  The need for application-specific design of multicore/manycore processing
platforms is evident with computing systems finding use in diverse application
domains. In order to tailor multicore/manycore processors for application
specific requirements, a multitude of processor design parameters have to be
tuned accordingly which involves rigorous and extensive design space
exploration over large search spaces. In this paper, we propose an efficient
methodology for design space exploration. We evaluate our methodology over two
search spaces - small and large, using a cycle-accurate simulator (ESESC) and a
standard set of PARSEC and SPLASH-2 benchmarks. For the smaller design space,
we compare results obtained from our design space exploration methodology with
results obtained from fully exhaustive search. The results show that solution
quality obtained from our methodology are within 1.35% - 3.69% of the results
obtained from fully exhaustive search while only exploring 2.74% - 3% of the
design space. For larger design space, we compare solution quality of different
results obtained by varying the number of tunable processor design parameters
included in the exhaustive search phase of our methodology. The results show
that including more number of tunable parameters in the exhaustive search phase
of our methodology greatly improves solution quality.
