Mongkol Ekpanyapong, Sung Kyu Lim
Performance-driven Global Placement via Adaptive Network Characterization
Delay minimization continues to be an important objective in the design of
high-performance computing system. In this paper, we present an effective
methodology to guide the delay optimization process of the mincut-based global
placement via adaptive sequential network characterization. The contribution of
this work is the development of a fully automated approach to determine
critical parameters related to performance-driven multi-level
partitioning-based global placement with retiming. We validate our approach by
incorporating this adaptive method into a state-of-the-art global placer GEO.
Our A-GEO, the adaptive version of GEO, achieves 67% maximum and 22% average
delay improvement over GEO.