
arXiv: 1112.0427
Our general motivation is to answer the question: "What is a model of concurrent computation?". As a preliminary exercise, we study dataflow networks. We develop a very general notion of model for asynchronous networks. The "Kahn Principle", which states that a network built from functional nodes is the least fixpoint of a system of equations associated with the network, has become a benchmark for the formal study of dataflow networks. We formulate a generalized version of the Kahn Principle, which applies to a large class of non-deterministic systems, in the setting of abstract asynchronous networks; and prove that the Kahn Principle holds under certain natural assumptions on the model. We also show that a class of models, which represent networks that compute over arbitrary event structures, generalizing dataflow networks which compute over streams, satisfy these assumptions.
25 pages. Published in the Proceedings of the Symposium on Mathematical Foundations of Programming Language Semantics, Springer Lecture Notes in Computer Science vol. 442, pp. 1--21
FOS: Computer and information sciences, Computer Science - Logic in Computer Science, Quantum Physics, FOS: Mathematics, FOS: Physical sciences, Mathematics - Category Theory, Category Theory (math.CT), Quantum Physics (quant-ph), Logic in Computer Science (cs.LO)
FOS: Computer and information sciences, Computer Science - Logic in Computer Science, Quantum Physics, FOS: Mathematics, FOS: Physical sciences, Mathematics - Category Theory, Category Theory (math.CT), Quantum Physics (quant-ph), Logic in Computer Science (cs.LO)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 10 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
