Insert & save: Energy optimization in ip core integration for FPGA-based real-time systems

Today, many industrial, automotive and autonomous systems like robots are deployed in high-temperature and battery-powered environments. Due to cooling and runtime, this limits the energy consumption and makes the design of such embedded real-time systems even more challenging. Though Field Programmable Gate Arrays (FPGAs) offer the required performance, their static and - load-dependent - dynamic energy consumptions continue to prevent a widespread adoption. The existing methods for dynamic power reduction (like clock gating) are either limited in savings or require disruptive changes to well-established FPGA design flows. Whilst the former is caused by optimizing on fabric level only, the latter is due to the lack of support for a more efficient (but not yet mature and standardized) high-level design entry in current tools. In this paper, we thus explore an optimization methodology based on an existing, but not-fully-utilized intermediate level of abstraction that emerges in the IP core integration phase of the design. To this end, we exploit the fact that the vast majority of FPGA-based real-time processing pipelines is not exclusively assembled using a single type of design entry - i.e., neither entirely hand-written nor high-level synthesis only. Instead, suitable IP cores (from a variety of sources) are integrated via standardized bus interfaces such as AXI, Avalon or Wishbone. To facilitate effort- and power-efficient clock gating on integration-level, we present two 'insert and save' IP cores that harness application information extracted from current AXI3 and AXI4-Stream interfaces. Based thereon, both cores precisely control the clock signals of every downstream processing stage for maximum energy savings. This approach not only nicely integrates with today's predominantly AXI-based designs but also results in clock gating structures that are particularly suitable for current FPGAs - as demonstrated by experimental evaluations on a Zynq-based Visual Servoing System with energy savings of 26%.