SLG is a table-oriented resolution method that extends SLD evaluation in two ways. It
computes the well-founded model for logic programs with negation with polynomial data complexity,
and it terminates for programs with the bounded-term-size property. Furthermore SLG has an efficient
sequential implementation for modularly stratified programs in the SLG-WAM of XSB. This
paper addresses general issues involved in parallelizing tabled evaluations by introducing a model of
shared-memory parallelism which we call table parallelism and by comparing it to traditional models
of parallelizing SLD. A basic architecture for supporting table parallelism in the framework of the
SLG-WAM is also presented, along with an algorithm for detecting termination of subcomputations.