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 of resource allocation in multicores do not consider these complex topologies, which results in poor scaling, or worse, non-functioning algorithms. In this paper we present mpsym, a C++ library designed to alleviate this problem in an algorithm-agnostic fashion. Using methods from computational group theory, we present domain-specific algorithms to improve design-space exploration in hierarchical architecture topologies. We evaluate mpsym on multiple designspace exploration algorithms from literature. Without modifying the algorithm, our methods improve the execution time by a factor up to 8:6× on the E3S 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× better on average, while requiring less time to explore.