The Stony Brook SYNCHEM program, a well-established intelligent problem-solving system for synthesis route discovery, recently has been upgraded to execute in a network of multiprocessor workstations under both Linda tuple space and PVM message passing protocols. We describe the implementation and report experimental results. In addition, we discuss the effect of parallelizing SYNCHEM's search algorithm on the global best-first heuristic exploration of the synthesis problem space. Though reasonably wide-ranging and inclusive, sequential exploration exhibits a pronounced depth-first flavor. Parallelization introduces a countervailing breadth-first tendency that alters the region of the problem space explored by the search engine with mixed consequences, the positive clearly outweighing the negative.