The need for ultra-low-power embedded processors that can function well under severe energy limitations is rising due to the Internet of Things’ (IoT) edge computing systems’ quick development. Due to constant switching activity during idle computing intervals, conventional microcontroller designs frequently incur high dynamic power dissipation, which lowers overall energy efficiency and operational lifespan. This paper uses a clock-gated openMSP430 processor architecture to propose an application-specific power optimization solution for Internet of Things edge nodes. The suggested method suppresses redundant switching transitions during idle execution periods by integrating fine-grained clock gating methods into certain sequential portions of the processor data path and control logic. In order to assess power, timing, and area characteristics, the architecture is generated using power-aware synthesis techniques and implemented at Register Transfer Level (RTL) using Verilog HDL. The optimization approach concentrates on reducing dynamic power consumption without compromising temporal stability, instruction execution precision, or processor functionality. The results of experimental synthesis show a significant decrease in switching power and total energy consumption while preserving architectural dependability appropriate for embedded Internet of Things applications. For battery-operated edge devices, wireless sensor nodes, and portable low-power embedded systems needing longer operating lifetimes and increased energy efficiency, the suggested architecture is ideal.

The openMSP430 processor architecture’s RTL-level low-power optimization was effectively accomplished through the use of clock gating, operand isolation, conditional register updates, and switching activity reduction approaches. The clock network, ALU, register file, memory interface, and decoder logic were found to be the primary sources of dynamic power consumption in a thorough baseline RTL study. While maintaining functional correctness, time stability, and synthesizability, the suggested optimization approach successfully decreased needless switching activity across combinational and sequential logic. Following optimization, proper processor functioning was verified using functional verification and synthesis analysis. With just 3.2% area reduction following synthesis, the improved architecture reduced dynamic power usage by about 53% as compared to the baseline design. The collected findings show that optimizing embedded processor designs for FPGA and ASIC implementations at the RTL level is an efficient and technology-independent way to increase energy efficiency.

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