Search space splitting and portfolio are the two main approaches used in parallel SAT solving. Each of them has its strengths but also, its weaknesses. Decomposition in search space splitting can help improve speedup on satisfiable instances while competition in portfolio increases robustness. Many parallel hybrid approaches have been proposed in the literature but most of them still cope with load balancing issues that are the cause of a non-negligible overhead. In this paper, we describe a new parallel hybridization scheme based on both search space splitting and portfolio that does not require the use of load balancing mechanisms (such as dynamic work stealing).