Pre-architectural performance estimation for ASIP design based on abstract processor models

Application Specific Instruction Set Processors (ASIPs) seek for an optimal performance/area/energy trade-off for a given algorithm. In all current design methodologies an architectural model must be first manually created based on designers experience. These models are increasingly refined until the design constraints are met, through several time consuming algorithmic/architecture co-exploration iterations. This paper presents a novel performance estimation approach that shortens the design cycle of existing methodologies by providing an early assessment of the impact of customizations on the achievable performance. The approach does so by eliminating the need for a completely specified architecture, without limiting designer´s freedom and without simulating the application repeatedly. Overall, our approach reduces the number of necessary co-exploration iterations, thus increasing design productivity. We validate our approach via two different case studies: a butterfly-enabled ASIP for Fast Fourier Transform computation and a Connected Components Labeling ASIP for computer vision.