A method for fast hardware specialization at run-time

Dynamic hardware generation is a powerful technique that can substantially reduce both the required hardware resources and the time needed to perform a calculation, reflected in an improved functional density. This performance improvement is a result of additional run-time optimizations enabled by the knowledge of values at certain inputs at run-time. However, due to the large overhead conventional hardware generation tools incur, the usability of dynamic hardware generation is limited. We present a dual approach that combines compile-time generation of generic hardware and run-time specialization. This drastically decreases the dynamic generation overhead. Our approach is used for dynamic generation of FIR filters and compared to a static and a conventional dynamic implementation. The experiments clearly show that the dual approach improves the usability of dynamic hardware generation.