A semantics and implementation of a causal logic programming language

The increasingly widespread availability of multicore and manycore computers demands new programming languages that make parallel programming dramatically easier and less error prone. This paper describes a semantics for a new class of declarative programming languages that support massive amounts of implicit parallelism. The key idea is that rather than writing low-level imperative programs that define a sequence of state updates, we write a set of high-level rules that are all executed in parallel, acting on a global database of facts. A simple declarative semantics is possible, because rules can add new tuples to the database but cannot modify existing tuples, and because abstract timestamps are used to record causality relationships between tuples. It turns out that negation and garbage collection are the two crucial features that enable us to recover the efficient mutable updates that are possible in imperative languages. This paper develops the semantics of negation, using a direct least-fix-point (LFP) construction, and shows that this semantics agrees with the well-founded, perfect and stable semantics. The paper develops an efficient bottom-up execution algorithm based directly on the LFP construction. It also gives a declarative formulation of the problem of garbage collection and describes an algorithm for doing garbage collection. Finally it is claimed that the programming language described can form the basis of a practical general purpose programming language.

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