dataflow Network Compute Function Individual Process |
| Content Type | Text |
| Resource Type | Article |
