Microarchitecture parameters tuning is critical in the microprocessor design cycle. It is a non-trivial design space exploration (DSE) problem due to the large solution space, cycle-accurate simulators’ modeling inaccuracy, and high simulation runtime for performance evaluations. Previous methods require massive expert efforts to construct interpretable equations or high computing resource demands to train black-box prediction models. This paper follows the black-box methods due to better solution qualities than analytical methods in general. We summarize two learned lessons and propose BOOM-Explorer accordingly. First, embedding microarchitecture domain knowledge in the DSE improves the solution quality. Second, BOOM-Explorer makes the microarchitecture DSE for register-transfer-level designs within the limited time budget feasible. We enhance BOOM-Explorer with the diversity-guidance, further improving the algorithm performance. Experimental results with RISC-V Berkeley-Out-of-Order Machine under 7-nm technology show that our proposed methodology achieves an average of
\(18.75\% \)
higher Pareto hypervolume,
\(35.47\% \)
less average distance to reference set, and
\(65.38\% \)
less overall running time compared to previous approaches.