RISC32-LP: Low-power FPGA-based IoT Sensor Nodes with Energy Reduction Program Analyzer

Abstract

Field-Programmable Gate Array (FPGA)-based sensor nodes are popular for their flexible design approach and field reconfigurability. RISC32 is one of the recent Internet of Things (IoT) processors proposed for the development of FPGA-based sensor nodes, and it includes the ability to reconfigure the micro-architecture on the fly in order to reduce dynamic energy consumption. However, such a method does not minimize static energy consumption, which is important in FPGA-based systems. In this work, clock gating and dynamic voltage and frequency scaling are applied to further reduce the energy consumption in RISC32. In the research presented here, we implemented a new software called the Energy Reduction Program Analyser to estimate the parameters that configure a sensor node to achieve minimum energy consumption, targeting the typical IoT application scenario. Experimental results show that the low-power techniques applied in this work (RISC32-LP) can reduce energy consumption by 47%, compared to the standard RISC32 processor. IEEE