A Grammar Induction Method for Clustering of Operations in Complex FPGA Designs

In large-scale datapaths, complex interconnection requirements limit resource utilization and often dominate critical path delay. A variety of scheduling and binding algorithms have been proposed to reduce routing requirements by clustering frequently-used set of operations to avoid longer, inter-operational interconnects. In this paper we introduce a grammar induction approach for datapath synthesis. The proposed approach deals with the problem of routing using information at a higher level of abstraction, even before resource scheduling and binding. It is applied on a given data flow graph (DFG) and builds a compact form of DFG by identifying and exploiting repetitive operations patterns with one or more outputs. Fully placed and routed circuits were successfully generated for complex designs that failed to be placed and routed by the standard manufacturer tool-chain without applying our method. Moreover, placement and routing time was accelerated by 16% on average. Our grammar-based approach achieved 12% reduction in area on average, mostly as a result of reducing multiplexer sizes and the number of flip-flops, without noticeable adverse effect on clock frequency. Our comparison with a state of the art algorithm described in [8] shows that our approach outperforms it in both reduction in FPGA area and time to place and route the design.