Optimized thermal sensor allocation for field-programmable gate array temperature measurements based on self-heating test. (February 2017) - Li, Jingwei; Feng, Shiwei; Zhang, Yamin; Wang, Chao; He, Xin
Abstract: In this paper, an optimization method for ring oscillator (RO)-based thermal sensor allocation based on a fuzzy clustering algorithm is proposed. A sensor array is distributed uniformly on a field programmable gate array (FPGA) as an original layout. Using a trade-off between sensor numbers and measurement resolution, the thermal sensors are combined based on their mutual clustering levels, which are inversely proportional to the temperature difference. This method is suitable for various applications on FPGAs. A self-heating test module that uses the FPGA resources to generate hotspots and large temperature gradients for measurement validation is presented. The experimental results show that when the temperature gradients range from 0 °C up to 40 °C on an Altera Cyclone IV FPGA, we can reduce sensor resource requirements by 37.5% while maintaining a measurement resolution of 1 °C. Highlights: The thermal sensors allocation is optimized based on Fuzzy Clustering Algorithm. The temperature measured by sensors is analyzed in temporal and spatial domains. A self-heating test module using the FPGA resources is presented for validation. The optimization method is suitable for various applications on FPGA.