Abstract
While traditional cluster computers are more constrained by power and cooling costs for solving extreme-scale (or exascale) problems, the continuing progress and integration levels in silicon technologies make possible complete end-user systems on a single chip. This massive level of integration makes modern multicore chips all pervasive in domains ranging from climate forecasting and astronomical data analysis, to consumer electronics, smart phones, and biological applications. Consequently, designing multicore chips for exascale computing while using the embedded systems design principles looks like a promising alternative to traditional cluster-based solutions. This paper aims to present an overview of new, far-reaching design methodologies and run-time optimization techniques that can help breaking the energy efficiency wall in massively integrated single-chip computing platforms.