An efficient algorithm for isomorphism-aware custom instruction identification for extensible processors

Extensible processors have been widely used to achieve the conflicting demands for performance improvement, low power consumption, and flexibility. As extensible processors have become more popular, several algorithms have been proposed for automatically identifying instruction-set extensions in order to reduce the effort of manual design and verification. However, most of them focus on finding large and complex instructions that are used only once, rather than repeatedly used ones. Moreover, some other approaches that consider recurrence are limited to finding small instructions. This paper proposes a novel algorithm that considers the instruction reusability as well as I/O serialization. In order to overcome high complexity of the problem, we develop a canonical form construction algorithm for fast isomorphism detection on directed acyclic graphs and an incremental template generation algorithm that identifies the best custom instruction with a user-defined fitness function. Moreover, our algorithm serializes I/O operations so that the numbers of inputs and outputs of custom instructions are not limited by the microarchitecture. Experimental results show that our algorithm achieves significant improvement over previous approaches in terms of algorithm runtime as well as performance gain obtained by the custom instructions.