With growing numbers of cores, the memory subsystem of manycore architectures increases in complexity. Many modern multicores are designed in a hierarchical fashion, with multiple clusters of processing elements. However, most algorithms for design-space exploration (DSE) of resource allocation in multicores do not consider these complex topologies, which results in poor scaling, or worse, nonfunctioning algorithms. In this article, we presentmpsym, a C++ library designed to alleviate this problem in an algorithm-agnostic fashion. Using methods from the computational group theory, we present domain-specific algorithms to improve DSE in hierarchical architecture topologies. We evaluatempsymon multiple DSE algorithms from the literature. Without modifying the algorithm, our methods improve the execution time by a factor up to$8.6 \times $on the embedded system synthesis benchmark suite benchmark suite for complex, clustered architecture topologies. Similarly, by pruning the design space, our methods consistently improve the result of the exploration. In particular, the results from a simulated annealing heuristic on the Kalray MPPA3 Coolidge topology are over$30 \times $better on average, while requiring less time to explore.