Indirect connection aware attraction for FPGA clustering (abstract only)

Abstract

Indirect connection aware attraction clustering algorithm is proposed for clustered field programmable gate array architecture model to achieve simultaneously optimization of several performance metrics. A new cost function considers the attraction of the subsequent basic logic elements (BLEs) to the selected cluster, the number of the used pins already in the cluster, as well as critical path delay. The attractions of which BLEs are directly and indirectly connected to the selected cluster are taken into account. As a result, more external nets are absorbed into clusters, less number of pins per cluster and fewer clusters are required. Hence, smaller channel width is required for routing and speed of the design is improved. Performance comparisons are carried out in details with respect to state-of-the-art clustering techniques interconnect resource aware clustering (iRAC) and many-objective clustering (MO-Pack). Results show that the proposed algorithm outperforms these two clustering approaches with achievements of 38.8% and 42.2% respectively in terms of channel widths and 40.1% and 44.8% respectively in terms of number of external nets but with no critical path and area overhead.