A data-driven model for parallel interpretation of logic programms [sic]

The main objective of this paper is to present a model of computation which permits logic programs to be executed on a highly-parallel computer architecture. It demonstrates how logic programs may be converted into collections of dataflow graphs in which resolution is viewed as a process of finding matches between certain graph templates and portions of the dataflow graphs. This graph fitting process is carried out by tokens propogating asynchronously through the dataflow graph; thus computation is entirely data-driven, without the need for any centralized control. It is shown that at the implementation level the proposed model is very similar to a general dataflow system and hence a dataflow architecture could easily be extended to support the proposed model

Microgrid - The microthreaded many-core architecture

Traditional processors use the von Neumann execution model, some other processors in the past have used the dataflow execution model. A combination of von Neuman model and dataflow model is also tried in the past and the resultant model is referred as hybrid dataflow execution model. We describe a hybrid dataflow model known as the microthreading. It provides constructs for creation, synchronization and communication between threads in an intermediate language. The microthreading model is an abstract programming and machine model for many-core architecture. A particular instance of this model is named as the microthreaded architecture or the Microgrid. This architecture implements all the concurrency constructs of the microthreading model in the hardware with the management of these constructs in the hardware.Comment: 30 pages, 16 figure

Network algebra for synchronous dataflow

We develop an algebraic theory of synchronous dataflow networks. First, a basic algebraic theory of networks, called BNA (Basic Network Algebra), is introduced. This theory captures the basic algebraic properties of networks. For synchronous dataflow networks, it is subsequently extended with additional constants for the branching connections that occur between the cells of synchronous dataflow networks and axioms for these additional constants. We also give two models of the resulting theory, the one based on stream transformers and the other based on processes as considered in process algebra.Comment: 24 page

An operations semantics for pure dataflow

We prove the equivalence between an operational and an extensional semantics for pure dataflow. The term pure dataflow refers to dataflow nets in which the nodes are functional (i.e. the output history is a function of the input history only) and the arcs are unbounded fifo queues. Gilles Kahn gave a method for the representation of a pure dataflow net as a set of equations; one equation for each arc in the net. We present a complete proof that the operational behaviour of a pure dataflow net is exactly described by the least fixed point solution to its associated set of equations. Our model is completely general since our nodes have the universality property, in that, for any continuous history function there exists a node that will compute it. Moreover since our nets are not built from a set of sequential primitive nodes the model is not in the communicating sequential processes framework. On the contrary our nets have the abstraction property in that any net can be collapsed into a node. The above proof gives complementary ways of viewing pure dataflow nets, that is, as either sets of equations or as graphs. It moreover gives rise to an elegant equational dataflow language. Pure dataflow then takes on an important role since it is a correct implementation for such a functional programming language; nodes being implementation of continuous history functions; arcs and datons being implementations of histories; and nets being mechanisms for computing the solutions to sets of equations

A relational dataflow database

A model of a relational database system based on the principles of functional, data-driven computation is proposed. Relations (sets of data tuples) are represented as streams of values carried by independent tokens among operators of an unraveling dataflow network.Values may be “updated” by circulating the database through an update operator. To perform a query on the database, streams involved in that query are replicated and submitted as inputs to dataflow programs (graphs) obtained by translating relational algebra expressions.