A Design Space Exploration Methodology for Parameter Optimization in Multicore Processors

TL;DR

This paper introduces an efficient design space exploration methodology for optimizing parameters in multicore processors, achieving near-exhaustive solution quality with significantly reduced search effort across small and large design spaces.

Contribution

The paper presents a novel, efficient methodology for parameter optimization in multicore processors that closely approximates exhaustive search results with less computational effort.

Findings

Solution quality within 3.69% of exhaustive search

Explores only 2.74% - 3% of the design space

Including more parameters improves results

Abstract

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.