  The architecture of a coarse-grained reconfigurable array (CGRA) processing
element (PE) has a significant effect on the performance and energy efficiency
of an application running on the CGRA. This paper presents an automated
approach for generating specialized PE architectures for an application or an
application domain. Frequent subgraphs mined from a set of applications are
merged to form a PE architecture specialized to that application domain. For
the image processing and machine learning domains, we generate specialized PEs
that are up to 10.5x more energy efficient and consume 9.1x less area than a
baseline PE.
