Granularity aspects for the design of multi-level reconfigurable architectures

Dynamically reconfigurable hardware has already been deployed for accelerating computationally demanding applications. Some of these hardware architectures allow run time reconfiguration but this leads usually to a large reconfiguration overhead. The advantage of run time reconfiguration is that it allows new algorithmic solutions for many applications. To study the potential of frequent run time reconfiguration it is interesting to investigate its costs and benefits from an abstract point of view and to develop new architectural concepts. Multilevel reconfigurable architectures are one such concept that introduce several levels of reconfiguration. This paper deals with new types of multi-level reconfigurable architectures. The corresponding problem of finding the best granularity for different reconfiguration levels is formulated and investigated. Although this problem is shown to be NP-complete, an interesting restricted subcase is solved optimally in polynomial time. For the general case, a good heuristic is proposed that is based on solutions for the restricted case. Results on three example applications show that the reconfiguration cost can be reduced with the new architectures. Based on a proposed measure of relative efficiency it is also shown that the new architectures are more efficient so that they obtain a larger reconfiguration cost reduction with less additional hardware