Development of the parallel inference machine RAP/LOP-WAM and its optimized parallel compiler

A brief overview is presented of the parallel abstract machine developed for the RAP/LOP parallel execution model. A description is also given of its optimized parallel compiler. The main features of the machine are: (i) the OR-forest description is used to describe the search space of a given problem, not only describing OR- and AND- parallelism explicitly, but also avoiding a class of redundant computations; (ii) coarse-grain parallelism is supported by the granularity-based scheduling policy; (iii) procedure-level and clause-level analysis at compile-time and dynamic simple run-time checks are used to identify independent goals of the body of a clause; and (iv) several optimization and implementation techniques such as improved indexing mechanism and code space reduction are used to increase the machine´s efficiency significantly