Quantifying the Benefits of Dynamic Partial Reconfiguration for Embedded Vision Applications

摘要

Dynamic partial reconfiguration (DPR) allows parts of an FPGA to be reprogrammed at runtime (i.e., repurposed). Though DPR has been supported by commercial devices and tools for more than a decade, it has been underutilized, perhaps, due to a shortage of demonstrated use-cases and quantified benefits over static FPGA mapping (without DPR). In this paper, we quantify the benefits of dynamic FPGA mapping (with DPR) over traditional static FPGA mapping for two vision applications deployed on systems with area/device cost, power or energy constraints (i.e., smart car and smart robot). In both applications, the FPGA needs to accelerate multiple tasks at 60 fps. However, all tasks are not required at the same time. In this work, instead of mapping all tasks statically on a large FPGA, the set of tasks needed at a given time is (1) repurposed on a smaller FPGA and (2) still meets the functional and performance requirements (i.e., 60 fps). In the two application examples, we show that dynamic mapping on smaller FPGAs reduces logic resource utilization by up to 3.2x, device cost by up to 10x, and power and energy consumption by up to 30% in comparison with static mapping on larger FPGAs. These benefits are crucial for applications deployed on systems where reducing area/device cost, power and energy is as important as meeting performance requirement.