Classification of Massively Parallel Computer Architectures

Faced with slowing performance and energy benefits of technology scaling, VLSI/Computer architectures have turned from parallel to massively parallel machines for personal and embedded applications in the form of multi and many core architectures. Additionally, in the pursuit of finding the sweet spot between engineering and computational efficiency, massively parallel Coarse Grain Reconfigurable Architectures(CRGAs) have been researched. While hese articles have been surveyed, they have not been rigorously classified to enable objective differentiation and comparison for performance, area and flexibility. In this paper, we extend the well known Skillicorn taxonomy to create new classes, present a scoring system to rate these classes on flexibility, and present equations for early estimation of area and configuration overheads. Furthermore, we use this extended classification scheme to classify and compare 25 different massively parallel architectures that covers most of the reported CGRAs and other well known multi and many core architectures.