A Scalable Systolic Accelerator for Estimation of the Spectral Correlation Density Function and Its FPGA Implementation

Autor: Xiangwei Li, Douglas L. Maskell, Carol Jingyi Li, Philip H. W. Leong, David Boland
Rok vydání: 2022
Předmět:
Zdroj: ACM Transactions on Reconfigurable Technology and Systems. 16:1-24
ISSN: 1936-7414
1936-7406
DOI: 10.1145/3546181
Popis: The spectral correlation density (SCD) function is the time-averaged correlation of two spectral components used for analyzing periodic signals with time-varying spectral content. Although the analysis is extremely powerful, it has not been widely adopted in real-time applications due to its high computational complexity. In this article, we present an efficient FPGA implementation of the FFT accumulation method (FAM) for estimating the SCD function and its alpha profile. The implementation uses a linear systolic array with a bi-directional datapath consisting of DSP-based processing elements (PEs) with a dedicated instruction schedule, achieving a PE utilization of 88.2%. The 128-PE implementation achieves a clock frequency in excess of 530 MHz and consumes 151K LUTs, 151K FFs, 264 BRAMs, 4 URAMs, and 1,054 DSPs, which is less than 36% of the logic fabric on a Zynq UltraScale+ XCZU28DR-2FFVG1517E RFSoC device. It has a modest 12.5W power consumption and an energy efficiency of 4,832 MOPS/W, which is 20.6× better than the published state-of-the-art GPU implementation. In terms of throughput, it achieves 15,340 windows/s (15,340 windows/s × 2,048 samples/window = 31.4 MS/s), which is a 4.65× improvement compared to the above-mentioned GPU implementation and 807× compared to an existing hybrid FPGA-GPU implementation.
Databáze: OpenAIRE