Delivering superior expressive power over RDBMS, while maintaining competitive per-formance, has represented the main goal and technical challenge for deductive database research since its inception forty years ago. Significant progress toward this ambitious goal is being achieved by the DeALS system through the parallel bottom-up evaluation of logic programs, including recursive programs with monotonic aggregates, on a shared-memory multicore machine. In DeALS, a program is represented as an AND/OR tree, where the parallel evalu-ation instantiates multiple copies of the same AND/OR tree that access the tables in the database concurrently. Synchronization methods such as locks are used to ensure the correctness of the evaluation. We describe a technique which finds an efficient hash par-titioning strategy of the tables that minimizes the use of locks during the evaluation. Experimental results demonstrate the effectiveness of the proposed technique — DeALS achieves competitive performance on non-recursive programs compared with commercial RDBMSs and superior performance on recursive programs compared with other existing systems.