Distributed execution of logic programs requires a match of granularity between a program and the distributed multi-processor it runs on to exploit its potential for performance fully. This paper presents methods to control the granularity of tasks on distributed heterogeneous processors effectively. It considers the characteristics of such platforms and relates the amount of local computation with the significant communication overheads by introducing the notion of a collection of parallel tasks. The experimental results indicate that the proposed controls can model all kinds of predicates (recursive, mutually recursive etc.) satisfactorily and improve the performance of various forms of parallelism (AND, OR, combinations